Determining crop residue type and class using satellite acquired data. M.S. Thesis Progress Report, Jun. 1990

NASA Technical Reports Server (NTRS)

Zhuang, Xin

1990-01-01

LANDSAT Thematic Mapper (TM) data for March 23, 1987 with accompanying ground truth data for the study area in Miami County, IN were used to determine crop residue type and class. Principle components and spectral ratioing transformations were applied to the LANDSAT TM data. One graphic information system (GIS) layer of land ownership was added to each original image as the eighth band of data in an attempt to improve classification. Maximum likelihood, minimum distance, and neural networks were used to classify the original, transformed, and GIS-enhanced remotely sensed data. Crop residues could be separated from one another and from bare soil and other biomass. Two types of crop residue and four classes were identified from each LANDSAT TM image. The maximum likelihood classifier performed the best classification for each original image without need of any transformation. The neural network classifier was able to improve the classification by incorporating a GIS-layer of land ownership as an eighth band of data. The maximum likelihood classifier was unable to consider this eighth band of data and thus, its results could not be improved by its consideration.

Neuro-classification of multi-type Landsat Thematic Mapper data

NASA Technical Reports Server (NTRS)

Zhuang, Xin; Engel, Bernard A.; Fernandez, R. N.; Johannsen, Chris J.

1991-01-01

Neural networks have been successful in image classification and have shown potential for classifying remotely sensed data. This paper presents classifications of multitype Landsat Thematic Mapper (TM) data using neural networks. The Landsat TM Image for March 23, 1987 with accompanying ground observation data for a study area In Miami County, Indiana, U.S.A. was utilized to assess recognition of crop residues. Principal components and spectral ratio transformations were performed on the TM data. In addition, a layer of the geographic information system (GIS) for the study site was incorporated to generate GIS-enhanced TM data. This paper discusses (1) the performance of neuro-classification on each type of data, (2) how neural networks recognized each type of data as a new image and (3) comparisons of the results for each type of data obtained using neural networks, maximum likelihood, and minimum distance classifiers.

The minimum distance approach to classification

NASA Technical Reports Server (NTRS)

Wacker, A. G.; Landgrebe, D. A.

1971-01-01

The work to advance the state-of-the-art of miminum distance classification is reportd. This is accomplished through a combination of theoretical and comprehensive experimental investigations based on multispectral scanner data. A survey of the literature for suitable distance measures was conducted and the results of this survey are presented. It is shown that minimum distance classification, using density estimators and Kullback-Leibler numbers as the distance measure, is equivalent to a form of maximum likelihood sample classification. It is also shown that for the parametric case, minimum distance classification is equivalent to nearest neighbor classification in the parameter space.

Construction of Protograph LDPC Codes with Linear Minimum Distance

NASA Technical Reports Server (NTRS)

Divsalar, Dariush; Dolinar, Sam; Jones, Christopher

2006-01-01

A construction method for protograph-based LDPC codes that simultaneously achieve low iterative decoding threshold and linear minimum distance is proposed. We start with a high-rate protograph LDPC code with variable node degrees of at least 3. Lower rate codes are obtained by splitting check nodes and connecting them by degree-2 nodes. This guarantees the linear minimum distance property for the lower-rate codes. Excluding checks connected to degree-1 nodes, we show that the number of degree-2 nodes should be at most one less than the number of checks for the protograph LDPC code to have linear minimum distance. Iterative decoding thresholds are obtained by using the reciprocal channel approximation. Thresholds are lowered by using either precoding or at least one very high-degree node in the base protograph. A family of high- to low-rate codes with minimum distance linearly increasing in block size and with capacity-approaching performance thresholds is presented. FPGA simulation results for a few example codes show that the proposed codes perform as predicted.

Status, distribution and morphometric/meristic characteristics of Cobitis elongata Heckel et Kner 1858 from Slovenia.

PubMed

Povz, Meta; Sumer, Suzana

2003-01-01

Cobitis elongata Heckel et Kner inhabits the rivers Sava, Kolpa, Krka, Gracnica and Hudinja (the Danube river basin). The species is common in its distribution area. In the Red List of endangered Pisces and Cyclostomata in Slovenia, it is classified as endangered. Status and distribution data of the species from previous reports and recent research were summarized. A total of 31 specimens from the river Kolpa were morphologically studied. Sixteen morphometric and four meristic characteristics were analysed using standard numerical taxonomic techniques. 99.8% of the total variation of standard length was explained by preanal distance, dorsal and ventral fin lengths as well as minimum body height.

Effect of Weight Transfer on a Vehicle's Stopping Distance.

ERIC Educational Resources Information Center

Whitmire, Daniel P.; Alleman, Timothy J.

1979-01-01

An analysis of the minimum stopping distance problem is presented taking into account the effect of weight transfer on nonskidding vehicles and front- or rear-wheels-skidding vehicles. Expressions for the minimum stopping distances are given in terms of vehicle geometry and the coefficients of friction. (Author/BB)

Subsurface event detection and classification using Wireless Signal Networks.

PubMed

Yoon, Suk-Un; Ghazanfari, Ehsan; Cheng, Liang; Pamukcu, Sibel; Suleiman, Muhannad T

2012-11-05

Subsurface environment sensing and monitoring applications such as detection of water intrusion or a landslide, which could significantly change the physical properties of the host soil, can be accomplished using a novel concept, Wireless Signal Networks (WSiNs). The wireless signal networks take advantage of the variations of radio signal strength on the distributed underground sensor nodes of WSiNs to monitor and characterize the sensed area. To characterize subsurface environments for event detection and classification, this paper provides a detailed list and experimental data of soil properties on how radio propagation is affected by soil properties in subsurface communication environments. Experiments demonstrated that calibrated wireless signal strength variations can be used as indicators to sense changes in the subsurface environment. The concept of WSiNs for the subsurface event detection is evaluated with applications such as detection of water intrusion, relative density change, and relative motion using actual underground sensor nodes. To classify geo-events using the measured signal strength as a main indicator of geo-events, we propose a window-based minimum distance classifier based on Bayesian decision theory. The window-based classifier for wireless signal networks has two steps: event detection and event classification. With the event detection, the window-based classifier classifies geo-events on the event occurring regions that are called a classification window. The proposed window-based classification method is evaluated with a water leakage experiment in which the data has been measured in laboratory experiments. In these experiments, the proposed detection and classification method based on wireless signal network can detect and classify subsurface events.

Subsurface Event Detection and Classification Using Wireless Signal Networks

PubMed Central

Yoon, Suk-Un; Ghazanfari, Ehsan; Cheng, Liang; Pamukcu, Sibel; Suleiman, Muhannad T.

2012-01-01

Subsurface environment sensing and monitoring applications such as detection of water intrusion or a landslide, which could significantly change the physical properties of the host soil, can be accomplished using a novel concept, Wireless Signal Networks (WSiNs). The wireless signal networks take advantage of the variations of radio signal strength on the distributed underground sensor nodes of WSiNs to monitor and characterize the sensed area. To characterize subsurface environments for event detection and classification, this paper provides a detailed list and experimental data of soil properties on how radio propagation is affected by soil properties in subsurface communication environments. Experiments demonstrated that calibrated wireless signal strength variations can be used as indicators to sense changes in the subsurface environment. The concept of WSiNs for the subsurface event detection is evaluated with applications such as detection of water intrusion, relative density change, and relative motion using actual underground sensor nodes. To classify geo-events using the measured signal strength as a main indicator of geo-events, we propose a window-based minimum distance classifier based on Bayesian decision theory. The window-based classifier for wireless signal networks has two steps: event detection and event classification. With the event detection, the window-based classifier classifies geo-events on the event occurring regions that are called a classification window. The proposed window-based classification method is evaluated with a water leakage experiment in which the data has been measured in laboratory experiments. In these experiments, the proposed detection and classification method based on wireless signal network can detect and classify subsurface events. PMID:23202191

The Minimum Binding Energy and Size of Doubly Muonic D3 Molecule

NASA Astrophysics Data System (ADS)

Eskandari, M. R.; Faghihi, F.; Mahdavi, M.

The minimum energy and size of doubly muonic D3 molecule, which two of the electrons are replaced by the much heavier muons, are calculated by the well-known variational method. The calculations show that the system possesses two minimum positions, one at typically muonic distance and the second at the atomic distance. It is shown that at the muonic distance, the effective charge, zeff is 2.9. We assumed a symmetric planar vibrational model between two minima and an oscillation potential energy is approximated in this region.

Prediction of fatigue-related driver performance from EEG data by deep Riemannian model.

PubMed

Hajinoroozi, Mehdi; Jianqiu Zhang; Yufei Huang

2017-07-01

Prediction of the drivers' drowsy and alert states is important for safety purposes. The prediction of drivers' drowsy and alert states from electroencephalography (EEG) using shallow and deep Riemannian methods is presented. For shallow Riemannian methods, the minimum distance to Riemannian mean (mdm) and Log-Euclidian metric are investigated, where it is shown that Log-Euclidian metric outperforms the mdm algorithm. In addition the SPDNet, a deep Riemannian model, that takes the EEG covariance matrix as the input is investigated. It is shown that SPDNet outperforms all tested shallow and deep classification methods. Performance of SPDNet is 6.02% and 2.86% higher than the best performance by the conventional Euclidian classifiers and shallow Riemannian models, respectively.

DETERMINING MINIMUM IGNITION ENERGIES AND QUENCHING DISTANCES OF DIFFICULT-TO-IGNITE COMPOUNDS

EPA Science Inventory

Minimum spark energies and corresponding flat-plate electrode quenching distances required to initiate propagation of a combustion wave have been experimentally measured for four flammable hydrofluorocarbon (HFC) refrigerants and propane using ASTM (American Society for Testing a...

Three-dimensional modeling and animation of two carpal bones: a technique.

PubMed

Green, Jason K; Werner, Frederick W; Wang, Haoyu; Weiner, Marsha M; Sacks, Jonathan M; Short, Walter H

2004-05-01

The objectives of this study were to (a). create 3D reconstructions of two carpal bones from single CT data sets and animate these bones with experimental in vitro motion data collected during dynamic loading of the wrist joint, (b). develop a technique to calculate the minimum interbone distance between the two carpal bones, and (c). validate the interbone distance calculation process. This method utilized commercial software to create the animations and an in-house program to interface with three-dimensional CAD software to calculate the minimum distance between the irregular geometries of the bones. This interbone minimum distance provides quantitative information regarding the motion of the bones studied and may help to understand and quantify the effects of ligamentous injury.

Determination of Minimum Training Sample Size for Microarray-Based Cancer Outcome Prediction–An Empirical Assessment

PubMed Central

Cheng, Ningtao; Wu, Leihong; Cheng, Yiyu

2013-01-01

The promise of microarray technology in providing prediction classifiers for cancer outcome estimation has been confirmed by a number of demonstrable successes. However, the reliability of prediction results relies heavily on the accuracy of statistical parameters involved in classifiers. It cannot be reliably estimated with only a small number of training samples. Therefore, it is of vital importance to determine the minimum number of training samples and to ensure the clinical value of microarrays in cancer outcome prediction. We evaluated the impact of training sample size on model performance extensively based on 3 large-scale cancer microarray datasets provided by the second phase of MicroArray Quality Control project (MAQC-II). An SSNR-based (scale of signal-to-noise ratio) protocol was proposed in this study for minimum training sample size determination. External validation results based on another 3 cancer datasets confirmed that the SSNR-based approach could not only determine the minimum number of training samples efficiently, but also provide a valuable strategy for estimating the underlying performance of classifiers in advance. Once translated into clinical routine applications, the SSNR-based protocol would provide great convenience in microarray-based cancer outcome prediction in improving classifier reliability. PMID:23861920

41 CFR 302-4.704 - Must we require a minimum driving distance per day?

Code of Federal Regulations, 2010 CFR

2010-07-01

... Federal Travel Regulation System RELOCATION ALLOWANCES PERMANENT CHANGE OF STATION (PCS) ALLOWANCES FOR... driving distance not less than an average of 300 miles per day. However, an exception to the daily minimum... reasons acceptable to you. ...

Distance estimation and collision prediction for on-line robotic motion planning

NASA Technical Reports Server (NTRS)

Kyriakopoulos, K. J.; Saridis, G. N.

1991-01-01

An efficient method for computing the minimum distance and predicting collisions between moving objects is presented. This problem has been incorporated in the framework of an in-line motion planning algorithm to satisfy collision avoidance between a robot and moving objects modeled as convex polyhedra. In the beginning the deterministic problem, where the information about the objects is assumed to be certain is examined. If instead of the Euclidean norm, L(sub 1) or L(sub infinity) norms are used to represent distance, the problem becomes a linear programming problem. The stochastic problem is formulated, where the uncertainty is induced by sensing and the unknown dynamics of the moving obstacles. Two problems are considered: (1) filtering of the minimum distance between the robot and the moving object, at the present time; and (2) prediction of the minimum distance in the future, in order to predict possible collisions with the moving obstacles and estimate the collision time.

Rate-compatible protograph LDPC code families with linear minimum distance

NASA Technical Reports Server (NTRS)

Divsalar, Dariush (Inventor); Dolinar, Jr., Samuel J (Inventor); Jones, Christopher R. (Inventor)

2012-01-01

Digital communication coding methods are shown, which generate certain types of low-density parity-check (LDPC) codes built from protographs. A first method creates protographs having the linear minimum distance property and comprising at least one variable node with degree less than 3. A second method creates families of protographs of different rates, all having the linear minimum distance property, and structurally identical for all rates except for a rate-dependent designation of certain variable nodes as transmitted or non-transmitted. A third method creates families of protographs of different rates, all having the linear minimum distance property, and structurally identical for all rates except for a rate-dependent designation of the status of certain variable nodes as non-transmitted or set to zero. LDPC codes built from the protographs created by these methods can simultaneously have low error floors and low iterative decoding thresholds, and families of such codes of different rates can be decoded efficiently using a common decoding architecture.

Ensemble Clustering Classification compete SVM and One-Class classifiers applied on plant microRNAs Data.

PubMed

Yousef, Malik; Khalifa, Waleed; AbedAllah, Loai

2016-12-22

The performance of many learning and data mining algorithms depends critically on suitable metrics to assess efficiency over the input space. Learning a suitable metric from examples may, therefore, be the key to successful application of these algorithms. We have demonstrated that the k-nearest neighbor (kNN) classification can be significantly improved by learning a distance metric from labeled examples. The clustering ensemble is used to define the distance between points in respect to how they co-cluster. This distance is then used within the framework of the kNN algorithm to define a classifier named ensemble clustering kNN classifier (EC-kNN). In many instances in our experiments we achieved highest accuracy while SVM failed to perform as well. In this study, we compare the performance of a two-class classifier using EC-kNN with different one-class and two-class classifiers. The comparison was applied to seven different plant microRNA species considering eight feature selection methods. In this study, the averaged results show that ECkNN outperforms all other methods employed here and previously published results for the same data. In conclusion, this study shows that the chosen classifier shows high performance when the distance metric is carefully chosen.

Ensemble Clustering Classification Applied to Competing SVM and One-Class Classifiers Exemplified by Plant MicroRNAs Data.

PubMed

Yousef, Malik; Khalifa, Waleed; AbdAllah, Loai

2016-12-01

The performance of many learning and data mining algorithms depends critically on suitable metrics to assess efficiency over the input space. Learning a suitable metric from examples may, therefore, be the key to successful application of these algorithms. We have demonstrated that the k-nearest neighbor (kNN) classification can be significantly improved by learning a distance metric from labeled examples. The clustering ensemble is used to define the distance between points in respect to how they co-cluster. This distance is then used within the framework of the kNN algorithm to define a classifier named ensemble clustering kNN classifier (EC-kNN). In many instances in our experiments we achieved highest accuracy while SVM failed to perform as well. In this study, we compare the performance of a two-class classifier using EC-kNN with different one-class and two-class classifiers. The comparison was applied to seven different plant microRNA species considering eight feature selection methods. In this study, the averaged results show that EC-kNN outperforms all other methods employed here and previously published results for the same data. In conclusion, this study shows that the chosen classifier shows high performance when the distance metric is carefully chosen.

Nearest Neighbor Algorithms for Pattern Classification

NASA Technical Reports Server (NTRS)

Barrios, J. O.

1972-01-01

A solution of the discrimination problem is considered by means of the minimum distance classifier, commonly referred to as the nearest neighbor (NN) rule. The NN rule is nonparametric, or distribution free, in the sense that it does not depend on any assumptions about the underlying statistics for its application. The k-NN rule is a procedure that assigns an observation vector z to a category F if most of the k nearby observations x sub i are elements of F. The condensed nearest neighbor (CNN) rule may be used to reduce the size of the training set required categorize The Bayes risk serves merely as a reference-the limit of excellence beyond which it is not possible to go. The NN rule is bounded below by the Bayes risk and above by twice the Bayes risk.

Maximum Likelihood and Minimum Distance Applied to Univariate Mixture Distributions.

ERIC Educational Resources Information Center

Wang, Yuh-Yin Wu; Schafer, William D.

This Monte-Carlo study compared modified Newton (NW), expectation-maximization algorithm (EM), and minimum Cramer-von Mises distance (MD), used to estimate parameters of univariate mixtures of two components. Data sets were fixed at size 160 and manipulated by mean separation, variance ratio, component proportion, and non-normality. Results…

47 CFR 73.807 - Minimum distance separation between stations.

Code of Federal Regulations, 2010 CFR

2010-10-01

... and the right-hand column lists (for informational purposes only) the minimum distance necessary for...) Within 320 km of the Mexican border, LP100 stations must meet the following separations with respect to any Mexican stations: Mexican station class Co-channel (km) First-adjacent channel (km) Second-third...

Dimensionality reduction based on distance preservation to local mean for symmetric positive definite matrices and its application in brain-computer interfaces

NASA Astrophysics Data System (ADS)

Davoudi, Alireza; Shiry Ghidary, Saeed; Sadatnejad, Khadijeh

2017-06-01

Objective. In this paper, we propose a nonlinear dimensionality reduction algorithm for the manifold of symmetric positive definite (SPD) matrices that considers the geometry of SPD matrices and provides a low-dimensional representation of the manifold with high class discrimination in a supervised or unsupervised manner. Approach. The proposed algorithm tries to preserve the local structure of the data by preserving distances to local means (DPLM) and also provides an implicit projection matrix. DPLM is linear in terms of the number of training samples. Main results. We performed several experiments on the multi-class dataset IIa from BCI competition IV and two other datasets from BCI competition III including datasets IIIa and IVa. The results show that our approach as dimensionality reduction technique—leads to superior results in comparison with other competitors in the related literature because of its robustness against outliers and the way it preserves the local geometry of the data. Significance. The experiments confirm that the combination of DPLM with filter geodesic minimum distance to mean as the classifier leads to superior performance compared with the state of the art on brain-computer interface competition IV dataset IIa. Also the statistical analysis shows that our dimensionality reduction method performs significantly better than its competitors.

Tomodensitometric survey of the distance between thoracic and abdominal vital organs and the wall according to BMI, abdominal diameter and gender: proposition of an indicative chart for the forensic activities.

PubMed

Venara, A; Gaudin, A; Lebigot, J; Airagnes, G; Hamel, J F; Jousset, N; Ridereau-Zins, C; Mauillon, D; Rouge-Maillart, C

2013-06-10

Forensic doctors are frequently asked by magistrates when dealing principally with knife wounds, about the depth of the blade which may have penetrated the victim's body. Without the use of imaging, it is often difficult to respond to this question, even in an approximate way. Knowledge of the various distances between organs and the skin wall would allow an assessment to be made of the minimum blade length required to obtain the injuries observed. The objective of this study is thus to determine average distances between the vital organs of the thorax and abdomen, and the skin wall, taking into account the person's body mass index (BMI). This is a prospective single-center study, carried out over a 2-month period at University Hospital in Angers. A sample of 200 people was studied. The inclusion criteria were as follows: all patients coming to the radiology department and the emergency department for an abdominal, thoracic or thoraco-abdominal scan with injection. The exclusion criteria included patients presenting a large lymphoma, a large abdominal or retroperitoneal tumor, a tumor in one of the organs targeted by our study and patients presenting ascites. The organs focused on were: the pericardium, pleura, aorta, liver, spleen, kidneys, abdominal aorta and femoral arteries. The shortest distance between the organ and the skin wall was noted. Median distances were calculated according to gender, abdominal diameter and BMI. We associated these values to propose an indicative chart which may be used by doctors in connection with their forensic activities. The problem of the depth of a wound is frequently exposed to the expert. Without a reliable tool, it is difficult to value and a personal interpretation is often done. Even if, in current days, tomodensitometry is frequently done in vivo or after death, measurement can be difficult because of the local conditions. We classified values according to the different factors of fat repartition (BMI, abdominal diameter, gender). These tables, collectively used, permit evaluation of the distance between wall and thoracic or abdominal vital organs. We suggest an indicative chart designed for forensic doctors in their professional life to help determine the minimum penetration length for a knife, which may wound a vital organ. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Vision-Based Detection and Distance Estimation of Micro Unmanned Aerial Vehicles

PubMed Central

Gökçe, Fatih; Üçoluk, Göktürk; Şahin, Erol; Kalkan, Sinan

2015-01-01

Detection and distance estimation of micro unmanned aerial vehicles (mUAVs) is crucial for (i) the detection of intruder mUAVs in protected environments; (ii) sense and avoid purposes on mUAVs or on other aerial vehicles and (iii) multi-mUAV control scenarios, such as environmental monitoring, surveillance and exploration. In this article, we evaluate vision algorithms as alternatives for detection and distance estimation of mUAVs, since other sensing modalities entail certain limitations on the environment or on the distance. For this purpose, we test Haar-like features, histogram of gradients (HOG) and local binary patterns (LBP) using cascades of boosted classifiers. Cascaded boosted classifiers allow fast processing by performing detection tests at multiple stages, where only candidates passing earlier simple stages are processed at the preceding more complex stages. We also integrate a distance estimation method with our system utilizing geometric cues with support vector regressors. We evaluated each method on indoor and outdoor videos that are collected in a systematic way and also on videos having motion blur. Our experiments show that, using boosted cascaded classifiers with LBP, near real-time detection and distance estimation of mUAVs are possible in about 60 ms indoors (1032×778 resolution) and 150 ms outdoors (1280×720 resolution) per frame, with a detection rate of 0.96 F-score. However, the cascaded classifiers using Haar-like features lead to better distance estimation since they can position the bounding boxes on mUAVs more accurately. On the other hand, our time analysis yields that the cascaded classifiers using HOG train and run faster than the other algorithms. PMID:26393599

Ensemble Weight Enumerators for Protograph LDPC Codes

NASA Technical Reports Server (NTRS)

Divsalar, Dariush

2006-01-01

Recently LDPC codes with projected graph, or protograph structures have been proposed. In this paper, finite length ensemble weight enumerators for LDPC codes with protograph structures are obtained. Asymptotic results are derived as the block size goes to infinity. In particular we are interested in obtaining ensemble average weight enumerators for protograph LDPC codes which have minimum distance that grows linearly with block size. As with irregular ensembles, linear minimum distance property is sensitive to the proportion of degree-2 variable nodes. In this paper the derived results on ensemble weight enumerators show that linear minimum distance condition on degree distribution of unstructured irregular LDPC codes is a sufficient but not a necessary condition for protograph LDPC codes.

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

PubMed

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

2016-01-01

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

Classification of biosensor time series using dynamic time warping: applications in screening cancer cells with characteristic biomarkers.

PubMed

Rai, Shesh N; Trainor, Patrick J; Khosravi, Farhad; Kloecker, Goetz; Panchapakesan, Balaji

2016-01-01

The development of biosensors that produce time series data will facilitate improvements in biomedical diagnostics and in personalized medicine. The time series produced by these devices often contains characteristic features arising from biochemical interactions between the sample and the sensor. To use such characteristic features for determining sample class, similarity-based classifiers can be utilized. However, the construction of such classifiers is complicated by the variability in the time domains of such series that renders the traditional distance metrics such as Euclidean distance ineffective in distinguishing between biological variance and time domain variance. The dynamic time warping (DTW) algorithm is a sequence alignment algorithm that can be used to align two or more series to facilitate quantifying similarity. In this article, we evaluated the performance of DTW distance-based similarity classifiers for classifying time series that mimics electrical signals produced by nanotube biosensors. Simulation studies demonstrated the positive performance of such classifiers in discriminating between time series containing characteristic features that are obscured by noise in the intensity and time domains. We then applied a DTW distance-based k -nearest neighbors classifier to distinguish the presence/absence of mesenchymal biomarker in cancer cells in buffy coats in a blinded test. Using a train-test approach, we find that the classifier had high sensitivity (90.9%) and specificity (81.8%) in differentiating between EpCAM-positive MCF7 cells spiked in buffy coats and those in plain buffy coats.

Impact of the reduced vertical separation minimum on the domestic United States

DOT National Transportation Integrated Search

2009-01-31

Aviation regulatory bodies have enacted the reduced vertical separation minimum standard over most of the globe. The reduced vertical separation minimum is a technique that reduces the minimum vertical separation distance between aircraft from 2000 t...

Detection of inter-patient left and right bundle branch block heartbeats in ECG using ensemble classifiers

PubMed Central

2014-01-01

Background Left bundle branch block (LBBB) and right bundle branch block (RBBB) not only mask electrocardiogram (ECG) changes that reflect diseases but also indicate important underlying pathology. The timely detection of LBBB and RBBB is critical in the treatment of cardiac diseases. Inter-patient heartbeat classification is based on independent training and testing sets to construct and evaluate a heartbeat classification system. Therefore, a heartbeat classification system with a high performance evaluation possesses a strong predictive capability for unknown data. The aim of this study was to propose a method for inter-patient classification of heartbeats to accurately detect LBBB and RBBB from the normal beat (NORM). Methods This study proposed a heartbeat classification method through a combination of three different types of classifiers: a minimum distance classifier constructed between NORM and LBBB; a weighted linear discriminant classifier between NORM and RBBB based on Bayesian decision making using posterior probabilities; and a linear support vector machine (SVM) between LBBB and RBBB. Each classifier was used with matching features to obtain better classification performance. The final types of the test heartbeats were determined using a majority voting strategy through the combination of class labels from the three classifiers. The optimal parameters for the classifiers were selected using cross-validation on the training set. The effects of different lead configurations on the classification results were assessed, and the performance of these three classifiers was compared for the detection of each pair of heartbeat types. Results The study results showed that a two-lead configuration exhibited better classification results compared with a single-lead configuration. The construction of a classifier with good performance between each pair of heartbeat types significantly improved the heartbeat classification performance. The results showed a sensitivity of 91.4% and a positive predictive value of 37.3% for LBBB and a sensitivity of 92.8% and a positive predictive value of 88.8% for RBBB. Conclusions A multi-classifier ensemble method was proposed based on inter-patient data and demonstrated a satisfactory classification performance. This approach has the potential for application in clinical practice to distinguish LBBB and RBBB from NORM of unknown patients. PMID:24903422

Detection of inter-patient left and right bundle branch block heartbeats in ECG using ensemble classifiers.

PubMed

Huang, Huifang; Liu, Jie; Zhu, Qiang; Wang, Ruiping; Hu, Guangshu

2014-06-05

Left bundle branch block (LBBB) and right bundle branch block (RBBB) not only mask electrocardiogram (ECG) changes that reflect diseases but also indicate important underlying pathology. The timely detection of LBBB and RBBB is critical in the treatment of cardiac diseases. Inter-patient heartbeat classification is based on independent training and testing sets to construct and evaluate a heartbeat classification system. Therefore, a heartbeat classification system with a high performance evaluation possesses a strong predictive capability for unknown data. The aim of this study was to propose a method for inter-patient classification of heartbeats to accurately detect LBBB and RBBB from the normal beat (NORM). This study proposed a heartbeat classification method through a combination of three different types of classifiers: a minimum distance classifier constructed between NORM and LBBB; a weighted linear discriminant classifier between NORM and RBBB based on Bayesian decision making using posterior probabilities; and a linear support vector machine (SVM) between LBBB and RBBB. Each classifier was used with matching features to obtain better classification performance. The final types of the test heartbeats were determined using a majority voting strategy through the combination of class labels from the three classifiers. The optimal parameters for the classifiers were selected using cross-validation on the training set. The effects of different lead configurations on the classification results were assessed, and the performance of these three classifiers was compared for the detection of each pair of heartbeat types. The study results showed that a two-lead configuration exhibited better classification results compared with a single-lead configuration. The construction of a classifier with good performance between each pair of heartbeat types significantly improved the heartbeat classification performance. The results showed a sensitivity of 91.4% and a positive predictive value of 37.3% for LBBB and a sensitivity of 92.8% and a positive predictive value of 88.8% for RBBB. A multi-classifier ensemble method was proposed based on inter-patient data and demonstrated a satisfactory classification performance. This approach has the potential for application in clinical practice to distinguish LBBB and RBBB from NORM of unknown patients.

Online Distance Teaching of Undergraduate Finance: A Case for Musashi University and Konan University, Japan

ERIC Educational Resources Information Center

Kubota, Keiichi; Fujikawa, Kiyoshi

2007-01-01

We implemented a synchronous distance course entitled: Introductory Finance designed for undergraduate students. This course was held between two Japanese universities. Stable Internet connections allowing minimum delay and minimum interruptions of the audio-video streaming signals were used. Students were equipped with their own PCs with…

A Linguistic Image of Nature: The Burmese Numerative Classifier System

ERIC Educational Resources Information Center

Becker, Alton L.

1975-01-01

The Burmese classifier system is coherent because it is based upon a single elementary semantic dimension: deixis. On that dimension, four distances are distinguished, distances which metaphorically substitute for other conceptual relations between people and other living beings, people and things, and people and concepts. (Author/RM)

41 CFR 105-62.102 - Authority to originally classify.

Code of Federal Regulations, 2013 CFR

2013-07-01

... originally classify. (a) Top secret, secret, and confidential. The authority to originally classify information as Top Secret, Secret, or Confidential may be exercised only by the Administrator and is delegable... classification authority. Delegations of original classification authority are limited to the minimum number...

41 CFR 105-62.102 - Authority to originally classify.

Code of Federal Regulations, 2011 CFR

2011-01-01

... originally classify. (a) Top secret, secret, and confidential. The authority to originally classify information as Top Secret, Secret, or Confidential may be exercised only by the Administrator and is delegable... classification authority. Delegations of original classification authority are limited to the minimum number...

41 CFR 105-62.102 - Authority to originally classify.

Code of Federal Regulations, 2014 CFR

2014-01-01

... originally classify. (a) Top secret, secret, and confidential. The authority to originally classify information as Top Secret, Secret, or Confidential may be exercised only by the Administrator and is delegable... classification authority. Delegations of original classification authority are limited to the minimum number...

Protograph LDPC Codes with Node Degrees at Least 3

NASA Technical Reports Server (NTRS)

Divsalar, Dariush; Jones, Christopher

2006-01-01

In this paper we present protograph codes with a small number of degree-3 nodes and one high degree node. The iterative decoding threshold for proposed rate 1/2 codes are lower, by about 0.2 dB, than the best known irregular LDPC codes with degree at least 3. The main motivation is to gain linear minimum distance to achieve low error floor. Also to construct rate-compatible protograph-based LDPC codes for fixed block length that simultaneously achieves low iterative decoding threshold and linear minimum distance. We start with a rate 1/2 protograph LDPC code with degree-3 nodes and one high degree node. Higher rate codes are obtained by connecting check nodes with degree-2 non-transmitted nodes. This is equivalent to constraint combining in the protograph. The condition where all constraints are combined corresponds to the highest rate code. This constraint must be connected to nodes of degree at least three for the graph to have linear minimum distance. Thus having node degree at least 3 for rate 1/2 guarantees linear minimum distance property to be preserved for higher rates. Through examples we show that the iterative decoding threshold as low as 0.544 dB can be achieved for small protographs with node degrees at least three. A family of low- to high-rate codes with minimum distance linearly increasing in block size and with capacity-approaching performance thresholds is presented. FPGA simulation results for a few example codes show that the proposed codes perform as predicted.

Interspecific geographic range size-body size relationship and the diversification dynamics of Neotropical furnariid birds.

PubMed

Inostroza-Michael, Oscar; Hernández, Cristián E; Rodríguez-Serrano, Enrique; Avaria-Llautureo, Jorge; Rivadeneira, Marcelo M

2018-05-01

Among the earliest macroecological patterns documented, is the range and body size relationship, characterized by a minimum geographic range size imposed by the species' body size. This boundary for the geographic range size increases linearly with body size and has been proposed to have implications in lineages evolution and conservation. Nevertheless, the macroevolutionary processes involved in the origin of this boundary and its consequences on lineage diversification have been poorly explored. We evaluate the macroevolutionary consequences of the difference (hereafter the distance) between the observed and the minimum range sizes required by the species' body size, to untangle its role on the diversification of a Neotropical species-rich bird clade using trait-dependent diversification models. We show that speciation rate is a positive hump-shaped function of the distance to the lower boundary. The species with highest and lowest distances to minimum range size had lower speciation rates, while species close to medium distances values had the highest speciation rates. Further, our results suggest that the distance to the minimum range size is a macroevolutionary constraint that affects the diversification process responsible for the origin of this macroecological pattern in a more complex way than previously envisioned. © 2018 The Author(s). Evolution © 2018 The Society for the Study of Evolution.

On the minimum orbital intersection distance computation: a new effective method

NASA Astrophysics Data System (ADS)

Hedo, José M.; Ruíz, Manuel; Peláez, Jesús

2018-06-01

The computation of the Minimum Orbital Intersection Distance (MOID) is an old, but increasingly relevant problem. Fast and precise methods for MOID computation are needed to select potentially hazardous asteroids from a large catalogue. The same applies to debris with respect to spacecraft. An iterative method that strictly meets these two premises is presented.

Reading Skill and the Minimum Distance Principle: A Comparison of Sentence Comprehension in Context and in Isolation.

ERIC Educational Resources Information Center

Goldman, Susan R.

The comprehension of the Minimum Distance Principle was examined in three experiments, using the "tell/promise" sentence construction. Experiment one compared the listening and reading comprehension of singly presented sentences, e.g. "John tells Bill to bake the cake" and "John promises Bill to bake the cake." The…

30 CFR 77.807-3 - Movement of equipment; minimum distance from high-voltage lines.

Code of Federal Regulations, 2010 CFR

2010-07-01

... high-voltage lines. 77.807-3 Section 77.807-3 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION... WORK AREAS OF UNDERGROUND COAL MINES Surface High-Voltage Distribution § 77.807-3 Movement of equipment; minimum distance from high-voltage lines. When any part of any equipment operated on the surface of any...

30 CFR 77.807-2 - Booms and masts; minimum distance from high-voltage lines.

Code of Federal Regulations, 2010 CFR

2010-07-01

...-voltage lines. 77.807-2 Section 77.807-2 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION... WORK AREAS OF UNDERGROUND COAL MINES Surface High-Voltage Distribution § 77.807-2 Booms and masts; minimum distance from high-voltage lines. The booms and masts of equipment operated on the surface of any...

Automatic tissue characterization from ultrasound imagery

NASA Astrophysics Data System (ADS)

Kadah, Yasser M.; Farag, Aly A.; Youssef, Abou-Bakr M.; Badawi, Ahmed M.

1993-08-01

In this work, feature extraction algorithms are proposed to extract the tissue characterization parameters from liver images. Then the resulting parameter set is further processed to obtain the minimum number of parameters representing the most discriminating pattern space for classification. This preprocessing step was applied to over 120 pathology-investigated cases to obtain the learning data for designing the classifier. The extracted features are divided into independent training and test sets and are used to construct both statistical and neural classifiers. The optimal criteria for these classifiers are set to have minimum error, ease of implementation and learning, and the flexibility for future modifications. Various algorithms for implementing various classification techniques are presented and tested on the data. The best performance was obtained using a single layer tensor model functional link network. Also, the voting k-nearest neighbor classifier provided comparably good diagnostic rates.

Protograph based LDPC codes with minimum distance linearly growing with block size

NASA Technical Reports Server (NTRS)

Divsalar, Dariush; Jones, Christopher; Dolinar, Sam; Thorpe, Jeremy

2005-01-01

We propose several LDPC code constructions that simultaneously achieve good threshold and error floor performance. Minimum distance is shown to grow linearly with block size (similar to regular codes of variable degree at least 3) by considering ensemble average weight enumerators. Our constructions are based on projected graph, or protograph, structures that support high-speed decoder implementations. As with irregular ensembles, our constructions are sensitive to the proportion of degree-2 variable nodes. A code with too few such nodes tends to have an iterative decoding threshold that is far from the capacity threshold. A code with too many such nodes tends to not exhibit a minimum distance that grows linearly in block length. In this paper we also show that precoding can be used to lower the threshold of regular LDPC codes. The decoding thresholds of the proposed codes, which have linearly increasing minimum distance in block size, outperform that of regular LDPC codes. Furthermore, a family of low to high rate codes, with thresholds that adhere closely to their respective channel capacity thresholds, is presented. Simulation results for a few example codes show that the proposed codes have low error floors as well as good threshold SNFt performance.

Grading vascularity from histopathological images based on traveling salesman distance and vessel size

NASA Astrophysics Data System (ADS)

Niazi, M. Khalid Khan; Hemminger, Jessica; Kurt, Habibe; Lozanski, Gerard; Gurcan, Metin

2014-03-01

Vascularity represents an important element of tissue/tumor microenvironment and is implicated in tumor growth, metastatic potential and resistence to therapy. Small blood vessels can be visualized using immunohistochemical stains specific to vascular cells. However, currently used manual methods to assess vascular density are poorly reproducible and are at best semi quantitative. Computer based quantitative and objective methods to measure microvessel density are urgently needed to better understand and clinically utilize microvascular density information. We propose a new method to quantify vascularity from images of bone marrow biopsies stained for CD34 vascular lining cells protein as a model. The method starts by automatically segmenting the blood vessels by methods of maxlink thresholding and minimum graph cuts. The segmentation is followed by morphological post-processing to reduce blast and small spurious objects from the bone marrow images. To classify the images into one of the four grades, we extracted 20 features from the segmented blood vessel images. These features include first four moments of the distribution of the area of blood vessels, first four moments of the distribution of 1) the edge weights in the minimum spanning tree of the blood vessels, 2) the shortest distance between blood vessels, 3) the homogeneity of the shortest distance (absolute difference in distance between consecutive blood vessels along the shortest path) between blood vessels and 5) blood vessel orientation. The method was tested on 26 bone marrow biopsy images stained with CD34 IHC stain, which were evaluated by three pathologists. The pathologists took part in this study by quantifying blood vessel density using gestalt assessment in hematopoietic bone marrow portions of bone marrow core biopsies images. To determine the intra-reader variability, each image was graded twice by each pathologist with two-week interval in between their readings. For each image, the ground truth (grade) was acquired through consensus among the three pathologists at the end of the study. A ranking of the features reveals that the fourth moment of the distribution of the area of blood vessels along with the first moment of the distribution of the shortest distance between blood vessels can correctly grade 68.2% of the bone marrow biopsies, while the intra- and inter-reader variability among the pathologists are 66.9% and 40.0%, respectively.

MSEBAG: a dynamic classifier ensemble generation based on `minimum-sufficient ensemble' and bagging

NASA Astrophysics Data System (ADS)

Chen, Lei; Kamel, Mohamed S.

2016-01-01

In this paper, we propose a dynamic classifier system, MSEBAG, which is characterised by searching for the 'minimum-sufficient ensemble' and bagging at the ensemble level. It adopts an 'over-generation and selection' strategy and aims to achieve a good bias-variance trade-off. In the training phase, MSEBAG first searches for the 'minimum-sufficient ensemble', which maximises the in-sample fitness with the minimal number of base classifiers. Then, starting from the 'minimum-sufficient ensemble', a backward stepwise algorithm is employed to generate a collection of ensembles. The objective is to create a collection of ensembles with a descending fitness on the data, as well as a descending complexity in the structure. MSEBAG dynamically selects the ensembles from the collection for the decision aggregation. The extended adaptive aggregation (EAA) approach, a bagging-style algorithm performed at the ensemble level, is employed for this task. EAA searches for the competent ensembles using a score function, which takes into consideration both the in-sample fitness and the confidence of the statistical inference, and averages the decisions of the selected ensembles to label the test pattern. The experimental results show that the proposed MSEBAG outperforms the benchmarks on average.

Molecular markers for establishing distinctness in vegetatively propagated crops: a case study in grapevine.

PubMed

Ibáñez, Javier; Vélez, M Dolores; de Andrés, M Teresa; Borrego, Joaquín

2009-11-01

Distinctness, uniformity and stability (DUS) testing of varieties is usually required to apply for Plant Breeders' Rights. This exam is currently carried out using morphological traits, where the establishment of distinctness through a minimum distance is the key issue. In this study, the possibility of using microsatellite markers for establishing the minimum distance in a vegetatively propagated crop (grapevine) has been evaluated. A collection of 991 accessions have been studied with nine microsatellite markers and pair-wise compared, and the highest intra-variety distance and the lowest inter-variety distance determined. The collection included 489 different genotypes, and synonyms and sports. Average values for number of alleles per locus (19), Polymorphic Information Content (0.764) and heterozygosities observed (0.773) and expected (0.785) indicated the high level of polymorphism existing in grapevine. The maximum intra-variety variability found was one allele between two accessions of the same variety, of a total of 3,171 pair-wise comparisons. The minimum inter-variety variability found was two alleles between two pairs of varieties, of a total of 119,316 pair-wise comparisons. In base to these results, the minimum distance required to set distinctness in grapevine with the nine microsatellite markers used could be established in two alleles. General rules for the use of the system as a support for establishing distinctness in vegetatively propagated crops are discussed.

LDPC Codes with Minimum Distance Proportional to Block Size

NASA Technical Reports Server (NTRS)

Divsalar, Dariush; Jones, Christopher; Dolinar, Samuel; Thorpe, Jeremy

2009-01-01

Low-density parity-check (LDPC) codes characterized by minimum Hamming distances proportional to block sizes have been demonstrated. Like the codes mentioned in the immediately preceding article, the present codes are error-correcting codes suitable for use in a variety of wireless data-communication systems that include noisy channels. The previously mentioned codes have low decoding thresholds and reasonably low error floors. However, the minimum Hamming distances of those codes do not grow linearly with code-block sizes. Codes that have this minimum-distance property exhibit very low error floors. Examples of such codes include regular LDPC codes with variable degrees of at least 3. Unfortunately, the decoding thresholds of regular LDPC codes are high. Hence, there is a need for LDPC codes characterized by both low decoding thresholds and, in order to obtain acceptably low error floors, minimum Hamming distances that are proportional to code-block sizes. The present codes were developed to satisfy this need. The minimum Hamming distances of the present codes have been shown, through consideration of ensemble-average weight enumerators, to be proportional to code block sizes. As in the cases of irregular ensembles, the properties of these codes are sensitive to the proportion of degree-2 variable nodes. A code having too few such nodes tends to have an iterative decoding threshold that is far from the capacity threshold. A code having too many such nodes tends not to exhibit a minimum distance that is proportional to block size. Results of computational simulations have shown that the decoding thresholds of codes of the present type are lower than those of regular LDPC codes. Included in the simulations were a few examples from a family of codes characterized by rates ranging from low to high and by thresholds that adhere closely to their respective channel capacity thresholds; the simulation results from these examples showed that the codes in question have low error floors as well as low decoding thresholds. As an example, the illustration shows the protograph (which represents the blueprint for overall construction) of one proposed code family for code rates greater than or equal to 1.2. Any size LDPC code can be obtained by copying the protograph structure N times, then permuting the edges. The illustration also provides Field Programmable Gate Array (FPGA) hardware performance simulations for this code family. In addition, the illustration provides minimum signal-to-noise ratios (Eb/No) in decibels (decoding thresholds) to achieve zero error rates as the code block size goes to infinity for various code rates. In comparison with the codes mentioned in the preceding article, these codes have slightly higher decoding thresholds.

Gas chimney detection based on improving the performance of combined multilayer perceptron and support vector classifier

NASA Astrophysics Data System (ADS)

Hashemi, H.; Tax, D. M. J.; Duin, R. P. W.; Javaherian, A.; de Groot, P.

2008-11-01

Seismic object detection is a relatively new field in which 3-D bodies are visualized and spatial relationships between objects of different origins are studied in order to extract geologic information. In this paper, we propose a method for finding an optimal classifier with the help of a statistical feature ranking technique and combining different classifiers. The method, which has general applicability, is demonstrated here on a gas chimney detection problem. First, we evaluate a set of input seismic attributes extracted at locations labeled by a human expert using regularized discriminant analysis (RDA). In order to find the RDA score for each seismic attribute, forward and backward search strategies are used. Subsequently, two non-linear classifiers: multilayer perceptron (MLP) and support vector classifier (SVC) are run on the ranked seismic attributes. Finally, to capitalize on the intrinsic differences between both classifiers, the MLP and SVC results are combined using logical rules of maximum, minimum and mean. The proposed method optimizes the ranked feature space size and yields the lowest classification error in the final combined result. We will show that the logical minimum reveals gas chimneys that exhibit both the softness of MLP and the resolution of SVC classifiers.

Electrofishing distance needed to estimate consistent Index of Biotic Integrity (IBI) scores in raftable Oregon rivers

EPA Science Inventory

An important issue surrounding assessment of riverine fish assemblages is the minimum amount of sampling distance needed to adequately determine biotic condition. Determining adequate sampling distance is important because sampling distance affects estimates of fish assemblage c...

New presentation method for magnetic resonance angiography images based on skeletonization

NASA Astrophysics Data System (ADS)

Nystroem, Ingela; Smedby, Orjan

2000-04-01

Magnetic resonance angiography (MRA) images are usually presented as maximum intensity projections (MIP), and the choice of viewing direction is then critical for the detection of stenoses. We propose a presentation method that uses skeletonization and distance transformations, which visualizes variations in vessel width independent of viewing direction. In the skeletonization, the object is reduced to a surface skeleton and further to a curve skeleton. The skeletal voxels are labeled with their distance to the original background. For the curve skeleton, the distance values correspond to the minimum radius of the object at that point, i.e., half the minimum diameter of the blood vessel at that level. The following image processing steps are performed: resampling to cubic voxels, segmentation of the blood vessels, skeletonization ,and reverse distance transformation on the curve skeleton. The reconstructed vessels may be visualized with any projection method. Preliminary results are shown. They indicate that locations of possible stenoses may be identified by presenting the vessels as a structure with the minimum radius at each point.

Hybrid Stochastic Models for Remaining Lifetime Prognosis

DTIC Science & Technology

2004-08-01

literature for techniques and comparisons. Os- ogami and Harchol-Balter [70], Perros [73], Johnson [36], and Altiok [5] provide excellent summaries of...and type of PH-distribution approximation for c2 > 0.5 is not as obvious. In order to use the minimum distance estimation, Perros [73] indicated that...moment-matching techniques. Perros [73] indicated that the maximum likelihood and minimum distance techniques require nonlinear optimization. Johnson

Distal scar-to-midline distance in pilonidal Limberg flap surgery is a recurrence-promoting factor: A multicenter, case-control study.

PubMed

Kaplan, Mehmet; Ozcan, Onder; Bilgic, Ethem; Kaplan, Elif Tugce; Kaplan, Tugba; Kaplan, Fatma Cigdem

2017-11-01

The Limberg flap (LF) procedure is widely performed for the treatment of sacrococcygeal pilonidal sinus (SPS); however, recurrences continues to be observed. The aim of this study was to assess the relationship between LF designs and the risk of SPS recurrence. Sixty-one cases with recurrent disease (study group) and 194 controls, with a minimum of 5 recurrence-free years following surgery (control group), were included in the study. LF reconstructions performed in each group were classified as off-midline closure (OMC) and non-OMC types. Subsequently, the 2 groups were analyzed. After adjustment for all variables, non-OMC types showed the most prominent correlation with recurrence, followed by interrupted suturing type, family history of SPS, smoking, prolonged healing time, and younger age. The best cut-off value for the critical distance from the midline was found to be 11 mm (with 72% sensitivity and 95% specificity for recurrence). We recommend OMC modifications, with the flap tailored to create a safe margin of at least 2 cm between the flap borders and the midline. Copyright © 2017 Elsevier Inc. All rights reserved.

Graphical Representations and Odds Ratios in a Distance-Association Model for the Analysis of Cross-Classified Data

ERIC Educational Resources Information Center

de Rooij, Mark; Heiser, Willem J.

2005-01-01

Although RC(M)-association models have become a generally useful tool for the analysis of cross-classified data, the graphical representation resulting from such an analysis can at times be misleading. The relationships present between row category points and column category points cannot be interpreted by inter point distances but only through…

Discrimination of different sub-basins on Tajo River based on water influence factor

NASA Astrophysics Data System (ADS)

Bermudez, R.; Gascó, J. M.; Tarquis, A. M.; Saa-Requejo, A.

2009-04-01

Numeric taxonomy has been applied to classify Tajo basin water (Spain) till Portugal border. Several stations, a total of 52, that estimate 15 water variables have been used in this study. The different groups have been obtained applying a Euclidean distance among stations (distance classification) and a Euclidean distance between each station and the centroid estimated among them (centroid classification), varying the number of parameters and with or without variable typification. In order to compare the classification a log-log relation has been established, between number of groups created and distances, to select the best one. It has been observed that centroid classification is more appropriate following in a more logic way the natural constrictions than the minimum distance among stations. Variable typification doesn't improve the classification except when the centroid method is applied. Taking in consideration the ions and the sum of them as variables, the classification improved. Stations are grouped based on electric conductivity (CE), total anions (TA), total cations (TC) and ions ratio (Na/Ca and Mg/Ca). For a given classification and comparing the different groups created a certain variation in ions concentration and ions ratio are observed. However, the variation in each ion among groups is different depending on the case. For the last group, regardless the classification, the increase in all ions is general. Comparing the dendrograms, and groups that originated, Tajo river basin can be sub dived in five sub-basins differentiated by the main influence on water: 1. With a higher ombrogenic influence (rain fed). 2. With ombrogenic and pedogenic influence (rain and groundwater fed). 3. With pedogenic influence. 4. With lithogenic influence (geological bedrock). 5. With a higher ombrogenic and lithogenic influence added.

Reliability Based Geometric Design of Horizontal Circular Curves

NASA Astrophysics Data System (ADS)

Rajbongshi, Pabitra; Kalita, Kuldeep

2018-06-01

Geometric design of horizontal circular curve primarily involves with radius of the curve and stopping sight distance at the curve section. Minimum radius is decided based on lateral thrust exerted on the vehicles and the minimum stopping sight distance is provided to maintain the safety in longitudinal direction of vehicles. Available sight distance at site can be regulated by changing the radius and middle ordinate at the curve section. Both radius and sight distance depend on design speed. Speed of vehicles at any road section is a variable parameter and therefore, normally the 98th percentile speed is taken as the design speed. This work presents a probabilistic approach for evaluating stopping sight distance, considering the variability of all input parameters of sight distance. It is observed that the 98th percentile sight distance value is much lower than the sight distance corresponding to 98th percentile speed. The distribution of sight distance parameter is also studied and found to follow a lognormal distribution. Finally, the reliability based design charts are presented for both plain and hill regions, and considering the effect of lateral thrust.

A unique concept for automatically controlling the braking action of wheeled vehicles during minimum distance stops

NASA Technical Reports Server (NTRS)

Barthlome, D. E.

1975-01-01

Test results of a unique automatic brake control system are outlined and a comparison is made of its mode of operation to that of an existing skid control system. The purpose of the test system is to provide automatic control of braking action such that hydraulic brake pressure is maintained at a near constant, optimum value during minimum distance stops.

Local Subspace Classifier with Transform-Invariance for Image Classification

NASA Astrophysics Data System (ADS)

Hotta, Seiji

A family of linear subspace classifiers called local subspace classifier (LSC) outperforms the k-nearest neighbor rule (kNN) and conventional subspace classifiers in handwritten digit classification. However, LSC suffers very high sensitivity to image transformations because it uses projection and the Euclidean distances for classification. In this paper, I present a combination of a local subspace classifier (LSC) and a tangent distance (TD) for improving accuracy of handwritten digit recognition. In this classification rule, we can deal with transform-invariance easily because we are able to use tangent vectors for approximation of transformations. However, we cannot use tangent vectors in other type of images such as color images. Hence, kernel LSC (KLSC) is proposed for incorporating transform-invariance into LSC via kernel mapping. The performance of the proposed methods is verified with the experiments on handwritten digit and color image classification.

Distance estimation and collision prediction for on-line robotic motion planning

NASA Technical Reports Server (NTRS)

Kyriakopoulos, K. J.; Saridis, G. N.

1992-01-01

An efficient method for computing the minimum distance and predicting collisions between moving objects is presented. This problem is incorporated into the framework of an in-line motion-planning algorithm to satisfy collision avoidance between a robot and moving objects modeled as convex polyhedra. In the beginning, the deterministic problem where the information about the objects is assumed to be certain is examined. L(1) or L(infinity) norms are used to represent distance and the problem becomes a linear programming problem. The stochastic problem is formulated where the uncertainty is induced by sensing and the unknown dynamics of the moving obstacles. Two problems are considered: First, filtering of the distance between the robot and the moving object at the present time. Second, prediction of the minimum distance in the future in order to predict the collision time.

The Minimum Wage and the Employment of Teenagers. Recent Research.

ERIC Educational Resources Information Center

Fallick, Bruce; Currie, Janet

A study used individual-level data from the National Longitudinal Study of Youth to examine the effects of changes in the federal minimum wage on teenage employment. Individuals in the sample were classified as either likely or unlikely to be affected by these increases in the federal minimum wage on the basis of their wage rates and industry of…

On the Nature of Distance Education.

ERIC Educational Resources Information Center

Baath, John A.

1981-01-01

Discusses several points made by Keegan in an article of the same title which appeared in "Distance Education" in March 1980 and also classifies the different types of distance education and their respective philosophies and teaching requirements. (EAO)

49 CFR 175.706 - Separation distances for undeveloped film from packages containing Class 7 (radioactive) materials.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 49 Transportation 2 2014-10-01 2014-10-01 false Separation distances for undeveloped film from... Classification of Material § 175.706 Separation distances for undeveloped film from packages containing Class 7... film. Transport index Minimum separation distance to nearest undeveloped film for various times in...

49 CFR 175.706 - Separation distances for undeveloped film from packages containing Class 7 (radioactive) materials.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 49 Transportation 2 2011-10-01 2011-10-01 false Separation distances for undeveloped film from... Classification of Material § 175.706 Separation distances for undeveloped film from packages containing Class 7... film. Transport index Minimum separation distance to nearest undeveloped film for various times in...

49 CFR 175.706 - Separation distances for undeveloped film from packages containing Class 7 (radioactive) materials.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 49 Transportation 2 2013-10-01 2013-10-01 false Separation distances for undeveloped film from... Classification of Material § 175.706 Separation distances for undeveloped film from packages containing Class 7... film. Transport index Minimum separation distance to nearest undeveloped film for various times in...

49 CFR 175.706 - Separation distances for undeveloped film from packages containing Class 7 (radioactive) materials.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 49 Transportation 2 2012-10-01 2012-10-01 false Separation distances for undeveloped film from... Classification of Material § 175.706 Separation distances for undeveloped film from packages containing Class 7... film. Transport index Minimum separation distance to nearest undeveloped film for various times in...

49 CFR 175.706 - Separation distances for undeveloped film from packages containing Class 7 (radioactive) materials.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 49 Transportation 2 2010-10-01 2010-10-01 false Separation distances for undeveloped film from... Classification of Material § 175.706 Separation distances for undeveloped film from packages containing Class 7... film. Transport index Minimum separation distance to nearest undeveloped film for various times in...

Minimum separation distances for natural gas pipeline and boilers in the 300 area, Hanford Site

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

Daling, P.M.; Graham, T.M.

1997-08-01

The U.S. Department of Energy (DOE) is proposing actions to reduce energy expenditures and improve energy system reliability at the 300 Area of the Hanford Site. These actions include replacing the centralized heating system with heating units for individual buildings or groups of buildings, constructing a new natural gas distribution system to provide a fuel source for many of these units, and constructing a central control building to operate and maintain the system. The individual heating units will include steam boilers that are to be housed in individual annex buildings located at some distance away from nearby 300 Area nuclearmore » facilities. This analysis develops the basis for siting the package boilers and natural gas distribution systems to be used to supply steam to 300 Area nuclear facilities. The effects of four potential fire and explosion scenarios involving the boiler and natural gas pipeline were quantified to determine minimum separation distances that would reduce the risks to nearby nuclear facilities. The resulting minimum separation distances are shown in Table ES.1.« less

30 CFR 75.1107-9 - Dry chemical devices; capacity; minimum requirements.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Dry chemical devices; capacity; minimum... Dry chemical devices; capacity; minimum requirements. (a) Dry chemical fire extinguishing systems used...; (3) Hose and pipe shall be as short as possible; the distance between the chemical container and...

30 CFR 75.1107-9 - Dry chemical devices; capacity; minimum requirements.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Dry chemical devices; capacity; minimum... Dry chemical devices; capacity; minimum requirements. (a) Dry chemical fire extinguishing systems used...; (3) Hose and pipe shall be as short as possible; the distance between the chemical container and...

