Effects of the body mass index on menopausal symptoms among Asian American midlife women using two different classification systems.

PubMed

Chang, Sun Ju; Chee, Wonshik; Im, Eun-Ok

2014-01-01

To explore the effects of the body mass index (BMI) on menopausal symptoms among Asian American midlife women using two different classification systems: the international classification and the BMI classification for public health action among Asian populations. Secondary analysis using data from two large Internet survey studies. Communities and groups of midlife women on the Internet. A total of 223 Asian American midlife women who were recruited over the Internet. The Midlife Women's Symptom Index and self-reports of height and weight were used to collect data. The data were analyzed using multiple analyses of covariance. No significant differences in the prevalence and severity scores among three subscales and total menopausal symptoms according to the international classification were found. When the BMI classification for public health action among Asian populations was used as an independent variable, significant differences were found in the severity scores of three subscales and total menopausal symptoms. Results of the post-hoc analyses showed that Asian American midlife women who were in the BMI classification for high risk had significantly more severe menopausal symptoms than those who were in the BMI classification for increased risk. For Asian American women, BMI categorized using the BMI classification for Asian populations is more closely related to the severity of menopausal symptoms than BMI categorized using the international classification. Nurses need to consider the BMI classification for Asian populations when they develop interventions to prevent and alleviate menopausal symptoms among Asian American midlife women. © 2013 AWHONN, the Association of Women's Health, Obstetric and Neonatal Nurses.

Can a Modified Bosniak Classification System Risk Stratify Pediatric Cystic Renal Masses?

PubMed

Saltzman, Amanda F; Carrasco, Alonso; Colvin, Alexandra N; Meyers, Mariana L; Cost, Nicholas G

2018-03-20

We characterize and apply the modified Bosniak classification system to a cohort of children with cystic renal lesions and known surgical pathology. We identified all patients at our institution with cystic renal masses who also underwent surgery for these lesions. Patients without available preoperative imaging or pathology were excluded. All radiological imaging was independently reviewed by a pediatric radiologist blinded to pathological findings. Imaging characteristics (size, border, septations, calcifications, solid components, vascularity) were recorded from the most recent preoperative ultrasounds and computerized tomograms. The modified Bosniak classification system was applied to these scans and then correlated with final pathology. A total of 22 patients met study criteria. Median age at surgery was 6.1 years (range 11 months to 16.8 years). Of the patients 12 (54.5%) underwent open nephrectomy, 6 (27.3%) open partial nephrectomy, 2 (9.1%) laparoscopic cyst decortication, 1 (4.5%) open renal biopsy and 1 (4.5%) laparoscopic partial nephrectomy. Final pathology was benign in 9 cases (41%), intermediate in 6 (27%) and malignant in 7 (32%). All malignant lesions were modified Bosniak class 4, all intermediate lesions were modified class 3 or 4 and 8 of 9 benign lesions (89%) were modified class 1 or 2. Cystic renal lesions in children with a modified Bosniak class of 1 or 2 were most often benign, while class 3 or 4 lesions warranted surgical excision since more than 90% of masses harbored intermediate or malignant pathology. The modified Bosniak classification system appears to allow for a reasonable clinical risk stratification of pediatric cystic renal masses. Copyright © 2018 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

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

PubMed

Cong, Rui; Li, Jing; Guo, Song

2017-02-01

To examine the efficacy of qualitative shear wave elastography (SWE) in the classification and evaluation of solid breast masses, and to compare this method with conventional ultrasonograghy (US), quantitative SWE parameters and qualitative SWE classification proposed before. From April 2015 to March 2016, 314 consecutive females with 325 breast masses who decided to undergo core needle biopsy and/or surgical biopsy were enrolled. Conventional US and SWE were previously performed in all enrolled subjects. Each mass was classified by two different qualitative classifications. One was established in our study, herein named the Qual1. Qual1 could classify the SWE images into five color patterns by the visual evaluations: Color pattern 1 (homogeneous pattern); Color pattern 2 (comparative homogeneous pattern); Color pattern 3 (irregularly heterogeneous pattern); Color pattern 4 (intralesional echo pattern); and Color pattern 5 (the stiff rim sign pattern). The second qualitative classification was named Qual2 here, and included a four-color overlay pattern classification (Tozaki and Fukuma, Acta Radiologica, 2011). The Breast Imaging Reporting and Data System (BI-RADS) assessment and quantitative SWE parameters were recorded. Diagnostic performances of conventional US, SWE parameters, and combinations of US and SWE parameters were compared. With pathological results as the gold standard, of the 325 examined breast masses, 139 (42.77%) samples were malignant and 186 (57.23%) were benign. The Qual1 showed a higher Az value than the Qual2 and quantitative SWE parameters (all P<0.05). When applying Qual1=Color pattern 1 for downgrading and Qual1=Color pattern 5 for upgrading the BI-RADS categories, we obtained the highest Az value (0.951), and achieved a significantly higher specificity (86.56%, P=0.002) than that of the US (81.18%) with the same sensitivity (94.96%). The qualitative classification proposed in this study may be representative of SWE parameters and has potential to be relevant assistance in breast mass diagnoses. Copyright © 2016. Published by Elsevier B.V.

In-Line Sorting of Harumanis Mango Based on External Quality Using Visible Imaging

PubMed Central

Ibrahim, Mohd Firdaus; Ahmad Sa’ad, Fathinul Syahir; Zakaria, Ammar; Md Shakaff, Ali Yeon

2016-01-01

The conventional method of grading Harumanis mango is time-consuming, costly and affected by human bias. In this research, an in-line system was developed to classify Harumanis mango using computer vision. The system was able to identify the irregularity of mango shape and its estimated mass. A group of images of mangoes of different size and shape was used as database set. Some important features such as length, height, centroid and parameter were extracted from each image. Fourier descriptor and size-shape parameters were used to describe the mango shape while the disk method was used to estimate the mass of the mango. Four features have been selected by stepwise discriminant analysis which was effective in sorting regular and misshapen mango. The volume from water displacement method was compared with the volume estimated by image processing using paired t-test and Bland-Altman method. The result between both measurements was not significantly different (P > 0.05). The average correct classification for shape classification was 98% for a training set composed of 180 mangoes. The data was validated with another testing set consist of 140 mangoes which have the success rate of 92%. The same set was used for evaluating the performance of mass estimation. The average success rate of the classification for grading based on its mass was 94%. The results indicate that the in-line sorting system using machine vision has a great potential in automatic fruit sorting according to its shape and mass. PMID:27801799

In-Line Sorting of Harumanis Mango Based on External Quality Using Visible Imaging.

PubMed

Ibrahim, Mohd Firdaus; Ahmad Sa'ad, Fathinul Syahir; Zakaria, Ammar; Md Shakaff, Ali Yeon

2016-10-27

The conventional method of grading Harumanis mango is time-consuming, costly and affected by human bias. In this research, an in-line system was developed to classify Harumanis mango using computer vision. The system was able to identify the irregularity of mango shape and its estimated mass. A group of images of mangoes of different size and shape was used as database set. Some important features such as length, height, centroid and parameter were extracted from each image. Fourier descriptor and size-shape parameters were used to describe the mango shape while the disk method was used to estimate the mass of the mango. Four features have been selected by stepwise discriminant analysis which was effective in sorting regular and misshapen mango. The volume from water displacement method was compared with the volume estimated by image processing using paired t -test and Bland-Altman method. The result between both measurements was not significantly different (P > 0.05). The average correct classification for shape classification was 98% for a training set composed of 180 mangoes. The data was validated with another testing set consist of 140 mangoes which have the success rate of 92%. The same set was used for evaluating the performance of mass estimation. The average success rate of the classification for grading based on its mass was 94%. The results indicate that the in-line sorting system using machine vision has a great potential in automatic fruit sorting according to its shape and mass.

Modelling and Analysis of the Excavation Phase by the Theory of Blocks Method of Tunnel 4 Kherrata Gorge, Algeria

NASA Astrophysics Data System (ADS)

Boukarm, Riadh; Houam, Abdelkader; Fredj, Mohammed; Boucif, Rima

2017-12-01

The aim of our work is to check the stability during excavation tunnel work in the rock mass of Kherrata, connecting the cities of Bejaia to Setif. The characterization methods through the Q system (method of Barton), RMR (Bieniawski classification) allowed us to conclude that the quality of rock mass is average in limestone, and poor in fractured limestone. Then modelling of excavation phase using the theory of blocks method (Software UNWEDGE) with the parameters from the recommendations of classification allowed us to check stability and to finally conclude that the use of geomechanical classification and the theory of blocks can be considered reliable in preliminary design.

Engineering and Design: Rock Mass Classification Data Requirements for Rippability

DTIC Science & Technology

1983-06-30

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

Importance of numerical analyses for determining support systems in tunneling: A comparative study from the trabzon-gumushane tunnel, Turkey

NASA Astrophysics Data System (ADS)

Kanik, Mustafa; Gurocak, Zulfu

2018-07-01

In this study, we determined the consistency of support elements from empirical rock mass classification systems, to obtain optimum support elements via comparative numerical analyses. For this purpose, the Macka tunnel, on the Trabzon-Gumushane highway and still under construction, was selected as the study area. Along the tunnel route, Late Cretaceous-aged Catak, Macka and Esiroglu Formations crop out. All the formations are cut by a Late Cretaceous Kackar Rhyodacite. Laboratory and field studies were done to determine the properties of the rock material and discontinuities. The results were used to define rock mass properties. Preliminary support systems were defined by using Rock Mass Rating (RMR), Rock Mass Quality (Q) and Rock Mass Index (RMi) systems, respectively. The suggested support elements of all classification systems were in turn evaluated using the Finite Elements Method (FEM), allowing the thickness of the plastic zone and total displacement values to be determined. Results of the analyses showed that it is possible to remove the instabilities around the tunnel section by applying lower numbers of support elements. When using the support systems from the numerical analyses it was found that the optimum support systems were compatible with the support systems suggested by the RMi system. Besides, when the shotcrete strength was increased to 40 MPa, the displacements and thickness of the plastic zone around the tunnel could be reduced to minimal values.

Models for predicting the mass of lime fruits by some engineering properties.

PubMed

Miraei Ashtiani, Seyed-Hassan; Baradaran Motie, Jalal; Emadi, Bagher; Aghkhani, Mohammad-Hosein

2014-11-01

Grading fruits based on mass is important in packaging and reduces the waste, also increases the marketing value of agricultural produce. The aim of this study was mass modeling of two major cultivars of Iranian limes based on engineering attributes. Models were classified into three: 1-Single and multiple variable regressions of lime mass and dimensional characteristics. 2-Single and multiple variable regressions of lime mass and projected areas. 3-Single regression of lime mass based on its actual volume and calculated volume assumed as ellipsoid and prolate spheroid shapes. All properties considered in the current study were found to be statistically significant (ρ < 0.01). The results indicated that mass modeling of lime based on minor diameter and first projected area are the most appropriate models in the first and the second classifications, respectively. In third classification, the best model was obtained on the basis of the prolate spheroid volume. It was finally concluded that the suitable grading system of lime mass is based on prolate spheroid volume.

System diagnostics using qualitative analysis and component functional classification

DOEpatents

Reifman, J.; Wei, T.Y.C.

1993-11-23

A method for detecting and identifying faulty component candidates during off-normal operations of nuclear power plants involves the qualitative analysis of macroscopic imbalances in the conservation equations of mass, energy and momentum in thermal-hydraulic control volumes associated with one or more plant components and the functional classification of components. The qualitative analysis of mass and energy is performed through the associated equations of state, while imbalances in momentum are obtained by tracking mass flow rates which are incorporated into a first knowledge base. The plant components are functionally classified, according to their type, as sources or sinks of mass, energy and momentum, depending upon which of the three balance equations is most strongly affected by a faulty component which is incorporated into a second knowledge base. Information describing the connections among the components of the system forms a third knowledge base. The method is particularly adapted for use in a diagnostic expert system to detect and identify faulty component candidates in the presence of component failures and is not limited to use in a nuclear power plant, but may be used with virtually any type of thermal-hydraulic operating system. 5 figures.

System diagnostics using qualitative analysis and component functional classification

DOEpatents

Reifman, Jaques; Wei, Thomas Y. C.

1993-01-01

A method for detecting and identifying faulty component candidates during off-normal operations of nuclear power plants involves the qualitative analysis of macroscopic imbalances in the conservation equations of mass, energy and momentum in thermal-hydraulic control volumes associated with one or more plant components and the functional classification of components. The qualitative analysis of mass and energy is performed through the associated equations of state, while imbalances in momentum are obtained by tracking mass flow rates which are incorporated into a first knowledge base. The plant components are functionally classified, according to their type, as sources or sinks of mass, energy and momentum, depending upon which of the three balance equations is most strongly affected by a faulty component which is incorporated into a second knowledge base. Information describing the connections among the components of the system forms a third knowledge base. The method is particularly adapted for use in a diagnostic expert system to detect and identify faulty component candidates in the presence of component failures and is not limited to use in a nuclear power plant, but may be used with virtually any type of thermal-hydraulic operating system.

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

PubMed

Lim, Jeong Uk; Lee, Jae Ha; Kim, Ju Sang; Hwang, Yong Il; Kim, Tae-Hyung; Lim, Seong Yong; Yoo, Kwang Ha; Jung, Ki-Suck; Kim, Young Kyoon; Rhee, Chin Kook

2017-01-01

A low body mass index (BMI) is associated with increased mortality and low health-related quality of life in patients with COPD. The Asia-Pacific classification of BMI has a lower cutoff for overweight and obese categories compared to the World Health Organization (WHO) classification. The present study assessed patients with COPD among different BMI categories according to two BMI classification systems: WHO and Asia-Pacific. Patients with COPD aged 40 years or older from the Korean COPD Subtype Study cohort were selected for evaluation. We enrolled 1,462 patients. Medical history including age, sex, St George's Respiratory Questionnaire (SGRQ-C), the modified Medical Research Council (mMRC) dyspnea scale, and post-bronchodilator forced expiratory volume in 1 second (FEV 1 ) were evaluated. Patients were categorized into different BMI groups according to the two BMI classification systems. FEV 1 and the diffusing capacity of the lung for carbon monoxide (DLCO) percentage revealed an inverse "U"-shaped pattern as the BMI groups changed from underweight to obese when WHO cutoffs were applied. When Asia-Pacific cutoffs were applied, FEV 1 and DLCO (%) exhibited a linearly ascending relationship as the BMI increased, and the percentage of patients in the overweight and obese groups linearly decreased with increasing severity of the Global Initiative for Chronic Obstructive Lung Disease criteria. From the underweight to the overweight groups, SGRQ-C and mMRC had a decreasing relationship in both the WHO and Asia-Pacific classifications. The prevalence of comorbidities in the different BMI groups showed similar trends in both BMI classifications systems. The present study demonstrated that patients with COPD who have a high BMI have better pulmonary function and health-related quality of life and reduced dyspnea symptoms. Furthermore, the Asia-Pacific BMI classification more appropriately reflects the correlation of obesity and disease manifestation in Asian COPD patients than the WHO classification.

Classification of weld defect based on information fusion technology for radiographic testing system

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

Jiang, Hongquan; Liang, Zeming, E-mail: heavenlzm@126.com; Gao, Jianmin

Improving the efficiency and accuracy of weld defect classification is an important technical problem in developing the radiographic testing system. This paper proposes a novel weld defect classification method based on information fusion technology, Dempster–Shafer evidence theory. First, to characterize weld defects and improve the accuracy of their classification, 11 weld defect features were defined based on the sub-pixel level edges of radiographic images, four of which are presented for the first time in this paper. Second, we applied information fusion technology to combine different features for weld defect classification, including a mass function defined based on the weld defectmore » feature information and the quartile-method-based calculation of standard weld defect class which is to solve a sample problem involving a limited number of training samples. A steam turbine weld defect classification case study is also presented herein to illustrate our technique. The results show that the proposed method can increase the correct classification rate with limited training samples and address the uncertainties associated with weld defect classification.« less

Classification of weld defect based on information fusion technology for radiographic testing system.

PubMed

Jiang, Hongquan; Liang, Zeming; Gao, Jianmin; Dang, Changying

2016-03-01

Improving the efficiency and accuracy of weld defect classification is an important technical problem in developing the radiographic testing system. This paper proposes a novel weld defect classification method based on information fusion technology, Dempster-Shafer evidence theory. First, to characterize weld defects and improve the accuracy of their classification, 11 weld defect features were defined based on the sub-pixel level edges of radiographic images, four of which are presented for the first time in this paper. Second, we applied information fusion technology to combine different features for weld defect classification, including a mass function defined based on the weld defect feature information and the quartile-method-based calculation of standard weld defect class which is to solve a sample problem involving a limited number of training samples. A steam turbine weld defect classification case study is also presented herein to illustrate our technique. The results show that the proposed method can increase the correct classification rate with limited training samples and address the uncertainties associated with weld defect classification.

77 FR 42318 - Orthopaedic and Rehabilitation Devices Panel of the Medical Devices Advisory Committee; Notice of...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-07-18

... regarding the classification of posterior cervical screws, including pedicle and lateral mass screws. Cervical pedicle and lateral mass screws are components of rigid, posterior spinal screw and rod systems... neck pain confirmed by radiographic studies), trauma, deformity, failed previous fusion, tumor...

Identifying the optimal segmentors for mass classification in mammograms

NASA Astrophysics Data System (ADS)

Zhang, Yu; Tomuro, Noriko; Furst, Jacob; Raicu, Daniela S.

2015-03-01

In this paper, we present the results of our investigation on identifying the optimal segmentor(s) from an ensemble of weak segmentors, used in a Computer-Aided Diagnosis (CADx) system which classifies suspicious masses in mammograms as benign or malignant. This is an extension of our previous work, where we used various parameter settings of image enhancement techniques to each suspicious mass (region of interest (ROI)) to obtain several enhanced images, then applied segmentation to each image to obtain several contours of a given mass. Each segmentation in this ensemble is essentially a "weak segmentor" because no single segmentation can produce the optimal result for all images. Then after shape features are computed from the segmented contours, the final classification model was built using logistic regression. The work in this paper focuses on identifying the optimal segmentor(s) from an ensemble mix of weak segmentors. For our purpose, optimal segmentors are those in the ensemble mix which contribute the most to the overall classification rather than the ones that produced high precision segmentation. To measure the segmentors' contribution, we examined weights on the features in the derived logistic regression model and computed the average feature weight for each segmentor. The result showed that, while in general the segmentors with higher segmentation success rates had higher feature weights, some segmentors with lower segmentation rates had high classification feature weights as well.

Mass classification in mammography with multi-agent based fusion of human and machine intelligence

NASA Astrophysics Data System (ADS)

Xi, Dongdong; Fan, Ming; Li, Lihua; Zhang, Juan; Shan, Yanna; Dai, Gang; Zheng, Bin

2016-03-01

Although the computer-aided diagnosis (CAD) system can be applied for classifying the breast masses, the effects of this method on improvement of the radiologist' accuracy for distinguishing malignant from benign lesions still remain unclear. This study provided a novel method to classify breast masses by integrating the intelligence of human and machine. In this research, 224 breast masses were selected in mammography from database of DDSM with Breast Imaging Reporting and Data System (BI-RADS) categories. Three observers (a senior and a junior radiologist, as well as a radiology resident) were employed to independently read and classify these masses utilizing the Positive Predictive Values (PPV) for each BI-RADS category. Meanwhile, a CAD system was also implemented for classification of these breast masses between malignant and benign. To combine the decisions from the radiologists and CAD, the fusion method of the Multi-Agent was provided. Significant improvements are observed for the fusion system over solely radiologist or CAD. The area under the receiver operating characteristic curve (AUC) of the fusion system increased by 9.6%, 10.3% and 21% compared to that of radiologists with senior, junior and resident level, respectively. In addition, the AUC of this method based on the fusion of each radiologist and CAD are 3.5%, 3.6% and 3.3% higher than that of CAD alone. Finally, the fusion of the three radiologists with CAD achieved AUC value of 0.957, which was 5.6% larger compared to CAD. Our results indicated that the proposed fusion method has better performance than radiologist or CAD alone.

Geotechnical Aspects of Rock Erosion in Emergency Spillway Channels. Report 5 Summary of Results, Conclusions and Recommendations

DTIC Science & Technology

1990-09-01

channel. Erosion susceptibility, similar to spillway evaluation, must emphasize rock-mass rating or classification systems (e.g. rippability ) which, when...recommends site-specific "proof of concept" testing of an Erosion Probability Index (EPI) based on rock-mass rippability rating and lithostratigraphic...and rock-mass parameters that provide key input parameters to Weaver’s (1975) Rippability Rating (RR) scheme (or Bieniawski’s (1974) Rock Mass Rating

Galaxy And Mass Assembly: automatic morphological classification of galaxies using statistical learning

NASA Astrophysics Data System (ADS)

Sreejith, Sreevarsha; Pereverzyev, Sergiy, Jr.; Kelvin, Lee S.; Marleau, Francine R.; Haltmeier, Markus; Ebner, Judith; Bland-Hawthorn, Joss; Driver, Simon P.; Graham, Alister W.; Holwerda, Benne W.; Hopkins, Andrew M.; Liske, Jochen; Loveday, Jon; Moffett, Amanda J.; Pimbblet, Kevin A.; Taylor, Edward N.; Wang, Lingyu; Wright, Angus H.

2018-03-01

We apply four statistical learning methods to a sample of 7941 galaxies (z < 0.06) from the Galaxy And Mass Assembly survey to test the feasibility of using automated algorithms to classify galaxies. Using 10 features measured for each galaxy (sizes, colours, shape parameters, and stellar mass), we apply the techniques of Support Vector Machines, Classification Trees, Classification Trees with Random Forest (CTRF) and Neural Networks, and returning True Prediction Ratios (TPRs) of 75.8 per cent, 69.0 per cent, 76.2 per cent, and 76.0 per cent, respectively. Those occasions whereby all four algorithms agree with each other yet disagree with the visual classification (`unanimous disagreement') serves as a potential indicator of human error in classification, occurring in ˜ 9 per cent of ellipticals, ˜ 9 per cent of little blue spheroids, ˜ 14 per cent of early-type spirals, ˜ 21 per cent of intermediate-type spirals, and ˜ 4 per cent of late-type spirals and irregulars. We observe that the choice of parameters rather than that of algorithms is more crucial in determining classification accuracy. Due to its simplicity in formulation and implementation, we recommend the CTRF algorithm for classifying future galaxy data sets. Adopting the CTRF algorithm, the TPRs of the five galaxy types are : E, 70.1 per cent; LBS, 75.6 per cent; S0-Sa, 63.6 per cent; Sab-Scd, 56.4 per cent, and Sd-Irr, 88.9 per cent. Further, we train a binary classifier using this CTRF algorithm that divides galaxies into spheroid-dominated (E, LBS, and S0-Sa) and disc-dominated (Sab-Scd and Sd-Irr), achieving an overall accuracy of 89.8 per cent. This translates into an accuracy of 84.9 per cent for spheroid-dominated systems and 92.5 per cent for disc-dominated systems.

Impurity profiling of liothyronine sodium by means of reversed phase HPLC, high resolution mass spectrometry, on-line H/D exchange and UV/Vis absorption.

PubMed

Ruggenthaler, M; Grass, J; Schuh, W; Huber, C G; Reischl, R J

2017-09-05

For the first time, a comprehensive investigation of the impurity profile of the synthetic thyroid API (active pharmaceutical ingredient) liothyronine sodium (LT 3 Na) was performed by using reversed phase HPLC and advanced structural elucidation techniques including high resolution tandem mass spectrometry (HRMS/MS) and on-line hydrogen-deuterium (H/D) exchange. Overall, 39 compounds were characterized and 25 of these related substances were previously unknown to literature. The impurity classification system recently developed for the closely related API levothyroxine sodium (LT 4 Na) could be applied to the newly characterized liothyronine sodium impurities resulting in a wholistic thyroid API impurity classification system. Furthermore, the mass-spectrometric CID-fragmentation of specific related substances was discussed and rationalized by detailed fragmentation pathways. Moreover, the UV/Vis absorption characteristics of the API and selected impurities were investigated to corroborate chemical structure assignments derived from MS data. Copyright © 2017 Elsevier B.V. All rights reserved.

Optimization of breast mass classification using sequential forward floating selection (SFFS) and a support vector machine (SVM) model

PubMed Central

Tan, Maxine; Pu, Jiantao; Zheng, Bin

2014-01-01

Purpose: Improving radiologists’ performance in classification between malignant and benign breast lesions is important to increase cancer detection sensitivity and reduce false-positive recalls. For this purpose, developing computer-aided diagnosis (CAD) schemes has been attracting research interest in recent years. In this study, we investigated a new feature selection method for the task of breast mass classification. Methods: We initially computed 181 image features based on mass shape, spiculation, contrast, presence of fat or calcifications, texture, isodensity, and other morphological features. From this large image feature pool, we used a sequential forward floating selection (SFFS)-based feature selection method to select relevant features, and analyzed their performance using a support vector machine (SVM) model trained for the classification task. On a database of 600 benign and 600 malignant mass regions of interest (ROIs), we performed the study using a ten-fold cross-validation method. Feature selection and optimization of the SVM parameters were conducted on the training subsets only. Results: The area under the receiver operating characteristic curve (AUC) = 0.805±0.012 was obtained for the classification task. The results also showed that the most frequently-selected features by the SFFS-based algorithm in 10-fold iterations were those related to mass shape, isodensity and presence of fat, which are consistent with the image features frequently used by radiologists in the clinical environment for mass classification. The study also indicated that accurately computing mass spiculation features from the projection mammograms was difficult, and failed to perform well for the mass classification task due to tissue overlap within the benign mass regions. Conclusions: In conclusion, this comprehensive feature analysis study provided new and valuable information for optimizing computerized mass classification schemes that may have potential to be useful as a “second reader” in future clinical practice. PMID:24664267

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

PubMed

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

2017-11-22

Little is known about the suitability of three commonly used body mass index (BMI) classification systems for Indigenous youth. We estimated overweight and obesity prevalence among Cree youth of Eeyou Istchee according to three BMI classification systems, assessed the level of agreement between them, and evaluated their accuracy through body fat and cardiometabolic risk factors. Data on 288 youth (aged 8-17 years) were collected. Overweight and obesity prevalence were estimated with Centers for Disease Control and Prevention (CDC), International Obesity Task Force (IOTF) and World Health Organization (WHO) criteria. Agreement was measured with weighted kappa (κw). Associations with body fat and cardiometabolic risk factors were evaluated by analysis of variance. Obesity prevalence was 42.7% with IOTF, 47.2% with CDC, and 49.3% with WHO criteria. Agreement was almost perfect between IOTF and CDC (κw = 0.93), IOTF and WHO (κw = 0.91), and WHO and CDC (κw = 0.94). Means of body fat and cardiometabolic risk factors were significantly higher (P trend  < 0.001) from normal weight to obesity, regardless of the system used. Youth considered overweight by IOTF but obese by CDC or WHO exhibited less severe clinical obesity. IOTF seems to be more accurate in identifying obesity in Cree youth.

Novel Strength Test Battery to Permit Evidence-Based Paralympic Classification

PubMed Central

Beckman, Emma M.; Newcombe, Peter; Vanlandewijck, Yves; Connick, Mark J.; Tweedy, Sean M.

2014-01-01

Abstract Ordinal-scale strength assessment methods currently used in Paralympic athletics classification prevent the development of evidence-based classification systems. This study evaluated a battery of 7, ratio-scale, isometric tests with the aim of facilitating the development of evidence-based methods of classification. This study aimed to report sex-specific normal performance ranges, evaluate test–retest reliability, and evaluate the relationship between the measures and body mass. Body mass and strength measures were obtained from 118 participants—63 males and 55 females—ages 23.2 years ± 3.7 (mean ± SD). Seventeen participants completed the battery twice to evaluate test–retest reliability. The body mass–strength relationship was evaluated using Pearson correlations and allometric exponents. Conventional patterns of force production were observed. Reliability was acceptable (mean intraclass correlation = 0.85). Eight measures had moderate significant correlations with body size (r = 0.30–61). Allometric exponents were higher in males than in females (mean 0.99 vs 0.30). Results indicate that this comprehensive and parsimonious battery is an important methodological advance because it has psychometric properties critical for the development of evidence-based classification. Measures were interrelated with body size, indicating further research is required to determine whether raw measures require normalization in order to be validly applied in classification. PMID:25068950

From wide to close binaries?

NASA Astrophysics Data System (ADS)

Eggleton, Peter P.

The mechanisms by which the periods of wide binaries (mass 8 solar mass or less and period 10-3000 d) are lengthened or shortened are discussed, synthesizing the results of recent theoretical investigations. A system of nomenclature involving seven evolutionary states, three geometrical states, and 10 types of orbital-period evolution is developed and applied; classifications of 71 binaries are presented in a table along with the basic observational parameters. Evolutionary processes in wide binaries (single-star-type winds, magnetic braking with tidal friction, and companion-reinforced attrition), late case B systems, low-mass X-ray binaries, and triple systems are examined in detail, and possible evolutionary paths are shown in diagrams.

Terrain classification and land hazard mapping in Kalsi-Chakrata area (Garhwal Himalaya), India

NASA Astrophysics Data System (ADS)

Choubey, Vishnu D.; Litoria, Pradeep K.

Terrain classification and land system mapping of a part of the Garhwal Himalaya (India) have been used to provide a base map for land hazard evaluation, with special reference to landslides and other mass movements. The study was based on MSS images, aerial photographs and 1:50,000 scale maps, followed by detailed field-work. The area is composed of two groups of rocks: well exposed sedimentary Precambrian formations in the Himalayan Main Boundary Thrust Belt and the Tertiary molasse deposits of the Siwaliks. Major tectonic boundaries were taken as the natural boundaries of land systems. A physiographic terrain classification included slope category, forest cover, occurrence of landslides, seismicity and tectonic activity in the area.

[Implementation of cytology images classification--the Bethesda 2001 System--in a group of screened women from Podlaskie region--effect evaluation].

PubMed

Zbroch, Tomasz; Knapp, Paweł Grzegorz; Knapp, Piotr Andrzej

2007-09-01

Increasing knowledge concerning carcinogenesis within cervical epithelium has forced us to make continues modifications of cytology classification of the cervical smears. Eventually, new descriptions of the submicroscopic cytomorphological abnormalities have enabled the implementation of Bethesda System which was meant to take place of the former Papanicolaou classification although temporarily both are sometimes used simultaneously. The aim of this study was to compare results of these two classification systems in the aspect of diagnostic accuracy verified by further tests of the diagnostic algorithm for the cervical lesion evaluation. The study was conducted in the group of women selected from general population, the criteria being the place of living and cervical cancer age risk group, in the consecutive periods of mass screening in Podlaski region. The performed diagnostic tests have been based on the commonly used algorithm, as well as identical laboratory and methodological conditions. Performed assessment revealed comparable diagnostic accuracy of both analyzing classifications, verified by histological examination, although with marked higher specificity for dysplastic lesions with decreased number of HSIL results and increased diagnosis of LSILs. Higher number of performed colposcopies and biopsies were an additional consequence of TBS classification. Results based on Bethesda System made it possible to find the sources and reasons of abnormalities with much greater precision, which enabled causing agent treatment. Two evaluated cytology classification systems, although not much different, depicted higher potential of TBS and better, more effective communication between cytology laboratory and gynecologist, making reasonable implementation of The Bethesda System in the daily cytology screening work.

Mammographic mass classification based on possibility theory

NASA Astrophysics Data System (ADS)

Hmida, Marwa; Hamrouni, Kamel; Solaiman, Basel; Boussetta, Sana

2017-03-01

Shape and margin features are very important for differentiating between benign and malignant masses in mammographic images. In fact, benign masses are usually round and oval and have smooth contours. However, malignant tumors have generally irregular shape and appear lobulated or speculated in margins. This knowledge suffers from imprecision and ambiguity. Therefore, this paper deals with the problem of mass classification by using shape and margin features while taking into account the uncertainty linked to the degree of truth of the available information and the imprecision related to its content. Thus, in this work, we proposed a novel mass classification approach which provides a possibility based representation of the extracted shape features and builds a possibility knowledge basis in order to evaluate the possibility degree of malignancy and benignity for each mass. For experimentation, the MIAS database was used and the classification results show the great performance of our approach in spite of using simple features.

A classification tree for the prediction of benign versus malignant disease in patients with small renal masses.

PubMed

Rendon, Ricardo A; Mason, Ross J; Kirkland, Susan; Lawen, Joseph G; Abdolell, Mohamed

2014-08-01

To develop a classification tree for the preoperative prediction of benign versus malignant disease in patients with small renal masses. This is a retrospective study including 395 consecutive patients who underwent surgical treatment for a renal mass < 5 cm in maximum diameter between July 1st 2001 and June 30th 2010. A classification tree to predict the risk of having a benign renal mass preoperatively was developed using recursive partitioning analysis for repeated measures outcomes. Age, sex, volume on preoperative imaging, tumor location (central/peripheral), degree of endophytic component (1%-100%), and tumor axis position were used as potential predictors to develop the model. Forty-five patients (11.4%) were found to have a benign mass postoperatively. A classification tree has been developed which can predict the risk of benign disease with an accuracy of 88.9% (95% CI: 85.3 to 91.8). The significant prognostic factors in the classification tree are tumor volume, degree of endophytic component and symptoms at diagnosis. As an example of its utilization, a renal mass with a volume of < 5.67 cm3 that is < 45% endophytic has a 52.6% chance of having benign pathology. Conversely, a renal mass with a volume ≥ 5.67 cm3 that is ≥ 35% endophytic has only a 5.3% possibility of being benign. A classification tree to predict the risk of benign disease in small renal masses has been developed to aid the clinician when deciding on treatment strategies for small renal masses.

Tunnel Design by Rock Mass Classifications

DTIC Science & Technology

1990-01-01

exhibited a slaking-like action when submerged . This is attributed to stress re- lief by coring. Bedding strikes roughly north-south and generally dips...dure ic diagrammatically depicted in Figure D5. This system, knorn as the Modified Basic RMR system or MBR in short, is based on experience gained in an

Use of border information in the classification of mammographic masses

NASA Astrophysics Data System (ADS)

Varela, C.; Timp, S.; Karssemeijer, N.

2006-01-01

We are developing a new method to characterize the margin of a mammographic mass lesion to improve the classification of benign and malignant masses. Towards this goal, we designed features that measure the degree of sharpness and microlobulation of mass margins. We calculated these features in a border region of the mass defined as a thin band along the mass contour. The importance of these features in the classification of benign and malignant masses was studied in relation to existing features used for mammographic mass detection. Features were divided into three groups, each representing a different mass segment: the interior region of a mass, the border and the outer area. The interior and the outer area of a mass were characterized using contrast and spiculation measures. Classification was done in two steps. First, features representing each of the three mass segments were merged into a neural network classifier resulting in a single regional classification score for each segment. Secondly, a classifier combined the three single scores into a final output to discriminate between benign and malignant lesions. We compared the classification performance of each regional classifier and the combined classifier on a data set of 1076 biopsy proved masses (590 malignant and 486 benign) from 481 women included in the Digital Database for Screening Mammography. Receiver operating characteristic (ROC) analysis was used to evaluate the accuracy of the classifiers. The area under the ROC curve (Az) was 0.69 for the interior mass segment, 0.76 for the border segment and 0.75 for the outer mass segment. The performance of the combined classifier was 0.81 for image-based and 0.83 for case-based evaluation. These results show that the combination of information from different mass segments is an effective approach for computer-aided characterization of mammographic masses. An advantage of this approach is that it allows the assessment of the contribution of regions rather than individual features. Results suggest that the border and the outer areas contained the most valuable information for discrimination between benign and malignant masses.

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

NASA Technical Reports Server (NTRS)

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

2007-01-01

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

Deep learning for tumor classification in imaging mass spectrometry.

PubMed

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

2018-04-01

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

Bosniak classification system: a prospective comparison of CT, contrast-enhanced US, and MR for categorizing complex renal cystic masses.

PubMed

Graumann, Ole; Osther, Susanne Sloth; Karstoft, Jens; Hørlyck, Arne; Osther, Palle Jörn Sloth

2016-11-01

Background The Bosniak classification was originally based on computed tomographic (CT) findings. Magnetic resonance (MR) and contrast-enhanced ultrasonography (CEUS) imaging may demonstrate findings that are not depicted at CT, and there may not always be a clear correlation between the findings at MR and CEUS imaging and those at CT. Purpose To compare diagnostic accuracy of MR, CEUS, and CT when categorizing complex renal cystic masses according to the Bosniak classification. Material and Methods From February 2011 to June 2012, 46 complex renal cysts were prospectively evaluated by three readers. Each mass was categorized according to the Bosniak classification and CT was chosen as gold standard. Kappa was calculated for diagnostic accuracy and data was compared with pathological results. Results CT images found 27 BII, six BIIF, seven BIII, and six BIV. Forty-three cysts could be characterized by CEUS, 79% were in agreement with CT (κ = 0.86). Five BII lesions were upgraded to BIIF and four lesions were categorized lower with CEUS. Forty-one lesions were examined with MR; 78% were in agreement with CT (κ = 0.91). Three BII lesions were upgraded to BIIF and six lesions were categorized one category lower. Pathologic correlation in six lesions revealed four malignant and two benign lesions. Conclusion CEUS and MR both up- and downgraded renal cysts compared to CT, and until these non-radiation modalities have been refined and adjusted, CT should remain the gold standard of the Bosniak classification.

Landscape analysis: Theoretical considerations and practical needs

USGS Publications Warehouse

Godfrey, A.E.; Cleaves, E.T.

1991-01-01

Numerous systems of land classification have been proposed. Most have led directly to or have been driven by an author's philosophy of earth-forming processes. However, the practical need of classifying land for planning and management purposes requires that a system lead to predictions of the results of management activities. We propose a landscape classification system composed of 11 units, from realm (a continental mass) to feature (a splash impression). The classification concerns physical aspects rather than economic or social factors; and aims to merge land inventory with dynamic processes. Landscape units are organized using a hierarchical system so that information may be assembled and communicated at different levels of scale and abstraction. Our classification uses a geomorphic systems approach that emphasizes the geologic-geomorphic attributes of the units. Realm, major division, province, and section are formulated by subdividing large units into smaller ones. For the larger units we have followed Fenneman's delineations, which are well established in the North American literature. Areas and districts are aggregated into regions and regions into sections. Units smaller than areas have, in practice, been subdivided into zones and smaller units if required. We developed the theoretical framework embodied in this classification from practical applications aimed at land use planning and land management in Maryland (eastern Piedmont Province near Baltimore) and Utah (eastern Uinta Mountains). ?? 1991 Springer-Verlag New York Inc.

An interactive system for computer-aided diagnosis of breast masses.

PubMed

Wang, Xingwei; Li, Lihua; Liu, Wei; Xu, Weidong; Lederman, Dror; Zheng, Bin

2012-10-01

Although mammography is the only clinically accepted imaging modality for screening the general population to detect breast cancer, interpreting mammograms is difficult with lower sensitivity and specificity. To provide radiologists "a visual aid" in interpreting mammograms, we developed and tested an interactive system for computer-aided detection and diagnosis (CAD) of mass-like cancers. Using this system, an observer can view CAD-cued mass regions depicted on one image and then query any suspicious regions (either cued or not cued by CAD). CAD scheme automatically segments the suspicious region or accepts manually defined region and computes a set of image features. Using content-based image retrieval (CBIR) algorithm, CAD searches for a set of reference images depicting "abnormalities" similar to the queried region. Based on image retrieval results and a decision algorithm, a classification score is assigned to the queried region. In this study, a reference database with 1,800 malignant mass regions and 1,800 benign and CAD-generated false-positive regions was used. A modified CBIR algorithm with a new function of stretching the attributes in the multi-dimensional space and decision scheme was optimized using a genetic algorithm. Using a leave-one-out testing method to classify suspicious mass regions, we compared the classification performance using two CBIR algorithms with either equally weighted or optimally stretched attributes. Using the modified CBIR algorithm, the area under receiver operating characteristic curve was significantly increased from 0.865 ± 0.006 to 0.897 ± 0.005 (p < 0.001). This study demonstrated the feasibility of developing an interactive CAD system with a large reference database and achieving improved performance.

Annotated Bibliography of REMR Technical Reports Through September 1992

DTIC Science & Technology

1992-11-01

that rippability and litho-stratigraphic discontinuity may serve as a good point of departure in describing the relative resistance to erosion of rocks...phasize rock-mass ratings or classification systems (e.g. rippability ) which, when combined with lithostratigraphic discontinuity and hydraulic data

Associations between ozone and morbidity using the Spatial Synoptic Classification system

PubMed Central

2011-01-01

Background Synoptic circulation patterns (large-scale tropospheric motion systems) affect air pollution and, potentially, air-pollution-morbidity associations. We evaluated the effect of synoptic circulation patterns (air masses) on the association between ozone and hospital admissions for asthma and myocardial infarction (MI) among adults in North Carolina. Methods Daily surface meteorology data (including precipitation, wind speed, and dew point) for five selected cities in North Carolina were obtained from the U.S. EPA Air Quality System (AQS), which were in turn based on data from the National Climatic Data Center of the National Oceanic and Atmospheric Administration. We used the Spatial Synoptic Classification system to classify each day of the 9-year period from 1996 through 2004 into one of seven different air mass types: dry polar, dry moderate, dry tropical, moist polar, moist moderate, moist tropical, or transitional. Daily 24-hour maximum 1-hour ambient concentrations of ozone were obtained from the AQS. Asthma and MI hospital admissions data for the 9-year period were obtained from the North Carolina Department of Health and Human Services. Generalized linear models were used to assess the association of the hospitalizations with ozone concentrations and specific air mass types, using pollutant lags of 0 to 5 days. We examined the effect across cities on days with the same air mass type. In all models we adjusted for dew point and day-of-the-week effects related to hospital admissions. Results Ozone was associated with asthma under dry tropical (1- to 5-day lags), transitional (3- and 4-day lags), and extreme moist tropical (0-day lag) air masses. Ozone was associated with MI only under the extreme moist tropical (5-day lag) air masses. Conclusions Elevated ozone levels are associated with dry tropical, dry moderate, and moist tropical air masses, with the highest ozone levels being associated with the dry tropical air mass. Certain synoptic circulation patterns/air masses in conjunction with ambient ozone levels were associated with increased asthma and MI hospitalizations. PMID:21609456

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

ERIC Educational Resources Information Center

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

2018-01-01

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

Comparison of estimates of body fat content in childhood-onset systemic lupus erythematosus.