30 CFR 75.1107-9 - Dry chemical devices; capacity; minimum requirements.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 1 2013-07-01 2013-07-01 false Dry chemical devices; capacity; minimum... Dry chemical devices; capacity; minimum requirements. (a) Dry chemical fire extinguishing systems used...; (3) Hose and pipe shall be as short as possible; the distance between the chemical container and...

30 CFR 75.1107-9 - Dry chemical devices; capacity; minimum requirements.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 1 2012-07-01 2012-07-01 false Dry chemical devices; capacity; minimum... Dry chemical devices; capacity; minimum requirements. (a) Dry chemical fire extinguishing systems used...; (3) Hose and pipe shall be as short as possible; the distance between the chemical container and...

Spatial variability in airborne pollen concentrations.

PubMed

Raynor, G S; Ogden, E C; Hayes, J V

1975-03-01

Tests were conducted to determine the relationship between airborne pollen concentrations and distance. Simultaneous samples were taken in 171 tests with sets of eight rotoslide samplers spaced from one to 486 M. apart in straight lines. Use of all possible pairs gave 28 separation distances. Tests were conducted over a 2-year period in urban and rural locations distant from major pollen sources during both tree and ragweed pollen seasons. Samples were taken at a height of 1.5 M. during 5-to 20-minute periods. Tests were grouped by pollen type, location, year, and direction of the wind relative to the line. Data were analyzed to evaluate variability without regard to sampler spacing and variability as a function of separation distance. The mean, standard deviation, coefficient of variation, ratio of maximum to the mean, and ratio of minimum to the mean were calculated for each test, each group of tests, and all cases. The average coefficient of variation is 0.21, the maximum over the mean, 1.39 and the minimum over the mean, 0.69. No relationship was found with experimental conditions. Samples taken at the minimum separation distance had a mean difference of 18 per cent. Differences between pairs of samples increased with distance in 10 of 13 groups. These results suggest that airborne pollens are not always well mixed in the lower atmosphere and that a sample becomes less representative with increasing distance from the sampling location.

49 CFR 176.708 - Segregation distances.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 49 Transportation 2 2011-10-01 2011-10-01 false Segregation distances. 176.708 Section 176.708... Requirements for Radioactive Materials § 176.708 Segregation distances. (a) Table IV lists minimum separation... into account any relocation of cargo during the voyage. (e) Any departure from the segregation...

Real Time Intelligent Target Detection and Analysis with Machine Vision

NASA Technical Reports Server (NTRS)

Howard, Ayanna; Padgett, Curtis; Brown, Kenneth

2000-01-01

We present an algorithm for detecting a specified set of targets for an Automatic Target Recognition (ATR) application. ATR involves processing images for detecting, classifying, and tracking targets embedded in a background scene. We address the problem of discriminating between targets and nontarget objects in a scene by evaluating 40x40 image blocks belonging to an image. Each image block is first projected onto a set of templates specifically designed to separate images of targets embedded in a typical background scene from those background images without targets. These filters are found using directed principal component analysis which maximally separates the two groups. The projected images are then clustered into one of n classes based on a minimum distance to a set of n cluster prototypes. These cluster prototypes have previously been identified using a modified clustering algorithm based on prior sensed data. Each projected image pattern is then fed into the associated cluster's trained neural network for classification. A detailed description of our algorithm will be given in this paper. We outline our methodology for designing the templates, describe our modified clustering algorithm, and provide details on the neural network classifiers. Evaluation of the overall algorithm demonstrates that our detection rates approach 96% with a false positive rate of less than 0.03%.

ELECTROFISHING DISTANCE NEEDED TO ESTIMATE FISH SPECIES RICHNESS IN RAFTABLE WESTERN USA RIVERS

EPA Science Inventory

A critical issue in river monitoring is the minimum amount of sampling distance required to adequately represent the fish assemblage of a reach. Determining adequate sampling distance is important because it affects estimates of fish assemblage integrity and diversity at local a...

A minimum spanning forest based classification method for dedicated breast CT images

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

Pike, Robert; Sechopoulos, Ioannis; Fei, Baowei, E-mail: bfei@emory.edu

Purpose: To develop and test an automated algorithm to classify different types of tissue in dedicated breast CT images. Methods: Images of a single breast of five different patients were acquired with a dedicated breast CT clinical prototype. The breast CT images were processed by a multiscale bilateral filter to reduce noise while keeping edge information and were corrected to overcome cupping artifacts. As skin and glandular tissue have similar CT values on breast CT images, morphologic processing is used to identify the skin based on its position information. A support vector machine (SVM) is trained and the resulting modelmore » used to create a pixelwise classification map of fat and glandular tissue. By combining the results of the skin mask with the SVM results, the breast tissue is classified as skin, fat, and glandular tissue. This map is then used to identify markers for a minimum spanning forest that is grown to segment the image using spatial and intensity information. To evaluate the authors’ classification method, they use DICE overlap ratios to compare the results of the automated classification to those obtained by manual segmentation on five patient images. Results: Comparison between the automatic and the manual segmentation shows that the minimum spanning forest based classification method was able to successfully classify dedicated breast CT image with average DICE ratios of 96.9%, 89.8%, and 89.5% for fat, glandular, and skin tissue, respectively. Conclusions: A 2D minimum spanning forest based classification method was proposed and evaluated for classifying the fat, skin, and glandular tissue in dedicated breast CT images. The classification method can be used for dense breast tissue quantification, radiation dose assessment, and other applications in breast imaging.« less

Recognizing upper limb movements with wrist worn inertial sensors using k-means clustering classification.

PubMed

Biswas, Dwaipayan; Cranny, Andy; Gupta, Nayaab; Maharatna, Koushik; Achner, Josy; Klemke, Jasmin; Jöbges, Michael; Ortmann, Steffen

2015-04-01

In this paper we present a methodology for recognizing three fundamental movements of the human forearm (extension, flexion and rotation) using pattern recognition applied to the data from a single wrist-worn, inertial sensor. We propose that this technique could be used as a clinical tool to assess rehabilitation progress in neurodegenerative pathologies such as stroke or cerebral palsy by tracking the number of times a patient performs specific arm movements (e.g. prescribed exercises) with their paretic arm throughout the day. We demonstrate this with healthy subjects and stroke patients in a simple proof of concept study in which these arm movements are detected during an archetypal activity of daily-living (ADL) - 'making-a-cup-of-tea'. Data is collected from a tri-axial accelerometer and a tri-axial gyroscope located proximal to the wrist. In a training phase, movements are initially performed in a controlled environment which are represented by a ranked set of 30 time-domain features. Using a sequential forward selection technique, for each set of feature combinations three clusters are formed using k-means clustering followed by 10 runs of 10-fold cross validation on the training data to determine the best feature combinations. For the testing phase, movements performed during the ADL are associated with each cluster label using a minimum distance classifier in a multi-dimensional feature space, comprised of the best ranked features, using Euclidean or Mahalanobis distance as the metric. Experiments were performed with four healthy subjects and four stroke survivors and our results show that the proposed methodology can detect the three movements performed during the ADL with an overall average accuracy of 88% using the accelerometer data and 83% using the gyroscope data across all healthy subjects and arm movement types. The average accuracy across all stroke survivors was 70% using accelerometer data and 66% using gyroscope data. We also use a Linear Discriminant Analysis (LDA) classifier and a Support Vector Machine (SVM) classifier in association with the same set of features to detect the three arm movements and compare the results to demonstrate the effectiveness of our proposed methodology. Copyright © 2014 Elsevier B.V. All rights reserved.

Structure for identifying, locating and quantifying physical phenomena

DOEpatents

Richardson, John G.

2006-10-24

A method and system for detecting, locating and quantifying a physical phenomena such as strain or a deformation in a structure. A minimum resolvable distance along the structure is selected and a quantity of laterally adjacent conductors is determined. Each conductor includes a plurality of segments coupled in series which define the minimum resolvable distance along the structure. When a deformation occurs, changes in the defined energy transmission characteristics along each conductor are compared to determine which segment contains the deformation.

Method and apparatus for identifying, locating and quantifying physical phenomena and structure including same

DOEpatents

Richardson, John G.

2006-01-24

A method and system for detecting, locating and quantifying a physical phenomena such as strain or a deformation in a structure. A minimum resolvable distance along the structure is selected and a quantity of laterally adjacent conductors is determined. Each conductor includes a plurality of segments coupled in series which define the minimum resolvable distance along the structure. When a deformation occurs, changes in the defined energy transmission characteristics along each conductor are compared to determine which segment contains the deformation.

Classifying features in CT imagery: accuracy for some single- and multiple-species classifiers

Treesearch

Daniel L. Schmoldt; Jing He; A. Lynn Abbott

1998-01-01

Our current approach to automatically label features in CT images of hardwood logs classifies each pixel of an image individually. These feature classifiers use a back-propagation artificial neural network (ANN) and feature vectors that include a small, local neighborhood of pixels and the distance of the target pixel to the center of the log. Initially, this type of...

The diabolo classifier

PubMed

Schwenk

1998-11-15

We present a new classification architecture based on autoassociative neural networks that are used to learn discriminant models of each class. The proposed architecture has several interesting properties with respect to other model-based classifiers like nearest-neighbors or radial basis functions: it has a low computational complexity and uses a compact distributed representation of the models. The classifier is also well suited for the incorporation of a priori knowledge by means of a problem-specific distance measure. In particular, we will show that tangent distance (Simard, Le Cun, & Denker, 1993) can be used to achieve transformation invariance during learning and recognition. We demonstrate the application of this classifier to optical character recognition, where it has achieved state-of-the-art results on several reference databases. Relations to other models, in particular those based on principal component analysis, are also discussed.

Minimum triplet covers of binary phylogenetic X-trees.

PubMed

Huber, K T; Moulton, V; Steel, M

2017-12-01

Trees with labelled leaves and with all other vertices of degree three play an important role in systematic biology and other areas of classification. A classical combinatorial result ensures that such trees can be uniquely reconstructed from the distances between the leaves (when the edges are given any strictly positive lengths). Moreover, a linear number of these pairwise distance values suffices to determine both the tree and its edge lengths. A natural set of pairs of leaves is provided by any 'triplet cover' of the tree (based on the fact that each non-leaf vertex is the median vertex of three leaves). In this paper we describe a number of new results concerning triplet covers of minimum size. In particular, we characterize such covers in terms of an associated graph being a 2-tree. Also, we show that minimum triplet covers are 'shellable' and thereby provide a set of pairs for which the inter-leaf distance values will uniquely determine the underlying tree and its associated branch lengths.

Cyclists' perceptions of motorist harassment pre- to post-trial of the minimum passing distance road rule amendment in Queensland, Australia.

PubMed

Heesch, Kristiann C; Schramm, Amy; Debnath, Ashim Kumar; Haworth, Narelle

2017-12-01

Issues addressed Cyclists' perceptions of harassment from motorists discourages cycling. This study examined changes in cyclists' reporting of harassment pre- to post-introduction of the Queensland trial of the minimum passing distance road rule amendment (MPD-RRA). Methods Cross-sectional online surveys of cyclists in Queensland, Australia were conducted in 2009 (pre-trial; n=1758) and 2015 (post-trial commencement; n=1997). Cyclists were asked about their experiences of harassment from motorists while cycling. Logistic regression modelling was used to examine differences in the reporting of harassment between these time periods, after adjustments for demographic characteristics and cycling behaviour. Results At both time periods, the most reported types of harassment were deliberately driving too close (causing fear or anxiety), shouting abuse and making obscene gestures or engaging in sexual harassment. The percentage of cyclists who reported tailgating by motorists increased between 2009 and 2015 (15.1% to 19.5%; P<0.001). The percentage of cyclists reporting other types of harassment did not change significantly. Conclusions Cyclists in Queensland continue to perceive harassment while cycling on the road. The amendment to the minimum passing distance rule in Queensland appears to be having a negative effect on one type of harassment but no significant effects on others. So what? Minimum passing distance rules may not be improving cyclists' perceptions of motorists' behaviours. Additional strategies are required to create a supportive environment for cycling.

Understanding auditory distance estimation by humpback whales: a computational approach.

PubMed

Mercado, E; Green, S R; Schneider, J N

2008-02-01

Ranging, the ability to judge the distance to a sound source, depends on the presence of predictable patterns of attenuation. We measured long-range sound propagation in coastal waters to assess whether humpback whales might use frequency degradation cues to range singing whales. Two types of neural networks, a multi-layer and a single-layer perceptron, were trained to classify recorded sounds by distance traveled based on their frequency content. The multi-layer network successfully classified received sounds, demonstrating that the distorting effects of underwater propagation on frequency content provide sufficient cues to estimate source distance. Normalizing received sounds with respect to ambient noise levels increased the accuracy of distance estimates by single-layer perceptrons, indicating that familiarity with background noise can potentially improve a listening whale's ability to range. To assess whether frequency patterns predictive of source distance were likely to be perceived by whales, recordings were pre-processed using a computational model of the humpback whale's peripheral auditory system. Although signals processed with this model contained less information than the original recordings, neural networks trained with these physiologically based representations estimated source distance more accurately, suggesting that listening whales should be able to range singers using distance-dependent changes in frequency content.

Benefits of Using Pairwise Trajectory Management in the Central East Pacific

NASA Technical Reports Server (NTRS)

Chartrand, Ryan; Ballard, Kathryn

2016-01-01

Pairwise Trajectory Management (PTM) is a concept that utilizes airborne and ground-based capabilities to enable airborne spacing operations in oceanic regions. The goal of PTM is to use enhanced surveillance, along with airborne tools, to manage the spacing between aircraft. Due to the enhanced airborne surveillance of Automatic Dependent Surveillance-Broadcast (ADS-B) information and reduced communication, the PTM minimum spacing distance will be less than distances currently required of an air traffic controller. Reduced minimum distance will increase the capacity of aircraft operations at a given altitude or volume of airspace, thereby increasing time on desired trajectory and overall flight efficiency. PTM is designed to allow a flight crew to resolve a specific traffic conflict (or conflicts), identified by the air traffic controller, while maintaining the flight crew's desired altitude. The air traffic controller issues a PTM clearance to a flight crew authorized to conduct PTM operations in order to resolve a conflict for the pair (or pairs) of aircraft (i.e., the PTM aircraft and a designated target aircraft). This clearance requires the flight crew of the PTM aircraft to use their ADS-B-enabled onboard equipment to manage their spacing relative to the designated target aircraft to ensure spacing distances that are no closer than the PTM minimum distance. When the air traffic controller determines that PTM is no longer required, the controller issues a clearance to cancel the PTM operation.

Scale-dependent correlation of seabirds with schooling fish in a coastal ecosystem

USGS Publications Warehouse

Schneider, Davod C.; Piatt, John F.

1986-01-01

The distribution of piscivorous seabirds relative to schooling fish was investigated by repeated censusing of 2 intersecting transects in the Avalon Channel, which carries the Labrador Current southward along the east coast of Newfoundland. Murres (primarily common murres Uria aalge), Atlantic puffins Fratercula arctica, and schooling fish (primarily capelin Mallotus villosus) were highly aggregated at spatial scales ranging from 0.25 to 15 km. Patchiness of murres, puffins and schooling fish was scale-dependent, as indicated by significantly higher variance-to-mean ratios at large measurement distances than at the minimum distance, 0.25 km. Patch scale of puffins ranged from 2.5 to 15 km, of murres from 3 to 8.75 km, and of schooling fish from 1.25 to 15 km. Patch scale of birds and schooling fish was similar m 6 out of 9 comparisons. Correlation between seabirds and schooling birds was significant at the minimum measurement distance in 6 out of 12 comparisons. Correlation was scale-dependent, as indicated by significantly higher coefficients at large measurement distances than at the minimum distance. Tracking scale, as indicated by the maximum significant correlation between birds and schooling fish, ranged from 2 to 6 km. Our analysis showed that extended aggregations of seabirds are associated with extended aggregations of schooling fish and that correlation of these marine carnivores with their prey is scale-dependent.

Supervised Variational Relevance Learning, An Analytic Geometric Feature Selection with Applications to Omic Datasets.

PubMed

Boareto, Marcelo; Cesar, Jonatas; Leite, Vitor B P; Caticha, Nestor

2015-01-01

We introduce Supervised Variational Relevance Learning (Suvrel), a variational method to determine metric tensors to define distance based similarity in pattern classification, inspired in relevance learning. The variational method is applied to a cost function that penalizes large intraclass distances and favors small interclass distances. We find analytically the metric tensor that minimizes the cost function. Preprocessing the patterns by doing linear transformations using the metric tensor yields a dataset which can be more efficiently classified. We test our methods using publicly available datasets, for some standard classifiers. Among these datasets, two were tested by the MAQC-II project and, even without the use of further preprocessing, our results improve on their performance.

27 CFR 555.220 - Table of separation distances of ammonium nitrate and blasting agents from explosives or blasting...

Code of Federal Regulations, 2010 CFR

2010-04-01

... distances of ammonium nitrate and blasting agents from explosives or blasting agents. 555.220 Section 555... ammonium nitrate and blasting agents from explosives or blasting agents. Table: Department of Defense... Not over Minimum separation distance of acceptor from donor when barricaded (ft.) Ammonium nitrate...

27 CFR 555.220 - Table of separation distances of ammonium nitrate and blasting agents from explosives or blasting...

Code of Federal Regulations, 2011 CFR

2011-04-01

... distances of ammonium nitrate and blasting agents from explosives or blasting agents. 555.220 Section 555... ammonium nitrate and blasting agents from explosives or blasting agents. Table: Department of Defense... Not over Minimum separation distance of acceptor from donor when barricaded (ft.) Ammonium nitrate...

27 CFR 555.220 - Table of separation distances of ammonium nitrate and blasting agents from explosives or blasting...

Code of Federal Regulations, 2012 CFR

2012-04-01

... distances of ammonium nitrate and blasting agents from explosives or blasting agents. 555.220 Section 555... ammonium nitrate and blasting agents from explosives or blasting agents. Table: Department of Defense... Not over Minimum separation distance of acceptor from donor when barricaded (ft.) Ammonium nitrate...

27 CFR 555.220 - Table of separation distances of ammonium nitrate and blasting agents from explosives or blasting...

Code of Federal Regulations, 2013 CFR

2013-04-01

... distances of ammonium nitrate and blasting agents from explosives or blasting agents. 555.220 Section 555... ammonium nitrate and blasting agents from explosives or blasting agents. Table: Department of Defense... Not over Minimum separation distance of acceptor from donor when barricaded (ft.) Ammonium nitrate...

27 CFR 555.220 - Table of separation distances of ammonium nitrate and blasting agents from explosives or blasting...

Code of Federal Regulations, 2014 CFR

2014-04-01

... distances of ammonium nitrate and blasting agents from explosives or blasting agents. 555.220 Section 555... ammonium nitrate and blasting agents from explosives or blasting agents. Table: Department of Defense... Not over Minimum separation distance of acceptor from donor when barricaded (ft.) Ammonium nitrate...

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.

46 CFR 42.20-70 - Minimum bow height.

Code of Federal Regulations, 2012 CFR

2012-10-01

... Freeboards § 42.20-70 Minimum bow height. (a) The bow height defined as the vertical distance at the forward... 46 Shipping 2 2012-10-01 2012-10-01 false Minimum bow height. 42.20-70 Section 42.20-70 Shipping... less than 0.68. (b) Where the bow height required in paragraph (a) of this section is obtained by sheer...

46 CFR 42.20-70 - Minimum bow height.

Code of Federal Regulations, 2011 CFR

2011-10-01

... Freeboards § 42.20-70 Minimum bow height. (a) The bow height defined as the vertical distance at the forward... 46 Shipping 2 2011-10-01 2011-10-01 false Minimum bow height. 42.20-70 Section 42.20-70 Shipping... less than 0.68. (b) Where the bow height required in paragraph (a) of this section is obtained by sheer...

46 CFR 42.20-70 - Minimum bow height.

Code of Federal Regulations, 2014 CFR

2014-10-01

... Freeboards § 42.20-70 Minimum bow height. (a) The bow height defined as the vertical distance at the forward... 46 Shipping 2 2014-10-01 2014-10-01 false Minimum bow height. 42.20-70 Section 42.20-70 Shipping... less than 0.68. (b) Where the bow height required in paragraph (a) of this section is obtained by sheer...

46 CFR 42.20-70 - Minimum bow height.

Code of Federal Regulations, 2013 CFR

2013-10-01

... Freeboards § 42.20-70 Minimum bow height. (a) The bow height defined as the vertical distance at the forward... 46 Shipping 2 2013-10-01 2013-10-01 false Minimum bow height. 42.20-70 Section 42.20-70 Shipping... less than 0.68. (b) Where the bow height required in paragraph (a) of this section is obtained by sheer...

46 CFR 42.20-70 - Minimum bow height.

Code of Federal Regulations, 2010 CFR

2010-10-01

... Freeboards § 42.20-70 Minimum bow height. (a) The bow height defined as the vertical distance at the forward... 46 Shipping 2 2010-10-01 2010-10-01 false Minimum bow height. 42.20-70 Section 42.20-70 Shipping... less than 0.68. (b) Where the bow height required in paragraph (a) of this section is obtained by sheer...

The Effects of Target and Missile Characteristics on Theoretical Minimum Miss Distance for a Beam-Rider Guidance System in the Presence of Noise

NASA Technical Reports Server (NTRS)

Stewart, Elwood C.; Druding, Frank; Nishiura, Togo

1959-01-01

A study has been made to determine the relative importance of those factors which place an inherent limitation on the minimum obtainable miss distance for a beam-rider navigation system operating in the presence of glint noise and target evasive maneuver. Target and missile motions are assumed to be coplanar. The factors considered are the missile natural frequencies and damping ratios, missile steady-state acceleration capabilities, target evasive maneuver characteristics, and angular scintillation noise characteristics.

Minimum requirements for adequate nighttime conspicuity of highway signs

DOT National Transportation Integrated Search

1988-02-01

A laboratory and field study were conducted to assess the minimum luminance levels of signs to ensure that they will be detected and identified at adequate distances under nighttime driving conditions. A total of 30 subjects participated in the field...

A Robust Step Detection Algorithm and Walking Distance Estimation Based on Daily Wrist Activity Recognition Using a Smart Band.

PubMed

Trong Bui, Duong; Nguyen, Nhan Duc; Jeong, Gu-Min

2018-06-25

Human activity recognition and pedestrian dead reckoning are an interesting field because of their importance utilities in daily life healthcare. Currently, these fields are facing many challenges, one of which is the lack of a robust algorithm with high performance. This paper proposes a new method to implement a robust step detection and adaptive distance estimation algorithm based on the classification of five daily wrist activities during walking at various speeds using a smart band. The key idea is that the non-parametric adaptive distance estimator is performed after two activity classifiers and a robust step detector. In this study, two classifiers perform two phases of recognizing five wrist activities during walking. Then, a robust step detection algorithm, which is integrated with an adaptive threshold, peak and valley correction algorithm, is applied to the classified activities to detect the walking steps. In addition, the misclassification activities are fed back to the previous layer. Finally, three adaptive distance estimators, which are based on a non-parametric model of the average walking speed, calculate the length of each strike. The experimental results show that the average classification accuracy is about 99%, and the accuracy of the step detection is 98.7%. The error of the estimated distance is 2.2⁻4.2% depending on the type of wrist activities.

Social Web Content Enhancement in a Distance Learning Environment: Intelligent Metadata Generation for Resources

ERIC Educational Resources Information Center

García-Floriano, Andrés; Ferreira-Santiago, Angel; Yáñez-Márquez, Cornelio; Camacho-Nieto, Oscar; Aldape-Pérez, Mario; Villuendas-Rey, Yenny

2017-01-01

Social networking potentially offers improved distance learning environments by enabling the exchange of resources between learners. The existence of properly classified content results in an enhanced distance learning experience in which appropriate materials can be retrieved efficiently; however, for this to happen, metadata needs to be present.…

Handwritten character recognition using background analysis

NASA Astrophysics Data System (ADS)

Tascini, Guido; Puliti, Paolo; Zingaretti, Primo

1993-04-01

The paper describes a low-cost handwritten character recognizer. It is constituted by three modules: the `acquisition' module, the `binarization' module, and the `core' module. The core module can be logically partitioned into six steps: character dilation, character circumscription, region and `profile' analysis, `cut' analysis, decision tree descent, and result validation. Firstly, it reduces the resolution of the binarized regions and detects the minimum rectangle (MR) which encloses the character; the MR partitions the background into regions that surround the character or are enclosed by it, and allows it to define features as `profiles' and `cuts;' a `profile' is the set of vertical or horizontal minimum distances between a side of the MR and the character itself; a `cut' is a vertical or horizontal image segment delimited by the MR. Then, the core module classifies the character by descending along the decision tree on the basis of the analysis of regions around the character, in particular of the `profiles' and `cuts,' and without using context information. Finally, it recognizes the character or reactivates the core module by analyzing validation test results. The recognizer is largely insensible to character discontinuity and is able to detect Arabic numerals and English alphabet capital letters. The recognition rate of a 32 X 32 pixel character is of about 97% after the first iteration, and of over 98% after the second iteration.

Minimum variance geographic sampling

NASA Technical Reports Server (NTRS)

Terrell, G. R. (Principal Investigator)

1980-01-01

Resource inventories require samples with geographical scatter, sometimes not as widely spaced as would be hoped. A simple model of correlation over distances is used to create a minimum variance unbiased estimate population means. The fitting procedure is illustrated from data used to estimate Missouri corn acreage.

7 CFR 1703.133 - Maximum and minimum amounts.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 11 2010-01-01 2010-01-01 false Maximum and minimum amounts. 1703.133 Section 1703.133 Agriculture Regulations of the Department of Agriculture (Continued) RURAL UTILITIES SERVICE, DEPARTMENT OF AGRICULTURE RURAL DEVELOPMENT Distance Learning and Telemedicine Combination Loan and Grant...

7 CFR 1703.133 - Maximum and minimum amounts.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 11 2011-01-01 2011-01-01 false Maximum and minimum amounts. 1703.133 Section 1703.133 Agriculture Regulations of the Department of Agriculture (Continued) RURAL UTILITIES SERVICE, DEPARTMENT OF AGRICULTURE RURAL DEVELOPMENT Distance Learning and Telemedicine Combination Loan and Grant...

7 CFR 1703.133 - Maximum and minimum amounts.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 11 2013-01-01 2013-01-01 false Maximum and minimum amounts. 1703.133 Section 1703.133 Agriculture Regulations of the Department of Agriculture (Continued) RURAL UTILITIES SERVICE, DEPARTMENT OF AGRICULTURE RURAL DEVELOPMENT Distance Learning and Telemedicine Combination Loan and Grant...

7 CFR 1703.133 - Maximum and minimum amounts.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 7 Agriculture 11 2012-01-01 2012-01-01 false Maximum and minimum amounts. 1703.133 Section 1703.133 Agriculture Regulations of the Department of Agriculture (Continued) RURAL UTILITIES SERVICE, DEPARTMENT OF AGRICULTURE RURAL DEVELOPMENT Distance Learning and Telemedicine Combination Loan and Grant...

7 CFR 1703.133 - Maximum and minimum amounts.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 11 2014-01-01 2014-01-01 false Maximum and minimum amounts. 1703.133 Section 1703.133 Agriculture Regulations of the Department of Agriculture (Continued) RURAL UTILITIES SERVICE, DEPARTMENT OF AGRICULTURE RURAL DEVELOPMENT Distance Learning and Telemedicine Combination Loan and Grant...

Geographical diffusion of prazosin across Veterans Health Administration: Examination of regional variation in daily dosing and quality indicators among veterans with posttraumatic stress disorder.

PubMed

Abrams, Thad E; Lund, Brian C; Alexander, Bruce; Bernardy, Nancy C; Friedman, Matthew J

2015-01-01

Posttraumatic stress disorder (PTSD) is a high-priority treatment area for the Veterans Health Administration (VHA), and dissemination patterns of innovative, efficacious therapies can inform areas for potential improvement of diffusion efforts and quality prescribing. In this study, we replicated a prior examination of the period prevalence of prazosin use as a function of distance from Puget Sound, Washington, where prazosin was first tested as an effective treatment for PTSD and where prazosin use was previously shown to be much greater than in other parts of the United States. We tested the following three hypotheses related to prazosin geographic diffusion: (1) a positive geographical correlation exists between the distance from Puget Sound and the proportion of users treated according to a guideline recommended minimum therapeutic target dose (>/=6 mg/d), (2) an inverse geographic correlation exists between prazosin and benzodiazepine use, and (3) no geographical correlation exists between prazosin use and serotonin reuptake inhibitor/serotonin norepinephrine reuptake inhibitor (SSRI/SNRI) use. Among a national sample of veterans with PTSD, overall prazosin utilization increased from 5.5 to 14.8% from 2006 to 2012. During this time period, rates at the Puget Sound VHA location declined from 34.4 to 29.9%, whereas utilization rates at locations a minimum of 2,500 miles away increased from 3.0 to 12.8%. Rates of minimum target dosing fell from 42.6 to 34.6% at the Puget Sound location. In contrast, at distances of at least 2,500 miles from Puget Sound, minimum threshold dosing rates remained stable (range, 18.6 to 17.7%). No discernible association was demonstrated between SSRI/SNRI or benzodiazepine utilization and the geographic distance from Puget Sound. Minimal threshold dosing of prazosin correlated positively with increased diffusion of prazosin use, but there was still a distance diffusion gradient. Although prazosin adoption has improved, geographic differences persist in both prescribing rates and minimum target dosing. Importantly, these regional disparities appear to be limited to prazosin prescribing and are not meaningfully correlated with SSRI/SNRI and benzodiazepine use as indicators of PTSD prescribing quality.

HMM for hyperspectral spectrum representation and classification with endmember entropy vectors

NASA Astrophysics Data System (ADS)

Arabi, Samir Y. W.; Fernandes, David; Pizarro, Marco A.

2015-10-01

The Hyperspectral images due to its good spectral resolution are extensively used for classification, but its high number of bands requires a higher bandwidth in the transmission data, a higher data storage capability and a higher computational capability in processing systems. This work presents a new methodology for hyperspectral data classification that can work with a reduced number of spectral bands and achieve good results, comparable with processing methods that require all hyperspectral bands. The proposed method for hyperspectral spectra classification is based on the Hidden Markov Model (HMM) associated to each Endmember (EM) of a scene and the conditional probabilities of each EM belongs to each other EM. The EM conditional probability is transformed in EM vector entropy and those vectors are used as reference vectors for the classes in the scene. The conditional probability of a spectrum that will be classified is also transformed in a spectrum entropy vector, which is classified in a given class by the minimum ED (Euclidian Distance) among it and the EM entropy vectors. The methodology was tested with good results using AVIRIS spectra of a scene with 13 EM considering the full 209 bands and the reduced spectral bands of 128, 64 and 32. For the test area its show that can be used only 32 spectral bands instead of the original 209 bands, without significant loss in the classification process.

Chemistry of Aviation Fuels

NASA Technical Reports Server (NTRS)

Knepper, Bryan; Hwang, Soon Muk; DeWitt, Kenneth J.

2004-01-01

Minimum ignition energies of various methanol/air mixtures were measured in a temperature controlled constant volume combustion vessel using a spark ignition method with a spark gap distance of 2 mm. The minimum ignition energies decrease rapidly as the mixture composition (equivalence ratio, Phi) changes from lean to stoichiometric, reach a minimum value, and then increase rather slowly with Phi. The minimum of the minimum ignition energy (MIE) and the corresponding mixture composition were determined to be 0.137 mJ and Phi = 1.16, a slightly rich mixture. The variation of minimum ignition energy with respect to the mixture composition is explained in terms of changes in reaction chemistry.

Rail vs truck transport of biomass.

PubMed

Mahmudi, Hamed; Flynn, Peter C

2006-01-01

This study analyzes the economics of transshipping biomass from truck to train in a North American setting. Transshipment will only be economic when the cost per unit distance of a second transportation mode is less than the original mode. There is an optimum number of transshipment terminals which is related to biomass yield. Transshipment incurs incremental fixed costs, and hence there is a minimum shipping distance for rail transport above which lower costs/km offset the incremental fixed costs. For transport by dedicated unit train with an optimum number of terminals, the minimum economic rail shipping distance for straw is 170 km, and for boreal forest harvest residue wood chips is 145 km. The minimum economic shipping distance for straw exceeds the biomass draw distance for economically sized centrally located power plants, and hence the prospects for rail transport are limited to cases in which traffic congestion from truck transport would otherwise preclude project development. Ideally, wood chip transport costs would be lowered by rail transshipment for an economically sized centrally located power plant, but in a specific case in Alberta, Canada, the layout of existing rail lines precludes a centrally located plant supplied by rail, whereas a more versatile road system enables it by truck. Hence for wood chips as well as straw the economic incentive for rail transport to centrally located processing plants is limited. Rail transshipment may still be preferred in cases in which road congestion precludes truck delivery, for example as result of community objections.

Solar wind velocity and temperature in the outer heliosphere

NASA Technical Reports Server (NTRS)

Gazis, P. R.; Barnes, A.; Mihalov, J. D.; Lazarus, A. J.

1994-01-01

At the end of 1992, the Pioneer 10, Pioneer 11, and Voyager 2 spacecraft were at heliocentric distances of 56.0, 37.3, and 39.0 AU and heliographic latitudes of 3.3 deg N, 17.4 deg N, and 8.6 deg S, respectively. Pioneer 11 and Voyager 2 are at similar celestial longitudes, while Pioneer 10 is on the opposite side of the Sun. All three spacecraft have working plasma analyzers, so intercomparison of data from these spacecraft provides important information about the global character of the solar wind in the outer heliosphere. The averaged solar wind speed continued to exhibit its well-known variation with solar cycle: Even at heliocentric distances greater than 50 AU, the average speed is highest during the declining phase of the solar cycle and lowest near solar minimum. There was a strong latitudinal gradient in solar wind speed between 3 deg and 17 deg N during the last solar minimum, but this gradient has since disappeared. The solar wind temperature declined with increasing heliocentric distance out to a heliocentric distance of at least 20 AU; this decline appeared to continue at larger heliocentric distances, but temperatures in the outer heliosphere were suprisingly high. While Pioneer 10 and Voyager 2 observed comparable solar wind temperatures, the temperature at Pioneer 11 was significantly higher, which suggests the existence of a large-scale variation of temperature with heliographic longitude. There was also some suggestion that solar wind temperatures were higher near solar minimum.

33 CFR 67.05-20 - Minimum lighting requirements.

Code of Federal Regulations, 2013 CFR

2013-07-01

... for Lights § 67.05-20 Minimum lighting requirements. The obstruction lighting requirements prescribed... application for authorization to establish more lights, or lights of greater intensity than required to be visible at the distances prescribed: Provided, That the prescribed characteristics of color and flash...

33 CFR 67.05-20 - Minimum lighting requirements.

Code of Federal Regulations, 2011 CFR

2011-07-01

... for Lights § 67.05-20 Minimum lighting requirements. The obstruction lighting requirements prescribed... application for authorization to establish more lights, or lights of greater intensity than required to be visible at the distances prescribed: Provided, That the prescribed characteristics of color and flash...

33 CFR 67.05-20 - Minimum lighting requirements.

Code of Federal Regulations, 2010 CFR

2010-07-01

... for Lights § 67.05-20 Minimum lighting requirements. The obstruction lighting requirements prescribed... application for authorization to establish more lights, or lights of greater intensity than required to be visible at the distances prescribed: Provided, That the prescribed characteristics of color and flash...

33 CFR 67.05-20 - Minimum lighting requirements.

Code of Federal Regulations, 2012 CFR

2012-07-01

... for Lights § 67.05-20 Minimum lighting requirements. The obstruction lighting requirements prescribed... application for authorization to establish more lights, or lights of greater intensity than required to be visible at the distances prescribed: Provided, That the prescribed characteristics of color and flash...

33 CFR 67.05-20 - Minimum lighting requirements.

Code of Federal Regulations, 2014 CFR

2014-07-01

... for Lights § 67.05-20 Minimum lighting requirements. The obstruction lighting requirements prescribed... application for authorization to establish more lights, or lights of greater intensity than required to be visible at the distances prescribed: Provided, That the prescribed characteristics of color and flash...

7 CFR 1703.143 - Maximum and minimum amounts.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 11 2010-01-01 2010-01-01 false Maximum and minimum amounts. 1703.143 Section 1703.143 Agriculture Regulations of the Department of Agriculture (Continued) RURAL UTILITIES SERVICE, DEPARTMENT OF AGRICULTURE RURAL DEVELOPMENT Distance Learning and Telemedicine Loan Program § 1703.143...

7 CFR 1703.143 - Maximum and minimum amounts.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 7 Agriculture 11 2012-01-01 2012-01-01 false Maximum and minimum amounts. 1703.143 Section 1703.143 Agriculture Regulations of the Department of Agriculture (Continued) RURAL UTILITIES SERVICE, DEPARTMENT OF AGRICULTURE RURAL DEVELOPMENT Distance Learning and Telemedicine Loan Program § 1703.143...

7 CFR 1703.143 - Maximum and minimum amounts.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 11 2013-01-01 2013-01-01 false Maximum and minimum amounts. 1703.143 Section 1703.143 Agriculture Regulations of the Department of Agriculture (Continued) RURAL UTILITIES SERVICE, DEPARTMENT OF AGRICULTURE RURAL DEVELOPMENT Distance Learning and Telemedicine Loan Program § 1703.143...

7 CFR 1703.143 - Maximum and minimum amounts.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 11 2014-01-01 2014-01-01 false Maximum and minimum amounts. 1703.143 Section 1703.143 Agriculture Regulations of the Department of Agriculture (Continued) RURAL UTILITIES SERVICE, DEPARTMENT OF AGRICULTURE RURAL DEVELOPMENT Distance Learning and Telemedicine Loan Program § 1703.143...

7 CFR 1703.143 - Maximum and minimum amounts.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 11 2011-01-01 2011-01-01 false Maximum and minimum amounts. 1703.143 Section 1703.143 Agriculture Regulations of the Department of Agriculture (Continued) RURAL UTILITIES SERVICE, DEPARTMENT OF AGRICULTURE RURAL DEVELOPMENT Distance Learning and Telemedicine Loan Program § 1703.143...

40 CFR 257.25 - Assessment monitoring program.

Code of Federal Regulations, 2012 CFR

2012-07-01

...) Minimum distance between upgradient edge of the unit and downgradient monitoring well screen (minimum... that is likely to be without appreciable risk of deleterious effects during a lifetime. For purposes of this subpart, systemic toxicants include toxic chemicals that cause effects other than cancer or...

40 CFR 257.25 - Assessment monitoring program.

Code of Federal Regulations, 2013 CFR

2013-07-01

...) Minimum distance between upgradient edge of the unit and downgradient monitoring well screen (minimum... that is likely to be without appreciable risk of deleterious effects during a lifetime. For purposes of this subpart, systemic toxicants include toxic chemicals that cause effects other than cancer or...

40 CFR 257.25 - Assessment monitoring program.

Code of Federal Regulations, 2011 CFR

2011-07-01

...) Minimum distance between upgradient edge of the unit and downgradient monitoring well screen (minimum... that is likely to be without appreciable risk of deleterious effects during a lifetime. For purposes of this subpart, systemic toxicants include toxic chemicals that cause effects other than cancer or...

Analysis of Radiation Impact on White Mice through Radiation Dose Mapping in Medical Physics Laboratory

NASA Astrophysics Data System (ADS)

Sutikno, Madnasri; Susilo; Arya Wijayanti, Riza

2016-08-01

A study about X-ray radiation impact on the white mice through radiation dose mapping in Medical Physic Laboratory is already done. The purpose of this research is to determine the minimum distance of radiologist to X-ray instrument through treatment on the white mice. The radiation exposure doses are measured on the some points in the distance from radiation source between 30 cm up to 80 with interval of 30 cm. The impact of radiation exposure on the white mice and the effects of radiation measurement in different directions are investigated. It is founded that minimum distance of radiation worker to radiation source is 180 cm and X-ray has decreased leukocyte number and haemoglobin and has increased thrombocyte number in the blood of white mice.

Estimates of the absolute error and a scheme for an approximate solution to scheduling problems

NASA Astrophysics Data System (ADS)

Lazarev, A. A.

2009-02-01

An approach is proposed for estimating absolute errors and finding approximate solutions to classical NP-hard scheduling problems of minimizing the maximum lateness for one or many machines and makespan is minimized. The concept of a metric (distance) between instances of the problem is introduced. The idea behind the approach is, given the problem instance, to construct another instance for which an optimal or approximate solution can be found at the minimum distance from the initial instance in the metric introduced. Instead of solving the original problem (instance), a set of approximating polynomially/pseudopolynomially solvable problems (instances) are considered, an instance at the minimum distance from the given one is chosen, and the resulting schedule is then applied to the original instance.

A Modified Hopfield Neural Network Algorithm (MHNNA) Using ALOS Image for Water Quality Mapping

PubMed Central

Kzar, Ahmed Asal; Mat Jafri, Mohd Zubir; Mutter, Kussay N.; Syahreza, Saumi

2015-01-01

Decreasing water pollution is a big problem in coastal waters. Coastal health of ecosystems can be affected by high concentrations of suspended sediment. In this work, a Modified Hopfield Neural Network Algorithm (MHNNA) was used with remote sensing imagery to classify the total suspended solids (TSS) concentrations in the waters of coastal Langkawi Island, Malaysia. The adopted remote sensing image is the Advanced Land Observation Satellite (ALOS) image acquired on 18 January 2010. Our modification allows the Hopfield neural network to convert and classify color satellite images. The samples were collected from the study area simultaneously with the acquiring of satellite imagery. The sample locations were determined using a handheld global positioning system (GPS). The TSS concentration measurements were conducted in a lab and used for validation (real data), classification, and accuracy assessments. Mapping was achieved by using the MHNNA to classify the concentrations according to their reflectance values in band 1, band 2, and band 3. The TSS map was color-coded for visual interpretation. The efficiency of the proposed algorithm was investigated by dividing the validation data into two groups. The first group was used as source samples for supervisor classification via the MHNNA. The second group was used to test the MHNNA efficiency. After mapping, the locations of the second group in the produced classes were detected. Next, the correlation coefficient (R) and root mean square error (RMSE) were calculated between the two groups, according to their corresponding locations in the classes. The MHNNA exhibited a higher R (0.977) and lower RMSE (2.887). In addition, we test the MHNNA with noise, where it proves its accuracy with noisy images over a range of noise levels. All results have been compared with a minimum distance classifier (Min-Dis). Therefore, TSS mapping of polluted water in the coastal Langkawi Island, Malaysia can be performed using the adopted MHNNA with remote sensing techniques (as based on ALOS images). PMID:26729148

Neural Decoding and "Inner" Psychophysics: A Distance-to-Bound Approach for Linking Mind, Brain, and Behavior.

PubMed

Ritchie, J Brendan; Carlson, Thomas A

2016-01-01

A fundamental challenge for cognitive neuroscience is characterizing how the primitives of psychological theory are neurally implemented. Attempts to meet this challenge are a manifestation of what Fechner called "inner" psychophysics: the theory of the precise mapping between mental quantities and the brain. In his own time, inner psychophysics remained an unrealized ambition for Fechner. We suggest that, today, multivariate pattern analysis (MVPA), or neural "decoding," methods provide a promising starting point for developing an inner psychophysics. A cornerstone of these methods are simple linear classifiers applied to neural activity in high-dimensional activation spaces. We describe an approach to inner psychophysics based on the shared architecture of linear classifiers and observers under decision boundary models such as signal detection theory. Under this approach, distance from a decision boundary through activation space, as estimated by linear classifiers, can be used to predict reaction time in accordance with signal detection theory, and distance-to-bound models of reaction time. Our "neural distance-to-bound" approach is potentially quite general, and simple to implement. Furthermore, our recent work on visual object recognition suggests it is empirically viable. We believe the approach constitutes an important step along the path to an inner psychophysics that links mind, brain, and behavior.

Study of Noise-Certification Standards for Aircraft Engines. Volume 2. Procedures for Measuring Far Field Sound Pressure Levels around an Outdoor Jet-Engine Test Stand.

DTIC Science & Technology

1983-06-01

60 References ........................................................... 79 AccesSqlon For NTIS rFA&I r"!’ TAU U: .,P Dist r A. -. S iv...separate exhaust nozzles for discharge of fan and turbine exhaust flows (e.g., JT15D, TFE731 , ALF-502, CF34, JT3D, CFM56, RB.211, CF6, JT9D, and PW2037...minimum radial distance from the effective source of sound at 40 Hz should then be approxi- mately 69 m. At 60 Hz, the minimum radial distance should be

7 CFR 1703.124 - Maximum and minimum grant amounts.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 11 2010-01-01 2010-01-01 false Maximum and minimum grant amounts. 1703.124 Section 1703.124 Agriculture Regulations of the Department of Agriculture (Continued) RURAL UTILITIES SERVICE, DEPARTMENT OF AGRICULTURE RURAL DEVELOPMENT Distance Learning and Telemedicine Grant Program § 1703.124...

7 CFR 1703.124 - Maximum and minimum grant amounts.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 11 2013-01-01 2013-01-01 false Maximum and minimum grant amounts. 1703.124 Section 1703.124 Agriculture Regulations of the Department of Agriculture (Continued) RURAL UTILITIES SERVICE, DEPARTMENT OF AGRICULTURE RURAL DEVELOPMENT Distance Learning and Telemedicine Grant Program § 1703.124...

7 CFR 1703.124 - Maximum and minimum grant amounts.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 7 Agriculture 11 2012-01-01 2012-01-01 false Maximum and minimum grant amounts. 1703.124 Section 1703.124 Agriculture Regulations of the Department of Agriculture (Continued) RURAL UTILITIES SERVICE, DEPARTMENT OF AGRICULTURE RURAL DEVELOPMENT Distance Learning and Telemedicine Grant Program § 1703.124...

7 CFR 1703.124 - Maximum and minimum grant amounts.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 11 2011-01-01 2011-01-01 false Maximum and minimum grant amounts. 1703.124 Section 1703.124 Agriculture Regulations of the Department of Agriculture (Continued) RURAL UTILITIES SERVICE, DEPARTMENT OF AGRICULTURE RURAL DEVELOPMENT Distance Learning and Telemedicine Grant Program § 1703.124...

7 CFR 1703.124 - Maximum and minimum grant amounts.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 11 2014-01-01 2014-01-01 false Maximum and minimum grant amounts. 1703.124 Section 1703.124 Agriculture Regulations of the Department of Agriculture (Continued) RURAL UTILITIES SERVICE, DEPARTMENT OF AGRICULTURE RURAL DEVELOPMENT Distance Learning and Telemedicine Grant Program § 1703.124...

Nonlinear dimension reduction and clustering by Minimum Curvilinearity unfold neuropathic pain and tissue embryological classes.

PubMed

Cannistraci, Carlo Vittorio; Ravasi, Timothy; Montevecchi, Franco Maria; Ideker, Trey; Alessio, Massimo

2010-09-15

Nonlinear small datasets, which are characterized by low numbers of samples and very high numbers of measures, occur frequently in computational biology, and pose problems in their investigation. Unsupervised hybrid-two-phase (H2P) procedures-specifically dimension reduction (DR), coupled with clustering-provide valuable assistance, not only for unsupervised data classification, but also for visualization of the patterns hidden in high-dimensional feature space. 'Minimum Curvilinearity' (MC) is a principle that-for small datasets-suggests the approximation of curvilinear sample distances in the feature space by pair-wise distances over their minimum spanning tree (MST), and thus avoids the introduction of any tuning parameter. MC is used to design two novel forms of nonlinear machine learning (NML): Minimum Curvilinear embedding (MCE) for DR, and Minimum Curvilinear affinity propagation (MCAP) for clustering. Compared with several other unsupervised and supervised algorithms, MCE and MCAP, whether individually or combined in H2P, overcome the limits of classical approaches. High performance was attained in the visualization and classification of: (i) pain patients (proteomic measurements) in peripheral neuropathy; (ii) human organ tissues (genomic transcription factor measurements) on the basis of their embryological origin. MC provides a valuable framework to estimate nonlinear distances in small datasets. Its extension to large datasets is prefigured for novel NMLs. Classification of neuropathic pain by proteomic profiles offers new insights for future molecular and systems biology characterization of pain. Improvements in tissue embryological classification refine results obtained in an earlier study, and suggest a possible reinterpretation of skin attribution as mesodermal. https://sites.google.com/site/carlovittoriocannistraci/home.

Cognitive Load Theory and the Use of Worked Examples as an Instructional Strategy in Physics for Distance Learners: A Preliminary Study

ERIC Educational Resources Information Center

Saw, Kim Guan

2017-01-01

This article revisits the cognitive load theory to explore the use of worked examples to teach a selected topic in a higher level undergraduate physics course for distance learners at the School of Distance Education, Universiti Sains Malaysia. With a break of several years from receiving formal education and having only minimum science…

Comparing exposure metrics for classifying ‘dangerous heat’ in heat wave and health warning systems

PubMed Central

Zhang, Kai; Rood, Richard B.; Michailidis, George; Oswald, Evan M.; Schwartz, Joel D.; Zanobetti, Antonella; Ebi, Kristie L.; O’Neill, Marie S.

2012-01-01

Heat waves have been linked to excess mortality and morbidity, and are projected to increase in frequency and intensity with a warming climate. This study compares exposure metrics to trigger heat wave and health warning systems (HHWS), and introduces a novel multi-level hybrid clustering method to identify potential dangerously hot days. Two-level and three-level hybrid clustering analysis as well as common indices used to trigger HHWS, including spatial synoptic classification (SSC); and 90th, 95th, and 99th percentiles of minimum and relative minimum temperature (using a 10 day reference period), were calculated using a summertime weather dataset in Detroit from 1976 to 2006. The days classified as ‘hot’ with hybrid clustering analysis, SSC, minimum and relative minimum temperature methods differed by method type. SSC tended to include the days with, on average, 2.6 °C lower daily minimum temperature and 5.3 °C lower dew point than days identified by other methods. These metrics were evaluated by comparing their performance in predicting excess daily mortality. The 99th percentile of minimum temperature was generally the most predictive, followed by the three-level hybrid clustering method, the 95th percentile of minimum temperature, SSC and others. Our proposed clustering framework has more flexibility and requires less substantial meteorological prior information than the synoptic classification methods. Comparison of these metrics in predicting excess daily mortality suggests that metrics thought to better characterize physiological heat stress by considering several weather conditions simultaneously may not be the same metrics that are better at predicting heat-related mortality, which has significant implications in HHWSs. PMID:22673187

Minimum Expected Risk Estimation for Near-neighbor Classification

DTIC Science & Technology

2006-04-01

We consider the problems of class probability estimation and classification when using near-neighbor classifiers, such as k-nearest neighbors ( kNN ...estimate for weighted kNN classifiers with different prior information, for a broad class of risk functions. Theory and simulations show how significant...the difference is compared to the standard maximum likelihood weighted kNN estimates. Comparisons are made with uniform weights, symmetric weights

Non-Intrusive Impedance-Based Cable Tester

NASA Technical Reports Server (NTRS)

Medelius, Pedro J. (Inventor); Simpson, Howard J. (Inventor)

1999-01-01

A non-intrusive electrical cable tester determines the nature and location of a discontinuity in a cable through application of an oscillating signal to one end of the cable. The frequency of the oscillating signal is varied in increments until a minimum, close to zero voltage is measured at a signal injection point which is indicative of a minimum impedance at that point. The frequency of the test signal at which the minimum impedance occurs is then employed to determine the distance to the discontinuity by employing a formula which relates this distance to the signal frequency and the velocity factor of the cable. A numerically controlled oscillator is provided to generate the oscillating signal, and a microcontroller automatically controls operation of the cable tester to make the desired measurements and display the results. The device is contained in a portable housing which may be hand held to facilitate convenient use of the device in difficult to access locations.

Supervised novelty detection in brain tissue classification with an application to white matter hyperintensities

NASA Astrophysics Data System (ADS)

Kuijf, Hugo J.; Moeskops, Pim; de Vos, Bob D.; Bouvy, Willem H.; de Bresser, Jeroen; Biessels, Geert Jan; Viergever, Max A.; Vincken, Koen L.

2016-03-01

Novelty detection is concerned with identifying test data that differs from the training data of a classifier. In the case of brain MR images, pathology or imaging artefacts are examples of untrained data. In this proof-of-principle study, we measure the behaviour of a classifier during the classification of trained labels (i.e. normal brain tissue). Next, we devise a measure that distinguishes normal classifier behaviour from abnormal behavior that occurs in the case of a novelty. This will be evaluated by training a kNN classifier on normal brain tissue, applying it to images with an untrained pathology (white matter hyperintensities (WMH)), and determine if our measure is able to identify abnormal classifier behaviour at WMH locations. For our kNN classifier, behaviour is modelled as the mean, median, or q1 distance to the k nearest points. Healthy tissue was trained on 15 images; classifier behaviour was trained/tested on 5 images with leave-one-out cross-validation. For each trained class, we measure the distribution of mean/median/q1 distances to the k nearest point. Next, for each test voxel, we compute its Z-score with respect to the measured distribution of its predicted label. We consider a Z-score >=4 abnormal behaviour of the classifier, having a probability due to chance of 0.000032. Our measure identified >90% of WMH volume and also highlighted other non-trained findings. The latter being predominantly vessels, cerebral falx, brain mask errors, choroid plexus. This measure is generalizable to other classifiers and might help in detecting unexpected findings or novelties by measuring classifier behaviour.

Short Distance Standoff Raman Detection of Extra Virgin Olive Oil Adulterated with Canola and Grapeseed Oils.

PubMed

Farley, Carlton; Kassu, Aschalew; Bose, Nayana; Jackson-Davis, Armitra; Boateng, Judith; Ruffin, Paul; Sharma, Anup

2017-06-01

A short distance standoff Raman technique is demonstrated for detecting economically motivated adulteration (EMA) in extra virgin olive oil (EVOO). Using a portable Raman spectrometer operating with a 785 nm laser and a 2-in. refracting telescope, adulteration of olive oil with grapeseed oil and canola oil is detected between 1% and 100% at a minimum concentration of 2.5% from a distance of 15 cm and at a minimum concentration of 5% from a distance of 1 m. The technique involves correlating the intensity ratios of prominent Raman bands of edible oils at 1254, 1657, and 1441 cm -1 to the degree of adulteration. As a novel variation in the data analysis technique, integrated intensities over a spectral range of 100 cm -1 around the Raman line were used, making it possible to increase the sensitivity of the technique. The technique is demonstrated by detecting adulteration of EVOO with grapeseed and canola oils at 0-100%. Due to the potential of this technique for making measurements from a convenient distance, the short distance standoff Raman technique has the promise to be used for routine applications in food industry such as identifying food items and monitoring EMA at various checkpoints in the food supply chain and storage facilities.

Lazy orbits: An optimization problem on the sphere

NASA Astrophysics Data System (ADS)

Vincze, Csaba

2018-01-01

Non-transitive subgroups of the orthogonal group play an important role in the non-Euclidean geometry. If G is a closed subgroup in the orthogonal group such that the orbit of a single Euclidean unit vector does not cover the (Euclidean) unit sphere centered at the origin then there always exists a non-Euclidean Minkowski functional such that the elements of G preserve the Minkowskian length of vectors. In other words the Minkowski geometry is an alternative of the Euclidean geometry for the subgroup G. It is rich of isometries if G is "close enough" to the orthogonal group or at least to one of its transitive subgroups. The measure of non-transitivity is related to the Hausdorff distances of the orbits under the elements of G to the Euclidean sphere. Its maximum/minimum belongs to the so-called lazy/busy orbits, i.e. they are the solutions of an optimization problem on the Euclidean sphere. The extremal distances allow us to characterize the reducible/irreducible subgroups. We also formulate an upper and a lower bound for the ratio of the extremal distances. As another application of the analytic tools we introduce the rank of a closed non-transitive group G. We shall see that if G is of maximal rank then it is finite or reducible. Since the reducible and the finite subgroups form two natural prototypes of non-transitive subgroups, the rank seems to be a fundamental notion in their characterization. Closed, non-transitive groups of rank n - 1 will be also characterized. Using the general results we classify all their possible types in lower dimensional cases n = 2 , 3 and 4. Finally we present some applications of the results to the holonomy group of a metric linear connection on a connected Riemannian manifold.

[Optimization of cluster analysis based on drug resistance profiles of MRSA isolates].

PubMed

Tani, Hiroya; Kishi, Takahiko; Gotoh, Minehiro; Yamagishi, Yuka; Mikamo, Hiroshige

2015-12-01

We examined 402 methicillin-resistant Staphylococcus aureus (MRSA) strains isolated from clinical specimens in our hospital between November 19, 2010 and December 27, 2011 to evaluate the similarity between cluster analysis of drug susceptibility tests and pulsed-field gel electrophoresis (PFGE). The results showed that the 402 strains tested were classified into 27 PFGE patterns (151 subtypes of patterns). Cluster analyses of drug susceptibility tests with the cut-off distance yielding a similar classification capability showed favorable results--when the MIC method was used, and minimum inhibitory concentration (MIC) values were used directly in the method, the level of agreement with PFGE was 74.2% when 15 drugs were tested. The Unweighted Pair Group Method with Arithmetic mean (UPGMA) method was effective when the cut-off distance was 16. Using the SIR method in which susceptible (S), intermediate (I), and resistant (R) were coded as 0, 2, and 3, respectively, according to the Clinical and Laboratory Standards Institute (CLSI) criteria, the level of agreement with PFGE was 75.9% when the number of drugs tested was 17, the method used for clustering was the UPGMA, and the cut-off distance was 3.6. In addition, to assess the reproducibility of the results, 10 strains were randomly sampled from the overall test and subjected to cluster analysis. This was repeated 100 times under the same conditions. The results indicated good reproducibility of the results, with the level of agreement with PFGE showing a mean of 82.0%, standard deviation of 12.1%, and mode of 90.0% for the MIC method and a mean of 80.0%, standard deviation of 13.4%, and mode of 90.0% for the SIR method. In summary, cluster analysis for drug susceptibility tests is useful for the epidemiological analysis of MRSA.

47 CFR 73.610 - Minimum distance separations between stations.

Code of Federal Regulations, 2010 CFR

2010-10-01

... they fail to comply with the requirements specified in paragraphs (b), (c) and (d) of this section... separation. (c) Minimum allotment and station adjacent channel separations applicable to all zones: (1... pairs of channels (see § 73.603(a)). (d) In addition to the requirements of paragraphs (a), (b) and (c...

Beta Atomic Contacts: Identifying Critical Specific Contacts in Protein Binding Interfaces

PubMed Central

Liu, Qian; Kwoh, Chee Keong; Hoi, Steven C. H.

2013-01-01

Specific binding between proteins plays a crucial role in molecular functions and biological processes. Protein binding interfaces and their atomic contacts are typically defined by simple criteria, such as distance-based definitions that only use some threshold of spatial distance in previous studies. These definitions neglect the nearby atomic organization of contact atoms, and thus detect predominant contacts which are interrupted by other atoms. It is questionable whether such kinds of interrupted contacts are as important as other contacts in protein binding. To tackle this challenge, we propose a new definition called beta (β) atomic contacts. Our definition, founded on the β-skeletons in computational geometry, requires that there is no other atom in the contact spheres defined by two contact atoms; this sphere is similar to the van der Waals spheres of atoms. The statistical analysis on a large dataset shows that β contacts are only a small fraction of conventional distance-based contacts. To empirically quantify the importance of β contacts, we design βACV, an SVM classifier with β contacts as input, to classify homodimers from crystal packing. We found that our βACV is able to achieve the state-of-the-art classification performance superior to SVM classifiers with distance-based contacts as input. Our βACV also outperforms several existing methods when being evaluated on several datasets in previous works. The promising empirical performance suggests that β contacts can truly identify critical specific contacts in protein binding interfaces. β contacts thus provide a new model for more precise description of atomic organization in protein quaternary structures than distance-based contacts. PMID:23630569

Advances in Distance-Based Hole Cuts on Overset Grids

NASA Technical Reports Server (NTRS)

Chan, William M.; Pandya, Shishir A.

2015-01-01

An automatic and efficient method to determine appropriate hole cuts based on distances to the wall and donor stencil maps for overset grids is presented. A new robust procedure is developed to create a closed surface triangulation representation of each geometric component for accurate determination of the minimum hole. Hole boundaries are then displaced away from the tight grid-spacing regions near solid walls to allow grid overlap to occur away from the walls where cell sizes from neighboring grids are more comparable. The placement of hole boundaries is efficiently determined using a mid-distance rule and Cartesian maps of potential valid donor stencils with minimal user input. Application of this procedure typically results in a spatially-variable offset of the hole boundaries from the minimum hole with only a small number of orphan points remaining. Test cases on complex configurations are presented to demonstrate the new scheme.

Modeling the long-term evolution of space debris

DOEpatents

Nikolaev, Sergei; De Vries, Willem H.; Henderson, John R.; Horsley, Matthew A.; Jiang, Ming; Levatin, Joanne L.; Olivier, Scot S.; Pertica, Alexander J.; Phillion, Donald W.; Springer, Harry K.

2017-03-07

A space object modeling system that models the evolution of space debris is provided. The modeling system simulates interaction of space objects at simulation times throughout a simulation period. The modeling system includes a propagator that calculates the position of each object at each simulation time based on orbital parameters. The modeling system also includes a collision detector that, for each pair of objects at each simulation time, performs a collision analysis. When the distance between objects satisfies a conjunction criterion, the modeling system calculates a local minimum distance between the pair of objects based on a curve fitting to identify a time of closest approach at the simulation times and calculating the position of the objects at the identified time. When the local minimum distance satisfies a collision criterion, the modeling system models the debris created by the collision of the pair of objects.

An effective visualization technique for depth perception in augmented reality-based surgical navigation.

PubMed

Choi, Hyunseok; Cho, Byunghyun; Masamune, Ken; Hashizume, Makoto; Hong, Jaesung

2016-03-01

Depth perception is a major issue in augmented reality (AR)-based surgical navigation. We propose an AR and virtual reality (VR) switchable visualization system with distance information, and evaluate its performance in a surgical navigation set-up. To improve depth perception, seamless switching from AR to VR was implemented. In addition, the minimum distance between the tip of the surgical tool and the nearest organ was provided in real time. To evaluate the proposed techniques, five physicians and 20 non-medical volunteers participated in experiments. Targeting error, time taken, and numbers of collisions were measured in simulation experiments. There was a statistically significant difference between a simple AR technique and the proposed technique. We confirmed that depth perception in AR could be improved by the proposed seamless switching between AR and VR, and providing an indication of the minimum distance also facilitated the surgical tasks. Copyright © 2015 John Wiley & Sons, Ltd.

Classifier utility modeling and analysis of hypersonic inlet start/unstart considering training data costs

NASA Astrophysics Data System (ADS)

Chang, Juntao; Hu, Qinghua; Yu, Daren; Bao, Wen

2011-11-01

Start/unstart detection is one of the most important issues of hypersonic inlets and is also the foundation of protection control of scramjet. The inlet start/unstart detection can be attributed to a standard pattern classification problem, and the training sample costs have to be considered for the classifier modeling as the CFD numerical simulations and wind tunnel experiments of hypersonic inlets both cost time and money. To solve this problem, the CFD simulation of inlet is studied at first step, and the simulation results could provide the training data for pattern classification of hypersonic inlet start/unstart. Then the classifier modeling technology and maximum classifier utility theories are introduced to analyze the effect of training data cost on classifier utility. In conclusion, it is useful to introduce support vector machine algorithms to acquire the classifier model of hypersonic inlet start/unstart, and the minimum total cost of hypersonic inlet start/unstart classifier can be obtained by the maximum classifier utility theories.

Bayes classification of terrain cover using normalized polarimetric data

NASA Technical Reports Server (NTRS)

Yueh, H. A.; Swartz, A. A.; Kong, J. A.; Shin, R. T.; Novak, L. M.

1988-01-01

The normalized polarimetric classifier (NPC) which uses only the relative magnitudes and phases of the polarimetric data is proposed for discrimination of terrain elements. The probability density functions (PDFs) of polarimetric data are assumed to have a complex Gaussian distribution, and the marginal PDF of the normalized polarimetric data is derived by adopting the Euclidean norm as the normalization function. The general form of the distance measure for the NPC is also obtained. It is demonstrated that for polarimetric data with an arbitrary PDF, the distance measure of NPC will be independent of the normalization function selected even when the classifier is mistrained. A complex Gaussian distribution is assumed for the polarimetric data consisting of grass and tree regions. The probability of error for the NPC is compared with those of several other single-feature classifiers. The classification error of NPCs is shown to be independent of the normalization function.

Influence of the geomembrane on time-lapse ERT measurements for leachate injection monitoring.

PubMed

Audebert, M; Clément, R; Grossin-Debattista, J; Günther, T; Touze-Foltz, N; Moreau, S

2014-04-01

Leachate recirculation is a key process in the operation of municipal waste landfills as bioreactors. To quantify the water content and to evaluate the leachate injection system, in situ methods are required to obtain spatially distributed information, usually electrical resistivity tomography (ERT). However, this method can present false variations in the observations due to several parameters. This study investigates the impact of the geomembrane on ERT measurements. Indeed, the geomembrane tends to be ignored in the inversion process in most previously conducted studies. The presence of the geomembrane can change the boundary conditions of the inversion models, which have classically infinite boundary conditions. Using a numerical modelling approach, the authors demonstrate that a minimum distance is required between the electrode line and the geomembrane to satisfy the good conditions of use of the classical inversion tools. This distance is a function of the electrode line length (i.e. of the unit electrode spacing) used, the array type and the orientation of the electrode line. Moreover, this study shows that if this criterion on the minimum distance is not satisfied, it is possible to significantly improve the inversion process by introducing the complex geometry and the geomembrane location into the inversion tools. These results are finally validated on a field data set gathered on a small municipal solid waste landfill cell where this minimum distance criterion cannot be satisfied. Copyright © 2014 Elsevier Ltd. All rights reserved.

Classification of resistance to passive motion using minimum probability of error criterion.

PubMed

Chan, H C; Manry, M T; Kondraske, G V

1987-01-01

Neurologists diagnose many muscular and nerve disorders by classifying the resistance to passive motion of patients' limbs. Over the past several years, a computer-based instrument has been developed for automated measurement and parameterization of this resistance. In the device, a voluntarily relaxed lower extremity is moved at constant velocity by a motorized driver. The torque exerted on the extremity by the machine is sampled, along with the angle of the extremity. In this paper a computerized technique is described for classifying a patient's condition as 'Normal' or 'Parkinson disease' (rigidity), from the torque versus angle curve for the knee joint. A Legendre polynomial, fit to the curve, is used to calculate a set of eight normally distributed features of the curve. The minimum probability of error approach is used to classify the curve as being from a normal or Parkinson disease patient. Data collected from 44 different subjects was processes and the results were compared with an independent physician's subjective assessment of rigidity. There is agreement in better than 95% of the cases, when all of the features are used.

27 CFR 555.218 - Table of distances for storage of explosive materials.

Code of Federal Regulations, 2010 CFR

2010-04-01

... with traffic volume of more than 3,000 vehicles/day Barricaded Unbarricaded Separation of magazines... explosive materials are defined in § 555.11. (2) When two or more storage magazines are located on the same property, each magazine must comply with the minimum distances specified from inhabited buildings, railways...

14 CFR 91.177 - Minimum altitudes for IFR operations.

Code of Federal Regulations, 2010 CFR

2010-01-01

..., an altitude of 2,000 feet above the highest obstacle within a horizontal distance of 4 nautical miles from the course to be flown; or (ii) In any other case, an altitude of 1,000 feet above the highest... 14 Aeronautics and Space 2 2010-01-01 2010-01-01 false Minimum altitudes for IFR operations. 91...

A Method of Spatial Mapping and Reclassification for High-Spatial-Resolution Remote Sensing Image Classification

PubMed Central

Wang, Guizhou; Liu, Jianbo; He, Guojin

2013-01-01

This paper presents a new classification method for high-spatial-resolution remote sensing images based on a strategic mechanism of spatial mapping and reclassification. The proposed method includes four steps. First, the multispectral image is classified by a traditional pixel-based classification method (support vector machine). Second, the panchromatic image is subdivided by watershed segmentation. Third, the pixel-based multispectral image classification result is mapped to the panchromatic segmentation result based on a spatial mapping mechanism and the area dominant principle. During the mapping process, an area proportion threshold is set, and the regional property is defined as unclassified if the maximum area proportion does not surpass the threshold. Finally, unclassified regions are reclassified based on spectral information using the minimum distance to mean algorithm. Experimental results show that the classification method for high-spatial-resolution remote sensing images based on the spatial mapping mechanism and reclassification strategy can make use of both panchromatic and multispectral information, integrate the pixel- and object-based classification methods, and improve classification accuracy. PMID:24453808

Detection of cracks in shafts with the Approximated Entropy algorithm

NASA Astrophysics Data System (ADS)

Sampaio, Diego Luchesi; Nicoletti, Rodrigo

2016-05-01

The Approximate Entropy is a statistical calculus used primarily in the fields of Medicine, Biology, and Telecommunication for classifying and identifying complex signal data. In this work, an Approximate Entropy algorithm is used to detect cracks in a rotating shaft. The signals of the cracked shaft are obtained from numerical simulations of a de Laval rotor with breathing cracks modelled by the Fracture Mechanics. In this case, one analysed the vertical displacements of the rotor during run-up transients. The results show the feasibility of detecting cracks from 5% depth, irrespective of the unbalance of the rotating system and crack orientation in the shaft. The results also show that the algorithm can differentiate the occurrence of crack only, misalignment only, and crack + misalignment in the system. However, the algorithm is sensitive to intrinsic parameters p (number of data points in a sample vector) and f (fraction of the standard deviation that defines the minimum distance between two sample vectors), and good results are only obtained by appropriately choosing their values according to the sampling rate of the signal.

Detecting epileptic seizure with different feature extracting strategies using robust machine learning classification techniques by applying advance parameter optimization approach.

PubMed

Hussain, Lal

2018-06-01

Epilepsy is a neurological disorder produced due to abnormal excitability of neurons in the brain. The research reveals that brain activity is monitored through electroencephalogram (EEG) of patients suffered from seizure to detect the epileptic seizure. The performance of EEG detection based epilepsy require feature extracting strategies. In this research, we have extracted varying features extracting strategies based on time and frequency domain characteristics, nonlinear, wavelet based entropy and few statistical features. A deeper study was undertaken using novel machine learning classifiers by considering multiple factors. The support vector machine kernels are evaluated based on multiclass kernel and box constraint level. Likewise, for K-nearest neighbors (KNN), we computed the different distance metrics, Neighbor weights and Neighbors. Similarly, the decision trees we tuned the paramours based on maximum splits and split criteria and ensemble classifiers are evaluated based on different ensemble methods and learning rate. For training/testing tenfold Cross validation was employed and performance was evaluated in form of TPR, NPR, PPV, accuracy and AUC. In this research, a deeper analysis approach was performed using diverse features extracting strategies using robust machine learning classifiers with more advanced optimal options. Support Vector Machine linear kernel and KNN with City block distance metric give the overall highest accuracy of 99.5% which was higher than using the default parameters for these classifiers. Moreover, highest separation (AUC = 0.9991, 0.9990) were obtained at different kernel scales using SVM. Additionally, the K-nearest neighbors with inverse squared distance weight give higher performance at different Neighbors. Moreover, to distinguish the postictal heart rate oscillations from epileptic ictal subjects, and highest performance of 100% was obtained using different machine learning classifiers.

Clustering of financial time series

NASA Astrophysics Data System (ADS)

D'Urso, Pierpaolo; Cappelli, Carmela; Di Lallo, Dario; Massari, Riccardo

2013-05-01

This paper addresses the topic of classifying financial time series in a fuzzy framework proposing two fuzzy clustering models both based on GARCH models. In general clustering of financial time series, due to their peculiar features, needs the definition of suitable distance measures. At this aim, the first fuzzy clustering model exploits the autoregressive representation of GARCH models and employs, in the framework of a partitioning around medoids algorithm, the classical autoregressive metric. The second fuzzy clustering model, also based on partitioning around medoids algorithm, uses the Caiado distance, a Mahalanobis-like distance, based on estimated GARCH parameters and covariances that takes into account the information about the volatility structure of time series. In order to illustrate the merits of the proposed fuzzy approaches an application to the problem of classifying 29 time series of Euro exchange rates against international currencies is presented and discussed, also comparing the fuzzy models with their crisp version.

What Is the Optimal Minimum Penetration Depth for "All-Inside" Meniscal Repairs?

PubMed

McCulloch, Patrick C; Jones, Hugh L; Lue, Jeffrey; Parekh, Jesal N; Noble, Philip C

2016-08-01

To identify desired minimum depth setting for safe, effective placement of the all-inside meniscal suture anchors. Using 16 cadaveric knees and standard arthroscopic techniques, 3-dimensional surfaces of the meniscocapsular junction and posterior capsule were digitized. Using standard anteromedial and anterolateral portals, the distance from the meniscocapsular junction to the posterior capsule outer wall was measured for 3 locations along the posterior half of medial and lateral menisci. Multiple all-inside meniscal repairs were performed on 7 knees to determine an alternate measure of capsular thickness (X2) and compared with the digitized results. In the digitized group, the distance (X1) from the capsular junction to the posterior capsular wall was averaged in both menisci for 3 regions using anteromedial and anterolateral portals. Mean distances of 6.4 to 8.8 mm were found for the lateral meniscus and 6.5 to 9.1 mm for the medial meniscus. The actual penetration depth was determined in the repair group and labeled X2. It showed a similar pattern to the variation seen in X1 by region, although it exceeded predicted distances an average 1.7 mm in the medial and 1.5 mm in the lateral meniscus owing to visible deformation of the capsule as it pierced. Capsular thickness during arthroscopic repair measures approximately 6 to 9 mm (X1), with 1.5 to 2 mm additional depth needed to ensure penetration rather than bulging of the posterior capsule (X2), resulting in 8 to 10 mm minimum penetration depth range. Surgeons can add desired distance away from the meniscocapsular junction (L) at device implantation, finding optimal minimal setting for penetration depth (X2 + L), which for most repairable tears may be as short as 8 mm and not likely to be greater than 16 mm. Minimum depth setting for optimal placement of all-inside meniscal suture anchors when performing all-inside repair of the medial or lateral meniscus reduces risk of harming adjacent structures secondary to overpenetration and underpenetration of the posterior capsule. Copyright © 2016 Arthroscopy Association of North America. Published by Elsevier Inc. All rights reserved.

Spatial analyses for nonoverlapping objects with size variations and their application to coral communities.

PubMed

Muko, Soyoka; Shimatani, Ichiro K; Nozawa, Yoko

2014-07-01

Spatial distributions of individuals are conventionally analysed by representing objects as dimensionless points, in which spatial statistics are based on centre-to-centre distances. However, if organisms expand without overlapping and show size variations, such as is the case for encrusting corals, interobject spacing is crucial for spatial associations where interactions occur. We introduced new pairwise statistics using minimum distances between objects and demonstrated their utility when examining encrusting coral community data. We also calculated the conventional point process statistics and the grid-based statistics to clarify the advantages and limitations of each spatial statistical method. For simplicity, coral colonies were approximated by disks in these demonstrations. Focusing on short-distance effects, the use of minimum distances revealed that almost all coral genera were aggregated at a scale of 1-25 cm. However, when fragmented colonies (ramets) were treated as a genet, a genet-level analysis indicated weak or no aggregation, suggesting that most corals were randomly distributed and that fragmentation was the primary cause of colony aggregations. In contrast, point process statistics showed larger aggregation scales, presumably because centre-to-centre distances included both intercolony spacing and colony sizes (radius). The grid-based statistics were able to quantify the patch (aggregation) scale of colonies, but the scale was strongly affected by the colony size. Our approach quantitatively showed repulsive effects between an aggressive genus and a competitively weak genus, while the grid-based statistics (covariance function) also showed repulsion although the spatial scale indicated from the statistics was not directly interpretable in terms of ecological meaning. The use of minimum distances together with previously proposed spatial statistics helped us to extend our understanding of the spatial patterns of nonoverlapping objects that vary in size and the associated specific scales. © 2013 The Authors. Journal of Animal Ecology © 2013 British Ecological Society.

[Minimum Standards for the Spatial Accessibility of Primary Care: A Systematic Review].

PubMed

Voigtländer, S; Deiters, T

2015-12-01

Regional disparities of access to primary care are substantial in Germany, especially in terms of spatial accessibility. However, there is no legally or generally binding minimum standard for the spatial accessibility effort that is still acceptable. Our objective is to analyse existing minimum standards, the methods used as well as their empirical basis. A systematic literature review was undertaken of publications regarding minimum standards for the spatial accessibility of primary care based on a title word and keyword search using PubMed, SSCI/Web of Science, EMBASE and Cochrane Library. 8 minimum standards from the USA, Germany and Austria could be identified. All of them specify the acceptable spatial accessibility effort in terms of travel time; almost half include also distance(s). The travel time maximum, which is acceptable, is 30 min and it tends to be lower in urban areas. Primary care is, according to the identified minimum standards, part of the local area (Nahbereich) of so-called central places (Zentrale Orte) providing basic goods and services. The consideration of means of transport, e. g. public transport, is heterogeneous. The standards are based on empirical studies, consultation with service providers, practical experiences, and regional planning/central place theory as well as on legal or political regulations. The identified minimum standards provide important insights into the effort that is still acceptable regarding spatial accessibility, i. e. travel time, distance and means of transport. It seems reasonable to complement the current planning system for outpatient care, which is based on provider-to-population ratios, by a gravity-model method to identify places as well as populations with insufficient spatial accessibility. Due to a lack of a common minimum standard we propose - subject to further discussion - to begin with a threshold based on the spatial accessibility limit of the local area, i. e. 30 min to the next primary care provider for at least 90% of the regional population. The exceeding of the threshold would necessitate a discussion of a health care deficit and in line with this a potential need for intervention, e. g. in terms of alternative forms of health care provision. © Georg Thieme Verlag KG Stuttgart · New York.

First DNA Barcode Reference Library for the Identification of South American Freshwater Fish from the Lower Paraná River

PubMed Central

Brancolini, Florencia; del Pazo, Felipe; Posner, Victoria Maria; Grimberg, Alexis; Arranz, Silvia Eda

2016-01-01

Valid fish species identification is essential for biodiversity conservation and fisheries management. Here, we provide a sequence reference library based on mitochondrial cytochrome c oxidase subunit I for a valid identification of 79 freshwater fish species from the Lower Paraná River. Neighbour-joining analysis based on K2P genetic distances formed non-overlapping clusters for almost all species with a ≥99% bootstrap support each. Identification was successful for 97.8% of species as the minimum genetic distance to the nearest neighbour exceeded the maximum intraspecific distance in all these cases. A barcoding gap of 2.5% was apparent for the whole data set with the exception of four cases. Within-species distances ranged from 0.00% to 7.59%, while interspecific distances varied between 4.06% and 19.98%, without considering Odontesthes species with a minimum genetic distance of 0%. Sequence library validation was performed by applying BOLDs BIN analysis tool, Poisson Tree Processes model and Automatic Barcode Gap Discovery, along with a reliable taxonomic assignment by experts. Exhaustive revision of vouchers was performed when a conflicting assignment was detected after sequence analysis and BIN discordance evaluation. Thus, the sequence library presented here can be confidently used as a benchmark for identification of half of the fish species recorded for the Lower Paraná River. PMID:27442116

Qualitative Research in Distance Education: An Analysis of Journal Literature 2005-2012

ERIC Educational Resources Information Center

Hauser, Laura

2013-01-01

This review study examines the current research literature in distance education for the years 2005 to 2012. The author found 382 research articles published during that time in four prominent peer-reviewed research journals. The articles were classified and coded as quantitative, qualitative, or mixed methods. Further analysis found another…

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.

Relation between inflammables and ignition sources in aircraft environments

NASA Technical Reports Server (NTRS)

Scull, Wilfred E

1951-01-01

A literature survey was conducted to determine the relation between aircraft ignition sources and inflammables. Available literature applicable to the problem of aircraft fire hazards is analyzed and discussed. Data pertaining to the effect of many variables on ignition temperatures, minimum ignition pressures, minimum spark-ignition energies of inflammables, quenching distances of electrode configurations, and size of openings through which flame will not propagate are presented and discussed. Ignition temperatures and limits of inflammability of gasoline in air in different test environments, and the minimum ignition pressures and minimum size of opening for flame propagation in gasoline-air mixtures are included; inerting of gasoline-air mixtures is discussed.

Space availability in confined sheep during pregnancy, effects in movement patterns and use of space.

PubMed

Averós, Xavier; Lorea, Areta; Beltrán de Heredia, Ignacia; Arranz, Josune; Ruiz, Roberto; Estevez, Inma

2014-01-01

Space availability is essential to grant the welfare of animals. To determine the effect of space availability on movement and space use in pregnant ewes (Ovis aries), 54 individuals were studied during the last 11 weeks of gestation. Three treatments were tested (1, 2, and 3 m2/ewe; 6 ewes/group). Ewes' positions were collected for 15 minutes using continuous scan samplings two days/week. Total and net distance, net/total distance ratio, maximum and minimum step length, movement activity, angular dispersion, nearest, furthest and mean neighbour distance, peripheral location ratio, and corrected peripheral location ratio were calculated. Restriction in space availability resulted in smaller total travelled distance, net to total distance ratio, maximum step length, and angular dispersion but higher movement activity at 1 m2/ewe as compared to 2 and 3 m2/ewe (P<0.01). On the other hand, nearest and furthest neighbour distances increased from 1 to 3 m2/ewe (P<0.001). Largest total distance, maximum and minimum step length, and movement activity, as well as lowest net/total distance ratio and angular dispersion were observed during the first weeks (P<0.05) while inter-individual distances increased through gestation. Results indicate that movement patterns and space use in ewes were clearly restricted by limitations of space availability to 1 m2/ewe. This reflected in shorter, more sinuous trajectories composed of shorter steps, lower inter-individual distances and higher movement activity potentially linked with higher restlessness levels. On the contrary, differences between 2 and 3 m2/ewe, for most variables indicate that increasing space availability from 2 to 3 m2/ewe would appear to have limited benefits, reflected mostly in a further increment in the inter-individual distances among group members. No major variations in spatial requirements were detected through gestation, except for slight increments in inter-individual distances and an initial adaptation period, with ewes being restless and highly motivated to explore their new environment.

A Classroom Note on: The Average Distance in an Ellipse

ERIC Educational Resources Information Center

Gordon, Sheldon P.

2011-01-01

This article presents an applied calculus exercise that can be easily shared with students. One of Kepler's greatest discoveries was the fact that the planets move in elliptic orbits with the sun at one focus. Astronomers characterize the orbits of particular planets by their minimum and maximum distances to the sun, known respectively as the…

[Home health resource utilization measures using a case-mix adjustor model].

PubMed

You, Sun-Ju; Chang, Hyun-Sook

2005-08-01

The purpose of this study was to measure home health resource utilization using a Case-Mix Adjustor Model developed in the U.S. The subjects of this study were 484 patients who had received home health care more than 4 visits during a 60-day episode at 31 home health care institutions. Data on the 484 patients had to be merged onto a 60-day payment segment. Based on the results, the researcher classified home health resource groups (HHRG). The subjects were classified into 34 HHRGs in Korea. Home health resource utilization according to clinical severity was in order of Minimum (C0) < 'Low (C1) < 'Moderate (C2) < 'High (C3), according to dependency in daily activities was in order of Minimum (F0) < 'High (F3) < 'Medium (F2) < 'Low (F1) < 'Maximum (F4). Resource utilization by HHRGs was the highest 564,735 won in group C0F0S2 (clinical severity minimum, dependency in daily activity minimum, service utilization moderate), and the lowest 97,000 won in group C2F3S1, so the former was 5.82 times higher than the latter. Resource utilization in home health care has become an issue of concern due to rising costs for home health care. The results suggest the need for more analytical attention on the utilization and expenditures for home care using a Case-Mix Adjustor Model.

Egg embryo development detection with hyperspectral imaging

NASA Astrophysics Data System (ADS)

Lawrence, Kurt C.; Smith, Douglas P.; Windham, William R.; Heitschmidt, Gerald W.; Park, Bosoon

2006-10-01

In the U. S. egg industry, anywhere from 130 million to over one billion infertile eggs are incubated each year. Some of these infertile eggs explode in the hatching cabinet and can potentially spread molds or bacteria to all the eggs in the cabinet. A method to detect the embryo development of incubated eggs was developed. Twelve brown-shell hatching eggs from two replicates (n=24) were incubated and imaged to identify embryo development. A hyperspectral imaging system was used to collect transmission images from 420 to 840 nm of brown-shell eggs positioned with the air cell vertical and normal to the camera lens. Raw transmission images from about 400 to 900 nm were collected for every egg on days 0, 1, 2, and 3 of incubation. A total of 96 images were collected and eggs were broken out on day 6 to determine fertility. After breakout, all eggs were found to be fertile. Therefore, this paper presents results for egg embryo development, not fertility. The original hyperspectral data and spectral means for each egg were both used to create embryo development models. With the hyperspectral data range reduced to about 500 to 700 nm, a minimum noise fraction transformation was used, along with a Mahalanobis Distance classification model, to predict development. Days 2 and 3 were all correctly classified (100%), while day 0 and day 1 were classified at 95.8% and 91.7%, respectively. Alternatively, the mean spectra from each egg were used to develop a partial least squares regression (PLSR) model. First, a PLSR model was developed with all eggs and all days. The data were multiplicative scatter corrected, spectrally smoothed, and the wavelength range was reduced to 539 - 770 nm. With a one-out cross validation, all eggs for all days were correctly classified (100%). Second, a PLSR model was developed with data from day 0 and day 3, and the model was validated with data from day 1 and 2. For day 1, 22 of 24 eggs were correctly classified (91.7%) and for day 2, all eggs were correctly classified (100%). Although the results are based on relatively small sample sizes, they are encouraging. However, larger sample sizes, from multiple flocks, will be needed to fully validate and verify these models. Additionally, future experiments must also include non-fertile eggs so the fertile / non-fertile effect can be determined.

Combination of minimum enclosing balls classifier with SVM in coal-rock recognition.

PubMed

Song, QingJun; Jiang, HaiYan; Song, Qinghui; Zhao, XieGuang; Wu, Xiaoxuan

2017-01-01

Top-coal caving technology is a productive and efficient method in modern mechanized coal mining, the study of coal-rock recognition is key to realizing automation in comprehensive mechanized coal mining. In this paper we propose a new discriminant analysis framework for coal-rock recognition. In the framework, a data acquisition model with vibration and acoustic signals is designed and the caving dataset with 10 feature variables and three classes is got. And the perfect combination of feature variables can be automatically decided by using the multi-class F-score (MF-Score) feature selection. In terms of nonlinear mapping in real-world optimization problem, an effective minimum enclosing ball (MEB) algorithm plus Support vector machine (SVM) is proposed for rapid detection of coal-rock in the caving process. In particular, we illustrate how to construct MEB-SVM classifier in coal-rock recognition which exhibit inherently complex distribution data. The proposed method is examined on UCI data sets and the caving dataset, and compared with some new excellent SVM classifiers. We conduct experiments with accuracy and Friedman test for comparison of more classifiers over multiple on the UCI data sets. Experimental results demonstrate that the proposed algorithm has good robustness and generalization ability. The results of experiments on the caving dataset show the better performance which leads to a promising feature selection and multi-class recognition in coal-rock recognition.

Combination of minimum enclosing balls classifier with SVM in coal-rock recognition

PubMed Central

Song, QingJun; Jiang, HaiYan; Song, Qinghui; Zhao, XieGuang; Wu, Xiaoxuan

2017-01-01

Top-coal caving technology is a productive and efficient method in modern mechanized coal mining, the study of coal-rock recognition is key to realizing automation in comprehensive mechanized coal mining. In this paper we propose a new discriminant analysis framework for coal-rock recognition. In the framework, a data acquisition model with vibration and acoustic signals is designed and the caving dataset with 10 feature variables and three classes is got. And the perfect combination of feature variables can be automatically decided by using the multi-class F-score (MF-Score) feature selection. In terms of nonlinear mapping in real-world optimization problem, an effective minimum enclosing ball (MEB) algorithm plus Support vector machine (SVM) is proposed for rapid detection of coal-rock in the caving process. In particular, we illustrate how to construct MEB-SVM classifier in coal-rock recognition which exhibit inherently complex distribution data. The proposed method is examined on UCI data sets and the caving dataset, and compared with some new excellent SVM classifiers. We conduct experiments with accuracy and Friedman test for comparison of more classifiers over multiple on the UCI data sets. Experimental results demonstrate that the proposed algorithm has good robustness and generalization ability. The results of experiments on the caving dataset show the better performance which leads to a promising feature selection and multi-class recognition in coal-rock recognition. PMID:28937987

Combating speckle in SAR images - Vector filtering and sequential classification based on a multiplicative noise model

NASA Technical Reports Server (NTRS)

Lin, Qian; Allebach, Jan P.

1990-01-01

An adaptive vector linear minimum mean-squared error (LMMSE) filter for multichannel images with multiplicative noise is presented. It is shown theoretically that the mean-squared error in the filter output is reduced by making use of the correlation between image bands. The vector and conventional scalar LMMSE filters are applied to a three-band SIR-B SAR, and their performance is compared. Based on a mutliplicative noise model, the per-pel maximum likelihood classifier was derived. The authors extend this to the design of sequential and robust classifiers. These classifiers are also applied to the three-band SIR-B SAR image.

Connecticut Proposes New Legislation Designed To Enhance and Increase Interactive Distance Learning for Telephone and CATV Technologies.

ERIC Educational Resources Information Center

Pietras, Jesse John

Connecticut has proposed legislation to augment the remote education infrastructure which includes public libraries, public schools, and institutions of higher learning. The purpose of one bill is to explore the possibilities of transmitting interactive distance education to all schools intrastate and to classify public libraries at a cheaper…

Theory and Practice in the Teaching of Composition: Processing, Distancing, and Modeling.

ERIC Educational Resources Information Center

Myers, Miles, Ed.; Gray, James, Ed.

Intended to show teachers how their approaches to the teaching of writing reflect a particular area of research and to show researchers how the intuitions of teachers reflect research findings, the articles in this book are classified according to three approaches to writing: processing, distancing, and modeling. After an introductory essay that…

Planar Steering of a Single Ferrofluid Drop by Optimal Minimum Power Dynamic Feedback Control of Four Electromagnets at a Distance

PubMed Central

Probst, R.; Lin, J.; Komaee, A.; Nacev, A.; Cummins, Z.

2010-01-01

Any single permanent or electro magnet will always attract a magnetic fluid. For this reason it is difficult to precisely position and manipulate ferrofluid at a distance from magnets. We develop and experimentally demonstrate optimal (minimum electrical power) 2-dimensional manipulation of a single droplet of ferrofluid by feedback control of 4 external electromagnets. The control algorithm we have developed takes into account, and is explicitly designed for, the nonlinear (fast decay in space, quadratic in magnet strength) nature of how the magnets actuate the ferrofluid, and it also corrects for electro-magnet charging time delays. With this control, we show that dynamic actuation of electro-magnets held outside a domain can be used to position a droplet of ferrofluid to any desired location and steer it along any desired path within that domain – an example of precision control of a ferrofluid by magnets acting at a distance. PMID:21218157

Prevalence of alveolar bone loss in healthy children treated at private pediatric dentistry clinics

PubMed Central

GUIMARÃES, Maria do Carmo Machado; de ARAÚJO, Valéria Martins; AVENA, Márcia Raquel; DUARTE, Daniel Rocha da Silva; FREITAS, Francisco Valter

2010-01-01

Objectives The purpose of this study was to evaluate the prevalence of alveolar bone loss (BL) in healthy children treated at private pediatric dentistry clinics in Brasília, Brazil. Material and Methods The research included 7,436 sites present in 885 radiographs from 450 children. The BL prevalence was estimated by measuring the distance from the cementoenamel junction (CEJ) to alveolar bone crest (ABC). Data were divided in groups: (I) No BL: distance from CEJ to ABC is ≤2 mm; (II) questionable BL (QBL): distance from CEJ to ABC is >2 and <3 mm; (III) definite BL (DBL): distance from CEJ to ABC ≥3 mm. Data were treated by the chi-square nonparametric test and Fisher's exact test (p<0.05). Results Among males, 89.31% were classified in group I, 9.82% were classified in group II and 0.85% in group III. Among females, 93.05%, 6.48% and 0.46% patients were classified in Group I, II and III, respectively. The differences between genders were not statistically significant (Chi-square test, p = 0.375). Group composition according to patients’ age showed that 91.11% of individuals were classified as group I, 8.22% in group II and 0.67% in group III. The differences among the age ranges were not statistically significant (Chi-square test, p = 0.418). The mesial and distal sites showed a higher prevalence of BL in the jaw, QBL (89.80%) and DBL (79.40%), and no significant difference was observed in the distribution of QBL (Fisher’s exact test p = 0.311) and DBL (Fisher’s exact test p = 0.672) in the dental arches. The distal sites exhibited higher prevalence of both QBL (77.56%) and DBL (58.82%). Conclusions The periodontal status of children should never be underestimated because BL occurs even in healthy populations, although in a lower frequency. PMID:20857009

Prevalence of alveolar bone loss in healthy children treated at private pediatric dentistry clinics.

PubMed

Guimarães, Maria do Carmo Machado; de Araújo, Valéria Martins; Avena, Márcia Raquel; Duarte, Daniel Rocha da Silva; Freitas, Francisco Valter

2010-01-01

The purpose of this study was to evaluate the prevalence of alveolar bone loss (BL) in healthy children treated at private pediatric dentistry clinics in Brasília, Brazil. The research included 7,436 sites present in 885 radiographs from 450 children. The BL prevalence was estimated by measuring the distance from the cementoenamel junction (CEJ) to alveolar bone crest (ABC). Data were divided in groups: (I) No BL: distance from CEJ to ABC is <2 mm; (II) questionable BL (QBL): distance from CEJ to ABC is >2 and <3 mm; (III) definite BL (DBL): distance from CEJ to ABC >3 mm. Data were treated by the chi-square nonparametric test and Fisher's exact test (p<0.05). Among males, 89.31% were classified in group I, 9.82% were classified in group II and 0.85% in group III. Among females, 93.05%, 6.48% and 0.46% patients were classified in Group I, II and III, respectively. The differences between genders were not statistically significant (Chi-square test, p = 0.375). Group composition according to patients' age showed that 91.11% of individuals were classified as group I, 8.22% in group II and 0.67% in group III. The differences among the age ranges were not statistically significant (Chi-square test, p = 0.418). The mesial and distal sites showed a higher prevalence of BL in the jaw, QBL (89.80%) and DBL (79.40%), and no significant difference was observed in the distribution of QBL (Fisher's exact test p = 0.311) and DBL (Fisher's exact test p = 0.672) in the dental arches. The distal sites exhibited higher prevalence of both QBL (77.56%) and DBL (58.82%). The periodontal status of children should never be underestimated because BL occurs even in healthy populations, although in a lower frequency.

32 CFR 154.18 - Certain positions not necessarily requiring access to classified information.

Code of Federal Regulations, 2013 CFR

2013-07-01

... to meet the high standards required. At a minimum, all such personnel shall have had a favorably... information systems may be assigned to one of three position sensitivity designations (in accordance with...

32 CFR 154.18 - Certain positions not necessarily requiring access to classified information.

Code of Federal Regulations, 2014 CFR

2014-07-01

... to meet the high standards required. At a minimum, all such personnel shall have had a favorably... information systems may be assigned to one of three position sensitivity designations (in accordance with...

A Large-scale Distributed Indexed Learning Framework for Data that Cannot Fit into Memory

DTIC Science & Technology

2015-03-27

learn a classifier. Integrating three learning techniques (online, semi-supervised and active learning ) together with a selective sampling with minimum communication between the server and the clients solved this problem.

MOnthly TEmperature DAtabase of Spain 1951-2010: MOTEDAS (2): The Correlation Decay Distance (CDD) and the spatial variability of maximum and minimum monthly temperature in Spain during (1981-2010).

NASA Astrophysics Data System (ADS)

Cortesi, Nicola; Peña-Angulo, Dhais; Simolo, Claudia; Stepanek, Peter; Brunetti, Michele; Gonzalez-Hidalgo, José Carlos

2014-05-01

One of the key point in the develop of the MOTEDAS dataset (see Poster 1 MOTEDAS) in the framework of the HIDROCAES Project (Impactos Hidrológicos del Calentamiento Global en España, Spanish Ministery of Research CGL2011-27574-C02-01) is the reference series for which no generalized metadata exist. In this poster we present an analysis of spatial variability of monthly minimum and maximum temperatures in the conterminous land of Spain (Iberian Peninsula, IP), by using the Correlation Decay Distance function (CDD), with the aim of evaluating, at sub-regional level, the optimal threshold distance between neighbouring stations for producing the set of reference series used in the quality control (see MOTEDAS Poster 1) and the reconstruction (see MOREDAS Poster 3). The CDD analysis for Tmax and Tmin was performed calculating a correlation matrix at monthly scale between 1981-2010 among monthly mean values of maximum (Tmax) and minimum (Tmin) temperature series (with at least 90% of data), free of anomalous data and homogenized (see MOTEDAS Poster 1), obtained from AEMEt archives (National Spanish Meteorological Agency). Monthly anomalies (difference between data and mean 1981-2010) were used to prevent the dominant effect of annual cycle in the CDD annual estimation. For each station, and time scale, the common variance r2 (using the square of Pearson's correlation coefficient) was calculated between all neighbouring temperature series and the relation between r2 and distance was modelled according to the following equation (1): Log (r2ij) = b*°dij (1) being Log(rij2) the common variance between target (i) and neighbouring series (j), dij the distance between them and b the slope of the ordinary least-squares linear regression model applied taking into account only the surrounding stations within a starting radius of 50 km and with a minimum of 5 stations required. Finally, monthly, seasonal and annual CDD values were interpolated using the Ordinary Kriging with a spherical variogram over conterminous land of Spain, and converted on a regular 10 km2 grid (resolution similar to the mean distance between stations) to map the results. In the conterminous land of Spain the distance at which couples of stations have a common variance in temperature (both maximum Tmax, and minimum Tmin) above the selected threshold (50%, r Pearson ~0.70) on average does not exceed 400 km, with relevant spatial and temporal differences. The spatial distribution of the CDD shows a clear coastland-to-inland gradient at annual, seasonal and monthly scale, with highest spatial variability along the coastland areas and lower variability inland. The highest spatial variability coincide particularly with coastland areas surrounded by mountain chains and suggests that the orography is one of the most driving factor causing higher interstation variability. Moreover, there are some differences between the behaviour of Tmax and Tmin, being Tmin spatially more homogeneous than Tmax, but its lower CDD values indicate that night-time temperature is more variable than diurnal one. The results suggest that in general local factors affects the spatial variability of monthly Tmin more than Tmax and then higher network density would be necessary to capture the higher spatial variability highlighted for Tmin respect to Tmax. The results suggest that in general local factors affects the spatial variability of Tmin more than Tmax and then higher network density would be necessary to capture the higher spatial variability highlighted for minimum temperature respect to maximum temperature. A conservative distance for reference series could be evaluated in 200 km, that we propose for continental land of Spain and use in the development of MOTEDAS.

The Effects of Long Distance Running on Preadolescent Children.

ERIC Educational Resources Information Center

Covington, N. Kay

This study investigated the effects of selected physiological variables on preadolescent male and female long distance runners. The trained group was comprised of 20 children between the ages of 8 and 10 who had been running a minimum of 20 miles per week for two months or longer. The control group was made up of 20 children of the same ages who…

Optimizing the Launch of a Projectile to Hit a Target

ERIC Educational Resources Information Center

Mungan, Carl E.

2017-01-01

Some teenagers are exploring the outer perimeter of a castle. They notice a spy hole in its wall, across the moat a horizontal distance "x" and vertically up the wall a distance "y." They decide to throw pebbles at the hole. One girl wants to use physics to throw with the minimum speed necessary to hit the hole. What is the…

[Effects of temperature increase on zooplankton size spectra in thermal discharge seawaters near a power plant, China].

PubMed

Yu, Jing; Zhu, Yi Feng; Dai, Mei Xia; Lin, Xia; Mao, Shuo Qian

2017-05-18

Utilizing the plankton 1 (505 Μm), 2 (160 Μm), 3 (77 Μm) nets to seasonally collect zooplankton samples at 10 stations and the corresponding abundance data was obtained. Based on individual zooplankton biovolume, size groups were classified to test the changes in spatiotemporal characteristics of both Sheldon and normalized biovolume size spectra in thermal discharge seawaters near the Guohua Power Plant, so as to explore the effects of temperature increase on zooplankton size spectra in the seawaters. The results showed that the individual biovolume of zooplankton ranged from 0.00012 to 127.0 mm 3 ·ind -1 , which could be divided into 21 size groups, and corresponding logarithmic ranges were from -13.06 to 6.99. According to Sheldon size spectra, the predominant species to form main peaks of the size spectrum in different months were Copepodite larvae, Centropages mcmurrichi, Calanus sinicus, fish larvae, Sagitta bedoti, Sagitta nagae and Pleurobrachia globosa, and minor peaks mostly consisted of individuals with smaller larvae, Cyclops and Paracalanus aculeatus. In different warming sections, Copepodite larvae, fish eggs and Cyclops were mostly unaffected by the temperature increase, while the macrozooplankton such as S. bedoti, S. nagae, P. globosa, C. sinicus and Beroe cucumis had an obvious tendency to avoid the outfall of the power plant. Based on the results of normalized size spectra, the intercepts from low to high occurred in November, February, May and August, respectively. At the same time, the minimum slope was found in February, and similarly bigger slopes were observed in May and August. These results indicated that the proportion of small zooplankton was highest in February, while the proportions of the meso- and macro-zooplankton were relatively high in May and August. Among different sections, the slope in the 0.2 km section was minimum, which increased with the increase of section distance to the outfall. The result obviously demonstrated that the closer the distance was from outfall of the power plant, the smaller the zooplankton became. On the whole, the average intercept of normalized size spectrum in Xiangshan Bay was 4.68, and the slope was -0.655.

Multiple Spectral-Spatial Classification Approach for Hyperspectral Data

NASA Technical Reports Server (NTRS)

Tarabalka, Yuliya; Benediktsson, Jon Atli; Chanussot, Jocelyn; Tilton, James C.

2010-01-01

A .new multiple classifier approach for spectral-spatial classification of hyperspectral images is proposed. Several classifiers are used independently to classify an image. For every pixel, if all the classifiers have assigned this pixel to the same class, the pixel is kept as a marker, i.e., a seed of the spatial region, with the corresponding class label. We propose to use spectral-spatial classifiers at the preliminary step of the marker selection procedure, each of them combining the results of a pixel-wise classification and a segmentation map. Different segmentation methods based on dissimilar principles lead to different classification results. Furthermore, a minimum spanning forest is built, where each tree is rooted on a classification -driven marker and forms a region in the spectral -spatial classification: map. Experimental results are presented for two hyperspectral airborne images. The proposed method significantly improves classification accuracies, when compared to previously proposed classification techniques.

Enhancing the Performance of LibSVM Classifier by Kernel F-Score Feature Selection

NASA Astrophysics Data System (ADS)

Sarojini, Balakrishnan; Ramaraj, Narayanasamy; Nickolas, Savarimuthu

Medical Data mining is the search for relationships and patterns within the medical datasets that could provide useful knowledge for effective clinical decisions. The inclusion of irrelevant, redundant and noisy features in the process model results in poor predictive accuracy. Much research work in data mining has gone into improving the predictive accuracy of the classifiers by applying the techniques of feature selection. Feature selection in medical data mining is appreciable as the diagnosis of the disease could be done in this patient-care activity with minimum number of significant features. The objective of this work is to show that selecting the more significant features would improve the performance of the classifier. We empirically evaluate the classification effectiveness of LibSVM classifier on the reduced feature subset of diabetes dataset. The evaluations suggest that the feature subset selected improves the predictive accuracy of the classifier and reduce false negatives and false positives.

Performance Analysis of Classification Methods for Indoor Localization in Vlc Networks

NASA Astrophysics Data System (ADS)

Sánchez-Rodríguez, D.; Alonso-González, I.; Sánchez-Medina, J.; Ley-Bosch, C.; Díaz-Vilariño, L.

2017-09-01

Indoor localization has gained considerable attention over the past decade because of the emergence of numerous location-aware services. Research works have been proposed on solving this problem by using wireless networks. Nevertheless, there is still much room for improvement in the quality of the proposed classification models. In the last years, the emergence of Visible Light Communication (VLC) brings a brand new approach to high quality indoor positioning. Among its advantages, this new technology is immune to electromagnetic interference and has the advantage of having a smaller variance of received signal power compared to RF based technologies. In this paper, a performance analysis of seventeen machine leaning classifiers for indoor localization in VLC networks is carried out. The analysis is accomplished in terms of accuracy, average distance error, computational cost, training size, precision and recall measurements. Results show that most of classifiers harvest an accuracy above 90 %. The best tested classifier yielded a 99.0 % accuracy, with an average error distance of 0.3 centimetres.

Toward Improving Electrocardiogram (ECG) Biometric Verification using Mobile Sensors: A Two-Stage Classifier Approach

PubMed Central

Tan, Robin; Perkowski, Marek

2017-01-01

Electrocardiogram (ECG) signals sensed from mobile devices pertain the potential for biometric identity recognition applicable in remote access control systems where enhanced data security is demanding. In this study, we propose a new algorithm that consists of a two-stage classifier combining random forest and wavelet distance measure through a probabilistic threshold schema, to improve the effectiveness and robustness of a biometric recognition system using ECG data acquired from a biosensor integrated into mobile devices. The proposed algorithm is evaluated using a mixed dataset from 184 subjects under different health conditions. The proposed two-stage classifier achieves a total of 99.52% subject verification accuracy, better than the 98.33% accuracy from random forest alone and 96.31% accuracy from wavelet distance measure algorithm alone. These results demonstrate the superiority of the proposed algorithm for biometric identification, hence supporting its practicality in areas such as cloud data security, cyber-security or remote healthcare systems. PMID:28230745

Toward Improving Electrocardiogram (ECG) Biometric Verification using Mobile Sensors: A Two-Stage Classifier Approach.

PubMed

Tan, Robin; Perkowski, Marek

2017-02-20

Electrocardiogram (ECG) signals sensed from mobile devices pertain the potential for biometric identity recognition applicable in remote access control systems where enhanced data security is demanding. In this study, we propose a new algorithm that consists of a two-stage classifier combining random forest and wavelet distance measure through a probabilistic threshold schema, to improve the effectiveness and robustness of a biometric recognition system using ECG data acquired from a biosensor integrated into mobile devices. The proposed algorithm is evaluated using a mixed dataset from 184 subjects under different health conditions. The proposed two-stage classifier achieves a total of 99.52% subject verification accuracy, better than the 98.33% accuracy from random forest alone and 96.31% accuracy from wavelet distance measure algorithm alone. These results demonstrate the superiority of the proposed algorithm for biometric identification, hence supporting its practicality in areas such as cloud data security, cyber-security or remote healthcare systems.

Relation Between Inflammables and Ignition Sources in Aircraft Environments

NASA Technical Reports Server (NTRS)

Scull, Wilfred E

1950-01-01

A literature survey was conducted to determine the relation between aircraft ignition sources and inflammables. Available literature applicable to the problem of aircraft fire hazards is analyzed and, discussed herein. Data pertaining to the effect of many variables on ignition temperatures, minimum ignition pressures, and minimum spark-ignition energies of inflammables, quenching distances of electrode configurations, and size of openings incapable of flame propagation are presented and discussed. The ignition temperatures and the limits of inflammability of gasoline in air in different test environments, and the minimum ignition pressure and the minimum size of openings for flame propagation of gasoline - air mixtures are included. Inerting of gasoline - air mixtures is discussed.

A new approach to keratoconus detection based on corneal morphogeometric analysis.

PubMed

Cavas-Martínez, Francisco; Bataille, Laurent; Fernández-Pacheco, Daniel G; Cañavate, Francisco J F; Alió, Jorge L

2017-01-01

To characterize corneal structural changes in keratoconus using a new morphogeometric approach and to evaluate its potential diagnostic ability. Comparative study including 464 eyes of 464 patients (age, 16 and 72 years) divided into two groups: control group (143 healthy eyes) and keratoconus group (321 keratoconus eyes). Topographic information (Sirius, CSO, Italy) was processed with SolidWorks v2012 and a solid model representing the geometry of each cornea was generated. The following parameters were defined: anterior (Aant) and posterior (Apost) corneal surface areas, area of the cornea within the sagittal plane passing through the Z axis and the apex (Aapexant, Aapexpost) and minimum thickness points (Amctant, Amctpost) of the anterior and posterior corneal surfaces, and average distance from the Z axis to the apex (Dapexant, Dapexpost) and minimum thickness points (Dmctant, Dmctpost) of both corneal surfaces. Significant differences among control and keratoconus group were found in Aapexant, Aapexpost, Amctant, Amctpost, Dapexant, Dapexpost (all p<0.001), Apost (p = 0.014), and Dmctpost (p = 0.035). Significant correlations in keratoconus group were found between Aant and Apost (r = 0.836), Amctant and Amctpost (r = 0.983), and Dmctant and Dmctpost (r = 0.954, all p<0.001). A logistic regression analysis revealed that the detection of keratoconus grade I (Amsler Krumeich) was related to Apost, Atot, Aapexant, Amctant, Amctpost, Dapexpost, Dmctant and Dmctpost (Hosmer-Lemeshow: p>0.05, R2 Nagelkerke: 0.926). The overall percentage of cases correctly classified by the model was 97.30%. Our morphogeometric approach based on the analysis of the cornea as a solid is useful for the characterization and detection of keratoconus.

On the star partition dimension of comb product of cycle and path

NASA Astrophysics Data System (ADS)

Alfarisi, Ridho; Darmaji

2017-08-01

Let G = (V, E) be a connected graphs with vertex set V(G), edge set E(G) and S ⊆ V(G). Given an ordered partition Π = {S1, S2, S3, …, Sk} of the vertex set V of G, the representation of a vertex v ∈ V with respect to Π is the vector r(v|Π) = (d(v, S1), d(v, S2), …, d(v, Sk)), where d(v, Sk) represents the distance between the vertex v and the set Sk and d(v, Sk) = min{d(v, x)|x ∈ Sk }. A partition Π of V(G) is a resolving partition if different vertices of G have distinct representations, i.e., for every pair of vertices u, v ∈ V(G), r(u|Π) ≠ r(v|Π). The minimum k of Π resolving partition is a partition dimension of G, denoted by pd(G). The resolving partition Π = {S1, S2, S3, …, Sk } is called a star resolving partition for G if it is a resolving partition and each subgraph induced by Si, 1 ≤ i ≤ k, is a star. The minimum k for which there exists a star resolving partition of V(G) is the star partition dimension of G, denoted by spd(G). Finding the star partition dimension of G is classified to be a NP-Hard problem. In this paper, we will show that the partition dimension of comb product of cycle and path namely Cm⊳Pn and Pn⊳Cm for n ≥ 2 and m ≥ 3.

Transport of Escherichia coli in 25 m quartz sand columns

NASA Astrophysics Data System (ADS)

Lutterodt, G.; Foppen, J. W. A.; Maksoud, A.; Uhlenbrook, S.

2011-01-01

To help improve the prediction of bacteria travel distances in aquifers laboratory experiments were conducted to measure the distant dependent sticking efficiencies of two low attaching Escherichia coli strains (UCFL-94 and UCFL-131). The experimental set up consisted of a 25 m long helical column with a diameter of 3.2 cm packed with 99.1% pure-quartz sand saturated with a solution of magnesium sulfate and calcium chloride. Bacteria mass breakthrough at sampling distances ranging from 6 to 25.65 m were observed to quantify bacteria attachment over total transport distances ( αL) and sticking efficiencies at large intra-column segments ( αi) (> 5 m). Fractions of cells retained ( Fi) in a column segment as a function of αi were fitted with a power-law distribution from which the minimum sticking efficiency defined as the sticking efficiency of 0.001% bacteria fraction of the total input mass retained that results in a 5 log removal were extrapolated. Low values of αL in the order 10 - 4 and 10 - 3 were obtained for UCFL-94 and UCFL-131 respectively, while αi-values ranged between 10 - 6 to 10 - 3 for UCFL-94 and 10 - 5 to 10 - 4 for UCFL-131. In addition, both αL and αi reduced with increasing transport distance, and high coefficients of determination (0.99) were obtained for power-law distributions of αi for the two strains. Minimum sticking efficiencies extrapolated were 10 - 7 and 10 - 8 for UCFL-94 and UCFL-131, respectively. Fractions of cells exiting the column were 0.19 and 0.87 for UCFL-94 and UCL-131, respectively. We concluded that environmentally realistic sticking efficiency values in the order of 10 - 4 and 10 - 3 and much lower sticking efficiencies in the order 10 - 5 are measurable in the laboratory, Also power-law distributions in sticking efficiencies commonly observed for limited intra-column distances (< 2 m) are applicable at large transport distances(> 6 m) in columns packed with quartz grains. High fractions of bacteria populations may possess the so-called minimum sticking efficiency, thus expressing their ability to be transported over distances longer than what might be predicted using measured sticking efficiencies from experiments with both short (< 1 m) and long columns (> 25 m). Also variable values of sticking efficiencies within and among the strains show heterogeneities possibly due to variations in cell surface characteristics of the strains. The low sticking efficiency values measured express the importance of the long columns used in the experiments and the lower values of extrapolated minimum sticking efficiencies makes the method a valuable tool in delineating protection areas in real-world scenarios.

A new analytical method for the classification of time-location data obtained from the global positioning system (GPS).