PubMed

Sinicato, N A; Peres, F A; de Oliveira Peliçari, K; de Oliveira Santos, A; Ramos, C D; Marini, R; Appenzeller, S

2017-04-01

Objective We aimed to compare estimates of body fat content with respect to their ability to predict the percentage of body fat, confirmed by dual-energy X-ray absorptiometry scans in childhood-onset systemic lupus erythematosus. Methods We included 64 consecutive childhood-onset systemic lupus erythematosus patients and 64 healthy age and sex-matched controls in a cross-sectional study. Anthropometric data, body mass index and body adiposity index were calculated for all subjects. Childhood-onset systemic lupus erythematosus patients were further assessed for clinical and laboratory childhood-onset systemic lupus erythematosus manifestations and fat mass, lean mass and percentage of body fat evaluated by dual-energy X-ray absorptiometry. Results Elevated waist/hip ratio was observed in childhood-onset systemic lupus erythematosus patients when compared to controls ( p < 0.001). We did not find differences between body mass index and body adiposity index classification in childhood-onset systemic lupus erythematosus patients and controls. Using dual-energy X-ray absorptiometry as gold standard we observed that all indirect estimates of body fat were correlated with whole body fat mass. We observed a correlation between height and cumulative corticosteroid dose adjusted by weight ( r = 0.429, p = 0.005) in childhood-onset systemic lupus erythematosus. On whole body analysis we observed a correlation between lean mass and ACR Damage Index scores ( r = -0.395; p = 0.019); percentage of body fat and adjusted Systemic Lupus Erythematosus Disease Activity Index ( r = 0.402; p = 0.008), disease duration ( r = -0.370; p = 0.012). On trunk analysis we observed a correlation between lean mass and ACR Damage Index ( r = -0.319; p = 0.042); percentage of body fat with adjusted Systemic Lupus Erythematosus Disease Activity Index ( r = 0.402; p = 0.005), disease duration ( r = -0.408; p = 0.005). Conclusions This is the first study analyzing body adiposity index in childhood-onset systemic lupus erythematosus patients. We observed that all indirect estimates of body fat were correlated with whole body fat mass. This study shows that we should not replace body mass index by body adiposity index to evaluating fat levels in childhood-onset systemic lupus erythematosus. In consideration of the importance of overweight classification in cardiovascular diseases, any direct estimates of body fat can be used in an attempt to improve the prognosis of patients. Note We believe that we have presented evidence of body adiposity index accuracy in childhood-onset systemic lupus erythematosus patients but further research on the generalizability of body adiposity index to other patient groups needs to be done.

A new classification and treatment protocol for gynecomastia.

PubMed

Ratnam, B Venkata

2009-01-01

It is not uncommon to encounter patients who have undergone surgery for gynecomastia but who were not fully satisfied with the results. Although various approaches and techniques based on presurgical classification systems aimed at yielding the best possible surgical outcomes have been offered, standardized recommendation that is generally accepted by surgeons is lacking. The author reports on a new classification system and treatment protocol for the surgical treatment of gynecomastia. A system was developed that classifies patients into 3 types based on skin elasticity, presence of an inframammary fold (IMF), and mammary ptosis. Surgical excision of the breast mass was followed by a combination of destruction of the IMF, ultrasound-assisted lipoplasty (UAL) of the chest wall, ultrasound stimulation of the breast skin, and periareolar deepithelialization, depending on the gyneocomastia classification. This classification and the treatment protocol were applied to 30 patients, 13 to 60 years of age, between January 2005 and December 2007. Among these patients, 12 were classified as type 1, 6 as type 2, and 12 as type 3. Follow-up ranged from 3 to 18 months. Complications were common to all types of cases and techniques. They included 2 hematomas, 1 wound dehiscence, 5 cases of residual gynecomastia in those patients who underwent UAL alone, and 3 minor aesthetic problems near areolae. The proposed new classification and treatment protocol were found to help solve problems associated with surgical outcomes for all types of gynecomastia, although the issue of residual gynecomastia in patients undergoing UAL alone requires further study.

Using an object-based grid system to evaluate a newly developed EP approach to formulate SVMs as applied to the classification of organophosphate nerve agents

NASA Astrophysics Data System (ADS)

Land, Walker H., Jr.; Lewis, Michael; Sadik, Omowunmi; Wong, Lut; Wanekaya, Adam; Gonzalez, Richard J.; Balan, Arun

2004-04-01

This paper extends the classification approaches described in reference [1] in the following way: (1.) developing and evaluating a new method for evolving organophosphate nerve agent Support Vector Machine (SVM) classifiers using Evolutionary Programming, (2.) conducting research experiments using a larger database of organophosphate nerve agents, and (3.) upgrading the architecture to an object-based grid system for evaluating the classification of EP derived SVMs. Due to the increased threats of chemical and biological weapons of mass destruction (WMD) by international terrorist organizations, a significant effort is underway to develop tools that can be used to detect and effectively combat biochemical warfare. This paper reports the integration of multi-array sensors with Support Vector Machines (SVMs) for the detection of organophosphates nerve agents using a grid computing system called Legion. Grid computing is the use of large collections of heterogeneous, distributed resources (including machines, databases, devices, and users) to support large-scale computations and wide-area data access. Finally, preliminary results using EP derived support vector machines designed to operate on distributed systems have provided accurate classification results. In addition, distributed training time architectures are 50 times faster when compared to standard iterative training time methods.

Computer-aided Classification of Mammographic Masses Using Visually Sensitive Image Features

PubMed Central

Wang, Yunzhi; Aghaei, Faranak; Zarafshani, Ali; Qiu, Yuchen; Qian, Wei; Zheng, Bin

2017-01-01

Purpose To develop a new computer-aided diagnosis (CAD) scheme that computes visually sensitive image features routinely used by radiologists to develop a machine learning classifier and distinguish between the malignant and benign breast masses detected from digital mammograms. Methods An image dataset including 301 breast masses was retrospectively selected. From each segmented mass region, we computed image features that mimic five categories of visually sensitive features routinely used by radiologists in reading mammograms. We then selected five optimal features in the five feature categories and applied logistic regression models for classification. A new CAD interface was also designed to show lesion segmentation, computed feature values and classification score. Results Areas under ROC curves (AUC) were 0.786±0.026 and 0.758±0.027 when to classify mass regions depicting on two view images, respectively. By fusing classification scores computed from two regions, AUC increased to 0.806±0.025. Conclusion This study demonstrated a new approach to develop CAD scheme based on 5 visually sensitive image features. Combining with a “visual aid” interface, CAD results may be much more easily explainable to the observers and increase their confidence to consider CAD generated classification results than using other conventional CAD approaches, which involve many complicated and visually insensitive texture features. PMID:27911353

Breast cancer risk assessment and diagnosis model using fuzzy support vector machine based expert system

NASA Astrophysics Data System (ADS)

Dheeba, J.; Jaya, T.; Singh, N. Albert

2017-09-01

Classification of cancerous masses is a challenging task in many computerised detection systems. Cancerous masses are difficult to detect because these masses are obscured and subtle in mammograms. This paper investigates an intelligent classifier - fuzzy support vector machine (FSVM) applied to classify the tissues containing masses on mammograms for breast cancer diagnosis. The algorithm utilises texture features extracted using Laws texture energy measures and a FSVM to classify the suspicious masses. The new FSVM treats every feature as both normal and abnormal samples, but with different membership. By this way, the new FSVM have more generalisation ability to classify the masses in mammograms. The classifier analysed 219 clinical mammograms collected from breast cancer screening laboratory. The tests made on the real clinical mammograms shows that the proposed detection system has better discriminating power than the conventional support vector machine. With the best combination of FSVM and Laws texture features, the area under the Receiver operating characteristic curve reached .95, which corresponds to a sensitivity of 93.27% with a specificity of 87.17%. The results suggest that detecting masses using FSVM contribute to computer-aided detection of breast cancer and as a decision support system for radiologists.

Classification of bacteria by simultaneous methylation-solid phase microextraction and gas chromatography/mass spectrometry analysis of fatty acid methyl esters.

PubMed

Lu, Yao; Harrington, Peter B

2010-08-01

Direct methylation and solid-phase microextraction (SPME) were used as a sample preparation technique for classification of bacteria based on fatty acid methyl ester (FAME) profiles. Methanolic tetramethylammonium hydroxide was applied as a dual-function reagent to saponify and derivatize whole-cell bacterial fatty acids into FAMEs in one step, and SPME was used to extract the bacterial FAMEs from the headspace. Compared with traditional alkaline saponification and sample preparation using liquid-liquid extraction, the method presented in this work avoids using comparatively large amounts of inorganic and organic solvents and greatly decreases the sample preparation time as well. Characteristic gas chromatography/mass spectrometry (GC/MS) of FAME profiles was achieved for six bacterial species. The difference between Gram-positive and Gram-negative bacteria was clearly visualized with the application of principal component analysis of the GC/MS data of bacterial FAMEs. A cross-validation study using ten bootstrap Latin partitions and the fuzzy rule building expert system demonstrated 87 +/- 3% correct classification efficiency.

Primary mass discrimination of high energy cosmic rays using PNN and k-NN methods

NASA Astrophysics Data System (ADS)

Rastegarzadeh, G.; Nemati, M.

2018-02-01

Probabilistic neural network (PNN) and k-Nearest Neighbors (k-NN) methods are widely used data classification techniques. In this paper, these two methods have been used to classify the Extensive Air Shower (EAS) data sets which were simulated using the CORSIKA code for three primary cosmic rays. The primaries are proton, oxygen and iron nuclei at energies of 100 TeV-10 PeV. This study is performed in the following of the investigations into the primary cosmic ray mass sensitive observables. We propose a new approach for measuring the mass sensitive observables of EAS in order to improve the primary mass separation. In this work, the EAS observables measurement has performed locally instead of total measurements. Also the relationships between the included number of observables in the classification methods and the prediction accuracy have been investigated. We have shown that the local measurements and inclusion of more mass sensitive observables in the classification processes can improve the classifying quality and also we have shown that muons and electrons energy density can be considered as primary mass sensitive observables in primary mass classification. Also it must be noted that this study is performed for Tehran observation level without considering the details of any certain EAS detection array.

A Spectroscopic and Mineralogical Study of Multiple Asteroid Systems

NASA Astrophysics Data System (ADS)

Lindsay, Sean S.; Emery, J. P.; Marchis, F.; Enriquez, J.; Assafin, M.

2013-10-01

There are currently ~200 identified multiple asteroid systems (MASs). These systems display a large diversity in heliocentric distance, size/mass ratio, system angular momentum, mutual orbital parameters, and taxonomic class. These characteristics are simplified under the nomenclature of Descamps and Marchis (2008), which divides MASs into four types: Type-1 - large asteroids with small satellites; Type-2 - similar size double asteroids; Type-3 - small asynchronous systems; and Type-4 - contact-binary asteroids. The large MAS diversity suggests multiple formation mechanisms are required to understand their origins. There are currently three broad formation scenarios: 1) ejecta from impacts; 2) catastrophic disruption followed by rotational fission; and 3) tidal disruption. The taxonomic class and mineralogy of the MASs coupled with the average density and system angular momentum provide a potential means to discriminate between proposed formation mechanisms. We present visible and near-infrared (NIR) spectra spanning 0.45 - 2.45 μm for 23 Main Belt MASs. The data were primarily obtained using the Southern Astrophysical Research Telescope (SOAR) Goodman High Throughput Spectrograph (August 2011 - July 2012) for the visible data and the InfraRed Telescope Facility (IRTF) SpeX Spectrograph (August 2008 - May 2013) for the IR data. Our data were supplemented using previously published data when necessary. The asteroids' Bus-DeMeo taxonomic classes are determined using the MIT SMASS online classification routines. Our sample includes 3 C-types, 1 X-type, 1 K-type, 1 L-type, 4 V-types, 10 S-types, 2 Sq- or Q-types, and 1 ambiguous classification. We calculate the 1- and 2-μm band centers, depths, and areas to determine the pyroxene mineralogy (molar Fs and Wo) of the surfaces using empirically derived equations. The NIR band analysis allows us to determine the S-type subclasses, S(I) - S(VII), which roughly tracks olivine-pyroxene chemistry. A comparison of the orbital parameters, physical parameters (size, density, and angular momentum), collisional family membership, and taxonomy is presented in an effort to find correlations, which may give insights to how these MASs formation mechanisms.

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

PubMed

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

2013-09-01

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

Real-Time Food Authentication Using a Miniature Mass Spectrometer.

PubMed

Gerbig, Stefanie; Neese, Stephan; Penner, Alexander; Spengler, Bernhard; Schulz, Sabine

2017-10-17

Food adulteration is a threat to public health and the economy. In order to determine food adulteration efficiently, rapid and easy-to-use on-site analytical methods are needed. In this study, a miniaturized mass spectrometer in combination with three ambient ionization methods was used for food authentication. The chemical fingerprints of three milk types, five fish species, and two coffee types were measured using electrospray ionization, desorption electrospray ionization, and low temperature plasma ionization. Minimum sample preparation was needed for the analysis of liquid and solid food samples. Mass spectrometric data was processed using the laboratory-built software MS food classifier, which allows for the definition of specific food profiles from reference data sets using multivariate statistical methods and the subsequent classification of unknown data. Applicability of the obtained mass spectrometric fingerprints for food authentication was evaluated using different data processing methods, leave-10%-out cross-validation, and real-time classification of new data. Classification accuracy of 100% was achieved for the differentiation of milk types and fish species, and a classification accuracy of 96.4% was achieved for coffee types in cross-validation experiments. Measurement of two milk mixtures yielded correct classification of >94%. For real-time classification, the accuracies were comparable. Functionality of the software program and its performance is described. Processing time for a reference data set and a newly acquired spectrum was found to be 12 s and 2 s, respectively. These proof-of-principle experiments show that the combination of a miniaturized mass spectrometer, ambient ionization, and statistical analysis is suitable for on-site real-time food authentication.

A moderate resolution inventory of small glaciers and ice caps surrounding Greenland and the Antarctic peninsula

NASA Astrophysics Data System (ADS)

Chen, C.; Box, J. E.; Hock, R. M.; Cogley, J. G.

2011-12-01

Current estimates of global Mountain Glacier and Ice Caps (MG&IC) mass changes are subject to large uncertainties due to incomplete inventories and uncertainties in land surface classification. This presentation features mitigative efforts through the creation of a MODIS dependent land ice classification system and its application for glacier inventory. Estimates of total area of mountain glaciers [IPCC, 2007] and ice caps (including those in Greenland and Antarctica) vary 15%, that is, 680 - 785 10e3 sq. km. To date only an estimated 40% of glaciers (by area) is inventoried in the World Glacier Inventory (WGI) and made available through the World Glacier Monitoring System (WGMS) and the National Snow and Ice Data Center [NSIDC, 1999]. Cogley [2009] recently compiled a more complete version of WGI, called WGI-XF, containing records for just over 131,000 glaciers, covering approximately half of the estimated global MG&IC area. The glaciers isolated from the conterminous Antarctic and Greenland ice sheets remain incompletely inventoried in WGI-XF but have been estimated to contribute 35% to the MG&IC sea-level equivalent during 1961-2004 [Hock et al., 2009]. Together with Arctic Canada and Alaska these regions alone make up almost 90% of the area that is missing in the global WGI-XF inventory. Global mass balance projections tend to exclude ice masses in Greenland and Antarctica due to the paucity of data with respect to basic inventory base data such as area, number of glaciers or size distributions. We address the need for an accurate Greenland and Antarctic peninsula land surface classification with a novel glacier surface classification and inventory based on NASA Moderate Resolution Imaging Spectroradiometer (MODIS) data gridded at 250 m pixel resolution. The presentation includes a sensitivity analysis for surface mass balance as it depends on the land surface classification. Works Cited +Cogley, J. G. (2009), A more complete version of the World Glacier Inventory, Ann. Glaciol. 50(53). +Hock, R., M. de Woul, V. Radi and M. Dyurgerov, 2009. Mountain glaciers and ice caps around Antarctica make a large sea-level rise contribution. Geophys. Res. Lett. 36, L07501, doi:10.1029/2008GL037020. +IPCC, Climate Change 2007 The Physical Science Basis, 2007. Contribution of working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (eds. Solomon, S. et al.) Cambridge University Press, Cambridge, UK.

Improving mass candidate detection in mammograms via feature maxima propagation and local feature selection.

PubMed

Melendez, Jaime; Sánchez, Clara I; van Ginneken, Bram; Karssemeijer, Nico

2014-08-01

Mass candidate detection is a crucial component of multistep computer-aided detection (CAD) systems. It is usually performed by combining several local features by means of a classifier. When these features are processed on a per-image-location basis (e.g., for each pixel), mismatching problems may arise while constructing feature vectors for classification, which is especially true when the behavior expected from the evaluated features is a peaked response due to the presence of a mass. In this study, two of these problems, consisting of maxima misalignment and differences of maxima spread, are identified and two solutions are proposed. The first proposed method, feature maxima propagation, reproduces feature maxima through their neighboring locations. The second method, local feature selection, combines different subsets of features for different feature vectors associated with image locations. Both methods are applied independently and together. The proposed methods are included in a mammogram-based CAD system intended for mass detection in screening. Experiments are carried out with a database of 382 digital cases. Sensitivity is assessed at two sets of operating points. The first one is the interval of 3.5-15 false positives per image (FPs/image), which is typical for mass candidate detection. The second one is 1 FP/image, which allows to estimate the quality of the mass candidate detector's output for use in subsequent steps of the CAD system. The best results are obtained when the proposed methods are applied together. In that case, the mean sensitivity in the interval of 3.5-15 FPs/image significantly increases from 0.926 to 0.958 (p < 0.0002). At the lower rate of 1 FP/image, the mean sensitivity improves from 0.628 to 0.734 (p < 0.0002). Given the improved detection performance, the authors believe that the strategies proposed in this paper can render mass candidate detection approaches based on image location classification more robust to feature discrepancies and prove advantageous not only at the candidate detection level, but also at subsequent steps of a CAD system.

Galaxy Zoo 1: data release of morphological classifications for nearly 900 000 galaxies

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

Linott, C.; Slosar, A.; Lintott, C.

Morphology is a powerful indicator of a galaxy's dynamical and merger history. It is strongly correlated with many physical parameters, including mass, star formation history and the distribution of mass. The Galaxy Zoo project collected simple morphological classifications of nearly 900,000 galaxies drawn from the Sloan Digital Sky Survey, contributed by hundreds of thousands of volunteers. This large number of classifications allows us to exclude classifier error, and measure the influence of subtle biases inherent in morphological classification. This paper presents the data collected by the project, alongside measures of classification accuracy and bias. The data are now publicly availablemore » and full catalogues can be downloaded in electronic format from http://data.galaxyzoo.org.« less

Identification and Classification of Mass Transport Complexes in Offshore Trinidad/Venezuela and Their Potential Anthropogenic Impact as Tsunamigenic Hazards

NASA Astrophysics Data System (ADS)

Moscardelli, L.; Wood, L. J.

2006-12-01

Several late Pleistocene-age seafloor destabilization events have been identified in the continental margin of eastern offshore Trinidad, of sufficient scale to produce tsunamigenic forces. This area, situated along the obliquely-converging-boundary of the Caribbean/South American plates and proximal to the Orinoco Delta, is characterized by catastrophic shelf-margin processes, intrusive-extrusive mobile shales, and active tectonism. A mega-merged, 10,000km2, 3D seismic survey reveals several mass transport complexes that range in area from 11.3km2 to 2017km2. Historical records indicate that this region has experienced submarine landslide- generated tsunamigenic events, including tsunamis that affected Venezuela during the 1700's-1900's. This work concentrates on defining those ancient deep marine mass transport complexes whose occurrence could potentially triggered tsunamis. Three types of failures are identified; 1) source-attached failures that are fed by shelf edge deltas whose sediment input is controlled by sea-level fluctuations and sedimentation rates, 2) source-detached systems, which occur when upper slope sediments catastrophically fail due to gas hydrate disruptions and/or earthquakes, and 3) locally sourced failures, formed when local instabilities in the sea floor trigger relatively smaller collapses. Such classification of the relationship between slope mass failures and the sourcing regions enables a better understanding of the nature of initiation, length of development history and petrography of such mass transport deposits. Source-detached systems, generated due to sudden sediment remobilizations, are more likely to disrupt the overlying water column causing a rise in tsunamigenic risk. Unlike 2D seismic, 3D seismic enables scientists to calculate more accurate deposit volumes, improve deposit imaging and thus increase the accuracy of physical and computer simulations of mass failure processes.

76 FR 16292 - Medical Devices; Immunology and Microbiology Devices; Classification of Ovarian Adnexal Mass...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-03-23

... test system into class II (special controls). The special control that will apply to these devices is the guidance document entitled ``Guidance for Industry and FDA Staff; Class II Special Controls... devices into class II (special controls) because special controls, in addition to general controls, will...

Hybrid ANN optimized artificial fish swarm algorithm based classifier for classification of suspicious lesions in breast DCE-MRI

NASA Astrophysics Data System (ADS)

Janaki Sathya, D.; Geetha, K.

2017-12-01

Automatic mass or lesion classification systems are developed to aid in distinguishing between malignant and benign lesions present in the breast DCE-MR images, the systems need to improve both the sensitivity and specificity of DCE-MR image interpretation in order to be successful for clinical use. A new classifier (a set of features together with a classification method) based on artificial neural networks trained using artificial fish swarm optimization (AFSO) algorithm is proposed in this paper. The basic idea behind the proposed classifier is to use AFSO algorithm for searching the best combination of synaptic weights for the neural network. An optimal set of features based on the statistical textural features is presented. The investigational outcomes of the proposed suspicious lesion classifier algorithm therefore confirm that the resulting classifier performs better than other such classifiers reported in the literature. Therefore this classifier demonstrates that the improvement in both the sensitivity and specificity are possible through automated image analysis.

Classification of cultivation locations of Panax quinquefolius L samples using high performance liquid chromatography-electrospray ionization mass spectrometry and chemometric analysis

USDA-ARS?s Scientific Manuscript database

Panax quinquefolius L (P. quinquefolius L) samples grown in the United States and China were analyzed with high performance liquid chromatography-mass spectrometry (HPLC—MS). Prior to classification, the two-way datasets were subjected to pretreatment including baseline correction and retention tim...

Classification of cultivation locations of panax quinquefolius L samples using high performance liquid chromatography-electrospray ionization mass spectrometry and chemometric analysis

USDA-ARS?s Scientific Manuscript database

Panax quinquefolius L (P. quinquefolius L) samples grown in the United States and China were analyzed with high performance liquid chromatography-mass spectrometry (HPLC—MS). Prior to classification, the two-way datasets were subjected to pretreatment including baseline correction and retention ti...

Obesity classification in military personnel: A comparison of body fat, waist circumference, and body mass index measurements

USDA-ARS?s Scientific Manuscript database

The purpose of this study was to evaluate obesity classifications from body fat percentage (BF%), body mass index (BMI), and waist circumference (WC). A total of 451 overweight/obese active duty military personnel completed all three assessments. Most were obese (men, 81%; women, 98%) using National...

Correlation of mass spectrometry identified bacterial biomarkers from a fielded pyrolysis-gas chromatography-ion mobility spectrometry biodetector with the microbiological gram stain classification scheme.

PubMed

Snyder, A Peter; Dworzanski, Jacek P; Tripathi, Ashish; Maswadeh, Waleed M; Wick, Charles H

2004-11-01

A pyrolysis-gas chromatography-ion mobility spectrometry (Py-GC-IMS) briefcase system has been shown to detect and classify deliberately released bioaerosols in outdoor field scenarios. The bioaerosols included Gram-positive and Gram-negative bacteria, MS-2 coliphage virus, and ovalbumin protein species. However, the origin and structural identities of the pyrolysate peaks in the GC-IMS data space, their microbiological information content, and taxonomic importance with respect to biodetection have not been determined. The present work interrogates the identities of the peaks by inserting a time-of-flight mass spectrometry system in parallel with the IMS detector through a Tee connection in the GC module. Biological substances producing ion mobility peaks from the pyrolysis of microorganisms were identified by their GC retention time, matching of their electron ionization mass spectra with authentic standards, and the National Institutes for Standards and Technology mass spectral database. Strong signals from 2-pyridinecarboxamide were identified in Bacillus samples including Bacillus anthracis, and its origin was traced to the cell wall peptidoglycan macromolecule. 3-Hydroxymyristic acid is a component of lipopolysaccharides in the cell walls of Gram-negative organisms. The Gram-negative Escherichia coli organism showed significant amounts of 3-hydroxymyristic acid derivatives and degradation products in Py-GC-MS analyses. Some of the fatty acid derivatives were observed in very low abundance in the ion mobility spectra, and the higher boiling lipid species were absent. Evidence is presented that the Py-GC-ambient temperature and pressure-IMS system generates and detects bacterial biochemical information that can serve as components of a biological classification scheme directly correlated to the Gram stain reaction in microorganism taxonomy.

Benign-malignant mass classification in mammogram using edge weighted local texture features

NASA Astrophysics Data System (ADS)

Rabidas, Rinku; Midya, Abhishek; Sadhu, Anup; Chakraborty, Jayasree

2016-03-01

This paper introduces novel Discriminative Robust Local Binary Pattern (DRLBP) and Discriminative Robust Local Ternary Pattern (DRLTP) for the classification of mammographic masses as benign or malignant. Mass is one of the common, however, challenging evidence of breast cancer in mammography and diagnosis of masses is a difficult task. Since DRLBP and DRLTP overcome the drawbacks of Local Binary Pattern (LBP) and Local Ternary Pattern (LTP) by discriminating a brighter object against the dark background and vice-versa, in addition to the preservation of the edge information along with the texture information, several edge-preserving texture features are extracted, in this study, from DRLBP and DRLTP. Finally, a Fisher Linear Discriminant Analysis method is incorporated with discriminating features, selected by stepwise logistic regression method, for the classification of benign and malignant masses. The performance characteristics of DRLBP and DRLTP features are evaluated using a ten-fold cross-validation technique with 58 masses from the mini-MIAS database, and the best result is observed with DRLBP having an area under the receiver operating characteristic curve of 0.982.

Improving Resource Allocation Decisions to Reduce the Risk of Terrorist Attacks on Passenger Rail Systems

DTIC Science & Technology

2016-12-01

theory, passenger rail bombing , attacker-defender methodology 15. NUMBER OF PAGES 103 16. PRICE CODE 17. SECURITY CLASSIFICATION OF REPORT...bombers carried out a successful coordinated attack against the London mass transit system in July 2005. Three suicide bombings occurred on trains and...iron rods to make shrapnel. The precise timing indicates the terrorists themselves detonated their own devices. In March 2016, a suicide bomb

Development of an Automated Modality-Independent Elastographic Image Analysis System for Tumor Screening

DTIC Science & Technology

2006-02-01

further develop modality-independent elastography as a system that is able to reproducibly detect regions of increased stiffness within the breast based...tested on a tissue-like polymer phantom. elastography , breast cancer screening, image processing 16. SECURITY CLASSIFICATION OF: 17. LIMITATION...is a map of the breast (or other tissue of interest) that reflects material inhomogeneity, such as in the case of a tumor mass that disrupts the

3 CFR 13526 - Executive Order 13526 of December 29, 2009. Classified National Security Information

Code of Federal Regulations, 2010 CFR

2010-01-01

... of weapons of mass destruction. Sec. 1.5. Duration of Classification. (a) At the time of original... intelligence source or key design concepts of weapons of mass destruction, the date or event shall not exceed the time frame established in paragraph (b) of this section. (b) If the original classification...

Mechanical Face Seal Dynamics.

DTIC Science & Technology

1985-12-01

1473, 83 APR EDITION OF I JAN 73 IS OBSOLETE. UNCLASSIFIED SECURITY CLASSIFICATION OF THIS PAGE -,1 - " P V 7 V - • ... f -N- PRE FACE This final...dimensionless mass m and support damping 1), ~ at-e aisas M"= -1,,i -4 4) y positive. ’he damping D is Ihe tinplete system of momeints acting on tile

Osteoarthritis classification using self organizing map based on gabor kernel and contrast-limited adaptive histogram equalization.

PubMed

Anifah, Lilik; Purnama, I Ketut Eddy; Hariadi, Mochamad; Purnomo, Mauridhi Hery

2013-01-01

Localization is the first step in osteoarthritis (OA) classification. Manual classification, however, is time-consuming, tedious, and expensive. The proposed system is designed as decision support system for medical doctors to classify the severity of knee OA. A method has been proposed here to localize a joint space area for OA and then classify it in 4 steps to classify OA into KL-Grade 0, KL-Grade 1, KL-Grade 2, KL-Grade 3 and KL-Grade 4, which are preprocessing, segmentation, feature extraction, and classification. In this proposed system, right and left knee detection was performed by employing the Contrast-Limited Adaptive Histogram Equalization (CLAHE) and the template matching. The Gabor kernel, row sum graph and moment methods were used to localize the junction space area of knee. CLAHE is used for preprocessing step, i.e.to normalize the varied intensities. The segmentation process was conducted using the Gabor kernel, template matching, row sum graph and gray level center of mass method. Here GLCM (contrast, correlation, energy, and homogeinity) features were employed as training data. Overall, 50 data were evaluated for training and 258 data for testing. Experimental results showed the best performance by using gabor kernel with parameters α=8, θ=0, Ψ=[0 π/2], γ=0,8, N=4 and with number of iterations being 5000, momentum value 0.5 and α0=0.6 for the classification process. The run gave classification accuracy rate of 93.8% for KL-Grade 0, 70% for KL-Grade 1, 4% for KL-Grade 2, 10% for KL-Grade 3 and 88.9% for KL-Grade 4.

Osteoarthritis Classification Using Self Organizing Map Based on Gabor Kernel and Contrast-Limited Adaptive Histogram Equalization

PubMed Central

Anifah, Lilik; Purnama, I Ketut Eddy; Hariadi, Mochamad; Purnomo, Mauridhi Hery

2013-01-01

Localization is the first step in osteoarthritis (OA) classification. Manual classification, however, is time-consuming, tedious, and expensive. The proposed system is designed as decision support system for medical doctors to classify the severity of knee OA. A method has been proposed here to localize a joint space area for OA and then classify it in 4 steps to classify OA into KL-Grade 0, KL-Grade 1, KL-Grade 2, KL-Grade 3 and KL-Grade 4, which are preprocessing, segmentation, feature extraction, and classification. In this proposed system, right and left knee detection was performed by employing the Contrast-Limited Adaptive Histogram Equalization (CLAHE) and the template matching. The Gabor kernel, row sum graph and moment methods were used to localize the junction space area of knee. CLAHE is used for preprocessing step, i.e.to normalize the varied intensities. The segmentation process was conducted using the Gabor kernel, template matching, row sum graph and gray level center of mass method. Here GLCM (contrast, correlation, energy, and homogeinity) features were employed as training data. Overall, 50 data were evaluated for training and 258 data for testing. Experimental results showed the best performance by using gabor kernel with parameters α=8, θ=0, Ψ=[0 π/2], γ=0,8, N=4 and with number of iterations being 5000, momentum value 0.5 and α0=0.6 for the classification process. The run gave classification accuracy rate of 93.8% for KL-Grade 0, 70% for KL-Grade 1, 4% for KL-Grade 2, 10% for KL-Grade 3 and 88.9% for KL-Grade 4. PMID:23525188

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

PubMed

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

2016-10-01

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

Fast microcalcification detection in ultrasound images using image enhancement and threshold adjacency statistics

NASA Astrophysics Data System (ADS)

Cho, Baek Hwan; Chang, Chuho; Lee, Jong-Ha; Ko, Eun Young; Seong, Yeong Kyeong; Woo, Kyoung-Gu

2013-02-01

The existence of microcalcifications (MCs) is an important marker of malignancy in breast cancer. In spite of the benefits in mass detection for dense breasts, ultrasonography is believed that it might not reliably detect MCs. For computer aided diagnosis systems, however, accurate detection of MCs has the possibility of improving the performance in both Breast Imaging-Reporting and Data System (BI-RADS) lexicon description for calcifications and malignancy classification. We propose a new efficient and effective method for MC detection using image enhancement and threshold adjacency statistics (TAS). The main idea of TAS is to threshold an image and to count the number of white pixels with a given number of adjacent white pixels. Our contribution is to adopt TAS features and apply image enhancement to facilitate MC detection in ultrasound images. We employed fuzzy logic, tophat filter, and texture filter to enhance images for MCs. Using a total of 591 images, the classification accuracy of the proposed method in MC detection showed 82.75%, which is comparable to that of Haralick texture features (81.38%). When combined, the performance was as high as 85.11%. In addition, our method also showed the ability in mass classification when combined with existing features. In conclusion, the proposed method exploiting image enhancement and TAS features has the potential to deal with MC detection in ultrasound images efficiently and extend to the real-time localization and visualization of MCs.

Rock Mass Classification of Karstic Terrain in the Reservoir Slopes of Tekeze Hydropower Project

NASA Astrophysics Data System (ADS)

Hailemariam Gugsa, Trufat; Schneider, Jean Friedrich

2010-05-01

Hydropower reservoirs in deep gorges usually experience slope failures and mass movements. History also showed that some of these projects suffered severe landslides, which left lots of victims and enormous economic loss. Thus, it became vital to make substantial slope stability studies in such reservoirs to ensure safe project development. This study also presents a regional scale instability assessment of the Tekeze Hydropower reservoir slopes. Tekeze hydropower project is a newly constructed double arch dam that completed in August 2009. It is developed on Tekeze River, tributary of Blue Nile River that runs across the northern highlands of Ethiopia. It cuts a savage gorge 2000m deep, the deepest canyon in Africa. The dam is the highest dam in Ethiopia at 188m, 10 m higher than China's Three Gorges Dam. It is being developed by Chinese company at a cost of US350M. The reservoir is designed at 1140 m elevation, as retention level to store more than 9000 million m3 volume of water that covers an area of 150 km2, mainly in channel filling form. In this study, generation of digital elevation model from ASTER satellite imagery and surface field investigation is initially considered for further image processing and terrain parameters' analyses. Digitally processed multi spectral ASTER ortho-images drape over the DEM are used to have different three dimensional perspective views in interpreting lithological, structural and geomorphological features, which are later verified by field mapping. Terrain slopes are also delineated from the relief scene. A GIS database is ultimately developed to facilitate the delineation of geotechnical units for slope rock mass classification. Accordingly, 83 geotechnical units are delineated and, within them, 240 measurement points are established to quantify in-situ geotechnical parameters. Due to geotechnical uncertainties, four classification systems; namely geomorphic rock mass strength classification (RMS), slope mass rating (SMR), rock slope stability probability classification (SSPC) and geological strength index (GSI) are employed to classify the rock mass. The results are further compared with one another to delineate the instability conditions and produce an instability map of the reservoir slopes. Instability of the reservoir slopes is found to be mainly associated with daylighting discontinuities, thinly bedded/foliated slates, and karstified limestone. It is also noted that these features are mostly located in the regional gliding plane and shear zone, which are related with old slides scars. In general, the instabilities are found relatively far from the dam axis, in relatively less elevated and less steep slopes, which are going to be nearly covered by the impoundment; thus, they are normally expected to have less hazard in relation to the reservoir setting. Some minor failures will be generally expected during the reservoir filling.

A Characteristics-Based Approach to Radioactive Waste Classification in Advanced Nuclear Fuel Cycles

NASA Astrophysics Data System (ADS)

Djokic, Denia

The radioactive waste classification system currently used in the United States primarily relies on a source-based framework. This has lead to numerous issues, such as wastes that are not categorized by their intrinsic risk, or wastes that do not fall under a category within the framework and therefore are without a legal imperative for responsible management. Furthermore, in the possible case that advanced fuel cycles were to be deployed in the United States, the shortcomings of the source-based classification system would be exacerbated: advanced fuel cycles implement processes such as the separation of used nuclear fuel, which introduce new waste streams of varying characteristics. To be able to manage and dispose of these potential new wastes properly, development of a classification system that would assign appropriate level of management to each type of waste based on its physical properties is imperative. This dissertation explores how characteristics from wastes generated from potential future nuclear fuel cycles could be coupled with a characteristics-based classification framework. A static mass flow model developed under the Department of Energy's Fuel Cycle Research & Development program, called the Fuel-cycle Integration and Tradeoffs (FIT) model, was used to calculate the composition of waste streams resulting from different nuclear fuel cycle choices: two modified open fuel cycle cases (recycle in MOX reactor) and two different continuous-recycle fast reactor recycle cases (oxide and metal fuel fast reactors). This analysis focuses on the impact of waste heat load on waste classification practices, although future work could involve coupling waste heat load with metrics of radiotoxicity and longevity. The value of separation of heat-generating fission products and actinides in different fuel cycles and how it could inform long- and short-term disposal management is discussed. It is shown that the benefits of reducing the short-term fission-product heat load of waste destined for geologic disposal are neglected under the current source-based radioactive waste classification system, and that it is useful to classify waste streams based on how favorable the impact of interim storage is on increasing repository capacity. The need for a more diverse set of waste classes is discussed, and it is shown that the characteristics-based IAEA classification guidelines could accommodate wastes created from advanced fuel cycles more comprehensively than the U.S. classification framework.

Orbit classification in an equal-mass non-spinning binary black hole pseudo-Newtonian system

NASA Astrophysics Data System (ADS)

Zotos, Euaggelos E.; Dubeibe, Fredy L.; González, Guillermo A.

2018-07-01

The dynamics of a test particle in a non-spinning binary black hole system of equal masses is numerically investigated. The binary system is modelled in the context of the pseudo-Newtonian circular restricted three-body problem, such that the primaries are separated by a fixed distance and move in a circular orbit around each other. In particular, the Paczyński-Wiita potential is used for describing the gravitational field of the two non-Newtonian primaries. The orbital properties of the test particle are determined through the classification of the initial conditions of the orbits, using several values of the Jacobi constant, in the Hill's regions of possible motion. The initial conditions are classified into three main categories: (i) bounded, (ii) escaping, and (iii) displaying close encounters. Using the smaller alignment index chaos indicator, we further classify bounded orbits into regular, sticky, or chaotic. To gain a complete view of the dynamics of the system, we define grids of initial conditions on different types of two-dimensional planes. The orbital structure of the configuration plane, along with the corresponding distributions of the escape and collision/close encounter times, allow us to observe the transition from the classical Newtonian to the pseudo-Newtonian regime. Our numerical results reveal a strong dependence of the properties of the considered basins with the Jacobi constant as well as with the Schwarzschild radius of the black holes.

Relative scale and the strength and deformability of rock masses

NASA Astrophysics Data System (ADS)

Schultz, Richard A.

1996-09-01

The strength and deformation of rocks depend strongly on the degree of fracturing, which can be assessed in the field and related systematically to these properties. Appropriate Mohr envelopes obtained from the Rock Mass Rating (RMR) classification system and the Hoek-Brown criterion for outcrops and other large-scale exposures of fractured rocks show that rock-mass cohesive strength, tensile strength, and unconfined compressive strength can be reduced by as much as a factor often relative to values for the unfractured material. The rock-mass deformation modulus is also reduced relative to Young's modulus. A "cook-book" example illustrates the use of RMR in field applications. The smaller values of rock-mass strength and deformability imply that there is a particular scale of observation whose identification is critical to applying laboratory measurements and associated failure criteria to geologic structures.

Chemical Discrimination in Turbulent Gas Mixtures with MOX Sensors Validated by Gas Chromatography-Mass Spectrometry

PubMed Central

Fonollosa, Jordi; Rodríguez-Luján, Irene; Trincavelli, Marco; Vergara, Alexander; Huerta, Ramón

2014-01-01

Chemical detection systems based on chemo-resistive sensors usually include a gas chamber to control the sample air flow and to minimize turbulence. However, such a kind of experimental setup does not reproduce the gas concentration fluctuations observed in natural environments and destroys the spatio-temporal information contained in gas plumes. Aiming at reproducing more realistic environments, we utilize a wind tunnel with two independent gas sources that get naturally mixed along a turbulent flow. For the first time, chemo-resistive gas sensors are exposed to dynamic gas mixtures generated with several concentration levels at the sources. Moreover, the ground truth of gas concentrations at the sensor location was estimated by means of gas chromatography-mass spectrometry. We used a support vector machine as a tool to show that chemo-resistive transduction can be utilized to reliably identify chemical components in dynamic turbulent mixtures, as long as sufficient gas concentration coverage is used. We show that in open sampling systems, training the classifiers only on high concentrations of gases produces less effective classification and that it is important to calibrate the classification method with data at low gas concentrations to achieve optimal performance. PMID:25325339

Chemical discrimination in turbulent gas mixtures with MOX sensors validated by gas chromatography-mass spectrometry.