PubMed

Kim, Taehyun; Lee, Kiyoung; Yang, Wonho; Yu, Seung Do

2012-08-01

Although the global positioning system (GPS) has been suggested as an alternative way to determine time-location patterns, its use has been limited. The purpose of this study was to evaluate a new analytical method of classifying time-location data obtained by GPS. A field technician carried a GPS device while simulating various scripted activities and recorded all movements by the second in an activity diary. The GPS device recorded geological data once every 15 s. The daily monitoring was repeated 18 times. The time-location data obtained by the GPS were compared with the activity diary to determine selection criteria for the classification of the GPS data. The GPS data were classified into four microenvironments (residential indoors, other indoors, transit, and walking outdoors); the selection criteria used were used number of satellites (used-NSAT), speed, and distance from residence. The GPS data were classified as indoors when the used-NSAT was below 9. Data classified as indoors were further classified as residential indoors when the distance from the residence was less than 40 m; otherwise, they were classified as other indoors. Data classified as outdoors were further classified as being in transit when the speed exceeded 2.5 m s(-1); otherwise, they were classified as walking outdoors. The average simple percentage agreement between the time-location classifications and the activity diary was 84.3 ± 12.4%, and the kappa coefficient was 0.71. The average differences between the time diary and the GPS results were 1.6 ± 2.3 h for the time spent in residential indoors, 0.9 ± 1.7 h for the time spent in other indoors, 0.4 ± 0.4 h for the time spent in transit, and 0.8 ± 0.5 h for the time spent walking outdoors. This method can be used to determine time-activity patterns in exposure-science studies.

Read distance performance and variation of 5 low-frequency radio frequency identification panel transceiver manufacturers.

PubMed

Ryan, S E; Blasi, D A; Anglin, C O; Bryant, A M; Rickard, B A; Anderson, M P; Fike, K E

2010-07-01

Use of electronic animal identification technologies by livestock managers is increasing, but performance of these technologies can be variable when used in livestock production environments. This study was conducted to determine whether 1) read distance of low-frequency radio frequency identification (RFID) transceivers is affected by type of transponder being interrogated; 2) read distance variation of low-frequency RFID transceivers is affected by transceiver manufacturer; and 3) read distance of various transponder-transceiver manufacturer combinations meet the 2004 United States Animal Identification Plan (USAIP) bovine standards subcommittee minimum read distance recommendation of 60 cm. Twenty-four transceivers (n = 5 transceivers per manufacturer for Allflex, Boontech, Farnam, and Osborne; n = 4 transceivers for Destron Fearing) were tested with 60 transponders [n = 10 transponders per type for Allflex full duplex B (FDX-B), Allflex half duplex (HDX), Destron Fearing FDX-B, Farnam FDX-B, and Y-Tex FDX-B; n = 6 for Temple FDX-B (EM Microelectronic chip); and n = 4 for Temple FDX-B (HiTag chip)] presented in the parallel orientation. All transceivers and transponders met International Organization for Standardization 11784 and 11785 standards. Transponders represented both one-half duplex and full duplex low-frequency air interface technologies. Use of a mechanical trolley device enabled the transponders to be presented to the center of each transceiver at a constant rate, thereby reducing human error. Transponder and transceiver manufacturer interacted (P < 0.0001) to affect read distance, indicating that transceiver performance was greatly dependent upon the transponder type being interrogated. Twenty-eight of 30 combinations of transceivers and transponders evaluated met the minimum recommended USAIP read distance. The mean read distance across all 30 combinations was 45.1 to 129.4 cm. Transceiver manufacturer and transponder type interacted to affect read distance variance (P < 0.05). Maximum read distance performance of low-frequency RFID technologies with low variance can be achieved by selecting specific transponder-transceiver combinations.

Computational fluid dynamics (CFD) investigation of impacts of an obstruction on airflow in underground mines.

PubMed

Zhou, L; Goodman, G; Martikainen, A

2013-01-01

Continuous airflow monitoring can improve the safety of the underground work force by ensuring the uninterrupted and controlled distribution of mine ventilation to all working areas. Air velocity measurements vary significantly and can change rapidly depending on the exact measurement location and, in particular, due to the presence of obstructions in the air stream. Air velocity must be measured at locations away from obstructions to avoid the vortices and eddies that can produce inaccurate readings. Further, an uninterrupted measurement path cannot always be guaranteed when using continuous airflow monitors due to the presence of nearby equipment, personnel, roof falls and rib rolls. Effective use of these devices requires selection of a minimum distance from an obstacle, such that an air velocity measurement can be made but not affected by the presence of that obstacle. This paper investigates the impacts of an obstruction on the behavior of downstream airflow using a numerical CFD model calibrated with experimental test results from underground testing. Factors including entry size, obstruction size and the inlet or incident velocity are examined for their effects on the distributions of airflow around an obstruction. A relationship is developed between the minimum measurement distance and the hydraulic diameters of the entry and the obstruction. A final analysis considers the impacts of continuous monitor location on the accuracy of velocity measurements and on the application of minimum measurement distance guidelines.

Computational fluid dynamics (CFD) investigation of impacts of an obstruction on airflow in underground mines

PubMed Central

Zhou, L.; Goodman, G.; Martikainen, A.

2015-01-01

Continuous airflow monitoring can improve the safety of the underground work force by ensuring the uninterrupted and controlled distribution of mine ventilation to all working areas. Air velocity measurements vary significantly and can change rapidly depending on the exact measurement location and, in particular, due to the presence of obstructions in the air stream. Air velocity must be measured at locations away from obstructions to avoid the vortices and eddies that can produce inaccurate readings. Further, an uninterrupted measurement path cannot always be guaranteed when using continuous airflow monitors due to the presence of nearby equipment, personnel, roof falls and rib rolls. Effective use of these devices requires selection of a minimum distance from an obstacle, such that an air velocity measurement can be made but not affected by the presence of that obstacle. This paper investigates the impacts of an obstruction on the behavior of downstream airflow using a numerical CFD model calibrated with experimental test results from underground testing. Factors including entry size, obstruction size and the inlet or incident velocity are examined for their effects on the distributions of airflow around an obstruction. A relationship is developed between the minimum measurement distance and the hydraulic diameters of the entry and the obstruction. A final analysis considers the impacts of continuous monitor location on the accuracy of velocity measurements and on the application of minimum measurement distance guidelines. PMID:26388684

Open and Distance Learning for Health: Supporting Health Workers through Education and Training

ERIC Educational Resources Information Center

Dodds, Tony

2011-01-01

This case study surveys the growing use of open and distance learning approaches to the provision of support, education and training to health workers over the past few decades. It classifies such uses under four headings, providing brief descriptions from the literature of a few examples of each group. In conclusion, it identifies key lessons…

Association between mild cognitive impairment and trajectory-based spatial parameters during timed up and go test using a laser range sensor.

PubMed

Nishiguchi, Shu; Yorozu, Ayanori; Adachi, Daiki; Takahashi, Masaki; Aoyama, Tomoki

2017-08-08

The Timed Up and Go (TUG) test may be a useful tool to detect not only mobility impairment but also possible cognitive impairment. In this cross-sectional study, we used the TUG test to investigate the associations between trajectory-based spatial parameters measured by laser range sensor (LRS) and cognitive impairment in community-dwelling older adults. The participants were 63 community-dwelling older adults (mean age, 73.0 ± 6.3 years). The trajectory-based spatial parameters during the TUG test were measured using an LRS. In each forward and backward phase, we calculated the minimum distance from the marker, the maximum distance from the x-axis (center line), the length of the trajectories, and the area of region surrounded by the trajectory of the center of gravity and the x-axis (center line). We measured mild cognitive impairment using the Mini-Mental State Examination score (26/27 was the cut-off score for defining mild cognitive impairment). Compared with participants with normal cognitive function, those with mild cognitive impairment exhibited the following trajectory-based spatial parameters: short minimum distance from the marker (p = 0.044), narrow area of center of gravity in the forward phase (p = 0.012), and a large forward/whole phase ratio of the area of the center of gravity (p = 0.026) during the TUG test. In multivariate logistic regression analyses, a short minimum distance from the marker (odds ratio [OR]: 0.82, 95% confidence interval [CI]: 0.69-0.98), narrow area of the center of gravity in the forward phase (OR: 0.01, 95% CI: 0.00-0.36), and large forward/whole phase ratio of the area of the center of gravity (OR: 0.94, 95% CI: 0.88-0.99) were independently associated with mild cognitive impairment. In conclusion, our results indicate that some of the trajectory-based spatial parameters measured by LRS during the TUG test were independently associated with cognitive impairment in older adults. In particular, older adults with cognitive impairment exhibit shorter minimum distances from the marker and asymmetrical trajectories during the TUG test.

Multivariate pattern analysis for MEG: A comparison of dissimilarity measures.

PubMed

Guggenmos, Matthias; Sterzer, Philipp; Cichy, Radoslaw Martin

2018-06-01

Multivariate pattern analysis (MVPA) methods such as decoding and representational similarity analysis (RSA) are growing rapidly in popularity for the analysis of magnetoencephalography (MEG) data. However, little is known about the relative performance and characteristics of the specific dissimilarity measures used to describe differences between evoked activation patterns. Here we used a multisession MEG data set to qualitatively characterize a range of dissimilarity measures and to quantitatively compare them with respect to decoding accuracy (for decoding) and between-session reliability of representational dissimilarity matrices (for RSA). We tested dissimilarity measures from a range of classifiers (Linear Discriminant Analysis - LDA, Support Vector Machine - SVM, Weighted Robust Distance - WeiRD, Gaussian Naïve Bayes - GNB) and distances (Euclidean distance, Pearson correlation). In addition, we evaluated three key processing choices: 1) preprocessing (noise normalisation, removal of the pattern mean), 2) weighting decoding accuracies by decision values, and 3) computing distances in three different partitioning schemes (non-cross-validated, cross-validated, within-class-corrected). Four main conclusions emerged from our results. First, appropriate multivariate noise normalization substantially improved decoding accuracies and the reliability of dissimilarity measures. Second, LDA, SVM and WeiRD yielded high peak decoding accuracies and nearly identical time courses. Third, while using decoding accuracies for RSA was markedly less reliable than continuous distances, this disadvantage was ameliorated by decision-value-weighting of decoding accuracies. Fourth, the cross-validated Euclidean distance provided unbiased distance estimates and highly replicable representational dissimilarity matrices. Overall, we strongly advise the use of multivariate noise normalisation as a general preprocessing step, recommend LDA, SVM and WeiRD as classifiers for decoding and highlight the cross-validated Euclidean distance as a reliable and unbiased default choice for RSA. Copyright © 2018 Elsevier Inc. All rights reserved.

Off-Resonant Two-Photon Absorption Cross-Section Enhancement of an Organic Chromophore on Gold Nanorods

PubMed Central

Sivapalan, Sean T.; Vella, Jarrett H.; Yang, Timothy K.; Dalton, Matthew J.; Haley, Joy E.; Cooper, Thomas M.; Urbas, Augustine M.; Tan, Loon-Seng; Murphy, Catherine J.

2013-01-01

Surface-plasmon-initiated interference effects of polyelectrolyte-coated gold nanorods on the two-photon absorption of an organic chromophore were investigated. With polyelectrolyte bearing gold nanorods of 2,4,6 and 8 layers, the role of the plasmonic fields as function of distance on such effects was examined. An unusual distance dependence was found: enhancements in the two-photon cross-section were at a minimum at an intermediate distance, then rose again at a further distance. The observed values of enhancement were compared to theoretical predictions using finite element analysis and showed good agreementdue to constructive and destructive interference effects. PMID:23687561

A Near-infrared Period–Luminosity Relation for Miras in NGC 4258, an Anchor for a New Distance Ladder

NASA Astrophysics Data System (ADS)

Huang, Caroline D.; Riess, Adam G.; Hoffmann, Samantha L.; Klein, Christopher; Bloom, Joshua; Yuan, Wenlong; Macri, Lucas M.; Jones, David O.; Whitelock, Patricia A.; Casertano, Stefano; Anderson, Richard I.

2018-04-01

We present year-long, near-infrared (NIR) Hubble Space Telescope (HST) WFC3 observations of Mira variables in the water megamaser host galaxy NGC 4258. Miras are asymptotic giant branch variables that can be divided into oxygen- (O-) and carbon- (C-) rich subclasses. Oxygen-rich Miras follow a tight (scatter ∼0.14 mag) period–luminosity relation (PLR) in the NIR and can be used to measure extragalactic distances. The water megamaser in NGC 4258 gives a geometric distance to the galaxy accurate to 2.6% that can serve to calibrate the Mira PLR. We develop criteria for detecting and classifying O-rich Miras with optical and NIR data as well as NIR data alone. In total, we discover 438 Mira candidates that we classify with high confidence as O-rich. Our most stringent criteria produce a sample of 139 Mira candidates that we use to measure a PLR. We use the OGLE-III sample of O-rich Miras in the Large Magellanic Cloud to obtain a relative distance modulus, μ 4258 ‑ μ LMC = 10.95 ± 0.01 (statistical) ±0.06 (systematic) mag, that is statistically consistent with the relative distance determined using Cepheids. These results demonstrate the feasibility of discovering and characterizing Miras using the NIR with the HST and the upcoming James Webb Space Telescope and using those Miras to measure extragalactic distances and determine the Hubble constant.

Triple-decker sandwiches and related compounds of the first-row transition metals containing cyclopentadienyl and benzene rings.

PubMed

Liu, Haibo; Li, Qian-shu; Xie, Yaoming; King, R Bruce; Schaefer, Henry F

2010-08-12

The triple-decker sandwich compound trans-Cp(2)V(2)(eta(6):eta(6)-mu-C(6)H(6)) has been synthesized, as well as "slipped" sandwich compounds of the type trans-Cp(2)Co(2)(eta(4):eta(4)-mu-arene) and the cis-Cp(2)Fe(2)(eta(4):eta(4)-mu-C(6)R(6)) derivatives with an Fe-Fe bond (Cp = eta(5)-cyclopentadienyl). Theoretical studies show that the symmetrical triple-decker sandwich structures trans-Cp(2)M(2)(eta(6):eta(6)-mu-C(6)H(6)) are the global minima for M = Ti, V, and Mn but lie approximately 10 kcal/mol above the global minimum for M = Cr. The nonbonding M...M distances and spin states in these triple decker sandwich compounds can be related to the occupancies of the frontier bonding molecular orbitals. The global minimum for the chromium derivative is a singlet spin state cis-Cp(2)Cr(2)(eta(4):eta(4)-mu-C(6)H(6)) structure with a very short CrCr distance of 2.06 A, suggesting a formal quadruple bond. A triplet state cis-Cp(2)Cr(2)(eta(4):eta(4)-mu-C(6)H(6)) structure with a predicted Cr[triple bond]Cr distance of 2.26 A lies only approximately 3 kcal/mol above this global minimum. For the later transition metals the global minima are predicted to be cis-Cp(2)M(2)(eta(6):eta(6)-mu-C(6)H(6)) structures with a metal-metal bond, rather than triple decker sandwiches. These include singlet cis-Cp(2)Fe(2)(eta(4):eta(4)-mu-C(6)H(6)) with a predicted Fe=Fe double bond distance of 2.43 A, singlet cis-Cp(2)Co(2)(eta(3):eta(3)-mu-C(6)H(6)) with a predicted Co-Co single bond distance of 2.59 A, and triplet cis-Cp(2)Ni(2)(eta(3):eta(3)-mu-C(6)H(6)) with a predicted Ni-Ni distance of 2.71 A.

Hyperspectral feature mapping classification based on mathematical morphology

NASA Astrophysics Data System (ADS)

Liu, Chang; Li, Junwei; Wang, Guangping; Wu, Jingli

2016-03-01

This paper proposed a hyperspectral feature mapping classification algorithm based on mathematical morphology. Without the priori information such as spectral library etc., the spectral and spatial information can be used to realize the hyperspectral feature mapping classification. The mathematical morphological erosion and dilation operations are performed respectively to extract endmembers. The spectral feature mapping algorithm is used to carry on hyperspectral image classification. The hyperspectral image collected by AVIRIS is applied to evaluate the proposed algorithm. The proposed algorithm is compared with minimum Euclidean distance mapping algorithm, minimum Mahalanobis distance mapping algorithm, SAM algorithm and binary encoding mapping algorithm. From the results of the experiments, it is illuminated that the proposed algorithm's performance is better than that of the other algorithms under the same condition and has higher classification accuracy.

Rate-compatible protograph LDPC code families with linear minimum distance

NASA Technical Reports Server (NTRS)

Divsalar, Dariush (Inventor); Dolinar, Jr., Samuel J. (Inventor); Jones, Christopher R. (Inventor)

2012-01-01

Digital communication coding methods are shown, which generate certain types of low-density parity-check (LDPC) codes built from protographs. A first method creates protographs having the linear minimum distance property and comprising at least one variable node with degree less than 3. A second method creates families of protographs of different rates, all structurally identical for all rates except for a rate-dependent designation of certain variable nodes as transmitted or non-transmitted. A third method creates families of protographs of different rates, all structurally identical for all rates except for a rate-dependent designation of the status of certain variable nodes as non-transmitted or set to zero. LDPC codes built from the protographs created by these methods can simultaneously have low error floors and low iterative decoding thresholds.

Transverse Stress Decay in a Specially Orthotropic Strip Under Localizing Normal Edge Loading

NASA Technical Reports Server (NTRS)

Fichter, W. B.

2000-01-01

Solutions are presented for the stresses in a specially orthotropic infinite strip which is subjected to localized uniform normal loading on one edge while the other edge is either restrained against normal displacement only, or completely fixed. The solutions are used to investigate the diffusion of load into the strip and in particular the decay of normal stress across the width of the strip. For orthotropic strips representative of a broad range of balanced and symmetric angle-ply composite laminates, minimum strip widths are found that ensure at least 90% decay of the normal stress across the strip. In addition, in a few cases where, on the fixed edge the peak shear stress exceeds the normal stress in magnitude, minimum strip widths that ensure 90% decay of both stresses are found. To help in putting these results into perspective, and to illustrate the influence of material properties on load 9 orthotropic materials, closed-form solutions for the stresses in similarly loaded orthotropic half-planes are obtained. These solutions are used to generate illustrative stress contour plots for several representative laminates. Among the laminates, those composed of intermediate-angle plies, i.e., from about 30 degrees to 60 degrees, exhibit marked changes in normal stress contour shape with stress level. The stress contours are also used to find 90% decay distances in the half-planes. In all cases, the minimum strip widths for 90% decay of the normal stress exceed the 90% decay distances in the corresponding half-planes, in amounts ranging from only a few percent to about 50% of the half-plane decay distances. The 90% decay distances depend on both material properties and the boundary conditions on the supported edge.

Classification of Salmonella serotypes with hyperspectral microscope imagery

USDA-ARS?s Scientific Manuscript database

Previous research has demonstrated an optical method with acousto-optic tunable filter (AOTF) based hyperspectral microscope imaging (HMI) had potential for classifying gram-negative from gram-positive foodborne pathogenic bacteria rapidly and nondestructively with a minimum sample preparation. In t...

External-beam Co-60 radiotherapy for canine nasal tumors: a comparison of survival by treatment protocol.

PubMed

Yoon, J H; Feeney, D A; Jessen, C R; Walter, P A

2008-02-01

A retrospective analysis of survival times in dogs with intranasal tumors was performed comparing those treated using hypofractionated or full course Co-60 radiotherapy protocols alone or with surgical adjuvant therapy and those receiving no radiation treatment. One hundred thirty-nine dogs presented to the University of Minnesota Veterinary Medical Center for treatment of histologically-confirmed nasal neoplasia between July 1983 and October 2001 met the criteria for review. Statistically analyzed parameters included age at diagnosis, tumor histologic classification, fractionation schedule (number of treatments, and number of treatment days/week) (classified as hypofractionated if 2 or less treatments/week); calculated minimum tumor dose/fraction; calculated total minimum tumor dose (classified as hypofractionated if less than 37 Gy in six or fewer fractions); number of radiotherapy portals, a treatment gap of more than 7 days in a full course (3-5 treatments/week, 3-3.5 week treatment time) radiotherapy protocol, the influence of eye shields on survival following single portal DV fields, the survey radiographic extent of the disease, and the presence or absence of cytoreductive surgery. There was a significant relationship only between protocols using 3 or more treatments/week and at least 37 Gy cumulative minimum tumor dose and survival. However, there was no significant relationship between either total minimum tumor dose or dose/fraction and survival and there were no significant relationships between survival and any of the other variables analyzed including tumor histologic type.

Space Availability in Confined Sheep during Pregnancy, Effects in Movement Patterns and Use of Space

PubMed Central

Averós, Xavier; Lorea, Areta; Beltrán de Heredia, Ignacia; Arranz, Josune; Ruiz, Roberto; Estevez, Inma

2014-01-01

Space availability is essential to grant the welfare of animals. To determine the effect of space availability on movement and space use in pregnant ewes (Ovis aries), 54 individuals were studied during the last 11 weeks of gestation. Three treatments were tested (1, 2, and 3 m2/ewe; 6 ewes/group). Ewes' positions were collected for 15 minutes using continuous scan samplings two days/week. Total and net distance, net/total distance ratio, maximum and minimum step length, movement activity, angular dispersion, nearest, furthest and mean neighbour distance, peripheral location ratio, and corrected peripheral location ratio were calculated. Restriction in space availability resulted in smaller total travelled distance, net to total distance ratio, maximum step length, and angular dispersion but higher movement activity at 1 m2/ewe as compared to 2 and 3 m2/ewe (P<0.01). On the other hand, nearest and furthest neighbour distances increased from 1 to 3 m2/ewe (P<0.001). Largest total distance, maximum and minimum step length, and movement activity, as well as lowest net/total distance ratio and angular dispersion were observed during the first weeks (P<0.05) while inter-individual distances increased through gestation. Results indicate that movement patterns and space use in ewes were clearly restricted by limitations of space availability to 1 m2/ewe. This reflected in shorter, more sinuous trajectories composed of shorter steps, lower inter-individual distances and higher movement activity potentially linked with higher restlessness levels. On the contrary, differences between 2 and 3 m2/ewe, for most variables indicate that increasing space availability from 2 to 3 m2/ewe would appear to have limited benefits, reflected mostly in a further increment in the inter-individual distances among group members. No major variations in spatial requirements were detected through gestation, except for slight increments in inter-individual distances and an initial adaptation period, with ewes being restless and highly motivated to explore their new environment. PMID:24733027

Nucleation theory with delayed interactions: an application to the early stages of the receptor-mediated adhesion/fusion kinetics of lipid vesicles.

PubMed

Raudino, Antonio; Pannuzzo, Martina

2010-01-28

A semiquantitative theory aimed to describe the adhesion kinetics between soft objects, such as living cells or vesicles, has been developed. When rigid bodies are considered, the adhesion kinetics is successfully described by the classical Derjaguin, Landau, Verwey, and Overbeek (DLVO) picture, where the energy profile of two approaching bodies is given by a two asymmetrical potential wells separated by a barrier. The transition probability from the long-distance to the short-distance minimum defines the adhesion rate. Conversely, soft bodies might follow a different pathway to reach the short-distance minimum: thermally excited fluctuations give rise to local protrusions connecting the approaching bodies. These transient adhesion sites are stabilized by short-range adhesion forces (e.g., ligand-receptor interactions between membranes brought at contact distance), while they are destabilized both by repulsive forces and by the elastic deformation energy. Above a critical area of the contact site, the adhesion forces prevail: the contact site grows in size until the complete adhesion of the two bodies inside a short-distance minimum is attained. This nucleation mechanism has been developed in the framework of a nonequilibrium Fokker-Planck picture by considering both the adhesive patch growth and dissolution processes. In addition, we also investigated the effect of the ligand-receptor pairing kinetics at the adhesion site in the time course of the patch expansion. The ratio between the ligand-receptor pairing kinetics and the expansion rate of the adhesion site is of paramount relevance in determining the overall nucleation rate. The theory enables one to self-consistently include both thermodynamics (energy barrier height) and dynamic (viscosity) parameters, giving rise in some limiting cases to simple analytical formulas. The model could be employed to rationalize fusion kinetics between vesicles, provided the short-range adhesion transition is the rate-limiting step to the whole adhesion process. Approximate relationships between the experimental fusion rates reported in the literature and parameters such as membrane elastic bending modulus, repulsion strength, temperature, osmotic forces, ligand-receptor binding energy, solvent and membrane viscosities are satisfactory explained by our model. The present results hint a possible role of the initial long-distance-->short-distance transition in determining the whole fusion kinetics.

Evaluation of isometric strength and fatty infiltration of the subscapularis in latarjet surgery.

PubMed

Dos Santos, Ricardo Barreto Monteiro; Kauffman, Fábio Neumann; de Lima, Gabriel Praxedes; Ferreira, Avraham Machado Costa; Dos Santos, Saulo Monteiro; Aguiar, José Lamartine de Andrade

2015-01-01

To evaluate the function of the subscapularis muscle by means of isometric strength, clinical examination and analysis of fatty infiltration in patients with recurrent anterior dislocation of the shoulder undergoing Latarjet-Patte surgery. 38 patients operated from March 2011 to March 2012, with minimum follow-up of two years were evaluated, being 26 males and 12 females, with a mean age of 28.7 years old. Isometric strength was measured using a portable dynamometer and measuring the distance from the back of the hand during the lift-off test. We used the Rowe and Walch-Duplay scores for clinical evaluation. The degree of fatty infiltration of the subscapularis belly was assessed by computed tomography. The mean scores in the Walch-Duplay and Rowe were 84.7 and 89.4, respectively. The mean distance to the back of the hand was 7.34 cm on the operated side and 8.72 cm on the opposite side (p <0.0001). The mean strength measured in the lift-off test was 0.38 kg lower than on the contralateral side (p = 0.001). There was no fatty infiltration of the subscapularis in 16 patients (42.1%). Sixteen patients (42.1%) were classified as Goutallier grade 1 and six (15.8%) as grade 2. We found that the measured isometric strength decreases with increasing the degree of fatty infiltration (p <0.0001). The decrease in subscapularis strength, albeit of low magnitude (0.38 kg), was directly related to the degree of fatty infiltration and worse clinical outcomes. Level of Evidence III, Therapeutic Study - Investigating the Results of Treatment.

An ensemble of dissimilarity based classifiers for Mackerel gender determination

NASA Astrophysics Data System (ADS)

Blanco, A.; Rodriguez, R.; Martinez-Maranon, I.

2014-03-01

Mackerel is an infravalored fish captured by European fishing vessels. A manner to add value to this specie can be achieved by trying to classify it attending to its sex. Colour measurements were performed on Mackerel females and males (fresh and defrozen) extracted gonads to obtain differences between sexes. Several linear and non linear classifiers such as Support Vector Machines (SVM), k Nearest Neighbors (k-NN) or Diagonal Linear Discriminant Analysis (DLDA) can been applied to this problem. However, theyare usually based on Euclidean distances that fail to reflect accurately the sample proximities. Classifiers based on non-Euclidean dissimilarities misclassify a different set of patterns. We combine different kind of dissimilarity based classifiers. The diversity is induced considering a set of complementary dissimilarities for each model. The experimental results suggest that our algorithm helps to improve classifiers based on a single dissimilarity.

Evaluation of several schemes for classification of remotely sensed data: Their parameters and performance. [Foster County, North Dakota; Grant County, Kansas; Iroquois County, Illinois, Tippecanoe County, Indiana; and Pottawattamie and Shelby Counties, Iowa

NASA Technical Reports Server (NTRS)

Scholz, D.; Fuhs, N.; Hixson, M.; Akiyama, T. (Principal Investigator)

1979-01-01

The author has identified the following significant results. Data sets for corn, soybeans, winter wheat, and spring wheat were used to evaluate the following schemes for crop identification: (1) per point Gaussian maximum classifier; (2) per point sum of normal densities classifiers; (3) per point linear classifier; (4) per point Gaussian maximum likelihood decision tree classifiers; and (5) texture sensitive per field Gaussian maximum likelihood classifier. Test site location and classifier both had significant effects on classification accuracy of small grains; classifiers did not differ significantly in overall accuracy, with the majority of the difference among classifiers being attributed to training method rather than to the classification algorithm applied. The complexity of use and computer costs for the classifiers varied significantly. A linear classification rule which assigns each pixel to the class whose mean is closest in Euclidean distance was the easiest for the analyst and cost the least per classification.

On the Implementation of a Land Cover Classification System for SAR Images Using Khoros

NASA Technical Reports Server (NTRS)

Medina Revera, Edwin J.; Espinosa, Ramon Vasquez

1997-01-01

The Synthetic Aperture Radar (SAR) sensor is widely used to record data about the ground under all atmospheric conditions. The SAR acquired images have very good resolution which necessitates the development of a classification system that process the SAR images to extract useful information for different applications. In this work, a complete system for the land cover classification was designed and programmed using the Khoros, a data flow visual language environment, taking full advantages of the polymorphic data services that it provides. Image analysis was applied to SAR images to improve and automate the processes of recognition and classification of the different regions like mountains and lakes. Both unsupervised and supervised classification utilities were used. The unsupervised classification routines included the use of several Classification/Clustering algorithms like the K-means, ISO2, Weighted Minimum Distance, and the Localized Receptive Field (LRF) training/classifier. Different texture analysis approaches such as Invariant Moments, Fractal Dimension and Second Order statistics were implemented for supervised classification of the images. The results and conclusions for SAR image classification using the various unsupervised and supervised procedures are presented based on their accuracy and performance.

A comparative study of sequence- and structure-based features of small RNAs and other RNAs of bacteria.

PubMed

Barik, Amita; Das, Santasabuj

2018-01-02

Small RNAs (sRNAs) in bacteria have emerged as key players in transcriptional and post-transcriptional regulation of gene expression. Here, we present a statistical analysis of different sequence- and structure-related features of bacterial sRNAs to identify the descriptors that could discriminate sRNAs from other bacterial RNAs. We investigated a comprehensive and heterogeneous collection of 816 sRNAs, identified by northern blotting across 33 bacterial species and compared their various features with other classes of bacterial RNAs, such as tRNAs, rRNAs and mRNAs. We observed that sRNAs differed significantly from the rest with respect to G+C composition, normalized minimum free energy of folding, motif frequency and several RNA-folding parameters like base-pairing propensity, Shannon entropy and base-pair distance. Based on the selected features, we developed a predictive model using Random Forests (RF) method to classify the above four classes of RNAs. Our model displayed an overall predictive accuracy of 89.5%. These findings would help to differentiate bacterial sRNAs from other RNAs and further promote prediction of novel sRNAs in different bacterial species.

Detection of terrain indices related to soil salinity and mapping salt-affected soils using remote sensing and geostatistical techniques.

PubMed

Triki Fourati, Hela; Bouaziz, Moncef; Benzina, Mourad; Bouaziz, Samir

2017-04-01

Traditional surveying methods of soil properties over landscapes are dramatically cost and time-consuming. Thus, remote sensing is a proper choice for monitoring environmental problem. This research aims to study the effect of environmental factors on soil salinity and to map the spatial distribution of this salinity over the southern east part of Tunisia by means of remote sensing and geostatistical techniques. For this purpose, we used Advanced Spaceborne Thermal Emission and Reflection Radiometer data to depict geomorphological parameters: elevation, slope, plan curvature (PLC), profile curvature (PRC), and aspect. Pearson correlation between these parameters and soil electrical conductivity (EC soil ) showed that mainly slope and elevation affect the concentration of salt in soil. Moreover, spectral analysis illustrated the high potential of short-wave infrared (SWIR) bands to identify saline soils. To map soil salinity in southern Tunisia, ordinary kriging (OK), minimum distance (MD) classification, and simple regression (SR) were used. The findings showed that ordinary kriging technique provides the most reliable performances to identify and classify saline soils over the study area with a root mean square error of 1.83 and mean error of 0.018.

A semi-supervised classification algorithm using the TAD-derived background as training data

NASA Astrophysics Data System (ADS)

Fan, Lei; Ambeau, Brittany; Messinger, David W.

2013-05-01

In general, spectral image classification algorithms fall into one of two categories: supervised and unsupervised. In unsupervised approaches, the algorithm automatically identifies clusters in the data without a priori information about those clusters (except perhaps the expected number of them). Supervised approaches require an analyst to identify training data to learn the characteristics of the clusters such that they can then classify all other pixels into one of the pre-defined groups. The classification algorithm presented here is a semi-supervised approach based on the Topological Anomaly Detection (TAD) algorithm. The TAD algorithm defines background components based on a mutual k-Nearest Neighbor graph model of the data, along with a spectral connected components analysis. Here, the largest components produced by TAD are used as regions of interest (ROI's),or training data for a supervised classification scheme. By combining those ROI's with a Gaussian Maximum Likelihood (GML) or a Minimum Distance to the Mean (MDM) algorithm, we are able to achieve a semi supervised classification method. We test this classification algorithm against data collected by the HyMAP sensor over the Cooke City, MT area and University of Pavia scene.

Using Scribe to Select Fonts on the Penguin.

DTIC Science & Technology

1984-02-01

indicates several things about that font. The first segment of the name (for example, Helvetica or TimesRoman) may indicate its shape and form. The number...nesting mi0me Penguins wre classified in the phylum Chordat &. subohylum Vefletwa. ciMs Ayes, order Spheniciformee. family Sphenclae. *4xtiracted fromt...somtimes great distances--each fall to their nesting sites. Penguins are classified In thes phylum Chordate , subphylum Vertebrate, class Ave$, order

An automatic aerosol classification for earlinet: application and results

NASA Astrophysics Data System (ADS)

Papagiannopoulos, Nikolaos; Mona, Lucia; Amiridis, Vassilis; Binietoglou, Ioannis; D'Amico, Giuseppe; Guma-Claramunt, P.; Schwarz, Anja; Alados-Arboledas, Lucas; Amodeo, Aldo; Apituley, Arnoud; Baars, Holger; Bortoli, Daniele; Comeron, Adolfo; Guerrero-Rascado, Juan Luis; Kokkalis, Panos; Nicolae, Doina; Papayannis, Alex; Pappalardo, Gelsomina; Wandinger, Ulla; Wiegner, Matthias

2018-04-01

Aerosol typing is essential for understanding the impact of the different aerosol sources on climate, weather system and air quality. An aerosol classification method for EARLINET (European Aerosol Research Lidar Network) measurements is introduced which makes use the Mahalanobis distance classifier. The performance of the automatic classification is tested against manually classified EARLINET data. Results of the application of the method to an extensive aerosol dataset will be presented.

Fuzziness-based active learning framework to enhance hyperspectral image classification performance for discriminative and generative classifiers

PubMed Central

2018-01-01

Hyperspectral image classification with a limited number of training samples without loss of accuracy is desirable, as collecting such data is often expensive and time-consuming. However, classifiers trained with limited samples usually end up with a large generalization error. To overcome the said problem, we propose a fuzziness-based active learning framework (FALF), in which we implement the idea of selecting optimal training samples to enhance generalization performance for two different kinds of classifiers, discriminative and generative (e.g. SVM and KNN). The optimal samples are selected by first estimating the boundary of each class and then calculating the fuzziness-based distance between each sample and the estimated class boundaries. Those samples that are at smaller distances from the boundaries and have higher fuzziness are chosen as target candidates for the training set. Through detailed experimentation on three publically available datasets, we showed that when trained with the proposed sample selection framework, both classifiers achieved higher classification accuracy and lower processing time with the small amount of training data as opposed to the case where the training samples were selected randomly. Our experiments demonstrate the effectiveness of our proposed method, which equates favorably with the state-of-the-art methods. PMID:29304512

Graph distance for complex networks

NASA Astrophysics Data System (ADS)

Shimada, Yutaka; Hirata, Yoshito; Ikeguchi, Tohru; Aihara, Kazuyuki

2016-10-01

Networks are widely used as a tool for describing diverse real complex systems and have been successfully applied to many fields. The distance between networks is one of the most fundamental concepts for properly classifying real networks, detecting temporal changes in network structures, and effectively predicting their temporal evolution. However, this distance has rarely been discussed in the theory of complex networks. Here, we propose a graph distance between networks based on a Laplacian matrix that reflects the structural and dynamical properties of networked dynamical systems. Our results indicate that the Laplacian-based graph distance effectively quantifies the structural difference between complex networks. We further show that our approach successfully elucidates the temporal properties underlying temporal networks observed in the context of face-to-face human interactions.

Recognition of In-Vehicle Group Activities (iVGA): Phase-I, Feasibility Study

DTIC Science & Technology

2014-08-27

the driver is either adjusting his/her eyeglasses , adjusting his/her makeup, or possibly attempt to hiding his/her face from getting recognized. In...closest of two patterns measured based on hamming distance determine the best class representing a test pattern. Figure 61 presents the Hamming neural...symbols are different. In another way, it measures the minimum number of substitutions required to change one string into the other, or the minimum

Discrimination of malignant lymphomas and leukemia using Radon transform based-higher order spectra

NASA Astrophysics Data System (ADS)

Luo, Yi; Celenk, Mehmet; Bejai, Prashanth

2006-03-01

A new algorithm that can be used to automatically recognize and classify malignant lymphomas and leukemia is proposed in this paper. The algorithm utilizes the morphological watersheds to obtain boundaries of cells from cell images and isolate them from the surrounding background. The areas of cells are extracted from cell images after background subtraction. The Radon transform and higher-order spectra (HOS) analysis are utilized as an image processing tool to generate class feature vectors of different type cells and to extract testing cells' feature vectors. The testing cells' feature vectors are then compared with the known class feature vectors for a possible match by computing the Euclidean distances. The cell in question is classified as belonging to one of the existing cell classes in the least Euclidean distance sense.

Complex networks in the Euclidean space of communicability distances

NASA Astrophysics Data System (ADS)

Estrada, Ernesto

2012-06-01

We study the properties of complex networks embedded in a Euclidean space of communicability distances. The communicability distance between two nodes is defined as the difference between the weighted sum of walks self-returning to the nodes and the weighted sum of walks going from one node to the other. We give some indications that the communicability distance identifies the least crowded routes in networks where simultaneous submission of packages is taking place. We define an index Q based on communicability and shortest path distances, which allows reinterpreting the “small-world” phenomenon as the region of minimum Q in the Watts-Strogatz model. It also allows the classification and analysis of networks with different efficiency of spatial uses. Consequently, the communicability distance displays unique features for the analysis of complex networks in different scenarios.

The finite body triangulation: algorithms, subgraphs, homogeneity estimation and application.

PubMed

Carson, Cantwell G; Levine, Jonathan S

2016-09-01

The concept of a finite body Dirichlet tessellation has been extended to that of a finite body Delaunay 'triangulation' to provide a more meaningful description of the spatial distribution of nonspherical secondary phase bodies in 2- and 3-dimensional images. A finite body triangulation (FBT) consists of a network of minimum edge-to-edge distances between adjacent objects in a microstructure. From this is also obtained the characteristic object chords formed by the intersection of the object boundary with the finite body tessellation. These two sets of distances form the basis of a parsimonious homogeneity estimation. The characteristics of the spatial distribution are then evaluated with respect to the distances between objects and the distances within them. Quantitative analysis shows that more physically representative distributions can be obtained by selecting subgraphs, such as the relative neighbourhood graph and the minimum spanning tree, from the finite body tessellation. To demonstrate their potential, we apply these methods to 3-dimensional X-ray computed tomographic images of foamed cement and their 2-dimensional cross sections. The Python computer code used to estimate the FBT is made available. Other applications for the algorithm - such as porous media transport and crack-tip propagation - are also discussed. © 2016 The Authors Journal of Microscopy © 2016 Royal Microscopical Society.

Protein-protein interaction site predictions with minimum covariance determinant and Mahalanobis distance.

PubMed

Qiu, Zhijun; Zhou, Bo; Yuan, Jiangfeng

2017-11-21

Protein-protein interaction site (PPIS) prediction must deal with the diversity of interaction sites that limits their prediction accuracy. Use of proteins with unknown or unidentified interactions can also lead to missing interfaces. Such data errors are often brought into the training dataset. In response to these two problems, we used the minimum covariance determinant (MCD) method to refine the training data to build a predictor with better performance, utilizing its ability of removing outliers. In order to predict test data in practice, a method based on Mahalanobis distance was devised to select proper test data as input for the predictor. With leave-one-validation and independent test, after the Mahalanobis distance screening, our method achieved higher performance according to Matthews correlation coefficient (MCC), although only a part of test data could be predicted. These results indicate that data refinement is an efficient approach to improve protein-protein interaction site prediction. By further optimizing our method, it is hopeful to develop predictors of better performance and wide range of application. Copyright © 2017 Elsevier Ltd. All rights reserved.

Normative evaluation of blood banks in the Brazilian Amazon region in respect to the prevention of transfusion-transmitted malaria

PubMed Central

Freitas, Daniel Roberto Coradi; Duarte, Elisabeth Carmen

2014-01-01

Objective To evaluate blood banks in the Brazilian Amazon region with regard to structure and procedures directed toward the prevention of transfusion-transmitted malaria (TTM). Methods This was a normative evaluation based on the Brazilian National Health Surveillance Agency (ANVISA) Resolution RDC No. 153/2004. Ten blood banks were included in the study and classified as ‘adequate’ (≥80 points), ‘partially adequate’ (from 50 to 80 points), or ‘inadequate’ (<50 points). The following components were evaluated: ‘donor education’ (5 points), ‘clinical screening’ (40 points), ‘laboratory screening’ (40 points) and ‘hemovigilance’ (15 points). Results The overall median score was 49.8 (minimum = 16; maximum = 78). Five blood banks were classified as ‘inadequate’ and five as ‘partially adequate’. The median clinical screening score was 26 (minimum = 16; maximum = 32). The median laboratory screening score was 20 (minimum = 0; maximum = 32). Eight blood banks performed laboratory tests for malaria; six tested all donations. Seven used thick smears, but only one performed this procedure in accordance with Ministry of Health requirements. One service had a Program of External Quality Evaluation for malaria testing. With regard to hemovigilance, two institutions reported having procedures to detect cases of transfusion-transmitted malaria. Conclusion Malaria is neglected as a blood–borne disease in the blood banks of the Brazilian Amazon region. None of the institutions were classified as ‘adequate’ in the overall classification or with regard to clinical screening and laboratory screening. Blood bank professionals, the Ministry of Health and Health Surveillance service managers need to pay more attention to this matter so that the safety procedures required by law are complied with. PMID:25453648

An Improvement To The k-Nearest Neighbor Classifier For ECG Database

NASA Astrophysics Data System (ADS)

Jaafar, Haryati; Hidayah Ramli, Nur; Nasir, Aimi Salihah Abdul

2018-03-01

The k nearest neighbor (kNN) is a non-parametric classifier and has been widely used for pattern classification. However, in practice, the performance of kNN often tends to fail due to the lack of information on how the samples are distributed among them. Moreover, kNN is no longer optimal when the training samples are limited. Another problem observed in kNN is regarding the weighting issues in assigning the class label before classification. Thus, to solve these limitations, a new classifier called Mahalanobis fuzzy k-nearest centroid neighbor (MFkNCN) is proposed in this study. Here, a Mahalanobis distance is applied to avoid the imbalance of samples distribition. Then, a surrounding rule is employed to obtain the nearest centroid neighbor based on the distributions of training samples and its distance to the query point. Consequently, the fuzzy membership function is employed to assign the query point to the class label which is frequently represented by the nearest centroid neighbor Experimental studies from electrocardiogram (ECG) signal is applied in this study. The classification performances are evaluated in two experimental steps i.e. different values of k and different sizes of feature dimensions. Subsequently, a comparative study of kNN, kNCN, FkNN and MFkCNN classifier is conducted to evaluate the performances of the proposed classifier. The results show that the performance of MFkNCN consistently exceeds the kNN, kNCN and FkNN with the best classification rates of 96.5%.

The Application of Speaker Recognition Techniques in the Detection of Tsunamigenic Earthquakes

NASA Astrophysics Data System (ADS)

Gorbatov, A.; O'Connell, J.; Paliwal, K.

2015-12-01

Tsunami warning procedures adopted by national tsunami warning centres largely rely on the classical approach of earthquake location, magnitude determination, and the consequent modelling of tsunami waves. Although this approach is based on known physics theories of earthquake and tsunami generation processes, this may be the main shortcoming due to the need to satisfy minimum seismic data requirement to estimate those physical parameters. At least four seismic stations are necessary to locate the earthquake and a minimum of approximately 10 minutes of seismic waveform observation to reliably estimate the magnitude of a large earthquake similar to the 2004 Indian Ocean Tsunami Earthquake of M9.2. Consequently the total time to tsunami warning could be more than half an hour. In attempt to reduce the time of tsunami alert a new approach is proposed based on the classification of tsunamigenic and non tsunamigenic earthquakes using speaker recognition techniques. A Tsunamigenic Dataset (TGDS) was compiled to promote the development of machine learning techniques for application to seismic trace analysis and, in particular, tsunamigenic event detection, and compare them to existing seismological methods. The TGDS contains 227 off shore events (87 tsunamigenic and 140 non-tsunamigenic earthquakes with M≥6) from Jan 2000 to Dec 2011, inclusive. A Support Vector Machine classifier using a radial-basis function kernel was applied to spectral features derived from 400 sec frames of 3-comp. 1-Hz broadband seismometer data. Ten-fold cross-validation was used during training to choose classifier parameters. Voting was applied to the classifier predictions provided from each station to form an overall prediction for an event. The F1 score (harmonic mean of precision and recall) was chosen to rate each classifier as it provides a compromise between type-I and type-II errors, and due to the imbalance between the representative number of events in the tsunamigenic and non-tsunamigenic classes. The described classifier achieved an F1 score of 0.923, with tsunamigenic classification precision and recall/sensitivity of 0.928 and 0.919 respectively. The system requires a minimum of 3 stations with ~400 seconds of data each to make a prediction. The accuracy improves as further stations and data become available.

Generalising Ward's Method for Use with Manhattan Distances.

PubMed

Strauss, Trudie; von Maltitz, Michael Johan

2017-01-01

The claim that Ward's linkage algorithm in hierarchical clustering is limited to use with Euclidean distances is investigated. In this paper, Ward's clustering algorithm is generalised to use with l1 norm or Manhattan distances. We argue that the generalisation of Ward's linkage method to incorporate Manhattan distances is theoretically sound and provide an example of where this method outperforms the method using Euclidean distances. As an application, we perform statistical analyses on languages using methods normally applied to biology and genetic classification. We aim to quantify differences in character traits between languages and use a statistical language signature based on relative bi-gram (sequence of two letters) frequencies to calculate a distance matrix between 32 Indo-European languages. We then use Ward's method of hierarchical clustering to classify the languages, using the Euclidean distance and the Manhattan distance. Results obtained from using the different distance metrics are compared to show that the Ward's algorithm characteristic of minimising intra-cluster variation and maximising inter-cluster variation is not violated when using the Manhattan metric.

An ultra low power feature extraction and classification system for wearable seizure detection.

PubMed

Page, Adam; Pramod Tim Oates, Siddharth; Mohsenin, Tinoosh

2015-01-01

In this paper we explore the use of a variety of machine learning algorithms for designing a reliable and low-power, multi-channel EEG feature extractor and classifier for predicting seizures from electroencephalographic data (scalp EEG). Different machine learning classifiers including k-nearest neighbor, support vector machines, naïve Bayes, logistic regression, and neural networks are explored with the goal of maximizing detection accuracy while minimizing power, area, and latency. The input to each machine learning classifier is a 198 feature vector containing 9 features for each of the 22 EEG channels obtained over 1-second windows. All classifiers were able to obtain F1 scores over 80% and onset sensitivity of 100% when tested on 10 patients. Among five different classifiers that were explored, logistic regression (LR) proved to have minimum hardware complexity while providing average F-1 score of 91%. Both ASIC and FPGA implementations of logistic regression are presented and show the smallest area, power consumption, and the lowest latency when compared to the previous work.

49 CFR 192.735 - Compressor stations: Storage of combustible materials.

Code of Federal Regulations, 2010 CFR

2010-10-01

... SAFETY TRANSPORTATION OF NATURAL AND OTHER GAS BY PIPELINE: MINIMUM FEDERAL SAFETY STANDARDS Maintenance... buildings, must be stored a safe distance from the compressor building. (b) Aboveground oil or gasoline...

27 CFR 555.206 - Location of magazines.

Code of Federal Regulations, 2013 CFR

2013-04-01

... in the table of distances for storage of explosive materials in § 555.218. (2) Ammonium nitrate and... for the separation of ammonium nitrate and blasting agents in § 555.220. However, the minimum...

27 CFR 555.206 - Location of magazines.

Code of Federal Regulations, 2014 CFR

2014-04-01

... in the table of distances for storage of explosive materials in § 555.218. (2) Ammonium nitrate and... for the separation of ammonium nitrate and blasting agents in § 555.220. However, the minimum...

27 CFR 555.206 - Location of magazines.

Code of Federal Regulations, 2011 CFR

2011-04-01

... in the table of distances for storage of explosive materials in § 555.218. (2) Ammonium nitrate and... for the separation of ammonium nitrate and blasting agents in § 555.220. However, the minimum...

27 CFR 555.206 - Location of magazines.

Code of Federal Regulations, 2012 CFR

2012-04-01

... in the table of distances for storage of explosive materials in § 555.218. (2) Ammonium nitrate and... for the separation of ammonium nitrate and blasting agents in § 555.220. However, the minimum...

Detection of Epileptic Seizure Event and Onset Using EEG

PubMed Central

Ahammad, Nabeel; Fathima, Thasneem; Joseph, Paul

2014-01-01

This study proposes a method of automatic detection of epileptic seizure event and onset using wavelet based features and certain statistical features without wavelet decomposition. Normal and epileptic EEG signals were classified using linear classifier. For seizure event detection, Bonn University EEG database has been used. Three types of EEG signals (EEG signal recorded from healthy volunteer with eye open, epilepsy patients in the epileptogenic zone during a seizure-free interval, and epilepsy patients during epileptic seizures) were classified. Important features such as energy, entropy, standard deviation, maximum, minimum, and mean at different subbands were computed and classification was done using linear classifier. The performance of classifier was determined in terms of specificity, sensitivity, and accuracy. The overall accuracy was 84.2%. In the case of seizure onset detection, the database used is CHB-MIT scalp EEG database. Along with wavelet based features, interquartile range (IQR) and mean absolute deviation (MAD) without wavelet decomposition were extracted. Latency was used to study the performance of seizure onset detection. Classifier gave a sensitivity of 98.5% with an average latency of 1.76 seconds. PMID:24616892

Dual tasking negatively impacts obstacle avoidance abilities in post-stroke individuals with visuospatial neglect: Task complexity matters!

PubMed

Aravind, Gayatri; Lamontagne, Anouk

2017-01-01

Persons with perceptual-attentional deficits due to visuospatial neglect (VSN) after a stroke are at a risk of collisions while walking in the presence of moving obstacles. The attentional burden of performing a dual-task may further compromise their obstacle avoidance performance, putting them at a greater risk of collisions. The objective of this study was to compare the ability of persons with (VSN+) and without VSN (VSN-) to dual task while negotiating moving obstacles. Twenty-six stroke survivors (13 VSN+, 13 VSN-) were assessed on their ability to (a) negotiate moving obstacles while walking (locomotor single task); (b) perform a pitch-discrimination task (cognitive single task) and (c) simultaneously perform the walking and cognitive tasks (dual task). We compared the groups on locomotor (collision rates, minimum distance from obstacle and onset of strategies) and cognitive (error rates) outcomes. For both single and dual task walking, VSN+ individuals showed higher collision rates compared to VSN- individuals. Dual tasking caused deterioration of locomotor (more collisions, delayed onset and smaller minimum distances) and cognitive performances (higher error rate) in VSN+ individuals. Contrastingly, VSN- individuals maintained collision rates, increased minimum distance, but showed more cognitive errors, prioritizing their locomotor performance. Individuals with VSN demonstrate cognitive-locomotor interference under dual task conditions, which could severely compromise safety when ambulating in community environments and may explain the poor recovery of independent community ambulation in these individuals.

A Minimum Spanning Forest Based Method for Noninvasive Cancer Detection with Hyperspectral Imaging

PubMed Central

Pike, Robert; Lu, Guolan; Wang, Dongsheng; Chen, Zhuo Georgia; Fei, Baowei

2016-01-01

Goal The purpose of this paper is to develop a classification method that combines both spectral and spatial information for distinguishing cancer from healthy tissue on hyperspectral images in an animal model. Methods An automated algorithm based on a minimum spanning forest (MSF) and optimal band selection has been proposed to classify healthy and cancerous tissue on hyperspectral images. A support vector machine (SVM) classifier is trained to create a pixel-wise classification probability map of cancerous and healthy tissue. This map is then used to identify markers that are used to compute mutual information for a range of bands in the hyperspectral image and thus select the optimal bands. An MSF is finally grown to segment the image using spatial and spectral information. Conclusion The MSF based method with automatically selected bands proved to be accurate in determining the tumor boundary on hyperspectral images. Significance Hyperspectral imaging combined with the proposed classification technique has the potential to provide a noninvasive tool for cancer detection. PMID:26285052

Contributions of long-distance dispersal to population growth in colonising Pinus ponderosa populations.

PubMed

Lesser, Mark R; Jackson, Stephen T

2013-03-01

Long-distance dispersal is an integral part of plant species migration and population development. We aged and genotyped 1125 individuals in four disjunct populations of Pinus ponderosa that were initially established by long-distance dispersal in the 16th and 17th centuries. Parentage analysis was used to determine if individuals were the product of local reproductive events (two parents present), long-distance pollen dispersal (one parent present) or long-distance seed dispersal (no parents present). All individuals established in the first century at each site were the result of long-distance dispersal. Individuals reproduced at younger ages with increasing age of the overall population. These results suggest Allee effects, where populations were initially unable to expand on their own, and were dependent on long-distance dispersal to overcome a minimum-size threshold. Our results demonstrate that long-distance dispersal was not only necessary for initial colonisation but also to sustain subsequent population growth during early phases of expansion. © 2012 Blackwell Publishing Ltd/CNRS.

New method for estimating low-earth-orbit collision probabilities

NASA Technical Reports Server (NTRS)

Vedder, John D.; Tabor, Jill L.

1991-01-01

An unconventional but general method is described for estimating the probability of collision between an earth-orbiting spacecraft and orbital debris. This method uses a Monte Caralo simulation of the orbital motion of the target spacecraft and each discrete debris object to generate an empirical set of distances, each distance representing the separation between the spacecraft and the nearest debris object at random times. Using concepts from the asymptotic theory of extreme order statistics, an analytical density function is fitted to this set of minimum distances. From this function, it is possible to generate realistic collision estimates for the spacecraft.

Application of up-sampling and resolution scaling to Fresnel reconstruction of digital holograms.

PubMed

Williams, Logan A; Nehmetallah, Georges; Aylo, Rola; Banerjee, Partha P

2015-02-20

Fresnel transform implementation methods using numerical preprocessing techniques are investigated in this paper. First, it is shown that up-sampling dramatically reduces the minimum reconstruction distance requirements and allows maximal signal recovery by eliminating aliasing artifacts which typically occur at distances much less than the Rayleigh range of the object. Second, zero-padding is employed to arbitrarily scale numerical resolution for the purpose of resolution matching multiple holograms, where each hologram is recorded using dissimilar geometric or illumination parameters. Such preprocessing yields numerical resolution scaling at any distance. Both techniques are extensively illustrated using experimental results.

Neuro-ergonomic Research for Online Assessment of Cognitive Workload

DTIC Science & Technology

2011-10-01

computer interface (BCI) and medical diagnoses areas. In [65], Kullback - Leibler (KL) divergence was used in the classification 39 of raw EEG signals. It...the features for each EEG channel recorded, and then compared the effectiveness of each feature using a Kruskal-Wallis test . Table 1 lists the...and the KL-distance 5-NN classifier), using different sets of activities. The feature vector and distance measures were tested in pairwise

Intelligent query by humming system based on score level fusion of multiple classifiers

NASA Astrophysics Data System (ADS)

Pyo Nam, Gi; Thu Trang Luong, Thi; Ha Nam, Hyun; Ryoung Park, Kang; Park, Sung-Joo

2011-12-01

Recently, the necessity for content-based music retrieval that can return results even if a user does not know information such as the title or singer has increased. Query-by-humming (QBH) systems have been introduced to address this need, as they allow the user to simply hum snatches of the tune to find the right song. Even though there have been many studies on QBH, few have combined multiple classifiers based on various fusion methods. Here we propose a new QBH system based on the score level fusion of multiple classifiers. This research is novel in the following three respects: three local classifiers [quantized binary (QB) code-based linear scaling (LS), pitch-based dynamic time warping (DTW), and LS] are employed; local maximum and minimum point-based LS and pitch distribution feature-based LS are used as global classifiers; and the combination of local and global classifiers based on the score level fusion by the PRODUCT rule is used to achieve enhanced matching accuracy. Experimental results with the 2006 MIREX QBSH and 2009 MIR-QBSH corpus databases show that the performance of the proposed method is better than that of single classifier and other fusion methods.

Unsupervised classification of surface defects in wire rod production obtained by eddy current sensors.

PubMed

Saludes-Rodil, Sergio; Baeyens, Enrique; Rodríguez-Juan, Carlos P

2015-04-29

An unsupervised approach to classify surface defects in wire rod manufacturing is developed in this paper. The defects are extracted from an eddy current signal and classified using a clustering technique that uses the dynamic time warping distance as the dissimilarity measure. The new approach has been successfully tested using industrial data. It is shown that it outperforms other classification alternatives, such as the modified Fourier descriptors.

Using self-organizing maps to classify humpback whale song units and quantify their similarity.

PubMed

Allen, Jenny A; Murray, Anita; Noad, Michael J; Dunlop, Rebecca A; Garland, Ellen C

2017-10-01

Classification of vocal signals can be undertaken using a wide variety of qualitative and quantitative techniques. Using east Australian humpback whale song from 2002 to 2014, a subset of vocal signals was acoustically measured and then classified using a Self-Organizing Map (SOM). The SOM created (1) an acoustic dictionary of units representing the song's repertoire, and (2) Cartesian distance measurements among all unit types (SOM nodes). Utilizing the SOM dictionary as a guide, additional song recordings from east Australia were rapidly (manually) transcribed. To assess the similarity in song sequences, the Cartesian distance output from the SOM was applied in Levenshtein distance similarity analyses as a weighting factor to better incorporate unit similarity in the calculation (previously a qualitative process). SOMs provide a more robust and repeatable means of categorizing acoustic signals along with a clear quantitative measurement of sound type similarity based on acoustic features. This method can be utilized for a wide variety of acoustic databases especially those containing very large datasets and can be applied across the vocalization research community to help address concerns surrounding inconsistency in manual classification.

The Variance of Solar Wind Magnetic Fluctuations: Solutions and Further Puzzles

NASA Technical Reports Server (NTRS)

Roberts, D. A.; Goldstein, M. L.

2006-01-01

We study the dependence of the variance directions of the magnetic field in the solar wind as a function of scale, radial distance, and Alfvenicity. The study resolves the question of why different studies have arrived at widely differing values for the maximum to minimum power (approximately equal to 3:1 up to approximately equal to 20:1). This is due to the decreasing anisotropy with increasing time interval chosen for the variance, and is a direct result of the "spherical polarization" of the waves which follows from the near constancy of |B|. The reason for the magnitude preserving evolution is still unresolved. Moreover, while the long-known tendency for the minimum variance to lie along the mean field also follows from this view (as shown by Barnes many years ago), there is no theory for why the minimum variance follows the field direction as the Parker angle changes. We show that this turning is quite generally true in Alfvenic regions over a wide range of heliocentric distances. The fact that nonAlfvenic regions, while still showing strong power anisotropies, tend to have a much broader range of angles between the minimum variance and the mean field makes it unlikely that the cause of the variance turning is to be found in a turbulence mechanism. There are no obvious alternative mechanisms, leaving us with another intriguing puzzle.

Modified fuzzy c-means applied to a Bragg grating-based spectral imager for material clustering

NASA Astrophysics Data System (ADS)

Rodríguez, Aida; Nieves, Juan Luis; Valero, Eva; Garrote, Estíbaliz; Hernández-Andrés, Javier; Romero, Javier

2012-01-01

We have modified the Fuzzy C-Means algorithm for an application related to segmentation of hyperspectral images. Classical fuzzy c-means algorithm uses Euclidean distance for computing sample membership to each cluster. We have introduced a different distance metric, Spectral Similarity Value (SSV), in order to have a more convenient similarity measure for reflectance information. SSV distance metric considers both magnitude difference (by the use of Euclidean distance) and spectral shape (by the use of Pearson correlation). Experiments confirmed that the introduction of this metric improves the quality of hyperspectral image segmentation, creating spectrally more dense clusters and increasing the number of correctly classified pixels.

Do school classrooms meet the visual requirements of children and recommended vision standards?

PubMed

Negiloni, Kalpa; Ramani, Krishna Kumar; Sudhir, Rachapalle Reddi

2017-01-01

Visual demands of school children tend to vary with diverse classroom environments. The study aimed to evaluate the distance and near Visual Acuity (VA) demand in Indian school classrooms and their comparison with the recommended vision standards. The distance and near VA demands were assessed in 33 classrooms (grades 4 to 12) of eight schools. The VA threshold demand relied on the smallest size of distance and near visual task material and viewing distance. The logMAR equivalents of minimum VA demand at specific seating positions (desk) and among different grades were evaluated. The near threshold was converted into actual near VA demand by including the acuity reserve. The existing dimensions of chalkboard and classroom, gross area in a classroom per student and class size in all the measured classrooms were compared to the government recommended standards. In 33 classrooms assessed (35±10 students per room), the average distance and near logMAR VA threshold demand was 0.31±0.17 and 0.44±0.14 respectively. The mean distance VA demand (minimum) in front desk position was 0.56±0.18 logMAR. Increased distance threshold demand (logMAR range -0.06, 0.19) was noted in 7 classrooms (21%). The mean VA demand in grades 4 to 8 and grades 9 to 12 was 0.35±0.16 and 0.24±0.16 logMAR respectively and the difference was not statistically significant (p = 0.055). The distance from board to front desk was greater than the recommended standard of 2.2m in 27 classrooms (82%). The other measured parameters were noted to be different from the proposed standards in majority of the classrooms. The study suggests the inclusion of task demand assessment in school vision screening protocol to provide relevant guidance to school authorities. These findings can serve as evidence to accommodate children with mild to moderate visual impairment in the regular classrooms.

Optimizing the Launch of a Projectile to Hit a Target

NASA Astrophysics Data System (ADS)

Mungan, Carl E.

2017-12-01

Some teenagers are exploring the outer perimeter of a castle. They notice a spy hole in its wall, across the moat a horizontal distance x and vertically up the wall a distance y. They decide to throw pebbles at the hole. One girl wants to use physics to throw with the minimum speed necessary to hit the hole. What is the required launch speed v and launch angle θ above the horizontal?

A new approach to keratoconus detection based on corneal morphogeometric analysis

PubMed Central

Bataille, Laurent; Fernández-Pacheco, Daniel G.; Cañavate, Francisco J. F.; Alió, Jorge L.

2017-01-01

Purpose To characterize corneal structural changes in keratoconus using a new morphogeometric approach and to evaluate its potential diagnostic ability. Methods Comparative study including 464 eyes of 464 patients (age, 16 and 72 years) divided into two groups: control group (143 healthy eyes) and keratoconus group (321 keratoconus eyes). Topographic information (Sirius, CSO, Italy) was processed with SolidWorks v2012 and a solid model representing the geometry of each cornea was generated. The following parameters were defined: anterior (Aant) and posterior (Apost) corneal surface areas, area of the cornea within the sagittal plane passing through the Z axis and the apex (Aapexant, Aapexpost) and minimum thickness points (Amctant, Amctpost) of the anterior and posterior corneal surfaces, and average distance from the Z axis to the apex (Dapexant, Dapexpost) and minimum thickness points (Dmctant, Dmctpost) of both corneal surfaces. Results Significant differences among control and keratoconus group were found in Aapexant, Aapexpost, Amctant, Amctpost, Dapexant, Dapexpost (all p<0.001), Apost (p = 0.014), and Dmctpost (p = 0.035). Significant correlations in keratoconus group were found between Aant and Apost (r = 0.836), Amctant and Amctpost (r = 0.983), and Dmctant and Dmctpost (r = 0.954, all p<0.001). A logistic regression analysis revealed that the detection of keratoconus grade I (Amsler Krumeich) was related to Apost, Atot, Aapexant, Amctant, Amctpost, Dapexpost, Dmctant and Dmctpost (Hosmer-Lemeshow: p>0.05, R2 Nagelkerke: 0.926). The overall percentage of cases correctly classified by the model was 97.30%. Conclusions Our morphogeometric approach based on the analysis of the cornea as a solid is useful for the characterization and detection of keratoconus. PMID:28886157

Analysis of C-shaped canal systems in mandibular second molars using surgical operating microscope and cone beam computed tomography: A clinical approach.

PubMed

Chhabra, Sanjay; Yadav, Seema; Talwar, Sangeeta

2014-05-01

The study was aimed to acquire better understanding of C-shaped canal systems in mandibular second molar teeth through a clinical approach using sophisticated techniques such as surgical operating microscope and cone beam computed tomography (CBCT). A total of 42 extracted mandibular second molar teeth with fused roots and longitudinal grooves were collected randomly from native Indian population. Pulp chamber floors of all specimens were examined under surgical operating microscope and classified into four types (Min's method). Subsequently, samples were subjected to CBCT scan after insertion of K-files size #10 or 15 into each canal orifice and evaluated using the cross-sectional and 3-dimensional images in consultation with dental radiologist so as to obtain more accurate results. Minimum distance between the external root surface on the groove and initial file placed in the canal was also measured at different levels and statistically analyzed. Out of 42 teeth, maximum number of samples (15) belonged to Type-II category. A total of 100 files were inserted in 86 orifices of various types of specimens. Evaluation of the CBCT scan images of the teeth revealed that a total of 21 canals were missing completely or partially at different levels. The mean values for the minimum thickness were highest at coronal followed by middle and apical third levels in all the categories. Lowest values were obtained for teeth with Type-III category at all three levels. The present study revealed anatomical variations of C-shaped canal system in mandibular second molars. The prognosis of such complex canal anatomies can be improved by simultaneous employment of modern techniques such as surgical operating microscope and CBCT.

10 CFR 1046.14 - Access authorization.

Code of Federal Regulations, 2010 CFR

2010-01-01

... authorization for the highest level of classified matter to which they potentially have access. Security police... by the site security organization and approved by the Head of the Field Element. Security police officers shall possess a minimum of an “L” or DOE Secret access authorization. Security police officers...

Data preprocessing methods of FT-NIR spectral data for the classification cooking oil

NASA Astrophysics Data System (ADS)

Ruah, Mas Ezatul Nadia Mohd; Rasaruddin, Nor Fazila; Fong, Sim Siong; Jaafar, Mohd Zuli

2014-12-01

This recent work describes the data pre-processing method of FT-NIR spectroscopy datasets of cooking oil and its quality parameters with chemometrics method. Pre-processing of near-infrared (NIR) spectral data has become an integral part of chemometrics modelling. Hence, this work is dedicated to investigate the utility and effectiveness of pre-processing algorithms namely row scaling, column scaling and single scaling process with Standard Normal Variate (SNV). The combinations of these scaling methods have impact on exploratory analysis and classification via Principle Component Analysis plot (PCA). The samples were divided into palm oil and non-palm cooking oil. The classification model was build using FT-NIR cooking oil spectra datasets in absorbance mode at the range of 4000cm-1-14000cm-1. Savitzky Golay derivative was applied before developing the classification model. Then, the data was separated into two sets which were training set and test set by using Duplex method. The number of each class was kept equal to 2/3 of the class that has the minimum number of sample. Then, the sample was employed t-statistic as variable selection method in order to select which variable is significant towards the classification models. The evaluation of data pre-processing were looking at value of modified silhouette width (mSW), PCA and also Percentage Correctly Classified (%CC). The results show that different data processing strategies resulting to substantial amount of model performances quality. The effects of several data pre-processing i.e. row scaling, column standardisation and single scaling process with Standard Normal Variate indicated by mSW and %CC. At two PCs model, all five classifier gave high %CC except Quadratic Distance Analysis.

Mediagraphy: Print and Nonprint Resources.

ERIC Educational Resources Information Center

Educational Media and Technology Yearbook, 1998

1998-01-01

Lists educational media-related journals, books, ERIC documents, journal articles, and nonprint resources classified by Artificial Intelligence, Robotics, Electronic Performance Support Systems; Computer-Assisted Instruction; Distance Education; Educational Research; Educational Technology; Electronic Publishing; Information Science and…

Spectral Properties and Variability of BIS objects

NASA Astrophysics Data System (ADS)

Gaudenzi, S.; Nesci, R.; Rossi, C.; Sclavi, S.; Gigoyan, K. S.; Mickaelian, A. M.

2017-10-01

Through the analysis and interpretation of newly obtained and of literature data we have clarified the nature of poorly investigated IRAS point sources classified as late type stars, belonging to the Byurakan IRAS Stars catalog. From medium resolution spectroscopy of 95 stars we have strongly revised 47 spectral types and newly classified 31 sources. Nine stars are of G or K types, four are N carbon stars in the Asymptotic Giant Branch, the others being M-type stars. From literature and new photometric observations we have studied their variability behaviour. For the regular variables we determined distances, absolute magnitudes and mass loss rates. For the other stars we estimated the distances, ranging between 1.3 and 10 kpc with a median of 2.8 kpc from the galactic plane, indicating that BIS stars mostly belong to the halo population.

Madurese cultural communication approach

NASA Astrophysics Data System (ADS)

Dharmawan, A.; Aji, G. G.; Mutiah

2018-01-01

Madura is a tribe with a cultural entity influenced by the ecological aspect and Madurese people. Assessing Madurese culture cannot be separated from the relation of society and ecological aspects that form the characteristics of Madura culture. Stereotypes of Madurese include a stubborn attitude, and carok or killing as a problem solving. On the other hand, Madurese are known to be inclusive, religious, and hardworking. The basic assumption is that the ecological conditions in Madura also shape the social and cultural life of the Madurese. Therefore, judging the Madurese cannot just be seen from a single event only. Moreover, the assessment only focuses on Madurese violence and disregards their structure and social aspects. Assessing Madura culture as a whole can explain the characteristics of Madurese community. According Hofstede culture is a characteristic mindset and perspective of individuals or groups of society in addressing a distinguished life. These differences distinguish individuals from others, or one country to the other. According to Hofstede to be able to assess the culture can be explained by four dimensions namely, individualism-collectivism, uncertainty avoidance, masculinity-femininity and power distance. The method used in this research is a case study. The Result is Madurese classified collectivism can be viewed from the pattern of settlements called kampong meji. Madurese can be classified into low and high uncertainty avoidance. the power distance for the Madurese is classified as unequally or there is a distance of power based on social groups. The element of masculinity of the Madurese is shown to be found when the earnestness of work.

Handwritten document age classification based on handwriting styles

NASA Astrophysics Data System (ADS)

Ramaiah, Chetan; Kumar, Gaurav; Govindaraju, Venu

2012-01-01

Handwriting styles are constantly changing over time. We approach the novel problem of estimating the approximate age of Historical Handwritten Documents using Handwriting styles. This system will have many applications in handwritten document processing engines where specialized processing techniques can be applied based on the estimated age of the document. We propose to learn a distribution over styles across centuries using Topic Models and to apply a classifier over weights learned in order to estimate the approximate age of the documents. We present a comparison of different distance metrics such as Euclidean Distance and Hellinger Distance within this application.

The minimum test battery to screen for binocular vision anomalies: report 3 of the BAND study.

PubMed

Hussaindeen, Jameel Rizwana; Rakshit, Archayeeta; Singh, Neeraj Kumar; Swaminathan, Meenakshi; George, Ronnie; Kapur, Suman; Scheiman, Mitchell; Ramani, Krishna Kumar

2018-03-01

This study aims to report the minimum test battery needed to screen non-strabismic binocular vision anomalies (NSBVAs) in a community set-up. When large numbers are to be screened we aim to identify the most useful test battery when there is no opportunity for a more comprehensive and time-consuming clinical examination. The prevalence estimates and normative data for binocular vision parameters were estimated from the Binocular Vision Anomalies and Normative Data (BAND) study, following which cut-off estimates and receiver operating characteristic curves to identify the minimum test battery have been plotted. In the receiver operating characteristic phase of the study, children between nine and 17 years of age were screened in two schools in the rural arm using the minimum test battery, and the prevalence estimates with the minimum test battery were found. Receiver operating characteristic analyses revealed that near point of convergence with penlight and red filter (> 7.5 cm), monocular accommodative facility (< 10 cycles per minute), and the difference between near and distance phoria (> 1.25 prism dioptres) were significant factors with cut-off values for best sensitivity and specificity. This minimum test battery was applied to a cohort of 305 children. The mean (standard deviation) age of the subjects was 12.7 (two) years with 121 males and 184 females. Using the minimum battery of tests obtained through the receiver operating characteristic analyses, the prevalence of NSBVAs was found to be 26 per cent. Near point of convergence with penlight and red filter > 10 cm was found to have the highest sensitivity (80 per cent) and specificity (73 per cent) for the diagnosis of convergence insufficiency. For the diagnosis of accommodative infacility, monocular accommodative facility with a cut-off of less than seven cycles per minute was the best predictor for screening (92 per cent sensitivity and 90 per cent specificity). The minimum test battery of near point of convergence with penlight and red filter, difference between distance and near phoria, and monocular accommodative facility yield good sensitivity and specificity for diagnosis of NSBVAs in a community set-up. © 2017 Optometry Australia.

An information-based network approach for protein classification

PubMed Central

Wan, Xiaogeng; Zhao, Xin; Yau, Stephen S. T.

2017-01-01

Protein classification is one of the critical problems in bioinformatics. Early studies used geometric distances and polygenetic-tree to classify proteins. These methods use binary trees to present protein classification. In this paper, we propose a new protein classification method, whereby theories of information and networks are used to classify the multivariate relationships of proteins. In this study, protein universe is modeled as an undirected network, where proteins are classified according to their connections. Our method is unsupervised, multivariate, and alignment-free. It can be applied to the classification of both protein sequences and structures. Nine examples are used to demonstrate the efficiency of our new method. PMID:28350835

Comparison Analysis of Recognition Algorithms of Forest-Cover Objects on Hyperspectral Air-Borne and Space-Borne Images

NASA Astrophysics Data System (ADS)

Kozoderov, V. V.; Kondranin, T. V.; Dmitriev, E. V.

2017-12-01

The basic model for the recognition of natural and anthropogenic objects using their spectral and textural features is described in the problem of hyperspectral air-borne and space-borne imagery processing. The model is based on improvements of the Bayesian classifier that is a computational procedure of statistical decision making in machine-learning methods of pattern recognition. The principal component method is implemented to decompose the hyperspectral measurements on the basis of empirical orthogonal functions. Application examples are shown of various modifications of the Bayesian classifier and Support Vector Machine method. Examples are provided of comparing these classifiers and a metrical classifier that operates on finding the minimal Euclidean distance between different points and sets in the multidimensional feature space. A comparison is also carried out with the " K-weighted neighbors" method that is close to the nonparametric Bayesian classifier.

Nucleation theory with delayed interactions: An application to the early stages of the receptor-mediated adhesion/fusion kinetics of lipid vesicles

NASA Astrophysics Data System (ADS)

Raudino, Antonio; Pannuzzo, Martina

2010-01-01

A semiquantitative theory aimed to describe the adhesion kinetics between soft objects, such as living cells or vesicles, has been developed. When rigid bodies are considered, the adhesion kinetics is successfully described by the classical Derjaguin, Landau, Verwey, and Overbeek (DLVO) picture, where the energy profile of two approaching bodies is given by a two asymmetrical potential wells separated by a barrier. The transition probability from the long-distance to the short-distance minimum defines the adhesion rate. Conversely, soft bodies might follow a different pathway to reach the short-distance minimum: thermally excited fluctuations give rise to local protrusions connecting the approaching bodies. These transient adhesion sites are stabilized by short-range adhesion forces (e.g., ligand-receptor interactions between membranes brought at contact distance), while they are destabilized both by repulsive forces and by the elastic deformation energy. Above a critical area of the contact site, the adhesion forces prevail: the contact site grows in size until the complete adhesion of the two bodies inside a short-distance minimum is attained. This nucleation mechanism has been developed in the framework of a nonequilibrium Fokker-Planck picture by considering both the adhesive patch growth and dissolution processes. In addition, we also investigated the effect of the ligand-receptor pairing kinetics at the adhesion site in the time course of the patch expansion. The ratio between the ligand-receptor pairing kinetics and the expansion rate of the adhesion site is of paramount relevance in determining the overall nucleation rate. The theory enables one to self-consistently include both thermodynamics (energy barrier height) and dynamic (viscosity) parameters, giving rise in some limiting cases to simple analytical formulas. The model could be employed to rationalize fusion kinetics between vesicles, provided the short-range adhesion transition is the rate-limiting step to the whole adhesion process. Approximate relationships between the experimental fusion rates reported in the literature and parameters such as membrane elastic bending modulus, repulsion strength, temperature, osmotic forces, ligand-receptor binding energy, solvent and membrane viscosities are satisfactory explained by our model. The present results hint a possible role of the initial long-distance→short-distance transition in determining the whole fusion kinetics.

The effect of different distance measures in detecting outliers using clustering-based algorithm for circular regression model

NASA Astrophysics Data System (ADS)

Di, Nur Faraidah Muhammad; Satari, Siti Zanariah

2017-05-01

Outlier detection in linear data sets has been done vigorously but only a small amount of work has been done for outlier detection in circular data. In this study, we proposed multiple outliers detection in circular regression models based on the clustering algorithm. Clustering technique basically utilizes distance measure to define distance between various data points. Here, we introduce the similarity distance based on Euclidean distance for circular model and obtain a cluster tree using the single linkage clustering algorithm. Then, a stopping rule for the cluster tree based on the mean direction and circular standard deviation of the tree height is proposed. We classify the cluster group that exceeds the stopping rule as potential outlier. Our aim is to demonstrate the effectiveness of proposed algorithms with the similarity distances in detecting the outliers. It is found that the proposed methods are performed well and applicable for circular regression model.

Exploiting Sparsity in Hyperspectral Image Classification via Graphical Models

DTIC Science & Technology

2013-05-01

distribution p by minimizing the Kullback – Leibler (KL) distance D(p‖p̂) = Ep[log(p/p̂)] using first- and second-order statistics, via a maximum-weight...Obtain sparse representations αl, l = 1, . . . , T , in RN from test image. 6: Inference: Classify based on the output of the resulting classifier using ...The public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing

Site classification of Indian strong motion network using response spectra ratios

NASA Astrophysics Data System (ADS)

Chopra, Sumer; Kumar, Vikas; Choudhury, Pallabee; Yadav, R. B. S.

2018-03-01

In the present study, we tried to classify the Indian strong motion sites spread all over Himalaya and adjoining region, located on varied geological formations, based on response spectral ratio. A total of 90 sites were classified based on 395 strong motion records from 94 earthquakes recorded at these sites. The magnitude of these earthquakes are between 2.3 and 7.7 and the hypocentral distance for most of the cases is less than 50 km. The predominant period obtained from response spectral ratios is used to classify these sites. It was found that the shape and predominant peaks of the spectra at these sites match with those in Japan, Italy, Iran, and at some of the sites in Europe and the same classification scheme can be applied to Indian strong motion network. We found that the earlier schemes based on description of near-surface geology, geomorphology, and topography were not able to capture the effect of sediment thickness. The sites are classified into seven classes (CL-I to CL-VII) with varying predominant periods and ranges as proposed by Alessandro et al. (Bull Seismol Soc Am 102:680-695 2012). The effect of magnitudes and hypocentral distances on the shape and predominant peaks were also studied and found to be very small. The classification scheme is robust and cost-effective and can be used in region-specific attenuation relationships for accounting local site effect.

U S Navy Diving Manual. Volume 2. Mixed-Gas Diving. Revision 1.

DTIC Science & Technology

1981-07-01

has been soaked in a solution of portant aspects of underwater physics and physiology caustic potash. This chemical absorbed the carbon as they...between the diver’s breathing passages and the circuit must be of minimum volume minimum of caustic fumes. Water produced by the to preclude deadspace and...strongly react with water to pro- space around the absorbent bed to reduce the gas duce caustic fumes and cannot be used in UBA’s. flow distance. The

Maximum and minimum return losses from a passive two-port network terminated with a mismatched load

NASA Technical Reports Server (NTRS)

Otoshi, T. Y.

1993-01-01

This article presents an analytical method for determining the exact distance a load is required to be offset from a passive two-port network to obtain maximum or minimum return losses from the terminated two-port network. Equations are derived in terms of two-port network S-parameters and load reflection coefficient. The equations are useful for predicting worst-case performances of some types of networks that are terminated with offset short-circuit loads.

Geometric characterization of separability and entanglement in pure Gaussian states by single-mode unitary operations

NASA Astrophysics Data System (ADS)

Adesso, Gerardo; Giampaolo, Salvatore M.; Illuminati, Fabrizio

2007-10-01

We present a geometric approach to the characterization of separability and entanglement in pure Gaussian states of an arbitrary number of modes. The analysis is performed adapting to continuous variables a formalism based on single subsystem unitary transformations that has been recently introduced to characterize separability and entanglement in pure states of qubits and qutrits [S. M. Giampaolo and F. Illuminati, Phys. Rev. A 76, 042301 (2007)]. In analogy with the finite-dimensional case, we demonstrate that the 1×M bipartite entanglement of a multimode pure Gaussian state can be quantified by the minimum squared Euclidean distance between the state itself and the set of states obtained by transforming it via suitable local symplectic (unitary) operations. This minimum distance, corresponding to a , uniquely determined, extremal local operation, defines an entanglement monotone equivalent to the entropy of entanglement, and amenable to direct experimental measurement with linear optical schemes.

Analysis of the minimum swerving distance for the development of a motorcycle autonomous braking system.

PubMed

Giovannini, Federico; Savino, Giovanni; Pierini, Marco; Baldanzini, Niccolò

2013-10-01

In the recent years the autonomous emergency brake (AEB) was introduced in the automotive field to mitigate the injury severity in case of unavoidable collisions. A crucial element for the activation of the AEB is to establish when the obstacle is no longer avoidable by lateral evasive maneuvers (swerving). In the present paper a model to compute the minimum swerving distance needed by a powered two-wheeler (PTW) to avoid the collision against a fixed obstacle, named last-second swerving model (Lsw), is proposed. The effectiveness of the model was investigated by an experimental campaign involving 12 volunteers riding a scooter equipped with a prototype autonomous emergency braking, named motorcycle autonomous emergency braking system (MAEB). The tests showed the performance of the model in evasive trajectory computation for different riding styles and fixed obstacles. Copyright © 2013 Elsevier Ltd. All rights reserved.

System and method employing a minimum distance and a load feature database to identify electric load types of different electric loads

DOEpatents

Lu, Bin; Yang, Yi; Sharma, Santosh K; Zambare, Prachi; Madane, Mayura A

2014-12-23

A method identifies electric load types of a plurality of different electric loads. The method includes providing a load feature database of a plurality of different electric load types, each of the different electric load types including a first load feature vector having at least four different load features; sensing a voltage signal and a current signal for each of the different electric loads; determining a second load feature vector comprising at least four different load features from the sensed voltage signal and the sensed current signal for a corresponding one of the different electric loads; and identifying by a processor one of the different electric load types by determining a minimum distance of the second load feature vector to the first load feature vector of the different electric load types of the load feature database.

29 CFR Appendix A to Part 510 - Manufacturing Industries Eligible for Minimum Wage Phase-In

Code of Federal Regulations, 2010 CFR

2010-07-01

.... 286 1 Industrial organic chemicals. 2865 1 Cyclic organic crudes and intermediates, and organic dyes and pigments. 2869 a Industrial organic chemicals, not elsewhere classified. 287 1 Agricultural chemicals. 2873 1 Nitrogenous fertilizers. 2879 1 Pesticides and agricultural chemicals, not elsewhere...

Optimum nonparametric estimation of population density based on ordered distances

USGS Publications Warehouse

Patil, S.A.; Kovner, J.L.; Burnham, Kenneth P.

1982-01-01

The asymptotic mean and error mean square are determined for the nonparametric estimator of plant density by distance sampling proposed by Patil, Burnham and Kovner (1979, Biometrics 35, 597-604. On the basis of these formulae, a bias-reduced version of this estimator is given, and its specific form is determined which gives minimum mean square error under varying assumptions about the true probability density function of the sampled data. Extension is given to line-transect sampling.

Texture Analysis and Cartographic Feature Extraction.

DTIC Science & Technology

1985-01-01

Investigations into using various image descriptors as well as developing interactive feature extraction software on the Digital Image Analysis Laboratory...system. Originator-supplied keywords: Ad-Hoc image descriptor; Bayes classifier; Bhattachryya distance; Clustering; Digital Image Analysis Laboratory

Variation of z-height of the molecular clouds on the Galactic Plane

NASA Astrophysics Data System (ADS)

Lee, Y.; Stark, A. A.

2002-12-01

Using the Bell Laboratories Galactic plane in the J=1-0 transition of 13CO, (l, b) = (-5o to 117o, -1o to +1o), and cloud identification code, 13CO clouds have been identified and cataloged as a function of threshold temperature. Distance estimates to the identified clouds have been made with several criteria. Minimum and maximum distances to each identified cloud are determined from a set of all the possible distances of a cloud. Several physical parameters can be determined with distances, such as z-height [D sin (b)], CO luminosity, virial mass and so forth. We select the clouds with a ratio of maximum and minimum of CO luminosities less than 3. The number of selected clouds is 281 out of 1400 identified clouds with 1 K threshold temperature. These clouds are mostly located on the tangential positions in the inner Galaxy, and some are in the Outer Galaxy. It is found that the z-height of lower luminosity clouds (less massive clouds) is systimatically larger than that of high-luminosity clouds (more massive clouds). We claim that this is the first observational evidence of the z-height variation depending on the luminosities (or masses) of molecular clouds on the Galactic plane. Our results could be a basis explaining the formation mechanism of massive clouds, such as giant molecular clouds.

Minimization of municipal solid waste transportation route in West Jakarta using Tabu Search method

NASA Astrophysics Data System (ADS)

Chaerul, M.; Mulananda, A. M.

2018-04-01

Indonesia still adopts the concept of collect-haul-dispose for municipal solid waste handling and it leads to the queue of the waste trucks at final disposal site (TPA). The study aims to minimize the total distance of waste transportation system by applying a Transshipment model. In this case, analogous of transshipment point is a compaction facility (SPA). Small capacity of trucks collects the waste from waste temporary collection points (TPS) to the compaction facility which located near the waste generator. After compacted, the waste is transported using big capacity of trucks to the final disposal site which is located far away from city. Problem related with the waste transportation can be solved using Vehicle Routing Problem (VRP). In this study, the shortest distance of route from truck pool to TPS, TPS to SPA, and SPA to TPA was determined by using meta-heuristic methods, namely Tabu Search 2 Phases. TPS studied is the container type with total 43 units throughout the West Jakarta City with 38 units of Armroll truck with capacity of 10 m3 each. The result determines the assignment of each truck from the pool to the selected TPS, SPA and TPA with the total minimum distance of 2,675.3 KM. The minimum distance causing the total cost for waste transportation to be spent by the government also becomes minimal.

BOREAS AES READAC Surface Meteorological Data

NASA Technical Reports Server (NTRS)

Atkinson, G. Barrie; Funk, Barry; Hall, Forrest G. (Editor); Knapp, David E. (Editor)

2000-01-01

Canadian AES personnel collected and processed data related to surface atmospheric meteorological conditions over the BOREAS region. This data set contains 15-minute meteorological data from one READAC meteorology station in Hudson Bay, Saskatchewan. Parameters include day, time, type of report, sky condition, visibility, mean sea level pressure, temperature, dewpoint, wind, altimeter, opacity, minimum and maximum visibility, station pressure, minimum and maximum air temperature, a wind group, precipitation, and precipitation in the last hour. The data were collected non-continuously from 24-May-1994 to 20-Sep-1994. The data are provided in tabular ASCII files, and are classified as AFM-Staff data.

On the design of classifiers for crop inventories

NASA Technical Reports Server (NTRS)

Heydorn, R. P.; Takacs, H. C.

1986-01-01

Crop proportion estimators that use classifications of satellite data to correct, in an additive way, a given estimate acquired from ground observations are discussed. A linear version of these estimators is optimal, in terms of minimum variance, when the regression of the ground observations onto the satellite observations in linear. When this regression is not linear, but the reverse regression (satellite observations onto ground observations) is linear, the estimator is suboptimal but still has certain appealing variance properties. In this paper expressions are derived for those regressions which relate the intercepts and slopes to conditional classification probabilities. These expressions are then used to discuss the question of classifier designs that can lead to low-variance crop proportion estimates. Variance expressions for these estimates in terms of classifier omission and commission errors are also derived.

Dynamics of ultralight aircraft: Dive recovery of hang gliders

NASA Technical Reports Server (NTRS)

Jones, R. T.

1977-01-01

Longitudinal control of a hang glider by weight shift is not always adequate for recovery from a vertical dive. According to Lanchester's phugoid theory, recovery from rest to horizontal flight ought to be possible within a distance equal to three times the height of fall needed to acquire level flight velocity. A hang glider, having a wing loading of 5 kg sq m and capable of developing a lift coefficient of 1.0, should recover to horizontal flight within a vertical distance of about 12 m. The minimum recovery distance can be closely approached if the glider is equipped with a small all-moveable tail surface having sufficient upward deflection.

Pairwise Trajectory Management (PTM): Concept Overview

NASA Technical Reports Server (NTRS)

Jones, Kenneth M.; Graff, Thomas J.; Chartrand, Ryan C.; Carreno, Victor; Kibler, Jennifer L.

2017-01-01

Pairwise Trajectory Management (PTM) is an Interval Management (IM) concept that utilizes airborne and ground-based capabilities to enable the implementation of airborne pairwise spacing capabilities in oceanic regions. The goal of PTM is to use airborne surveillance and tools to manage an "at or greater than" inter-aircraft spacing. Due to the precision of Automatic Dependent Surveillance-Broadcast (ADS-B) information and the use of airborne spacing guidance, the PTM minimum spacing distance will be less than distances a controller can support with current automation systems that support oceanic operations. Ground tools assist the controller in evaluating the traffic picture and determining appropriate PTM clearances to be issued. Avionics systems provide guidance information that allows the flight crew to conform to the PTM clearance issued by the controller. The combination of a reduced minimum distance and airborne spacing management will increase the capacity and efficiency of aircraft operations at a given altitude or volume of airspace. This paper provides an overview of the proposed application, description of a few key scenarios, high level discussion of expected air and ground equipment and procedure changes, overview of a potential flight crew human-machine interface that would support PTM operations and some initial PTM benefits results.

11. VIEW OF HOCK OUTCROPPING, CONCRETE GRAVITY DAM FACE AND ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

11. VIEW OF HOCK OUTCROPPING, CONCRETE GRAVITY DAM FACE AND LAKE WITH TUNNEL INLET STRUCTURE IN DISTANCE, SHOWN AT MINIMUM WATER FLOW, LOOKING SOUTHEAST (UPSTREAM) - Van Arsdale Dam, South Fork of Eel River, Ukiah, Mendocino County, CA

Potential energy function for CH3+CH3 ⇆ C2H6: Attributes of the minimum energy path

NASA Astrophysics Data System (ADS)

Robertson, S. H.; Wardlaw, D. M.; Hirst, D. M.

1993-11-01

The region of the potential energy surface for the title reaction in the vicinity of its minimum energy path has been predicted from the analysis of ab initio electronic energy calculations. The ab initio procedure employs a 6-31G** basis set and a configuration interaction calculation which uses the orbitals obtained in a generalized valence bond calculation. Calculated equilibrium properties of ethane and of isolated methyl radical are compared to existing theoretical and experimental results. The reaction coordinate is represented by the carbon-carbon interatomic distance. The following attributes are reported as a function of this distance and fit to functional forms which smoothly interpolate between reactant and product values of each attribute: the minimum energy path potential, the minimum energy path geometry, normal mode frequencies for vibrational motion orthogonal to the reaction coordinate, a torsional potential, and a fundamental anharmonic frequency for local mode, out-of-plane CH3 bending (umbrella motion). The best representation is provided by a three-parameter modified Morse function for the minimum energy path potential and a two-parameter hyperbolic tangent switching function for all other attributes. A poorer but simpler representation, which may be satisfactory for selected applications, is provided by a standard Morse function and a one-parameter exponential switching function. Previous applications of the exponential switching function to estimate the reaction coordinate dependence of the frequencies and geometry of this system have assumed the same value of the range parameter α for each property and have taken α to be less than or equal to the ``standard'' value of 1.0 Å-1. Based on the present analysis this is incorrect: The α values depend on the property and range from ˜1.2 to ˜1.8 Å-1.

Mediagraphy: Print and Nonprint Resources.

ERIC Educational Resources Information Center

Educational Media and Technology Yearbook, 1996

1996-01-01

This annotated list includes media-related resources classified under the following headings: artificial intelligence and robotics, CD-ROM, computer-assisted instruction, databases and online searching, distance education, educational research, educational technology, electronic publishing, information science and technology, instructional design…

Mediagraphy: Print and Nonprint Resources.

ERIC Educational Resources Information Center

Educational Media and Technology Yearbook, 1997

1997-01-01

This annotated list includes media-related resources classified under the following headings: artificial intelligence and robotics, CD-ROM, computer-assisted instruction, databases and online searching, distance education, educational research, educational technology, electronic publishing, information science and technology, instructional design…

Improved target detection algorithm using Fukunaga-Koontz transform and distance classifier correlation filter

NASA Astrophysics Data System (ADS)

Bal, A.; Alam, M. S.; Aslan, M. S.

2006-05-01

Often sensor ego-motion or fast target movement causes the target to temporarily go out of the field-of-view leading to reappearing target detection problem in target tracking applications. Since the target goes out of the current frame and reenters at a later frame, the reentering location and variations in rotation, scale, and other 3D orientations of the target are not known thus complicating the detection algorithm has been developed using Fukunaga-Koontz Transform (FKT) and distance classifier correlation filter (DCCF). The detection algorithm uses target and background information, extracted from training samples, to detect possible candidate target images. The detected candidate target images are then introduced into the second algorithm, DCCF, called clutter rejection module, to determine the target coordinates are detected and tracking algorithm is initiated. The performance of the proposed FKT-DCCF based target detection algorithm has been tested using real-world forward looking infrared (FLIR) video sequences.

Classification With Truncated Distance Kernel.

PubMed

Huang, Xiaolin; Suykens, Johan A K; Wang, Shuning; Hornegger, Joachim; Maier, Andreas

2018-05-01

This brief proposes a truncated distance (TL1) kernel, which results in a classifier that is nonlinear in the global region but is linear in each subregion. With this kernel, the subregion structure can be trained using all the training data and local linear classifiers can be established simultaneously. The TL1 kernel has good adaptiveness to nonlinearity and is suitable for problems which require different nonlinearities in different areas. Though the TL1 kernel is not positive semidefinite, some classical kernel learning methods are still applicable which means that the TL1 kernel can be directly used in standard toolboxes by replacing the kernel evaluation. In numerical experiments, the TL1 kernel with a pregiven parameter achieves similar or better performance than the radial basis function kernel with the parameter tuned by cross validation, implying the TL1 kernel a promising nonlinear kernel for classification tasks.

Predicting Flavonoid UGT Regioselectivity

PubMed Central

Jackson, Rhydon; Knisley, Debra; McIntosh, Cecilia; Pfeiffer, Phillip

2011-01-01

Machine learning was applied to a challenging and biologically significant protein classification problem: the prediction of avonoid UGT acceptor regioselectivity from primary sequence. Novel indices characterizing graphical models of residues were proposed and found to be widely distributed among existing amino acid indices and to cluster residues appropriately. UGT subsequences biochemically linked to regioselectivity were modeled as sets of index sequences. Several learning techniques incorporating these UGT models were compared with classifications based on standard sequence alignment scores. These techniques included an application of time series distance functions to protein classification. Time series distances defined on the index sequences were used in nearest neighbor and support vector machine classifiers. Additionally, Bayesian neural network classifiers were applied to the index sequences. The experiments identified improvements over the nearest neighbor and support vector machine classifications relying on standard alignment similarity scores, as well as strong correlations between specific subsequences and regioselectivities. PMID:21747849

Optimal Geometrical Set for Automated Marker Placement to Virtualized Real-Time Facial Emotions

PubMed Central

Maruthapillai, Vasanthan; Murugappan, Murugappan

2016-01-01

In recent years, real-time face recognition has been a major topic of interest in developing intelligent human-machine interaction systems. Over the past several decades, researchers have proposed different algorithms for facial expression recognition, but there has been little focus on detection in real-time scenarios. The present work proposes a new algorithmic method of automated marker placement used to classify six facial expressions: happiness, sadness, anger, fear, disgust, and surprise. Emotional facial expressions were captured using a webcam, while the proposed algorithm placed a set of eight virtual markers on each subject’s face. Facial feature extraction methods, including marker distance (distance between each marker to the center of the face) and change in marker distance (change in distance between the original and new marker positions), were used to extract three statistical features (mean, variance, and root mean square) from the real-time video sequence. The initial position of each marker was subjected to the optical flow algorithm for marker tracking with each emotional facial expression. Finally, the extracted statistical features were mapped into corresponding emotional facial expressions using two simple non-linear classifiers, K-nearest neighbor and probabilistic neural network. The results indicate that the proposed automated marker placement algorithm effectively placed eight virtual markers on each subject’s face and gave a maximum mean emotion classification rate of 96.94% using the probabilistic neural network. PMID:26859884

Similarities among receptor pockets and among compounds: analysis and application to in silico ligand screening.

PubMed

Fukunishi, Yoshifumi; Mikami, Yoshiaki; Nakamura, Haruki

2005-09-01

We developed a new method to evaluate the distances and similarities between receptor pockets or chemical compounds based on a multi-receptor versus multi-ligand docking affinity matrix. The receptors were classified by a cluster analysis based on calculations of the distance between receptor pockets. A set of low homologous receptors that bind a similar compound could be classified into one cluster. Based on this line of reasoning, we proposed a new in silico screening method. According to this method, compounds in a database were docked to multiple targets. The new docking score was a slightly modified version of the multiple active site correction (MASC) score. Receptors that were at a set distance from the target receptor were not included in the analysis, and the modified MASC scores were calculated for the selected receptors. The choice of the receptors is important to achieve a good screening result, and our clustering of receptors is useful to this purpose. This method was applied to the analysis of a set of 132 receptors and 132 compounds, and the results demonstrated that this method achieves a high hit ratio, as compared to that of a uniform sampling, using a receptor-ligand docking program, Sievgene, which was newly developed with a good docking performance yielding 50.8% of the reconstructed complexes at a distance of less than 2 A RMSD.

Optimal Geometrical Set for Automated Marker Placement to Virtualized Real-Time Facial Emotions.

PubMed

Maruthapillai, Vasanthan; Murugappan, Murugappan

2016-01-01

In recent years, real-time face recognition has been a major topic of interest in developing intelligent human-machine interaction systems. Over the past several decades, researchers have proposed different algorithms for facial expression recognition, but there has been little focus on detection in real-time scenarios. The present work proposes a new algorithmic method of automated marker placement used to classify six facial expressions: happiness, sadness, anger, fear, disgust, and surprise. Emotional facial expressions were captured using a webcam, while the proposed algorithm placed a set of eight virtual markers on each subject's face. Facial feature extraction methods, including marker distance (distance between each marker to the center of the face) and change in marker distance (change in distance between the original and new marker positions), were used to extract three statistical features (mean, variance, and root mean square) from the real-time video sequence. The initial position of each marker was subjected to the optical flow algorithm for marker tracking with each emotional facial expression. Finally, the extracted statistical features were mapped into corresponding emotional facial expressions using two simple non-linear classifiers, K-nearest neighbor and probabilistic neural network. The results indicate that the proposed automated marker placement algorithm effectively placed eight virtual markers on each subject's face and gave a maximum mean emotion classification rate of 96.94% using the probabilistic neural network.

Design for minimum energy in interstellar communication

NASA Astrophysics Data System (ADS)

Messerschmitt, David G.

2015-02-01

Microwave digital communication at interstellar distances is the foundation of extraterrestrial civilization (SETI and METI) communication of information-bearing signals. Large distances demand large transmitted power and/or large antennas, while the propagation is transparent over a wide bandwidth. Recognizing a fundamental tradeoff, reduced energy delivered to the receiver at the expense of wide bandwidth (the opposite of terrestrial objectives) is advantageous. Wide bandwidth also results in simpler design and implementation, allowing circumvention of dispersion and scattering arising in the interstellar medium and motion effects and obviating any related processing. The minimum energy delivered to the receiver per bit of information is determined by cosmic microwave background alone. By mapping a single bit onto a carrier burst, the Morse code invented for the telegraph in 1836 comes closer to this minimum energy than approaches used in modern terrestrial radio. Rather than the terrestrial approach of adding phases and amplitudes increases information capacity while minimizing bandwidth, adding multiple time-frequency locations for carrier bursts increases capacity while minimizing energy per information bit. The resulting location code is simple and yet can approach the minimum energy as bandwidth is expanded. It is consistent with easy discovery, since carrier bursts are energetic and straightforward modifications to post-detection pattern recognition can identify burst patterns. Time and frequency coherence constraints leading to simple signal discovery are addressed, and observations of the interstellar medium by transmitter and receiver constrain the burst parameters and limit the search scope.

Elastohydrodynamic lubrication of elliptical contacts

NASA Technical Reports Server (NTRS)

Hamrock, B. J.

1981-01-01

The determination of the minimum film thickness within contact is considered for both fully flooded and starved conditions. A fully flooded conjunction is one in which the film thickness is not significantly changed when the amount of lubricant is increased. The fully flooded results presented show the influence of contact geometry on minimum film thickness as expressed by the ellipticity parameter and the dimensionless speed, load, and materials parameters. These results are applied to materials of high elastic modulus (hard EHL), such as metal, and to materials of low elastic modulus(soft EHL), such as rubber. In addition to the film thickness equations that are developed, contour plots of pressure and film thickness are given which show the essential features of elastohydrodynamically lubricated conjunctions. The crescent shaped region of minimum film thickness, with its side lobes in which the separation between the solids is a minimum, clearly emerges in the numerical solutions. In addition to the 3 presented for the fully flooded results, 15 more cases are used for hard EHL contacts and 18 cases are used for soft EHL contacts in a theoretical study of the influence of lubricant starvation on film thickness and pressure. From the starved results for both hard and soft EHL contacts, a simple and important dimensionless inlet boundary distance is specified. This inlet boundary distance defines whether a fully flooded or a starved condition exists in the contact. Contour plots of pressure and film thickness in and around the contact are shown for conditions.

A distance-independent calibration of the luminosity of type Ia supernovae and the Hubble constant

NASA Technical Reports Server (NTRS)

Leibundgut, Bruno; Pinto, Philip A.

1992-01-01

The absolute magnitude of SNe Ia at maximum is calibrated here using radioactive decay models for the light curve and a minimum of assumptions. The absolute magnitude parameter space is studied using explosion models and a range of rise times, and absolute B magnitudes at maximum are used to derive a range of the H0 and the distance to the Virgo Cluster from SNe Ia. Rigorous limits for H0 of 45 and 105 km/s/Mpc are derived.

Natural migration rates of trees: Global terrestrial carbon cycle implications. Book chapter

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

Solomon, A.M.

The paper discusses the forest-ecological processes which constrain the rate of response by forests to rapid future environmental change. It establishes a minimum response time by natural tree populations which invade alien landscapes and reach the status of a mature, closed canopy forest when maximum carbon storage is realized. It considers rare long-distance and frequent short-distance seed transport, seedling and tree establishment, sequential tree and stand maturation, and spread between newly established colonies.

Supernova bangs as a tool to study big bang

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

Blinnikov, S. I., E-mail: Sergei.Blinnikov@itep.ru

Supernovae and gamma-ray bursts are the most powerful explosions in observed Universe. This educational review tells about supernovae and their applications in cosmology. It is explained how to understand the production of light in the most luminous events with minimum required energy of explosion. These most luminous phenomena can serve as primary cosmological distance indicators. Comparing the observed distance dependence on red shift with theoretical models one can extract information on evolution of the Universe from Big Bang until our epoch.

VSOP: the variable star one-shot project. I. Project presentation and first data release

NASA Astrophysics Data System (ADS)

Dall, T. H.; Foellmi, C.; Pritchard, J.; Lo Curto, G.; Allende Prieto, C.; Bruntt, H.; Amado, P. J.; Arentoft, T.; Baes, M.; Depagne, E.; Fernandez, M.; Ivanov, V.; Koesterke, L.; Monaco, L.; O'Brien, K.; Sarro, L. M.; Saviane, I.; Scharwächter, J.; Schmidtobreick, L.; Schütz, O.; Seifahrt, A.; Selman, F.; Stefanon, M.; Sterzik, M.

2007-08-01

Context: About 500 new variable stars enter the General Catalogue of Variable Stars (GCVS) every year. Most of them however lack spectroscopic observations, which remains critical for a correct assignement of the variability type and for the understanding of the object. Aims: The Variable Star One-shot Project (VSOP) is aimed at (1) providing the variability type and spectral type of all unstudied variable stars, (2) process, publish, and make the data available as automatically as possible, and (3) generate serendipitous discoveries. This first paper describes the project itself, the acquisition of the data, the dataflow, the spectroscopic analysis and the on-line availability of the fully calibrated and reduced data. We also present the results on the 221 stars observed during the first semester of the project. Methods: We used the high-resolution echelle spectrographs HARPS and FEROS in the ESO La Silla Observatory (Chile) to survey known variable stars. Once reduced by the dedicated pipelines, the radial velocities are determined from cross correlation with synthetic template spectra, and the spectral types are determined by an automatic minimum distance matching to synthetic spectra, with traditional manual spectral typing cross-checks. The variability types are determined by manually evaluating the available light curves and the spectroscopy. In the future, a new automatic classifier, currently being developed by members of the VSOP team, based on these spectroscopic data and on the photometric classifier developed for the COROT and Gaia space missions, will be used. Results: We confirm or revise spectral types of 221 variable stars from the GCVS. We identify 26 previously unknown multiple systems, among them several visual binaries with spectroscopic binary individual components. We present new individual results for the multiple systems V349 Vel and BC Gru, for the composite spectrum star V4385 Sgr, for the T Tauri star V1045 Sco, and for DM Boo which we re-classify as a BY Draconis variable. The complete data release can be accessed via the VSOP web site. Based on data obtained at the La Silla Observatory, European Southern Observatory, under program ID 077.D-0085.

A responder analysis of the effects of yoga for individuals with COPD: who benefits and how?

PubMed

Donesky, DorAnne; Melendez, Michelle; Nguyen, Huong Q; Carrieri-Kohlman, Virginia

2012-01-01

We previously reported that a twice-weekly, modified Iyengar yoga program was a safe and viable self-management strategy for patients with chronic obstructive pulmonary disease (COPD). 1 The primary purpose of this exploratory analysis was to classify yoga participants into 1 of 3 responder categories by using minimum clinically important difference (MCID) criteria for each of 3 variables: 6-minute walk distance (6MW), distress related to dyspnea (shortness of breath; DD), and functional performance (FPI). Changes in health-related quality of life (HRQL) and in psychological well-being (anxiety and depression), and participants' self-reported improvements by responder category were also examined. A secondary goal was to identify baseline participant characteristics, including initial randomization assignment that might predict response to treatment. Participants were randomly assigned to either an initial yoga (IY) or an enhanced wait-list control (WLC) group. Those in the WLC group were offered the yoga program immediately following the IY group's participation. Individuals from both groups who completed at least 18 of 24 yoga classes were categorized as responders, partial responders, or non-responders for each of the 3 outcome variables (6MW, DD, FPI) on the basis of MCID criteria. Baseline characteristics and changes in HRQL and psychological well-being were also analyzed. None of the participants demonstrated MCIDs for all 3 outcomes; however, 6 were classified as responders for 2 out-come variables and 4 were classified as non-responders for all 3 outcome variables. Two-thirds of the female participant group and one-third of the male participant group completed the yoga program. DD responders showed increased anxiety levels, whereas anxiety levels of the DD non-responders remained unchanged. FPI responders reported significant improvements in physical function, whereas partial and non-FPI responders noted declined function. Participants assigned to the IY group demonstrated greater benefit from yoga than did those in the W LC group. Although this modified Iyengar yoga program appears to have benefited some individuals with COPD, further studies are required to assess who the intervention works for and under what conditions.

Distance Learning Materials for Elementary Astronomy with Lab

NASA Astrophysics Data System (ADS)

Castle, K. G.

2004-05-01

I have developed a distance learning astronomy course with an integral lab. The materials for this course are available from the site below. Test and quiz contents can be obtained upon request In this distance-learning format, students take quizzes online, tests in person and meet with the instructor for assistance. Student activities include homework, laboratory exercises and observing projects using household and community resources. This course (Astro 128) has been approved to fulfill general education requirements for University of California and the California State University system. Materials include instructions and reference materials for measuring parallax, analyzing radial velocity and light curves, finding ages of star clusters, tracking planets, recording sunrise or sunset time, simulating lunar phases, assessing lunar feature ages, classifying stellar spectra from tracings, and classifying galaxy morphology. Students analyze actual astronomical data from the literature in many cases. A comparatively large number of observational examples allows each student to work with a unique assignment. Course management includes a calendar where students schedule meetings with the instructor and WebCT test, quiz and grade maintenance. Course materials are supplied with links to data sets in PDF. This class was developed with technical assistance from the Instructional Technology Department at Diablo Valley College.

Electrophysiological evidence for differential processing of numerical quantity and order in humans.

PubMed

Turconi, Eva; Jemel, Boutheina; Rossion, Bruno; Seron, Xavier

2004-09-01

It is yet unclear whether the processing of number magnitude and order rely on common or different functional processes and neural substrates. On the one hand, recent neuroimaging studies show that quantity and order coding activate the same areas in the parietal and prefrontal cortices. On the other hand, evidence from developmental and neuropsychological studies suggest dissociated mechanisms for processing quantity and order information. To clarify this issue, the present study investigated the spatio-temporal course of quantity and order coding operations using event-related potentials (ERPs). Twenty-four subjects performed a quantity task (classifying numbers as smaller or larger than 15) and an order task on the same material (classifying numbers as coming before or after 15), as well as a control order task on letters (classifying letters as coming before or after M). Behavioral results showed a classical distance effect (decreasing reaction times [RTs] with increasing distance from the standard) for all tasks. In agreement with previous electrophysiological evidence, this effect was significant on a P2 parietal component for numerical material. However, the difference between processing numbers close or far from the target appeared earlier and was larger on the left hemisphere for quantity processing, while it was delayed and bilateral for order processing. There was also a significant distance effect in all tasks on parietal sites for the following P3 component elicited by numbers, but this effect was larger on prefrontal areas for the order judgment. In conclusion, both quantity and order show similar behavioral effects, but they are associated with different spatio-temporal courses in parietal and prefrontal cortices.

An improved global wind resource estimate for integrated assessment models

DOE PAGES

Eurek, Kelly; Sullivan, Patrick; Gleason, Michael; ...

2017-11-25

This study summarizes initial steps to improving the robustness and accuracy of global renewable resource and techno-economic assessments for use in integrated assessment models. We outline a method to construct country-level wind resource supply curves, delineated by resource quality and other parameters. Using mesoscale reanalysis data, we generate estimates for wind quality, both terrestrial and offshore, across the globe. Because not all land or water area is suitable for development, appropriate database layers provide exclusions to reduce the total resource to its technical potential. We expand upon estimates from related studies by: using a globally consistent data source of uniquelymore » detailed wind speed characterizations; assuming a non-constant coefficient of performance for adjusting power curves for altitude; categorizing the distance from resource sites to the electric power grid; and characterizing offshore exclusions on the basis of sea ice concentrations. The product, then, is technical potential by country, classified by resource quality as determined by net capacity factor. Additional classifications dimensions are available, including distance to transmission networks for terrestrial wind and distance to shore and water depth for offshore. We estimate the total global wind generation potential of 560 PWh for terrestrial wind with 90% of resource classified as low-to-mid quality, and 315 PWh for offshore wind with 67% classified as mid-to-high quality. These estimates are based on 3.5 MW composite wind turbines with 90 m hub heights, 0.95 availability, 90% array efficiency, and 5 MW/km 2 deployment density in non-excluded areas. We compare the underlying technical assumption and results with other global assessments.« less

An improved global wind resource estimate for integrated assessment models

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

Eurek, Kelly; Sullivan, Patrick; Gleason, Michael

This study summarizes initial steps to improving the robustness and accuracy of global renewable resource and techno-economic assessments for use in integrated assessment models. We outline a method to construct country-level wind resource supply curves, delineated by resource quality and other parameters. Using mesoscale reanalysis data, we generate estimates for wind quality, both terrestrial and offshore, across the globe. Because not all land or water area is suitable for development, appropriate database layers provide exclusions to reduce the total resource to its technical potential. We expand upon estimates from related studies by: using a globally consistent data source of uniquelymore » detailed wind speed characterizations; assuming a non-constant coefficient of performance for adjusting power curves for altitude; categorizing the distance from resource sites to the electric power grid; and characterizing offshore exclusions on the basis of sea ice concentrations. The product, then, is technical potential by country, classified by resource quality as determined by net capacity factor. Additional classifications dimensions are available, including distance to transmission networks for terrestrial wind and distance to shore and water depth for offshore. We estimate the total global wind generation potential of 560 PWh for terrestrial wind with 90% of resource classified as low-to-mid quality, and 315 PWh for offshore wind with 67% classified as mid-to-high quality. These estimates are based on 3.5 MW composite wind turbines with 90 m hub heights, 0.95 availability, 90% array efficiency, and 5 MW/km 2 deployment density in non-excluded areas. We compare the underlying technical assumption and results with other global assessments.« less

Feature selection for the classification of traced neurons.

PubMed

López-Cabrera, José D; Lorenzo-Ginori, Juan V

2018-06-01

The great availability of computational tools to calculate the properties of traced neurons leads to the existence of many descriptors which allow the automated classification of neurons from these reconstructions. This situation determines the necessity to eliminate irrelevant features as well as making a selection of the most appropriate among them, in order to improve the quality of the classification obtained. The dataset used contains a total of 318 traced neurons, classified by human experts in 192 GABAergic interneurons and 126 pyramidal cells. The features were extracted by means of the L-measure software, which is one of the most used computational tools in neuroinformatics to quantify traced neurons. We review some current feature selection techniques as filter, wrapper, embedded and ensemble methods. The stability of the feature selection methods was measured. For the ensemble methods, several aggregation methods based on different metrics were applied to combine the subsets obtained during the feature selection process. The subsets obtained applying feature selection methods were evaluated using supervised classifiers, among which Random Forest, C4.5, SVM, Naïve Bayes, Knn, Decision Table and the Logistic classifier were used as classification algorithms. Feature selection methods of types filter, embedded, wrappers and ensembles were compared and the subsets returned were tested in classification tasks for different classification algorithms. L-measure features EucDistanceSD, PathDistanceSD, Branch_pathlengthAve, Branch_pathlengthSD and EucDistanceAve were present in more than 60% of the selected subsets which provides evidence about their importance in the classification of this neurons. Copyright © 2018 Elsevier B.V. All rights reserved.