PubMed

Fonollosa, Jordi; Rodríguez-Luján, Irene; Trincavelli, Marco; Vergara, Alexander; Huerta, Ramón

2014-10-16

Chemical detection systems based on chemo-resistive sensors usually include a gas chamber to control the sample air flow and to minimize turbulence. However, such a kind of experimental setup does not reproduce the gas concentration fluctuations observed in natural environments and destroys the spatio-temporal information contained in gas plumes. Aiming at reproducing more realistic environments, we utilize a wind tunnel with two independent gas sources that get naturally mixed along a turbulent flow. For the first time, chemo-resistive gas sensors are exposed to dynamic gas mixtures generated with several concentration levels at the sources. Moreover, the ground truth of gas concentrations at the sensor location was estimated by means of gas chromatography-mass spectrometry. We used a support vector machine as a tool to show that chemo-resistive transduction can be utilized to reliably identify chemical components in dynamic turbulent mixtures, as long as sufficient gas concentration coverage is used. We show that in open sampling systems, training the classifiers only on high concentrations of gases produces less effective classification and that it is important to calibrate the classification method with data at low gas concentrations to achieve optimal performance.

Applying Data Mining Techniques to Improve Breast Cancer Diagnosis.

PubMed

Diz, Joana; Marreiros, Goreti; Freitas, Alberto

2016-09-01

In the field of breast cancer research, and more than ever, new computer aided diagnosis based systems have been developed aiming to reduce diagnostic tests false-positives. Within this work, we present a data mining based approach which might support oncologists in the process of breast cancer classification and diagnosis. The present study aims to compare two breast cancer datasets and find the best methods in predicting benign/malignant lesions, breast density classification, and even for finding identification (mass / microcalcification distinction). To carry out these tasks, two matrices of texture features extraction were implemented using Matlab, and classified using data mining algorithms, on WEKA. Results revealed good percentages of accuracy for each class: 89.3 to 64.7 % - benign/malignant; 75.8 to 78.3 % - dense/fatty tissue; 71.0 to 83.1 % - finding identification. Among the different tests classifiers, Naive Bayes was the best to identify masses texture, and Random Forests was the first or second best classifier for the majority of tested groups.

Classification of gravity-flow deposits and their significance for unconventional petroleum exploration, with a case study from the Triassic Yanchang Formation (southern Ordos Basin, China)

NASA Astrophysics Data System (ADS)

Fan, Aiping; Yang, Renchao; (Tom) van Loon, A. J.; Yin, Wei; Han, Zuozhen; Zavala, Carlos

2018-08-01

The ongoing exploration for shale oil and gas has focused sedimentological research on the transport and deposition mechanisms of fine-grained sediments, and more specifically on fine-grained mass-flow deposits. It appears, however, that no easily applicable classification scheme for gravity-flow deposits exists, and that such classifications almost exclusively deal with sandy and coarser sediments. Since the lack of a good classification system for fine-grained gravity flow deposits hampers scientific communication and understanding, we propose a classification scheme on the basis of the mud content in combination with the presumed transport mechanism. This results in twelve types of gravity-flow deposits. In order to show the practical applicability of this classification system, we apply it to the Triassic lacustrine Yanchang Formation in the southern Ordos Basin (China), which contains numerous slumps, debris-flows deposits, turbidites and hyperpycnites. The slumps and debrites occur mostly close to a delta front, and the turbidites and hyperpycnites extend over large areas from the delta slopes into the basin plain. The case study shows that (1) mud cannot only be transported but also deposited under active hydrodynamic conditions; (2) fine-grained gravity-flow constitute a significant part of the lacustrine mudstones and shales; (3) muddy gravity flows are important for the transport and deposition of clastic particles, clay minerals and organic matter, and thus are important mechanisms involved in the generation of hydrocarbons, also largely determining the reservoir capability for unconventional petroleum.

LIBS data analysis using a predictor-corrector based digital signal processor algorithm

NASA Astrophysics Data System (ADS)

Sanders, Alex; Griffin, Steven T.; Robinson, Aaron

2012-06-01

There are many accepted sensor technologies for generating spectra for material classification. Once the spectra are generated, communication bandwidth limitations favor local material classification with its attendant reduction in data transfer rates and power consumption. Transferring sensor technologies such as Cavity Ring-Down Spectroscopy (CRDS) and Laser Induced Breakdown Spectroscopy (LIBS) require effective material classifiers. A result of recent efforts has been emphasis on Partial Least Squares - Discriminant Analysis (PLS-DA) and Principle Component Analysis (PCA). Implementation of these via general purpose computers is difficult in small portable sensor configurations. This paper addresses the creation of a low mass, low power, robust hardware spectra classifier for a limited set of predetermined materials in an atmospheric matrix. Crucial to this is the incorporation of PCA or PLS-DA classifiers into a predictor-corrector style implementation. The system configuration guarantees rapid convergence. Software running on multi-core Digital Signal Processor (DSPs) simulates a stream-lined plasma physics model estimator, reducing Analog-to-Digital (ADC) power requirements. This paper presents the results of a predictorcorrector model implemented on a low power multi-core DSP to perform substance classification. This configuration emphasizes the hardware system and software design via a predictor corrector model that simultaneously decreases the sample rate while performing the classification.

Classification of Unmanned Aircraft Systems. UAS Classification/Categorization for Certification

NASA Technical Reports Server (NTRS)

2004-01-01

Category, class, and type designations are primary means to identify appropriate aircraft certification basis, operating rules/limitations, and pilot qualifications to operate in the National Airspace System (NAS). The question is whether UAS fit into existing aircraft categories or classes, or are unique enough to justify the creation of a new category/class. In addition, the characteristics or capabilities, which define when an UAS becomes a regulated aircraft, must also be decided. This issue focuses on UAS classification for certification purposes. Several approaches have been considered for classifying UAS. They basically group into either using a weight/mass basis, or a safety risk basis, factoring in the performance of the UAS, including where the UAS would operate. Under existing standards, aircraft must have a Type Certificate and Certificate of Airworthiness, in order to be used for "compensation or hire", a major difference from model aircraft. Newer technologies may make it possible for very small UAS to conduct commercial services, but that is left for a future discussion to extend the regulated aircraft to a lower level. The Access 5 position is that UAS are aircraft and should be regulated above the weight threshold differentiating them from model airplanes. The recommended classification grouping is summarized in a chart.

Clinical staging: its importance in therapeutic decisions and clinical trials.

PubMed

Denis, L J

1992-02-01

International collaboration has resulted in a revised and unified 1987 formulation for the TNM classification in solid tumors. The simplification and eliminations of most variables caused difficulties for the clinical use of the system in some tumors such as bladder cancer. The approval of the proposed adaptation covering the tumor mass, subdividing the T4 category and adapting the stage grouping, resolves these difficulties. Published reports demonstrate support for the TNM system as a clinical base for treatment decisions and prognosis. The TNMG stage and grade are important basic prognostic factors, but other prognostic factors, especially biologic tumor activity, are under clinical investigation. The TNM classification is the initial evaluation after histologic confirmation of cancer to guide treatment and prognosis. The quality of the evaluation is enhanced by precise communication on the employed methodology.

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

NASA Technical Reports Server (NTRS)

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

1994-01-01

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

Classification of mass and normal breast tissue: A convolution neural network classifier with spatial domain and texture images

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

Sahiner, B.; Chan, H.P.; Petrick, N.

1996-10-01

The authors investigated the classification of regions of interest (ROI`s) on mammograms as either mass or normal tissue using a convolution neural network (CNN). A CNN is a back-propagation neural network with two-dimensional (2-D) weight kernels that operate on images. A generalized, fast and stable implementation of the CNN was developed. The input images to the CNN were obtained form the ROI`s using two techniques. The first technique employed averaging and subsampling. The second technique employed texture feature extraction methods applied to small subregions inside the ROI. Features computed over different subregions were arranged as texture images, which were subsequentlymore » used as CNN inputs. The effects of CNN architecture and texture feature parameters on classification accuracy were studied. Receiver operating characteristic (ROC) methodology was used to evaluate the classification accuracy. A data set consisting of 168 ROI`s containing biopsy-proven masses and 504 ROI`s containing normal breast tissue was extracted from 168 mammograms by radiologists experienced in mammography. This data set was used for training and testing the CNN. With the best combination of CNN architecture and texture feature parameters, the area under the test ROC curve reached 0.87, which corresponded to a true-positive fraction of 90% at a false positive fraction of 31%. The results demonstrate the feasibility of using a CNN for classification of masses and normal tissue on mammograms.« less

Particle analysis using laser ablation mass spectroscopy

DOEpatents

Parker, Eric P.; Rosenthal, Stephen E.; Trahan, Michael W.; Wagner, John S.

2003-09-09

The present invention provides a method of quickly identifying bioaerosols by class, even if the subject bioaerosol has not been previously encountered. The method begins by collecting laser ablation mass spectra from known particles. The spectra are correlated with the known particles, including the species of particle and the classification (e.g., bacteria). The spectra can then be used to train a neural network, for example using genetic algorithm-based training, to recognize each spectra and to recognize characteristics of the classifications. The spectra can also be used in a multivariate patch algorithm. Laser ablation mass specta from unknown particles can be presented as inputs to the trained neural net for identification as to classification. The description below first describes suitable intelligent algorithms and multivariate patch algorithms, then presents an example of the present invention including results.

Evaluation of a New Ensemble Learning Framework for Mass Classification in Mammograms.

PubMed

Rahmani Seryasat, Omid; Haddadnia, Javad

2018-06-01

Mammography is the most common screening method for diagnosis of breast cancer. In this study, a computer-aided system for diagnosis of benignity and malignity of the masses was implemented in mammogram images. In the computer aided diagnosis system, we first reduce the noise in the mammograms using an effective noise removal technique. After the noise removal, the mass in the region of interest must be segmented and this segmentation is done using a deformable model. After the mass segmentation, a number of features are extracted from it. These features include: features of the mass shape and border, tissue properties, and the fractal dimension. After extracting a large number of features, a proper subset must be chosen from among them. In this study, we make use of a new method on the basis of a genetic algorithm for selection of a proper set of features. After determining the proper features, a classifier is trained. To classify the samples, a new architecture for combination of the classifiers is proposed. In this architecture, easy and difficult samples are identified and trained using different classifiers. Finally, the proposed mass diagnosis system was also tested on mini-Mammographic Image Analysis Society and digital database for screening mammography databases. The obtained results indicate that the proposed system can compete with the state-of-the-art methods in terms of accuracy. Copyright © 2017 Elsevier Inc. All rights reserved.

Detection of colorectal masses in CT colonography: application of deep residual networks for differentiating masses from normal colon anatomy

NASA Astrophysics Data System (ADS)

Näppi, Janne J.; Hironaka, Toru; Yoshida, Hiroyuki

2018-02-01

Even though the clinical consequences of a missed colorectal cancer far outweigh those of a missed polyp, there has been little work on computer-aided detection (CADe) for colorectal masses in CT colonography (CTC). One of the problems is that it is not clear how to manually design mathematical image-based features that could be used to differentiate effectively between masses and certain types of normal colon anatomy such as ileocecal valves (ICVs). Deep learning has demonstrated ability to automatically determine effective discriminating features in many image-based problems. Recently, residual networks (ResNets) were developed to address the practical problems of constructing deep network architectures for optimizing the performance of deep learning. In this pilot study, we compared the classification performance of a conventional 2D-convolutional ResNet (2D-ResNet) with that of a volumetric 3D-convolutional ResNet (3D-ResNet) in differentiating masses from normal colon anatomy in CTC. For the development and evaluation of the ResNets, 695 volumetric images of biopsy-proven colorectal masses, ICVs, haustral folds, and rectal tubes were sampled from 196 clinical CTC cases and divided randomly into independent training, validation, and test datasets. The training set was expanded by use of volumetric data augmentation. Our preliminary results on the 140 test samples indicate that it is feasible to train a deep volumetric 3D-ResNet for performing effective image-based discriminations in CTC. The 3D-ResNet slightly outperformed the 2D-ResNet in the discrimination of masses and normal colon anatomy, but the statistical difference between their very high classification accuracies was not significant. The highest classification accuracy was obtained by combining the mass-likelihood estimates of the 2D- and 3D-ResNets, which enabled correct classification of all of the masses.

The Human Skeletal Muscle Proteome Project: a reappraisal of the current literature

PubMed Central

Gonzalez‐Freire, Marta; Semba, Richard D.; Ubaida‐Mohien, Ceereena; Fabbri, Elisa; Scalzo, Paul; Højlund, Kurt; Dufresne, Craig; Lyashkov, Alexey

2016-01-01

Abstract Skeletal muscle is a large organ that accounts for up to half the total mass of the human body. A progressive decline in muscle mass and strength occurs with ageing and in some individuals configures the syndrome of ‘sarcopenia’, a condition that impairs mobility, challenges autonomy, and is a risk factor for mortality. The mechanisms leading to sarcopenia as well as myopathies are still little understood. The Human Skeletal Muscle Proteome Project was initiated with the aim to characterize muscle proteins and how they change with ageing and disease. We conducted an extensive review of the literature and analysed publically available protein databases. A systematic search of peer‐reviewed studies was performed using PubMed. Search terms included ‘human’, ‘skeletal muscle’, ‘proteome’, ‘proteomic(s)’, and ‘mass spectrometry’, ‘liquid chromatography‐mass spectrometry (LC‐MS/MS)’. A catalogue of 5431 non‐redundant muscle proteins identified by mass spectrometry‐based proteomics from 38 peer‐reviewed scientific publications from 2002 to November 2015 was created. We also developed a nosology system for the classification of muscle proteins based on localization and function. Such inventory of proteins should serve as a useful background reference for future research on changes in muscle proteome assessed by quantitative mass spectrometry‐based proteomic approaches that occur with ageing and diseases. This classification and compilation of the human skeletal muscle proteome can be used for the identification and quantification of proteins in skeletal muscle to discover new mechanisms for sarcopenia and specific muscle diseases that can be targeted for the prevention and treatment. PMID:27897395

Resolving anthropogenic aerosol pollution types - deconvolution and exploratory classification of pollution events

NASA Astrophysics Data System (ADS)

Äijälä, Mikko; Heikkinen, Liine; Fröhlich, Roman; Canonaco, Francesco; Prévôt, André S. H.; Junninen, Heikki; Petäjä, Tuukka; Kulmala, Markku; Worsnop, Douglas; Ehn, Mikael

2017-03-01

Mass spectrometric measurements commonly yield data on hundreds of variables over thousands of points in time. Refining and synthesizing this raw data into chemical information necessitates the use of advanced, statistics-based data analytical techniques. In the field of analytical aerosol chemistry, statistical, dimensionality reductive methods have become widespread in the last decade, yet comparable advanced chemometric techniques for data classification and identification remain marginal. Here we present an example of combining data dimensionality reduction (factorization) with exploratory classification (clustering), and show that the results cannot only reproduce and corroborate earlier findings, but also complement and broaden our current perspectives on aerosol chemical classification. We find that applying positive matrix factorization to extract spectral characteristics of the organic component of air pollution plumes, together with an unsupervised clustering algorithm, k-means+ + , for classification, reproduces classical organic aerosol speciation schemes. Applying appropriately chosen metrics for spectral dissimilarity along with optimized data weighting, the source-specific pollution characteristics can be statistically resolved even for spectrally very similar aerosol types, such as different combustion-related anthropogenic aerosol species and atmospheric aerosols with similar degree of oxidation. In addition to the typical oxidation level and source-driven aerosol classification, we were also able to classify and characterize outlier groups that would likely be disregarded in a more conventional analysis. Evaluating solution quality for the classification also provides means to assess the performance of mass spectral similarity metrics and optimize weighting for mass spectral variables. This facilitates algorithm-based evaluation of aerosol spectra, which may prove invaluable for future development of automatic methods for spectra identification and classification. Robust, statistics-based results and data visualizations also provide important clues to a human analyst on the existence and chemical interpretation of data structures. Applying these methods to a test set of data, aerosol mass spectrometric data of organic aerosol from a boreal forest site, yielded five to seven different recurring pollution types from various sources, including traffic, cooking, biomass burning and nearby sawmills. Additionally, three distinct, minor pollution types were discovered and identified as amine-dominated aerosols.

Classification Model for Damage Localization in a Plate Structure

NASA Astrophysics Data System (ADS)

Janeliukstis, R.; Ruchevskis, S.; Chate, A.

2018-01-01

The present study is devoted to the problem of damage localization by means of data classification. The commercial ANSYS finite-elements program was used to make a model of a cantilevered composite plate equipped with numerous strain sensors. The plate was divided into zones, and, for data classification purposes, each of them housed several points to which a point mass of magnitude 5 and 10% of plate mass was applied. At each of these points, a numerical modal analysis was performed, from which the first few natural frequencies and strain readings were extracted. The strain data for every point were the input for a classification procedure involving k nearest neighbors and decision trees. The classification model was trained and optimized by finetuning the key parameters of both algorithms. Finally, two new query points were simulated and subjected to a classification in terms of assigning a label to one of the zones of the plate, thus localizing these points. Damage localization results were compared for both algorithms and were found to be in good agreement with the actual application positions of point load.

Atmospheric pressure chemical ionisation mass spectrometry analysis linked with chemometrics for food classification - a case study: geographical provenance and cultivar classification of monovarietal clarified apple juices.

PubMed

Gan, Heng-Hui; Soukoulis, Christos; Fisk, Ian

2014-03-01

In the present work, we have evaluated for first time the feasibility of APCI-MS volatile compound fingerprinting in conjunction with chemometrics (PLS-DA) as a new strategy for rapid and non-destructive food classification. For this purpose 202 clarified monovarietal juices extracted from apples differing in their botanical and geographical origin were used for evaluation of the performance of APCI-MS as a classification tool. For an independent test set PLS-DA analyses of pre-treated spectral data gave 100% and 94.2% correct classification rate for the classification by cultivar and geographical origin, respectively. Moreover, PLS-DA analysis of APCI-MS in conjunction with GC-MS data revealed that masses within the spectral ACPI-MS data set were related with parent ions or fragments of alkyesters, carbonyl compounds (hexanal, trans-2-hexenal) and alcohols (1-hexanol, 1-butanol, cis-3-hexenol) and had significant discriminating power both in terms of cultivar and geographical origin. Copyright © 2013 The Authors. Published by Elsevier Ltd.. All rights reserved.

Rock Quality Designation (RQD) after Twenty Years.

DTIC Science & Technology

1989-02-01

strength, and seismic refraction velocity for prediction of single-tooth rippability with a D-8 dozer, all correlated by field rippability tests...Smith (1986) utilizes the RMR System to estimate rippability . Kirsten (1988) characterizes excavatability for trenching, digging, dozing, and...Lisbon, Portugal, Vol. 1, pp. II. 33 - II. 42. Smith, H.J., (1986), "Estimating Rippability by Rock Mass Classification," Proc. 27th U.S. Symposium on

Authentication of Organically and Conventionally Grown Basils by Gas Chromatography/Mass Spectrometry Chemical Profiles

PubMed Central

Wang, Zhengfang; Chen, Pei; Yu, Liangli; Harrington, Peter de B.

2013-01-01

Basil plants cultivated by organic and conventional farming practices were accurately classified by pattern recognition of gas chromatography/mass spectrometry (GC/MS) data. A novel extraction procedure was devised to extract characteristic compounds from ground basil powders. Two in-house fuzzy classifiers, i.e., the fuzzy rule-building expert system (FuRES) and the fuzzy optimal associative memory (FOAM) for the first time, were used to build classification models. Two crisp classifiers, i.e., soft independent modeling by class analogy (SIMCA) and the partial least-squares discriminant analysis (PLS-DA), were used as control methods. Prior to data processing, baseline correction and retention time alignment were performed. Classifiers were built with the two-way data sets, the total ion chromatogram representation of data sets, and the total mass spectrum representation of data sets, separately. Bootstrapped Latin partition (BLP) was used as an unbiased evaluation of the classifiers. By using two-way data sets, average classification rates with FuRES, FOAM, SIMCA, and PLS-DA were 100 ± 0%, 94.4 ± 0.4%, 93.3 ± 0.4%, and 100 ± 0%, respectively, for 100 independent evaluations. The established classifiers were used to classify a new validation set collected 2.5 months later with no parametric changes except that the training set and validation set were individually mean-centered. For the new two-way validation set, classification rates with FuRES, FOAM, SIMCA, and PLS-DA were 100%, 83%, 97%, and 100%, respectively. Thereby, the GC/MS analysis was demonstrated as a viable approach for organic basil authentication. It is the first time that a FOAM has been applied to classification. A novel baseline correction method was used also for the first time. The FuRES and the FOAM are demonstrated as powerful tools for modeling and classifying GC/MS data of complex samples and the data pretreatments are demonstrated to be useful to improve the performance of classifiers. PMID:23398171

Bacillus Classification Based on Matrix-Assisted Laser Desorption Ionization Time-of-Flight Mass Spectrometry-Effects of Culture Conditions.

PubMed

Shu, Lin-Jie; Yang, Yu-Liang

2017-11-14

Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) is a reliable and rapid technique applied widely in the identification and classification of microbes. MALDI-TOF MS has been used to identify many endospore-forming Bacillus species; however, endospores affect the identification accuracy when using MALDI-TOF MS because they change the protein composition of samples. Since culture conditions directly influence endospore formation and Bacillus growth, in this study we clarified how culture conditions influence the classification of Bacillus species by using MALDI-TOF MS. We analyzed members of the Bacillus subtilis group and Bacillus cereus group using different incubation periods, temperatures and media. Incubation period was found to affect mass spectra due to endospores which were observed mixing with vegetative cells after 24 hours. Culture temperature also resulted in different mass spectra profiles depending on the temperature best suited growth and sporulation. Conversely, the four common media for Bacillus incubation, Luria-Bertani agar, nutrient agar, plate count agar and brain-heart infusion agar did not result in any significant differences in mass spectra profiles. Profiles in the range m/z 1000-3000 were found to provide additional data to the standard ribosomal peptide/protein region m/z 3000-15000 profiles to enable easier differentiation of some highly similar species and the identification of new strains under fresh culture conditions. In summary, control of culture conditions is vital for Bacillus identification and classification by MALDI-TOF MS.

Definition and classification of cancer cachexia: an international consensus.

PubMed

Fearon, Kenneth; Strasser, Florian; Anker, Stefan D; Bosaeus, Ingvar; Bruera, Eduardo; Fainsinger, Robin L; Jatoi, Aminah; Loprinzi, Charles; MacDonald, Neil; Mantovani, Giovanni; Davis, Mellar; Muscaritoli, Maurizio; Ottery, Faith; Radbruch, Lukas; Ravasco, Paula; Walsh, Declan; Wilcock, Andrew; Kaasa, Stein; Baracos, Vickie E

2011-05-01

To develop a framework for the definition and classification of cancer cachexia a panel of experts participated in a formal consensus process, including focus groups and two Delphi rounds. Cancer cachexia was defined as a multifactorial syndrome defined by an ongoing loss of skeletal muscle mass (with or without loss of fat mass) that cannot be fully reversed by conventional nutritional support and leads to progressive functional impairment. Its pathophysiology is characterised by a negative protein and energy balance driven by a variable combination of reduced food intake and abnormal metabolism. The agreed diagnostic criterion for cachexia was weight loss greater than 5%, or weight loss greater than 2% in individuals already showing depletion according to current bodyweight and height (body-mass index [BMI] <20 kg/m(2)) or skeletal muscle mass (sarcopenia). An agreement was made that the cachexia syndrome can develop progressively through various stages--precachexia to cachexia to refractory cachexia. Severity can be classified according to degree of depletion of energy stores and body protein (BMI) in combination with degree of ongoing weight loss. Assessment for classification and clinical management should include the following domains: anorexia or reduced food intake, catabolic drive, muscle mass and strength, functional and psychosocial impairment. Consensus exists on a framework for the definition and classification of cancer cachexia. After validation, this should aid clinical trial design, development of practice guidelines, and, eventually, routine clinical management. Copyright © 2011 Elsevier Ltd. All rights reserved.

Geothermal systems: Principles and case histories

NASA Astrophysics Data System (ADS)

Rybach, L.; Muffler, L. J. P.

The classification of geothermal systems is considered along with the geophysical and geochemical signatures of geothermal systems, aspects of conductive heat transfer and regional heat flow, and geothermal anomalies and their plate tectonic framework. An investigation of convective heat and mass transfer in hydrothermal systems is conducted, taking into account the mathematical modelling of hydrothermal systems, aspects of idealized convective heat and mass transport, plausible models of geothermal reservoirs, and preproduction models of hydrothermal systems. Attention is given to the prospecting for geothermal resources, the application of water geochemistry to geothermal exploration and reservoir engineering, heat extraction from geothermal reservoirs, questions of geothermal resource assessment, and environmental aspects of geothermal energy development. A description is presented of a number of case histories, taking into account the low enthalpy geothermal resource of the Pannonian Basin in Hungary, the Krafla geothermal field in Northeast Iceland, the geothermal system of the Jemez Mountains in New Mexico, and extraction-reinjection at the Ahuachapan geothermal field in El Salvador.

Orbit classification in an equal-mass non-spinning binary black hole pseudo-Newtonian system

NASA Astrophysics Data System (ADS)

Zotos, Euaggelos E.; Dubeibe, F. L.; González, Guillermo A.

2018-04-01

The dynamics of a test particle in a non-spinning binary black hole system of equal masses is numerically investigated. The binary system is modeled in the context of the pseudo-Newtonian circular restricted three-body problem, such that the primaries are separated by a fixed distance and move in a circular orbit around each other. In particular, the Paczyński-Wiita potential is used for describing the gravitational field of the two non-Newtonian primaries. The orbital properties of the test particle are determined through the classification of the initial conditions of the orbits, using several values of the Jacobi constant, in the Hill's regions of possible motion. The initial conditions are classified into three main categories: (i) bounded, (ii) escaping and (iii) displaying close encounters. Using the smaller alignment index (SALI) chaos indicator, we further classify bounded orbits into regular, sticky or chaotic. To gain a complete view of the dynamics of the system, we define grids of initial conditions on different types of two-dimensional planes. The orbital structure of the configuration plane, along with the corresponding distributions of the escape and collision/close encounter times, allow us to observe the transition from the classical Newtonian to the pseudo-Newtonian regime. Our numerical results reveal a strong dependence of the properties of the considered basins with the Jacobi constant as well as with the Schwarzschild radius of the black holes.

The iron complex in high mass X-ray binaries

NASA Astrophysics Data System (ADS)

Giménez-García, A.; Torrejón, J. M.; Martínez-Núñez, S.; Rodes-Rocas, J. J.; Bernabéu, G.

2013-05-01

An X-ray binary system consists of a compact object (a white dwarf, a neutron star or a black hole) accreting material from an optical companion star. The spectral type of the optical component strongly affects the mass transfer to the compact object. This is the reason why X-ray binary systems are usually divided in High Mass X-ray Binaries (companion O or B type, denoted HMXB) and Low Mass X-ray Binaries (companion type A or later). The HMXB are divided depending on the partner's luminosity class in two main groups: the Supergiant X-ray Binaries (SGXB) and Be X-ray Binaries (BeXB). We introduce the spectral characterization of a sample of 9 High Mass X-ray Binaries in the iron complex (˜ 6-7 keV). This spectral range is a fundamental tool in the study of the surrounding material of these systems. The sources have been divided into three main groups according to their current standard classification: SGXB, BeXB and γ Cassiopeae-like. The purpose of this work is to look for qualitative patterns in the iron complex, around 6-7 keV, in order to discern between current different classes that make up the group of HMXB. We find significant spectral patterns for each of the sets, reflecting differences in accretion physics thereof.

Low mass companions to nearby stars: Spectral classification and its relation to the stellar/substellar break

NASA Technical Reports Server (NTRS)

Kirkpatrick, J. Davy; Mccarthy, Donald W., Jr.

1994-01-01

The relationship between mass and spectral class for main-sequence stars has never been obtained for dwarfs cooler than M6; currently, the true nature of objects classified as M7, M8, M9, or later (be they stellar or substellar) is not known. In this paper, spectral types for the components in five low mass binary systems are estimated based on previously published infrared speckle measurements, red/infrared photometry, and parallax data, together with newly acquired high signal-to-noise composite spectra of the systems and revised magnitude difference relations for M dwarfs. For two of these binaries, the secondary has a smaller mass (less than 0.09 solar mass) than any object having a dynamically measured mass and a known spectral type, thus extending the spectral class/mass relation to lower masses than has previously been possible. Data from the higher mass components (0.09 solar mass less than M less than 0.40 solar mass) are consistent with earlier results; the two lowest mass objects -- though having mass errors which could place them on either side of the M dwarf/brown dwarf dividing line (Mass is about 0.08 solar mass) -- are found to have spectral types no cooler than M6.5 V. An extrapolation of the updated spectral class/mass relation to the hydrogen-burning limit suggests that objects of type M7 and later may be substellar. Direct confirmation of this awaits the discovery of a close, very late-type binary for which dynamical masses can be measured.

Preplanetary Nebulae: A Hubble Space Telescope Imaging Survey and a New Morphological Classification System

NASA Technical Reports Server (NTRS)

Sahai, Raghvendra; Morris, Mark; Sanchez Contreras, Carmen; Claussen, Mark

2007-01-01

Using the Hubble Space Telescope (HST ), we have carried out a survey of candidate preplanetary nebulae (PPNs). We report here our discoveries of objects having well-resolved geometric structures, and we use the large sample of PPNs now imaged with HST (including previously studied objects in this class) to devise a comprehensive morphological classification system for this category of objects. The wide variety of aspherical morphologies which we have found for PPNs are qualitatively similar to those found for young planetary nebulae (PNs) in previous surveys. We also find prominent halos surrounding the central aspherical shapes in many of our objects; these are direct signatures of the undisturbed circumstellar envelopes of the progenitor AGB stars. Although the majority of these have surface brightness distributions consistent with a constant mass-loss rate with a constant expansion velocity, there are also examples of objects with varying mass-loss rates. As in our surveys of young PNs, we find no round PPNs. The similarities in morphologies between our survey objects and young PNs supports the view that the former are the progenitors of aspherical PNs. This suggests that the primary shaping of a PN does not occur during the PN phase via the fast radiative wind of the hot central star, but significantly earlier in its evolution.

Classification of Astrocytomas and Oligodendrogliomas from Mass Spectrometry Data Using Sparse Kernel Machines

PubMed Central

Huang, Jacob; Gholami, Behnood; Agar, Nathalie Y. R.; Norton, Isaiah; Haddad, Wassim M.; Tannenbaum, Allen R.

2013-01-01

Glioma histologies are the primary factor in prognostic estimates and are used in determining the proper course of treatment. Furthermore, due to the sensitivity of cranial environments, real-time tumor-cell classification and boundary detection can aid in the precision and completeness of tumor resection. A recent improvement to mass spectrometry known as desorption electrospray ionization operates in an ambient environment without the application of a preparation compound. This allows for a real-time acquisition of mass spectra during surgeries and other live operations. In this paper, we present a framework using sparse kernel machines to determine a glioma sample’s histopathological subtype by analyzing its chemical composition acquired by desorption electrospray ionization mass spectrometry. PMID:22256188

At a Loss for Words: Nosological Impotence in the Search for Justice.

PubMed

Weiss, Kenneth J

2016-03-01

The assessment and trial of Norwegian mass-murderer Anders Breivik, including disparate opinions about his sanity, raise questions about distinguishing "bad" from "mad." Although he was ultimately found criminally responsible, the tenacity and pervasiveness of his beliefs suggested delusional thinking. The author reflects on the difficulty psychiatrists have with nomenclature generally and on the application of imprecise classification to criminal justice. Ideally, a classification system should "carve nature at its joints." Barring that, psychiatry needs operational definitions to appreciate the differences between idiosyncratic, psychotic thinking, and shared subcultural beliefs or ideologies. The concept of extreme overvalued belief provides a basis for making this distinction, when applied in the criminal justice context. © 2016 American Academy of Psychiatry and the Law.

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

PubMed

Barao, Katia; Forones, Nora Manoukian

2012-01-01

The body mass index (BMI) is the most common marker used on diagnoses of the nutritional status. The great advantage of this index is the easy way to measure, the low cost, the good correlation with the fat mass and the association to morbidity and mortality. To compare the BMI differences according to the WHO, OPAS and Lipschitz classification. A prospective study on 352 patients with esophageal, gastric or colorectal cancer was done. The BMI was calculated and analyzed by the classification of WHO, Lipschitz and OPAS. The mean age was 62.1 ± 12.4 years and 59% of them had more than 59 years. The BMI had not difference between the genders in patients <59 years (P = 0.75), but over 59 years the BMI was higher in women (P<0.01). The percentage of undernourished was 7%, 18% and 21% (P<0.01) by WHO, Lipschitz and OPAS, respectively. The overweight/obesity was also different among the various classifications (P<0.01). Most of the patients with gastrointestinal cancer had more than 65 years. A different cut off must be used for this patients, because undernourished patients may be wrongly considered well nourished.

Significance and Application of Digital Breast Tomosynthesis for the BI-RADS Classification of Breast Cancer.

PubMed

Cai, Si-Qing; Yan, Jian-Xiang; Chen, Qing-Shi; Huang, Mei-Ling; Cai, Dong-Lu

2015-01-01

Full-field digital mammography (FFDM) with dense breasts has a high rate of missed diagnosis, and digital breast tomosynthesis (DBT) could reduce organization overlapping and provide more reliable images for BI-RADS classification. This study aims to explore application of COMBO (FFDM+DBT) for effect and significance of BI-RADS classification of breast cancer. In this study, we selected 832 patients who had been treated from May 2013 to November 2013. Classify FFDM and COMBO examination according to BI-RADS separately and compare the differences for glands in the image of the same patient in judgment, mass characteristics display and indirect signs. Employ Paired Wilcoxon rank sum test was used in 79 breast cancer patients to find differences between two examine methods. The results indicated that COMBO pattern is able to observe more details in distribution of glands when estimating content. Paired Wilcoxon rank sum test showed that overall classification level of COMBO is higher significantly compared to FFDM to BI-RADS diagnosis and classification of breast (P<0.05). The area under FFDM ROC curve is 0.805, while that is 0.941 in COMBO pattern. COMBO shows relation of mass with the surrounding tissues, the calcification in the mass, and multiple foci clearly in breast cancer tissues. The optimal sensitivity of cut-off value in COMBO pattern is 82.9%, which is higher than that in FFDM (60%). They share the same specificity which is both 93.2%. Digital Breast Tomosynthesis (DBT) could be used for the BI-RADS classification in breast cancer in clinical.

Optical information processing for NASA's space exploration

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin; Ochoa, Ellen; Juday, Richard

1990-01-01

The development status of optical processing techniques under development at NASA-JPL, NASA-Ames, and NASA-Johnson, is evaluated with a view to their potential applications in future NASA planetary exploration missions. It is projected that such optical processing systems can yield major reductions in mass, volume, and power requirements relative to exclusively electronic systems of comparable processing capabilities. Attention is given to high-order neural networks for distortion-invariant classification and pattern recognition, multispectral imaging using an acoustooptic tunable filter, and an optical matrix processor for control problems.

Rock flows

NASA Technical Reports Server (NTRS)

Matveyev, S. N.

1986-01-01

Rock flows are defined as forms of spontaneous mass movements, commonly found in mountainous countries, which have been studied very little. The article considers formations known as rock rivers, rock flows, boulder flows, boulder stria, gravel flows, rock seas, and rubble seas. It describes their genesis as seen from their morphological characteristics and presents a classification of these forms. This classification is based on the difference in the genesis of the rubbly matter and characterizes these forms of mass movement according to their source, drainage, and deposit areas.

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

NASA Astrophysics Data System (ADS)

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

2015-03-01

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

Multi-resolution analysis using integrated microscopic configuration with local patterns for benign-malignant mass classification

NASA Astrophysics Data System (ADS)

Rabidas, Rinku; Midya, Abhishek; Chakraborty, Jayasree; Sadhu, Anup; Arif, Wasim

2018-02-01

In this paper, Curvelet based local attributes, Curvelet-Local configuration pattern (C-LCP), is introduced for the characterization of mammographic masses as benign or malignant. Amid different anomalies such as micro- calcification, bilateral asymmetry, architectural distortion, and masses, the reason for targeting the mass lesions is due to their variation in shape, size, and margin which makes the diagnosis a challenging task. Being efficient in classification, multi-resolution property of the Curvelet transform is exploited and local information is extracted from the coefficients of each subband using Local configuration pattern (LCP). The microscopic measures in concatenation with the local textural information provide more discriminating capability than individual. The measures embody the magnitude information along with the pixel-wise relationships among the neighboring pixels. The performance analysis is conducted with 200 mammograms of the DDSM database containing 100 mass cases of each benign and malignant. The optimal set of features is acquired via stepwise logistic regression method and the classification is carried out with Fisher linear discriminant analysis. The best area under the receiver operating characteristic curve and accuracy of 0.95 and 87.55% are achieved with the proposed method, which is further compared with some of the state-of-the-art competing methods.

The BANYAN-Sigma Bayesian classifier and the search for isolated planetary-mass objects

NASA Astrophysics Data System (ADS)

Gagné, Jonathan

2018-01-01

I will present new developments in the construction of a Bayesian classification tool to identify members of 22 young associations within 150 pc from partially complete kinematic data sets such as Gaia-DR1 and DR2. The new BANYAN-Sigma tool makes it possible to quickly analyze massive data sets and yields a better classification performance than all its predecessors. It will open the door to large-scale surveys to complete the stellar and substellar populations of nearby associations, which will provide deep insights in the low-mass end of the initial mass function and valuable age-calibrated targets for exoplanet surveys.I will also presents preliminary results of a search for T-type isolated planetary-mass objects in these young associations, based on BANYAN-Sigma and a cross-match between the AllWISE and 2MASS-Reject catalogs.

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

NASA Technical Reports Server (NTRS)

Tiffany, Melissa E.; Nelson, Michael L.

1998-01-01

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

Texture analysis of common renal masses in multiple MR sequences for prediction of pathology

NASA Astrophysics Data System (ADS)

Hoang, Uyen N.; Malayeri, Ashkan A.; Lay, Nathan S.; Summers, Ronald M.; Yao, Jianhua

2017-03-01

This pilot study performs texture analysis on multiple magnetic resonance (MR) images of common renal masses for differentiation of renal cell carcinoma (RCC). Bounding boxes are drawn around each mass on one axial slice in T1 delayed sequence to use for feature extraction and classification. All sequences (T1 delayed, venous, arterial, pre-contrast phases, T2, and T2 fat saturated sequences) are co-registered and texture features are extracted from each sequence simultaneously. Random forest is used to construct models to classify lesions on 96 normal regions, 87 clear cell RCCs, 8 papillary RCCs, and 21 renal oncocytomas; ground truths are verified through pathology reports. The highest performance is seen in random forest model when data from all sequences are used in conjunction, achieving an overall classification accuracy of 83.7%. When using data from one single sequence, the overall accuracies achieved for T1 delayed, venous, arterial, and pre-contrast phase, T2, and T2 fat saturated were 79.1%, 70.5%, 56.2%, 61.0%, 60.0%, and 44.8%, respectively. This demonstrates promising results of utilizing intensity information from multiple MR sequences for accurate classification of renal masses.

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

PubMed

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

2013-12-01

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

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

PubMed

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

2016-06-13

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

Increased situation awareness in major incidents-radio frequency identification (RFID) technique: a promising tool.

PubMed

Jokela, Jorma; Rådestad, Monica; Gryth, Dan; Nilsson, Helené; Rüter, Anders; Svensson, Leif; Harkke, Ville; Luoto, Markku; Castrén, Maaret

2012-02-01

In mass-casualty situations, communications and information management to improve situational awareness is a major challenge for responders. In this study, the feasibility of a prototype system that utilizes commercially available, low-cost components, including Radio Frequency Identification (RFID) and mobile phone technology, was tested in two simulated mass-casualty incidents. The feasibility and the direct benefits of the system were evaluated in two simulated mass-casualty situations: one in Finland involving a passenger ship accident resulting in multiple drowning/hypothermia patients, and another at a major airport in Sweden using an aircraft crash scenario. Both simulations involved multiple agencies and functioned as test settings for comparing the disaster management's situational awareness with and without using the RFID-based system. Triage documentation was done using both an RFID-based system, which automatically sent the data to the Medical Command, and a traditional method using paper triage tags. The situational awareness was measured by comparing the availability of up-to date information at different points in the care chain using both systems. Information regarding the numbers and status or triage classification of the casualties was available approximately one hour earlier using the RFID system compared to the data obtained using the traditional method. The tested prototype system was quick, stable, and easy to use, and proved to work seamlessly even in harsh field conditions. It surpassed the paper-based system in all respects except simplicity of use. It also improved the general view of the mass-casualty situations, and enhanced medical emergency readiness in a multi-organizational medical setting. The tested technology is feasible in a mass-casualty incident; further development and testing should take place.

Automatic Quality Inspection of Percussion Cap Mass Production by Means of 3D Machine Vision and Machine Learning Techniques

NASA Astrophysics Data System (ADS)

Tellaeche, A.; Arana, R.; Ibarguren, A.; Martínez-Otzeta, J. M.

The exhaustive quality control is becoming very important in the world's globalized market. One of these examples where quality control becomes critical is the percussion cap mass production. These elements must achieve a minimum tolerance deviation in their fabrication. This paper outlines a machine vision development using a 3D camera for the inspection of the whole production of percussion caps. This system presents multiple problems, such as metallic reflections in the percussion caps, high speed movement of the system and mechanical errors and irregularities in percussion cap placement. Due to these problems, it is impossible to solve the problem by traditional image processing methods, and hence, machine learning algorithms have been tested to provide a feasible classification of the possible errors present in the percussion caps.