Textual and visual content-based anti-phishing: a Bayesian approach.

PubMed

Zhang, Haijun; Liu, Gang; Chow, Tommy W S; Liu, Wenyin

2011-10-01

A novel framework using a Bayesian approach for content-based phishing web page detection is presented. Our model takes into account textual and visual contents to measure the similarity between the protected web page and suspicious web pages. A text classifier, an image classifier, and an algorithm fusing the results from classifiers are introduced. An outstanding feature of this paper is the exploration of a Bayesian model to estimate the matching threshold. This is required in the classifier for determining the class of the web page and identifying whether the web page is phishing or not. In the text classifier, the naive Bayes rule is used to calculate the probability that a web page is phishing. In the image classifier, the earth mover's distance is employed to measure the visual similarity, and our Bayesian model is designed to determine the threshold. In the data fusion algorithm, the Bayes theory is used to synthesize the classification results from textual and visual content. The effectiveness of our proposed approach was examined in a large-scale dataset collected from real phishing cases. Experimental results demonstrated that the text classifier and the image classifier we designed deliver promising results, the fusion algorithm outperforms either of the individual classifiers, and our model can be adapted to different phishing cases. © 2011 IEEE

Machine learning classifiers for glaucoma diagnosis based on classification of retinal nerve fibre layer thickness parameters measured by Stratus OCT.

PubMed

Bizios, Dimitrios; Heijl, Anders; Hougaard, Jesper Leth; Bengtsson, Boel

2010-02-01

To compare the performance of two machine learning classifiers (MLCs), artificial neural networks (ANNs) and support vector machines (SVMs), with input based on retinal nerve fibre layer thickness (RNFLT) measurements by optical coherence tomography (OCT), on the diagnosis of glaucoma, and to assess the effects of different input parameters. We analysed Stratus OCT data from 90 healthy persons and 62 glaucoma patients. Performance of MLCs was compared using conventional OCT RNFLT parameters plus novel parameters such as minimum RNFLT values, 10th and 90th percentiles of measured RNFLT, and transformations of A-scan measurements. For each input parameter and MLC, the area under the receiver operating characteristic curve (AROC) was calculated. There were no statistically significant differences between ANNs and SVMs. The best AROCs for both ANN (0.982, 95%CI: 0.966-0.999) and SVM (0.989, 95% CI: 0.979-1.0) were based on input of transformed A-scan measurements. Our SVM trained on this input performed better than ANNs or SVMs trained on any of the single RNFLT parameters (p < or = 0.038). The performance of ANNs and SVMs trained on minimum thickness values and the 10th and 90th percentiles were at least as good as ANNs and SVMs with input based on the conventional RNFLT parameters. No differences between ANN and SVM were observed in this study. Both MLCs performed very well, with similar diagnostic performance. Input parameters have a larger impact on diagnostic performance than the type of machine classifier. Our results suggest that parameters based on transformed A-scan thickness measurements of the RNFL processed by machine classifiers can improve OCT-based glaucoma diagnosis.

78 FR 24061 - Minimum Technical Standards for Class II Gaming Systems and Equipment

Federal Register 2010, 2011, 2012, 2013, 2014

2013-04-24

... Register that established technical standards for ensuring the integrity of electronic Class II games and aids. 73 FR 60508, Oct. 10, 2008. The technical standards were designed to assist tribal gaming... Class II gaming systems. The standards did not classify which games were Class II games and which games...

Mediagraphy: Print and Nonprint Resources.

ERIC Educational Resources Information Center

Price, Brooke, Ed.

2001-01-01

Lists media-related journals, books, ERIC documents, journal articles, and nonprint resources published in 1999-2000. The annotated entries are classified under the following headings: artificial intelligence; computer assisted instruction; distance education; educational research; educational technology; information science and technology;…

Mediagraphy: Print and Nonprint Resources.

ERIC Educational Resources Information Center

Burdett, Anna E.

2003-01-01

Lists media-related journals, books, ERIC documents, journal articles, and nonprint resources published in 2001-2002. The annotated entries are classified under the following headings: artificial intelligence; computer assisted instruction; distance education; educational research; educational technology; information science and technology;…

Extremal values on Zagreb indices of trees with given distance k-domination number.

PubMed

Pei, Lidan; Pan, Xiangfeng

2018-01-01

Let [Formula: see text] be a graph. A set [Formula: see text] is a distance k -dominating set of G if for every vertex [Formula: see text], [Formula: see text] for some vertex [Formula: see text], where k is a positive integer. The distance k -domination number [Formula: see text] of G is the minimum cardinality among all distance k -dominating sets of G . The first Zagreb index of G is defined as [Formula: see text] and the second Zagreb index of G is [Formula: see text]. In this paper, we obtain the upper bounds for the Zagreb indices of n -vertex trees with given distance k -domination number and characterize the extremal trees, which generalize the results of Borovićanin and Furtula (Appl. Math. Comput. 276:208-218, 2016). What is worth mentioning, for an n -vertex tree T , is that a sharp upper bound on the distance k -domination number [Formula: see text] is determined.

Ground-based Observations for the Asteroid Itokawa

NASA Astrophysics Data System (ADS)

Ishiguro, M.; Tholen, D. J.; Hasegawa, S.; Abe, M.; Sekiguchi, T.; Ostro, S. J.; Kaasalainen, M.

Apollo-type near-Earth asteroid (25143) Itokawa is a target of the asteroid explorer "HAYABUSA" launched in May 2003. On March 29, 2001, Itokawa was close to the Earth at a minimum distance of 0.038 AU. During the apparition, vigorous ground-based observations have performed. Multi-band photometry (e.g. ECAS and Johnson-Cousins photometric system) and spectroscopy in visible and near-infrared revealed that Itokawa is classified as an S(IV)-type asteroid, and the surface composition is like an anhydrous ordinary chondrite. The extensive photometric campaign data indicate that the rotation is retrograde (i.e., the pole orientation of the asteroid is south of the ecliptic plane) and its rotational period is 12 hr. From the mid-infrared observation, Itokawa is found to be a sub-km size. Detail three dimensional model was constructed based on both the radar observations and the optical lightcurve. Moreover, the bulk density determined by radar observations is 2.5 g/cc. Generally, the results obtained by optical, infrared and radar observations are consistent with each other. These observational results provide constraints on the thermal and optical design of Hayabusa spacecraft and its scientific devices. In this paper, we review these results mentioned above. In addition, we are planning to introduce the latest results obtained during the apparition in 2004.

A Neural-Network Clustering-Based Algorithm for Privacy Preserving Data Mining

NASA Astrophysics Data System (ADS)

Tsiafoulis, S.; Zorkadis, V. C.; Karras, D. A.

The increasing use of fast and efficient data mining algorithms in huge collections of personal data, facilitated through the exponential growth of technology, in particular in the field of electronic data storage media and processing power, has raised serious ethical, philosophical and legal issues related to privacy protection. To cope with these concerns, several privacy preserving methodologies have been proposed, classified in two categories, methodologies that aim at protecting the sensitive data and those that aim at protecting the mining results. In our work, we focus on sensitive data protection and compare existing techniques according to their anonymity degree achieved, the information loss suffered and their performance characteristics. The ℓ-diversity principle is combined with k-anonymity concepts, so that background information can not be exploited to successfully attack the privacy of data subjects data refer to. Based on Kohonen Self Organizing Feature Maps (SOMs), we firstly organize data sets in subspaces according to their information theoretical distance to each other, then create the most relevant classes paying special attention to rare sensitive attribute values, and finally generalize attribute values to the minimum extend required so that both the data disclosure probability and the information loss are possibly kept negligible. Furthermore, we propose information theoretical measures for assessing the anonymity degree achieved and empirical tests to demonstrate it.

Fifteen new earthworm mitogenomes shed new light on phylogeny within the Pheretima complex

PubMed Central

Zhang, Liangliang; Sechi, Pierfrancesco; Yuan, Minglong; Jiang, Jibao; Dong, Yan; Qiu, Jiangping

2016-01-01

The Pheretima complex within the Megascolecidae family is a major earthworm group. Recently, the systematic status of the Pheretima complex based on morphology was challenged by molecular studies. In this study, we carry out the first comparative mitogenomic study in oligochaetes. The mitogenomes of 15 earthworm species were sequenced and compared with other 9 available earthworm mitogenomes, with the main aim to explore their phylogenetic relationships and test different analytical approaches on phylogeny reconstruction. The general earthworm mitogenomic features revealed to be conservative: all genes encoded on the same strand, all the protein coding loci shared the same initiation codon (ATG), and tRNA genes showed conserved structures. The Drawida japonica mitogenome displayed the highest A + T content, reversed AT/GC-skews and the highest genetic diversity. Genetic distances among protein coding genes displayed their maximum and minimum interspecific values in the ATP8 and CO1 genes, respectively. The 22 tRNAs showed variable substitution patterns between the considered earthworm mitogenomes. The inclusion of rRNAs positively increased phylogenetic support. Furthermore, we tested different trimming tools for alignment improvement. Our analyses rejected reciprocal monophyly among Amynthas and Metaphire and indicated that the two genera should be systematically classified into one. PMID:26833286

Area under precision-recall curves for weighted and unweighted data.

PubMed

Keilwagen, Jens; Grosse, Ivo; Grau, Jan

2014-01-01

Precision-recall curves are highly informative about the performance of binary classifiers, and the area under these curves is a popular scalar performance measure for comparing different classifiers. However, for many applications class labels are not provided with absolute certainty, but with some degree of confidence, often reflected by weights or soft labels assigned to data points. Computing the area under the precision-recall curve requires interpolating between adjacent supporting points, but previous interpolation schemes are not directly applicable to weighted data. Hence, even in cases where weights were available, they had to be neglected for assessing classifiers using precision-recall curves. Here, we propose an interpolation for precision-recall curves that can also be used for weighted data, and we derive conditions for classification scores yielding the maximum and minimum area under the precision-recall curve. We investigate accordances and differences of the proposed interpolation and previous ones, and we demonstrate that taking into account existing weights of test data is important for the comparison of classifiers.

Area under Precision-Recall Curves for Weighted and Unweighted Data

PubMed Central

Grosse, Ivo

2014-01-01

Precision-recall curves are highly informative about the performance of binary classifiers, and the area under these curves is a popular scalar performance measure for comparing different classifiers. However, for many applications class labels are not provided with absolute certainty, but with some degree of confidence, often reflected by weights or soft labels assigned to data points. Computing the area under the precision-recall curve requires interpolating between adjacent supporting points, but previous interpolation schemes are not directly applicable to weighted data. Hence, even in cases where weights were available, they had to be neglected for assessing classifiers using precision-recall curves. Here, we propose an interpolation for precision-recall curves that can also be used for weighted data, and we derive conditions for classification scores yielding the maximum and minimum area under the precision-recall curve. We investigate accordances and differences of the proposed interpolation and previous ones, and we demonstrate that taking into account existing weights of test data is important for the comparison of classifiers. PMID:24651729

On the Relation Between Spotless Days and the Sunspot Cycle

NASA Technical Reports Server (NTRS)

Wilson, Robert M.; Hathaway, David H.

2005-01-01

Spotless days are examined as a predictor for the size and timing of a sunspot cycle. For cycles 16-23 the first spotless day for a new cycle, which occurs during the decline of the old cycle, is found to precede minimum amplitude for the new cycle by about approximately equal to 34 mo, having a range of 25-40 mo. Reports indicate that the first spotless day for cycle 24 occurred in January 2004, suggesting that minimum amplitude for cycle 24 should be expected before April 2007, probably sometime during the latter half of 2006. If true, then cycle 23 will be classified as a cycle of shorter period, inferring further that cycle 24 likely will be a cycle of larger than average minimum and maximum amplitudes and faster than average rise, peaking sometime in 2010.

Development of Gis Tool for the Solution of Minimum Spanning Tree Problem using Prim's Algorithm

NASA Astrophysics Data System (ADS)

Dutta, S.; Patra, D.; Shankar, H.; Alok Verma, P.

2014-11-01

minimum spanning tree (MST) of a connected, undirected and weighted network is a tree of that network consisting of all its nodes and the sum of weights of all its edges is minimum among all such possible spanning trees of the same network. In this study, we have developed a new GIS tool using most commonly known rudimentary algorithm called Prim's algorithm to construct the minimum spanning tree of a connected, undirected and weighted road network. This algorithm is based on the weight (adjacency) matrix of a weighted network and helps to solve complex network MST problem easily, efficiently and effectively. The selection of the appropriate algorithm is very essential otherwise it will be very hard to get an optimal result. In case of Road Transportation Network, it is very essential to find the optimal results by considering all the necessary points based on cost factor (time or distance). This paper is based on solving the Minimum Spanning Tree (MST) problem of a road network by finding it's minimum span by considering all the important network junction point. GIS technology is usually used to solve the network related problems like the optimal path problem, travelling salesman problem, vehicle routing problems, location-allocation problems etc. Therefore, in this study we have developed a customized GIS tool using Python script in ArcGIS software for the solution of MST problem for a Road Transportation Network of Dehradun city by considering distance and time as the impedance (cost) factors. It has a number of advantages like the users do not need a greater knowledge of the subject as the tool is user-friendly and that allows to access information varied and adapted the needs of the users. This GIS tool for MST can be applied for a nationwide plan called Prime Minister Gram Sadak Yojana in India to provide optimal all weather road connectivity to unconnected villages (points). This tool is also useful for constructing highways or railways spanning several cities optimally or connecting all cities with minimum total road length.

Optimization of self-study room open problem based on green and low-carbon campus construction

NASA Astrophysics Data System (ADS)

Liu, Baoyou

2017-04-01

The optimization of self-study room open arrangement problem in colleges and universities is conducive to accelerate the fine management of the campus and promote green and low-carbon campus construction. Firstly, combined with the actual survey data, the self-study area and living area were divided into different blocks, and the electricity consumption in each self-study room and distance between different living and studying areas were normalized. Secondly, the minimum of total satisfaction index and the minimum of the total electricity consumption were selected as the optimization targets respectively. The mathematical models of linear programming were established and resolved by LINGO software. The results showed that the minimum of total satisfaction index was 4055.533 and the total minimum electricity consumption was 137216 W. Finally, some advice had been put forward on how to realize the high efficient administration of the study room.

Elastohydrodynamic lubrication of point contacts. Ph.D. Thesis - Leeds Univ.

NASA Technical Reports Server (NTRS)

Hamrock, B. J.

1976-01-01

A procedure for the numerical solution of the complete, isothermal, elastohydrodynamic lubrication problem for point contacts is given. This procedure calls for the simultaneous solution of the elasticity and Reynolds equations. By using this theory the influence of the ellipticity parameter and the dimensionless speed, load, and material parameters on the minimum and central film thicknesses was investigated. Thirty-four different cases were used in obtaining the fully flooded minimum- and central-film-thickness formulas. Lubricant starvation was also studied. From the results it was possible to express the minimum film thickness for a starved condition in terms of the minimum film thickness for a fully flooded condition, the speed parameter, and the inlet distance. Fifteen additional cases plus three fully flooded cases were used in obtaining this formula. Contour plots of pressure and film thickness in and around the contact have been presented for both fully flooded and starved lubrication conditions.

Kinematic Distances: A Monte Carlo Method

NASA Astrophysics Data System (ADS)

Wenger, Trey V.; Balser, Dana S.; Anderson, L. D.; Bania, T. M.

2018-03-01

Distances to high-mass star-forming regions (HMSFRs) in the Milky Way are a crucial constraint on the structure of the Galaxy. Only kinematic distances are available for a majority of the HMSFRs in the Milky Way. Here, we compare the kinematic and parallax distances of 75 Galactic HMSFRs to assess the accuracy of kinematic distances. We derive the kinematic distances using three different methods: the traditional method using the Brand & Blitz rotation curve (Method A), the traditional method using the Reid et al. rotation curve and updated solar motion parameters (Method B), and a Monte Carlo technique (Method C). Methods B and C produce kinematic distances closest to the parallax distances, with median differences of 13% (0.43 {kpc}) and 17% (0.42 {kpc}), respectively. Except in the vicinity of the tangent point, the kinematic distance uncertainties derived by Method C are smaller than those of Methods A and B. In a large region of the Galaxy, the Method C kinematic distances constrain both the distances and the Galactocentric positions of HMSFRs more accurately than parallax distances. Beyond the tangent point along ℓ = 30°, for example, the Method C kinematic distance uncertainties reach a minimum of 10% of the parallax distance uncertainty at a distance of 14 {kpc}. We develop a prescription for deriving and applying the Method C kinematic distances and distance uncertainties. The code to generate the Method C kinematic distances is publicly available and may be utilized through an online tool.

Interstellar reddening information system

NASA Astrophysics Data System (ADS)

Burnashev, V. I.; Grigorieva, E. A.; Malkov, O. Yu.

2013-10-01

We describe an electronic bibliographic information system, based on a card catalog, containing some 2500 references (publications of 1930-2009) on interstellar extinction. We have classified the articles according to their content. We present here a list of articles devoted to two categories: maps of total extinction and variation of interstellar extinction with the distance to the object. The catalog is tested using published data on open clusters, and conclusions on the applicability of different maps of interstellar extinctions for various distances are made.

About neighborhood counting measure metric and minimum risk metric.

PubMed

Argentini, Andrea; Blanzieri, Enrico

2010-04-01

In a 2006 TPAMI paper, Wang proposed the Neighborhood Counting Measure, a similarity measure for the k-NN algorithm. In his paper, Wang mentioned the Minimum Risk Metric (MRM), an early distance measure based on the minimization of the risk of misclassification. Wang did not compare NCM to MRM because of its allegedly excessive computational load. In this comment paper, we complete the comparison that was missing in Wang's paper and, from our empirical evaluation, we show that MRM outperforms NCM and that its running time is not prohibitive as Wang suggested.

Rate-Compatible Protograph LDPC Codes

NASA Technical Reports Server (NTRS)

Nguyen, Thuy V. (Inventor); Nosratinia, Aria (Inventor); Divsalar, Dariush (Inventor)

2014-01-01

Digital communication coding methods resulting in rate-compatible low density parity-check (LDPC) codes built from protographs. Described digital coding methods start with a desired code rate and a selection of the numbers of variable nodes and check nodes to be used in the protograph. Constraints are set to satisfy a linear minimum distance growth property for the protograph. All possible edges in the graph are searched for the minimum iterative decoding threshold and the protograph with the lowest iterative decoding threshold is selected. Protographs designed in this manner are used in decode and forward relay channels.

Keep at bay!--Abnormal personal space regulation as marker of paranoia in schizophrenia.

PubMed

Schoretsanitis, G; Kutynia, A; Stegmayer, K; Strik, W; Walther, S

2016-01-01

During threat, interpersonal distance is deliberately increased. Personal space regulation is related to amygdala function and altered in schizophrenia, but it remains unknown whether it is particularly associated with paranoid threat. We compared performance in two tests on personal space between 64 patients with schizophrenia spectrum disorders and 24 matched controls. Patients were stratified in those with paranoid threat, neutral affect or paranoid experience of power. In the stop-distance paradigm, participants indicated the minimum tolerable interpersonal distance. In the fixed-distance paradigm, they indicated the level of comfort at fixed interpersonal distances. Paranoid threat increased interpersonal distance two-fold in the stop-distance paradigm, and reduced comfort ratings in the fixed-distance paradigm. In contrast, patients experiencing paranoid power had high comfort ratings at any distance. Patients with neutral affect did not differ from controls in the stop-distance paradigm. Differences between groups remained when controlling for gender and positive symptom severity. Among schizophrenia patients, the stop-distance paradigm detected paranoid threat with 93% sensitivity and 83% specificity. Personal space regulation is not generally altered in schizophrenia. However, state paranoid experience has distinct contributions to personal space regulation. Subjects experiencing current paranoid threat share increased safety-seeking behavior. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Analytic processing of distance.

PubMed

Dopkins, Stephen; Galyer, Darin

2018-01-01

How does a human observer extract from the distance between two frontal points the component corresponding to an axis of a rectangular reference frame? To find out we had participants classify pairs of small circles, varying on the horizontal and vertical axes of a computer screen, in terms of the horizontal distance between them. A response signal controlled response time. The error rate depended on the irrelevant vertical as well as the relevant horizontal distance between the test circles with the relevant distance effect being larger than the irrelevant distance effect. The results implied that the horizontal distance between the test circles was imperfectly extracted from the overall distance between them. The results supported an account, derived from the Exemplar Based Random Walk model (Nosofsky & Palmieri, 1997), under which distance classification is based on the overall distance between the test circles, with relevant distance being extracted from overall distance to the extent that the relevant and irrelevant axes are differentially weighted so as to reduce the contribution of irrelevant distance to overall distance. The results did not support an account, derived from the General Recognition Theory (Ashby & Maddox, 1994), under which distance classification is based on the relevant distance between the test circles, with the irrelevant distance effect arising because a test circle's perceived location on the relevant axis depends on its location on the irrelevant axis, and with relevant distance being extracted from overall distance to the extent that this dependency is absent. Copyright © 2017 Elsevier B.V. All rights reserved.

29 CFR 29.2 - Definitions.

Code of Federal Regulations, 2010 CFR

2010-07-01

... the Administrator. Apprentice means a worker at least 16 years of age, except where a higher minimum age standard is otherwise fixed by law, who is employed to learn an apprenticeable occupation as... physical movement of removable/transportable electronic media and/or interactive distance learning...

Tandem steerable running gear

NASA Technical Reports Server (NTRS)

Fincannon, O. J.; Glenn, D. L.

1972-01-01

Characteristics of steering assembly for vehicle designed to move large components of space flight vehicles are presented. Design makes it possible to move heavy and bulky items through narrow passageways with tight turns. Typical configuration is illustrated to show dimensions of turning radius and minimum distances involved.

Simulation of Collision of Arbitrary Shape Particles with Wall in a Viscous Fluid

NASA Astrophysics Data System (ADS)

Mohaghegh, Fazlolah; Udaykumar, H. S.

2016-11-01

Collision of finite size arbitrary shape particles with wall in a viscous flow is modeled using immersed boundary method. A potential function indicating the distance from the interface is introduced for the particles and the wall. The potential can be defined by using either an analytical expression or level set method. The collision starts when the indicator potentials of the particle and wall are overlapping based on a minimum cut off. A simplified mass spring model is used in order to apply the collision forces. Instead of using a dashpot in order to damp the energy, the spring stiffness is adjusted during the bounce. The results for the case of collision of a falling sphere with the bottom wall agrees well with the experiments. Moreover, it is shown that the results are independent from the minimum collision cut off distance value. Finally, when the particle's shape is ellipsoidal, the rotation of the particle after the collision becomes important and noticeable: At low Stokes number values, the particle almost adheres to the wall in one side and rotates until it reaches the minimum gravitational potential. At high Stokes numbers, the particle bounces and loses the energy until it reaches a situation with low Stokes number.

Fuzzy scalar and vector median filters based on fuzzy distances.

PubMed

Chatzis, V; Pitas, I

1999-01-01

In this paper, the fuzzy scalar median (FSM) is proposed, defined by using ordering of fuzzy numbers based on fuzzy minimum and maximum operations defined by using the extension principle. Alternatively, the FSM is defined from the minimization of a fuzzy distance measure, and the equivalence of the two definitions is proven. Then, the fuzzy vector median (FVM) is proposed as an extension of vector median, based on a novel distance definition of fuzzy vectors, which satisfy the property of angle decomposition. By defining properly the fuzziness of a value, the combination of the basic properties of the classical scalar and vector median (VM) filter with other desirable characteristics can be succeeded.

Edit distance for marked point processes revisited: An implementation by binary integer programming

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

Hirata, Yoshito; Aihara, Kazuyuki

2015-12-15

We implement the edit distance for marked point processes [Suzuki et al., Int. J. Bifurcation Chaos 20, 3699–3708 (2010)] as a binary integer program. Compared with the previous implementation using minimum cost perfect matching, the proposed implementation has two advantages: first, by using the proposed implementation, we can apply a wide variety of software and hardware, even spin glasses and coherent ising machines, to calculate the edit distance for marked point processes; second, the proposed implementation runs faster than the previous implementation when the difference between the numbers of events in two time windows for a marked point process ismore » large.« less

How far and how fast can mushroom spores fly? Physical limits on ballistospore size and discharge distance in the Basidiomycota

PubMed Central

Fischer, Mark W. F.; Stolze-Rybczynski, Jessica L.; Cui, Yunluan; Money, Nicholas P.

2010-01-01

Active discharge of basidiospores in most species of Basidiomycota is powered by the rapid movement of a droplet of fluid, called Buller’s drop, over the spore surface. This paper is concerned with the operation of the launch mechanism in species with the largest and smallest ballistospores. Aleurodiscus gigasporus (Russulales) produces the largest basidiospores on record. The maximum dimensions of the spores, 34 × 28 µm, correspond to a volume of 14 pL and to an estimated mass of 17 ng. The smallest recorded basidiospores are produced by Hyphodontia latitans (Hymenochaetales). Minimum spore dimensions in this species, 3.5 × 0.5 µm, correspond to a volume of 0.5 fL and mass of 0.6 pg. Neither species has been studied using high-speed video microscopy, but this technique was used to examine ballistospore discharge in species with spores of similar sizes (slightly smaller than A. gigasporus and slightly larger than those of H. latitans). Extrapolation of velocity measurements from these fungi provided estimates of discharge distances ranging from a maximum of almost 2 mm in A. gigasporus to a minimum of 4 µm in H. latitans. These are, respectively, the longest and shortest predicted discharge distances for ballistospores. Limitations to the distances traveled by basidiospores are discussed in relation to the mechanics of the discharge process and the types of fruit-bodies from which the spores are released. PMID:20835365

Using traveling salesman problem algorithms for evolutionary tree construction.

PubMed

Korostensky, C; Gonnet, G H

2000-07-01

The construction of evolutionary trees is one of the major problems in computational biology, mainly due to its complexity. We present a new tree construction method that constructs a tree with minimum score for a given set of sequences, where the score is the amount of evolution measured in PAM distances. To do this, the problem of tree construction is reduced to the Traveling Salesman Problem (TSP). The input for the TSP algorithm are the pairwise distances of the sequences and the output is a circular tour through the optimal, unknown tree plus the minimum score of the tree. The circular order and the score can be used to construct the topology of the optimal tree. Our method can be used for any scoring function that correlates to the amount of changes along the branches of an evolutionary tree, for instance it could also be used for parsimony scores, but it cannot be used for least squares fit of distances. A TSP solution reduces the space of all possible trees to 2n. Using this order, we can guarantee that we reconstruct a correct evolutionary tree if the absolute value of the error for each distance measurement is smaller than f2.gif" BORDER="0">, where f3.gif" BORDER="0">is the length of the shortest edge in the tree. For data sets with large errors, a dynamic programming approach is used to reconstruct the tree. Finally simulations and experiments with real data are shown.

Species-distance relation for birds of the Solomon Archipelago, and the paradox of the great speciators

PubMed Central

Diamond, Jared M.; Gilpin, Michael E.; Mayr, Ernst

1976-01-01

For scattered remote islands and for likely forms of immigration and extinction curves, the equilibrium theory of island biogeography leads to the prediction [unk]2 log S/[unk]A[unk]D > 0, where S is the number of species on an island, A island area, and D island distance from the colonization source. This prediction is confirmed for birds of the Solomon Archipelago. Bird species can be classified into three types according to how distance affects their distributions: non-water-crossers, which are stopped completely (usually for psychological reasons) by water gaps of even 1 mile; short-distance colonists, successful at colonizing close but not remote islands; and long-distance colonists, successful at colonizing remote as well as close islands. Almost all of the “great speciators”, the species for whose inter-island geographic variation the Solomons are famous, prove to be short-distance colonists. Lack's interpretation of the decrease in S with D is shown to rest on incorrect assumptions. PMID:16592328

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

Ferré, Grégoire; Maillet, Jean-Bernard; Stoltz, Gabriel

We present a permutation-invariant distance between atomic configurations, defined through a functional representation of atomic positions. This distance enables us to directly compare different atomic environments with an arbitrary number of particles, without going through a space of reduced dimensionality (i.e., fingerprints) as an intermediate step. Moreover, this distance is naturally invariant through permutations of atoms, avoiding the time consuming associated minimization required by other common criteria (like the root mean square distance). Finally, the invariance through global rotations is accounted for by a minimization procedure in the space of rotations solved by Monte Carlo simulated annealing. A formal frameworkmore » is also introduced, showing that the distance we propose verifies the property of a metric on the space of atomic configurations. Two examples of applications are proposed. The first one consists in evaluating faithfulness of some fingerprints (or descriptors), i.e., their capacity to represent the structural information of a configuration. The second application concerns structural analysis, where our distance proves to be efficient in discriminating different local structures and even classifying their degree of similarity.« less

Faulting type classification of small earthquakes using a template approach and their hypocenter relocation along the Japan and Kuril trenches

NASA Astrophysics Data System (ADS)

Nakamura, W.; Uchida, N.; Matsuzawa, T.

2013-12-01

After the 2011 Tohoku-oki earthquake, the number of interplate earthquakes off Miyagi was dramatically decreased (e.g., Asano et al., 2011), while many normal faulting earthquakes occurred in the outer trench region (e.g., Obana et al., 2012). To understand the meaning of the seismicity change caused by the huge earthquake, it is essential to know faulting types of small offshore earthquakes which cannot be determined using conventional methods. In this study, we developed a method to classify focal mechanisms of small earthquakes by using template events whose focal mechanisms were known. Here, we made pairs of earthquakes with inter-event distances of less than 20 km and difference in magnitude of less than 1.0, and calculated their waveform cross-correlation coefficients (CCs) in 1.5 and 5.0 sec windows for P and S waves, respectively. We first calculated 3D minimum rotation angle (Kagan's angle; Kagan, 1991) for pairs whose focal mechanisms were listed in the F-net catalogue, to examine the relationships among the Kagan's angles, CCs and inter-event distances. The CCs decrease with increasing inter-event distances and Kagan's angles. We set a CC threshold of 0.8 for Tohoku (to the south of 40° N), and 0.7 for Hokkaido (to the north of 40° N) regions to judge whether the two events have the same focal mechanisms. This is because more than 90% of event pairs whose CCs are greater than the thresholds show Kagan's angles of less than 30° when we calculated them for the mechanism-known earthquakes (templates). In total, 4012 earthquakes from 2003 to 2012 are newly classified and 60% and 30% of them are of interplate and normal faulting types, respectively. In the area of large coseismic slip of the 2011 Tohoku-oki earthquake, we found no interplate earthquakes after the main shock, while many interplate earthquakes occurred around the M9 coseismic slip area. We also found many normal faulting earthquakes near the trench after the 2011 main shock. Along the Kuril trench, many interplate earthquakes occurred as aftershocks of the 2003 Tokachi-oki earthquake (M8.0). To verify the validity of the results and to examine the detail of the focal mechanism distribution, we relocated hypocenters by tomoFDD code (Zhang and Thurber. 2006) using a 3D velocity structure. Most of interplate-type earthquakes were located near the plate boundary except in the near trench-region, suggesting the correctness of mechanism and earthquake location. The hypocenters of normal faulting events that occurred after the 2011 Tohoku-oki earthquake off Miyagi were relocated within 20km from the surface of the Pacific plate. This result suggests the normal faulting event in the incoming Pacific plate occurred in a shallower part of the plate as suggested from OBS data analyses. Normal faulting earthquakes off Miyagi occurred not only in the outer trench region but also above the plate boundary near the coast. The focal mechanism classification method developed in the present study using waveform cross-correlations increases the number of classified earthquakes that show the temporal changes in the interplate coupling and stress field around the plate boundary.

Comparison of Different EHG Feature Selection Methods for the Detection of Preterm Labor

PubMed Central

Alamedine, D.; Khalil, M.; Marque, C.

2013-01-01

Numerous types of linear and nonlinear features have been extracted from the electrohysterogram (EHG) in order to classify labor and pregnancy contractions. As a result, the number of available features is now very large. The goal of this study is to reduce the number of features by selecting only the relevant ones which are useful for solving the classification problem. This paper presents three methods for feature subset selection that can be applied to choose the best subsets for classifying labor and pregnancy contractions: an algorithm using the Jeffrey divergence (JD) distance, a sequential forward selection (SFS) algorithm, and a binary particle swarm optimization (BPSO) algorithm. The two last methods are based on a classifier and were tested with three types of classifiers. These methods have allowed us to identify common features which are relevant for contraction classification. PMID:24454536

Stackable differential mobility analyzer for aerosol measurement

DOEpatents

Cheng, Meng-Dawn [Oak Ridge, TN; Chen, Da-Ren [Creve Coeur, MO

2007-05-08

A multi-stage differential mobility analyzer (MDMA) for aerosol measurements includes a first electrode or grid including at least one inlet or injection slit for receiving an aerosol including charged particles for analysis. A second electrode or grid is spaced apart from the first electrode. The second electrode has at least one sampling outlet disposed at a plurality different distances along its length. A volume between the first and the second electrode or grid between the inlet or injection slit and a distal one of the plurality of sampling outlets forms a classifying region, the first and second electrodes for charging to suitable potentials to create an electric field within the classifying region. At least one inlet or injection slit in the second electrode receives a sheath gas flow into an upstream end of the classifying region, wherein each sampling outlet functions as an independent DMA stage and classifies different size ranges of charged particles based on electric mobility simultaneously.

A new algorithm for reducing the workload of experts in performing systematic reviews.

PubMed

Matwin, Stan; Kouznetsov, Alexandre; Inkpen, Diana; Frunza, Oana; O'Blenis, Peter

2010-01-01

To determine whether a factorized version of the complement naïve Bayes (FCNB) classifier can reduce the time spent by experts reviewing journal articles for inclusion in systematic reviews of drug class efficacy for disease treatment. The proposed classifier was evaluated on a test collection built from 15 systematic drug class reviews used in previous work. The FCNB classifier was constructed to classify each article as containing high-quality, drug class-specific evidence or not. Weight engineering (WE) techniques were added to reduce underestimation for Medical Subject Headings (MeSH)-based and Publication Type (PubType)-based features. Cross-validation experiments were performed to evaluate the classifier's parameters and performance. Work saved over sampling (WSS) at no less than a 95% recall was used as the main measure of performance. The minimum workload reduction for a systematic review for one topic, achieved with a FCNB/WE classifier, was 8.5%; the maximum was 62.2% and the average over the 15 topics was 33.5%. This is 15.0% higher than the average workload reduction obtained using a voting perceptron-based automated citation classification system. The FCNB/WE classifier is simple, easy to implement, and produces significantly better results in reducing the workload than previously achieved. The results support it being a useful algorithm for machine-learning-based automation of systematic reviews of drug class efficacy for disease treatment.

75 FR 51237 - Fisheries in the Western Pacific; Hawaii Bottomfish and Seamount Groundfish; Management Measures...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-08-19

... armorhead stock is rebuilt, establish a minimum rebuilding time of 35 years for the U.S. portion of the armorhead stock, and classify the portion of the U.S. Exclusive Economic Zone (EEZ) around the Hancock... armorhead stock. DATES: Comments on the amendment must be received by October 18, 2010. ADDRESSES: Comments...

15 CFR 758.6 - Destination control statement.

Code of Federal Regulations, 2010 CFR

2010-01-01

... be entered on the invoice and on the bill of lading, air waybill, or other export control document... Control List that are not classified as EAR99, unless the export may be made under License Exception BAG or GFT (see part 740 of the EAR). At a minimum, the DCS must state: “These commodities, technology or...

15 CFR 758.6 - Destination control statement.

Code of Federal Regulations, 2011 CFR

2011-01-01

... be entered on the invoice and on the bill of lading, air waybill, or other export control document... Control List that are not classified as EAR99, unless the export may be made under License Exception BAG or GFT (see part 740 of the EAR). At a minimum, the DCS must state: “These commodities, technology or...

77 FR 75946 - Radio Broadcasting Services; Dove Creek, CO

Federal Register 2010, 2011, 2012, 2013, 2014

2012-12-26

...]. Radio Broadcasting Services; Dove Creek, CO AGENCY: Federal Communications Commission. ACTION: Proposed... service at Dove Creek, Colorado. Channel 229C3 can be allotted at Dove Creek, Colorado, in compliance with the Commission's minimum distance separation requirements, at the proposed reference coordinates: 37...

40 CFR 258.55 - Assessment monitoring program.

Code of Federal Regulations, 2013 CFR

2013-07-01

... upgradient edge of the MSWLF unit and downgradient monitoring well screen (minimum distance of travel); (5... effects during a lifetime. For purposes of this subpart, systemic toxicants include toxic chemicals that cause effects other than cancer or mutation. (ii) [Reserved] (j) In establishing ground-water protection...

40 CFR 258.55 - Assessment monitoring program.

Code of Federal Regulations, 2011 CFR

2011-07-01

... upgradient edge of the MSWLF unit and downgradient monitoring well screen (minimum distance of travel); (5... effects during a lifetime. For purposes of this subpart, systemic toxicants include toxic chemicals that cause effects other than cancer or mutation. (ii) [Reserved] (j) In establishing ground-water protection...

40 CFR 258.55 - Assessment monitoring program.

Code of Federal Regulations, 2012 CFR

2012-07-01

... upgradient edge of the MSWLF unit and downgradient monitoring well screen (minimum distance of travel); (5... effects during a lifetime. For purposes of this subpart, systemic toxicants include toxic chemicals that cause effects other than cancer or mutation. (ii) [Reserved] (j) In establishing ground-water protection...

Permutation-invariant distance between atomic configurations

NASA Astrophysics Data System (ADS)

Ferré, Grégoire; Maillet, Jean-Bernard; Stoltz, Gabriel

2015-09-01

We present a permutation-invariant distance between atomic configurations, defined through a functional representation of atomic positions. This distance enables us to directly compare different atomic environments with an arbitrary number of particles, without going through a space of reduced dimensionality (i.e., fingerprints) as an intermediate step. Moreover, this distance is naturally invariant through permutations of atoms, avoiding the time consuming associated minimization required by other common criteria (like the root mean square distance). Finally, the invariance through global rotations is accounted for by a minimization procedure in the space of rotations solved by Monte Carlo simulated annealing. A formal framework is also introduced, showing that the distance we propose verifies the property of a metric on the space of atomic configurations. Two examples of applications are proposed. The first one consists in evaluating faithfulness of some fingerprints (or descriptors), i.e., their capacity to represent the structural information of a configuration. The second application concerns structural analysis, where our distance proves to be efficient in discriminating different local structures and even classifying their degree of similarity.

Rate-Compatible LDPC Codes with Linear Minimum Distance

NASA Technical Reports Server (NTRS)

Divsalar, Dariush; Jones, Christopher; Dolinar, Samuel

2009-01-01

A recently developed method of constructing protograph-based low-density parity-check (LDPC) codes provides for low iterative decoding thresholds and minimum distances proportional to block sizes, and can be used for various code rates. A code constructed by this method can have either fixed input block size or fixed output block size and, in either case, provides rate compatibility. The method comprises two submethods: one for fixed input block size and one for fixed output block size. The first mentioned submethod is useful for applications in which there are requirements for rate-compatible codes that have fixed input block sizes. These are codes in which only the numbers of parity bits are allowed to vary. The fixed-output-blocksize submethod is useful for applications in which framing constraints are imposed on the physical layers of affected communication systems. An example of such a system is one that conforms to one of many new wireless-communication standards that involve the use of orthogonal frequency-division modulation

Study of hopping type conduction from AC conductivity in multiferroic composite

NASA Astrophysics Data System (ADS)

Pandey, Rabichandra; Guha, Shampa; Pradhan, Lagen Kumar; Kumar, Sunil; Supriya, Sweety; Kar, Manoranjan

2018-05-01

0.5BiFe0.80Ti0.20O3-0.5Co0.5Ni0.5Fe2O4(BFTO-CNFO) multiferroic composite was prepared by planetary ball mill method. X-ray diffraction analysis confirms the formation of the compound with the simultaneous presence of spinel Co0.5Ni0.5Fe2O4 (CNFO) and perovskite BiFe0.80Ti0.20O3 (BFTO) phase. Temperature dependent dielectric permittivity and loss tangent were studied with a frequency range of 100Hz to 1MHz. AC conductivity study was performed to analyze the electrical conduction behaviour in the composite. Johnscher's power law was employed to the AC conductivity data to understand the hopping of localized charge carrier in the compound. The binding energy, minimum hopping distance and density of states of the charge carriers in the composite were evaluated from the AC conductivity data. Minimum hopping distance is found to be in order of Angstrom (Å).

Geometric characterization of separability and entanglement in pure Gaussian states by single-mode unitary operations

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

Adesso, Gerardo; CNR-INFM Coherentia, Naples; CNISM, Unita di Salerno, Salerno

2007-10-15

We present a geometric approach to the characterization of separability and entanglement in pure Gaussian states of an arbitrary number of modes. The analysis is performed adapting to continuous variables a formalism based on single subsystem unitary transformations that has been recently introduced to characterize separability and entanglement in pure states of qubits and qutrits [S. M. Giampaolo and F. Illuminati, Phys. Rev. A 76, 042301 (2007)]. In analogy with the finite-dimensional case, we demonstrate that the 1xM bipartite entanglement of a multimode pure Gaussian state can be quantified by the minimum squared Euclidean distance between the state itself andmore » the set of states obtained by transforming it via suitable local symplectic (unitary) operations. This minimum distance, corresponding to a, uniquely determined, extremal local operation, defines an entanglement monotone equivalent to the entropy of entanglement, and amenable to direct experimental measurement with linear optical schemes.« less

The Simplified Aircraft-Based Paired Approach With the ALAS Alerting Algorithm

NASA Technical Reports Server (NTRS)

Perry, Raleigh B.; Madden, Michael M.; Torres-Pomales, Wilfredo; Butler, Ricky W.

2013-01-01

This paper presents the results of an investigation of a proposed concept for closely spaced parallel runways called the Simplified Aircraft-based Paired Approach (SAPA). This procedure depends upon a new alerting algorithm called the Adjacent Landing Alerting System (ALAS). This study used both low fidelity and high fidelity simulations to validate the SAPA procedure and test the performance of the new alerting algorithm. The low fidelity simulation enabled a determination of minimum approach distance for the worst case over millions of scenarios. The high fidelity simulation enabled an accurate determination of timings and minimum approach distance in the presence of realistic trajectories, communication latencies, and total system error for 108 test cases. The SAPA procedure and the ALAS alerting algorithm were applied to the 750-ft parallel spacing (e.g., SFO 28L/28R) approach problem. With the SAPA procedure as defined in this paper, this study concludes that a 750-ft application does not appear to be feasible, but preliminary results for 1000-ft parallel runways look promising.

A comparison of minimum distance and maximum likelihood techniques for proportion estimation

NASA Technical Reports Server (NTRS)

Woodward, W. A.; Schucany, W. R.; Lindsey, H.; Gray, H. L.

1982-01-01

The estimation of mixing proportions P sub 1, P sub 2,...P sub m in the mixture density f(x) = the sum of the series P sub i F sub i(X) with i = 1 to M is often encountered in agricultural remote sensing problems in which case the p sub i's usually represent crop proportions. In these remote sensing applications, component densities f sub i(x) have typically been assumed to be normally distributed, and parameter estimation has been accomplished using maximum likelihood (ML) techniques. Minimum distance (MD) estimation is examined as an alternative to ML where, in this investigation, both procedures are based upon normal components. Results indicate that ML techniques are superior to MD when component distributions actually are normal, while MD estimation provides better estimates than ML under symmetric departures from normality. When component distributions are not symmetric, however, it is seen that neither of these normal based techniques provides satisfactory results.

Optical design of microlens array for CMOS image sensors

NASA Astrophysics Data System (ADS)

Zhang, Rongzhu; Lai, Liping

2016-10-01

The optical crosstalk between the pixel units can influence the image quality of CMOS image sensor. In the meantime, the duty ratio of CMOS is low because of its pixel structure. These two factors cause the low detection sensitivity of CMOS. In order to reduce the optical crosstalk and improve the fill factor of CMOS image sensor, a microlens array has been designed and integrated with CMOS. The initial parameters of the microlens array have been calculated according to the structure of a CMOS. Then the parameters have been optimized by using ZEMAX and the microlens arrays with different substrate thicknesses have been compared. The results show that in order to obtain the best imaging quality, when the effect of optical crosstalk for CMOS is the minimum, the best distance between microlens array and CMOS is about 19.3 μm. When incident light successively passes through microlens array and the distance, obtaining the minimum facula is around 0.347 um in the active area. In addition, when the incident angle of the light is 0o 22o, the microlens array has obvious inhibitory effect on the optical crosstalk. And the anti-crosstalk distance between microlens array and CMOS is 0 μm 162 μm.

SU-C-BRA-04: Automated Segmentation of Head-And-Neck CT Images for Radiotherapy Treatment Planning Via Multi-Atlas Machine Learning (MAML)

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

Ren, X; Gao, H; Sharp, G

Purpose: Accurate image segmentation is a crucial step during image guided radiation therapy. This work proposes multi-atlas machine learning (MAML) algorithm for automated segmentation of head-and-neck CT images. Methods: As the first step, the algorithm utilizes normalized mutual information as similarity metric, affine registration combined with multiresolution B-Spline registration, and then fuses together using the label fusion strategy via Plastimatch. As the second step, the following feature selection strategy is proposed to extract five feature components from reference or atlas images: intensity (I), distance map (D), box (B), center of gravity (C) and stable point (S). The box feature Bmore » is novel. It describes a relative position from each point to minimum inscribed rectangle of ROI. The center-of-gravity feature C is the 3D Euclidean distance from a sample point to the ROI center of gravity, and then S is the distance of the sample point to the landmarks. Then, we adopt random forest (RF) in Scikit-learn, a Python module integrating a wide range of state-of-the-art machine learning algorithms as classifier. Different feature and atlas strategies are used for different ROIs for improved performance, such as multi-atlas strategy with reference box for brainstem, and single-atlas strategy with reference landmark for optic chiasm. Results: The algorithm was validated on a set of 33 CT images with manual contours using a leave-one-out cross-validation strategy. Dice similarity coefficients between manual contours and automated contours were calculated: the proposed MAML method had an improvement from 0.79 to 0.83 for brainstem and 0.11 to 0.52 for optic chiasm with respect to multi-atlas segmentation method (MA). Conclusion: A MAML method has been proposed for automated segmentation of head-and-neck CT images with improved performance. It provides the comparable result in brainstem and the improved result in optic chiasm compared with MA. Xuhua Ren and Hao Gao were partially supported by the NSFC (#11405105), the 973 Program (#2015CB856000), and the Shanghai Pujiang Talent Program (#14PJ1404500).« less

Spatially balanced provision of health equipment: a cross-sectional study oriented to the identification of challenges to access promotion.

PubMed

Amaral, Pedro Vasconcelos; Rocha, Thiago Augusto Hernandes; Barbosa, Allan Claudius Queiroz; Lein, Adriana; Vissoci, João Ricardo Nickenig

2017-12-04

Access to health services is in part defined by the spatial distribution of healthcare equipment. To ensure equity in the provision of health services, it is important to examine availability across different health care providers taking into account population demand. Given the importance of the equitable provision of health equipment, we evaluate its spatial distribution in Brazil. This study is classified as cross-sectional with an ecological design. We evaluate Brazilian data on distance to available health equipment considering: dialysis machines (385), magnetic resonance imaging (MRI) (257), hospital beds (3675) and bone densitometers (429). We define two distance thresholds (50 km and 200 km) from a municipality to the center of services provision. The balance between infrastructure capacity and potential demand was evaluated to identify a lack or surplus of health services. The distribution of dialysis equipment and bone densitometers is not balanced across Brazilian states, and unmet demand is high. With respect to MRIs, the large capacity of this equipment results in a large excess of supply. However, this characteristic alone cannot account for excesses of supply of over 700%, as is the case of the Federal District when the range is limited to 50 km. At the same time, four states in the Northeastern region of Brazil show a net excess of demand. Some regions do not meet the standard amount of supply defined by Brazilian Ministry of Health. The quantity and distribution of hospital beds are not sufficient to provide full coverage to the population. Our main focus was to evaluate the network of the provision of health equipment in Brazil, considering both private and public sectors conjointly. We take into account two main aspects of a spatially balanced health system: the regional availability of health equipment and the geographic distance between its demand and supply at the municipality level. Some regions do not meet the minimum requirement defined by the Brazilian Ministry of Health regarding the supply of health services.

A label distance maximum-based classifier for multi-label learning.

PubMed

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

2015-01-01

Multi-label classification is useful in many bioinformatics tasks such as gene function prediction and protein site localization. This paper presents an improved neural network algorithm, Max Label Distance Back Propagation Algorithm for Multi-Label Classification. The method was formulated by modifying the total error function of the standard BP by adding a penalty term, which was realized by maximizing the distance between the positive and negative labels. Extensive experiments were conducted to compare this method against state-of-the-art multi-label methods on three popular bioinformatic benchmark datasets. The results illustrated that this proposed method is more effective for bioinformatic multi-label classification compared to commonly used techniques.

MINIMUM CORE MASSES FOR GIANT PLANET FORMATION WITH REALISTIC EQUATIONS OF STATE AND OPACITIES

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

Piso, Ana-Maria A.; Murray-Clay, Ruth A.; Youdin, Andrew N., E-mail: apiso@cfa.harvard.edu

2015-02-20

Giant planet formation by core accretion requires a core that is sufficiently massive to trigger runaway gas accretion in less than the typical lifetime of protoplanetary disks. We explore how the minimum required core mass, M {sub crit}, depends on a non-ideal equation of state (EOS) and on opacity changes due to grain growth across a range of stellocentric distances from 5-100 AU. This minimum M {sub crit} applies when planetesimal accretion does not substantially heat the atmosphere. Compared to an ideal gas polytrope, the inclusion of molecular hydrogen (H{sub 2}) dissociation and variable occupation of H{sub 2} rotational statesmore » increases M {sub crit}. Specifically, M {sub crit} increases by a factor of ∼2 if the H{sub 2} spin isomers, ortho- and parahydrogen, are in thermal equilibrium, and by a factor of ∼2-4 if the ortho-to-para ratio is fixed at 3:1. Lower opacities due to grain growth reduce M {sub crit}. For a standard disk model around a Solar mass star, we calculate M {sub crit} ∼ 8 M {sub ⊕} at 5 AU, decreasing to ∼5 M {sub ⊕} at 100 AU, for a realistic EOS with an equilibrium ortho-to-para ratio and for grain growth to centimeter-sizes. If grain coagulation is taken into account, M {sub crit} may further reduce by up to one order of magnitude. These results for the minimum critical core mass are useful for the interpretation of surveys that find exoplanets at a range of orbital distances.« less

Packed Planetary Systems

NASA Astrophysics Data System (ADS)

Barnes, R.; Greenberg, R.

2005-08-01

Planetary systems display a wide range of appearances, with apparently arbitrary values of semi-major axis, eccentricity, etc. We reduce the complexity of orbital configurations to a single value, δ , which is a measure of how close, over secular timescales ( ˜10,000 orbits), two consecutive planets come to each other. We measure this distance relative to the sum of the radii of their Hill spheres, sometimes referred to as mutual Hill radii (MHR). We determine the closest approach distance by numerically integrating the entire system on coplanar orbits, using minimum masses. For non-resonant systems, close approach occurs during apsidal alignment, either parallel or anti-parallel. For resonant pairs the distance at conjunction determines the closest approach distance. Previous analytic work found that planets on circular orbits were assuredly unstable if they came within 3.5 MHR (i.e. Gladman 1993; Chambers, Wetherill & Boss 1996). We find that most known pairs of jovian planets (including those in our solar system) come within 3.5 -- 7 MHR of each other. We also find that several systems are unstable (their closest approach distance is less than 3.5 MHR). These systems, if they are real, probably exist in an observationally permitted location somewhat different from the current best fit. In these cases, the planets' closest approach distance will most likely also be slightly larger than 3.5 MHR. Most pairs beyond 7 MHR probably experienced post-formation migration (i.e. tidal circularization, inward scattering of small bodies) which moved them further apart. This result is even more remarkable since we have used the minimum masses; most likely the systems are inclined to the line of sight, making the Hill spheres larger, and shrinking δ . This dense packing may reflect a tendency for planets to form as close together as they can without being dynamically unstable. This result further implies there may be a large number of smaller, currently undetectable companions packed in orbits around stars with known planets.

Information Theoretic Extraction of EEG Features for Monitoring Subject Attention

NASA Technical Reports Server (NTRS)

Principe, Jose C.

2000-01-01

The goal of this project was to test the applicability of information theoretic learning (feasibility study) to develop new brain computer interfaces (BCI). The difficulty to BCI comes from several aspects: (1) the effective data collection of signals related to cognition; (2) the preprocessing of these signals to extract the relevant information; (3) the pattern recognition methodology to detect reliably the signals related to cognitive states. We only addressed the two last aspects in this research. We started by evaluating an information theoretic measure of distance (Bhattacharyya distance) for BCI performance with good predictive results. We also compared several features to detect the presence of event related desynchronization (ERD) and synchronization (ERS), and concluded that at least for now the bandpass filtering is the best compromise between simplicity and performance. Finally, we implemented several classifiers for temporal - pattern recognition. We found out that the performance of temporal classifiers is superior to static classifiers but not by much. We conclude by stating that the future of BCI should be found in alternate approaches to sense, collect and process the signals created by populations of neurons. Towards this goal, cross-disciplinary teams of neuroscientists and engineers should be funded to approach BCIs from a much more principled view point.

Covalence of atoms in the heavier transition metals*

PubMed Central

Pauling, Linus

1977-01-01

The observed magnetic properties of the heavier transition metals permit them to have larger metallic valences than their iron-group congeners. With 0.72 metallic orbital, as found for the iron-group metals, the maximum metallic valence and minimum interatomic distance would occur for 8.28 transargononic electrons. The curves of observed interatomic distances for the close-packed metals of the second and third long periods have minima at this point, supporting the assignment of high valences to these metals. Values of the single-bond radii corresponding to these valences are calculated. PMID:16592407

A unified classifier for robust face recognition based on combining multiple subspace algorithms

NASA Astrophysics Data System (ADS)

Ijaz Bajwa, Usama; Ahmad Taj, Imtiaz; Waqas Anwar, Muhammad

2012-10-01

Face recognition being the fastest growing biometric technology has expanded manifold in the last few years. Various new algorithms and commercial systems have been proposed and developed. However, none of the proposed or developed algorithm is a complete solution because it may work very well on one set of images with say illumination changes but may not work properly on another set of image variations like expression variations. This study is motivated by the fact that any single classifier cannot claim to show generally better performance against all facial image variations. To overcome this shortcoming and achieve generality, combining several classifiers using various strategies has been studied extensively also incorporating the question of suitability of any classifier for this task. The study is based on the outcome of a comprehensive comparative analysis conducted on a combination of six subspace extraction algorithms and four distance metrics on three facial databases. The analysis leads to the selection of the most suitable classifiers which performs better on one task or the other. These classifiers are then combined together onto an ensemble classifier by two different strategies of weighted sum and re-ranking. The results of the ensemble classifier show that these strategies can be effectively used to construct a single classifier that can successfully handle varying facial image conditions of illumination, aging and facial expressions.

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

PubMed

Zhang, WenJun

2007-07-01

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

An Improved Global Wind Resource Estimate for Integrated Assessment Models: Preprint

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

Eurek, Kelly; Sullivan, Patrick; Gleason, Michael

This paper summarizes initial steps to improving the robustness and accuracy of global renewable resource and techno-economic assessments for use in integrated assessment models. We outline a method to construct country-level wind resource supply curves, delineated by resource quality and other parameters. Using mesoscale reanalysis data, we generate estimates for wind quality, both terrestrial and offshore, across the globe. Because not all land or water area is suitable for development, appropriate database layers provide exclusions to reduce the total resource to its technical potential. We expand upon estimates from related studies by: using a globally consistent data source of uniquelymore » detailed wind speed characterizations; assuming a non-constant coefficient of performance for adjusting power curves for altitude; categorizing the distance from resource sites to the electric power grid; and characterizing offshore exclusions on the basis of sea ice concentrations. The product, then, is technical potential by country, classified by resource quality as determined by net capacity factor. Additional classifications dimensions are available, including distance to transmission networks for terrestrial wind and distance to shore and water depth for offshore. We estimate the total global wind generation potential of 560 PWh for terrestrial wind with 90% of resource classified as low-to-mid quality, and 315 PWh for offshore wind with 67% classified as mid-to-high quality. These estimates are based on 3.5 MW composite wind turbines with 90 m hub heights, 0.95 availability, 90% array efficiency, and 5 MW/km2 deployment density in non-excluded areas. We compare the underlying technical assumption and results with other global assessments.« less

[Discrimination of donkey meat by NIR and chemometrics].

PubMed

Niu, Xiao-Ying; Shao, Li-Min; Dong, Fang; Zhao, Zhi-Lei; Zhu, Yan

2014-10-01

Donkey meat samples (n = 167) from different parts of donkey body (neck, costalia, rump, and tendon), beef (n = 47), pork (n = 51) and mutton (n = 32) samples were used to establish near-infrared reflectance spectroscopy (NIR) classification models in the spectra range of 4,000~12,500 cm(-1). The accuracies of classification models constructed by Mahalanobis distances analysis, soft independent modeling of class analogy (SIMCA) and least squares-support vector machine (LS-SVM), respectively combined with pretreatment of Savitzky-Golay smooth (5, 15 and 25 points) and derivative (first and second), multiplicative scatter correction and standard normal variate, were compared. The optimal models for intact samples were obtained by Mahalanobis distances analysis with the first 11 principal components (PCs) from original spectra as inputs and by LS-SVM with the first 6 PCs as inputs, and correctly classified 100% of calibration set and 98. 96% of prediction set. For minced samples of 7 mm diameter the optimal result was attained by LS-SVM with the first 5 PCs from original spectra as inputs, which gained an accuracy of 100% for calibration and 97.53% for prediction. For minced diameter of 5 mm SIMCA model with the first 8 PCs from original spectra as inputs correctly classified 100% of calibration and prediction. And for minced diameter of 3 mm Mahalanobis distances analysis and SIMCA models both achieved 100% accuracy for calibration and prediction respectively with the first 7 and 9 PCs from original spectra as inputs. And in these models, donkey meat samples were all correctly classified with 100% either in calibration or prediction. The results show that it is feasible that NIR with chemometrics methods is used to discriminate donkey meat from the else meat.

Optimal architectures for long distance quantum communication.

PubMed

Muralidharan, Sreraman; Li, Linshu; Kim, Jungsang; Lütkenhaus, Norbert; Lukin, Mikhail D; Jiang, Liang

2016-02-15

Despite the tremendous progress of quantum cryptography, efficient quantum communication over long distances (≥ 1000 km) remains an outstanding challenge due to fiber attenuation and operation errors accumulated over the entire communication distance. Quantum repeaters (QRs), as a promising approach, can overcome both photon loss and operation errors, and hence significantly speedup the communication rate. Depending on the methods used to correct loss and operation errors, all the proposed QR schemes can be classified into three categories (generations). Here we present the first systematic comparison of three generations of quantum repeaters by evaluating the cost of both temporal and physical resources, and identify the optimized quantum repeater architecture for a given set of experimental parameters for use in quantum key distribution. Our work provides a roadmap for the experimental realizations of highly efficient quantum networks over transcontinental distances.

Towards the use of similarity distances to music genre classification: A comparative study.

PubMed

Goienetxea, Izaro; Martínez-Otzeta, José María; Sierra, Basilio; Mendialdua, Iñigo

2018-01-01

Music genre classification is a challenging research concept, for which open questions remain regarding classification approach, music piece representation, distances between/within genres, and so on. In this paper an investigation on the classification of generated music pieces is performed, based on the idea that grouping close related known pieces in different sets -or clusters- and then generating in an automatic way a new song which is somehow "inspired" in each set, the new song would be more likely to be classified as belonging to the set which inspired it, based on the same distance used to separate the clusters. Different music pieces representations and distances among pieces are used; obtained results are promising, and indicate the appropriateness of the used approach even in a such a subjective area as music genre classification is.

Towards the use of similarity distances to music genre classification: A comparative study

PubMed Central

Martínez-Otzeta, José María; Sierra, Basilio; Mendialdua, Iñigo

2018-01-01

Music genre classification is a challenging research concept, for which open questions remain regarding classification approach, music piece representation, distances between/within genres, and so on. In this paper an investigation on the classification of generated music pieces is performed, based on the idea that grouping close related known pieces in different sets –or clusters– and then generating in an automatic way a new song which is somehow “inspired” in each set, the new song would be more likely to be classified as belonging to the set which inspired it, based on the same distance used to separate the clusters. Different music pieces representations and distances among pieces are used; obtained results are promising, and indicate the appropriateness of the used approach even in a such a subjective area as music genre classification is. PMID:29444160

Optimal architectures for long distance quantum communication

PubMed Central

Muralidharan, Sreraman; Li, Linshu; Kim, Jungsang; Lütkenhaus, Norbert; Lukin, Mikhail D.; Jiang, Liang

2016-01-01

Despite the tremendous progress of quantum cryptography, efficient quantum communication over long distances (≥1000 km) remains an outstanding challenge due to fiber attenuation and operation errors accumulated over the entire communication distance. Quantum repeaters (QRs), as a promising approach, can overcome both photon loss and operation errors, and hence significantly speedup the communication rate. Depending on the methods used to correct loss and operation errors, all the proposed QR schemes can be classified into three categories (generations). Here we present the first systematic comparison of three generations of quantum repeaters by evaluating the cost of both temporal and physical resources, and identify the optimized quantum repeater architecture for a given set of experimental parameters for use in quantum key distribution. Our work provides a roadmap for the experimental realizations of highly efficient quantum networks over transcontinental distances. PMID:26876670

Optimal architectures for long distance quantum communication

NASA Astrophysics Data System (ADS)

Muralidharan, Sreraman; Li, Linshu; Kim, Jungsang; Lütkenhaus, Norbert; Lukin, Mikhail D.; Jiang, Liang

2016-02-01

Despite the tremendous progress of quantum cryptography, efficient quantum communication over long distances (≥1000 km) remains an outstanding challenge due to fiber attenuation and operation errors accumulated over the entire communication distance. Quantum repeaters (QRs), as a promising approach, can overcome both photon loss and operation errors, and hence significantly speedup the communication rate. Depending on the methods used to correct loss and operation errors, all the proposed QR schemes can be classified into three categories (generations). Here we present the first systematic comparison of three generations of quantum repeaters by evaluating the cost of both temporal and physical resources, and identify the optimized quantum repeater architecture for a given set of experimental parameters for use in quantum key distribution. Our work provides a roadmap for the experimental realizations of highly efficient quantum networks over transcontinental distances.

Support vector machine as a binary classifier for automated object detection in remotely sensed data

NASA Astrophysics Data System (ADS)

Wardaya, P. D.

2014-02-01

In the present paper, author proposes the application of Support Vector Machine (SVM) for the analysis of satellite imagery. One of the advantages of SVM is that, with limited training data, it may generate comparable or even better results than the other methods. The SVM algorithm is used for automated object detection and characterization. Specifically, the SVM is applied in its basic nature as a binary classifier where it classifies two classes namely, object and background. The algorithm aims at effectively detecting an object from its background with the minimum training data. The synthetic image containing noises is used for algorithm testing. Furthermore, it is implemented to perform remote sensing image analysis such as identification of Island vegetation, water body, and oil spill from the satellite imagery. It is indicated that SVM provides the fast and accurate analysis with the acceptable result.

Slit identification for a uranium slab using a binary classifier based on cosmic-ray muon scattering

NASA Astrophysics Data System (ADS)

Xiao, S.; He, W.; Chen, Y.; Dang, X.; Wu, L.; Shuai, M.

2017-12-01

Traditional muon tomographic method has been fraught with difficulty when it is applied to identify some defective high-Z objects or other complicated structures, since it usually gets into trouble when attempting to produce a precise three-dimensional image for such objects. In this paper, we present a binary classifier based on cosmic-ray muon scattering to identify the slit potentially located in a uranium slab. The superiority of this classifier is established by steering clear of the stubborn imaging procedure necessary for the conventional methods. Simulation results demonstrate its capability to spot a horizontal or vertical slit with a reasonable exposure time. The minimum width of a spotted slit is on the level of millimeters or even sub-millimeters. Therefore, this technique will be prospective in terms of monitoring the long-term status of nuclear storage and facilities in real life.

Recruitments of trained citizen volunteering for conventional cardiopulmonary resuscitation are necessary to improve the outcome after out-of-hospital cardiac arrests in remote time-distance area: A nationwide population-based study.

PubMed

Takei, Yutaka; Kamikura, Takahisa; Nishi, Taiki; Maeda, Tetsuo; Sakagami, Satoru; Kubo, Minoru; Inaba, Hideo

2016-08-01

To compare the factors associated with survival after out-of-hospital cardiac arrests (OHCAs) among three time-distance areas (defined as interquartile range of time for emergency medical services response to patient's side). From a nationwide, prospectively collected data on 716,608 OHCAs between 2007 and 2012, this study analyzed 193,914 bystander-witnessed OHCAs without pre-hospital physician involvement. Overall neurologically favourable 1-month survival rates were 7.4%, 4.1% and 1.7% for close, intermediate and remote areas, respectively. We classified BCPR by type (compression-only vs. conventional) and by dispatcher-assisted CPR (DA-CPR) (with vs. without); the effects on time-distance area survival were analyzed by BCPR classification. Association of each BCPR classification with survival was affected by time-distance area and arrest aetiology (p<0.05). The survival rates in the remote area were much higher with conventional BCPR than with compression-only BCPR (odds ratio; 95% confidence interval, 1.26; 1.05-1.51) and with BCPR without DA-CPR than with BCPR with DA-CPR (1.54; 1.29-1.82). Accordingly, we classified BCPR into five groups (no BCPR, compression-only with DA-CPR, conventional with DA-CPR, compression-only without DA-CPR, and conventional without DA-CPR) and analyzed for associations with survival, both cardiac and non-cardiac related, in each time-distance area by multivariate logistic regression analysis. In the remote area, conventional BCPR without DA-CPR significantly improved survival after OHCAs of cardiac aetiology, compared with all the other BCPR groups. Other correctable factors associated with survival were short collapse-to-call and call-to-first CPR intervals. Every effort to recruit trained citizens initiating conventional BCPR should be made in remote time-distance areas. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Horizontal alignment of 5' -> 3' intergene distance segment tropy with respect to the gene as the conserved basis for DNA transcription.

PubMed

Sarin, Hemant

2017-03-01

To study the conserved basis for gene expression in comparative cell types at opposite ends of the cell pressuromodulation spectrum, the lymphatic endothelial cell and the blood microvascular capillary endothelial cell. The mechanism for gene expression is studied in terms of the 5' -> 3' direction paired point tropy quotients ( prpT Q s) and the final 5' -> 3' direction episodic sub-episode block sums split-integrated weighted average-averaged gene overexpression tropy quotient ( esebssiwaagoT Q ). The final 5' -> 3' esebssiwaagoT Q classifies an lymphatic endothelial cell overexpressed gene as a supra-pressuromodulated gene ( esebssiwaagoT Q ≥ 0.25 < 0.75) every time and classifies a blood microvascular capillary endothelial cell overexpressed gene every time as an infra-pressuromodulated gene ( esebssiwaagoT Q < 0.25) (100% sensitivity; 100% specificity). Horizontal alignment of 5' -> 3' intergene distance segment tropy wrt the gene is the basis for DNA transcription in the pressuromodulated state.

Method of Menu Selection by Gaze Movement Using AC EOG Signals

NASA Astrophysics Data System (ADS)

Kanoh, Shin'ichiro; Futami, Ryoko; Yoshinobu, Tatsuo; Hoshimiya, Nozomu

A method to detect the direction and the distance of voluntary eye gaze movement from EOG (electrooculogram) signals was proposed and tested. In this method, AC-amplified vertical and horizontal transient EOG signals were classified into 8-class directions and 2-class distances of voluntary eye gaze movements. A horizontal and a vertical EOGs during eye gaze movement at each sampling time were treated as a two-dimensional vector, and the center of gravity of the sample vectors whose norms were more than 80% of the maximum norm was used as a feature vector to be classified. By the classification using the k-nearest neighbor algorithm, it was shown that the averaged correct detection rates on each subject were 98.9%, 98.7%, 94.4%, respectively. This method can avoid strict EOG-based eye tracking which requires DC amplification of very small signal. It would be useful to develop robust human interfacing systems based on menu selection for severely paralyzed patients.

A swarm-trained k-nearest prototypes adaptive classifier with automatic feature selection for interval data.

PubMed

Silva Filho, Telmo M; Souza, Renata M C R; Prudêncio, Ricardo B C

2016-08-01

Some complex data types are capable of modeling data variability and imprecision. These data types are studied in the symbolic data analysis field. One such data type is interval data, which represents ranges of values and is more versatile than classic point data for many domains. This paper proposes a new prototype-based classifier for interval data, trained by a swarm optimization method. Our work has two main contributions: a swarm method which is capable of performing both automatic selection of features and pruning of unused prototypes and a generalized weighted squared Euclidean distance for interval data. By discarding unnecessary features and prototypes, the proposed algorithm deals with typical limitations of prototype-based methods, such as the problem of prototype initialization. The proposed distance is useful for learning classes in interval datasets with different shapes, sizes and structures. When compared to other prototype-based methods, the proposed method achieves lower error rates in both synthetic and real interval datasets. Copyright © 2016 Elsevier Ltd. All rights reserved.

Minimum-Light Spectral Classifications for M-Type Mira Variables

NASA Astrophysics Data System (ADS)

Wing, Robert F.

2015-08-01

Many bright, well-known Mira variables, including most of the 378 stars for which the AAVSO publishes predicted dates of maximum and minimum in its annual Bulletins, have never been spectroscopically observed close to the time of minimum light, and consequently their catalogued ranges in spectral type are often grossly and misleadingly under-represented. In an effort to improve this situation, for the past 12 years I have been using my 6-color system of narrow-band classification photometry to observe Miras predicted to be near minimum light at the times of my biannual observing runs with the CTIO 0.9-m telescope (operated by the SMARTS consortium). The 6-color system measures the 7100 A band of TiO, which serves to classify stars in the interval K4 to M8, and the 1.06 micron band of VO, which is effective for stars of type M8 and later. To date I have made 431 observations of approximately 220 different (and mostly southern) Miras. Examples are shown of the observed 6-color spectra, and the classifications derived from them.

13CO Survey of Northern Intermediate-Mass Star-Forming Regions

NASA Astrophysics Data System (ADS)

Lundquist, Michael J.; Kobulnicky, H. A.; Kerton, C. R.

2014-01-01

We conducted a survey of 13CO with the OSO 20-m telescope toward 68 intermediate-mass star-forming regions (IM SFRs) visible in the northern hemisphere. These regions have mostly been excluded from previous CO surveys and were selected from IRAS colors that specify cool dust and large PAH contribution. These regions are known to host stars up to, but not exceeding, about 8 solar masses. We detect 13CO in 57 of the 68 IM SFRs down to a typical RMS of ~50 mK. We present kinematic distances, minimum column densities, and minimum masses for these IM SFRs.

Tracking of white-tailed deer migration by Global Positioning System

USGS Publications Warehouse

Nelson, M.E.; Mech, L.D.; Frame, P.F.

2004-01-01

Based on global positioning system (GPS) radiocollars in northeastern Minnesota, deer migrated 23-45 km in spring during 31-356 h, deviating a maximum 1.6-4.0 km perpendicular from a straight line of travel between their seasonal ranges. They migrated a minimum of 2.1-18.6 km/day over 11-56 h during 2-14 periods of travel. Minimum travel during 1-h intervals averaged 1.5 km/h. Deer paused 1-12 times, averaging 24 h/pause. Deer migrated similar distances in autumn with comparable rates and patterns of travel.

A methodology for the generation of the 2-D map from unknown navigation environment by traveling a short distance

NASA Technical Reports Server (NTRS)

Bourbakis, N.; Sarkar, D.

1994-01-01

A technique for generation of a 2-D space map by traveling a short distance is described. The space to be mapped can be classified as: (1) space without obstacles, (2) space with stationary obstacles, and (3) space with moving obstacles. This paper presents the methodology used to generate a 2-D map of an unknown navigation space. The ability to minimize the redundancy during traveling and maximize the confidence function for generation of the map are advantages of this technique.

A simplified flight-test method for determining aircraft takeoff performance that includes effects of pilot technique

NASA Technical Reports Server (NTRS)

Larson, T. J.; Schweikhard, W. G.

1974-01-01

A method for evaluating aircraft takeoff performance from brake release to air-phase height that requires fewer tests than conventionally required is evaluated with data for the XB-70 airplane. The method defines the effects of pilot technique on takeoff performance quantitatively, including the decrease in acceleration from drag due to lift. For a given takeoff weight and throttle setting, a single takeoff provides enough data to establish a standardizing relationship for the distance from brake release to any point where velocity is appropriate to rotation. The lower rotation rates penalized takeoff performance in terms of ground roll distance; the lowest observed rotation rate required a ground roll distance that was 19 percent longer than the highest. Rotations at the minimum rate also resulted in lift-off velocities that were approximately 5 knots lower than the highest rotation rate at any given lift-off distance.

Ranging algebraically with more observations than unknowns

NASA Astrophysics Data System (ADS)

Awange, J. L.; Fukuda, Y.; Takemoto, S.; Ateya, I. L.; Grafarend, E. W.

2003-07-01

In the recently developed Spatial Reference System that is designed to check and control the accuracy of the three-dimensional coordinate measuring machines and tooling equipment (Metronom US., Inc., Ann Arbor: http://www.metronomus.com), the coordinates of the edges of the instrument are computed from distances of the bars. The use of distances in industrial application is fast gaining momentum just as in Geodesy and in Geophysical applications and thus necessitating efficient algorithms to solve the nonlinear distance equations. Whereas the ranging problem with minimum known stations was considered in our previous contribution in the same Journal, the present contribution extends to the case where one is faced with many distance observations than unknowns (overdetermined case) as is usually the case in practise. Using the Gauss-Jacobi Combinatorial approach, we demonstrate how one can proceed to position without reverting to iterative and linearizing procedures such as Newton's or Least Squares approach.

Transitions between corona, glow, and spark regimes of nanosecond repetitively pulsed discharges in air at atmospheric pressure

NASA Astrophysics Data System (ADS)

Pai, David Z.; Lacoste, Deanna A.; Laux, Christophe O.

2010-05-01

In atmospheric pressure air preheated from 300 to 1000 K, the nanosecond repetitively pulsed (NRP) method has been used to generate corona, glow, and spark discharges. Experiments have been performed to determine the parameter space (applied voltage, pulse repetition frequency, ambient gas temperature, and interelectrode gap distance) of each discharge regime. In particular, the experimental conditions necessary for the glow regime of NRP discharges have been determined, with the notable result that there exists a minimum and maximum gap distance for its existence at a given ambient gas temperature. The minimum gap distance increases with decreasing gas temperature, whereas the maximum does not vary appreciably. To explain the experimental results, an analytical model is developed to explain the corona-to-glow (C-G) and glow-to-spark (G-S) transitions. The C-G transition is analyzed in terms of the avalanche-to-streamer transition and the breakdown field during the conduction phase following the establishment of a conducting channel across the discharge gap. The G-S transition is determined by the thermal ionization instability, and we show analytically that this transition occurs at a certain reduced electric field for the NRP discharges studied here. This model shows that the electrode geometry plays an important role in the existence of the NRP glow regime at a given gas temperature. We derive a criterion for the existence of the NRP glow regime as a function of the ambient gas temperature, pulse repetition frequency, electrode radius of curvature, and interelectrode gap distance.

Floating and Tether-Coupled Adhesion of Bacteria to Hydrophobic and Hydrophilic Surfaces

PubMed Central

2018-01-01

Models for bacterial adhesion to substratum surfaces all include uncertainty with respect to the (ir)reversibility of adhesion. In a model, based on vibrations exhibited by adhering bacteria parallel to a surface, adhesion was described as a result of reversible binding of multiple bacterial tethers that detach from and successively reattach to a surface, eventually making bacterial adhesion irreversible. Here, we use total internal reflection microscopy to determine whether adhering bacteria also exhibit variations over time in their perpendicular distance above surfaces. Streptococci with fibrillar surface tethers showed perpendicular vibrations with amplitudes of around 5 nm, regardless of surface hydrophobicity. Adhering, nonfibrillated streptococci vibrated with amplitudes around 20 nm above a hydrophobic surface. Amplitudes did not depend on ionic strength for either strain. Calculations of bacterial energies from their distances above the surfaces using the Boltzman equation showed that bacteria with fibrillar tethers vibrated as a harmonic oscillator. The energy of bacteria without fibrillar tethers varied with distance in a comparable fashion as the DLVO (Derjaguin, Landau, Verwey, and Overbeek)-interaction energy. Distance variations above the surface over time of bacteria with fibrillar tethers are suggested to be governed by the harmonic oscillations, allowed by elasticity of the tethers, piercing through the potential energy barrier. Bacteria without fibrillar tethers “float” above a surface in the secondary energy minimum, with their perpendicular displacement restricted by their thermal energy and the width of the secondary minimum. The distinction between “tether-coupled” and “floating” adhesion is new, and may have implications for bacterial detachment strategies. PMID:29649869

Assessing the Utility of Uav-Borne Hyperspectral Image and Photogrammetry Derived 3d Data for Wetland Species Distribution Quick Mapping

NASA Astrophysics Data System (ADS)

Li, Q. S.; Wong, F. K. K.; Fung, T.

2017-08-01

Lightweight unmanned aerial vehicle (UAV) loaded with novel sensors offers a low cost and minimum risk solution for data acquisition in complex environment. This study assessed the performance of UAV-based hyperspectral image and digital surface model (DSM) derived from photogrammetric point clouds for 13 species classification in wetland area of Hong Kong. Multiple feature reduction methods and different classifiers were compared. The best result was obtained when transformed components from minimum noise fraction (MNF) and DSM were combined in support vector machine (SVM) classifier. Wavelength regions at chlorophyll absorption green peak, red, red edge and Oxygen absorption at near infrared were identified for better species discrimination. In addition, input of DSM data reduces overestimation of low plant species and misclassification due to the shadow effect and inter-species morphological variation. This study establishes a framework for quick survey and update on wetland environment using UAV system. The findings indicate that the utility of UAV-borne hyperspectral and derived tree height information provides a solid foundation for further researches such as biological invasion monitoring and bio-parameters modelling in wetland.

An improved algorithm for evaluating trellis phase codes

NASA Technical Reports Server (NTRS)

Mulligan, M. G.; Wilson, S. G.

1982-01-01

A method is described for evaluating the minimum distance parameters of trellis phase codes, including CPFSK, partial response FM, and more importantly, coded CPM (continuous phase modulation) schemes. The algorithm provides dramatically faster execution times and lesser memory requirements than previous algorithms. Results of sample calculations and timing comparisons are included.

An improved algorithm for evaluating trellis phase codes

NASA Technical Reports Server (NTRS)

Mulligan, M. G.; Wilson, S. G.

1984-01-01

A method is described for evaluating the minimum distance parameters of trellis phase codes, including CPFSK, partial response FM, and more importantly, coded CPM (continuous phase modulation) schemes. The algorithm provides dramatically faster execution times and lesser memory requirements than previous algorithms. Results of sample calculations and timing comparisons are included.

78 FR 61251 - Radio Broadcasting Services; Heber Springs, Arkansas.

Federal Register 2010, 2011, 2012, 2013, 2014

2013-10-03

...] Radio Broadcasting Services; Heber Springs, Arkansas. AGENCY: Federal Communications Commission. ACTION... third local service. Channel 270C3 can be allotted to Heber Springs consistent with the minimum distance... community. The reference coordinates are 35-34-12 NL and 91-55-41 WL. DATES: Comments must be filed on or...

Some Evidence of Continuing Linguistic Acquisitions in Learning Adolescents.

ERIC Educational Resources Information Center

Thomas, Elizabeth K.; Walmsley, Sean A.

The linguistic development of 42 learning disabled students 10-16 years old was examined. Responses were elicited to five linguistic structures, including the distinction between "ask" and "tell", pronominal restriction, and the minimum distance principle. Data were analyzed in terms of three groups based on Verbal and Performance differentials on…

Evaluation of Semi-supervised Learning for Classification of Protein Crystallization Imagery.

PubMed

Sigdel, Madhav; Dinç, İmren; Dinç, Semih; Sigdel, Madhu S; Pusey, Marc L; Aygün, Ramazan S

2014-03-01

In this paper, we investigate the performance of two wrapper methods for semi-supervised learning algorithms for classification of protein crystallization images with limited labeled images. Firstly, we evaluate the performance of semi-supervised approach using self-training with naïve Bayesian (NB) and sequential minimum optimization (SMO) as the base classifiers. The confidence values returned by these classifiers are used to select high confident predictions to be used for self-training. Secondly, we analyze the performance of Yet Another Two Stage Idea (YATSI) semi-supervised learning using NB, SMO, multilayer perceptron (MLP), J48 and random forest (RF) classifiers. These results are compared with the basic supervised learning using the same training sets. We perform our experiments on a dataset consisting of 2250 protein crystallization images for different proportions of training and test data. Our results indicate that NB and SMO using both self-training and YATSI semi-supervised approaches improve accuracies with respect to supervised learning. On the other hand, MLP, J48 and RF perform better using basic supervised learning. Overall, random forest classifier yields the best accuracy with supervised learning for our dataset.

Learning time series for intelligent monitoring

NASA Technical Reports Server (NTRS)

Manganaris, Stefanos; Fisher, Doug

1994-01-01

We address the problem of classifying time series according to their morphological features in the time domain. In a supervised machine-learning framework, we induce a classification procedure from a set of preclassified examples. For each class, we infer a model that captures its morphological features using Bayesian model induction and the minimum message length approach to assign priors. In the performance task, we classify a time series in one of the learned classes when there is enough evidence to support that decision. Time series with sufficiently novel features, belonging to classes not present in the training set, are recognized as such. We report results from experiments in a monitoring domain of interest to NASA.

The challenge of global water access monitoring: evaluating straight-line distance versus self-reported travel time among rural households in Mozambique.

PubMed

Ho, Jeff C; Russel, Kory C; Davis, Jennifer

2014-03-01

Support is growing for the incorporation of fetching time and/or distance considerations in the definition of access to improved water supply used for global monitoring. Current efforts typically rely on self-reported distance and/or travel time data that have been shown to be unreliable. To date, however, there has been no head-to-head comparison of such indicators with other possible distance/time metrics. This study provides such a comparison. We examine the association between both straight-line distance and self-reported one-way travel time with measured route distances to water sources for 1,103 households in Nampula province, Mozambique. We find straight-line, or Euclidean, distance to be a good proxy for route distance (R(2) = 0.98), while self-reported travel time is a poor proxy (R(2) = 0.12). We also apply a variety of time- and distance-based indicators proposed in the literature to our sample data, finding that the share of households classified as having versus lacking access would differ by more than 70 percentage points depending on the particular indicator employed. This work highlights the importance of the ongoing debate regarding valid, reliable, and feasible strategies for monitoring progress in the provision of improved water supply services.

ELECTROFISHING IN BOATABLE RIVERS: DOES SAMPLING DESIGN AFFECT BIOASSESSMENT METRICS?

EPA Science Inventory

Data were collected from 60 boatable sites using an electrofishing design that permitted comparisons of the effects of designs and distances on fish assemblage metrics. Sites were classified a priori as Run-of-the-River (ROR) or Restricted Flow (RF). Data representing four diff...

Identification of terrain cover using the optimum polarimetric classifier

NASA Technical Reports Server (NTRS)

Kong, J. A.; Swartz, A. A.; Yueh, H. A.; Novak, L. M.; Shin, R. T.

1988-01-01

A systematic approach for the identification of terrain media such as vegetation canopy, forest, and snow-covered fields is developed using the optimum polarimetric classifier. The covariance matrices for various terrain cover are computed from theoretical models of random medium by evaluating the scattering matrix elements. The optimal classification scheme makes use of a quadratic distance measure and is applied to classify a vegetation canopy consisting of both trees and grass. Experimentally measured data are used to validate the classification scheme. Analytical and Monte Carlo simulated classification errors using the fully polarimetric feature vector are compared with classification based on single features which include the phase difference between the VV and HH polarization returns. It is shown that the full polarimetric results are optimal and provide better classification performance than single feature measurements.

Comparison of Classifier Architectures for Online Neural Spike Sorting.

PubMed

Saeed, Maryam; Khan, Amir Ali; Kamboh, Awais Mehmood

2017-04-01

High-density, intracranial recordings from micro-electrode arrays need to undergo Spike Sorting in order to associate the recorded neuronal spikes to particular neurons. This involves spike detection, feature extraction, and classification. To reduce the data transmission and power requirements, on-chip real-time processing is becoming very popular. However, high computational resources are required for classifiers in on-chip spike-sorters, making scalability a great challenge. In this review paper, we analyze several popular classifiers to propose five new hardware architectures using the off-chip training with on-chip classification approach. These include support vector classification, fuzzy C-means classification, self-organizing maps classification, moving-centroid K-means classification, and Cosine distance classification. The performance of these architectures is analyzed in terms of accuracy and resource requirement. We establish that the neural networks based Self-Organizing Maps classifier offers the most viable solution. A spike sorter based on the Self-Organizing Maps classifier, requires only 7.83% of computational resources of the best-reported spike sorter, hierarchical adaptive means, while offering a 3% better accuracy at 7 dB SNR.

Effect of available space and previous contact in the social integration of Saint Croix and Suffolk ewes.

PubMed

Orihuela, A; Averós, X; Solano, J; Clemente, N; Estevez, I

2016-03-01

Reproduction in tropical sheep is not affected by season, whereas the reproductive cycle of temperate-climate breeds such as Suffolk depends on the photoperiod. Close contact with tropical ewes during the anestrous period might induce Suffolk ewes to cycle, making the use of artificial light or hormonal treatments unnecessary. However, the integration of both breeds within the social group would be necessary to trigger this effect, and so the aim of the experiment was to determine the speed of integration of 2 groups of Saint Croix and Suffolk ewes into a single flock, according to space allowance and previous experience. For this, 6 groups of 10 ewes (half from each breed) from both breeds, housed at 2 or 4 m/ewe (3 groups/treatment) and with or without previous contact with the other breed, were monitored for 3 d. Each observation day, the behavior, movement, and use of space of ewes were collected during 10 min at 1-h intervals between 0900 and 1400 h. Generalized linear mixed models were used to test the effects of breed, space allowance, and previous experience on behavior, movement, and use of space. Net distances, interbreed farthest neighbor distance, mean interbreed distance, and walking frequencies were greater at 4 m/ewe ( < 0.05). Intrabreed nearest neighbor, mean intrabreed neighbor, and interbreed nearest neighbor distances and minimum convex polygons at 4 m/ewe were greatest for Saint Croix ewes, whereas the opposite was found for lying down ( < 0.05). Experienced ewes showed larger intrabreed nearest neighbor distances, minimum convex polygons, and home range overlapping ( < 0.05). Experienced ewes at 4 m/ewe showed longest total distances and step lengths and greatest movement activity ( < 0.05). Experienced ewes walked longer total distances during Day 1 and 2 ( < 0.05). Lying down frequency was greater for Day 3 than Day 1 ( < 0.05), and Suffolk ewes kept longer interindividual distances during Day 1 ( < 0.05). After 3 d of cohabitation, Suffolk and Saint Croix ewes did not fully integrate into a cohesive flock, with each breed displaying specific behavioral patterns. Decreasing space allowance and previous experience resulted in limited benefits for the successful group cohesion. Longer cohabitation periods might result in complete integration, although practical implementation might be difficult.

Node Deployment with k-Connectivity in Sensor Networks for Crop Information Full Coverage Monitoring

PubMed Central

Liu, Naisen; Cao, Weixing; Zhu, Yan; Zhang, Jingchao; Pang, Fangrong; Ni, Jun

2016-01-01

Wireless sensor networks (WSNs) are suitable for the continuous monitoring of crop information in large-scale farmland. The information obtained is great for regulation of crop growth and achieving high yields in precision agriculture (PA). In order to realize full coverage and k-connectivity WSN deployment for monitoring crop growth information of farmland on a large scale and to ensure the accuracy of the monitored data, a new WSN deployment method using a genetic algorithm (GA) is here proposed. The fitness function of GA was constructed based on the following WSN deployment criteria: (1) nodes must be located in the corresponding plots; (2) WSN must have k-connectivity; (3) WSN must have no communication silos; (4) the minimum distance between node and plot boundary must be greater than a specific value to prevent each node from being affected by the farmland edge effect. The deployment experiments were performed on natural farmland and on irregular farmland divided based on spatial differences of soil nutrients. Results showed that both WSNs gave full coverage, there were no communication silos, and the minimum connectivity of nodes was equal to k. The deployment was tested for different values of k and transmission distance (d) to the node. The results showed that, when d was set to 200 m, as k increased from 2 to 4 the minimum connectivity of nodes increases and is equal to k. When k was set to 2, the average connectivity of all nodes increased in a linear manner with the increase of d from 140 m to 250 m, and the minimum connectivity does not change. PMID:27941704

Method for selecting minimum width of leaf in multileaf adjustable collimator while inhibiting passage of particle beams of radiation through sawtooth joints between collimator leaves

DOEpatents

Ludewigt, Bernhard; Bercovitz, John; Nyman, Mark; Chu, William

1995-01-01

A method is disclosed for selecting the minimum width of individual leaves of a multileaf adjustable collimator having sawtooth top and bottom surfaces between adjacent leaves of a first stack of leaves and sawtooth end edges which are capable of intermeshing with the corresponding sawtooth end edges of leaves in a second stack of leaves of the collimator. The minimum width of individual leaves in the collimator, each having a sawtooth configuration in the surface facing another leaf in the same stack and a sawtooth end edge, is selected to comprise the sum of the penetration depth or range of the particular type of radiation comprising the beam in the particular material used for forming the leaf; plus the total path length across all the air gaps in the area of the joint at the edges between two leaves defined between lines drawn across the peaks of adjacent sawtooth edges; plus at least one half of the length or period of a single sawtooth. To accomplish this, in accordance with the method of the invention, the penetration depth of the particular type of radiation in the particular material to be used for the collimator leaf is first measured. Then the distance or gap between adjoining or abutting leaves is selected, and the ratio of this distance to the height of the sawteeth is selected. Finally the number of air gaps through which the radiation will pass between sawteeth is determined by selecting the number of sawteeth to be formed in the joint. The measurement and/or selection of these parameters will permit one to determine the minimum width of the leaf which is required to prevent passage of the beam through the sawtooth joint.

Minimum viewing angle for visually guided ground speed control in bumblebees.

PubMed

Baird, Emily; Kornfeldt, Torill; Dacke, Marie

2010-05-01

To control flight, flying insects extract information from the pattern of visual motion generated during flight, known as optic flow. To regulate their ground speed, insects such as honeybees and Drosophila hold the rate of optic flow in the axial direction (front-to-back) constant. A consequence of this strategy is that its performance varies with the minimum viewing angle (the deviation from the frontal direction of the longitudinal axis of the insect) at which changes in axial optic flow are detected. The greater this angle, the later changes in the rate of optic flow, caused by changes in the density of the environment, will be detected. The aim of the present study is to examine the mechanisms of ground speed control in bumblebees and to identify the extent of the visual range over which optic flow for ground speed control is measured. Bumblebees were trained to fly through an experimental tunnel consisting of parallel vertical walls. Flights were recorded when (1) the distance between the tunnel walls was either 15 or 30 cm, (2) the visual texture on the tunnel walls provided either strong or weak optic flow cues and (3) the distance between the walls changed abruptly halfway along the tunnel's length. The results reveal that bumblebees regulate ground speed using optic flow cues and that changes in the rate of optic flow are detected at a minimum viewing angle of 23-30 deg., with a visual field that extends to approximately 155 deg. By measuring optic flow over a visual field that has a low minimum viewing angle, bumblebees are able to detect and respond to changes in the proximity of the environment well before they are encountered.

Multiclass Continuous Correspondence Learning

NASA Technical Reports Server (NTRS)

Bue, Brian D,; Thompson, David R.

2011-01-01

We extend the Structural Correspondence Learning (SCL) domain adaptation algorithm of Blitzer er al. to the realm of continuous signals. Given a set of labeled examples belonging to a 'source' domain, we select a set of unlabeled examples in a related 'target' domain that play similar roles in both domains. Using these 'pivot samples, we map both domains into a common feature space, allowing us to adapt a classifier trained on source examples to classify target examples. We show that when between-class distances are relatively preserved across domains, we can automatically select target pivots to bring the domains into correspondence.

Color Image Classification Using Block Matching and Learning

NASA Astrophysics Data System (ADS)

Kondo, Kazuki; Hotta, Seiji

In this paper, we propose block matching and learning for color image classification. In our method, training images are partitioned into small blocks. Given a test image, it is also partitioned into small blocks, and mean-blocks corresponding to each test block are calculated with neighbor training blocks. Our method classifies a test image into the class that has the shortest total sum of distances between mean blocks and test ones. We also propose a learning method for reducing memory requirement. Experimental results show that our classification outperforms other classifiers such as support vector machine with bag of keypoints.

Oxygen desaturation during the six-minute walk test in COPD patients*

PubMed Central

Moreira, Maria Ângela Fontoura; de Medeiros, Gabriel Arriola; Boeno, Francesco Pinto; Sanches, Paulo Roberto Stefani; da Silva, Danton Pereira; Müller, André Frotta

2014-01-01

Objective: To evaluate the behavior of oxygen saturation curves throughout the six-minute walk test (6MWT) in patients with COPD. Methods: We included 85 patients, all of whom underwent spirometry and were classified as having moderate COPD (modCOPD, n = 30) or severe COPD (sevCOPD, n = 55). All of the patients performed a 6MWT, in a 27-m corridor with continuous SpO2 and HR monitoring by telemetry. We studied the SpO2 curves in order to determine the time to a 4% decrease in SpO2, the time to the minimum SpO2 (Tmin), and the post-6MWT time to return to the initial SpO2, the last designated recovery time (RT). For each of those curves, we calculated the slope. Results: The mean age in the modCOPD and sevCOPD groups was 66 ± 10 years and 62 ± 11 years, respectively. At baseline, SpO2 was > 94% in all of the patients; none received supplemental oxygen during the 6MWT; and none of the tests were interrupted. The six-minute walk distance did not differ significantly between the groups. The SpO2 values were lowest in the sevCOPD group. There was no difference between the groups regarding RT. In 71% and 63% of the sevCOPD and modCOPD group patients, respectively, a ≥ 4% decrease in SpO2 occurred within the first minute. We found that FEV1% correlated significantly with the ΔSpO2 (r = −0.398; p < 0.001), Tmin (r = −0.449; p < 0.001), and minimum SpO2 (r = 0.356; p < 0.005). Conclusions: In the sevCOPD group, in comparison with the modCOPD group, SpO2 was lower and the Tmin was greater, suggesting a worse prognosis in the former. PMID:25029644

REDSHIFT-INDEPENDENT DISTANCES IN THE NASA/IPAC EXTRAGALACTIC DATABASE: METHODOLOGY, CONTENT, AND USE OF NED-D

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

Steer, Ian; Madore, Barry F.; Mazzarella, Joseph M.

Estimates of galaxy distances based on indicators that are independent of cosmological redshift are fundamental to astrophysics. Researchers use them to establish the extragalactic distance scale, to underpin estimates of the Hubble constant, and to study peculiar velocities induced by gravitational attractions that perturb the motions of galaxies with respect to the “Hubble flow” of universal expansion. In 2006 the NASA/IPAC Extragalactic Database (NED) began making available a comprehensive compilation of redshift-independent extragalactic distance estimates. A decade later, this compendium of distances (NED-D) now contains more than 100,000 individual estimates based on primary and secondary indicators, available for more thanmore » 28,000 galaxies, and compiled from over 2000 references in the refereed astronomical literature. This paper describes the methodology, content, and use of NED-D, and addresses challenges to be overcome in compiling such distances. Currently, 75 different distance indicators are in use. We include a figure that facilitates comparison of the indicators with significant numbers of estimates in terms of the minimum, 25th percentile, median, 75th percentile, and maximum distances spanned. Brief descriptions of the indicators, including examples of their use in the database, are given in an appendix.« less

Nutritional analysis and microbiological evaluation of commercially available enteral diets for cats.

PubMed

Prantil, Lori R; Markovich, Jessica E; Heinze, Cailin R; Linder, Deborah E; Tams, Todd R; Freeman, Lisa M

2016-01-01

To determine the prevalence of nutrients less than or greater than accepted standards in commercially available enteral diets for cats, and to identify contamination incidence in enteral diets for cats. Prospective cross-sectional study. University teaching hospital. Seven commercial enteral diets for cats. Labels were evaluated to determine if diets were intended to be nutritionally complete and balanced. One diet under storage techniques partially representative of clinical conditions was sampled on days 0, 1, 3, 5, and 7 of storage for aerobic bacterial culture. All 7 diets were analyzed for key nutrients and results were compared to Association of American Feed Control Officials (AAFCO) Nutrient Profiles for Adult Cats for maintenance and National Research Council recommended allowance (NRC-RA). From label information, 4 diets were classified as complete and balanced and 3 diets were classified as not complete and balanced. All 7 diets had at least 1 nutrient less than the AAFCO minimums and the NRC-RA. The total number of nutrients less than AAFCO minimums ranged from 3 to 9 (median = 4), with iron, potassium, and manganese being the most common. Concentrations of some nutrients were undetectable. None of the samples tested had a positive aerobic culture at baseline (day 0) or on subsequent samples from days 1, 3, 5, and 7 under any storage condition. None of the diets analyzed met all of the minimum nutrient concentrations. While short-term feeding may not be of concern for an individual patient, clinicians should be aware of potential nutritional limitations when feeding enteral diets to ill or injured cats. © Veterinary Emergency and Critical Care Society 2015.

National forest trail users: planning for recreation opportunities

Treesearch

John J. Daigle; Alan E. Watson; Glenn E. Haas

1994-01-01

National forest trail users in four geographical regions of the United States are described based on participation in clusters of recreation activities. Visitors are classified into day hiking, undeveloped recreation, and two developed camping and hiking activity clusters for the Appalachian, Pacific, Rocky Mountain, and Southwestern regions. Distance and time traveled...

Distance M-Me: A novel parameter having significant potential as a predictor of mandibular growth.

PubMed

Jain, Parul; Kaul, Rahul; Mukhopadhyay, Santanu; Saha, Subrata; Sarkar, Subir

2017-01-01

The purpose of the present study was to investigate the relationship of the measured distance between two mandibular points (distance M-Me) to chronological age and to find out whether the absolute values of distance M-Me could be classified age-wise into a unique range, which could be directly read for predicting the stage of mandibular growth. The study sample consists of lateral cephalometric records of 65 patients (34 females and 31 males; age range: 6-21 years). Chronological age was calculated in decimal years. Lateral cephalograms were assessed by two independent examiners. Points M and Me were located on the lateral cephalograms, and linear distance between them was measured. Pearson product-moment correlation coefficients showed a high correlation between chronological age and distance M-Me (0.746 for females and 0.869 for males, p < 0.01). When the values of distance M-Me were compared with chronological age, it was possible to make four age groups (for females and males separately), where each group showed a unique range of value for distance M-Me. The values increased with increasing age. Increase in value of distance M-Me with age, showing reduced individual variation, depicts a well-conserved linear dimension. Values of distance M-Me can be directly read for predicting the stage of mandibular growth and can be used as a valuable adjunct or substitute to chronological age.

[Urban heat island intensity and its grading in Liaoning Province of Northeast China].

PubMed

Li, Li-Guang; Wang, Hong-Bo; Jia, Qing-Yu; Lü, Guo-Hong; Wang, Xiao-Ying; Zhang, Yu-Shu; Ai, Jing-Feng

2012-05-01

According to the recorded air temperature data and their continuity of each weather station, the location of each weather station, the numbers of and the distances among the weather stations, and the records on the weather stations migration, several weather stations in Liaoning Province were selected as the urban and rural representative stations to study the characteristics of urban heat island (UHI) intensity in the province. Based on the annual and monthly air temperature data of the representative stations, the ranges and amplitudes of the UHI intensity were analyzed, and the grades of the UHI intensity were classified. The Tieling station, Dalian station, Anshan station, Chaoyang station, Dandong station, and Jinzhou station and the 18 stations including Tai' an station were selected as the representative urban and rural weather stations, respectively. In 1980-2009, the changes of the annual UHI intensity in the 6 representative cities differed. The annual UHI intensity in Tieling was in a decreasing trend, while that in the other five cities was in an increasing trend. The UHI intensity was strong in Tieling but weak in Dalian. The changes of the monthly UHI intensity in the 6 representative cities also differed. The distribution of the monthly UHI intensity in Dandong, Jinzhou and Tieling took a "U" shape, with the maximum and minimum appeared in January and in May-August, respectively, indicating that the monthly UHI intensity was strong in winter and weak in summer. The ranges of the annual and monthly UHI intensity in the 6 cities were 0.57-2.15 degrees C and -0.70-4.60 degrees C, and the ranges of 0.5-2.0 degrees C accounted for 97.8% and 72.3%, respectively. The UHI intensity in the province could be classified into 4 grades, i. e., weak, strong, stronger and strongest.

The origin of facet selectivity and alignment in anatase TiO 2 nanoparticles in electrolyte solutions: implications for oriented attachment in metal oxides

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

Sushko, M. L.; Rosso, K. M.

Atomic-to-mesoscale simulations were used to reveal the origin of oriented attachment between anatase TiO2 nanoparticles in aqueous HCl solutions. Analysis of the distance and pH dependence of interparticle interactions demonstrates that ion correlation forces are responsible for facet-specific attraction and rotation into lattice co-alignment at long-range. These forces give rise to a metastable solvent separated capture minimum on the disjoining pressure-distance curve, with the barrier to attachment largely due to steric hydration forces from structured intervening solvent.

A study of polaritonic transparency in couplers made from excitonic materials

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

Singh, Mahi R.; Racknor, Chris

2015-03-14

We have studied light matter interaction in quantum dot and exciton-polaritonic coupler hybrid systems. The coupler is made by embedding two slabs of an excitonic material (CdS) into a host excitonic material (ZnO). An ensemble of non-interacting quantum dots is doped in the coupler. The bound exciton polariton states are calculated in the coupler using the transfer matrix method in the presence of the coupling between the external light (photons) and excitons. These bound exciton-polaritons interact with the excitons present in the quantum dots and the coupler is acting as a reservoir. The Schrödinger equation method has been used tomore » calculate the absorption coefficient in quantum dots. It is found that when the distance between two slabs (CdS) is greater than decay length of evanescent waves the absorption spectrum has two peaks and one minimum. The minimum corresponds to a transparent state in the system. However, when the distance between the slabs is smaller than the decay length of evanescent waves, the absorption spectra has three peaks and two transparent states. In other words, one transparent state can be switched to two transparent states when the distance between the two layers is modified. This could be achieved by applying stress and strain fields. It is also found that transparent states can be switched on and off by applying an external control laser field.« less

Hiding Information Using different lighting Color images

NASA Astrophysics Data System (ADS)

Majead, Ahlam; Awad, Rash; Salman, Salema S.

2018-05-01

The host medium for the secret message is one of the important principles for the designers of steganography method. In this study, the best color image was studied to carrying any secret image.The steganography approach based Lifting Wavelet Transform (LWT) and Least Significant Bits (LSBs) substitution. The proposed method offers lossless and unnoticeable changes in the contrast carrier color image and imperceptible by human visual system (HVS), especially the host images which was captured in dark lighting conditions. The aim of the study was to study the process of masking the data in colored images with different light intensities. The effect of the masking process was examined on the images that are classified by a minimum distance and the amount of noise and distortion in the image. The histogram and statistical characteristics of the cover image the results showed the efficient use of images taken with different light intensities in hiding data using the least important bit substitution method. This method succeeded in concealing textual data without distorting the original image (low light) Lire developments due to the concealment process.The digital image segmentation technique was used to distinguish small areas with masking. The result is that smooth homogeneous areas are less affected as a result of hiding comparing with high light areas. It is possible to use dark color images to send any secret message between two persons for the purpose of secret communication with good security.

Image classification independent of orientation and scale

NASA Astrophysics Data System (ADS)

Arsenault, Henri H.; Parent, Sebastien; Moisan, Sylvain

1998-04-01

The recognition of targets independently of orientation has become fairly well developed in recent years for in-plane rotation. The out-of-plane rotation problem is much less advanced. When both out-of-plane rotations and changes of scale are present, the problem becomes very difficult. In this paper we describe our research on the combined out-of- plane rotation problem and the scale invariance problem. The rotations were limited to rotations about an axis perpendicular to the line of sight. The objects to be classified were three kinds of military vehicles. The inputs used were infrared imagery and photographs. We used a variation of a method proposed by Neiberg and Casasent, where a neural network is trained with a subset of the database and a minimum distances from lines in feature space are used for classification instead of nearest neighbors. Each line in the feature space corresponds to one class of objects, and points on one line correspond to different orientations of the same target. We found that the training samples needed to be closer for some orientations than for others, and that the most difficult orientations are where the target is head-on to the observer. By means of some additional training of the neural network, we were able to achieve 100% correct classification for 360 degree rotation and a range of scales over a factor of five.

Using Multispectral Analysis in GIS to Model the Potential for Urban Agriculture in Philadelphia

NASA Astrophysics Data System (ADS)

Dmochowski, J. E.; Cooper, W. P.

2010-12-01

In the context of growing concerns about the international food system’s dependence on fossil fuels, soil degradation, climate change, and other diverse issues, a number of initiatives have arisen to develop and implement sustainable agricultural practices. Many seeking to reform the food system look to urban agriculture as a means to create localized, sustainable agricultural production, while simultaneously providing a locus for community building, encouraging better nutrition, and promoting the rebirth of depressed urban areas. The actual impact of such system, however, is not well understood, and many critics of urban agriculture regard its implementation as impractical and unrealistic. This project uses multispectral imagery from United States Department of Agriculture’s National Agricultural Imagery Program with a one-meter resolution to quantify the potential for increasing urban agriculture in an effort to create a sustainable food system in Philadelphia. Color infrared images are classified with a minimum distance algorithm in ArcGIS to generate baseline data on vegetative cover in Philadelphia. These data, in addition to mapping on the ground, form the basis of a model of land suitable for conversion to agriculture in Philadelphia, which will help address questions related to potential yields, workforce, and energy requirements. This research will help city planners, entrepreneurs, community leaders, and citizens understand how urban agriculture can contribute to creating a sustainable food system in a major North American city.

On the partition dimension of comb product of path and complete graph

NASA Astrophysics Data System (ADS)

Darmaji, Alfarisi, Ridho

2017-08-01

For a vertex v of a connected graph G(V, E) with vertex set V(G), edge set E(G) and S ⊆ V(G). Given an ordered partition Π = {S1, S2, S3, …, Sk} of the vertex set V of G, the representation of a vertex v ∈ V with respect to Π is the vector r(v|Π) = (d(v, S1), d(v, S2), …, d(v, Sk)), where d(v, Sk) represents the distance between the vertex v and the set Sk and d(v, Sk) = min{d(v, x)|x ∈ Sk}. A partition Π of V(G) is a resolving partition if different vertices of G have distinct representations, i.e., for every pair of vertices u, v ∈ V(G), r(u|Π) ≠ r(v|Π). The minimum k of Π resolving partition is a partition dimension of G, denoted by pd(G). Finding the partition dimension of G is classified to be a NP-Hard problem. In this paper, we will show that the partition dimension of comb product of path and complete graph. The results show that comb product of complete grapph Km and path Pn namely p d (Km⊳Pn)=m where m ≥ 3 and n ≥ 2 and p d (Pn⊳Km)=m where m ≥ 3, n ≥ 2 and m ≥ n.

Mathematical values in the processing of Chinese numeral classifiers and measure words.

PubMed

Her, One-Soon; Chen, Ying-Chun; Yen, Nai-Shing

2017-01-01

A numeral classifier is required between a numeral and a noun in Chinese, which comes in two varieties, sortal classifer (C) and measural classifier (M), also known as 'classifier' and 'measure word', respectively. Cs categorize objects based on semantic attributes and Cs and Ms both denote quantity in terms of mathematical values. The aim of this study was to conduct a psycholinguistic experiment to examine whether participants process C/Ms based on their mathematical values with a semantic distance comparison task, where participants judged which of the two C/M phrases was semantically closer to the target C/M. Results showed that participants performed more accurately and faster for C/Ms with fixed values than the ones with variable values. These results demonstrated that mathematical values do play an important role in the processing of C/Ms. This study may thus shed light on the influence of the linguistic system of C/Ms on magnitude cognition.

Feature and Score Fusion Based Multiple Classifier Selection for Iris Recognition

PubMed Central

Islam, Md. Rabiul

2014-01-01

The aim of this work is to propose a new feature and score fusion based iris recognition approach where voting method on Multiple Classifier Selection technique has been applied. Four Discrete Hidden Markov Model classifiers output, that is, left iris based unimodal system, right iris based unimodal system, left-right iris feature fusion based multimodal system, and left-right iris likelihood ratio score fusion based multimodal system, is combined using voting method to achieve the final recognition result. CASIA-IrisV4 database has been used to measure the performance of the proposed system with various dimensions. Experimental results show the versatility of the proposed system of four different classifiers with various dimensions. Finally, recognition accuracy of the proposed system has been compared with existing N hamming distance score fusion approach proposed by Ma et al., log-likelihood ratio score fusion approach proposed by Schmid et al., and single level feature fusion approach proposed by Hollingsworth et al. PMID:25114676

Stackable differential mobility analyzer for aerosol measurement

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

Cheng, Meng-Dawn; Chen, Da-Ren

2007-05-08

A multi-stage differential mobility analyzer (MDMA) for aerosol measurements includes a first electrode or grid including at least one inlet or injection slit for receiving an aerosol including charged particles for analysis. A second electrode or grid is spaced apart from the first electrode. The second electrode has at least one sampling outlet disposed at a plurality different distances along its length. A volume between the first and the second electrode or grid between the inlet or injection slit and a distal one of the plurality of sampling outlets forms a classifying region, the first and second electrodes for chargingmore » to suitable potentials to create an electric field within the classifying region. At least one inlet or injection slit in the second electrode receives a sheath gas flow into an upstream end of the classifying region, wherein each sampling outlet functions as an independent DMA stage and classifies different size ranges of charged particles based on electric mobility simultaneously.« less

Feature and score fusion based multiple classifier selection for iris recognition.

PubMed

Islam, Md Rabiul

2014-01-01

The aim of this work is to propose a new feature and score fusion based iris recognition approach where voting method on Multiple Classifier Selection technique has been applied. Four Discrete Hidden Markov Model classifiers output, that is, left iris based unimodal system, right iris based unimodal system, left-right iris feature fusion based multimodal system, and left-right iris likelihood ratio score fusion based multimodal system, is combined using voting method to achieve the final recognition result. CASIA-IrisV4 database has been used to measure the performance of the proposed system with various dimensions. Experimental results show the versatility of the proposed system of four different classifiers with various dimensions. Finally, recognition accuracy of the proposed system has been compared with existing N hamming distance score fusion approach proposed by Ma et al., log-likelihood ratio score fusion approach proposed by Schmid et al., and single level feature fusion approach proposed by Hollingsworth et al.

Automated diagnosis of dry eye using infrared thermography images

NASA Astrophysics Data System (ADS)

Acharya, U. Rajendra; Tan, Jen Hong; Koh, Joel E. W.; Sudarshan, Vidya K.; Yeo, Sharon; Too, Cheah Loon; Chua, Chua Kuang; Ng, E. Y. K.; Tong, Louis

2015-07-01

Dry Eye (DE) is a condition of either decreased tear production or increased tear film evaporation. Prolonged DE damages the cornea causing the corneal scarring, thinning and perforation. There is no single uniform diagnosis test available to date; combinations of diagnostic tests are to be performed to diagnose DE. The current diagnostic methods available are subjective, uncomfortable and invasive. Hence in this paper, we have developed an efficient, fast and non-invasive technique for the automated identification of normal and DE classes using infrared thermography images. The features are extracted from nonlinear method called Higher Order Spectra (HOS). Features are ranked using t-test ranking strategy. These ranked features are fed to various classifiers namely, K-Nearest Neighbor (KNN), Nave Bayesian Classifier (NBC), Decision Tree (DT), Probabilistic Neural Network (PNN), and Support Vector Machine (SVM) to select the best classifier using minimum number of features. Our proposed system is able to identify the DE and normal classes automatically with classification accuracy of 99.8%, sensitivity of 99.8%, and specificity if 99.8% for left eye using PNN and KNN classifiers. And we have reported classification accuracy of 99.8%, sensitivity of 99.9%, and specificity if 99.4% for right eye using SVM classifier with polynomial order 2 kernel.

Multi-image acquisition-based distance sensor using agile laser spot beam.

PubMed

Riza, Nabeel A; Amin, M Junaid

2014-09-01

We present a novel laser-based distance measurement technique that uses multiple-image-based spatial processing to enable distance measurements. Compared with the first-generation distance sensor using spatial processing, the modified sensor is no longer hindered by the classic Rayleigh axial resolution limit for the propagating laser beam at its minimum beam waist location. The proposed high-resolution distance sensor design uses an electronically controlled variable focus lens (ECVFL) in combination with an optical imaging device, such as a charged-coupled device (CCD), to produce and capture different laser spot size images on a target with these beam spot sizes different from the minimal spot size possible at this target distance. By exploiting the unique relationship of the target located spot sizes with the varying ECVFL focal length for each target distance, the proposed distance sensor can compute the target distance with a distance measurement resolution better than the axial resolution via the Rayleigh resolution criterion. Using a 30 mW 633 nm He-Ne laser coupled with an electromagnetically actuated liquid ECVFL, along with a 20 cm focal length bias lens, and using five spot images captured per target position by a CCD-based Nikon camera, a proof-of-concept proposed distance sensor is successfully implemented in the laboratory over target ranges from 10 to 100 cm with a demonstrated sub-cm axial resolution, which is better than the axial Rayleigh resolution limit at these target distances. Applications for the proposed potentially cost-effective distance sensor are diverse and include industrial inspection and measurement and 3D object shape mapping and imaging.