Classification of Ancient Mammal Individuals Using Dental Pulp MALDI-TOF MS Peptide Profiling

PubMed Central

Tran, Thi-Nguyen-Ny; Aboudharam, Gérard; Gardeisen, Armelle; Davoust, Bernard; Bocquet-Appel, Jean-Pierre; Flaudrops, Christophe; Belghazi, Maya; Raoult, Didier; Drancourt, Michel

2011-01-01

Background The classification of ancient animal corpses at the species level remains a challenging task for forensic scientists and anthropologists. Severe damage and mixed, tiny pieces originating from several skeletons may render morphological classification virtually impossible. Standard approaches are based on sequencing mitochondrial and nuclear targets. Methodology/Principal Findings We present a method that can accurately classify mammalian species using dental pulp and mass spectrometry peptide profiling. Our work was organized into three successive steps. First, after extracting proteins from the dental pulp collected from 37 modern individuals representing 13 mammalian species, trypsin-digested peptides were used for matrix-assisted laser desorption/ionization time-of-flight mass spectrometry analysis. The resulting peptide profiles accurately classified every individual at the species level in agreement with parallel cytochrome b gene sequencing gold standard. Second, using a 279–modern spectrum database, we blindly classified 33 of 37 teeth collected in 37 modern individuals (89.1%). Third, we classified 10 of 18 teeth (56%) collected in 15 ancient individuals representing five mammal species including human, from five burial sites dating back 8,500 years. Further comparison with an upgraded database comprising ancient specimen profiles yielded 100% classification in ancient teeth. Peptide sequencing yield 4 and 16 different non-keratin proteins including collagen (alpha-1 type I and alpha-2 type I) in human ancient and modern dental pulp, respectively. Conclusions/Significance Mass spectrometry peptide profiling of the dental pulp is a new approach that can be added to the arsenal of species classification tools for forensics and anthropology as a complementary method to DNA sequencing. The dental pulp is a new source for collagen and other proteins for the species classification of modern and ancient mammal individuals. PMID:21364886

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

NASA Astrophysics Data System (ADS)

Lin, Y.; Chen, X.

2016-12-01

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

Classification of time-of-flight secondary ion mass spectrometry spectra from complex Cu-Fe sulphides by principal component analysis and artificial neural networks.

PubMed

Kalegowda, Yogesh; Harmer, Sarah L

2013-01-08

Artificial neural network (ANN) and a hybrid principal component analysis-artificial neural network (PCA-ANN) classifiers have been successfully implemented for classification of static time-of-flight secondary ion mass spectrometry (ToF-SIMS) mass spectra collected from complex Cu-Fe sulphides (chalcopyrite, bornite, chalcocite and pyrite) at different flotation conditions. ANNs are very good pattern classifiers because of: their ability to learn and generalise patterns that are not linearly separable; their fault and noise tolerance capability; and high parallelism. In the first approach, fragments from the whole ToF-SIMS spectrum were used as input to the ANN, the model yielded high overall correct classification rates of 100% for feed samples, 88% for conditioned feed samples and 91% for Eh modified samples. In the second approach, the hybrid pattern classifier PCA-ANN was integrated. PCA is a very effective multivariate data analysis tool applied to enhance species features and reduce data dimensionality. Principal component (PC) scores which accounted for 95% of the raw spectral data variance, were used as input to the ANN, the model yielded high overall correct classification rates of 88% for conditioned feed samples and 95% for Eh modified samples. Copyright © 2012 Elsevier B.V. All rights reserved.

42 CFR 412.620 - Patient classification system.

Code of Federal Regulations, 2010 CFR

2010-10-01

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

42 CFR 412.620 - Patient classification system.

Code of Federal Regulations, 2011 CFR

2011-10-01

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

A hazard and risk classification system for catastrophic rock slope failures in Norway

NASA Astrophysics Data System (ADS)

Hermanns, R.; Oppikofer, T.; Anda, E.; Blikra, L. H.; Böhme, M.; Bunkholt, H.; Dahle, H.; Devoli, G.; Eikenæs, O.; Fischer, L.; Harbitz, C. B.; Jaboyedoff, M.; Loew, S.; Yugsi Molina, F. X.

2012-04-01

The Geological Survey of Norway carries out systematic geologic mapping of potentially unstable rock slopes in Norway that can cause a catastrophic failure. As catastrophic failure we describe failures that involve substantial fragmentation of the rock mass during run-out and that impact an area larger than that of a rock fall (shadow angle of ca. 28-32° for rock falls). This includes therefore rock slope failures that lead to secondary effects, such as a displacement wave when impacting a water body or damming of a narrow valley. Our systematic mapping revealed more than 280 rock slopes with significant postglacial deformation, which might represent localities of large future rock slope failures. This large number necessitates prioritization of follow-up activities, such as more detailed investigations, periodic monitoring and permanent monitoring and early-warning. In the past hazard and risk were assessed qualitatively for some sites, however, in order to compare sites so that political and financial decisions can be taken, it was necessary to develop a quantitative hazard and risk classification system. A preliminary classification system was presented and discussed with an expert group of Norwegian and international experts and afterwards adapted following their recommendations. This contribution presents the concept of this final hazard and risk classification that should be used in Norway in the upcoming years. Historical experience and possible future rockslide scenarios in Norway indicate that hazard assessment of large rock slope failures must be scenario-based, because intensity of deformation and present displacement rates, as well as the geological structures activated by the sliding rock mass can vary significantly on a given slope. In addition, for each scenario the run-out of the rock mass has to be evaluated. This includes the secondary effects such as generation of displacement waves or landslide damming of valleys with the potential of later outburst floods. It became obvious that large rock slope failures cannot be evaluated on a slope scale with frequency analyses of historical and prehistorical events only, as multiple rockslides have occurred within one century on a single slope that prior to the recent failures had been inactive for several thousand years. In addition, a systematic analysis on temporal distribution indicates that rockslide activity following deglaciation after the Last Glacial Maximum has been much higher than throughout the Holocene. Therefore the classification system has to be based primarily on the geological conditions on the deforming slope and on the deformation rates and only to a lesser weight on a frequency analyses. Our hazard classification therefore is primarily based on several criteria: 1) Development of the back-scarp, 2) development of the lateral release surfaces, 3) development of the potential basal sliding surface, 4) morphologic expression of the basal sliding surface, 5) kinematic feasibility tests for different displacement mechanisms, 6) landslide displacement rates, 7) change of displacement rates (acceleration), 8) increase of rockfall activity on the unstable rock slope, 9) Presence post-glacial events of similar size along the affected slope and its vicinity. For each of these criteria several conditions are possible to choose from (e.g. different velocity classes for the displacement rate criterion). A score is assigned to each condition and the sum of all scores gives the total susceptibility score. Since many of these observations are somewhat uncertain, the classification system is organized in a decision tree where probabilities can be assigned to each condition. All possibilities in the decision tree are computed and the individual probabilities giving the same total score are summed. Basic statistics show the minimum and maximum total scores of a scenario, as well as the mean and modal value. The final output is a cumulative frequency distribution of the susceptibility scores that can be divided into several classes, which are interpreted as susceptibility classes (very high, high, medium, low, and very low). Today the Norwegian Planning and Building Act uses hazard classes with annual probabilities of impact on buildings producing damages (<1/100, <1/1000, <1/5000 and zero for critical buildings). However, up to now there is not enough scientific knowledge to predict large rock slope failures in these strict classes. Therefore, the susceptibility classes will be matched with the hazard classes from the Norwegian Building Act (e.g. very high susceptibility represents the hazard class with annual probability >1/100). The risk analysis focuses on the potential fatalities of a worst case rock slide scenario and its secondary effects only and is done in consequence classes with a decimal logarithmic scale. However we recommend for all high risk objects that municipalities carry out detailed risk analyses. Finally, the hazard and risk classification system will give recommendations where surveillance in form of continuous 24/7 monitoring systems coupled with early-warning systems (high risk class) or periodic monitoring (medium risk class) should be carried out. These measures are understood as to reduce the risk of life loss due to a rock slope failure close to 0 as population can be evacuated on time if a change of stability situation occurs. The final hazard and risk classification for all potentially unstable rock slopes in Norway, including all data used for its classification will be published within the national landslide database (available on www.skrednett.no).

Excavatability and the effect of weathering degree on the excavatability of rock masses: An example from Eastern Turkey

NASA Astrophysics Data System (ADS)

Gurocak, Zulfu; Yalcin, Erkut

2016-06-01

In this study, the effect of the weathering degree on the excavatability of rock masses was investigated. The ophiolitic rock mass along the route of Komurhan Tunnel was chosen as the case study. Both laboratory and field studies were carried out for this purpose. In the first stage, the ophiolitic rock mass along the tunnel route was classified into three subzones according to the weathering degree and the ophiolitic rock masses of the each subzones were classified using the empirical excavatability classifications proposed by the different researchers. Furthermore, in-situ excavatability classes of rock masses in each zone were determined and the results were compared. The in-situ excavatability class of fresh (Zone-I) and slightly weathered (Zone-II) rock masses was determined as Blasting and that of moderately weathered (Zone-III) rock mass was determined as Very Hard/Very Difficult. As the obtained results were compared, it was found that the weathering degree has a significant effect on the excavatability and that it is more appropriate to prefer empirical classifications in the empirical determination of excavatability classes of rock masses having the same lithology by taking the weathering degree into account.

Unusual collateral vessel from right subclavian vein to left atrium, a rare complication of superior vena cava obstruction.

PubMed

Parsaee, Mozhgan; Pouraliakbar, Hamidreza; Ghadrdoost, Behshid; Moosavi, Jamal; Behjati, Mohaddeseh

2018-06-10

The most commonly reported collateral systems in the setting of superior vena cava obstruction are azygos venous system, vertebral venous system, external and internal thoracic venous system based on McLntire and Sykes classification. A 49-year-old female with renal disease complained dyspnea on exertion. Transesophageal echocardiography showed significant mitral annular calcification, large multi-lobulated mass at posterior aspect of RA, and complete obstruction of superior vena cava by thrombus formation. Computed tomography angiography showed a collateral vein to the left atrium (LA) roof. This case report is the first one which shows development of collateral vein from right subclavian to LA. © 2018 Wiley Periodicals, Inc.

Development of a Computer-Aided Diagnosis System for Early Detection of Masses Using Retrospectively Detected Cancers on Prior Mammograms

DTIC Science & Technology

2006-06-01

Hadjiiski, and N. Petrick, "Computerized nipple identification for multiple image analysis in computer-aided diagnosis," Medical Physics 31, 2871...candidates, 3 identification of suspicious objects, 4 feature extraction and analysis, and 5 FP reduc- tion by classification of normal tissue...detection of microcalcifi- cations on digitized mammograms.41 An illustration of a La- placian decomposition tree is shown on the left-hand side of Fig. 4

A discrimination model in waste plastics sorting using NIR hyperspectral imaging system.

PubMed

Zheng, Yan; Bai, Jiarui; Xu, Jingna; Li, Xiayang; Zhang, Yimin

2018-02-01

Classification of plastics is important in the recycling industry. A plastic identification model in the near infrared spectroscopy wavelength range 1000-2500 nm is proposed for the characterization and sorting of waste plastics using acrylonitrile butadiene styrene (ABS), polystyrene (PS), polypropylene (PP), polyethylene (PE), polyethylene terephthalate (PET), and polyvinyl chloride (PVC). The model is built by the feature wavelengths of standard samples applying the principle component analysis (PCA), and the accuracy, property and cross-validation of the model were analyzed. The model just contains a simple equation, center of mass coordinates, and radial distance, with which it is easy to develop classification and sorting software. A hyperspectral imaging system (HIS) with the identification model verified its practical application by using the unknown plastics. Results showed that the identification accuracy of unknown samples is 100%. All results suggested that the discrimination model was potential to an on-line characterization and sorting platform of waste plastics based on HIS. Copyright © 2017 Elsevier Ltd. All rights reserved.

The spectra of the chemically peculiar stars

NASA Astrophysics Data System (ADS)

Hack, M.

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

Metabolomics for organic food authentication: Results from a long-term field study in carrots.

PubMed

Cubero-Leon, Elena; De Rudder, Olivier; Maquet, Alain

2018-01-15

Increasing demand for organic products and their premium prices make them an attractive target for fraudulent malpractices. In this study, a large-scale comparative metabolomics approach was applied to investigate the effect of the agronomic production system on the metabolite composition of carrots and to build statistical models for prediction purposes. Orthogonal projections to latent structures-discriminant analysis (OPLS-DA) was applied successfully to predict the origin of the agricultural system of the harvested carrots on the basis of features determined by liquid chromatography-mass spectrometry. When the training set used to build the OPLS-DA models contained samples representative of each harvest year, the models were able to classify unknown samples correctly (100% correct classification). If a harvest year was left out of the training sets and used for predictions, the correct classification rates achieved ranged from 76% to 100%. The results therefore highlight the potential of metabolomic fingerprinting for organic food authentication purposes. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

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

PubMed

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

2018-04-18

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

A new texture descriptor based on local micro-pattern for detection of architectural distortion in mammographic images

NASA Astrophysics Data System (ADS)

de Oliveira, Helder C. R.; Moraes, Diego R.; Reche, Gustavo A.; Borges, Lucas R.; Catani, Juliana H.; de Barros, Nestor; Melo, Carlos F. E.; Gonzaga, Adilson; Vieira, Marcelo A. C.

2017-03-01

This paper presents a new local micro-pattern texture descriptor for the detection of Architectural Distortion (AD) in digital mammography images. AD is a subtle contraction of breast parenchyma that may represent an early sign of breast cancer. Due to its subtlety and variability, AD is more difficult to detect compared to microcalcifications and masses, and is commonly found in retrospective evaluations of false-negative mammograms. Several computer-based systems have been proposed for automatic detection of AD, but their performance are still unsatisfactory. The proposed descriptor, Local Mapped Pattern (LMP), is a generalization of the Local Binary Pattern (LBP), which is considered one of the most powerful feature descriptor for texture classification in digital images. Compared to LBP, the LMP descriptor captures more effectively the minor differences between the local image pixels. Moreover, LMP is a parametric model which can be optimized for the desired application. In our work, the LMP performance was compared to the LBP and four Haralick's texture descriptors for the classification of 400 regions of interest (ROIs) extracted from clinical mammograms. ROIs were selected and divided into four classes: AD, normal tissue, microcalcifications and masses. Feature vectors were used as input to a multilayer perceptron neural network, with a single hidden layer. Results showed that LMP is a good descriptor to distinguish AD from other anomalies in digital mammography. LMP performance was slightly better than the LBP and comparable to Haralick's descriptors (mean classification accuracy = 83%).

Comparison of Clinical and Automated Breast Density Measurements: Implications for Risk Prediction and Supplemental Screening

PubMed Central

Brandt, Kathleen R.; Scott, Christopher G.; Ma, Lin; Mahmoudzadeh, Amir P.; Jensen, Matthew R.; Whaley, Dana H.; Wu, Fang Fang; Malkov, Serghei; Hruska, Carrie B.; Norman, Aaron D.; Heine, John; Shepherd, John; Pankratz, V. Shane; Kerlikowske, Karla

2016-01-01

Purpose To compare the classification of breast density with two automated methods, Volpara (version 1.5.0; Matakina Technology, Wellington, New Zealand) and Quantra (version 2.0; Hologic, Bedford, Mass), with clinical Breast Imaging Reporting and Data System (BI-RADS) density classifications and to examine associations of these measures with breast cancer risk. Materials and Methods In this study, 1911 patients with breast cancer and 4170 control subjects matched for age, race, examination date, and mammography machine were evaluated. Participants underwent mammography at Mayo Clinic or one of four sites within the San Francisco Mammography Registry between 2006 and 2012 and provided informed consent or a waiver for research, in compliance with HIPAA regulations and institutional review board approval. Digital mammograms were retrieved a mean of 2.1 years (range, 6 months to 6 years) before cancer diagnosis, with the corresponding clinical BI-RADS density classifications, and Volpara and Quantra density estimates were generated. Agreement was assessed with weighted κ statistics among control subjects. Breast cancer associations were evaluated with conditional logistic regression, adjusted for age and body mass index. Odds ratios, C statistics, and 95% confidence intervals (CIs) were estimated. Results Agreement between clinical BI-RADS density classifications and Volpara and Quantra BI-RADS estimates was moderate, with κ values of 0.57 (95% CI: 0.55, 0.59) and 0.46 (95% CI: 0.44, 0.47), respectively. Differences of up to 14% in dense tissue classification were found, with Volpara classifying 51% of women as having dense breasts, Quantra classifying 37%, and clinical BI-RADS assessment used to classify 43%. Clinical and automated measures showed similar breast cancer associations; odds ratios for extremely dense breasts versus scattered fibroglandular densities were 1.8 (95% CI: 1.5, 2.2), 1.9 (95% CI: 1.5, 2.5), and 2.3 (95% CI: 1.9, 2.8) for Volpara, Quantra, and BI-RADS classifications, respectively. Clinical BI-RADS assessment showed better discrimination of case status (C = 0.60; 95% CI: 0.58, 0.61) than did Volpara (C = 0.58; 95% CI: 0.56, 0.59) and Quantra (C = 0.56; 95% CI: 0.54, 0.58) BI-RADS classifications. Conclusion Automated and clinical assessments of breast density are similarly associated with breast cancer risk but differ up to 14% in the classification of women with dense breasts. This could have substantial effects on clinical practice patterns. © RSNA, 2015 Online supplemental material is available for this article. PMID:26694052

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

PubMed

Park, Myoung-Ok

2017-02-01

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

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

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-26

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

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

PubMed

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

2011-01-30

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

A Neural-Network-Based Semi-Automated Geospatial Classification Tool

NASA Astrophysics Data System (ADS)

Hale, R. G.; Herzfeld, U. C.

2014-12-01

North America's largest glacier system, the Bering Bagley Glacier System (BBGS) in Alaska, surged in 2011-2013, as shown by rapid mass transfer, elevation change, and heavy crevassing. Little is known about the physics controlling surge glaciers' semi-cyclic patterns; therefore, it is crucial to collect and analyze as much data as possible so that predictive models can be made. In addition, physical signs frozen in ice in the form of crevasses may help serve as a warning for future surges. The BBGS surge provided an opportunity to develop an automated classification tool for crevasse classification based on imagery collected from small aircraft. The classification allows one to link image classification to geophysical processes associated with ice deformation. The tool uses an approach that employs geostatistical functions and a feed-forward perceptron with error back-propagation. The connectionist-geostatistical approach uses directional experimental (discrete) variograms to parameterize images into a form that the Neural Network (NN) can recognize. In an application to preform analysis on airborne video graphic data from the surge of the BBGS, an NN was able to distinguish 18 different crevasse classes with 95 percent or higher accuracy, for over 3,000 images. Recognizing that each surge wave results in different crevasse types and that environmental conditions affect the appearance in imagery, we designed the tool's semi-automated pre-training algorithm to be adaptable. The tool can be optimized to specific settings and variables of image analysis: (airborne and satellite imagery, different camera types, observation altitude, number and types of classes, and resolution). The generalization of the classification tool brings three important advantages: (1) multiple types of problems in geophysics can be studied, (2) the training process is sufficiently formalized to allow non-experts in neural nets to perform the training process, and (3) the time required to manually pre-sort imagery into classes is greatly reduced.

Evolutionary pruning of transfer learned deep convolutional neural network for breast cancer diagnosis in digital breast tomosynthesis.

PubMed

Samala, Ravi K; Chan, Heang-Ping; Hadjiiski, Lubomir M; Helvie, Mark A; Richter, Caleb; Cha, Kenny

2018-05-01

Deep learning models are highly parameterized, resulting in difficulty in inference and transfer learning for image recognition tasks. In this work, we propose a layered pathway evolution method to compress a deep convolutional neural network (DCNN) for classification of masses in digital breast tomosynthesis (DBT). The objective is to prune the number of tunable parameters while preserving the classification accuracy. In the first stage transfer learning, 19 632 augmented regions-of-interest (ROIs) from 2454 mass lesions on mammograms were used to train a pre-trained DCNN on ImageNet. In the second stage transfer learning, the DCNN was used as a feature extractor followed by feature selection and random forest classification. The pathway evolution was performed using genetic algorithm in an iterative approach with tournament selection driven by count-preserving crossover and mutation. The second stage was trained with 9120 DBT ROIs from 228 mass lesions using leave-one-case-out cross-validation. The DCNN was reduced by 87% in the number of neurons, 34% in the number of parameters, and 95% in the number of multiply-and-add operations required in the convolutional layers. The test AUC on 89 mass lesions from 94 independent DBT cases before and after pruning were 0.88 and 0.90, respectively, and the difference was not statistically significant (p  >  0.05). The proposed DCNN compression approach can reduce the number of required operations by 95% while maintaining the classification performance. The approach can be extended to other deep neural networks and imaging tasks where transfer learning is appropriate.

Evolutionary pruning of transfer learned deep convolutional neural network for breast cancer diagnosis in digital breast tomosynthesis

NASA Astrophysics Data System (ADS)

Samala, Ravi K.; Chan, Heang-Ping; Hadjiiski, Lubomir M.; Helvie, Mark A.; Richter, Caleb; Cha, Kenny

2018-05-01

Deep learning models are highly parameterized, resulting in difficulty in inference and transfer learning for image recognition tasks. In this work, we propose a layered pathway evolution method to compress a deep convolutional neural network (DCNN) for classification of masses in digital breast tomosynthesis (DBT). The objective is to prune the number of tunable parameters while preserving the classification accuracy. In the first stage transfer learning, 19 632 augmented regions-of-interest (ROIs) from 2454 mass lesions on mammograms were used to train a pre-trained DCNN on ImageNet. In the second stage transfer learning, the DCNN was used as a feature extractor followed by feature selection and random forest classification. The pathway evolution was performed using genetic algorithm in an iterative approach with tournament selection driven by count-preserving crossover and mutation. The second stage was trained with 9120 DBT ROIs from 228 mass lesions using leave-one-case-out cross-validation. The DCNN was reduced by 87% in the number of neurons, 34% in the number of parameters, and 95% in the number of multiply-and-add operations required in the convolutional layers. The test AUC on 89 mass lesions from 94 independent DBT cases before and after pruning were 0.88 and 0.90, respectively, and the difference was not statistically significant (p  >  0.05). The proposed DCNN compression approach can reduce the number of required operations by 95% while maintaining the classification performance. The approach can be extended to other deep neural networks and imaging tasks where transfer learning is appropriate.

How a national vegetation classification can help ecological research and management

Treesearch

Scott Franklin; Patrick Comer; Julie Evens; Exequiel Ezcurra; Don Faber-Langendoen; Janet Franklin; Michael Jennings; Carmen Josse; Chris Lea; Orie Loucks; Esteban Muldavin; Robert Peet; Serguei Ponomarenko; David Roberts; Ayzik Solomeshch; Todd Keeler-Wolf; James Van Kley; Alan Weakley; Alexa McKerrow; Marianne Burke; Carol Spurrier

2015-01-01

The elegance of classification lies in its ability to compile and systematize various terminological conventions and masses of information that are unattainable during typical research projects. Imagine a discipline without standards for collection, analysis, and interpretation; unfortunately, that describes much of 20th-century vegetation ecology.

Galaxy Zoo: Morphological Classification of Galaxy Images from the Illustris  Simulation

NASA Astrophysics Data System (ADS)

Dickinson, Hugh; Fortson, Lucy; Lintott, Chris; Scarlata, Claudia; Willett, Kyle; Bamford, Steven; Beck, Melanie; Cardamone, Carolin; Galloway, Melanie; Simmons, Brooke; Keel, William; Kruk, Sandor; Masters, Karen; Vogelsberger, Mark; Torrey, Paul; Snyder, Gregory F.

2018-02-01

Modern large-scale cosmological simulations model the universe with increasing sophistication and at higher spatial and temporal resolutions. These ongoing enhancements permit increasingly detailed comparisons between the simulation outputs and real observational data. Recent projects such as Illustris are capable of producing simulated images that are designed to be comparable to those obtained from local surveys. This paper tests the degree to which Illustris achieves this goal across a diverse population of galaxies using visual morphologies derived from Galaxy Zoo citizen scientists. Morphological classifications provided by these volunteers for simulated galaxies are compared with similar data for a compatible sample of images drawn from the Sloan Digital Sky Survey (SDSS) Legacy Survey. This paper investigates how simple morphological characterization by human volunteers asked to distinguish smooth from featured systems differs between simulated and real galaxy images. Significant differences are identified, which are most likely due to the limited resolution of the simulation, but which could be revealing real differences in the dynamical evolution of populations of galaxies in the real and model universes. Specifically, for stellar masses {M}\\star ≲ {10}11 {M}ȯ , a substantially larger proportion of Illustris galaxies that exhibit disk-like morphology or visible substructure, relative to their SDSS counterparts. Toward higher masses, the visual morphologies for simulated and observed galaxies converge and exhibit similar distributions. The stellar mass threshold indicated by this divergent behavior confirms recent works using parametric measures of morphology from Illustris simulated images. When {M}\\star ≳ {10}11 {M}ȯ , the Illustris data set contains substantially fewer galaxies that classifiers regard as unambiguously featured. In combination, these results suggest that comparison between the detailed properties of observed and simulated galaxies, even when limited to reasonably massive systems, may be misleading.

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

PubMed

Strudwick, Gillian; Hardiker, Nicholas R

2016-10-01

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

Quality classification of Spanish olive oils by untargeted gas chromatography coupled to hybrid quadrupole-time of flight mass spectrometry with atmospheric pressure chemical ionization and metabolomics-based statistical approach.

PubMed

Sales, C; Cervera, M I; Gil, R; Portolés, T; Pitarch, E; Beltran, J

2017-02-01

The novel atmospheric pressure chemical ionization (APCI) source has been used in combination with gas chromatography (GC) coupled to hybrid quadrupole time-of-flight (QTOF) mass spectrometry (MS) for determination of volatile components of olive oil, enhancing its potential for classification of olive oil samples according to their quality using a metabolomics-based approach. The full-spectrum acquisition has allowed the detection of volatile organic compounds (VOCs) in olive oil samples, including Extra Virgin, Virgin and Lampante qualities. A dynamic headspace extraction with cartridge solvent elution was applied. The metabolomics strategy consisted of three different steps: a full mass spectral alignment of GC-MS data using MzMine 2.0, a multivariate analysis using Ez-Info and the creation of the statistical model with combinations of responses for molecular fragments. The model was finally validated using blind samples, obtaining an accuracy in oil classification of 70%, taking the official established method, "PANEL TEST", as reference. Copyright © 2016 Elsevier Ltd. All rights reserved.

Using transfer learning to detect galaxy mergers

NASA Astrophysics Data System (ADS)

Ackermann, Sandro; Schawinksi, Kevin; Zhang, Ce; Weigel, Anna K.; Turp, M. Dennis

2018-05-01

We investigate the use of deep convolutional neural networks (deep CNNs) for automatic visual detection of galaxy mergers. Moreover, we investigate the use of transfer learning in conjunction with CNNs, by retraining networks first trained on pictures of everyday objects. We test the hypothesis that transfer learning is useful for improving classification performance for small training sets. This would make transfer learning useful for finding rare objects in astronomical imaging datasets. We find that these deep learning methods perform significantly better than current state-of-the-art merger detection methods based on nonparametric systems like CAS and GM20. Our method is end-to-end and robust to image noise and distortions; it can be applied directly without image preprocessing. We also find that transfer learning can act as a regulariser in some cases, leading to better overall classification accuracy (p = 0.02). Transfer learning on our full training set leads to a lowered error rate from 0.0381 down to 0.0321, a relative improvement of 15%. Finally, we perform a basic sanity-check by creating a merger sample with our method, and comparing with an already existing, manually created merger catalogue in terms of colour-mass distribution and stellar mass function.

Silesia Dryvit

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

Presz, K.

1995-12-31

MT International, as a manufacturer and distributor for of US company named Dryvit Systems is focused on weatherization techniques as well as on facade and external wall finishing. The materials manufactured by Dryvit for building and construction purposes (plaster masses, building binders, insulating materials, reinforced fabric, etc.) are used at many sites. The consistent and well-selected composition of these materials guarantees highest quality of facade finishing in building structures of any type. The first implementation of Dryvit system in Warsaw was completed in 1974 and it remains the first exampled of professionally weatherized building in Poland. Different versions of Dryvitmore » system have been elaborated for various plaster base types. Consequently the assembling procedure differs, too. The main classification includes methods used directly on-site by a specialized contractor as well as prefabrication systems in which the ready-made elements prefabricated in a central plant or in a moveable unit are mounted on the walls. Distribution of materials and systems is based upon a network of branch offices and plaster mass mixter plants located in Warsaw, Szczecin, Lublin, Gdansk and Zabrze.« less

A complete solution classification and unified algorithmic treatment for the one- and two-step asymmetric S-transverse mass event scale statistic

NASA Astrophysics Data System (ADS)

Walker, Joel W.

2014-08-01

The M T2, or "s-transverse mass", statistic was developed to associate a parent mass scale to a missing transverse energy signature, given that escaping particles are generally expected in pairs, while collider experiments are sensitive to just a single transverse momentum vector sum. This document focuses on the generalized extension of that statistic to asymmetric one- and two-step decay chains, with arbitrary child particle masses and upstream missing transverse momentum. It provides a unified theoretical formulation, complete solution classification, taxonomy of critical points, and technical algorithmic prescription for treatment of the event scale. An implementation of the described algorithm is available for download, and is also a deployable component of the author's selection cut software package AEAC uS (Algorithmic Event Arbiter and C ut Selector). appendices address combinatoric event assembly, algorithm validation, and a complete pseudocode.

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

Treesearch

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

1991-01-01

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

High Throughput Ambient Mass Spectrometric Approach to Species Identification and Classification from Chemical Fingerprint Signatures

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

Musah, Rabi A.; Espinoza, Edgard O.; Cody, Robert B.

A high throughput method for species identification and classification through chemometric processing of direct analysis in real time (DART) mass spectrometry-derived fingerprint signatures has been developed. The method entails introduction of samples to the open air space between the DART ion source and the mass spectrometer inlet, with the entire observed mass spectral fingerprint subjected to unsupervised hierarchical clustering processing. Moreover, a range of both polar and non-polar chemotypes are instantaneously detected. The result is identification and species level classification based on the entire DART-MS spectrum. In this paper, we illustrate how the method can be used to: (1) distinguishmore » between endangered woods regulated by the Convention for the International Trade of Endangered Flora and Fauna (CITES) treaty; (2) assess the origin and by extension the properties of biodiesel feedstocks; (3) determine insect species from analysis of puparial casings; (4) distinguish between psychoactive plants products; and (5) differentiate between Eucalyptus species. An advantage of the hierarchical clustering approach to processing of the DART-MS derived fingerprint is that it shows both similarities and differences between species based on their chemotypes. Furthermore, full knowledge of the identities of the constituents contained within the small molecule profile of analyzed samples is not required.« less

High Throughput Ambient Mass Spectrometric Approach to Species Identification and Classification from Chemical Fingerprint Signatures

DOE PAGES

Musah, Rabi A.; Espinoza, Edgard O.; Cody, Robert B.; ...

2015-07-09

A high throughput method for species identification and classification through chemometric processing of direct analysis in real time (DART) mass spectrometry-derived fingerprint signatures has been developed. The method entails introduction of samples to the open air space between the DART ion source and the mass spectrometer inlet, with the entire observed mass spectral fingerprint subjected to unsupervised hierarchical clustering processing. Moreover, a range of both polar and non-polar chemotypes are instantaneously detected. The result is identification and species level classification based on the entire DART-MS spectrum. In this paper, we illustrate how the method can be used to: (1) distinguishmore » between endangered woods regulated by the Convention for the International Trade of Endangered Flora and Fauna (CITES) treaty; (2) assess the origin and by extension the properties of biodiesel feedstocks; (3) determine insect species from analysis of puparial casings; (4) distinguish between psychoactive plants products; and (5) differentiate between Eucalyptus species. An advantage of the hierarchical clustering approach to processing of the DART-MS derived fingerprint is that it shows both similarities and differences between species based on their chemotypes. Furthermore, full knowledge of the identities of the constituents contained within the small molecule profile of analyzed samples is not required.« less

A High Throughput Ambient Mass Spectrometric Approach to Species Identification and Classification from Chemical Fingerprint Signatures

PubMed Central

Musah, Rabi A.; Espinoza, Edgard O.; Cody, Robert B.; Lesiak, Ashton D.; Christensen, Earl D.; Moore, Hannah E.; Maleknia, Simin; Drijfhout, Falko P.

2015-01-01

A high throughput method for species identification and classification through chemometric processing of direct analysis in real time (DART) mass spectrometry-derived fingerprint signatures has been developed. The method entails introduction of samples to the open air space between the DART ion source and the mass spectrometer inlet, with the entire observed mass spectral fingerprint subjected to unsupervised hierarchical clustering processing. A range of both polar and non-polar chemotypes are instantaneously detected. The result is identification and species level classification based on the entire DART-MS spectrum. Here, we illustrate how the method can be used to: (1) distinguish between endangered woods regulated by the Convention for the International Trade of Endangered Flora and Fauna (CITES) treaty; (2) assess the origin and by extension the properties of biodiesel feedstocks; (3) determine insect species from analysis of puparial casings; (4) distinguish between psychoactive plants products; and (5) differentiate between Eucalyptus species. An advantage of the hierarchical clustering approach to processing of the DART-MS derived fingerprint is that it shows both similarities and differences between species based on their chemotypes. Furthermore, full knowledge of the identities of the constituents contained within the small molecule profile of analyzed samples is not required. PMID:26156000

A High Throughput Ambient Mass Spectrometric Approach to Species Identification and Classification from Chemical Fingerprint Signatures

NASA Astrophysics Data System (ADS)

Musah, Rabi A.; Espinoza, Edgard O.; Cody, Robert B.; Lesiak, Ashton D.; Christensen, Earl D.; Moore, Hannah E.; Maleknia, Simin; Drijfhout, Falko P.

2015-07-01

A high throughput method for species identification and classification through chemometric processing of direct analysis in real time (DART) mass spectrometry-derived fingerprint signatures has been developed. The method entails introduction of samples to the open air space between the DART ion source and the mass spectrometer inlet, with the entire observed mass spectral fingerprint subjected to unsupervised hierarchical clustering processing. A range of both polar and non-polar chemotypes are instantaneously detected. The result is identification and species level classification based on the entire DART-MS spectrum. Here, we illustrate how the method can be used to: (1) distinguish between endangered woods regulated by the Convention for the International Trade of Endangered Flora and Fauna (CITES) treaty; (2) assess the origin and by extension the properties of biodiesel feedstocks; (3) determine insect species from analysis of puparial casings; (4) distinguish between psychoactive plants products; and (5) differentiate between Eucalyptus species. An advantage of the hierarchical clustering approach to processing of the DART-MS derived fingerprint is that it shows both similarities and differences between species based on their chemotypes. Furthermore, full knowledge of the identities of the constituents contained within the small molecule profile of analyzed samples is not required.

Joint passive radar tracking and target classification using radar cross section

NASA Astrophysics Data System (ADS)

Herman, Shawn M.

2004-01-01

We present a recursive Bayesian solution for the problem of joint tracking and classification of airborne targets. In our system, we allow for complications due to multiple targets, false alarms, and missed detections. More importantly, though, we utilize the full benefit of a joint approach by implementing our tracker using an aerodynamically valid flight model that requires aircraft-specific coefficients such as wing area and vehicle mass, which are provided by our classifier. A key feature that bridges the gap between tracking and classification is radar cross section (RCS). By modeling the true deterministic relationship that exists between RCS and target aspect, we are able to gain both valuable class information and an estimate of target orientation. However, the lack of a closed-form relationship between RCS and target aspect prevents us from using the Kalman filter or its variants. Instead, we rely upon a sequential Monte Carlo-based approach known as particle filtering. In addition to allowing us to include RCS as a measurement, the particle filter also simplifies the implementation of our nonlinear non-Gaussian flight model.

Joint passive radar tracking and target classification using radar cross section

NASA Astrophysics Data System (ADS)

Herman, Shawn M.

2003-12-01

We present a recursive Bayesian solution for the problem of joint tracking and classification of airborne targets. In our system, we allow for complications due to multiple targets, false alarms, and missed detections. More importantly, though, we utilize the full benefit of a joint approach by implementing our tracker using an aerodynamically valid flight model that requires aircraft-specific coefficients such as wing area and vehicle mass, which are provided by our classifier. A key feature that bridges the gap between tracking and classification is radar cross section (RCS). By modeling the true deterministic relationship that exists between RCS and target aspect, we are able to gain both valuable class information and an estimate of target orientation. However, the lack of a closed-form relationship between RCS and target aspect prevents us from using the Kalman filter or its variants. Instead, we rely upon a sequential Monte Carlo-based approach known as particle filtering. In addition to allowing us to include RCS as a measurement, the particle filter also simplifies the implementation of our nonlinear non-Gaussian flight model.

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

PubMed

Fesharaki, Nooshin Jafari; Pourghassem, Hossein

2013-07-01

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

A rare cause of childhood renal cysts: Xp11.2 translocation renal cell carcinoma

PubMed Central

Taşkınlar, Hakan; Avlan, Dinçer; Çıtak, Çağlar; Polat, Ayşe; Naycı, Ali

2015-01-01

Pediatric renal cysts are rare, usually asymptomatic and incidentally detected in children. Cyst associated renal cell carcinoma (RCC) or cystic RCC is extremely rare in children. Bosniak classification system has been accepted for the management of cystic renal masses. Xp11.2 translocation RCC is a recently classified distinct subtype and usually affects children and adolescents. We report the case of a 10-year-old girl with Xp11.2 translocation RCC from a cyst of the right kidney. PMID:25624966

A rare cause of childhood renal cysts: Xp11.2 translocation renal cell carcinoma.

PubMed

Taşkınlar, Hakan; Avlan, Dinçer; Çıtak, Çağlar; Polat, Ayşe; Naycı, Ali

2015-01-01

Pediatric renal cysts are rare, usually asymptomatic and incidentally detected in children. Cyst associated renal cell carcinoma (RCC) or cystic RCC is extremely rare in children. Bosniak classification system has been accepted for the management of cystic renal masses. Xp11.2 translocation RCC is a recently classified distinct subtype and usually affects children and adolescents. We report the case of a 10-year-old girl with Xp11.2 translocation RCC from a cyst of the right kidney.

Correlation of Mass Spectrometry Identified Bacterial Biomarkers From a Fielded Pyrolysis-Gas Chromatography-Ion Mobility Spectrometry Biodetector With the Microbiological Gram Stain Classification Scheme

DTIC Science & Technology

2005-09-01

Escherichia coliphage virus, and ovalbumnin (OV) protein species. The work suggests certain improvements that can be made to the IMS detection System...Escherichia coliphage virus, and ovalbumin (OV) protein species. However, the origin and structural identities of the pyrolyzate peaks observed in the GC-IMS...niger), Gram-negative Pantoea agglomerans ((EH) formerly Erwinia herbicola ), ovalbumin protein (OV), and the MS-2 Escherichia coliphage virus were

42 CFR 412.513 - Patient classification system.

Code of Federal Regulations, 2010 CFR

2010-10-01

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

42 CFR 412.513 - Patient classification system.

Code of Federal Regulations, 2011 CFR

2011-10-01

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

Proposal for a bariatric mortality risk classification system for patients undergoing bariatric surgery.

PubMed

Nguyen, Ninh T; Nguyen, Brian; Smith, Brian; Reavis, Kevin M; Elliott, Christian; Hohmann, Samuel

2013-01-01

An obesity surgery mortality risk score derived from a single clinical series can be used to stratify the mortality risk of patients undergoing gastric bypass. However, such a scoring system does not take into account 2 important factors in contemporary bariatric surgery--increased use of the laparoscopic approach and laparoscopic adjustable gastric banding. The present study analyzed the preoperative factors that might predict in-hospital mortality after bariatric surgery using data from academic medical centers and proposes a classification system for predicting mortality. Using the "International Classification of Diseases, 9th revision," diagnosis and procedural codes, the data for all patients who underwent bariatric surgery for the treatment of morbid obesity from 2002 to 2009 were obtained from the University HealthSystem Consortium database. The limitations of this database included the lack of the body mass index and the underestimation of some co-morbidities, such as sleep apnea. Multiple regression analyses were performed to determine the factors predictive of greater in-hospital mortality. The factors examined included race, gender, age, co-morbidities, surgical technique (laparoscopic versus open), bariatric operation (gastric bypass versus nongastric bypass), and payer type. A scoring system was devised by assigning 1 point for each major factor (those with an adjusted odds ratio [AOR] of ≥2.0) and .5 point for each minor factor (those with an AOR <2.0). Using contemporary data from 2007 to 2009, the in-hospital mortality was analyzed according to the classification: class I, 0-0.5 point; class II, 1.0-1.5 points; class III, 2.0-3.0 points; and class IV, ≥3.5 points. During the 8-year period, 105,287 patients underwent bariatric surgery. The operations included laparoscopic gastric bypass (45%), open gastric bypass (41%), and laparoscopic gastric banding or gastroplasty (14%). The overall in-hospital mortality rate was .17%. The number of deaths per 1000 bariatric operations decreased from 4.0 in 2002 to .6 in 2009. Using regression analyses, the factors predictive of greater in-hospital mortality were male gender (AOR 3.2), gastric bypass procedure (AOR 5.8), open surgical technique (AOR 4.8), Medicare payer (AOR 3.0), diabetes (AOR 1.6), and age >60 years (AOR 1.9). The mortality rate was .10% for class I patients, .15% for class II, .33% for class III, and .70% for class IV (P < .05 among all classes). Within the context of academic centers, the mortality after bariatric surgery has decreased substantially since 2002, with an increase in the use of the laparoscopic technique and laparoscopic gastric banding. A bariatric mortality risk classification system was developed to stratify mortality, given the limits of this database, which does not include the body mass index and underestimates the incidence of sleep apnea. It might be useful to aid surgeons in surgical decision-making, to inform patients of their risks, and for quality improvement reporting purposes. Copyright © 2013 American Society for Metabolic and Bariatric Surgery. Published by Elsevier Inc. All rights reserved.