75 FR 71148 - Solicitation for a Cooperative Agreement-Production of Seven Live Satellite/Internet Broadcasts

Federal Register 2010, 2011, 2012, 2013, 2014

2010-11-22

... defined as training/ education transpiring between trainers and facilitators at one location and... NIC's distance learning administrator (DLA) on program design, program coordination, design and field... activities that support each broadcast. A minimum of one face-to-face planning session will be held for each...

76 FR 295 - Proposed Amendments to the Water Quality Regulations, Water Code and Comprehensive Plan To...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-01-04

... endangered (T&E) species. Minimum setbacks from water bodies, wetlands, surface water supply intakes and water supply reservoirs at distances specified in the regulations, and from occupied homes, public buildings, public roads, public water supply wells, and domestic water supply wells as provided by...

24 CFR 3280.611 - Vents and venting.

Code of Federal Regulations, 2014 CFR

2014-04-01

... drain piping for each toilet shall be vented by a 11/2 inch minimum diameter vent or rectangular vent of..., connected to the toilet drain by one of the following methods: (i) A 11/2 inch diameter (min.) individual vent pipe or equivalent directly connected to the toilet drain within the distance allowed in § 3280...

75 FR 70854 - Harmonization of Various Airworthiness Standards for Transport Category Airplanes-Flight Rules

Federal Register 2010, 2011, 2012, 2013, 2014

2010-11-19

..., deploy speed brakes) to stop the airplane within the accelerate stop distance. It also means the minimum... flight diving speed. List of Subjects in 14 CFR Part 25 Aircraft, Aviation safety, Reporting and... transport category airplanes. This action would harmonize the requirements for takeoff speeds, static...

40 CFR 86.436-78 - Additional service accumulation.

Code of Federal Regulations, 2010 CFR

2010-07-01

... minimum test distance and at the useful life, and, (3) The results of the half life emission tests, when... Regulations for 1978 and Later New Motorcycles, General Provisions § 86.436-78 Additional service accumulation. (a) Additional service up to the useful life will be accumulated under the same conditions as the...

40 CFR 86.436-78 - Additional service accumulation.

Code of Federal Regulations, 2011 CFR

2011-07-01

... minimum test distance and at the useful life, and, (3) The results of the half life emission tests, when... Regulations for 1978 and Later New Motorcycles, General Provisions § 86.436-78 Additional service accumulation. (a) Additional service up to the useful life will be accumulated under the same conditions as the...

29 CFR 1910.110 - Storage and handling of liquefied petroleum gases.

Code of Federal Regulations, 2011 CFR

2011-07-01

.... (i) Containers used with systems embodied in paragraphs (d), (e), (g), and (h) of this section... unit of weight for containers with a water capacity of 300 pounds or less. (h) With marking indicating... Table H-23. Table H-23 Water capacity per container Minimum distances Containers Underground Aboveground...

29 CFR 1910.110 - Storage and handling of liquefied petroleum gases.

Code of Federal Regulations, 2010 CFR

2010-07-01

.... (i) Containers used with systems embodied in paragraphs (d), (e), (g), and (h) of this section... unit of weight for containers with a water capacity of 300 pounds or less. (h) With marking indicating... Table H-23. Table H-23 Water capacity per container Minimum distances Containers Underground Aboveground...

46 CFR 45.69 - Correction for bow height.

Code of Federal Regulations, 2014 CFR

2014-10-01

... consideration by the Commandant. (e) The bow height is defined as the vertical distance at the forward... 46 Shipping 2 2014-10-01 2014-10-01 false Correction for bow height. 45.69 Section 45.69 Shipping... § 45.69 Correction for bow height. (a) The minimum summer freeboard of all manned vessels must be...

14 CFR 77.9 - Construction or alteration requiring notice.

Code of Federal Regulations, 2013 CFR

2013-01-01

... section. (c) Any highway, railroad, or other traverse way for mobile objects, of a height which, if... Interstate Highways where overcrossings are designed for a minimum of 17 feet vertical distance, 15 feet for any other public roadway, 10 feet or the height of the highest mobile object that would normally...

46 CFR 45.69 - Correction for bow height.

Code of Federal Regulations, 2012 CFR

2012-10-01

... consideration by the Commandant. (e) The bow height is defined as the vertical distance at the forward... 46 Shipping 2 2012-10-01 2012-10-01 false Correction for bow height. 45.69 Section 45.69 Shipping... § 45.69 Correction for bow height. (a) The minimum summer freeboard of all manned vessels must be...

14 CFR 77.9 - Construction or alteration requiring notice.

Code of Federal Regulations, 2014 CFR

2014-01-01

... section. (c) Any highway, railroad, or other traverse way for mobile objects, of a height which, if... Interstate Highways where overcrossings are designed for a minimum of 17 feet vertical distance, 15 feet for any other public roadway, 10 feet or the height of the highest mobile object that would normally...

14 CFR 77.9 - Construction or alteration requiring notice.

Code of Federal Regulations, 2012 CFR

2012-01-01

... section. (c) Any highway, railroad, or other traverse way for mobile objects, of a height which, if... Interstate Highways where overcrossings are designed for a minimum of 17 feet vertical distance, 15 feet for any other public roadway, 10 feet or the height of the highest mobile object that would normally...

46 CFR 45.69 - Correction for bow height.

Code of Federal Regulations, 2013 CFR

2013-10-01

... consideration by the Commandant. (e) The bow height is defined as the vertical distance at the forward... 46 Shipping 2 2013-10-01 2013-10-01 false Correction for bow height. 45.69 Section 45.69 Shipping... § 45.69 Correction for bow height. (a) The minimum summer freeboard of all manned vessels must be...

14 CFR 135.203 - VFR: Minimum altitudes.

Code of Federal Regulations, 2011 CFR

2011-01-01

... REQUIREMENTS: COMMUTER AND ON DEMAND OPERATIONS AND RULES GOVERNING PERSONS ON BOARD SUCH AIRCRAFT VFR/IFR... above the surface or less than 500 feet horizontally from any obstacle; or (2) At night, at an altitude less than 1,000 feet above the highest obstacle within a horizontal distance of 5 miles from the course...

Mapping Health Data: Improved Privacy Protection With Donut Method Geomasking

PubMed Central

Hampton, Kristen H.; Fitch, Molly K.; Allshouse, William B.; Doherty, Irene A.; Gesink, Dionne C.; Leone, Peter A.; Serre, Marc L.; Miller, William C.

2010-01-01

A major challenge in mapping health data is protecting patient privacy while maintaining the spatial resolution necessary for spatial surveillance and outbreak identification. A new adaptive geomasking technique, referred to as the donut method, extends current methods of random displacement by ensuring a user-defined minimum level of geoprivacy. In donut method geomasking, each geocoded address is relocated in a random direction by at least a minimum distance, but less than a maximum distance. The authors compared the donut method with current methods of random perturbation and aggregation regarding measures of privacy protection and cluster detection performance by masking multiple disease field simulations under a range of parameters. Both the donut method and random perturbation performed better than aggregation in cluster detection measures. The performance of the donut method in geoprivacy measures was at least 42.7% higher and in cluster detection measures was less than 4.8% lower than that of random perturbation. Results show that the donut method provides a consistently higher level of privacy protection with a minimal decrease in cluster detection performance, especially in areas where the risk to individual geoprivacy is greatest. PMID:20817785

Mapping health data: improved privacy protection with donut method geomasking.

PubMed

Hampton, Kristen H; Fitch, Molly K; Allshouse, William B; Doherty, Irene A; Gesink, Dionne C; Leone, Peter A; Serre, Marc L; Miller, William C

2010-11-01

A major challenge in mapping health data is protecting patient privacy while maintaining the spatial resolution necessary for spatial surveillance and outbreak identification. A new adaptive geomasking technique, referred to as the donut method, extends current methods of random displacement by ensuring a user-defined minimum level of geoprivacy. In donut method geomasking, each geocoded address is relocated in a random direction by at least a minimum distance, but less than a maximum distance. The authors compared the donut method with current methods of random perturbation and aggregation regarding measures of privacy protection and cluster detection performance by masking multiple disease field simulations under a range of parameters. Both the donut method and random perturbation performed better than aggregation in cluster detection measures. The performance of the donut method in geoprivacy measures was at least 42.7% higher and in cluster detection measures was less than 4.8% lower than that of random perturbation. Results show that the donut method provides a consistently higher level of privacy protection with a minimal decrease in cluster detection performance, especially in areas where the risk to individual geoprivacy is greatest.

The Stability of Main Characteristics of Possible Impacts of Asteroids with the Earth

NASA Astrophysics Data System (ADS)

Borukha, M.; Sokolov, L.; Petrov, N.; Vasiliev, A.

2017-12-01

The stability of the characteristics of asteroids trajectories leading to collisions with the Earth under small changes of the nominal orbit and the motion model (disturbing forces, integrator, etc.) is discussed. Examples of small changes in the relative positions and sizes of the keyholes leading to collisions, moments of collisions and minimum geocentric distances are demonstrated. It is shown that various ways of specifying the relative positions and sizes of the keyholes are possible, in particular, using differences in the osculating elements of the semi-major axis, as well as the differences of the minimum geocentric distances in the previous approach. Comparisons are made using examples of models of the Solar system DE403, DE405, DE430 for various nominal orbits of asteroids Apophis, 2015 RN35 and others. The ranges and causes for the observed stability are discussed. The stability of the structure of possible collisions is associated with the Lyapunov instability of the motion of asteroids during approach. This work is supported by RFBR grant 15-02-04340 and a grant from St. Petersburg State University 6.37.341.2015.

Model-based multiple patterning layout decomposition

NASA Astrophysics Data System (ADS)

Guo, Daifeng; Tian, Haitong; Du, Yuelin; Wong, Martin D. F.

2015-10-01

As one of the most promising next generation lithography technologies, multiple patterning lithography (MPL) plays an important role in the attempts to keep in pace with 10 nm technology node and beyond. With feature size keeps shrinking, it has become impossible to print dense layouts within one single exposure. As a result, MPL such as double patterning lithography (DPL) and triple patterning lithography (TPL) has been widely adopted. There is a large volume of literature on DPL/TPL layout decomposition, and the current approach is to formulate the problem as a classical graph-coloring problem: Layout features (polygons) are represented by vertices in a graph G and there is an edge between two vertices if and only if the distance between the two corresponding features are less than a minimum distance threshold value dmin. The problem is to color the vertices of G using k colors (k = 2 for DPL, k = 3 for TPL) such that no two vertices connected by an edge are given the same color. This is a rule-based approach, which impose a geometric distance as a minimum constraint to simply decompose polygons within the distance into different masks. It is not desired in practice because this criteria cannot completely capture the behavior of the optics. For example, it lacks of sufficient information such as the optical source characteristics and the effects between the polygons outside the minimum distance. To remedy the deficiency, a model-based layout decomposition approach to make the decomposition criteria base on simulation results was first introduced at SPIE 2013.1 However, the algorithm1 is based on simplified assumption on the optical simulation model and therefore its usage on real layouts is limited. Recently AMSL2 also proposed a model-based approach to layout decomposition by iteratively simulating the layout, which requires excessive computational resource and may lead to sub-optimal solutions. The approach2 also potentially generates too many stiches. In this paper, we propose a model-based MPL layout decomposition method using a pre-simulated library of frequent layout patterns. Instead of using the graph G in the standard graph-coloring formulation, we build an expanded graph H where each vertex represents a group of adjacent features together with a coloring solution. By utilizing the library and running sophisticated graph algorithms on H, our approach can obtain optimal decomposition results efficiently. Our model-based solution can achieve a practical mask design which significantly improves the lithography quality on the wafer compared to the rule based decomposition.

Optimal tyre usage for a Formula One car

NASA Astrophysics Data System (ADS)

Tremlett, A. J.; Limebeer, D. J. N.

2016-10-01

Variations in track temperature, surface conditions and layout have led tyre manufacturers to produce a range of rubber compounds for race events. Each compound has unique friction and durability characteristics. Efficient tyre management over a full race distance is a crucial component of a competitive race strategy. A minimum lap time optimal control calculation and a thermodynamic tyre wear model are used to establish optimal tyre warming and tyre usage strategies. Lap time sensitivities demonstrate that relatively small changes in control strategy can lead to significant reductions in the associated wear metrics. The illustrated methodology shows how vehicle setup parameters can be optimised for minimum tyre usage.

Root and Canal Morphology of Mandibular Molars in a Selected Iranian Population Using Cone-Beam Computed Tomography

PubMed Central

Madani, Zahra Sadat; Mehraban, Nika; Moudi, Ehsan; Bijani, Ali

2017-01-01

Introduction: The aim of this study was to evaluate the root canal morphology of mandibular first and second molars using cone-beam computed tomography (CBCT) in northern Iranian population and also to indicate the thinnest area around root canals. Methods and Materials: We evaluated CBCT images of 154 first molars and 147 second molars. By evaluating three axial, sagittal and coronal planes of each tooth we determined the number of root canals, prevalence of C-shaped Melton types, and prevalence of Vertucci configuration and inter orifice distance. Also the minimum wall thickness of root canals was determined by measuring buccal, lingual, distal and mesial wall thicknesses of each canal in levels with 2 mm intervals from apex to orifice. Results: Amongst 154 first mandibular molars, 149 (96.7%) had two roots, 3 (1.9%) had three roots and 2 (1.2%) had C-shaped root configuration. Of 147 second mandibular molars, 120 (81.6%) had two roots, 1 (0.6%) had three roots and 26 (17.6%) had C-shaped roots. There was no significant difference in the prevalence of Vertucci’s type between two genders. The most common configuration in mesial roots of first and second molars were type IV (57%-42.9%) and type II (31.5%-28%). Mesial and distal walls had the most frequency as the thinnest wall in all levels of root canals with mostly less than 1 mm thickness. In second molars the DB-DL inter orifice distance and in first molars the MB-ML distance were the minimum. MB-D in first molars had the maximum distance while ML-DL, MB-DB and ML-D had the same and maximum distance in second molars. Conclusion: Vertucci’s type IV and type I were the most prevalent configurations in mesial and distal roots of first and second mandibular molars and the thickness of thinnest area around the canals should be considered during endodontic treatments. PMID:28512476

Foot strike patterns of recreational and sub-elite runners in a long-distance road race.

PubMed

Larson, Peter; Higgins, Erin; Kaminski, Justin; Decker, Tamara; Preble, Janine; Lyons, Daniela; McIntyre, Kevin; Normile, Adam

2011-12-01

Although the biomechanical properties of the various types of running foot strike (rearfoot, midfoot, and forefoot) have been studied extensively in the laboratory, only a few studies have attempted to quantify the frequency of running foot strike variants among runners in competitive road races. We classified the left and right foot strike patterns of 936 distance runners, most of whom would be considered of recreational or sub-elite ability, at the 10 km point of a half-marathon/marathon road race. We classified 88.9% of runners at the 10 km point as rearfoot strikers, 3.4% as midfoot strikers, 1.8% as forefoot strikers, and 5.9% of runners exhibited discrete foot strike asymmetry. Rearfoot striking was more common among our sample of mostly recreational distance runners than has been previously reported for samples of faster runners. We also compared foot strike patterns of 286 individual marathon runners between the 10 km and 32 km race locations and observed increased frequency of rearfoot striking at 32 km. A large percentage of runners switched from midfoot and forefoot foot strikes at 10 km to rearfoot strikes at 32 km. The frequency of discrete foot strike asymmetry declined from the 10 km to the 32 km location. Among marathon runners, we found no significant relationship between foot strike patterns and race times.

SU-E-T-489: Quantum versus Classical Trajectory Monte Carlo Simulations of Low Energy Electron Transport.

PubMed

Thomson, R; Kawrakow, I

2012-06-01

Widely-used classical trajectory Monte Carlo simulations of low energy electron transport neglect the quantum nature of electrons; however, at sub-1 keV energies quantum effects have the potential to become significant. This work compares quantum and classical simulations within a simplified model of electron transport in water. Electron transport is modeled in water droplets using quantum mechanical (QM) and classical trajectory Monte Carlo (MC) methods. Water droplets are modeled as collections of point scatterers representing water molecules from which electrons may be isotropically scattered. The role of inelastic scattering is investigated by introducing absorption. QM calculations involve numerically solving a system of coupled equations for the electron wavefield incident on each scatterer. A minimum distance between scatterers is introduced to approximate structured water. The average QM water droplet incoherent cross section is compared with the MC cross section; a relative error (RE) on the MC results is computed. RE varies with electron energy, average and minimum distances between scatterers, and scattering amplitude. The mean free path is generally the relevant length scale for estimating RE. The introduction of a minimum distance between scatterers increases RE substantially (factors of 5 to 10), suggesting that the structure of water must be modeled for accurate simulations. Inelastic scattering does not improve agreement between QM and MC simulations: for the same magnitude of elastic scattering, the introduction of inelastic scattering increases RE. Droplet cross sections are sensitive to droplet size and shape; considerable variations in RE are observed with changing droplet size and shape. At sub-1 keV energies, quantum effects may become non-negligible for electron transport in condensed media. Electron transport is strongly affected by the structure of the medium. Inelastic scatter does not improve agreement between QM and MC simulations of low energy electron transport in condensed media. © 2012 American Association of Physicists in Medicine.

Motion data classification on the basis of dynamic time warping with a cloud point distance measure

NASA Astrophysics Data System (ADS)

Switonski, Adam; Josinski, Henryk; Zghidi, Hafedh; Wojciechowski, Konrad

2016-06-01

The paper deals with the problem of classification of model free motion data. The nearest neighbors classifier which is based on comparison performed by Dynamic Time Warping transform with cloud point distance measure is proposed. The classification utilizes both specific gait features reflected by a movements of subsequent skeleton joints and anthropometric data. To validate proposed approach human gait identification challenge problem is taken into consideration. The motion capture database containing data of 30 different humans collected in Human Motion Laboratory of Polish-Japanese Academy of Information Technology is used. The achieved results are satisfactory, the obtained accuracy of human recognition exceeds 90%. What is more, the applied cloud point distance measure does not depend on calibration process of motion capture system which results in reliable validation.

Building-up of a DNA barcode library for true bugs (insecta: hemiptera: heteroptera) of Germany reveals taxonomic uncertainties and surprises.

PubMed

Raupach, Michael J; Hendrich, Lars; Küchler, Stefan M; Deister, Fabian; Morinière, Jérome; Gossner, Martin M

2014-01-01

During the last few years, DNA barcoding has become an efficient method for the identification of species. In the case of insects, most published DNA barcoding studies focus on species of the Ephemeroptera, Trichoptera, Hymenoptera and especially Lepidoptera. In this study we test the efficiency of DNA barcoding for true bugs (Hemiptera: Heteroptera), an ecological and economical highly important as well as morphologically diverse insect taxon. As part of our study we analyzed DNA barcodes for 1742 specimens of 457 species, comprising 39 families of the Heteroptera. We found low nucleotide distances with a minimum pairwise K2P distance <2.2% within 21 species pairs (39 species). For ten of these species pairs (18 species), minimum pairwise distances were zero. In contrast to this, deep intraspecific sequence divergences with maximum pairwise distances >2.2% were detected for 16 traditionally recognized and valid species. With a successful identification rate of 91.5% (418 species) our study emphasizes the use of DNA barcodes for the identification of true bugs and represents an important step in building-up a comprehensive barcode library for true bugs in Germany and Central Europe as well. Our study also highlights the urgent necessity of taxonomic revisions for various taxa of the Heteroptera, with a special focus on various species of the Miridae. In this context we found evidence for on-going hybridization events within various taxonomically challenging genera (e.g. Nabis Latreille, 1802 (Nabidae), Lygus Hahn, 1833 (Miridae), Phytocoris Fallén, 1814 (Miridae)) as well as the putative existence of cryptic species (e.g. Aneurus avenius (Duffour, 1833) (Aradidae) or Orius niger (Wolff, 1811) (Anthocoridae)).

Building-Up of a DNA Barcode Library for True Bugs (Insecta: Hemiptera: Heteroptera) of Germany Reveals Taxonomic Uncertainties and Surprises

PubMed Central

Raupach, Michael J.; Hendrich, Lars; Küchler, Stefan M.; Deister, Fabian; Morinière, Jérome; Gossner, Martin M.

2014-01-01

During the last few years, DNA barcoding has become an efficient method for the identification of species. In the case of insects, most published DNA barcoding studies focus on species of the Ephemeroptera, Trichoptera, Hymenoptera and especially Lepidoptera. In this study we test the efficiency of DNA barcoding for true bugs (Hemiptera: Heteroptera), an ecological and economical highly important as well as morphologically diverse insect taxon. As part of our study we analyzed DNA barcodes for 1742 specimens of 457 species, comprising 39 families of the Heteroptera. We found low nucleotide distances with a minimum pairwise K2P distance <2.2% within 21 species pairs (39 species). For ten of these species pairs (18 species), minimum pairwise distances were zero. In contrast to this, deep intraspecific sequence divergences with maximum pairwise distances >2.2% were detected for 16 traditionally recognized and valid species. With a successful identification rate of 91.5% (418 species) our study emphasizes the use of DNA barcodes for the identification of true bugs and represents an important step in building-up a comprehensive barcode library for true bugs in Germany and Central Europe as well. Our study also highlights the urgent necessity of taxonomic revisions for various taxa of the Heteroptera, with a special focus on various species of the Miridae. In this context we found evidence for on-going hybridization events within various taxonomically challenging genera (e.g. Nabis Latreille, 1802 (Nabidae), Lygus Hahn, 1833 (Miridae), Phytocoris Fallén, 1814 (Miridae)) as well as the putative existence of cryptic species (e.g. Aneurus avenius (Duffour, 1833) (Aradidae) or Orius niger (Wolff, 1811) (Anthocoridae)). PMID:25203616

Orientation-dependent potential of mean force for protein folding

NASA Astrophysics Data System (ADS)

Mukherjee, Arnab; Bhimalapuram, Prabhakar; Bagchi, Biman

2005-07-01

We present a solvent-implicit minimalistic model potential among the amino acid residues of proteins, obtained by using the known native structures [deposited in the Protein Data Bank (PDB)]. In this model, the amino acid side chains are represented by a single ellipsoidal site, defined by the group of atoms about the center of mass of the side chain. These ellipsoidal sites interact with other sites through an orientation-dependent interaction potential which we construct in the following fashion. First, the site-site potential of mean force (PMF) between heavy atoms is calculated [following F. Melo and E. Feytsman, J. Mol. Biol. 267, 207 (1997)] from statistics of their distance separation obtained from crystal structures. These site-site potentials are then used to calculate the distance and the orientation-dependent potential between side chains of all the amino acid residues (AAR). The distance and orientation dependencies show several interesting results. For example, we find that the PMF between two hydrophobic AARs, such as phenylalanine, is strongly attractive at short distances (after the obvious repulsive region at very short separation) and is characterized by a deep minimum, for specific orientations. For the interaction between two hydrophilic AARs, such a deep minimum is absent and in addition, the potential interestingly reveals the combined effect of polar (charge) and hydrophobic interactions among some of these AARs. The effectiveness of our potential has been tested by calculating the Z-scores for a large set of proteins. The calculated Z-scores show high negative values for most of them, signifying the success of the potential to identify the native structure from among a large number of its decoy states.

Influence of Gap Distance on Vacuum Arc Characteristics of Cup Type AMF Electrode in Vacuum Interrupters

NASA Astrophysics Data System (ADS)

Cheng, Shaoyong; Xiu, Shixin; Wang, Jimei; Shen, Zhengchao

2006-11-01

The greenhouse effect of SF6 is a great concern today. The development of high voltage vacuum circuit breakers becomes more important. The vacuum circuit breaker has minimum pollution to the environment. The vacuum interrupter is the key part of a vacuum circuit breaker. The interrupting characteristics in vacuum and arc-controlling technique are the main problems to be solved for a longer gap distance in developing high voltage vacuum interrupters. To understand the vacuum arc characteristics and provide effective technique to control vacuum arc in a long gap distance, the arc mode transition of a cup-type axial magnetic field electrode is observed by a high-speed charge coupled device (CCD) video camera under different gap distances while the arc voltage and arc current are recorded. The controlling ability of the axial magnetic field on vacuum arc obviously decreases when the gap distance is longer than 40 mm. The noise components and mean value of the arc voltage significantly increase. The effective method for controlling the vacuum arc characteristics is provided by long gap distances based on the test results. The test results can be used as a reference to develop high voltage and large capacity vacuum interrupters.

A machine learned classifier for RR Lyrae in the VVV survey

NASA Astrophysics Data System (ADS)

Elorrieta, Felipe; Eyheramendy, Susana; Jordán, Andrés; Dékány, István; Catelan, Márcio; Angeloni, Rodolfo; Alonso-García, Javier; Contreras-Ramos, Rodrigo; Gran, Felipe; Hajdu, Gergely; Espinoza, Néstor; Saito, Roberto K.; Minniti, Dante

2016-11-01

Variable stars of RR Lyrae type are a prime tool with which to obtain distances to old stellar populations in the Milky Way. One of the main aims of the Vista Variables in the Via Lactea (VVV) near-infrared survey is to use them to map the structure of the Galactic Bulge. Owing to the large number of expected sources, this requires an automated mechanism for selecting RR Lyrae, and particularly those of the more easily recognized type ab (I.e., fundamental-mode pulsators), from the 106-107 variables expected in the VVV survey area. In this work we describe a supervised machine-learned classifier constructed for assigning a score to a Ks-band VVV light curve that indicates its likelihood of being ab-type RR Lyrae. We describe the key steps in the construction of the classifier, which were the choice of features, training set, selection of aperture, and family of classifiers. We find that the AdaBoost family of classifiers give consistently the best performance for our problem, and obtain a classifier based on the AdaBoost algorithm that achieves a harmonic mean between false positives and false negatives of ≈7% for typical VVV light-curve sets. This performance is estimated using cross-validation and through the comparison to two independent datasets that were classified by human experts.

Volcano spacing and plate rigidity

USGS Publications Warehouse

ten Brink, Uri S.

1991-01-01

In-plane stresses, which accompany the flexural deformation of the lithosphere under the load of adjacent volcanoes, may govern the spacing of volcanoes in hotspot provinces. Specifically, compressive stresses in the vicinity of a volcano prevent new upwelling in this area, forcing a new volcano to develop at a minimum distance that is equal to the distance in which the radial stresses change from compressional to tensile (the inflection point). If a volcano is modeled as a point load on a thin elastic plate, then the distance to the inflection point is proportional to the thickness of the plate to the power of 3/4. Compilation of volcano spacing in seven volcanic groups in East Africa and seven volcanic groups of oceanic hotspots shows significant correlation with the elastic thickness of the plate and matches the calculated distance to the inflection point. In contrast, volcano spacing in island arcs and over subduction zones is fairly uniform and is much larger than predicted by the distance to the inflection point, reflecting differences in the geometry of the source and the upwelling areas.

New method for distance-based close following safety indicator.

PubMed

Sharizli, A A; Rahizar, R; Karim, M R; Saifizul, A A

2015-01-01

The increase in the number of fatalities caused by road accidents involving heavy vehicles every year has raised the level of concern and awareness on road safety in developing countries like Malaysia. Changes in the vehicle dynamic characteristics such as gross vehicle weight, travel speed, and vehicle classification will affect a heavy vehicle's braking performance and its ability to stop safely in emergency situations. As such, the aim of this study is to establish a more realistic new distance-based safety indicator called the minimum safe distance gap (MSDG), which incorporates vehicle classification (VC), speed, and gross vehicle weight (GVW). Commercial multibody dynamics simulation software was used to generate braking distance data for various heavy vehicle classes under various loads and speeds. By applying nonlinear regression analysis to the simulation results, a mathematical expression of MSDG has been established. The results show that MSDG is dynamically changed according to GVW, VC, and speed. It is envisaged that this new distance-based safety indicator would provide a more realistic depiction of the real traffic situation for safety analysis.

Viterbi equalization for long-distance, high-speed underwater laser communication

NASA Astrophysics Data System (ADS)

Hu, Siqi; Mi, Le; Zhou, Tianhua; Chen, Weibiao

2017-07-01

In long-distance, high-speed underwater laser communication, because of the strong absorption and scattering processes, the laser pulse is stretched with the increase in communication distance and the decrease in water clarity. The maximum communication bandwidth is limited by laser-pulse stretching. Improving the communication rate increases the intersymbol interference (ISI). To reduce the effect of ISI, the Viterbi equalization (VE) algorithm is used to estimate the maximum-likelihood receiving sequence. The Monte Carlo method is used to simulate the stretching of the received laser pulse and the maximum communication rate at a wavelength of 532 nm in Jerlov IB and Jerlov II water channels with communication distances of 80, 100, and 130 m, respectively. The high-data rate communication performance for the VE and hard-decision algorithms is compared. The simulation results show that the VE algorithm can be used to reduce the ISI by selecting the minimum error path. The trade-off between the high-data rate communication performance and minor bit-error rate performance loss makes VE a promising option for applications in long-distance, high-speed underwater laser communication systems.

A binary linear programming formulation of the graph edit distance.

PubMed

Justice, Derek; Hero, Alfred

2006-08-01

A binary linear programming formulation of the graph edit distance for unweighted, undirected graphs with vertex attributes is derived and applied to a graph recognition problem. A general formulation for editing graphs is used to derive a graph edit distance that is proven to be a metric, provided the cost function for individual edit operations is a metric. Then, a binary linear program is developed for computing this graph edit distance, and polynomial time methods for determining upper and lower bounds on the solution of the binary program are derived by applying solution methods for standard linear programming and the assignment problem. A recognition problem of comparing a sample input graph to a database of known prototype graphs in the context of a chemical information system is presented as an application of the new method. The costs associated with various edit operations are chosen by using a minimum normalized variance criterion applied to pairwise distances between nearest neighbors in the database of prototypes. The new metric is shown to perform quite well in comparison to existing metrics when applied to a database of chemical graphs.

Solar wind and coronal structure near sunspot minimum - Pioneer and SMM observations from 1985-1987

NASA Technical Reports Server (NTRS)

Mihalov, J. D.; Barnes, A.; Hundhausen, A. J.; Smith, E. J.

1990-01-01

Changes in solar wind speed and magnetic polarity observed at the Pioneer spacecraft are discussed here in terms of the changing magnetic geometry implied by SMM coronagraph observations over the period 1985-1987. The pattern of recurrent solar wind streams, the long-term average speed, and the sector polarity of the interplanetary magnetic field all changed in a manner suggesting both a temporal variation, and a changing dependence on heliographic latitude. Coronal observations during this epoch show a systematic variation in coronal structure and the magnetic structure imposed on the expanding solar wind. These observations suggest interpretation of the solar wind speed variations in terms of the familiar model where the speed increases with distance from a nearly flat interplanetary current sheet, and where this current sheet becomes aligned with the solar equatorial plane as sunspot minimum approaches, but deviates rapidly from that orientation after minimum.

Mahalanobis Distance-Based Classifiers are Able to Recognize EEG Patterns by Using Few EEG Electrodes

DTIC Science & Technology

2001-10-25

Mouriño 3 , Angela Cattini 4 , Serenella Salinari 4 , Maria Grazia Marciani 2,5 and Febo Cincotti 5 1 Dip. Fisiologia umana e Farmacologia...Performing Organization Name(s) and Address(es) Dip. Fisiologia umana e Farmacologia, Università "La Sapienza", Rome, ITALY Performing Organization

Towards a Risk-Based Typology for Transnational Education

ERIC Educational Resources Information Center

Healey, Nigel Martin

2015-01-01

Transnational education (TNE) has been a growth area for UK universities over the last decade. The standard typology classifies TNE by the nature of the activity (i.e., distance learning, international branch campus, franchise, and validation). By analysing a large number of TNE partnerships around the world, this study reveals that the current…

Classifying E-Trainer Standards

ERIC Educational Resources Information Center

Julien, Anne

2005-01-01

Purpose: To set-up a classification of the types of profiles and competencies that are required to set-up a good e-learning programme. This approach provides a framework within which a set of standards can be defined for e-trainers. Design/methodology/approach: Open and distance learning (ODL) has been developing in Europe, due to new tools in…

Evaluation of Semi-supervised Learning for Classification of Protein Crystallization Imagery

PubMed Central

Sigdel, Madhav; Dinç, İmren; Dinç, Semih; Sigdel, Madhu S.; Pusey, Marc L.; Aygün, Ramazan S.

2015-01-01

In this paper, we investigate the performance of two wrapper methods for semi-supervised learning algorithms for classification of protein crystallization images with limited labeled images. Firstly, we evaluate the performance of semi-supervised approach using self-training with naïve Bayesian (NB) and sequential minimum optimization (SMO) as the base classifiers. The confidence values returned by these classifiers are used to select high confident predictions to be used for self-training. Secondly, we analyze the performance of Yet Another Two Stage Idea (YATSI) semi-supervised learning using NB, SMO, multilayer perceptron (MLP), J48 and random forest (RF) classifiers. These results are compared with the basic supervised learning using the same training sets. We perform our experiments on a dataset consisting of 2250 protein crystallization images for different proportions of training and test data. Our results indicate that NB and SMO using both self-training and YATSI semi-supervised approaches improve accuracies with respect to supervised learning. On the other hand, MLP, J48 and RF perform better using basic supervised learning. Overall, random forest classifier yields the best accuracy with supervised learning for our dataset. PMID:25914518

Analysis of signals under compositional noise with applications to SONAR data

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

Tucker, J. Derek; Wu, Wei; Srivastava, Anuj

2013-07-09

In this paper, we consider the problem of denoising and classification of SONAR signals observed under compositional noise, i.e., they have been warped randomly along the x-axis. The traditional techniques do not account for such noise and, consequently, cannot provide a robust classification of signals. We apply a recent framework that: 1) uses a distance-based objective function for data alignment and noise reduction; and 2) leads to warping-invariant distances between signals for robust clustering and classification. We use this framework to introduce two distances that can be used for signal classification: a) a y-distance, which is the distance between themore » aligned signals; and b) an x-distance that measures the amount of warping needed to align the signals. We focus on the task of clustering and classifying objects, using acoustic spectrum (acoustic color), which is complicated by the uncertainties in aspect angles at data collections. Small changes in the aspect angles corrupt signals in a way that amounts to compositional noise. As a result, we demonstrate the use of the developed metrics in classification of acoustic color data and highlight improvements in signal classification over current methods.« less

Influences of the separation distance, ship speed and channel dimension on ship maneuverability in a confined waterway

NASA Astrophysics Data System (ADS)

Du, Peng; Ouahsine, Abdellatif; Sergent, Philippe

2018-05-01

Ship maneuvering in the confined inland waterway is investigated using the system-based method, where a nonlinear transient hydrodynamic model is adopted and confinement models are implemented to account for the influence of the channel bank and bottom. The maneuvering model is validated using the turning circle test, and the confinement model is validated using the experimental data. The separation distance, ship speed, and channel width are then varied to investigate their influences on ship maneuverability. With smaller separation distances and higher speeds near the bank, the ship's trajectory deviates more from the original course and the bow is repelled with a larger yaw angle, which increase the difficulty of maneuvering. Smaller channel widths induce higher advancing resistances on the ship. The minimum distance to the bank are extracted and studied. It is suggested to navigate the ship in the middle of the channel and with a reasonable speed in the restricted waterway.

The applicability of ordinary least squares to consistently short distances between taxa in phylogenetic tree construction and the normal distribution test consequences.

PubMed

Roux, C Z

2009-05-01

Short phylogenetic distances between taxa occur, for example, in studies on ribosomal RNA-genes with slow substitution rates. For consistently short distances, it is proved that in the completely singular limit of the covariance matrix ordinary least squares (OLS) estimates are minimum variance or best linear unbiased (BLU) estimates of phylogenetic tree branch lengths. Although OLS estimates are in this situation equal to generalized least squares (GLS) estimates, the GLS chi-square likelihood ratio test will be inapplicable as it is associated with zero degrees of freedom. Consequently, an OLS normal distribution test or an analogous bootstrap approach will provide optimal branch length tests of significance for consistently short phylogenetic distances. As the asymptotic covariances between branch lengths will be equal to zero, it follows that the product rule can be used in tree evaluation to calculate an approximate simultaneous confidence probability that all interior branches are positive.

GROUND CLEARANCE INDICATOR

DOEpatents

Skinner, L.V.

1959-09-29

A narrow-band frequency-modulated distance measuring system is described. Reflected wave energy is fed into a mixer circuit together with a direct wave energy portion from the transmitter. These two input signals are out of phase by an amount proportional to the distance. Two band pass filter s select two different frequency components (both multiples of transmitter modulation frequency) from the beat frequency. These component frequencies are rectified and their voltage values, which are representative of those frequencies, are compared. It has been found that these voltages will have equal values producing a null output only when an object attains a preselected distance. The null output may be utilized to operate a normally closed relay, for example. At other ranges the voltage comparison will yield a voltage sufficient to keep the relay energized. Ranges may be changed by varying the degree of modulation of the transmitter carrier frequency. A particular advantage of this system lies in its high degree of accuracy throughout a range of distances approaching zero as a minimum.

Learning a Mahalanobis Distance-Based Dynamic Time Warping Measure for Multivariate Time Series Classification.

PubMed

Mei, Jiangyuan; Liu, Meizhu; Wang, Yuan-Fang; Gao, Huijun

2016-06-01

Multivariate time series (MTS) datasets broadly exist in numerous fields, including health care, multimedia, finance, and biometrics. How to classify MTS accurately has become a hot research topic since it is an important element in many computer vision and pattern recognition applications. In this paper, we propose a Mahalanobis distance-based dynamic time warping (DTW) measure for MTS classification. The Mahalanobis distance builds an accurate relationship between each variable and its corresponding category. It is utilized to calculate the local distance between vectors in MTS. Then we use DTW to align those MTS which are out of synchronization or with different lengths. After that, how to learn an accurate Mahalanobis distance function becomes another key problem. This paper establishes a LogDet divergence-based metric learning with triplet constraint model which can learn Mahalanobis matrix with high precision and robustness. Furthermore, the proposed method is applied on nine MTS datasets selected from the University of California, Irvine machine learning repository and Robert T. Olszewski's homepage, and the results demonstrate the improved performance of the proposed approach.

Human Movement Detection and Idengification Using Pyroelectric Infrared Sensors

PubMed Central

Yun, Jaeseok; Lee, Sang-Shin

2014-01-01

Pyroelectric infrared (PIR) sensors are widely used as a presence trigger, but the analog output of PIR sensors depends on several other aspects, including the distance of the body from the PIR sensor, the direction and speed of movement, the body shape and gait. In this paper, we present an empirical study of human movement detection and idengification using a set of PIR sensors. We have developed a data collection module having two pairs of PIR sensors orthogonally aligned and modified Fresnel lenses. We have placed three PIR-based modules in a hallway for monitoring people; one module on the ceiling; two modules on opposite walls facing each other. We have collected a data set from eight subjects when walking in three different conditions: two directions (back and forth), three distance intervals (close to one wall sensor, in the middle, close to the other wall sensor) and three speed levels (slow, moderate, fast). We have used two types of feature sets: a raw data set and a reduced feature set composed of amplitude and time to peaks; and passage duration extracted from each PIR sensor. We have performed classification analysis with well-known machine learning algorithms, including instance-based learning and support vector machine. Our findings show that with the raw data set captured from a single PIR sensor of each of the three modules, we could achieve more than 92% accuracy in classifying the direction and speed of movement, the distance interval and idengifying subjects. We could also achieve more than 94% accuracy in classifying the direction, speed and distance and idengifying subjects using the reduced feature set extracted from two pairs of PIR sensors of each of the three modules. PMID:24803195

Discrimination of Man-Made Events and Tectonic Earthquakes in Utah Using Data Recorded at Local Distances

NASA Astrophysics Data System (ADS)

Tibi, R.; Young, C. J.; Koper, K. D.; Pankow, K. L.

2017-12-01

Seismic event discrimination methods exploit the differing characteristics—in terms of amplitude and/or frequency content—of the generated seismic phases among the event types to be classified. Most of the commonly used seismic discrimination methods are designed for regional data recorded at distances of about 200 to 2000 km. Relatively little attention has focused on discriminants for local distances (< 200 km), the range at which the smallest events are recorded. Short-period fundamental mode Rayleigh waves (Rg) are commonly observed on seismograms of man-made seismic events, and shallow, naturally occurring tectonic earthquakes recorded at local distances. We leverage the well-known notion that Rg amplitude decreases dramatically with increasing event depth to propose a new depth discriminant based on Rg-to-Sg spectral amplitude ratios. The approach is successfully used to discriminate shallow events from deeper tectonic earthquakes in the Utah region recorded at local distances (< 150 km) by the University of Utah Seismographic Stations (UUSS) regional seismic network. Using Mood's median test, we obtained probabilities of nearly zero that the median Rg-to-Sg spectral amplitude ratios are the same between shallow events on one side (including both shallow tectonic earthquakes and man-made events), and deeper earthquakes on the other side, suggesting that there is a statistically significant difference in the estimated Rg-to-Sg ratios between the two populations. We also observed consistent disparities between the different types of shallow events (e.g., explosions vs. mining-induced events), implying that it may be possible to separate the sub-populations that make up this group. This suggests that using local distance Rg-to-Sg spectral amplitude ratios one can not only discriminate shallow from deeper events, but may also be able to discriminate different populations of shallow events. We also experimented with Pg-to-Sg amplitude ratios in multi-frequency linear discriminant functions to classify man-made events and tectonic earthquakes in Utah. Initial results are very promising, showing probabilities of misclassification of only 2.4-14.3%.

Notes on specifications for French airplane competitions

NASA Technical Reports Server (NTRS)

Margoulis, W

1920-01-01

Given here are the rules officially adopted by the Aeronautical Commission of the Aero Club of France for a flight competition to be held in France in 1920 at the Villacoublay Aerodrome. The prize will be awarded to the pilot who succeeds in obtaining the highest maximum and lowest minimum speeds, and in landing within the shortest distance.

Clonal growth and fine-scale genetic structure in tanoak (Notholithocarpus densiflorus: Fagaceae)

Treesearch

Richard S. Dodd; Wasima Mayer; Alejandro Nettel; Zara Afzal-Rafii

2013-01-01

The combination of sprouting and reproduction by seed can have important consequences on fine-scale spatial distribution of genetic structure (SGS). SGS is an important consideration for species’ restoration because it determines the minimum distance among seed trees to maximize genetic diversity while not prejudicing locally adapted genotypes. Local environmental...

46 CFR 194.10-20 - Magazine chest construction.

Code of Federal Regulations, 2012 CFR

2012-10-01

... lid shall have a minimum thickness of 1/8 inch. (b) Permanent sun shields shall be provided for sides... distance of 11/2 inches. Sun shields may be omitted when chests are installed “on deck protected,” shielded from direct exposure to the sun. (c) Chests shall be limited to a gross capacity of 100 cubic feet. (d...

46 CFR 194.10-20 - Magazine chest construction.

Code of Federal Regulations, 2010 CFR

2010-10-01

... lid shall have a minimum thickness of 1/8 inch. (b) Permanent sun shields shall be provided for sides... distance of 11/2 inches. Sun shields may be omitted when chests are installed “on deck protected,” shielded from direct exposure to the sun. (c) Chests shall be limited to a gross capacity of 100 cubic feet. (d...

46 CFR 194.10-20 - Magazine chest construction.

Code of Federal Regulations, 2014 CFR

2014-10-01

... lid shall have a minimum thickness of 1/8 inch. (b) Permanent sun shields shall be provided for sides... distance of 11/2 inches. Sun shields may be omitted when chests are installed “on deck protected,” shielded from direct exposure to the sun. (c) Chests shall be limited to a gross capacity of 100 cubic feet. (d...

46 CFR 194.10-20 - Magazine chest construction.

Code of Federal Regulations, 2011 CFR

2011-10-01

... lid shall have a minimum thickness of 1/8 inch. (b) Permanent sun shields shall be provided for sides... distance of 11/2 inches. Sun shields may be omitted when chests are installed “on deck protected,” shielded from direct exposure to the sun. (c) Chests shall be limited to a gross capacity of 100 cubic feet. (d...

46 CFR 194.10-20 - Magazine chest construction.

Code of Federal Regulations, 2013 CFR

2013-10-01

... lid shall have a minimum thickness of 1/8 inch. (b) Permanent sun shields shall be provided for sides... distance of 11/2 inches. Sun shields may be omitted when chests are installed “on deck protected,” shielded from direct exposure to the sun. (c) Chests shall be limited to a gross capacity of 100 cubic feet. (d...

One-time pad, complexity of verification of keys, and practical security of quantum cryptography

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

Molotkov, S. N., E-mail: sergei.molotkov@gmail.com

2016-11-15

A direct relation between the complexity of the complete verification of keys, which is one of the main criteria of security in classical systems, and a trace distance used in quantum cryptography is demonstrated. Bounds for the minimum and maximum numbers of verification steps required to determine the actual key are obtained.

27 CFR 555.206 - Location of magazines.

Code of Federal Regulations, 2010 CFR

2010-04-01

... in the table of distances for storage of explosive materials in § 555.218. (2) Ammonium nitrate and... for the separation of ammonium nitrate and blasting agents in § 555.220. However, the minimum... materials in § 555.218. [T.D. ATF-87, 46 FR 40384, Aug. 7, 1981, as amended by T.D. ATF-293, 55 FR 3722, Feb...

Electromagnetic immunity of infusion pumps to GSM mobile phones: a systematic review.

PubMed

Calcagnini, Giovanni; Censi, Federica; Triventi, Michele; Mattei, Eugenio; Bartolini, Pietro

2007-01-01

Electromagnetic interference with life-sustaining medical care devices has been reported by various groups. Previous studies have demonstrated that volumetric and syringe pumps are susceptible to false alarm buzzing and blocking, when exposed to various electromagnetic sources. The risk of electromagnetic interference depends on several factors such as the phone-emitted power, distance and carrier frequency, phone model and antenna type. The main recommendations and the relevant harmonized standard are also reported and discussed. >From the data available in literature emerges that, for distances lower than 1 m there is a non negligible risk of electromagnetic interferences, although significant differences exists in the reported minimum distances. Interference effects clinically relevant for the patients are rare. No permanent damage to the pumps has been ever reported, although in several cases intervention of personnel is required to resume normal operation.

Distance Domination Number of Graphs Resulting from Edge Comb Product

NASA Astrophysics Data System (ADS)

Slamin; Dafik; Angger Waspodo, Gembong

2018-05-01

Let G be a simple, finite and connected graph with a vertex-set V (G) and an edge-set E(G). For an integer 1 ≤ k ≤ diam (G), a distance k-dominating set of a connected graph G is a set S of vertices of G such that every vertex of V (G)\\S is at distance at most k from some vertex of S. The k-domination number of G, denoted by γk (G), is the minimum cardinality of a k-dominating set of G. In this paper, we determine the exact value of k-domination number of graphs resulting from an edge comb product of two graphs G 1 and G 2, where G 1 is a wheel, a friendship graph, or a triangular book and G 2 is a cycle.

High Performance Automatic Character Skinning Based on Projection Distance

NASA Astrophysics Data System (ADS)

Li, Jun; Lin, Feng; Liu, Xiuling; Wang, Hongrui

2018-03-01

Skeleton-driven-deformation methods have been commonly used in the character deformations. The process of painting skin weights for character deformation is a long-winded task requiring manual tweaking. We present a novel method to calculate skinning weights automatically from 3D human geometric model and corresponding skeleton. The method first, groups each mesh vertex of 3D human model to a skeleton bone by the minimum distance from a mesh vertex to each bone. Secondly, calculates each vertex's weights to the adjacent bones by the vertex's projection point distance to the bone joints. Our method's output can not only be applied to any kind of skeleton-driven deformation, but also to motion capture driven (mocap-driven) deformation. Experiments results show that our method not only has strong generality and robustness, but also has high performance.

Association of supermarket characteristics with the body mass index of their shoppers

PubMed Central

2013-01-01

Background Research on the built food environment and weight status has mostly focused on the presence/absence of food outlets while ignoring their internal features or where residents actually shop. We explored associations of distance travelled to supermarkets and supermarket characteristics with shoppers’ body mass index (BMI). Methods Shoppers (n=555) of five supermarkets situated in different income areas in the city were surveyed for food shopping habits, demographics, home postal code, height and weight. Associations of minimum distance to a supermarket (along road network, objectively measured using ArcGIS), its size, food variety and food basket price with shoppers’ BMI were investigated. The ‘food basket’ was defined as the mixture of several food items commonly consumed by residents and available in all supermarkets. Results Supermarkets ranged in total floor space (7500–135 000 square feet) and had similar varieties of fruits, vegetables and cereals. The majority of participants shopped at the surveyed supermarket more than once per week (mean range 1.2 ± 0.8 to 2.3 ± 2.1 times per week across the five supermarkets, p < 0.001), and identified it as their primary store for food (52% overall). Mean participant BMI of the five supermarkets ranged from 23.7 ± 4.3 kg/m2 to 27.1 ± 4.3 kg/m2 (p < 0.001). Median minimum distance from the shoppers’ residence to the supermarket they shopped at ranged from 0.96 (0.57, 2.31) km to 4.30 (2.83, 5.75) km (p < 0.001). A negative association was found between food basket price and BMI. There were no associations between BMI and minimum distance to the supermarket, or other supermarket characteristics. After adjusting for age, sex, dissemination area median individual income and car ownership, BMI of individuals who shopped at Store 1 and Store 2, the supermarkets with lowest price of the ‘food basket’, was 3.66 kg/m2 and 3.73 kg/m2 higher compared to their counterparts who shopped at the supermarket where the ‘food basket’ price was highest (p < 0.001). Conclusions The food basket price in supermarkets was inversely associated with BMI of their shoppers. Our results suggest that careful manipulation of food prices may be used as an intervention for decreasing BMI. PMID:23941309

Association of supermarket characteristics with the body mass index of their shoppers.

PubMed

Lear, Scott A; Gasevic, Danijela; Schuurman, Nadine

2013-08-13

Research on the built food environment and weight status has mostly focused on the presence/absence of food outlets while ignoring their internal features or where residents actually shop. We explored associations of distance travelled to supermarkets and supermarket characteristics with shoppers' body mass index (BMI). Shoppers (n=555) of five supermarkets situated in different income areas in the city were surveyed for food shopping habits, demographics, home postal code, height and weight. Associations of minimum distance to a supermarket (along road network, objectively measured using ArcGIS), its size, food variety and food basket price with shoppers' BMI were investigated. The 'food basket' was defined as the mixture of several food items commonly consumed by residents and available in all supermarkets. Supermarkets ranged in total floor space (7500-135,000 square feet) and had similar varieties of fruits, vegetables and cereals. The majority of participants shopped at the surveyed supermarket more than once per week (mean range 1.2 ± 0.8 to 2.3 ± 2.1 times per week across the five supermarkets, p < 0.001), and identified it as their primary store for food (52% overall). Mean participant BMI of the five supermarkets ranged from 23.7 ± 4.3 kg/m² to 27.1 ± 4.3 kg/m² (p < 0.001). Median minimum distance from the shoppers' residence to the supermarket they shopped at ranged from 0.96 (0.57, 2.31) km to 4.30 (2.83, 5.75) km (p < 0.001). A negative association was found between food basket price and BMI. There were no associations between BMI and minimum distance to the supermarket, or other supermarket characteristics. After adjusting for age, sex, dissemination area median individual income and car ownership, BMI of individuals who shopped at Store 1 and Store 2, the supermarkets with lowest price of the 'food basket', was 3.66 kg/m² and 3.73 kg/m² higher compared to their counterparts who shopped at the supermarket where the 'food basket' price was highest (p < 0.001). The food basket price in supermarkets was inversely associated with BMI of their shoppers. Our results suggest that careful manipulation of food prices may be used as an intervention for decreasing BMI.

A minimum distance estimation approach to the two-sample location-scale problem.

PubMed

Zhang, Zhiyi; Yu, Qiqing

2002-09-01

As reported by Kalbfleisch and Prentice (1980), the generalized Wilcoxon test fails to detect a difference between the lifetime distributions of the male and female mice died from Thymic Leukemia. This failure is a result of the test's inability to detect a distributional difference when a location shift and a scale change exist simultaneously. In this article, we propose an estimator based on the minimization of an average distance between two independent quantile processes under a location-scale model. Large sample inference on the proposed estimator, with possible right-censorship, is discussed. The mouse leukemia data are used as an example for illustration purpose.

Nuclear Fusion Rate Study of a Muonic Molecule via Nuclear Threshold Resonances

NASA Astrophysics Data System (ADS)

Faghihi, F.; Eskandari, M. R.

This work follows our previous calculations of the ground state binding energy, size, and the effective nuclear charge of the muonic T3 molecule, using the Born-Oppenheimer adiabatic approximation. In our past articles, we showed that the system possesses two minimum positions, the first one at the muonic distance and the second at the atomic distance. Also, the symmetric planner vibrational model assumed between the two minima and the approximated potential were calculated. Following from the previous studies, we now calculate the fusion rate of the T3 muonic molecule according to the overlap integral of the resonance nuclear compound nucleus and the molecular wave functions.

Constrained binary classification using ensemble learning: an application to cost-efficient targeted PrEP strategies.

PubMed

Zheng, Wenjing; Balzer, Laura; van der Laan, Mark; Petersen, Maya

2018-01-30

Binary classification problems are ubiquitous in health and social sciences. In many cases, one wishes to balance two competing optimality considerations for a binary classifier. For instance, in resource-limited settings, an human immunodeficiency virus prevention program based on offering pre-exposure prophylaxis (PrEP) to select high-risk individuals must balance the sensitivity of the binary classifier in detecting future seroconverters (and hence offering them PrEP regimens) with the total number of PrEP regimens that is financially and logistically feasible for the program. In this article, we consider a general class of constrained binary classification problems wherein the objective function and the constraint are both monotonic with respect to a threshold. These include the minimization of the rate of positive predictions subject to a minimum sensitivity, the maximization of sensitivity subject to a maximum rate of positive predictions, and the Neyman-Pearson paradigm, which minimizes the type II error subject to an upper bound on the type I error. We propose an ensemble approach to these binary classification problems based on the Super Learner methodology. This approach linearly combines a user-supplied library of scoring algorithms, with combination weights and a discriminating threshold chosen to minimize the constrained optimality criterion. We then illustrate the application of the proposed classifier to develop an individualized PrEP targeting strategy in a resource-limited setting, with the goal of minimizing the number of PrEP offerings while achieving a minimum required sensitivity. This proof of concept data analysis uses baseline data from the ongoing Sustainable East Africa Research in Community Health study. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Computing group cardinality constraint solutions for logistic regression problems.

PubMed

Zhang, Yong; Kwon, Dongjin; Pohl, Kilian M

2017-01-01

We derive an algorithm to directly solve logistic regression based on cardinality constraint, group sparsity and use it to classify intra-subject MRI sequences (e.g. cine MRIs) of healthy from diseased subjects. Group cardinality constraint models are often applied to medical images in order to avoid overfitting of the classifier to the training data. Solutions within these models are generally determined by relaxing the cardinality constraint to a weighted feature selection scheme. However, these solutions relate to the original sparse problem only under specific assumptions, which generally do not hold for medical image applications. In addition, inferring clinical meaning from features weighted by a classifier is an ongoing topic of discussion. Avoiding weighing features, we propose to directly solve the group cardinality constraint logistic regression problem by generalizing the Penalty Decomposition method. To do so, we assume that an intra-subject series of images represents repeated samples of the same disease patterns. We model this assumption by combining series of measurements created by a feature across time into a single group. Our algorithm then derives a solution within that model by decoupling the minimization of the logistic regression function from enforcing the group sparsity constraint. The minimum to the smooth and convex logistic regression problem is determined via gradient descent while we derive a closed form solution for finding a sparse approximation of that minimum. We apply our method to cine MRI of 38 healthy controls and 44 adult patients that received reconstructive surgery of Tetralogy of Fallot (TOF) during infancy. Our method correctly identifies regions impacted by TOF and generally obtains statistically significant higher classification accuracy than alternative solutions to this model, i.e., ones relaxing group cardinality constraints. Copyright © 2016 Elsevier B.V. All rights reserved.

PANTHER. Trajectory Analysis

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

Rintoul, Mark Daniel; Wilson, Andrew T.; Valicka, Christopher G.

We want to organize a body of trajectories in order to identify, search for, classify and predict behavior among objects such as aircraft and ships. Existing compari- son functions such as the Fr'echet distance are computationally expensive and yield counterintuitive results in some cases. We propose an approach using feature vectors whose components represent succinctly the salient information in trajectories. These features incorporate basic information such as total distance traveled and distance be- tween start/stop points as well as geometric features related to the properties of the convex hull, trajectory curvature and general distance geometry. Additionally, these features can generallymore » be mapped easily to behaviors of interest to humans that are searching large databases. Most of these geometric features are invariant under rigid transformation. We demonstrate the use of different subsets of these features to iden- tify trajectories similar to an exemplar, cluster a database of several hundred thousand trajectories, predict destination and apply unsupervised machine learning algorithms.« less