Qualitative stability assessment of cut slopes along the National Highway-05 around Jhakri area, Himachal Pradesh, India

NASA Astrophysics Data System (ADS)

Kundu, Jagadish; Sarkar, Kripamoy; Tripathy, Ashutosh; Singh, T. N.

2017-12-01

Several deformation phases in tectonically active Himalayas have rendered the rock masses very complex in terms of structure, lithology and degree of metamorphism. Again, anthropogenic activities such as roads, tunnels and other civil engineering constructions have led to a state of disequilibrium which in many cases, results in failure of rock masses. National Highway-05 around Jhakri area in India is a major connecting route to the China border in the hilly terrains of the state Himachal Pradesh. It cuts through the Himalayan rocks and has a hazardous history of landslides destroying human lives and interrupting communication very frequently. As a contribution towards the mitigation process, a study has been carried out along the highway to analyse kinematic stability and qualitative estimation of rock mass condition through rock mass classification systems. The kinematic analysis shows that the rock slopes are prone to planar and wedge failure. Rock mass rating for most of the locations lies between 7 and 34, representing a poor rock mass quality (Class IV), whereas slope mass rating is more disperse and ranges from 11 to 52 for most of the slopes (Class III, IV and V).

A Pan-STARRS1 Proper-Motion Survey for Young Brown Dwarfs in the Nearest Star-Forming Regions and a Reddening-Free Classification Method for Ultracool Dwarfs

NASA Astrophysics Data System (ADS)

Zhang, Zhoujian; Liu, Michael C.; Best, William M. J.; Magnier, Eugene; Aller, Kimberly

2018-01-01

Young brown dwarfs are of prime importance to investigate the universality of the initial mass function (IMF). Based on photometry and proper motions from the Pan-STARRS1 (PS1) 3π survey, we are conducting the widest and deepest brown dwarf survey in the nearby star-forming regions, Taurus–Auriga (Taurus) and Upper Scorpius (USco). Our work is the first to measure proper motions, a robust proxy of membership, for brown dwarf candidates in Taurus and USco over such a large area and long time baseline (≈ 15 year) with such high precision (≈ 4 mas yr-1). Since extinction complicates spectral classification, we have developed a new approach to quantitatively determine reddening-free spectral types, extinctions, and gravity classifications for mid-M to late-L ultracool dwarfs (≈ 100–5 MJup), using low-resolution near-infrared spectra. So far, our IRTF/SpeX spectroscopic follow-up has increased the substellar and planetary-mass census of Taurus by ≈ 50% and almost doubled the substellar census of USco, constituting the largest single increases of brown dwarfs and free-floating planets found in both regions to date. Most notably, our new discoveries reveal an older (> 10 Myr) low-mass population in Taurus, in accord with recent studies of the higher-mass stellar members. In addition, the mass function appears to differ between the younger and older Taurus populations, possibly due to incompleteness of the older stellar members or different star formation processes. Upon completion, our survey will establish the most complete substellar and planetary-mass census in both Taurus and USco associations, make a significant addition to the low-mass IMF in both regions, and deliver more comprehensive pictures of star formation histories.

Bayesian Integration and Classification of Composition C-4 Plastic Explosives Based on Time-of-Flight-Secondary Ion Mass Spectrometry and Laser Ablation-Inductively Coupled Plasma Mass Spectrometry.

PubMed

Mahoney, Christine M; Kelly, Ryan T; Alexander, Liz; Newburn, Matt; Bader, Sydney; Ewing, Robert G; Fahey, Albert J; Atkinson, David A; Beagley, Nathaniel

2016-04-05

Time-of-flight-secondary ion mass spectrometry (TOF-SIMS) and laser ablation-inductively coupled plasma mass spectrometry (LA-ICPMS) were used for characterization and identification of unique signatures from a series of 18 Composition C-4 plastic explosives. The samples were obtained from various commercial and military sources around the country. Positive and negative ion TOF-SIMS data were acquired directly from the C-4 residue on Si surfaces, where the positive ion mass spectra obtained were consistent with the major composition of organic additives, and the negative ion mass spectra were more consistent with explosive content in the C-4 samples. Each series of mass spectra was subjected to partial least squares-discriminant analysis (PLS-DA), a multivariate statistical analysis approach which serves to first find the areas of maximum variance within different classes of C-4 and subsequently to classify unknown samples based on correlations between the unknown data set and the original data set (often referred to as a training data set). This method was able to successfully classify test samples of C-4, though with a limited degree of certainty. The classification accuracy of the method was further improved by integrating the positive and negative ion data using a Bayesian approach. The TOF-SIMS data was combined with a second analytical method, LA-ICPMS, which was used to analyze elemental signatures in the C-4. The integrated data were able to classify test samples with a high degree of certainty. Results indicate that this Bayesian integrated approach constitutes a robust classification method that should be employable even in dirty samples collected in the field.

MALDI Mass Spectrometry Imaging: A Novel Tool for the Identification and Classification of Amyloidosis.

PubMed

Winter, Martin; Tholey, Andreas; Kristen, Arnt; Röcken, Christoph

2017-11-01

Amyloidosis is a group of diseases caused by extracellular accumulation of fibrillar polypeptide aggregates. So far, diagnosis is performed by Congo red staining of tissue sections in combination with polarization microscopy. Subsequent identification of the causative protein by immunohistochemistry harbors some difficulties regarding sensitivity and specificity. Mass spectrometry based approaches have been demonstrated to constitute a reliable method to supplement typing of amyloidosis, but still depend on Congo red staining. In the present study, we used matrix-assisted laser desorption/ionization mass spectrometry imaging coupled with ion mobility separation (MALDI-IMS MSI) to investigate amyloid deposits in formalin-fixed and paraffin-embedded tissue samples. Utilizing a novel peptide filter method, we found a universal peptide signature for amyloidoses. Furthermore, differences in the peptide composition of ALλ and ATTR amyloid were revealed and used to build a reliable classification model. Integrating the peptide filter in MALDI-IMS MSI analysis, we developed a bioinformatics workflow facilitating the identification and classification of amyloidosis in a less time and sample-consuming experimental setup. Our findings demonstrate also the feasibility to investigate the amyloid's protein composition, thus paving the way to establish classification models for the diverse types of amyloidoses and to shed further light on the complex process of amyloidogenesis. © 2017 The Authors, Proteomics Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Comparative evaluation of support vector machine classification for computer aided detection of breast masses in mammography

NASA Astrophysics Data System (ADS)

Lesniak, J. M.; Hupse, R.; Blanc, R.; Karssemeijer, N.; Székely, G.

2012-08-01

False positive (FP) marks represent an obstacle for effective use of computer-aided detection (CADe) of breast masses in mammography. Typically, the problem can be approached either by developing more discriminative features or by employing different classifier designs. In this paper, the usage of support vector machine (SVM) classification for FP reduction in CADe is investigated, presenting a systematic quantitative evaluation against neural networks, k-nearest neighbor classification, linear discriminant analysis and random forests. A large database of 2516 film mammography examinations and 73 input features was used to train the classifiers and evaluate for their performance on correctly diagnosed exams as well as false negatives. Further, classifier robustness was investigated using varying training data and feature sets as input. The evaluation was based on the mean exam sensitivity in 0.05-1 FPs on normals on the free-response receiver operating characteristic curve (FROC), incorporated into a tenfold cross validation framework. It was found that SVM classification using a Gaussian kernel offered significantly increased detection performance (P = 0.0002) compared to the reference methods. Varying training data and input features, SVMs showed improved exploitation of large feature sets. It is concluded that with the SVM-based CADe a significant reduction of FPs is possible outperforming other state-of-the-art approaches for breast mass CADe.

Reference standards for body fat measures using GE dual energy x-ray absorptiometry in Caucasian adults.

PubMed

Imboden, Mary T; Welch, Whitney A; Swartz, Ann M; Montoye, Alexander H K; Finch, Holmes W; Harber, Matthew P; Kaminsky, Leonard A

2017-01-01

Dual energy x-ray absorptiometry (DXA) is an established technique for the measurement of body composition. Reference values for these variables, particularly those related to fat mass, are necessary for interpretation and accurate classification of those at risk for obesity-related health complications and in need of lifestyle modifications (diet, physical activity, etc.). Currently, there are no reference values available for GE-Healthcare DXA systems and it is known that whole-body and regional fat mass measures differ by DXA manufacturer. To develop reference values by age and sex for DXA-derived fat mass measurements with GE-Healthcare systems. A de-identified sample of 3,327 participants (2,076 women, 1,251 men) was obtained from Ball State University's Clinical Exercise Physiology Laboratory and University of Wisconsin-Milwaukee's Physical Activity & Health Research Laboratory. All scans were completed using a GE Lunar Prodigy or iDXA and data reported included percent body fat (%BF), fat mass index (FMI), and ratios of android-to-gynoid (A/G), trunk/limb, and trunk/leg fat measurements. Percentiles were calculated and a factorial ANOVA was used to determine differences in the mean values for each variable between age and sex. Normative reference values for fat mass variables from DXA measurements obtained from GE-Healthcare DXA systems are presented as percentiles for both women and men in 10-year age groups. Women had higher (p<0.01) mean %BF and FMI than men, whereas men had higher (p<0.01) mean ratios of A/G, trunk/limb, and trunk/leg fat measurements than women. These reference values provide clinicians and researchers with a resource for interpretation of DXA-derived fat mass measurements specific to use with GE-Healthcare DXA systems.

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

PubMed Central

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

2014-01-01

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

An ensemble-based approach for breast mass classification in mammography images

NASA Astrophysics Data System (ADS)

Ribeiro, Patricia B.; Papa, João. P.; Romero, Roseli A. F.

2017-03-01

Mammography analysis is an important tool that helps detecting breast cancer at the very early stages of the disease, thus increasing the quality of life of hundreds of thousands of patients worldwide. In Computer-Aided Detection systems, the identification of mammograms with and without masses (without clinical findings) is highly needed to reduce the false positive rates regarding the automatic selection of regions of interest that may contain some suspicious content. In this work, the introduce a variant of the Optimum-Path Forest (OPF) classifier for breast mass identification, as well as we employed an ensemble-based approach that can enhance the effectiveness of individual classifiers aiming at dealing with the aforementioned purpose. The experimental results also comprise the naïve OPF and a traditional neural network, being the most accurate results obtained through the ensemble of classifiers, with an accuracy nearly to 86%.

Characterizing K2 Candidate Planetary Systems Orbiting Low-Mass Stars. I. Classifying Low-Mass Host Stars Observed During Campaigns 1-7

NASA Technical Reports Server (NTRS)

Dressing, Courtney D.; Newton, Elisabeth R.; Schlieder, Joshua E.; Charbomeau, David; Krutson, Heather A.; Vanderburg, Andrew; Sinukoff, Evan

2017-01-01

We present near-infrared spectra for 144 candidate planetary systems identified during Campaigns 1-7 of the NASA K2 Mission. The goal of the survey was to characterize planets orbiting low-mass stars, but our Infrared Telescope Facility/SpeX and Palomar/TripleSpec spectroscopic observations revealed that 49% of our targets were actually giant stars or hotter dwarfs reddened by interstellar extinction. For the 72 stars with spectra consistent with classification as cool dwarfs (spectral types K3-M4), we refined their stellar properties by applying empirical relations based on stars with interferometric radius measurements. Although our revised temperatures are generally consistent with those reported in the Ecliptic Plane Input Catalog (EPIC), our revised stellar radii are typically 0.13 solar radius (39%) larger than the EPIC values, which were based on model isochrones that have been shown to underestimate the radii of cool dwarfs. Our improved stellar characterizations will enable more efficient prioritization of K2 targets for follow-up studies.

On the implications of the period distributions of subclasses of cataclysmic variables

NASA Astrophysics Data System (ADS)

Verbunt, Frank

1997-09-01

The period distributions of dwarf novae and nova-like variables above the period gap are different if the VY Scl systems are classed with the nova-like variables, but the same when the VY Scl phenomenon is classed with the dwarf nova outbursts. For the remaining nova-like variables, the period gap is no longer significant. Classification of the VY Scl phenomenon with dwarf novae suggests that dwarf nova outbursts are caused by variation in mass transfer from the donor. Absence of the period gap obviates the need for models explaining it, and invalidates one piece of evidence for the importance of magnetic braking for the evolution of cataclysmic variables and of low-mass binaries in general.

Earthquake-Related Injuries in the Pediatric Population: A Systematic Review

PubMed Central

Jacquet, Gabrielle A.; Hansoti, Bhakti; Vu, Alexander; Bayram, Jamil D.

2013-01-01

Background: Children are a special population, particularly susceptible to injury. Registries for various injury types in the pediatric population are important, not only for epidemiological purposes but also for their implications on intervention programs. Although injury registries already exist, there is no uniform injury classification system for traumatic mass casualty events such as earthquakes. Objective: To systematically review peer-reviewed literature on the patterns of earthquake-related injuries in the pediatric population. Methods: On May 14, 2012, the authors performed a systematic review of literature from 1950 to 2012 indexed in Pubmed, EMBASE, Scopus, Web of Science, and Cochrane Library. Articles written in English, providing a quantitative description of pediatric injuries were included. Articles focusing on other types of disasters, geological, surgical, conceptual, psychological, indirect injuries, injury complications such as wound infections and acute kidney injury, case reports, reviews, and non-English articles were excluded. Results: A total of 2037 articles were retrieved, of which only 10 contained quantitative earthquake-related pediatric injury data. All studies were retrospective, had different age categorization, and reported injuries heterogeneously. Only 2 studies reported patterns of injury for all pediatric patients, including patients admitted and discharged. Seven articles described injuries by anatomic location, 5 articles described injuries by type, and 2 articles described injuries using both systems. Conclusions: Differences in age categorization of pediatric patients, and in the injury classification system make quantifying the burden of earthquake-related injuries in the pediatric population difficult. A uniform age categorization and injury classification system are paramount for drawing broader conclusions, enhancing disaster preparation for future disasters, and decreasing morbidity and mortality. PMID:24761308

Computational assessment of mammography accreditation phantom images and correlation with human observer analysis

NASA Astrophysics Data System (ADS)

Barufaldi, Bruno; Lau, Kristen C.; Schiabel, Homero; Maidment, D. A.

2015-03-01

Routine performance of basic test procedures and dose measurements are essential for assuring high quality of mammograms. International guidelines recommend that breast care providers ascertain that mammography systems produce a constant high quality image, using as low a radiation dose as is reasonably achievable. The main purpose of this research is to develop a framework to monitor radiation dose and image quality in a mixed breast screening and diagnostic imaging environment using an automated tracking system. This study presents a module of this framework, consisting of a computerized system to measure the image quality of the American College of Radiology mammography accreditation phantom. The methods developed combine correlation approaches, matched filters, and data mining techniques. These methods have been used to analyze radiological images of the accreditation phantom. The classification of structures of interest is based upon reports produced by four trained readers. As previously reported, human observers demonstrate great variation in their analysis due to the subjectivity of human visual inspection. The software tool was trained with three sets of 60 phantom images in order to generate decision trees using the software WEKA (Waikato Environment for Knowledge Analysis). When tested with 240 images during the classification step, the tool correctly classified 88%, 99%, and 98%, of fibers, speck groups and masses, respectively. The variation between the computer classification and human reading was comparable to the variation between human readers. This computerized system not only automates the quality control procedure in mammography, but also decreases the subjectivity in the expert evaluation of the phantom images.

Novel approach for differentiating Shigella species and Escherichia coli by matrix-assisted laser desorption ionization-time of flight mass spectrometry.

PubMed

Khot, Prasanna D; Fisher, Mark A

2013-11-01

Shigella species are so closely related to Escherichia coli that routine matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) cannot reliably differentiate them. Biochemical and serological methods are typically used to distinguish these species; however, "inactive" isolates of E. coli are biochemically very similar to Shigella species and thus pose a greater diagnostic challenge. We used ClinProTools (Bruker Daltonics) software to discover MALDI-TOF MS biomarker peaks and to generate classification models based on the genetic algorithm to differentiate between Shigella species and E. coli. Sixty-six Shigella spp. and 72 E. coli isolates were used to generate and test classification models, and the optimal models contained 15 biomarker peaks for genus-level classification and 12 peaks for species-level classification. We were able to identify 90% of E. coli and Shigella clinical isolates correctly to the species level. Only 3% of tested isolates were misidentified. This novel MALDI-TOF MS approach allows laboratories to streamline the identification of E. coli and Shigella species.

Local binary pattern texture-based classification of solid masses in ultrasound breast images

NASA Astrophysics Data System (ADS)

Matsumoto, Monica M. S.; Sehgal, Chandra M.; Udupa, Jayaram K.

2012-03-01

Breast cancer is one of the leading causes of cancer mortality among women. Ultrasound examination can be used to assess breast masses, complementarily to mammography. Ultrasound images reveal tissue information in its echoic patterns. Therefore, pattern recognition techniques can facilitate classification of lesions and thereby reduce the number of unnecessary biopsies. Our hypothesis was that image texture features on the boundary of a lesion and its vicinity can be used to classify masses. We have used intensity-independent and rotation-invariant texture features, known as Local Binary Patterns (LBP). The classifier selected was K-nearest neighbors. Our breast ultrasound image database consisted of 100 patient images (50 benign and 50 malignant cases). The determination of whether the mass was benign or malignant was done through biopsy and pathology assessment. The training set consisted of sixty images, randomly chosen from the database of 100 patients. The testing set consisted of forty images to be classified. The results with a multi-fold cross validation of 100 iterations produced a robust evaluation. The highest performance was observed for feature LBP with 24 symmetrically distributed neighbors over a circle of radius 3 (LBP24,3) with an accuracy rate of 81.0%. We also investigated an approach with a score of malignancy assigned to the images in the test set. This approach provided an ROC curve with Az of 0.803. The analysis of texture features over the boundary of solid masses showed promise for malignancy classification in ultrasound breast images.

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

PubMed

Waring, R; Knight, R

2013-01-01

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

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

Code of Federal Regulations, 2011 CFR

2011-01-01

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

Rapid identification of oral Actinomyces species cultivated from subgingival biofilm by MALDI-TOF-MS

PubMed Central

Stingu, Catalina S.; Borgmann, Toralf; Rodloff, Arne C.; Vielkind, Paul; Jentsch, Holger; Schellenberger, Wolfgang; Eschrich, Klaus

2015-01-01

Background Actinomyces are a common part of the residential flora of the human intestinal tract, genitourinary system and skin. Isolation and identification of Actinomyces by conventional methods is often difficult and time consuming. In recent years, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) has become a rapid and simple method to identify bacteria. Objective The present study evaluated a new in-house algorithm using MALDI-TOF-MS for rapid identification of different species of oral Actinomyces cultivated from subgingival biofilm. Design Eleven reference strains and 674 clinical strains were used in this study. All the strains were preliminarily identified using biochemical methods and then subjected to MALDI-TOF-MS analysis using both similarity-based analysis and classification methods (support vector machine [SVM]). The genotype of the reference strains and of 232 clinical strains was identified by sequence analysis of the 16S ribosomal RNA (rRNA). Results The sequence analysis of the 16S rRNA gene of all references strains confirmed their previous identification. The MALDI-TOF-MS spectra obtained from the reference strains and the other clinical strains undoubtedly identified as Actinomyces by 16S rRNA sequencing were used to create the mass spectra reference database. Already a visual inspection of the mass spectra of different species reveals both similarities and differences. However, the differences between them are not large enough to allow a reliable differentiation by similarity analysis. Therefore, classification methods were applied as an alternative approach for differentiation and identification of Actinomyces at the species level. A cross-validation of the reference database representing 14 Actinomyces species yielded correct results for all species which were represented by more than two strains in the database. Conclusions Our results suggest that a combination of MALDI-TOF-MS with powerful classification algorithms, such as SVMs, provide a useful tool for the differentiation and identification of oral Actinomyces. PMID:25597306

Source identification of western Oregon Douglas-Fir wood cores using mass spectrometry and random forest Classification

Treesearch

Kristen Finch; Edgard Espinoza; F. Andrew Jones; Richard Cronn

2017-01-01

Premise of the study: We investigated whether wood metabolite profiles from direct analysis in real time (time-of-flight) mass spectrometry (DART-TOFMS) could be used to determine the geographic origin of Douglas-fir wood cores originating from two regions in western Oregon, USA. Methods: Three annual ring mass...

Double-lined M dwarf eclipsing binaries from Catalina Sky Survey and LAMOST

NASA Astrophysics Data System (ADS)

Lee, Chien-Hsiu; Lin, Chien-Cheng

2017-02-01

Eclipsing binaries provide a unique opportunity to determine fundamental stellar properties. In the era of wide-field cameras and all-sky imaging surveys, thousands of eclipsing binaries have been reported through light curve classification, yet their basic properties remain unexplored due to the extensive efforts needed to follow them up spectroscopically. In this paper we investigate three M2-M3 type double-lined eclipsing binaries discovered by cross-matching eclipsing binaries from the Catalina Sky Survey with spectroscopically classified M dwarfs from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope survey data release one and two. Because these three M dwarf binaries are faint, we further acquire radial velocity measurements using GMOS on the Gemini North telescope with R˜ 4000, enabling us to determine the mass and radius of individual stellar components. By jointly fitting the light and radial velocity curves of these systems, we derive the mass and radius of the primary and secondary components of these three systems, in the range between 0.28-0.42M_⊙ and 0.29-0.67R_⊙, respectively. Future observations with a high resolution spectrograph will help us pin down the uncertainties in their stellar parameters, and render these systems benchmarks to study M dwarfs, providing inputs to improving stellar models in the low mass regime, or establishing an empirical mass-radius relation for M dwarf stars.

Compression of deep convolutional neural network for computer-aided diagnosis of masses in digital breast tomosynthesis

NASA Astrophysics Data System (ADS)

Samala, Ravi K.; Chan, Heang-Ping; Hadjiiski, Lubomir; Helvie, Mark A.; Richter, Caleb; Cha, Kenny

2018-02-01

Deep-learning models are highly parameterized, causing difficulty in inference and transfer learning. We propose a layered pathway evolution method to compress a deep convolutional neural network (DCNN) for classification of masses in DBT while maintaining the classification accuracy. Two-stage transfer learning was used to adapt the ImageNet-trained DCNN to mammography and then to DBT. In the first-stage transfer learning, transfer learning from ImageNet trained DCNN was performed using mammography data. In the second-stage transfer learning, the mammography-trained DCNN was trained on the DBT data using feature extraction from fully connected layer, recursive feature elimination and random forest classification. The layered pathway evolution encapsulates the feature extraction to the classification stages to compress the DCNN. Genetic algorithm was used in an iterative approach with tournament selection driven by count-preserving crossover and mutation to identify the necessary nodes in each convolution layer while eliminating the redundant nodes. The DCNN was reduced by 99% in the number of parameters and 95% in mathematical operations in the convolutional layers. The lesion-based area under the receiver operating characteristic curve on an independent DBT test set from the original and the compressed network resulted in 0.88+/-0.05 and 0.90+/-0.04, respectively. The difference did not reach statistical significance. We demonstrated a DCNN compression approach without additional fine-tuning or loss of performance for classification of masses in DBT. The approach can be extended to other DCNNs and transfer learning tasks. An ensemble of these smaller and focused DCNNs has the potential to be used in multi-target transfer learning.

Rapid and easy detection of low-level resistance to vancomycin in methicillin-resistant Staphylococcus aureus by matrix-assisted laser desorption ionization time-of-flight mass spectrometry.

PubMed

Asakura, Kota; Azechi, Takuya; Sasano, Hiroshi; Matsui, Hidehito; Hanaki, Hideaki; Miyazaki, Motoyasu; Takata, Tohru; Sekine, Miwa; Takaku, Tomoiku; Ochiai, Tomonori; Komatsu, Norio; Shibayama, Keigo; Katayama, Yuki; Yahara, Koji

2018-01-01

Vancomycin-intermediately resistant Staphylococcus aureus (VISA) and heterogeneous VISA (hVISA) are associated with treatment failure. hVISA contains only a subpopulation of cells with increased minimal inhibitory concentrations, and its detection is problematic because it is classified as vancomycin-susceptible by standard susceptibility testing and the gold-standard method for its detection is impractical in clinical microbiology laboratories. Recently, a research group developed a machine-learning classifier to distinguish VISA and hVISA from vancomycin-susceptible S. aureus (VSSA) according to matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) data. Nonetheless, the sensitivity of hVISA classification was found to be 76%, and the program was not completely automated with a graphical user interface. Here, we developed a more accurate machine-learning classifier for discrimination of hVISA from VSSA and VISA among MRSA isolates in Japanese hospitals by means of MALDI-TOF MS data. The classifier showed 99% sensitivity of hVISA classification. Furthermore, we clarified the procedures for preparing samples and obtaining MALDI-TOF MS data and developed all-in-one software, hVISA Classifier, with a graphical user interface that automates the classification and is easy for medical workers to use; it is publicly available at https://github.com/bioprojects/hVISAclassifier. This system is useful and practical for screening MRSA isolates for the hVISA phenotype in clinical microbiology laboratories and thus should improve treatment of MRSA infections.

Rapid and easy detection of low-level resistance to vancomycin in methicillin-resistant Staphylococcus aureus by matrix-assisted laser desorption ionization time-of-flight mass spectrometry

PubMed Central

Asakura, Kota; Azechi, Takuya; Sasano, Hiroshi; Matsui, Hidehito; Hanaki, Hideaki; Miyazaki, Motoyasu; Takata, Tohru; Sekine, Miwa; Takaku, Tomoiku; Ochiai, Tomonori; Komatsu, Norio; Shibayama, Keigo

2018-01-01

Vancomycin-intermediately resistant Staphylococcus aureus (VISA) and heterogeneous VISA (hVISA) are associated with treatment failure. hVISA contains only a subpopulation of cells with increased minimal inhibitory concentrations, and its detection is problematic because it is classified as vancomycin-susceptible by standard susceptibility testing and the gold-standard method for its detection is impractical in clinical microbiology laboratories. Recently, a research group developed a machine-learning classifier to distinguish VISA and hVISA from vancomycin-susceptible S. aureus (VSSA) according to matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) data. Nonetheless, the sensitivity of hVISA classification was found to be 76%, and the program was not completely automated with a graphical user interface. Here, we developed a more accurate machine-learning classifier for discrimination of hVISA from VSSA and VISA among MRSA isolates in Japanese hospitals by means of MALDI-TOF MS data. The classifier showed 99% sensitivity of hVISA classification. Furthermore, we clarified the procedures for preparing samples and obtaining MALDI-TOF MS data and developed all-in-one software, hVISA Classifier, with a graphical user interface that automates the classification and is easy for medical workers to use; it is publicly available at https://github.com/bioprojects/hVISAclassifier. This system is useful and practical for screening MRSA isolates for the hVISA phenotype in clinical microbiology laboratories and thus should improve treatment of MRSA infections. PMID:29522576

Expert identification of visual primitives used by CNNs during mammogram classification

NASA Astrophysics Data System (ADS)

Wu, Jimmy; Peck, Diondra; Hsieh, Scott; Dialani, Vandana; Lehman, Constance D.; Zhou, Bolei; Syrgkanis, Vasilis; Mackey, Lester; Patterson, Genevieve

2018-02-01

This work interprets the internal representations of deep neural networks trained for classification of diseased tissue in 2D mammograms. We propose an expert-in-the-loop inter- pretation method to label the behavior of internal units in convolutional neural networks (CNNs). Expert radiologists identify that the visual patterns detected by the units are correlated with meaningful medical phenomena such as mass tissue and calcificated vessels. We demonstrate that several trained CNN models are able to produce explanatory descriptions to support the final classification decisions. We view this as an important first step toward interpreting the internal representations of medical classification CNNs and explaining their predictions.

Breast masses in mammography classification with local contour features.

PubMed

Li, Haixia; Meng, Xianjing; Wang, Tingwen; Tang, Yuchun; Yin, Yilong

2017-04-14

Mammography is one of the most popular tools for early detection of breast cancer. Contour of breast mass in mammography is very important information to distinguish benign and malignant mass. Contour of benign mass is smooth and round or oval, while malignant mass has irregular shape and spiculated contour. Several studies have shown that 1D signature translated from 2D contour can describe the contour features well. In this paper, we propose a new method to translate 2D contour of breast mass in mammography into 1D signature. The method can describe not only the contour features but also the regularity of breast mass. Then we segment the whole 1D signature into different subsections. We extract four local features including a new contour descriptor from the subsections. The new contour descriptor is root mean square (RMS) slope. It can describe the roughness of the contour. KNN, SVM and ANN classifier are used to classify benign breast mass and malignant mass. The proposed method is tested on a set with 323 contours including 143 benign masses and 180 malignant ones from digital database of screening mammography (DDSM). The best accuracy of classification is 99.66% using the feature of root mean square slope with SVM classifier. The performance of the proposed method is better than traditional method. In addition, RMS slope is an effective feature comparable to most of the existing features.

Classification of the medicinal plants of the genus Atractylodes using high-performance liquid chromatography with diode array and tandem mass spectrometry detection combined with multivariate statistical analysis.

PubMed

Cho, Hyun-Deok; Kim, Unyong; Suh, Joon Hyuk; Eom, Han Young; Kim, Junghyun; Lee, Seul Gi; Choi, Yong Seok; Han, Sang Beom

2016-04-01

Analytical methods using high-performance liquid chromatography with diode array and tandem mass spectrometry detection were developed for the discrimination of the rhizomes of four Atractylodes medicinal plants: A. japonica, A. macrocephala, A. chinensis, and A. lancea. A quantitative study was performed, selecting five bioactive components, including atractylenolide I, II, III, eudesma-4(14),7(11)-dien-8-one and atractylodin, on twenty-six Atractylodes samples of various origins. Sample extraction was optimized to sonication with 80% methanol for 40 min at room temperature. High-performance liquid chromatography with diode array detection was established using a C18 column with a water/acetonitrile gradient system at a flow rate of 1.0 mL/min, and the detection wavelength was set at 236 nm. Liquid chromatography with tandem mass spectrometry was applied to certify the reliability of the quantitative results. The developed methods were validated by ensuring specificity, linearity, limit of quantification, accuracy, precision, recovery, robustness, and stability. Results showed that cangzhu contained higher amounts of atractylenolide I and atractylodin than baizhu, and especially atractylodin contents showed the greatest variation between baizhu and cangzhu. Multivariate statistical analysis, such as principal component analysis and hierarchical cluster analysis, were also employed for further classification of the Atractylodes plants. The established method was suitable for quality control of the Atractylodes plants. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Modeling the Impact of Baryons on Subhalo Populations with Machine Learning

NASA Astrophysics Data System (ADS)

Nadler, Ethan O.; Mao, Yao-Yuan; Wechsler, Risa H.; Garrison-Kimmel, Shea; Wetzel, Andrew

2018-06-01

We identify subhalos in dark matter–only (DMO) zoom-in simulations that are likely to be disrupted due to baryonic effects by using a random forest classifier trained on two hydrodynamic simulations of Milky Way (MW)–mass host halos from the Latte suite of the Feedback in Realistic Environments (FIRE) project. We train our classifier using five properties of each disrupted and surviving subhalo: pericentric distance and scale factor at first pericentric passage after accretion and scale factor, virial mass, and maximum circular velocity at accretion. Our five-property classifier identifies disrupted subhalos in the FIRE simulations with an 85% out-of-bag classification score. We predict surviving subhalo populations in DMO simulations of the FIRE host halos, finding excellent agreement with the hydrodynamic results; in particular, our classifier outperforms DMO zoom-in simulations that include the gravitational potential of the central galactic disk in each hydrodynamic simulation, indicating that it captures both the dynamical effects of a central disk and additional baryonic physics. We also predict surviving subhalo populations for a suite of DMO zoom-in simulations of MW-mass host halos, finding that baryons impact each system consistently and that the predicted amount of subhalo disruption is larger than the host-to-host scatter among the subhalo populations. Although the small size and specific baryonic physics prescription of our training set limits the generality of our results, our work suggests that machine-learning classification algorithms trained on hydrodynamic zoom-in simulations can efficiently predict realistic subhalo populations.

Mass detection with digitized screening mammograms by using Gabor features

NASA Astrophysics Data System (ADS)

Zheng, Yufeng; Agyepong, Kwabena

2007-03-01

Breast cancer is the leading cancer among American women. The current lifetime risk of developing breast cancer is 13.4% (one in seven). Mammography is the most effective technology presently available for breast cancer screening. With digital mammograms computer-aided detection (CAD) has proven to be a useful tool for radiologists. In this paper, we focus on mass detection that is a common category of breast cancers relative to calcification and architecture distortion. We propose a new mass detection algorithm utilizing Gabor filters, termed as "Gabor Mass Detection" (GMD). There are three steps in the GMD algorithm, (1) preprocessing, (2) generating alarms and (3) classification (reducing false alarms). Down-sampling, quantization, denoising and enhancement are done in the preprocessing step. Then a total of 30 Gabor filtered images (along 6 bands by 5 orientations) are produced. Alarm segments are generated by thresholding four Gabor images of full orientations (Stage-I classification) with image-dependent thresholds computed via histogram analysis. Next a set of edge histogram descriptors (EHD) are extracted from 24 Gabor images (6 by 4) that will be used for Stage-II classification. After clustering EHD features with fuzzy C-means clustering method, a k-nearest neighbor classifier is used to reduce the number of false alarms. We initially analyzed 431 digitized mammograms (159 normal images vs. 272 cancerous images, from the DDSM project, University of South Florida) with the proposed GMD algorithm. And a ten-fold cross validation was used for testing the GMD algorithm upon the available data. The GMD performance is as follows: sensitivity (true positive rate) = 0.88 at false positives per image (FPI) = 1.25, and the area under the ROC curve = 0.83. The overall performance of the GMD algorithm is satisfactory and the accuracy of locating masses (highlighting the boundaries of suspicious areas) is relatively high. Furthermore, the GMD algorithm can successfully detect early-stage (with small values of Assessment & low Subtlety) malignant masses. In addition, Gabor filtered images are used in both stages of classifications, which greatly simplifies the GMD algorithm.

Breast US as primary imaging modality for diagnosing gynecomastia.

PubMed

Telegrafo, M; Introna, T; Coi, L; Cornacchia, I; Rella, L; Stabile Ianora, A A; Angelelli, G; Moschetta, M

2016-01-01

To assess the role of breast US in diagnosing and classifying gynecomastia as the primary imaging modality and to compare US findings and classification system with the mammographic ones. 48 patients suspected of having gynecomastia underwent mammography and US. Two radiologists in consensus retrospectively evaluated mammograms and sonograms. Both US and mammographic images were evaluated categorizing gynecomastia into non-mass, nodular and flame shaped patterns. The two category assignations were compared in order to find any difference. The reference standard for both the classification systems was represented by the cytological examination in 18 out of 44 cases (41%) and the six-month US follow-up in the remaining cases. The US examination revealed pseudo-gynecomastia in 4/48 (8%) and true gynecomastia in the remaining 44 (92%). Gynecomastia was bilateral in 25/44 cases (57%) and unilateral in the remaining 19 (43%). The cases of true gynecomastia included non mass shape in 26/44 cases (59%), nodular shape in 12 (27%) and flame shape in 6 (14%). The mammographic examination revealed the same results as compared with US findings. 18/44 (41%) patients affected by nodular or dendritic gynecomastia underwent cytological examination confirming the presence of glandular tissue and the benign nature of the clinical condition. US could be proposed as the primary imaging tool for diagnosing and classifying gynecomastia, avoiding unnecessary Xray examinations or invasive procedures in case of diffuse gynecomastia. In case of nodular or dendritic patterns, biopsy remains mandatory for a definitive diagnosis.

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

PubMed

Waltho, Daniel; Hatchell, Alexandra; Thoma, Achilleas

2017-03-01

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

Extrasolar planetary systems.

NASA Technical Reports Server (NTRS)

Huang, S.-S.

1973-01-01

The terms 'planet' and 'planet-like objects' are defined. The observational search for extrasolar planetary systems is described, as performable by earthbound optical telescopes, by space probes, by long baseline radio interferometry, and finally by inference from the reception of signals sent by intelligent beings in other worlds. It is shown that any planetary system must be preceded by a rotating disk of gas and dust around a central mass. A brief review of the theories of the formation of the solar system is given, along with a proposed scheme for classification of these theories. The evidence for magnetic activity in the early stages of stellar evolution is presented. The magnetic braking theories of solar and stellar rotation are discussed, and an estimate is made for the frequency of occurrence of planetary systems in the universe.

The Feasibility of Classifying Breast Masses Using a Computer-Assisted Diagnosis (CAD) System Based on Ultrasound Elastography and BI-RADS Lexicon.

PubMed

Fleury, Eduardo F C; Gianini, Ana Claudia; Marcomini, Karem; Oliveira, Vilmar

2018-01-01

To determine the applicability of a computer-aided diagnostic system strain elastography system for the classification of breast masses diagnosed by ultrasound and scored using the criteria proposed by the breast imaging and reporting data system ultrasound lexicon and to determine the diagnostic accuracy and interobserver variability. This prospective study was conducted between March 1, 2016, and May 30, 2016. A total of 83 breast masses subjected to percutaneous biopsy were included. Ultrasound elastography images before biopsy were interpreted by 3 radiologists with and without the aid of computer-aided diagnostic system for strain elastography. The parameters evaluated by each radiologist results were sensitivity, specificity, and diagnostic accuracy, with and without computer-aided diagnostic system for strain elastography. Interobserver variability was assessed using a weighted κ test and an intraclass correlation coefficient. The areas under the receiver operating characteristic curves were also calculated. The areas under the receiver operating characteristic curve were 0.835, 0.801, and 0.765 for readers 1, 2, and 3, respectively, without computer-aided diagnostic system for strain elastography, and 0.900, 0.926, and 0.868, respectively, with computer-aided diagnostic system for strain elastography. The intraclass correlation coefficient between the 3 readers was 0.6713 without computer-aided diagnostic system for strain elastography and 0.811 with computer-aided diagnostic system for strain elastography. The proposed computer-aided diagnostic system for strain elastography system has the potential to improve the diagnostic performance of radiologists in breast examination using ultrasound associated with elastography.

Causes of death among full term stillbirths and early neonatal deaths in the Region of Southern Denmark.

PubMed

Basu, Millie Nguyen; Johnsen, Iben Birgit Gade; Wehberg, Sonja; Sørensen, Rikke Guldberg; Barington, Torben; Nørgård, Bente Mertz

2018-02-23

We examined the causes of death amongst full term stillbirths and early neonatal deaths. Our cohort includes women in the Region of Southern Denmark, who gave birth at full term to a stillborn infant or a neonate who died within the first 7 days from 2010 through 2014. Demographic, biometric and clinical variables were analyzed to assess the causes of death using two classification systems: causes of death and associated conditions (CODAC) and a Danish system based on initial causes of fetal death (INCODE). A total of 95 maternal-infant cases were included. Using the CODAC and INCODE classification systems, we found that the causes of death were unknown in 59/95 (62.1%). The second most common cause of death in CODAC was congenital anomalies in 10/95 (10.5%), similar to INCODE with fetal, genetic, structural and karyotypic anomalies in 11/95 (11.6%). The majority of the mothers were healthy, primiparous, non-smokers, aged 20-34 years and with a normal body mass index (BMI). Based on an unselected cohort from an entire region in Denmark, the cause of stillbirth and early neonatal deaths among full term infants remained unknown for the vast majority.

Pyrolysis Mass Spectrometry of Complex Organic Materials.

ERIC Educational Resources Information Center

Meuzelaar, Henk L. C.; And Others

1984-01-01

Illustrates the state of the art in pyrolysis mass spectrometry techniques through applications in: (1) structural determination and quality control of synthetic polymers; (2) quantitative analysis of polymer mixtures; (3) classification and structural characterization of fossil organic matter; and (4) nonsupervised numerical extraction of…

MURI: Optimal Quantum Dynamic Discrimination of Chemical and Biological Agents

DTIC Science & Technology

2008-06-12

multiparameter) Hilbert space for enhanced detection and classification: an application of receiver operating curve statistics to laser-based mass...Adaptive reshaping of objects in (multiparameter) Hilbert space for enhanced detection and classification: an application of receiver operating curve...Doctoral Associate Muhannad Zamari, Graduate Student Ilya Greenberg , Computer Consultant Getahun Menkir, Graduate Student Lalinda Palliyaguru, Graduate

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

PubMed

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

2015-12-01

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

Machine vision system for measuring conifer seedling morphology

NASA Astrophysics Data System (ADS)

Rigney, Michael P.; Kranzler, Glenn A.

1995-01-01

A PC-based machine vision system providing rapid measurement of bare-root tree seedling morphological features has been designed. The system uses backlighting and a 2048-pixel line- scan camera to acquire images with transverse resolutions as high as 0.05 mm for precise measurement of stem diameter. Individual seedlings are manually loaded on a conveyor belt and inspected by the vision system in less than 0.25 seconds. Designed for quality control and morphological data acquisition by nursery personnel, the system provides a user-friendly, menu-driven graphical interface. The system automatically locates the seedling root collar and measures stem diameter, shoot height, sturdiness ratio, root mass length, projected shoot and root area, shoot-root area ratio, and percent fine roots. Sample statistics are computed for each measured feature. Measurements for each seedling may be stored for later analysis. Feature measurements may be compared with multi-class quality criteria to determine sample quality or to perform multi-class sorting. Statistical summary and classification reports may be printed to facilitate the communication of quality concerns with grading personnel. Tests were conducted at a commercial forest nursery to evaluate measurement precision. Four quality control personnel measured root collar diameter, stem height, and root mass length on each of 200 conifer seedlings. The same seedlings were inspected four times by the machine vision system. Machine stem diameter measurement precision was four times greater than that of manual measurements. Machine and manual measurements had comparable precision for shoot height and root mass length.

Designing and Implementation of River Classification Assistant Management System

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Application of classification tree and logistic regression for the management and health intervention plans in a community-based study.

PubMed

Teng, Ju-Hsi; Lin, Kuan-Chia; Ho, Bin-Shenq

2007-10-01

A community-based aboriginal study was conducted and analysed to explore the application of classification tree and logistic regression. A total of 1066 aboriginal residents in Yilan County were screened during 2003-2004. The independent variables include demographic characteristics, physical examinations, geographic location, health behaviours, dietary habits and family hereditary diseases history. Risk factors of cardiovascular diseases were selected as the dependent variables in further analysis. The completion rate for heath interview is 88.9%. The classification tree results find that if body mass index is higher than 25.72 kg m(-2) and the age is above 51 years, the predicted probability for number of cardiovascular risk factors > or =3 is 73.6% and the population is 322. If body mass index is higher than 26.35 kg m(-2) and geographical latitude of the village is lower than 24 degrees 22.8', the predicted probability for number of cardiovascular risk factors > or =4 is 60.8% and the population is 74. As the logistic regression results indicate that body mass index, drinking habit and menopause are the top three significant independent variables. The classification tree model specifically shows the discrimination paths and interactions between the risk groups. The logistic regression model presents and analyses the statistical independent factors of cardiovascular risks. Applying both models to specific situations will provide a different angle for the design and management of future health intervention plans after community-based study.

Classification of cancer cell lines using matrix-assisted laser desorption/ionization time‑of‑flight mass spectrometry and statistical analysis.

PubMed

Serafim, Vlad; Shah, Ajit; Puiu, Maria; Andreescu, Nicoleta; Coricovac, Dorina; Nosyrev, Alexander; Spandidos, Demetrios A; Tsatsakis, Aristides M; Dehelean, Cristina; Pinzaru, Iulia

2017-10-01

Over the past decade, matrix-assisted laser desorption/ionization time‑of‑flight mass spectrometry (MALDI‑TOF MS) has been established as a valuable platform for microbial identification, and it is also frequently applied in biology and clinical studies to identify new markers expressed in pathological conditions. The aim of the present study was to assess the potential of using this approach for the classification of cancer cell lines as a quantifiable method for the proteomic profiling of cellular organelles. Intact protein extracts isolated from different tumor cell lines (human and murine) were analyzed using MALDI‑TOF MS and the obtained mass lists were processed using principle component analysis (PCA) within Bruker Biotyper® software. Furthermore, reference spectra were created for each cell line and were used for classification. Based on the intact protein profiles, we were able to differentiate and classify six cancer cell lines: two murine melanoma (B16‑F0 and B164A5), one human melanoma (A375), two human breast carcinoma (MCF7 and MDA‑MB‑231) and one human liver carcinoma (HepG2). The cell lines were classified according to cancer type and the species they originated from, as well as by their metastatic potential, offering the possibility to differentiate non‑invasive from invasive cells. The obtained results pave the way for developing a broad‑based strategy for the identification and classification of cancer cells.

Iterative variational mode decomposition based automated detection of glaucoma using fundus images.

PubMed

Maheshwari, Shishir; Pachori, Ram Bilas; Kanhangad, Vivek; Bhandary, Sulatha V; Acharya, U Rajendra

2017-09-01

Glaucoma is one of the leading causes of permanent vision loss. It is an ocular disorder caused by increased fluid pressure within the eye. The clinical methods available for the diagnosis of glaucoma require skilled supervision. They are manual, time consuming, and out of reach of common people. Hence, there is a need for an automated glaucoma diagnosis system for mass screening. In this paper, we present a novel method for an automated diagnosis of glaucoma using digital fundus images. Variational mode decomposition (VMD) method is used in an iterative manner for image decomposition. Various features namely, Kapoor entropy, Renyi entropy, Yager entropy, and fractal dimensions are extracted from VMD components. ReliefF algorithm is used to select the discriminatory features and these features are then fed to the least squares support vector machine (LS-SVM) for classification. Our proposed method achieved classification accuracies of 95.19% and 94.79% using three-fold and ten-fold cross-validation strategies, respectively. This system can aid the ophthalmologists in confirming their manual reading of classes (glaucoma or normal) using fundus images. Copyright © 2017 Elsevier Ltd. All rights reserved.

42 CFR 412.10 - Changes in the DRG classification system.

Code of Federal Regulations, 2010 CFR

2010-10-01

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

42 CFR 412.10 - Changes in the DRG classification system.

Code of Federal Regulations, 2011 CFR

2011-10-01

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

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

ERIC Educational Resources Information Center

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

2012-01-01

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

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

PubMed

Rabidas, Rinku; Midya, Abhishek; Chakraborty, Jayasree

2018-05-01

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

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

PubMed

Lanfranconi, Silvia; Markus, Hugh S

2013-12-01

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

Ensemble of sparse classifiers for high-dimensional biological data.

PubMed

Kim, Sunghan; Scalzo, Fabien; Telesca, Donatello; Hu, Xiao

2015-01-01

Biological data are often high in dimension while the number of samples is small. In such cases, the performance of classification can be improved by reducing the dimension of data, which is referred to as feature selection. Recently, a novel feature selection method has been proposed utilising the sparsity of high-dimensional biological data where a small subset of features accounts for most variance of the dataset. In this study we propose a new classification method for high-dimensional biological data, which performs both feature selection and classification within a single framework. Our proposed method utilises a sparse linear solution technique and the bootstrap aggregating algorithm. We tested its performance on four public mass spectrometry cancer datasets along with two other conventional classification techniques such as Support Vector Machines and Adaptive Boosting. The results demonstrate that our proposed method performs more accurate classification across various cancer datasets than those conventional classification techniques.

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

PubMed

Roers, Friederike; Mürbe, Dirk; Sundberg, Johan

2009-01-01

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

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

PubMed Central

2014-01-01

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

Computer-aided classification of mammographic masses using the deep learning technology: a preliminary study

NASA Astrophysics Data System (ADS)

Qiu, Yuchen; Yan, Shiju; Tan, Maxine; Cheng, Samuel; Liu, Hong; Zheng, Bin

2016-03-01

Although mammography is the only clinically acceptable imaging modality used in the population-based breast cancer screening, its efficacy is quite controversy. One of the major challenges is how to help radiologists more accurately classify between benign and malignant lesions. The purpose of this study is to investigate a new mammographic mass classification scheme based on a deep learning method. In this study, we used an image dataset involving 560 regions of interest (ROIs) extracted from digital mammograms, which includes 280 malignant and 280 benign mass ROIs, respectively. An eight layer deep learning network was applied, which employs three pairs of convolution-max-pooling layers for automatic feature extraction and a multiple layer perception (MLP) classifier for feature categorization. In order to improve robustness of selected features, each convolution layer is connected with a max-pooling layer. A number of 20, 10, and 5 feature maps were utilized for the 1st, 2nd and 3rd convolution layer, respectively. The convolution networks are followed by a MLP classifier, which generates a classification score to predict likelihood of a ROI depicting a malignant mass. Among 560 ROIs, 420 ROIs were used as a training dataset and the remaining 140 ROIs were used as a validation dataset. The result shows that the new deep learning based classifier yielded an area under the receiver operation characteristic curve (AUC) of 0.810+/-0.036. This study demonstrated the potential superiority of using a deep learning based classifier to distinguish malignant and benign breast masses without segmenting the lesions and extracting the pre-defined image features.

Extensions to the Speech Disorders Classification System (SDCS)

ERIC Educational Resources Information Center

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

2010-01-01

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

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

PubMed

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

2014-06-01

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

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

PubMed

Acién, Pedro; Acién, Maribel I

2011-01-01

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

Single-step solubilization of milk samples with N,N-dimethylformamide for inductively coupled plasma-mass spectrometry analysis and classification based on their elemental composition.

PubMed

Azcarate, Silvana M; Savio, Marianela; Smichowski, Patricia; Martinez, Luis D; Camiña, José M; Gil, Raúl A

2015-10-01

A single-step procedure for trace elements analysis of milk samples is presented. Solubilization with small amounts of dymethylformamide (DMF) was assayed prior to inductively coupled plasma mass spectrometry (ICPMS) detection with a high efficiency sample introduction system. All main instrumental conditions were optimized in order to readily introduce the samples without matrix elimination. In order to assess and mitigate matrix effects in the determination of As, Cd, Co, Cu, Eu, Ga, Gd, Ge, Mn, Mo, Nb, Nd, Ni, Pb, Pr, Rb, Sm, S, Sr, Ta, Tb, V, Zn, and Zr, matrix matching calibration with (103)Rh as internal standard (IS) was performed. The obtained limits of detection were between 0.68 (Tb) and 30 (Zn) μg L(-1). For accuracy verification, certified Skim milk powder reference material (BCR 063R) was employed. The developed method was applied to trace elements analysis of commercially available milks. Principal components analysis was used to correlate the content of trace metals with the kind of milk, obtaining a classification according to adults, baby or baby fortified milks. The outcomes highlight a simple and fast approach that could be trustworthy for routine analysis, quality control and traceability of milks. Copyright © 2015 Elsevier B.V. All rights reserved.

A rare case of malignant diaphragmatic hemangiopericytoma in a patient with pleural effusion.

PubMed

Pazzini, L; La Magra, C; D'Agata, A; Magnolfi, A; Cacchiarelli, M; Gotti, G

2006-06-01

This paper reports a case of primary malignant diaphragmatic hemangiopericytoma in a 30-year-old male patient operated on for a diaphragmatic mass. The tumour was discovered on a TC scanning performed to explain the etiology of an exudative pleural effusion in a patient admitted for dyspnea, fever and thoracic pain. Given the rarity of this disease, the histological and pathological features of hemangiopericytoma are discussed in the light of the new classification system for soft tissue and bone tumours, as well as its currently accepted therapeutical guidelines.

A 15.7-Minute AM CVn Binary Discovered in K2

NASA Astrophysics Data System (ADS)

Green, M. J.; Hermes, J. J.; Marsh, T. R.; Steeghs, D. T. H.; Bell, Keaton J.; Littlefair, S. P.; Parsons, S. G.; Dennihy, E.; Fuchs, J. T.; Reding, J. S.; Kaiser, B. C.; Ashley, R. P.; Breedt, E.; Dhillon, V. S.; Gentile Fusillo, N. P.; Kerry, P.; Sahman, D. I.

2018-04-01

We present the discovery of SDSS J135154.46-064309.0, a short-period variable observed using 30-minute cadence photometry in K2 Campaign 6. Follow-up spectroscopy and high-speed photometry support a classification as a new member of the rare class of ultracompact accreting binaries known as AM CVn stars. The spectroscopic orbital period of 15.65 ± 0.12 minutes makes this system the fourth-shortest period AM CVn known, and the second system of this type to be discovered by the Kepler spacecraft. The K2 data show photometric periods at 15.7306 ± 0.0003 minutes, 16.1121 ± 0.0004 minutes and 664.82 ± 0.06 minutes, which we identify as the orbital period, superhump period, and disc precession period, respectively. From the superhump and orbital periods we estimate the binary mass ratio q = M2/M1 = 0.111 ± 0.005, though this method of mass ratio determination may not be well calibrated for helium-dominated binaries. This system is likely to be a bright foreground source of gravitational waves in the frequency range detectable by LISA, and may be of use as a calibration source if future studies are able to constrain the masses of its stellar components.

A 15.7-minAM CVn binary discovered in K2

NASA Astrophysics Data System (ADS)

Green, M. J.; Hermes, J. J.; Marsh, T. R.; Steeghs, D. T. H.; Bell, Keaton J.; Littlefair, S. P.; Parsons, S. G.; Dennihy, E.; Fuchs, J. T.; Reding, J. S.; Kaiser, B. C.; Ashley, R. P.; Breedt, E.; Dhillon, V. S.; Gentile Fusillo, N. P.; Kerry, P.; Sahman, D. I.

2018-07-01

We present the discovery of SDSS J135154.46-064309.0, a short-period variable observed using 30-mincadence photometry in K2 Campaign 6. Follow-up spectroscopy and high-speed photometry support a classification as a new member of the rare class of ultracompact accreting binaries known as AM CVn stars. The spectroscopic orbital period of 15.65 ± 0.12 min makes this system the fourth-shortest-period AM CVn known, and the second system of this type to be discovered by the Kepler spacecraft. The K2 data show photometric periods at 15.7306 ± 0.0003 min, 16.1121 ± 0.0004 min, and 664.82 ± 0.06 min, which we identify as the orbital period, superhump period, and disc precession period, respectively. From the superhump and orbital periods we estimate the binary mass ratio q = M2/M1= 0.111 ± 0.005, though this method of mass ratio determination may not be well calibrated for helium-dominated binaries. This system is likely to be a bright foreground source of gravitational waves in the frequency range detectable by Laser Interferometer Space Antenna, and may be of use as a calibration source if future studies are able to constrain the masses of its stellar components.

Prototype Expert System for Climate Classification.

ERIC Educational Resources Information Center

Harris, Clay

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

Confidence level estimation in multi-target classification problems

NASA Astrophysics Data System (ADS)

Chang, Shi; Isaacs, Jason; Fu, Bo; Shin, Jaejeong; Zhu, Pingping; Ferrari, Silvia

2018-04-01

This paper presents an approach for estimating the confidence level in automatic multi-target classification performed by an imaging sensor on an unmanned vehicle. An automatic target recognition algorithm comprised of a deep convolutional neural network in series with a support vector machine classifier detects and classifies targets based on the image matrix. The joint posterior probability mass function of target class, features, and classification estimates is learned from labeled data, and recursively updated as additional images become available. Based on the learned joint probability mass function, the approach presented in this paper predicts the expected confidence level of future target classifications, prior to obtaining new images. The proposed approach is tested with a set of simulated sonar image data. The numerical results show that the estimated confidence level provides a close approximation to the actual confidence level value determined a posteriori, i.e. after the new image is obtained by the on-board sensor. Therefore, the expected confidence level function presented in this paper can be used to adaptively plan the path of the unmanned vehicle so as to optimize the expected confidence levels and ensure that all targets are classified with satisfactory confidence after the path is executed.

The classification of gunshot residue using laser electrospray mass spectrometry and offline multivariate statistical analysis

USDA-ARS?s Scientific Manuscript database

Nonresonant laser vaporization combined with high-resolution electrospray time-of-flight mass spectrometry enables analysis of a casing after discharge of a firearm revealing organic signature molecules including methyl centralite (MC), diphenylamine (DPA), N-nitrosodiphenylamine (N-NO-DPA), 4-nitro...

Can cardiovascular MRI be used to more definitively characterize cardiac masses initially identified using echocardiography?

PubMed

Rathi, Vikas K; Czajka, Anna T; Thompson, Diane V; Doyle, Mark; Tewatia, Tarun; Yamrozik, June; Williams, Ronald B; Biederman, Robert W W

2018-05-01

In diagnosing cardiac and paracardiac masses, cardiac MRI (CMR) has gained acceptance as the gold standard. CMR has been observed to be superior to echocardiography in characterizing soft-tissue structures and, specifically, in classifying cardiac masses. The aim of our study was to evaluate the association between mortality and cardiac or paracardiac masses initially identified by echocardiography (ECHO) and confirmed by CMR. Between January 2002 and August 2007, a total of 158 patients underwent both ECHO and CMR for the evaluation of cardiac masses that were equivocal or undefined by ECHO. The primary study endpoints were 5-year all-cause mortality and 5-year cardiac mortality. Causes of death as of April 1, 2015 were obtained from medical records or the National Death Index. Patients were analyzed according to mass type determined by CMR using the Kruskal-Wallis test, Kaplan-Meier curves, and the log-rank test. Over a mean duration of follow-up of 10.4 ± 2.9 years (range: 0.01-12 years) post-CMR, the overall all-cause mortality rate was 25.9% (41/158). Median age at death was 76 years and there were 21 females (51.2%). Mortality rates in the different classifications of cardiac masses by CMR were as follows: 20% (1/5) in patients with a Nondiagnostic CMR; 20% (1/5) in Other Diagnoses; 17.9% (7/39) in No Masses (includes Normal Anatomical Variants); 16.7% (3/18) in Benign Masses; 23.8% (15/63) in Fat; 50% (5/10) in Thrombus; and 61.5% (8/13) in Malignant Mass. The mean survival time in patients with No Mass (n = 39) was not significantly longer than patients with any type of cardiac mass (n = 114) (P = .16). No significant difference was found in age at death between patients when grouped by CMR classification (P = .40). However, among CMR-confirmed masses, there were some significant differences by mass classification type (P = .006). During the follow-up period, 26% (41/158) of patients died and 22% (9/41) of the deaths were cardiovascular related; there was no significant difference in mean survival times with respect to cause of mortality (P = .23). In patients with cardiac masses, dually confirmed by ECHO and CMR, significant differences in survival time were observed based upon CMR classified type of mass while CMR was instrumental in obviating invasive biopsy. © 2018 Wiley Periodicals, Inc.

A new classification method for MALDI imaging mass spectrometry data acquired on formalin-fixed paraffin-embedded tissue samples.

PubMed

Boskamp, Tobias; Lachmund, Delf; Oetjen, Janina; Cordero Hernandez, Yovany; Trede, Dennis; Maass, Peter; Casadonte, Rita; Kriegsmann, Jörg; Warth, Arne; Dienemann, Hendrik; Weichert, Wilko; Kriegsmann, Mark

2017-07-01

Matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) shows a high potential for applications in histopathological diagnosis, and in particular for supporting tumor typing and subtyping. The development of such applications requires the extraction of spectral fingerprints that are relevant for the given tissue and the identification of biomarkers associated with these spectral patterns. We propose a novel data analysis method based on the extraction of characteristic spectral patterns (CSPs) that allow automated generation of classification models for spectral data. Formalin-fixed paraffin embedded (FFPE) tissue samples from N=445 patients assembled on 12 tissue microarrays were analyzed. The method was applied to discriminate primary lung and pancreatic cancer, as well as adenocarcinoma and squamous cell carcinoma of the lung. A classification accuracy of 100% and 82.8%, resp., could be achieved on core level, assessed by cross-validation. The method outperformed the more conventional classification method based on the extraction of individual m/z values in the first application, while achieving a comparable accuracy in the second. LC-MS/MS peptide identification demonstrated that the spectral features present in selected CSPs correspond to peptides relevant for the respective classification. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann. Copyright © 2016 Elsevier B.V. All rights reserved.

5 CFR 9901.221 - Classification requirements.

Code of Federal Regulations, 2011 CFR

2011-01-01

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

5 CFR 9701.221 - Classification requirements.

Code of Federal Regulations, 2013 CFR

2013-01-01

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

5 CFR 9701.221 - Classification requirements.

Code of Federal Regulations, 2012 CFR

2012-01-01

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

5 CFR 9701.221 - Classification requirements.

Code of Federal Regulations, 2014 CFR

2014-01-01

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

5 CFR 9701.221 - Classification requirements.

Code of Federal Regulations, 2011 CFR

2011-01-01

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

A method to assess obstetric outcomes using the 10-Group Classification System: a quantitative descriptive study

PubMed Central

Rossen, Janne; Lucovnik, Miha; Eggebø, Torbjørn Moe; Tul, Natasa; Murphy, Martina; Vistad, Ingvild; Robson, Michael

2017-01-01

Objectives Internationally, the 10-Group Classification System (TGCS) has been used to report caesarean section rates, but analysis of other outcomes is also recommended. We now aim to present the TGCS as a method to assess outcomes of labour and delivery using routine collection of perinatal information. Design This research is a methodological study to describe the use of the TGCS. Setting Stavanger University Hospital (SUH), Norway, National Maternity Hospital Dublin, Ireland and Slovenian National Perinatal Database (SLO), Slovenia. Participants 9848 women from SUH, Norway, 9250 women from National Maternity Hospital Dublin, Ireland and 106 167 women, from SLO, Slovenia. Main outcome measures All women were classified according to the TGCS within which caesarean section, oxytocin augmentation, epidural analgesia, operative vaginal deliveries, episiotomy, sphincter rupture, postpartum haemorrhage, blood transfusion, maternal age >35 years, body mass index >30, Apgar score, umbilical cord pH, hypoxic–ischaemic encephalopathy, antepartum and perinatal deaths were incorporated. Results There were significant differences in the sizes of the groups of women and the incidences of events and outcomes within the TGCS between the three perinatal databases. Conclusions The TGCS is a standardised objective classification system where events and outcomes of labour and delivery can be incorporated. Obstetric core events and outcomes should be agreed and defined to set standards of care. This method provides continuous and available observations from delivery wards, possibly used for further interpretation, questions and international comparisons. The definition of quality may vary in different units and can only be ascertained when all the necessary information is available and considered together. PMID:28706102

Using Abbreviated Injury Scale (AIS) codes to classify Computed Tomography (CT) features in the Marshall System.

PubMed

Lesko, Mehdi M; Woodford, Maralyn; White, Laura; O'Brien, Sarah J; Childs, Charmaine; Lecky, Fiona E

2010-08-06

The purpose of Abbreviated Injury Scale (AIS) is to code various types of Traumatic Brain Injuries (TBI) based on their anatomical location and severity. The Marshall CT Classification is used to identify those subgroups of brain injured patients at higher risk of deterioration or mortality. The purpose of this study is to determine whether and how AIS coding can be translated to the Marshall Classification Initially, a Marshall Class was allocated to each AIS code through cross-tabulation. This was agreed upon through several discussion meetings with experts from both fields (clinicians and AIS coders). Furthermore, in order to make this translation possible, some necessary assumptions with regards to coding and classification of mass lesions and brain swelling were essential which were all approved and made explicit. The proposed method involves two stages: firstly to determine all possible Marshall Classes which a given patient can attract based on allocated AIS codes; via cross-tabulation and secondly to assign one Marshall Class to each patient through an algorithm. This method can be easily programmed in computer softwares and it would enable future important TBI research programs using trauma registry data.

Using Abbreviated Injury Scale (AIS) codes to classify Computed Tomography (CT) features in the Marshall System

PubMed Central

2010-01-01

Background The purpose of Abbreviated Injury Scale (AIS) is to code various types of Traumatic Brain Injuries (TBI) based on their anatomical location and severity. The Marshall CT Classification is used to identify those subgroups of brain injured patients at higher risk of deterioration or mortality. The purpose of this study is to determine whether and how AIS coding can be translated to the Marshall Classification Methods Initially, a Marshall Class was allocated to each AIS code through cross-tabulation. This was agreed upon through several discussion meetings with experts from both fields (clinicians and AIS coders). Furthermore, in order to make this translation possible, some necessary assumptions with regards to coding and classification of mass lesions and brain swelling were essential which were all approved and made explicit. Results The proposed method involves two stages: firstly to determine all possible Marshall Classes which a given patient can attract based on allocated AIS codes; via cross-tabulation and secondly to assign one Marshall Class to each patient through an algorithm. Conclusion This method can be easily programmed in computer softwares and it would enable future important TBI research programs using trauma registry data. PMID:20691038

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

PubMed Central

Mages, Keith C

2011-01-01

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

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

DOT National Transportation Integrated Search

1996-02-01

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

A Multiwavelength Characterization of Proto-brown-dwarf Candidates in Serpens

NASA Astrophysics Data System (ADS)

Riaz, B.; Vorobyov, E.; Harsono, D.; Caselli, P.; Tikare, K.; Gonzalez-Martin, O.

2016-11-01

We present results from a deep submillimeter survey in the Serpens Main and Serpens/G3-G6 clusters, conducted with the Submillimetre Common-User Bolometer Array (SCUBA-2) at the James Clerk Maxwell Telescope. We have combined near- and mid-infrared spectroscopy, Herschel PACS far-infrared photometry, submillimeter continuum, and molecular gas line observations, with the aim of conducting a detailed multiwavelength characterization of “proto-brown-dwarf” (proto-BD) candidates in Serpens. We have performed continuum and line radiative transfer modeling and have considered various classification schemes to understand the structure and the evolutionary stage of the system. We have identified four proto-BD candidates, of which the lowest-luminosity source has an L bol ˜ 0.05 L ⊙. Two of these candidates show characteristics consistent with Stage 0/I systems, while the other two are Stage I-T/Class Flat systems with tenuous envelopes. Our work has also revealed a ˜20% fraction of misidentified Class 0/I/Flat sources that show characteristics consistent with Class II edge-on disk systems. We have set constraints on the mass of the central object using the measured bolometric luminosities and numerical simulations of stellar evolution. Considering the available gas+dust mass reservoir and the current mass of the central source, three of these candidates are likely to evolve into BDs.

A MULTIWAVELENGTH CHARACTERIZATION OF PROTO-BROWN-DWARF CANDIDATES IN SERPENS

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

Riaz, B.; Caselli, P.; Vorobyov, E.

2016-11-10

We present results from a deep submillimeter survey in the Serpens Main and Serpens/G3–G6 clusters, conducted with the Submillimetre Common-User Bolometer Array (SCUBA-2) at the James Clerk Maxwell Telescope. We have combined near- and mid-infrared spectroscopy, Herschel PACS far-infrared photometry, submillimeter continuum, and molecular gas line observations, with the aim of conducting a detailed multiwavelength characterization of “proto-brown-dwarf” (proto-BD) candidates in Serpens. We have performed continuum and line radiative transfer modeling and have considered various classification schemes to understand the structure and the evolutionary stage of the system. We have identified four proto-BD candidates, of which the lowest-luminosity source hasmore » an L {sub bol} ∼ 0.05 L {sub ☉}. Two of these candidates show characteristics consistent with Stage 0/I systems, while the other two are Stage I-T/Class Flat systems with tenuous envelopes. Our work has also revealed a ∼20% fraction of misidentified Class 0/I/Flat sources that show characteristics consistent with Class II edge-on disk systems. We have set constraints on the mass of the central object using the measured bolometric luminosities and numerical simulations of stellar evolution. Considering the available gas+dust mass reservoir and the current mass of the central source, three of these candidates are likely to evolve into BDs.« less

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

NASA Astrophysics Data System (ADS)

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

2014-07-01

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

An Application of Computerized Axial Tomography (CAT) Technology to Mass Raid Tracking

DTIC Science & Technology

1989-08-01

ESD-TR-89-305 MTR-10542 An Application of Computerized Axial Tomography ( CAT ) Technology to Mass Raid Tracking By John K. Barr August 1989...NO 11. TITLE (Include Security Classification) An Application of Computerized Axial Tomography ( CAT ) Technology to Mass Raid Tracking 12...by block number) Computerized Axial Tomography ( CAT ) Scanner Electronic Support Measures (ESM) Fusion (continued) 19. ABSTRACT (Continue on

From Stars to Super-Planets: The Low-Mass IMF in the Young Cluster IC348

NASA Technical Reports Server (NTRS)

Najita, Joan R.; Tiede, Glenn P.; Carr, John S.

2000-01-01

We investigate the low-mass population of the young cluster IC348 down to the deuterium-burning limit, a fiducial boundary between brown dwarf and planetary mass objects, using a new and innovative method for the spectral classification of late-type objects. Using photometric indices, constructed from HST/NICMOS narrow-band imaging, that measure the strength of the 1.9 micron water band, we determine the spectral type and reddening for every M-type star in the field, thereby separating cluster members from the interloper population. Due to the efficiency of our spectral classification technique, our study is complete from approximately 0.7 solar mass to 0.015 solar mass. The mass function derived for the cluster in this interval, dN/d log M alpha M(sup 0.5), is similar to that obtained for the Pleiades, but appears significantly more abundant in brown dwarfs than the mass function for companions to nearby sun-like stars. This provides compelling observational evidence for different formation and evolutionary histories for substellar objects formed in isolation vs. as companions. Because our determination of the IMF is complete to very low masses, we can place interesting constraints on the role of physical processes such as fragmentation in the star and planet formation process and the fraction of dark matter in the Galactic halo that resides in substellar objects.

Winter air-mass-based synoptic climatological approach and hospital admissions for myocardial infarction in Florence, Italy.

PubMed

Morabito, Marco; Crisci, Alfonso; Grifoni, Daniele; Orlandini, Simone; Cecchi, Lorenzo; Bacci, Laura; Modesti, Pietro Amedeo; Gensini, Gian Franco; Maracchi, Giampiero

2006-09-01

The aim of this study was to evaluate the relationship between the risk of hospital admission for myocardial infarction (MI) and the daily weather conditions during the winters of 1998-2003, according to an air-mass-based synoptic climatological approach. The effects of time lag and 2-day sequences with specific air mass types were also investigated. Studies concerning the relationship between atmospheric conditions and human health need to take into consideration simultaneous effects of many weather variables. At the moment few studies have surveyed these effects on hospitalizations for MI. Analyses were concentrated on winter, when the maximum peak of hospitalization occurred. An objective daily air mass classification by means of statistical analyses based on ground meteorological data was carried out. A comparison between air mass classification and hospital admissions was made by the calculation of a MI admission index, and to detect significant relationships the Mann-Whitney U test, the analysis of variance, and the Bonferroni test were used. Significant increases in hospital admissions for MI were evident 24h after a day characterized by an anticyclonic continental air mass and 6 days after a day characterized by a cyclonic air mass. Increased risk of hospitalization was found even when specific 2-day air mass sequences occurred. These results represent an important step in identifying reliable linkages between weather and health.

Social Sensors (S2ensors): A Kind of Hardware-Software-Integrated Mediators for Social Manufacturing Systems Under Mass Individualization

NASA Astrophysics Data System (ADS)

Ding, Kai; Jiang, Ping-Yu

2017-09-01

Currently, little work has been devoted to the mediators and tools for multi-role production interactions in the mass individualization environment. This paper proposes a kind of hardware-software-integrated mediators called social sensors (S2ensors) to facilitate the production interactions among customers, manufacturers, and other stakeholders in the social manufacturing systems (SMS). The concept, classification, operational logics, and formalization of S2ensors are clarified. S2ensors collect subjective data from physical sensors and objective data from sensory input in mobile Apps, merge them into meaningful information for decision-making, and finally feed the decisions back for reaction and execution. Then, an S2ensors-Cloud platform is discussed to integrate different S2ensors to work for SMSs in an autonomous way. A demonstrative case is studied by developing a prototype system and the results show that S2ensors and S2ensors-Cloud platform can assist multi-role stakeholders interact and collaborate for the production tasks. It reveals the mediator-enabled mechanisms and methods for production interactions among stakeholders in SMS.

Topological gaps without masses in driven graphene-like systems

NASA Astrophysics Data System (ADS)

Iadecola, Thomas; Neupert, Titus; Chamon, Claudio

2014-03-01

We illustrate the possibility of realizing band gaps in graphene-like systems that fall outside the existing classification of gapped Dirac Hamiltonians in terms of masses. As our primary example we consider a band gap arising due to time-dependent distortions of the honeycomb lattice. By means of an exact, invertible, and transport-preserving mapping to a time-independent Hamiltonian, we show that the system exhibits Chern-insulating phases with quantized Hall conductivities +/-e2 / h . The chirality of the corresponding gapless edge modes is controllable by both the frequency of the driving and the manner in which sublattice symmetry is broken by the dynamical lattice modulations. We demonstrate that, while these phases are in the same topological sector as the Haldane model, they are nevertheless separated from the latter by a gap-closing transition unless an extra parameter is added to the Hamiltonian. Finally, we discuss a promising possible realization of this physics in photonic lattices. This work is supported in part by DOE Grant DEF-06ER46316 (T.I. and C.C.).

A dynamical classification of the cosmic web

NASA Astrophysics Data System (ADS)

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

2009-07-01

In this paper, we propose a new dynamical classification of the cosmic web. Each point in space is classified in one of four possible web types: voids, sheets, filaments and knots. The classification is based on the evaluation of the deformation tensor (i.e. the Hessian of the gravitational potential) on a grid. The classification is based on counting the number of eigenvalues above a certain threshold, λth, at each grid point, where the case of zero, one, two or three such eigenvalues corresponds to void, sheet, filament or a knot grid point. The collection of neighbouring grid points, friends of friends, of the same web type constitutes voids, sheets, filaments and knots as extended web objects. A simple dynamical consideration of the emergence of the web suggests that the threshold should not be null, as in previous implementations of the algorithm. A detailed dynamical analysis would have found different threshold values for the collapse of sheets, filaments and knots. Short of such an analysis a phenomenological approach has been opted for, looking for a single threshold to be determined by analysing numerical simulations. Our cosmic web classification has been applied and tested against a suite of large (dark matter only) cosmological N-body simulations. In particular, the dependence of the volume and mass filling fractions on λth and on the resolution has been calculated for the four web types. We also study the percolation properties of voids and filaments. Our main findings are as follows. (i) Already at λth = 0.1 the resulting web classification reproduces the visual impression of the cosmic web. (ii) Between 0.2 <~ λth <~ 0.4, a system of percolated voids coexists with a net of interconnected filaments. This suggests a reasonable choice for λth as the parameter that defines the cosmic web. (iii) The dynamical nature of the suggested classification provides a robust framework for incorporating environmental information into galaxy formation models, and in particular to semi-analytical models.

Classifications of Acute Scaphoid Fractures: A Systematic Literature Review.

PubMed

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

2016-05-01

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

Classification of close binary systems by Svechnikov

NASA Astrophysics Data System (ADS)

Dryomova, G. N.

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

Recursive heuristic classification

NASA Technical Reports Server (NTRS)

Wilkins, David C.

1994-01-01

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

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

PubMed

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

2017-12-01

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

A New Tool for Climatic Analysis Using the Koppen Climate Classification

ERIC Educational Resources Information Center

Larson, Paul R.; Lohrengel, C. Frederick, II

2011-01-01

The purpose of climate classification is to help make order of the seemingly endless spatial distribution of climates. The Koppen classification system in a modified format is the most widely applied system in use today. This system may not be the best nor most complete climate classification that can be conceived, but it has gained widespread…

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

PubMed

Wong, Wai Keat; Shetty, Subhaschandra

2017-08-01

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

Construction of the bridge in the cavern in the Vrata tunnel (Croatia)

NASA Astrophysics Data System (ADS)

Garasic, Mladen; Sasa Kovacevic, Meho; Juric-Kacunic, Danijela

2010-05-01

In the Dinaric karst system in Croatia some 11500 speleological objects have been explored so far, more than 1000 of which were discovered during construction works. Such speleological objects without natural entrance on the terrain surface (which are called "caverns") have been discovered on the construction sites of the highways. Over the past twenty years they have been systematically investigated and treated. A special kind of remediation was conducted in the cavern's large hall of the "Vrata" tunnel on the Zagreb - Rijeka highway. Due to size, shape, cavern's position and hydrogeological parameters (fissured and karstified aquifers) within the karst system it was necessary to design and construct a 58 m bridge over the cavern. In addition, the cavern's vault had to be reinforced and stabilized, as the overburden was very thin. The beam-and -stringer grid with special anchors was used. The cavern's rehabilitation in the "Vrata" tunnel was a unique undertaking, and the bridge (without piers) is the cavern's longest bridge in the world. A speleological object of large dimensions was discovered in the "Vrata"tunnel's right tube on the Rijeka-Zagreb highway. Speleological, geotechnical, engineering geological and hydrogeological investigation works were carried out for the purpose of preservation the speleological object (cavern). On the basis of classification results of rock masses and conducted numerical analyses the support system for the cavern's vault stabilization was selected. The support system's elements include the beam-and-stringer grid constructed on the terrain's surface above the cavern, tendons and geotechnical anchors. To ensure stability of the speleological object, and to conduct the backward numerical analyses the measurement of vertical deformations from the terrain's surface along the rock's mass by means of sliding micrometers was undertaken. Backward numerical analyses combined with geotechnical measurements enable safer and more rational approach to design and construction of underground structures. They contribute to the knowledge on rock mass performance and to determination of its physical and mechanical parameters connecting them with rock classification results. The analyses are a great help in verification or modification of elements' features of primary support system. Tunnel and bridge in tunnel "Vrata" were opened for traffic in November 2008. Keywords: speleology, cave, Dinaric karst, Croatia, tunnel, karst phenomena, geotechnical engineering.

Availability of MudPIT data for classification of biological samples.

PubMed

Silvestre, Dario Di; Zoppis, Italo; Brambilla, Francesca; Bellettato, Valeria; Mauri, Giancarlo; Mauri, Pierluigi

2013-01-14

Mass spectrometry is an important analytical tool for clinical proteomics. Primarily employed for biomarker discovery, it is increasingly used for developing methods which may help to provide unambiguous diagnosis of biological samples. In this context, we investigated the classification of phenotypes by applying support vector machine (SVM) on experimental data obtained by MudPIT approach. In particular, we compared the performance capabilities of SVM by using two independent collection of complex samples and different data-types, such as mass spectra (m/z), peptides and proteins. Globally, protein and peptide data allowed a better discriminant informative content than experimental mass spectra (overall accuracy higher than 87% in both collection 1 and 2). These results indicate that sequencing of peptides and proteins reduces the experimental noise affecting the raw mass spectra, and allows the extraction of more informative features available for the effective classification of samples. In addition, proteins and peptides features selected by SVM matched for 80% with the differentially expressed proteins identified by the MAProMa software. These findings confirm the availability of the most label-free quantitative methods based on processing of spectral count and SEQUEST-based SCORE values. On the other hand, it stresses the usefulness of MudPIT data for a correct grouping of sample phenotypes, by applying both supervised and unsupervised learning algorithms. This capacity permit the evaluation of actual samples and it is a good starting point to translate proteomic methodology to clinical application.

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

PubMed

Krause, Fabian G; Di Silvestro, Matthew; Penner, Murray J; Wing, Kevin J; Glazebrook, Mark A; Daniels, Timothy R; Lau, Johnny T C; Younger, Alastair S E

2012-02-01

End-stage ankle arthritis is operatively treated with numerous designs of total ankle replacement and different techniques for ankle fusion. For superior comparison of these procedures, outcome research requires a classification system to stratify patients appropriately. A postoperative 4-type classification system was designed by 6 fellowship-trained foot and ankle surgeons. Four surgeons reviewed blinded patient profiles and radiographs on 2 occasions to determine the interobserver and intraobserver reliability of the classification. Excellent interobserver reliability (κ = .89) and intraobserver reproducibility (κ = .87) were demonstrated for the postoperative classification system. In conclusion, the postoperative Canadian Orthopaedic Foot and Ankle Society (COFAS) end-stage ankle arthritis classification system appears to be a valid tool to evaluate the outcome of patients operated for end-stage ankle arthritis.

Railroad Classification Yard Technology Manual: Volume II : Yard Computer Systems

DOT National Transportation Integrated Search

1981-08-01

This volume (Volume II) of the Railroad Classification Yard Technology Manual documents the railroad classification yard computer systems methodology. The subjects covered are: functional description of process control and inventory computer systems,...

Cause of and factors associated with stillbirth: a systematic review of classification systems.

PubMed

Aminu, Mamuda; Bar-Zeev, Sarah; van den Broek, Nynke

2017-05-01

An estimated 2.6 million stillbirths occur worldwide each year. A standardized classification system setting out possible cause of death and contributing factors is useful to help obtain comparative data across different settings. We undertook a systematic review of stillbirth classification systems to highlight their strengths and weaknesses for practitioners and policymakers. We conducted a systematic search and review of the literature to identify the classification systems used to aggregate information for stillbirth and perinatal deaths. Narrative synthesis was used to compare the range and depth of information required to apply the systems, and the different categories provided for cause of and factors contributing to stillbirth. A total of 118 documents were screened; 31 classification systems were included, of which six were designed specifically for stillbirth, 14 for perinatal death, three systems included neonatal deaths and two included infant deaths. Most (27/31) were developed in and first tested using data obtained from high-income settings. All systems required information from clinical records. One-third of the classification systems (11/31) included information obtained from histology or autopsy. The percentage where cause of death remained unknown ranged from 0.39% using the Nordic-Baltic classification to 46.4% using the Keeling system. Over time, classification systems have become more complex. The success of application is dependent on the availability of detailed clinical information and laboratory investigations. Systems that adopt a layered approach allow for classification of cause of death to a broad as well as to a more detailed level. © 2017 The Authors. Acta Obstetricia et Gynecologica Scandinavica published by John Wiley & Sons Ltd on behalf of Nordic Federation of Societies of Obstetrics and Gynecology (NFOG).

Light extinction by fine atmospheric particles in the White Mountains region of New Hampshire and its relationship to air mass transport.

PubMed

Slater, John F; Dibb, Jack E; Keim, Barry D; Talbot, Robert W

2002-03-27

Chemical, optical, and physical measurements of fine aerosols (aerodynamic diameter < or = 2.5 microm) have been performed at a mountaintop location adjacent to the White Mountain National Forest in northern NH, USA. A 1-month long sampling campaign was conducted at Cranmore Mountain during spring 2000. We report on the apportionment of light extinction by fine aerosols into its major chemical components, and relationships between variations in aerosol parameters and changes in air mass origin. Filter-based, 24-h integrated samples were collected and analyzed for major inorganic ions, as well as organic (OC), elemental (EC), and total carbon. Light scattering and light absorption coefficients were measured at 5-min intervals using an integrating nephelometer and a light absorption photometer. Fine particle number density was measured with a condensation particle counter. Air mass origins and transport patterns were investigated through the use of 3-day backward trajectories and a synoptic climate classification system. Two distinct transport regimes were observed: (1) flow from the north/northeast (N/NE) occurred during 9 out of 18 sample-days; and (2) flow from the west/southwest (W/SW) occurred 8 out of 18 sample-days. All measured and derived aerosol and meteorological parameters were separated into two categories based on these different flow scenarios. During W/SW flow, higher values of aerosol chemical concentration, absorption and scattering coefficients, number density, and haziness were observed compared to N/NE flow. The highest level of haziness was associated with the climate classification Frontal Atlantic Return, which brought polluted air into the region from the mid-Atlantic corridor. Fine particle mass scattering efficiencies of (NH4)2SO4 and OC were 5.35 +/- 0.42 m2 g(-1) and 1.56 +/- 0.40 m2 g(-1), respectively, when transport was out of the N/NE. When transport was from the W/SW the values were 4.94 +/- 0.68 m2 g(-1) for (NH4)2SO4 and 2.18 +/- 0.91 m2 g(-1) for OC. EC mass absorption efficiency when transport was from the N/NE was 9.66 +/- 1.06 m2 g(-1) and 10.80 +/- 1.76 m2 g(-1) when transport was from the W/SW. Results from this work can be used to predict visual air quality in the White Mountain National Forest based on a forecasted synoptic climate classification and its associated visibility.

Mass Spectral Studies of 1-(2-Chloroethoxy)-2-[(2-chloroethyl)thio] Ethane and Related Compounds Using Gas ChromatographyMass Spectrometry and Gas ChromatographyTriple-Quadrupole Mass Spectrometry

DTIC Science & Technology

2016-02-01

NOTES 14. ABSTRACT: The electron impact and collision-induced- dissociation mass spectra of 1-(2-chloroethoxy)-2-[(2-chloroethyl)thio] ethane and 10...Collision-ion dissociation (CID) Triple-quadrupole mass spectrometry (QQQ) 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT...ratio, 10:1), and a 1.0 µL volume of sample was placed on the column. Nitrogen was used as the collision gas for the collision-induced dissociation (CID

Modeling the Impact of Baryons on Subhalo Populations with Machine Learning

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

Nadler, Ethan O.; Mao, Yao -Yuan; Wechsler, Risa H.

Here, we identify subhalos in dark matter–only (DMO) zoom-in simulations that are likely to be disrupted due to baryonic effects by using a random forest classifier trained on two hydrodynamic simulations of Milky Way (MW)–mass host halos from the Latte suite of the Feedback in Realistic Environments (FIRE) project. We train our classifier using five properties of each disrupted and surviving subhalo: pericentric distance and scale factor at first pericentric passage after accretion and scale factor, virial mass, and maximum circular velocity at accretion. Our five-property classifier identifies disrupted subhalos in the FIRE simulations with an 85% out-of-bag classification score.more » We predict surviving subhalo populations in DMO simulations of the FIRE host halos, finding excellent agreement with the hydrodynamic results; in particular, our classifier outperforms DMO zoom-in simulations that include the gravitational potential of the central galactic disk in each hydrodynamic simulation, indicating that it captures both the dynamical effects of a central disk and additional baryonic physics. We also predict surviving subhalo populations for a suite of DMO zoom-in simulations of MW-mass host halos, finding that baryons impact each system consistently and that the predicted amount of subhalo disruption is larger than the host-to-host scatter among the subhalo populations. Although the small size and specific baryonic physics prescription of our training set limits the generality of our results, our work suggests that machine-learning classification algorithms trained on hydrodynamic zoom-in simulations can efficiently predict realistic subhalo populations.« less

Modeling the Impact of Baryons on Subhalo Populations with Machine Learning

DOE PAGES

Nadler, Ethan O.; Mao, Yao -Yuan; Wechsler, Risa H.; ...

2018-06-01

Here, we identify subhalos in dark matter–only (DMO) zoom-in simulations that are likely to be disrupted due to baryonic effects by using a random forest classifier trained on two hydrodynamic simulations of Milky Way (MW)–mass host halos from the Latte suite of the Feedback in Realistic Environments (FIRE) project. We train our classifier using five properties of each disrupted and surviving subhalo: pericentric distance and scale factor at first pericentric passage after accretion and scale factor, virial mass, and maximum circular velocity at accretion. Our five-property classifier identifies disrupted subhalos in the FIRE simulations with an 85% out-of-bag classification score.more » We predict surviving subhalo populations in DMO simulations of the FIRE host halos, finding excellent agreement with the hydrodynamic results; in particular, our classifier outperforms DMO zoom-in simulations that include the gravitational potential of the central galactic disk in each hydrodynamic simulation, indicating that it captures both the dynamical effects of a central disk and additional baryonic physics. We also predict surviving subhalo populations for a suite of DMO zoom-in simulations of MW-mass host halos, finding that baryons impact each system consistently and that the predicted amount of subhalo disruption is larger than the host-to-host scatter among the subhalo populations. Although the small size and specific baryonic physics prescription of our training set limits the generality of our results, our work suggests that machine-learning classification algorithms trained on hydrodynamic zoom-in simulations can efficiently predict realistic subhalo populations.« less

Pseudogynecomastia after massive weight loss: detectability of technique, patient satisfaction, and classification.

PubMed

Gusenoff, Jeffrey A; Coon, Devin; Rubin, J Peter

2008-11-01

An increasing number of male patients are presenting for treatment of male chest deformity after massive weight loss. The authors prefer to preserve the nipple-areola complex on a dermoglandular pedicle. They sought to identify detectability of technique, assess patient satisfaction, and outline a treatment algorithm for this population. Ten male massive weight loss patients underwent chest-contouring procedures over a period of 6 years and were surveyed to identify satisfaction with reconstruction. Preoperative photographs were used to devise a classification system. Twenty-seven medical professionals evaluated and rated digital photographs of the patients. Eight patients had pedicled reconstructions and two had free-nipple grafts. Mean age was 42.9 +/- 9.5 years, mean pre-weight loss body mass index was 54.1 +/- 10.6, post-weight loss body mass index was 29.4 +/- 4.5, and mean change in body mass index was 24.8 +/- 9.7. All patients would have surgery again, nine would recommend it to a friend, six would go shirtless in public, nine reported no loss of nipple sensation, and three reported dysesthesias of the nipple-areola complex. Medical professionals reproducibly associated poor wound healing with free-nipple grafting and rated poorly positioned nipple-areola complexes with low aesthetic scores. Medical professional scores for chest contour and nipple-areola complex aesthetics did not correlate with technique and were lower than scores provided by the patients. Patient satisfaction for treatment of the male chest deformity after massive weight loss is high. In carefully selected patients, preservation of the nipple-areola complex on a dermoglandular pedicle can aid in achieving an optimal aesthetic result.

Maternal vascular malperfusion of the placental bed associated with hypertensive disorders in the Boston Birth Cohort.

PubMed

Bustamante Helfrich, Blandine; Chilukuri, Nymisha; He, Huan; Cerda, Sandra R; Hong, Xiumei; Wang, Guoying; Pearson, Colleen; Burd, Irina; Wang, Xiaobin

2017-04-01

The associations of maternal conditions, before or during pregnancy, with placental lesions have not been adequately studied in populations. In the Boston Birth Cohort, we evaluated associations between three maternal medical conditions (hypertensive disorders [HDs], gestational/pre-gestational diabetes and obesity), and placental histological findings, using a standardized classification system proposed by the Amsterdam Placental Workshop Group. Placental pathology diagnoses and clinical data from 3074 mothers with clinical indications who delivered singleton live births at the Boston Medical Center between October 1998 and November 2013 were evaluated. Associations between each maternal condition and maternal vascular malperfusion (MVM) of the placental bed and its standardized subgroups were examined using multivariate logistic and multinomial regressions. Women with HDs (chronic hypertension, eclampsia, preeclampsia, HELLP syndrome) had significantly increased odds of MVM lesions when compared to women with no HD (aOR 2.08 95% CI 1.74-2.50), after adjusting for demographics, substance use, diabetes and body mass index. No significant differences in frequencies or aORs were seen in women with and without diabetes, or across body mass index categories. Co-morbid condition patterns that included HDs were more likely to be associated with MVM than those without. Using a standardized classification system, we showed that MVM is strongly and specifically associated with maternal HDs, but not other maternal conditions. Additional studies are needed to confirm and validate our findings, and evaluate the role of maternal vascular lesions of the placental bed in relation to postnatal growth and development of the offspring and effect modifiers. Copyright © 2017 Elsevier Ltd. All rights reserved.

Breast US as primary imaging modality for diagnosing gynecomastia

PubMed Central

TELEGRAFO, M.; INTRONA, T.; COI, L.; CORNACCHIA, I.; RELLA, L.; IANORA, A.A. STABILE; ANGELELLI, G.; MOSCHETTA, M.

2016-01-01

Aim To assess the role of breast US in diagnosing and classifying gynecomastia as the primary imaging modality and to compare US findings and classification system with the mammographic ones. Patients and methods 48 patients suspected of having gynecomastia underwent mammography and US. Two radiologists in consensus retrospectively evaluated mammograms and sonograms. Both US and mammographic images were evaluated categorizing gynecomastia into non-mass, nodular and flame shaped patterns. The two category assignations were compared in order to find any difference. The reference standard for both the classification systems was represented by the cytological examination in 18 out of 44 cases (41%) and the six-month US follow-up in the remaining cases. Results The US examination revealed pseudo-gynecomastia in 4/48 (8%) and true gynecomastia in the remaining 44 (92%). Gynecomastia was bilateral in 25/44 cases (57%) and unilateral in the remaining 19 (43%). The cases of true gynecomastia included non mass shape in 26/44 cases (59%), nodular shape in 12 (27%) and flame shape in 6 (14%). The mammographic examination revealed the same results as compared with US findings. 18/44 (41%) patients affected by nodular or dendritic gynecomastia underwent cytological examination confirming the presence of glandular tissue and the benign nature of the clinical condition. Conclusions US could be proposed as the primary imaging tool for diagnosing and classifying gynecomastia, avoiding unnecessary X-ray examinations or invasive procedures in case of diffuse gynecomastia. In case of nodular or dendritic patterns, biopsy remains mandatory for a definitive diagnosis. PMID:27734795

Automated structural classification of lipids by machine learning.

PubMed

Taylor, Ryan; Miller, Ryan H; Miller, Ryan D; Porter, Michael; Dalgleish, James; Prince, John T

2015-03-01

Modern lipidomics is largely dependent upon structural ontologies because of the great diversity exhibited in the lipidome, but no automated lipid classification exists to facilitate this partitioning. The size of the putative lipidome far exceeds the number currently classified, despite a decade of work. Automated classification would benefit ongoing classification efforts by decreasing the time needed and increasing the accuracy of classification while providing classifications for mass spectral identification algorithms. We introduce a tool that automates classification into the LIPID MAPS ontology of known lipids with >95% accuracy and novel lipids with 63% accuracy. The classification is based upon simple chemical characteristics and modern machine learning algorithms. The decision trees produced are intelligible and can be used to clarify implicit assumptions about the current LIPID MAPS classification scheme. These characteristics and decision trees are made available to facilitate alternative implementations. We also discovered many hundreds of lipids that are currently misclassified in the LIPID MAPS database, strongly underscoring the need for automated classification. Source code and chemical characteristic lists as SMARTS search strings are available under an open-source license at https://www.github.com/princelab/lipid_classifier. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Searching bioremediation patents through Cooperative Patent Classification (CPC).

PubMed

Prasad, Rajendra

2016-03-01

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

Identification of phenological stages and vegetative types for land use classification

NASA Technical Reports Server (NTRS)

Mckendrick, J. D. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Classification of digital data for mapping Alaskan vegetation has been compared to ground truth data and found to have accuracies as high as 90%. These classifications are broad scale types as are currently being used on the Major Ecosystems of Alaska map prepared by the Joint Federal-State Land Use Planning Commission for Alaska. Cost estimates for several options using the ERTS-1 digital data to map the Alaskan land mass at the 1:250,000 scale ranged between $2.17 to $1.49 per square mile.

Source identification of western Oregon Douglas-fir wood cores using mass spectrometry and random forest classification.

PubMed

Finch, Kristen; Espinoza, Edgard; Jones, F Andrew; Cronn, Richard

2017-05-01

We investigated whether wood metabolite profiles from direct analysis in real time (time-of-flight) mass spectrometry (DART-TOFMS) could be used to determine the geographic origin of Douglas-fir wood cores originating from two regions in western Oregon, USA. Three annual ring mass spectra were obtained from 188 adult Douglas-fir trees, and these were analyzed using random forest models to determine whether samples could be classified to geographic origin, growth year, or growth year and geographic origin. Specific wood molecules that contributed to geographic discrimination were identified. Douglas-fir mass spectra could be differentiated into two geographic classes with an accuracy between 70% and 76%. Classification models could not accurately classify sample mass spectra based on growth year. Thirty-two molecules were identified as key for classifying western Oregon Douglas-fir wood cores to geographic origin. DART-TOFMS is capable of detecting minute but regionally informative differences in wood molecules over a small geographic scale, and these differences made it possible to predict the geographic origin of Douglas-fir wood with moderate accuracy. Studies involving DART-TOFMS, alone and in combination with other technologies, will be relevant for identifying the geographic origin of illegally harvested wood.

Identification of patients with nasopharyngeal carcinoma by serum protein profiling using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry.

PubMed

Zhu, Xiao-Dong; Su, Fang; Liang, Zhong-Guo; Li, Ling; Qu, Song; Liang, Xia; Wang, Qi; Liang, Shi-Xiong; Chen, Long

2014-08-01

As diagnosis of nasopharyngeal carcinoma at an early disease stage is important, we attempted to distinguish between patients with nasopharyngeal carcinoma and noncancer controls by using serum protein profiles. Surface-enhanced laser desorption/ionization time-of-flight mass spectrometry and CM10 protein chip were used to detect the serum proteomic patterns of 65 patients with nasopharyngeal carcinoma before radiotherapy and 93 noncancer controls. Proteomic spectra of serum samples from 50 nasopharyngeal carcinoma patients and 60 noncancer controls were used as a training set. The validity of the classification tree was then challenged with a blind test set which included another 15 patients with nasopharyngeal carcinoma and 33 noncancer controls. Biomarker Wizard 3.01 and Biomarker Pattern 5.01 were used in combination to analyze the data and to develop diagnostic models. 21 protein peaks were significantly different between nasopharyngeal carcinoma and controls. 4 mass peaks (M4182, M5343, M5913 and M8702 mass/charge ratio) were chosen automatically to construct a classification tree. The classification tree correctly determined 93.8 % (45/48) of the test samples with 93.3 % (14/15) of the nasopharyngeal carcinoma samples and 93.9 % (31/33) of the noncancer samples. Using a combination of serum protein profiles and Epstein-Barr viral capsid antigen immunoglobulin A antibody tests, the diagnostic sensitivity and specificity were increased to 100 and 97 %, respectively. Surface-enhanced laser desorption/ionization time-of-flight mass spectrometry could correctly distinguish nasopharyngeal carcinoma from noncancer individuals and showed great potential for the development of a screening test for the detection of nasopharyngeal carcinoma.

Diagnosis of major depressive disorder by combining multimodal information from heart rate dynamics and serum proteomics using machine-learning algorithm.

PubMed

Kim, Eun Young; Lee, Min Young; Kim, Se Hyun; Ha, Kyooseob; Kim, Kwang Pyo; Ahn, Yong Min

2017-06-02

Major depressive disorder (MDD) is a systemic and multifactorial disorder that involves abnormalities in multiple biochemical pathways and the autonomic nervous system. This study applied a machine-learning method to classify MDD and control groups by incorporating data from serum proteomic analysis and heart rate variability (HRV) analysis for the identification of novel peripheral biomarkers. The study subjects consisted of 25 drug-free female MDD patients and 25 age- and sex-matched healthy controls. First, quantitative serum proteome profiles were analyzed by liquid chromatography-tandem mass spectrometry using pooled serum samples from 10 patients and 10 controls. Next, candidate proteins were quantified with multiple reaction monitoring (MRM) in 50 subjects. We also analyzed 22 linear and nonlinear HRV parameters in 50 subjects. Finally, we identified a combined biomarker panel consisting of proteins and HRV indexes using a support vector machine with recursive feature elimination. A separation between MDD and control groups was achieved using five parameters (apolipoprotein B, group-specific component, ceruloplasmin, RMSSD, and SampEn) at 80.1% classification accuracy. A combination of HRV and proteomic data achieved better classification accuracy. A high classification accuracy can be achieved by combining multimodal information from heart rate dynamics and serum proteomics in MDD. Our approach can be helpful for accurate clinical diagnosis of MDD. Further studies using larger, independent cohorts are needed to verify the role of these candidate biomarkers for MDD diagnosis. Copyright © 2017 Elsevier Inc. All rights reserved.

Adverse events following cervical manipulative therapy: consensus on classification among Dutch medical specialists, manual therapists, and patients.

PubMed

Kranenburg, Hendrikus A; Lakke, Sandra E; Schmitt, Maarten A; Van der Schans, Cees P

2017-12-01

To obtain consensus-based agreement on a classification system of adverse events (AE) following cervical spinal manipulation. The classification system should be comprised of clear definitions, include patients' and clinicians' perspectives, and have an acceptable number of categories. Design : A three-round Delphi study. Participants : Thirty Dutch participants (medical specialists, manual therapists, and patients) participated in an online survey. Procedure : Participants inventoried AE and were asked about their preferences for either a three- or a four-category classification system. The identified AE were classified by two analysts following the International Classification of Functioning, Disability and Health (ICF), and the International Classification of Diseases and Related Health Problems (ICD-10). Participants were asked to classify the severity for all AE in relation to the time duration. Consensus occurred in a three-category classification system. There was strong consensus for 16 AE in all severities (no, minor, and major AE) and all three time durations [hours, days, weeks]. The 16 AE included anxiety, flushing, skin rash, fainting, dizziness, coma, altered sensation, muscle tenderness, pain, increased pain during movement, radiating pain, dislocation, fracture, transient ischemic attack, stroke, and death. Mild to strong consensus was reached for 13 AE. A consensus-based classification system of AE is established which includes patients' and clinicians' perspectives and has three categories. The classification comprises a precise description of potential AE in accordance with internationally accepted classifications. After international validation, clinicians and researchers may use this AE classification system to report AE in clinical practice and research.

Polyp morphology: an interobserver evaluation for the Paris classification among international experts.

PubMed

van Doorn, Sascha C; Hazewinkel, Y; East, James E; van Leerdam, Monique E; Rastogi, Amit; Pellisé, Maria; Sanduleanu-Dascalescu, Silvia; Bastiaansen, Barbara A J; Fockens, Paul; Dekker, Evelien

2015-01-01

The Paris classification is an international classification system for describing polyp morphology. Thus far, the validity and reproducibility of this classification have not been assessed. We aimed to determine the interobserver agreement for the Paris classification among seven Western expert endoscopists. A total of 85 short endoscopic video clips depicting polyps were created and assessed by seven expert endoscopists according to the Paris classification. After a digital training module, the same 85 polyps were assessed again. We calculated the interobserver agreement with a Fleiss kappa and as the proportion of pairwise agreement. The interobserver agreement of the Paris classification among seven experts was moderate with a Fleiss kappa of 0.42 and a mean pairwise agreement of 67%. The proportion of lesions assessed as "flat" by the experts ranged between 13 and 40% (P<0.001). After the digital training, the interobserver agreement did not change (kappa 0.38, pairwise agreement 60%). Our study is the first to validate the Paris classification for polyp morphology. We demonstrated only a moderate interobserver agreement among international Western experts for this classification system. Our data suggest that, in its current version, the use of this classification system in daily practice is questionable and it is unsuitable for comparative endoscopic research. We therefore suggest introduction of a simplification of the classification system.

5 CFR 9701.222 - Reconsideration of classification decisions.

Code of Federal Regulations, 2012 CFR

2012-01-01

... RESOURCES MANAGEMENT SYSTEM (DEPARTMENT OF HOMELAND SECURITY-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM Classification Classification Process § 9701.222...

5 CFR 9701.222 - Reconsideration of classification decisions.

Code of Federal Regulations, 2013 CFR

2013-01-01

... RESOURCES MANAGEMENT SYSTEM (DEPARTMENT OF HOMELAND SECURITY-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM Classification Classification Process § 9701.222...

5 CFR 9701.222 - Reconsideration of classification decisions.

Code of Federal Regulations, 2014 CFR

2014-01-01

... RESOURCES MANAGEMENT SYSTEM (DEPARTMENT OF HOMELAND SECURITY-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM Classification Classification Process § 9701.222...

5 CFR 9701.222 - Reconsideration of classification decisions.

Code of Federal Regulations, 2011 CFR

2011-01-01

... RESOURCES MANAGEMENT SYSTEM (DEPARTMENT OF HOMELAND SECURITY-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM Classification Classification Process § 9701.222...

Lattice Boltzmann simulation of the gas-solid adsorption process in reconstructed random porous media.

PubMed

Zhou, L; Qu, Z G; Ding, T; Miao, J Y

2016-04-01

The gas-solid adsorption process in reconstructed random porous media is numerically studied with the lattice Boltzmann (LB) method at the pore scale with consideration of interparticle, interfacial, and intraparticle mass transfer performances. Adsorbent structures are reconstructed in two dimensions by employing the quartet structure generation set approach. To implement boundary conditions accurately, all the porous interfacial nodes are recognized and classified into 14 types using a proposed universal program called the boundary recognition and classification program. The multiple-relaxation-time LB model and single-relaxation-time LB model are adopted to simulate flow and mass transport, respectively. The interparticle, interfacial, and intraparticle mass transfer capacities are evaluated with the permeability factor and interparticle transfer coefficient, Langmuir adsorption kinetics, and the solid diffusion model, respectively. Adsorption processes are performed in two groups of adsorbent media with different porosities and particle sizes. External and internal mass transfer resistances govern the adsorption system. A large porosity leads to an early time for adsorption equilibrium because of the controlling factor of external resistance. External and internal resistances are dominant at small and large particle sizes, respectively. Particle size, under which the total resistance is minimum, ranges from 3 to 7 μm with the preset parameters. Pore-scale simulation clearly explains the effect of both external and internal mass transfer resistances. The present paper provides both theoretical and practical guidance for the design and optimization of adsorption systems.

Lattice Boltzmann simulation of the gas-solid adsorption process in reconstructed random porous media

NASA Astrophysics Data System (ADS)

Zhou, L.; Qu, Z. G.; Ding, T.; Miao, J. Y.

2016-04-01

The gas-solid adsorption process in reconstructed random porous media is numerically studied with the lattice Boltzmann (LB) method at the pore scale with consideration of interparticle, interfacial, and intraparticle mass transfer performances. Adsorbent structures are reconstructed in two dimensions by employing the quartet structure generation set approach. To implement boundary conditions accurately, all the porous interfacial nodes are recognized and classified into 14 types using a proposed universal program called the boundary recognition and classification program. The multiple-relaxation-time LB model and single-relaxation-time LB model are adopted to simulate flow and mass transport, respectively. The interparticle, interfacial, and intraparticle mass transfer capacities are evaluated with the permeability factor and interparticle transfer coefficient, Langmuir adsorption kinetics, and the solid diffusion model, respectively. Adsorption processes are performed in two groups of adsorbent media with different porosities and particle sizes. External and internal mass transfer resistances govern the adsorption system. A large porosity leads to an early time for adsorption equilibrium because of the controlling factor of external resistance. External and internal resistances are dominant at small and large particle sizes, respectively. Particle size, under which the total resistance is minimum, ranges from 3 to 7 μm with the preset parameters. Pore-scale simulation clearly explains the effect of both external and internal mass transfer resistances. The present paper provides both theoretical and practical guidance for the design and optimization of adsorption systems.

An objective classification system of air mass types for Szeged, Hungary, with special attention to plant pollen levels.

PubMed

Makra, László; Juhász, Miklós; Mika, János; Bartzokas, Aristides; Béczi, Rita; Sümeghy, Zoltán

2006-07-01

This paper discusses the characteristic air mass types over the Carpathian Basin in relation to plant pollen levels over annual pollination periods. Based on the European Centre for Medium-Range Weather Forecasts dataset, daily sea-level pressure fields analysed at 00 UTC were prepared for each air mass type (cluster) in order to relate sea-level pressure patterns to pollen levels in Szeged, Hungary. The database comprises daily values of 12 meteorological parameters and daily pollen concentrations of 24 species for their pollination periods from 1997 to 2001. Characteristic air mass types were objectively defined via factor analysis and cluster analysis. According to the results, nine air mass types (clusters) were detected for pollination periods of the year corresponding to pollen levels that appear with higher concentration when irradiance is moderate while wind speed is moderate or high. This is the case when an anticyclone prevails in the region west of the Carpathian Basin and when Hungary is under the influence of zonal currents (wind speed is high). The sea level pressure systems associated with low pollen concentrations are mostly similar to those connected to higher pollen concentrations, and arise when wind speed is low or moderate. Low pollen levels occur when an anticyclone prevails in the region west of the Carpathian Basin, as well as when an anticyclone covers the region with Hungary at its centre. Hence, anticyclonic or anticyclonic ridge weather situations seem to be relevant in classifying pollen levels.

Multi-element analysis of wines by ICP-MS and ICP-OES and their classification according to geographical origin in Slovenia.

PubMed

Selih, Vid S; Sala, Martin; Drgan, Viktor

2014-06-15

Inductively coupled plasma mass spectrometry and optical emission were used to determine the multi-element composition of 272 bottled Slovenian wines. To achieve geographical classification of the wines by their elemental composition, principal component analysis (PCA) and counter-propagation artificial neural networks (CPANN) have been used. From 49 elements measured, 19 were used to build the final classification models. CPANN was used for the final predictions because of its superior results. The best model gave 82% correct predictions for external set of the white wine samples. Taking into account the small size of whole Slovenian wine growing regions, we consider the classification results were very good. For the red wines, which were mostly represented from one region, even-sub region classification was possible with great precision. From the level maps of the CPANN model, some of the most important elements for classification were identified. Copyright © 2013 Elsevier Ltd. All rights reserved.

How a national vegetation classification can help ecological research and management

USGS Publications Warehouse

Franklin, Scott; Comer, Patrick; Evens, Julie; Ezcurra, Exequiel; Faber-Langendoen, Don; Franklin, Janet; Jennings, Michael; Josse, Carmen; Lea, Chris; Loucks, Orie; Muldavin, Esteban; Peet, Robert K.; Ponomarenko, Serguei; Roberts, David G.; Solomeshch, Ayzik; Keeler-Wolf, Todd; Van Kley, James; Weakley, Alan; McKerrow, Alexa; Burke, Marianne; Spurrier, Carol

2015-01-01

The elegance of classification lies in its ability to compile and systematize various terminological conventions and masses of information that are unattainable during typical research projects. Imagine a discipline without standards for collection, analysis, and interpretation; unfortunately, that describes much of 20th-century vegetation ecology. With differing methods, how do we assess community dynamics over decades, much less centuries? How do we compare plant communities from different areas? The need for a widely applied vegetation classification has long been clear. Now imagine a multi-decade effort to assimilate hundreds of disparate vegetation classifications into one common classification for the US. In this letter, we introduce the US National Vegetation Classification (USNVC; www.usnvc.org) as a powerful tool for research and conservation, analogous to the argument made by Schimel and Chadwick (2013) for soils. The USNVC provides a national framework to classify and describe vegetation; here we describe the USNVC and offer brief examples of its efficacy.

Risk-informed radioactive waste classification and reclassification.

PubMed

Croff, Allen G

2006-11-01

Radioactive waste classification systems have been developed to allow wastes having similar hazards to be grouped for purposes of storage, treatment, packaging, transportation, and/or disposal. As recommended in the National Council on Radiation Protection and Measurements' Report No. 139, Risk-Based Classification of Radioactive and Hazardous Chemical Wastes, a preferred classification system would be based primarily on the health risks to the public that arise from waste disposal and secondarily on other attributes such as the near-term practicalities of managing a waste, i.e., the waste classification system would be risk informed. The current U.S. radioactive waste classification system is not risk informed because key definitions--especially that of high-level waste--are based on the source of the waste instead of its inherent characteristics related to risk. A second important reason for concluding the existing U.S. radioactive waste classification system is not risk informed is there are no general principles or provisions for exempting materials from being classified as radioactive waste which would then allow management without regard to its radioactivity. This paper elaborates the current system for classifying and reclassifying radioactive wastes in the United States, analyzes the extent to which the system is risk informed and the ramifications of its not being so, and provides observations on potential future direction of efforts to address shortcomings in the U.S. radioactive waste classification system as of 2004.

Thermospheric Data Assimilation

DTIC Science & Technology

2016-05-05

forecasting longer than 3 days. Furthermore, validation of assimilation analyses with independent CHAMP mass density observations confirms that the...approach developed in this project. 15. SUBJECT TERMS Data assimilation, Ensemble forecasting , Thermosphere-ionosphere coupled data assimilation...Neutral mass density specification and forecasting , 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT UU 18. NUMBER OF PAGES 6 19a. NAME

Body mass index distribution affects discrepancies in weight classifications in children

USDA-ARS?s Scientific Manuscript database

The aim of the present study was to investigate the effect of body mass index (BMI) distribution, ethnicity, and age at menarche on the consistency in the prevalence of underweight and overweight as defined by the Centers for Disease Control and Prevention (CDC) and the International Obesity Task Fo...

Parent Reactions to a School-Based Body Mass Index Screening Program

ERIC Educational Resources Information Center

Johnson, Suzanne Bennett; Pilkington, Lorri L.; Lamp, Camilla; He, Jianghua; Deeb, Larry C.

2009-01-01

Background: This study assessed parent reactions to school-based body mass index (BMI) screening. Methods: After a K-8 BMI screening program, parents were sent a letter detailing their child's BMI results. Approximately 50 parents were randomly selected for interview from each of 4 child weight-classification groups (overweight, at risk of…

48 CFR 219.303 - Determining North American Industry Classification System (NAICS) codes and size standards.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 48 Federal Acquisition Regulations System 3 2011-10-01 2011-10-01 false Determining North American Industry Classification System (NAICS) codes and size standards. 219.303 Section 219.303 Federal... Programs 219.303 Determining North American Industry Classification System (NAICS) codes and size standards...

48 CFR 219.303 - Determining North American Industry Classification System (NAICS) codes and size standards.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 48 Federal Acquisition Regulations System 3 2012-10-01 2012-10-01 false Determining North American Industry Classification System (NAICS) codes and size standards. 219.303 Section 219.303 Federal... Programs 219.303 Determining North American Industry Classification System (NAICS) codes and size standards...

48 CFR 219.303 - Determining North American Industry Classification System (NAICS) codes and size standards.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 48 Federal Acquisition Regulations System 3 2014-10-01 2014-10-01 false Determining North American Industry Classification System (NAICS) codes and size standards. 219.303 Section 219.303 Federal... Determining North American Industry Classification System (NAICS) codes and size standards. Contracting...

48 CFR 219.303 - Determining North American Industry Classification System (NAICS) codes and size standards.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 48 Federal Acquisition Regulations System 3 2013-10-01 2013-10-01 false Determining North American Industry Classification System (NAICS) codes and size standards. 219.303 Section 219.303 Federal... Determining North American Industry Classification System (NAICS) codes and size standards. Contracting...

15 CFR 921.3 - National Estuarine Research Reserve System biogeographic classification scheme and estuarine...

Code of Federal Regulations, 2012 CFR

2012-01-01

... System biogeographic classification scheme and estuarine typologies. 921.3 Section 921.3 Commerce and... biogeographic classification scheme and estuarine typologies. (a) National Estuarine Research Reserves are... classification scheme based on regional variations in the nation's coastal zone has been developed. The...

15 CFR 921.3 - National Estuarine Research Reserve System biogeographic classification scheme and estuarine...

Code of Federal Regulations, 2013 CFR

2013-01-01

... System biogeographic classification scheme and estuarine typologies. 921.3 Section 921.3 Commerce and... biogeographic classification scheme and estuarine typologies. (a) National Estuarine Research Reserves are... classification scheme based on regional variations in the nation's coastal zone has been developed. The...

15 CFR 921.3 - National Estuarine Research Reserve System biogeographic classification scheme and estuarine...

Code of Federal Regulations, 2010 CFR

2010-01-01

... System biogeographic classification scheme and estuarine typologies. 921.3 Section 921.3 Commerce and... biogeographic classification scheme and estuarine typologies. (a) National Estuarine Research Reserves are... classification scheme based on regional variations in the nation's coastal zone has been developed. The...

15 CFR 921.3 - National Estuarine Research Reserve System biogeographic classification scheme and estuarine...

Code of Federal Regulations, 2014 CFR

2014-01-01

... System biogeographic classification scheme and estuarine typologies. 921.3 Section 921.3 Commerce and... biogeographic classification scheme and estuarine typologies. (a) National Estuarine Research Reserves are... classification scheme based on regional variations in the nation's coastal zone has been developed. The...

15 CFR 921.3 - National Estuarine Research Reserve System biogeographic classification scheme and estuarine...

Code of Federal Regulations, 2011 CFR

2011-01-01

... System biogeographic classification scheme and estuarine typologies. 921.3 Section 921.3 Commerce and... biogeographic classification scheme and estuarine typologies. (a) National Estuarine Research Reserves are... classification scheme based on regional variations in the nation's coastal zone has been developed. The...

Use of Deo's classification system on rock : final report.

DOT National Transportation Integrated Search

1983-01-01

A shale from a construction site on Route 23 in Wise County, Virginia, was classified using Deo's classification system, and the usefulness of the classification system was evaluated. In addition, rock that had previously been used in the development...

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

PubMed

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

2017-04-01

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

Surge of a Complex Glacier System - The Current Surge of the Bering-Bagley Glacier System, Alaska

NASA Astrophysics Data System (ADS)

Herzfeld, U. C.; McDonald, B.; Trantow, T.; Hale, G.; Stachura, M.; Weltman, A.; Sears, T.

2013-12-01

Understanding fast glacier flow and glacial accelerations is important for understanding changes in the cryosphere and ultimately in sea level. Surge-type glaciers are one of four types of fast-flowing glaciers --- the other three being continuously fast-flowing glaciers, fjord glaciers and ice streams --- and the one that has seen the least amount of research. The Bering-Bagley Glacier System, Alaska, the largest glacier system in North America, surged in 2011 and 2012. Velocities decreased towards the end of 2011, while the surge kinematics continued to expand. A new surge phase started in summer and fall 2012. In this paper, we report results from airborne observations collected in September 2011, June/July and September/October 2012 and in 2013. Airborne observations include simultaneously collected laser altimeter data, videographic data, GPS data and photographic data and are complemented by satellite data analysis. Methods range from classic interpretation of imagery to analysis and classification of laser altimeter data and connectionist (neural-net) geostatistical classification of concurrent airborne imagery. Results focus on the characteristics of surge progression in a large and complex glacier system (as opposed to a small glacier with relatively simple geometry). We evaluate changes in surface elevations including mass transfer and sudden drawdowns, crevasse types, accelerations and changes in the supra-glacial and englacial hydrologic system. Supraglacial water in Bering Glacier during Surge, July 2012 Airborne laser altimeter profile across major rift in central Bering Glacier, Sept 2011

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

PubMed

Torrens, Francisco; Castellano, Gloria

2014-06-05

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

Influence of Weight Classification on Walking and Jogging Energy Expenditure Prediction in Women

ERIC Educational Resources Information Center

Heden, Timothy D.; LeCheminant, James D.; Smith, John D.

2012-01-01

The purpose of this study was to determine the influence of weight classification on predicting energy expenditure (EE) in women. Twelve overweight (body mass index [BMI] = 25-29.99 kg/m[superscript 2]) and 12 normal-weight (BMI = 18.5-24.99 kg/m[superscript 2]) women walked and jogged 1,609 m at 1.34 m.s[superscript -1] and 2.23 m.s[superscript…

Comprehensive two-dimensional liquid chromatography tandem diode array detector (DAD) and accurate mass QTOF-MS for the analysis of flavonoids and iridoid glycosides in Hedyotis diffusa.

PubMed

Li, Duxin; Schmitz, Oliver J

2015-01-01

The analysis of chemical constituents in Chinese herbal medicines (CHMs) is a challenge because of numerous compounds with various polarities and functional groups. Liquid chromatography coupled with quadrupole time-of-flight (QTOF) mass spectrometry (LC/MS) is of particular interest in the analysis of herbal components. One of the main attributes of QTOF that makes it an attractive analytical technique is its accurate mass measurement for both precursor and product ions. For the separation of CHMs, comprehensive two-dimensional chromatography (LCxLC) provides much higher resolving power than traditional one-dimensional separation. Therefore, a LCxLC-QTOF-MS system was developed and applied to the analysis of flavonoids and iridoid glycosides in aqueous extracts of Hedyotis diffusa (Rubiaceae). Shift gradient was applied in the two-dimensional separation in the LCxLC system to increase the orthogonality and effective peak distribution area of the analysis. Tentative identification of compounds was done by accurate mass interpretation and validation by UV spectrum. A clear classification of flavonol glycosides (FGs), acylated FGs, and iridoid glycosides (IGs) was shown in different regions of the LCxLC contour plot. In total, five FGs, four acylated FGs, and three IGs were tentatively identified. In addition, several novel flavonoids were found, which demonstrates that LCxLC-QTOF-MS detection also has great potential in herbal medicine analysis.

Diagnostic Yield of Computed Tomography-Guided Coaxial Core Biopsy of Undetermined Masses in the Free Retroperitoneal Space: Single-Center Experience

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

Stattaus, Joerg, E-mail: joerg.stattaus@uni-due.de; Kalkmann, Janine, E-mail: janine.kalkmann@uk-essen.de; Kuehl, Hilmar, E-mail: hilmar.kuehl@uni-due.d

2008-09-15

The purpose of this study was to evaluate the diagnostic yield of core biopsy in coaxial technique under guidance of computed tomography (CT) for retroperitoneal masses. We performed a retrospective analysis of CT-guided coaxial core biopsies of undetermined masses in the non-organ-bound retroperitoneal space in 49 patients. In 37 cases a 15-G guidance needle with a 16-G semiautomated core biopsy system, and in 12 cases a 16-G guidance needle with an 18-G biopsy system, was used. All biopsies were technically successful. A small hematoma was seen in one case, but no relevant complication occurred. With the coaxial technique, up tomore » 4 specimens were obtained from each lesion (mean, 2.8). Diagnostic accuracy in differentiation between malignant and benign diseases was 95.9%. A specific histological diagnosis could be established in 39 of 42 malignant lesions (92.9%). Correct subtyping of malignant lymphoma according to the WHO classification was possible in 87.0%. Benign lesions were correctly identified in seven cases, although a specific diagnosis could only be made in conjunction with clinical and radiological information. In conclusion, CT-guided coaxial core biopsy provides safe and accurate diagnosis of retroperitoneal masses. A specific histological diagnosis, which is essential for choosing the appropriate therapy, could be established in most cases of malignancy.« less

Body mass index in ambulatory cerebral palsy patients.

PubMed

Feeley, Brian T; Gollapudi, Kiran; Otsuka, Norman Y

2007-05-01

Malnutrition is a common problem in children with cerebral palsy. Although malnutrition is often recognized in patients with severe cerebral palsy, it can be unrecognized in less severely affected patients. The consequences of malnutrition are serious, and include decreased muscle strength, poor immune status, and depressed cerebral functioning. Low body mass index has been used as a marker for malnutrition. The purpose of this study was to determine which patients in an ambulatory cerebral palsy patient population were at risk for low body mass index. A retrospective chart review was performed on 75 patients. Age, sex, height, weight, type of cerebral palsy, and functional status [gross motor functional classification system (GMFCS) level] was recorded from the chart. Descriptive statistics with bivariate and multivariate regression analyses were performed. Thirty-eight boys and 37 girls with an average age of 8.11 years were included in the study. Unique to our patient population, all cerebral palsy patients were independent ambulators. Patients with quadriplegic cerebral palsy had a significantly lower body mass index than those with diplegic and hemiplegic cerebral palsy. Patients with a GMFCS III had significantly lower body mass index than those with GMFCS I and II. When multivariate regression analysis to control for age and sex was performed, low body mass index remained associated with quadriplegic cerebral palsy and GMFCS III. Malnutrition is a common health problem in patients with cerebral palsy, leading to significant morbidity in multiple organ systems. We found that in an ambulatory cerebral palsy population, patients with lower functional status or quadriplegia had significantly lower body mass index, suggesting that even highly functioning ambulatory cerebral palsy patients are at risk for malnutrition.

A domains-based taxonomy of supported accommodation for people with severe and persistent mental illness.

PubMed

Siskind, Dan; Harris, Meredith; Pirkis, Jane; Whiteford, Harvey

2013-06-01

A lack of definitional clarity in supported accommodation and the absence of a widely accepted system for classifying supported accommodation models creates barriers to service planning and evaluation. We undertook a systematic review of existing supported accommodation classification systems. Using a structured system for qualitative data analysis, we reviewed the stratification features in these classification systems, identified the key elements of supported accommodation and arranged them into domains and dimensions to create a new taxonomy. The existing classification systems were mapped onto the new taxonomy to verify the domains and dimensions. Existing classification systems used either a service-level characteristic or programmatic approach. We proposed a taxonomy based around four domains: duration of tenure; patient characteristics; housing characteristics; and service characteristics. All of the domains in the taxonomy were drawn from the existing classification structures; however, none of the existing classification structures covered all of the domains in the taxonomy. Existing classification systems are regionally based, limited in scope and lack flexibility. A domains-based taxonomy can allow more accurate description of supported accommodation services, aid in identifying the service elements likely to improve outcomes for specific patient populations, and assist in service planning.

A Model Assessment and Classification System for Men and Women in Correctional Institutions.

ERIC Educational Resources Information Center

Hellervik, Lowell W.; And Others

The report describes a manpower assessment and classification system for criminal offenders directed towards making practical training and job classification decisions. The model is not concerned with custody classifications except as they affect occupational/training possibilities. The model combines traditional procedures of vocational…

Comments on new classification, treatment algorithm and prognosis-estimating systems for sigmoid volvulus and ileosigmoid knotting: necessity and utility.

PubMed

Aksungur, N; Korkut, E

2018-05-24

We read Atamanalp classification, treatment algorithm and prognosis-estimating systems for sigmoid volvulus (SV) and ileosigmoid knotting (ISK) in Colorectal Disease [1,2]. Our comments relate to necessity and utility of these new classification systems. Classification or staging systems are generally used in malignant or premalignant pathologies such as colorectal cancers [3] or polyps [4]. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Critical evaluation of the PALM-COEIN classification system among women with abnormal uterine bleeding in low-resource settings.

PubMed

Shubham, Divya; Kawthalkar, Anjali S

2018-05-01

To assess the feasibility of the PALM-COEIN system for the classification of abnormal uterine bleeding (AUB) in low-resource settings and to suggest modifications. A prospective study was conducted among women with AUB who were admitted to the gynecology ward of a tertiary care hospital and research center in central India between November 2014 and October 2016. All patients were managed as per department protocols. The causes of AUB were classified before treatment using the PALM-COEIN system (classification I) and on the basis of the histopathology reports of the hysterectomy specimens (classification II); the results were compared using classification II as the gold standard. The study included 200 women with AUB; hysterectomy was performed in 174 women. Preoperative classification of AUB per the PALM-COEIN system was correct in 130 (65.0%) women. Adenomyosis (evaluated by transvaginal ultrasonography) and endometrial hyperplasia (evaluated by endometrial curettage) were underdiagnosed. The PALM-COEIN classification system helps in deciding the best treatment modality for women with AUB on a case-by-case basis. The incorporation of suggested modifications will further strengthen its utility as a pretreatment classification system in low-resource settings. © 2017 International Federation of Gynecology and Obstetrics.

In Harmony with the Population: Ethnomusicology as a Framework for Countering Violent Extremism in the Sahel

DTIC Science & Technology

2016-12-01

digital media , art, multiculturalism, communication flow theory 15. NUMBER OF PAGES 143 16. PRICE CODE 17. SECURITY CLASSIFICATION OF REPORT...and Chad as a Case Study,” 59. 41 methods), and mass communication ( communication to a large audience via mass media ).91 According to a 2007...proliferation of digital technology for at least the foreseeable future. Early communication theorists considered mass- media communication flow to be a

48 CFR 19.303 - Determining North American Industry Classification System (NAICS) codes and size standards.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 48 Federal Acquisition Regulations System 1 2010-10-01 2010-10-01 false Determining North American Industry Classification System (NAICS) codes and size standards. 19.303 Section 19.303 Federal Acquisition... Classification System (NAICS) codes and size standards. (a) The contracting officer shall determine the...

A new tree classification system for southern hardwoods

Treesearch

James S. Meadows; Daniel A. Jr. Skojac

2008-01-01

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

Cross-mapping the ICNP with NANDA, HHCC, Omaha System and NIC for unified nursing language system development. International Classification for Nursing Practice. International Council of Nurses. North American Nursing Diagnosis Association. Home Health Care Classification. Nursing Interventions Classification.

PubMed

Hyun, S; Park, H A

2002-06-01

Nursing language plays an important role in describing and defining nursing phenomena and nursing actions. There are numerous vocabularies describing nursing diagnoses, interventions and outcomes in nursing. However, the lack of a standardized unified nursing language is considered a problem for further development of the discipline of nursing. In an effort to unify the nursing languages, the International Council of Nurses (ICN) has proposed the International Classification for Nursing Practice (ICNP) as a unified nursing language system. The purpose of this study was to evaluate the inclusiveness and expressiveness of the ICNP terms by cross-mapping them with the existing nursing terminologies, specifically the North American Nursing Diagnosis Association (NANDA) taxonomy I, the Omaha System, the Home Health Care Classification (HHCC) and the Nursing Interventions Classification (NIC). Nine hundred and seventy-four terms from these four classifications were cross-mapped with the ICNP terms. This was performed in accordance with the Guidelines for Composing a Nursing Diagnosis and Guidelines for Composing a Nursing Intervention, which were suggested by the ICNP development team. An expert group verified the results. The ICNP Phenomena Classification described 87.5% of the NANDA diagnoses, 89.7% of the HHCC diagnoses and 72.7% of the Omaha System problem classification scheme. The ICNP Action Classification described 79.4% of the NIC interventions, 80.6% of the HHCC interventions and 71.4% of the Omaha System intervention scheme. The results of this study suggest that the ICNP has a sound starting structure for a unified nursing language system and can be used to describe most of the existing terminologies. Recommendations for the addition of terms to the ICNP are provided.

A method to assess obstetric outcomes using the 10-Group Classification System: a quantitative descriptive study.

PubMed

Rossen, Janne; Lucovnik, Miha; Eggebø, Torbjørn Moe; Tul, Natasa; Murphy, Martina; Vistad, Ingvild; Robson, Michael

2017-07-12

Internationally, the 10-Group Classification System (TGCS) has been used to report caesarean section rates, but analysis of other outcomes is also recommended. We now aim to present the TGCS as a method to assess outcomes of labour and delivery using routine collection of perinatal information. This research is a methodological study to describe the use of the TGCS. Stavanger University Hospital (SUH), Norway, National Maternity Hospital Dublin, Ireland and Slovenian National Perinatal Database (SLO), Slovenia. 9848 women from SUH, Norway, 9250 women from National Maternity Hospital Dublin, Ireland and 106 167 women, from SLO, Slovenia. All women were classified according to the TGCS within which caesarean section, oxytocin augmentation, epidural analgesia, operative vaginal deliveries, episiotomy, sphincter rupture, postpartum haemorrhage, blood transfusion, maternal age >35 years, body mass index >30, Apgar score, umbilical cord pH, hypoxic-ischaemic encephalopathy, antepartum and perinatal deaths were incorporated. There were significant differences in the sizes of the groups of women and the incidences of events and outcomes within the TGCS between the three perinatal databases. The TGCS is a standardised objective classification system where events and outcomes of labour and delivery can be incorporated. Obstetric core events and outcomes should be agreed and defined to set standards of care. This method provides continuous and available observations from delivery wards, possibly used for further interpretation, questions and international comparisons. The definition of quality may vary in different units and can only be ascertained when all the necessary information is available and considered together. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

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

Vernon, Christopher R.; Arntzen, Evan V.; Richmond, Marshall C.

Assessing the environmental benefits of proposed flow modification to large rivers provides invaluable insight into future hydropower project operations and relicensing activities. Providing a means to quantitatively define flow-ecology relationships is integral in establishing flow regimes that are mutually beneficial to power production and ecological needs. To compliment this effort an opportunity to create versatile tools that can be applied to broad geographic areas has been presented. In particular, integration with efforts standardized within the ecological limits of hydrologic alteration (ELOHA) is highly advantageous (Poff et al. 2010). This paper presents a geographic information system (GIS) framework for large rivermore » classification that houses a base geomorphic classification that is both flexible and accurate, allowing for full integration with other hydrologic models focused on addressing ELOHA efforts. A case study is also provided that integrates publically available National Hydrography Dataset Plus Version 2 (NHDPlusV2) data, Modular Aquatic Simulation System two-dimensional (MASS2) hydraulic data, and field collected data into the framework to produce a suite of flow-ecology related outputs. The case study objective was to establish areas of optimal juvenile salmonid rearing habitat under varying flow regimes throughout an impounded portion of the lower Snake River, USA (Figure 1) as an indicator to determine sites where the potential exists to create additional shallow water habitat. Additionally, an alternative hydrologic classification useable throughout the contiguous United States which can be coupled with the geomorphic aspect of this framework is also presented. This framework provides the user with the ability to integrate hydrologic and ecologic data into the base geomorphic aspect of this framework within a geographic information system (GIS) to output spatiotemporally variable flow-ecology relationship scenarios.« less

Body mass index and childhood obesity classification systems: A comparison of the French, International Obesity Task Force (IOTF) and World Health Organization (WHO) references.

PubMed

Kêkê, L M; Samouda, H; Jacobs, J; di Pompeo, C; Lemdani, M; Hubert, H; Zitouni, D; Guinhouya, B C

2015-06-01

This study aims to compare three body mass index (BMI)-based classification systems of childhood obesity: the French, the International Obesity Task Force (IOTF) and the World Health Organization (WHO) references. The study involved 1382 schoolchildren, recruited from the Lille Academic District in France in May 2009 aged 8.4±1.7 years (4.0-12.0 years). Their mean height and body mass were 131.5±10.9cm and 30.7±9.2kg, respectively, resulting in a BMI of 17.4±3.2kg/m(2). The weight status was defined according to the three systems considered in this study. The agreement between these references was tested using the Cohen's kappa coefficient. The prevalence of overweight was higher with the WHO references (20.0%) in comparison with the French references (13.8%; P<0.0001) and the IOTF (16.2%; P≤0.01). A similar result was found with obesity (WHO: 11.6% vs. IOTF: 6.7%; or French references: 6.7%; P<0.0001). Agreement between the three references ranged from "moderate" to "perfect" (0.43≤κ≤1.00; P<0.0001). Kappa coefficients were higher when the three references were used to classify children as obese (0.63≤κ≤1.00; P<0.0001) as compared to classification in the overweight (obesity excluded) category (0.43≤κ≤0.94; P<0.0001). When sex and age categories (4-6 years vs. 7-12 years) were considered to define the overweight status, the lowest kappa coefficient was found between the French and WHO references in boys aged 7-12 years (κ=0.28; P<0.0001), and the highest one in girls aged 7-12 years between the French references and IOTF (κ=0.97; P<0.0001). As for obesity, agreement between the three references ranged from 0.60 to 1.00 (P<0.0001), with the lowest values obtained in the comparison of the WHO references against French references or IOTF among boys aged 7-12 years (κ=0.60; P<0.0001). Overall, the WHO references yield an overestimation in overweight and/or obesity within this sample of schoolchildren as compared to the French references and the IOTF. The magnitude of agreement coefficients between the three references depends on of both sex and age categories. The French references seem to be in rather close agreement with the IOTF in defining overweight, especially in 7-12-year-old children. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

A "TNM" classification system for cancer pain: the Edmonton Classification System for Cancer Pain (ECS-CP).

PubMed

Fainsinger, Robin L; Nekolaichuk, Cheryl L

2008-06-01

The purpose of this paper is to provide an overview of the development of a "TNM" cancer pain classification system for advanced cancer patients, the Edmonton Classification System for Cancer Pain (ECS-CP). Until we have a common international language to discuss cancer pain, understanding differences in clinical and research experience in opioid rotation and use remains problematic. The complexity of the cancer pain experience presents unique challenges for the classification of pain. To date, no universally accepted pain classification measure can accurately predict the complexity of pain management, particularly for patients with cancer pain that is difficult to treat. In response to this gap in clinical assessment, the Edmonton Staging System (ESS), a classification system for cancer pain, was developed. Difficulties in definitions and interpretation of some aspects of the ESS restricted acceptance and widespread use. Construct, inter-rater reliability, and predictive validity evidence have contributed to the development of the ECS-CP. The five features of the ECS-CP--Pain Mechanism, Incident Pain, Psychological Distress, Addictive Behavior and Cognitive Function--have demonstrated value in predicting pain management complexity. The development of a standardized classification system that is comprehensive, prognostic and simple to use could provide a common language for clinical management and research of cancer pain. An international study to assess the inter-rater reliability and predictive value of the ECS-CP is currently in progress.

5 CFR 9901.224 - Appeal to OPM for review of classification decisions.

Code of Federal Regulations, 2011 CFR

2011-01-01

... RESOURCES MANAGEMENT AND LABOR RELATIONS SYSTEMS (DEPARTMENT OF DEFENSE-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF DEFENSE NATIONAL SECURITY PERSONNEL SYSTEM (NSPS) Classification Classification Process § 9901...

5 CFR 9901.224 - Appeal to OPM for review of classification decisions.

Code of Federal Regulations, 2010 CFR

2010-01-01

... RESOURCES MANAGEMENT AND LABOR RELATIONS SYSTEMS (DEPARTMENT OF DEFENSE-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF DEFENSE NATIONAL SECURITY PERSONNEL SYSTEM (NSPS) Classification Classification Process § 9901...

Efficacy measures associated to a plantar pressure based classification system in diabetic foot medicine.

PubMed

Deschamps, Kevin; Matricali, Giovanni Arnoldo; Desmet, Dirk; Roosen, Philip; Keijsers, Noel; Nobels, Frank; Bruyninckx, Herman; Staes, Filip

2016-09-01

The concept of 'classification' has, similar to many other diseases, been found to be fundamental in the field of diabetic medicine. In the current study, we aimed at determining efficacy measures of a recently published plantar pressure based classification system. Technical efficacy of the classification system was investigated by applying a high resolution, pixel-level analysis on the normalized plantar pressure pedobarographic fields of the original experimental dataset consisting of 97 patients with diabetes and 33 persons without diabetes. Clinical efficacy was assessed by considering the occurence of foot ulcers at the plantar aspect of the forefoot in this dataset. Classification efficacy was assessed by determining the classification recognition rate as well as its sensitivity and specificity using cross-validation subsets of the experimental dataset together with a novel cohort of 12 patients with diabetes. Pixel-level comparison of the four groups associated to the classification system highlighted distinct regional differences. Retrospective analysis showed the occurence of eleven foot ulcers in the experimental dataset since their gait analysis. Eight out of the eleven ulcers developed in a region of the foot which had the highest forces. Overall classification recognition rate exceeded 90% for all cross-validation subsets. Sensitivity and specificity of the four groups associated to the classification system exceeded respectively the 0.7 and 0.8 level in all cross-validation subsets. The results of the current study support the use of the novel plantar pressure based classification system in diabetic foot medicine. It may particularly serve in communication, diagnosis and clinical decision making. Copyright © 2016 Elsevier B.V. All rights reserved.

Classification System and Information Services in the Library of SAO RAS

NASA Astrophysics Data System (ADS)

Shvedova, G. S.

The classification system used at SAO RAS is described. It includes both special determinants from UDC (Universal Decimal Classification) and newer tables with astronomical terms from the Library-Bibliographical Classification (LBC). The classification tables are continually modified, and new astronomical terms are introduced. At the present time the information services of the scientists is fulfilled with the help of the Abstract Journal Astronomy, Astronomy and Astrophysics Abstracts, catalogues and card indexes of the library. Based on our classification system and The Astronomy Thesaurus completed by R.M. Shobbrook and R.R. Shobbrook the development of a database for the library has been started, which allows prompt service of the observatory's staff members.

Proximal humeral fracture classification systems revisited.

PubMed

Majed, Addie; Macleod, Iain; Bull, Anthony M J; Zyto, Karol; Resch, Herbert; Hertel, Ralph; Reilly, Peter; Emery, Roger J H

2011-10-01

This study evaluated several classification systems and expert surgeons' anatomic understanding of these complex injuries based on a consecutive series of patients. We hypothesized that current proximal humeral fracture classification systems, regardless of imaging methods, are not sufficiently reliable to aid clinical management of these injuries. Complex fractures in 96 consecutive patients were investigated by generation of rapid sequence prototyping models from computed tomography Digital Imaging and Communications in Medicine (DICOM) imaging data. Four independent senior observers were asked to classify each model using 4 classification systems: Neer, AO, Codman-Hertel, and a prototype classification system by Resch. Interobserver and intraobserver κ coefficient values were calculated for the overall classification system and for selected classification items. The κ coefficient values for the interobserver reliability were 0.33 for Neer, 0.11 for AO, 0.44 for Codman-Hertel, and 0.15 for Resch. Interobserver reliability κ coefficient values were 0.32 for the number of fragments and 0.30 for the anatomic segment involved using the Neer system, 0.30 for the AO type (A, B, C), and 0.53, 0.48, and 0.08 for the Resch impaction/distraction, varus/valgus and flexion/extension subgroups, respectively. Three-part fractures showed low reliability for the Neer and AO systems. Currently available evidence suggests fracture classifications in use have poor intra- and inter-observer reliability despite the modality of imaging used thus making treating these injuries difficult as weak as affecting scientific research as well. This study was undertaken to evaluate the reliability of several systems using rapid sequence prototype models. Overall interobserver κ values represented slight to moderate agreement. The most reliable interobserver scores were found with the Codman-Hertel classification, followed by elements of Resch's trial system. The AO system had the lowest values. The higher interobserver reliability values for the Codman-Hertel system showed that is the only comprehensive fracture description studied, whereas the novel classification by Resch showed clear definition in respect to varus/valgus and impaction/distraction angulation. Copyright © 2011 Journal of Shoulder and Elbow Surgery Board of Trustees. All rights reserved.

A prototype of mammography CADx scheme integrated to imaging quality evaluation techniques

NASA Astrophysics Data System (ADS)

Schiabel, Homero; Matheus, Bruno R. N.; Angelo, Michele F.; Patrocínio, Ana Claudia; Ventura, Liliane

2011-03-01

As all women over the age of 40 are recommended to perform mammographic exams every two years, the demands on radiologists to evaluate mammographic images in short periods of time has increased considerably. As a tool to improve quality and accelerate analysis CADe/Dx (computer-aided detection/diagnosis) schemes have been investigated, but very few complete CADe/Dx schemes have been developed and most are restricted to detection and not diagnosis. The existent ones usually are associated to specific mammographic equipment (usually DR), which makes them very expensive. So this paper describes a prototype of a complete mammography CADx scheme developed by our research group integrated to an imaging quality evaluation process. The basic structure consists of pre-processing modules based on image acquisition and digitization procedures (FFDM, CR or film + scanner), a segmentation tool to detect clustered microcalcifications and suspect masses and a classification scheme, which evaluates as the presence of microcalcifications clusters as well as possible malignant masses based on their contour. The aim is to provide enough information not only on the detected structures but also a pre-report with a BI-RADS classification. At this time the system is still lacking an interface integrating all the modules. Despite this, it is functional as a prototype for clinical practice testing, with results comparable to others reported in literature.

46 CFR 76.50-5 - Classification.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 46 Shipping 3 2011-10-01 2011-10-01 false Classification. 76.50-5 Section 76.50-5 Shipping COAST... Classification. (a) Hand portable fire extinguishers and semiportable fire extinguishing systems shall be... extinguishing systems are set forth in table 76.50-5(c). Table 76.50-5(c) Classification Type Size Soda acid and...

46 CFR 76.50-5 - Classification.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 46 Shipping 3 2010-10-01 2010-10-01 false Classification. 76.50-5 Section 76.50-5 Shipping COAST... Classification. (a) Hand portable fire extinguishers and semiportable fire extinguishing systems shall be... extinguishing systems are set forth in table 76.50-5(c). Table 76.50-5(c) Classification Type Size Soda acid and...

46 CFR 76.50-5 - Classification.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 46 Shipping 3 2014-10-01 2014-10-01 false Classification. 76.50-5 Section 76.50-5 Shipping COAST... Classification. (a) Hand portable fire extinguishers and semiportable fire extinguishing systems shall be... extinguishing systems are set forth in table 76.50-5(c). Table 76.50-5(c) Classification Type Size Soda acid and...

46 CFR 76.50-5 - Classification.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 46 Shipping 3 2013-10-01 2013-10-01 false Classification. 76.50-5 Section 76.50-5 Shipping COAST... Classification. (a) Hand portable fire extinguishers and semiportable fire extinguishing systems shall be... extinguishing systems are set forth in table 76.50-5(c). Table 76.50-5(c) Classification Type Size Soda acid and...

46 CFR 76.50-5 - Classification.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 46 Shipping 3 2012-10-01 2012-10-01 false Classification. 76.50-5 Section 76.50-5 Shipping COAST... Classification. (a) Hand portable fire extinguishers and semiportable fire extinguishing systems shall be... extinguishing systems are set forth in table 76.50-5(c). Table 76.50-5(c) Classification Type Size Soda acid and...

43 CFR 2461.1 - Proposed classifications.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 43 Public Lands: Interior 2 2011-10-01 2011-10-01 false Proposed classifications. 2461.1 Section... MANAGEMENT, DEPARTMENT OF THE INTERIOR LAND RESOURCE MANAGEMENT (2000) BUREAU INITIATED CLASSIFICATION SYSTEM Multiple-Use Classification Procedures § 2461.1 Proposed classifications. (a) Proposed classifications will...

43 CFR 2461.4 - Changing classifications.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 43 Public Lands: Interior 2 2011-10-01 2011-10-01 false Changing classifications. 2461.4 Section... MANAGEMENT, DEPARTMENT OF THE INTERIOR LAND RESOURCE MANAGEMENT (2000) BUREAU INITIATED CLASSIFICATION SYSTEM Multiple-Use Classification Procedures § 2461.4 Changing classifications. Classifications may be changed...

43 CFR 2461.1 - Proposed classifications.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 43 Public Lands: Interior 2 2013-10-01 2013-10-01 false Proposed classifications. 2461.1 Section... MANAGEMENT, DEPARTMENT OF THE INTERIOR LAND RESOURCE MANAGEMENT (2000) BUREAU INITIATED CLASSIFICATION SYSTEM Multiple-Use Classification Procedures § 2461.1 Proposed classifications. (a) Proposed classifications will...

43 CFR 2461.4 - Changing classifications.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 43 Public Lands: Interior 2 2012-10-01 2012-10-01 false Changing classifications. 2461.4 Section... MANAGEMENT, DEPARTMENT OF THE INTERIOR LAND RESOURCE MANAGEMENT (2000) BUREAU INITIATED CLASSIFICATION SYSTEM Multiple-Use Classification Procedures § 2461.4 Changing classifications. Classifications may be changed...

43 CFR 2461.1 - Proposed classifications.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 43 Public Lands: Interior 2 2012-10-01 2012-10-01 false Proposed classifications. 2461.1 Section... MANAGEMENT, DEPARTMENT OF THE INTERIOR LAND RESOURCE MANAGEMENT (2000) BUREAU INITIATED CLASSIFICATION SYSTEM Multiple-Use Classification Procedures § 2461.1 Proposed classifications. (a) Proposed classifications will...

43 CFR 2461.4 - Changing classifications.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 43 Public Lands: Interior 2 2014-10-01 2014-10-01 false Changing classifications. 2461.4 Section... MANAGEMENT, DEPARTMENT OF THE INTERIOR LAND RESOURCE MANAGEMENT (2000) BUREAU INITIATED CLASSIFICATION SYSTEM Multiple-Use Classification Procedures § 2461.4 Changing classifications. Classifications may be changed...

43 CFR 2461.1 - Proposed classifications.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 43 Public Lands: Interior 2 2014-10-01 2014-10-01 false Proposed classifications. 2461.1 Section... MANAGEMENT, DEPARTMENT OF THE INTERIOR LAND RESOURCE MANAGEMENT (2000) BUREAU INITIATED CLASSIFICATION SYSTEM Multiple-Use Classification Procedures § 2461.1 Proposed classifications. (a) Proposed classifications will...

43 CFR 2461.4 - Changing classifications.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 43 Public Lands: Interior 2 2013-10-01 2013-10-01 false Changing classifications. 2461.4 Section... MANAGEMENT, DEPARTMENT OF THE INTERIOR LAND RESOURCE MANAGEMENT (2000) BUREAU INITIATED CLASSIFICATION SYSTEM Multiple-Use Classification Procedures § 2461.4 Changing classifications. Classifications may be changed...

Staging of chronic myeloid leukemia in the imatinib era: an evaluation of the World Health Organization proposal.

PubMed

Cortes, Jorge E; Talpaz, Moshe; O'Brien, Susan; Faderl, Stefan; Garcia-Manero, Guillermo; Ferrajoli, Alessandra; Verstovsek, Srdan; Rios, Mary B; Shan, Jenny; Kantarjian, Hagop M

2006-03-15

Several staging classification systems, all of which were designed in the preimatinib era, are used for chronic myeloid leukemia (CML). The World Health Organization (WHO) recently proposed a new classification system that has not been validated clinically. The authors investigated the significance of the WHO classification system and compared it with the classification systems used to date in imatinib trials ("standard definition") to determine its impact in establishing the outcome of patients after therapy with imatinib. In total, 809 patients who received imatinib for CML were classified into chronic phase (CP), accelerated phase (AP), and blast phase (BP) based on standard definitions and then were reclassified according to the new WHO classification system. Their outcomes with imatinib therapy were compared, and the value of individual components of these classification systems was determined. With the WHO classification, 78 patients (10%) were reclassified: 45 patients (6%) were reclassified from CP to AP, 14 patients (2%) were reclassified from AP to CP, and 19 patients (2%) were reclassified from AP to BP. The rates of complete cytogenetic response for patients in CP, AP, and BP according to the standard definition were 72%, 45%, and 8%, respectively. After these patients were reclassified according to WHO criteria, the response rates were 77% (P = 0.07), 39% (P = 0.28), and 11% (P = 0.61), respectively. The 3-year survival rates were 91%, 65%, and 10%, respectively, according to the standard classification and 95% (P = 0.05), 63% (P = 0.76), and 16% (P = 0.18), respectively, according to the WHO classification. Patients who had a blast percentage of 20-29%, which is considered CML-BP according to the WHO classification, had a significantly better response rate (21% vs. 8%; P = 0.11) and 3-year survival rate (42% vs. 10%; P = 0.0001) compared with patients who had blasts > or = 30%. Different classification systems had an impact on the outcome of patients, and some prognostic features had different prognostic implications in the imatinib era. The authors believe that a new, uniform staging system for CML is warranted, and they propose such a system. (c) 2006 American Cancer Society.

Resonant Acoustic Determination of Complex Elastic Moduli

DTIC Science & Technology

1991-03-01

Classification uncssified/.unimled - sae as report [] DnC ui, Unclassified 22a Name of Responsible Individual 22b Telephone (Include Area code) 22c Office Symbol...4090 DISP " Run: "Block2$ 4100 WAIT 1 4110 DISP "Mode: "Blocic3$ 4120 WAIT 1 4130 DISP" Date: "Block4$ 4140 WAIT 1 4150 DISP "Mass: "Mass;"grams

Apocrine hidradenocarcinoma of the scalp: a classification conundrum.

PubMed

Cohen, Marc; Cassarino, David S; Shih, Hubert B; Abemayor, Elliot; St John, Maie

2009-03-01

The classification of malignant sweat gland lesions is complex. Traditionally, cutaneous sweat gland tumors have been classified by either eccrine or apocrine features. A case report of a 33-year-old Hispanic man with a left scalp mass diagnosed as a malignancy of adnexal origin preoperatively is discussed. After presentation at our multidisciplinary tumor board, excision with ipsilateral neck dissection was undertaken. Final pathology revealed an apocrine hidradenocarcinoma. The classification and behavior of this entity are discussed in this report. Apocrine hidradenocarcinoma can be viewed as an aggressive malignant lesion of cutaneous sweat glands on a spectrum that involves both eccrine and apoeccrine lesions.

Apocrine Hidradenocarcinoma of the Scalp: A Classification Conundrum

PubMed Central

Cassarino, David S.; Shih, Hubert B.; Abemayor, Elliot; John, Maie St.

2008-01-01

Introduction The classification of malignant sweat gland lesions is complex. Traditionally, cutaneous sweat gland tumors have been classified by either eccrine or apocrine features. Methods A case report of a 33-year-old Hispanic man with a left scalp mass diagnosed as a malignancy of adnexal origin preoperatively is discussed. After presentation at our multidisciplinary tumor board, excision with ipsilateral neck dissection was undertaken. Results Final pathology revealed an apocrine hidradenocarcinoma. The classification and behavior of this entity are discussed in this report. Conclusion Apocrine hidradenocarcinoma can be viewed as an aggressive malignant lesion of cutaneous sweat glands on a spectrum that involves both eccrine and apoeccrine lesions. PMID:20596988

Characteristics of a global classification system for perinatal deaths: a Delphi consensus study.

PubMed

Wojcieszek, Aleena M; Reinebrant, Hanna E; Leisher, Susannah Hopkins; Allanson, Emma; Coory, Michael; Erwich, Jan Jaap; Frøen, J Frederik; Gardosi, Jason; Gordijn, Sanne; Gulmezoglu, Metin; Heazell, Alexander E P; Korteweg, Fleurisca J; McClure, Elizabeth; Pattinson, Robert; Silver, Robert M; Smith, Gordon; Teoh, Zheyi; Tunçalp, Özge; Flenady, Vicki

2016-08-15

Despite the global burden of perinatal deaths, there is currently no single, globally-acceptable classification system for perinatal deaths. Instead, multiple, disparate systems are in use world-wide. This inconsistency hinders accurate estimates of causes of death and impedes effective prevention strategies. The World Health Organisation (WHO) is developing a globally-acceptable classification approach for perinatal deaths. To inform this work, we sought to establish a consensus on the important characteristics of such a system. A group of international experts in the classification of perinatal deaths were identified and invited to join an expert panel to develop a list of important characteristics of a quality global classification system for perinatal death. A Delphi consensus methodology was used to reach agreement. Three rounds of consultation were undertaken using a purpose built on-line survey. Round one sought suggested characteristics for subsequent scoring and selection in rounds two and three. The panel of experts agreed on a total of 17 important characteristics for a globally-acceptable perinatal death classification system. Of these, 10 relate to the structural design of the system and 7 relate to the functional aspects and use of the system. This study serves as formative work towards the development of a globally-acceptable approach for the classification of the causes of perinatal deaths. The list of functional and structural characteristics identified should be taken into consideration when designing and developing such a system.

Rock mass characterisation and stability analyses of excavated slopes

NASA Astrophysics Data System (ADS)

Zangerl, Christian; Lechner, Heidrun

2016-04-01

Excavated slopes in fractured rock masses are frequently designed for open pit mining, quarries, buildings, highways, railway lines, and canals. These slopes can reach heights of several hundreds of metres and in cases concerning open pit mines slopes larger than 1000 m are not uncommon. Given that deep-seated slope failures can cause large damage or even loss of life, the slope design needs to incorporate sufficient stability. Thus, slope design methods based on comprehensive approaches need to be applied. Excavation changes slope angle, groundwater flow, and blasting increases the degree of rock mass fracturing as well as rock mass disturbance. As such, excavation leads to considerable stress changes in the slopes. Generally, slope design rely on the concept of factor of safety (FOS), often a requirement by international or national standards. A limitation of the factor of safety is that time dependent failure processes, stress-strain relationships, and the impact of rock mass strain and displacement are not considered. Usually, there is a difficulty to estimate the strength of the rock mass, which in turn is controlled by an interaction of intact rock and discontinuity strength. In addition, knowledge about in-situ stresses for the failure criterion is essential. Thus, the estimation of the state of stress of the slope and the strength parameters of the rock mass is still challenging. Given that, large-scale in-situ testing is difficult and costly, back-calculations of case studies in similar rock types or rock mass classification systems are usually the methods of choice. Concerning back-calculations, often a detailed and standardised documentation is missing, and a direct applicability to new projects is not always given. Concerning rock mass classification systems, it is difficult to consider rock mass anisotropy and thus the empirical estimation of the strength properties possesses high uncertainty. In the framework of this study an approach based on numerical discrete element modelling (DEM) in combination with limit-equilibrium (LE) methods are presented. The advantage of DEM methods is that failure and displacement of discontinuities and the intact rock for the investigation of failure mechanisms and slope deformations are considered. Furthermore, DEM methods have its strength when rock masses are highly anisotropic and slope failure is structurally controlled. Herein DEM methods are applied to model potential failure geometries, which in turn serve as basis for further investigations by limit-equilibrium methods. LE-methods are used to determine the factor of safety for the pre-defined failure geometries where a sliding mechanism with a discrete and pre-defined basal shear zone is the most likely kinematical failure mode. In this study a parameter variation was performed to find the most reliable FOS based on field estimated strength parameters and the critical strength parameter where a FOS is equal to one (i.e. the lower limit for the parameters). Furthermore, the sensitivity of the shear strength parameters is studied, which enables plausibility checks with field measurements and back-calculated values. The combined approach can help to gain a better insight into failure processes and deformation mechanisms and facilitate to perform a parameter-variation study at a reasonable time frame.

Interobserver reliability of the young-burgess and tile classification systems for fractures of the pelvic ring.

PubMed

Koo, Henry; Leveridge, Mike; Thompson, Charles; Zdero, Rad; Bhandari, Mohit; Kreder, Hans J; Stephen, David; McKee, Michael D; Schemitsch, Emil H

2008-07-01

The purpose of this study was to measure interobserver reliability of 2 classification systems of pelvic ring fractures and to determine whether computed tomography (CT) improves reliability. The reliability of several radiographic findings was also tested. Thirty patients taken from a database at a Level I trauma facility were reviewed. For each patient, 3 radiographs (AP pelvis, inlet, and outlet) and CT scans were available. Six different reviewers (pelvic and acetabular specialist, orthopaedic traumatologist, or orthopaedic trainee) classified the injury according to Young-Burgess and Tile classification systems after reviewing plain radiographs and then after CT scans. The Kappa coefficient was used to determine interobserver reliability of these classification systems before and after CT scan. For plain radiographs, overall Kappa values for the Young-Burgess and Tile classification systems were 0.72 and 0.30, respectively. For CT scan and plain radiographs, the overall Kappa values for the Young-Burgess and Tile classification systems were 0.63 and 0.33, respectively. The pelvis/acetabular surgeons demonstrated the highest level of agreement using both classification systems. For individual questions, the addition of CT did significantly improve reviewer interpretation of fracture stability. The pre-CT and post-CT Kappa values for fracture stability were 0.59 and 0.93, respectively. The CT scan can improve the reliability of assessment of pelvic stability because of its ability to identify anatomical features of injury. The Young-Burgess system may be optimal for the learning surgeon. The Tile classification system is more beneficial for specialists in pelvic and acetabular surgery.

A Review of Major Nursing Vocabularies and the Extent to Which They Have the Characteristics Required for Implementation in Computer-based Systems

PubMed Central

Henry, Suzanne Bakken; Warren, Judith J.; Lange, Linda; Button, Patricia

1998-01-01

Building on the work of previous authors, the Computer-based Patient Record Institute (CPRI) Work Group on Codes and Structures has described features of a classification scheme for implementation within a computer-based patient record. The authors of the current study reviewed the evaluation literature related to six major nursing vocabularies (the North American Nursing Diagnosis Association Taxonomy 1, the Nursing Interventions Classification, the Nursing Outcomes Classification, the Home Health Care Classification, the Omaha System, and the International Classification for Nursing Practice) to determine the extent to which the vocabularies include the CPRI features. None of the vocabularies met all criteria. The Omaha System, Home Health Care Classification, and International Classification for Nursing Practice each included five features. Criteria not fully met by any systems were clear and non-redundant representation of concepts, administrative cross-references, syntax and grammar, synonyms, uncertainty, context-free identifiers, and language independence. PMID:9670127

Projectile Measurements and Instrumentation Laboratory Mass Property Measurements

DTIC Science & Technology

1974-09-01

STATEMENT (ol III* abalrael anlarad In Block 20, II dlllaranl Irom Rmpotl) 11. SUPPLEMENTARY NOTES Available in DDC . 1». KEY WORDS fConllnu* on...FORM I JAN 73 1473 EDITION OF I NOV SB IS OBSOLETE UNCLASSIFIED SECURITY CLASSIFICATION OF THIS PAGE (Whmn Dmlm Enlmrmd) ■auHHaUi^L^u^. ^^-..-^-i... CLASSIFICATION Of THIS PAQE(Whm> Dmlm Knltrmd) Item 19 (Continued): Top Loading Balance Center of Gravity Balance Moment of Inertia Instrument

Comparison of wheat classification accuracy using different classifiers of the image-100 system

NASA Technical Reports Server (NTRS)

Dejesusparada, N. (Principal Investigator); Chen, S. C.; Moreira, M. A.; Delima, A. M.

1981-01-01

Classification results using single-cell and multi-cell signature acquisition options, a point-by-point Gaussian maximum-likelihood classifier, and K-means clustering of the Image-100 system are presented. Conclusions reached are that: a better indication of correct classification can be provided by using a test area which contains various cover types of the study area; classification accuracy should be evaluated considering both the percentages of correct classification and error of commission; supervised classification approaches are better than K-means clustering; Gaussian distribution maximum likelihood classifier is better than Single-cell and Multi-cell Signature Acquisition Options of the Image-100 system; and in order to obtain a high classification accuracy in a large and heterogeneous crop area, using Gaussian maximum-likelihood classifier, homogeneous spectral subclasses of the study crop should be created to derive training statistics.

Classification in Australia.

ERIC Educational Resources Information Center

McKinlay, John

Despite some inroads by the Library of Congress Classification and short-lived experimentation with Universal Decimal Classification and Bliss Classification, Dewey Decimal Classification, with its ability in recent editions to be hospitable to local needs, remains the most widely used classification system in Australia. Although supplemented at…

Second Language Writing Classification System Based on Word-Alignment Distribution

ERIC Educational Resources Information Center

Kotani, Katsunori; Yoshimi, Takehiko

2010-01-01

The present paper introduces an automatic classification system for assisting second language (L2) writing evaluation. This system, which classifies sentences written by L2 learners as either native speaker-like or learner-like sentences, is constructed by machine learning algorithms using word-alignment distributions as classification features…

Library Classification 2020

ERIC Educational Resources Information Center

Harris, Christopher

2013-01-01

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

48 CFR 19.303 - Determining North American Industry Classification System codes and size standards.

Code of Federal Regulations, 2014 CFR

2014-10-01

... Industry Classification System codes and size standards. 19.303 Section 19.303 Federal Acquisition... of Small Business Status for Small Business Programs 19.303 Determining North American Industry... North American Industry Classification System (NAICS) code and related small business size standard and...

Should the Gross Motor Function Classification System be used for children who do not have cerebral palsy?

PubMed

Towns, Megan; Rosenbaum, Peter; Palisano, Robert; Wright, F Virginia

2018-02-01

This literature review addressed four questions. (1) In which populations other than cerebral palsy (CP) has the Gross Motor Function Classification System (GMFCS) been applied? (2) In what types of study, and why was it used? (3) How was it modified to facilitate these applications? (4) What justifications and evidence of psychometric adequacy were used to support its application? A search of PubMed, MEDLINE, and Embase databases (January 1997 to April 2017) using the terms: 'GMFCS' OR 'Gross Motor Function Classification System' yielded 2499 articles. 118 met inclusion criteria and reported children/adults with 133 health conditions/clinical descriptions other than CP. Three broad GMFCS applications were observed: as a categorization tool, independent variable, or outcome measure. While the GMFCS is widely used for children with health conditions/clinical description other than CP, researchers rarely provided adequate justification for these uses. We offer recommendations for development/validation of other condition-specific classification systems and discuss the potential need for a generic gross motor function classification system. The Gross Motor Function Classification System should not be used outside cerebral palsy or as an outcome measure. The authors provide recommendations for development and validation of condition-specific or generic classification systems. © 2017 Mac Keith Press.

A multilayered approach for the analysis of perinatal mortality using different classification systems.

PubMed

Gordijn, Sanne J; Korteweg, Fleurisca J; Erwich, Jan Jaap H M; Holm, Jozien P; van Diem, Mariet Th; Bergman, Klasien A; Timmer, Albertus

2009-06-01

Many classification systems for perinatal mortality are available, all with their own strengths and weaknesses: none of them has been universally accepted. We present a systematic multilayered approach for the analysis of perinatal mortality based on information related to the moment of death, the conditions associated with death and the underlying cause of death, using a combination of representatives of existing classification systems. We compared the existing classification systems regarding their definition of the perinatal period, level of complexity, inclusion of maternal, foetal and/or placental factors and whether they focus at a clinical or pathological viewpoint. Furthermore, we allocated the classification systems to one of three categories: 'when', 'what' or 'why', dependent on whether the allocation of the individual cases of perinatal mortality is based on the moment of death ('when'), the clinical conditions associated with death ('what'), or the underlying cause of death ('why'). A multilayered approach for the analysis and classification of perinatal mortality is possible by using combinations of existing systems; for example the Wigglesworth or Nordic Baltic ('when'), ReCoDe ('what') and Tulip ('why') classification systems. This approach is useful not only for in depth analysis of perinatal mortality in the developed world but also for analysis of perinatal mortality in the developing countries, where resources to investigate death are often limited.

A new 2D segmentation method based on dynamic programming applied to computer aided detection in mammography.

PubMed

Timp, Sheila; Karssemeijer, Nico

2004-05-01

Mass segmentation plays a crucial role in computer-aided diagnosis (CAD) systems for classification of suspicious regions as normal, benign, or malignant. In this article we present a robust and automated segmentation technique--based on dynamic programming--to segment mass lesions from surrounding tissue. In addition, we propose an efficient algorithm to guarantee resulting contours to be closed. The segmentation method based on dynamic programming was quantitatively compared with two other automated segmentation methods (region growing and the discrete contour model) on a dataset of 1210 masses. For each mass an overlap criterion was calculated to determine the similarity with manual segmentation. The mean overlap percentage for dynamic programming was 0.69, for the other two methods 0.60 and 0.59, respectively. The difference in overlap percentage was statistically significant. To study the influence of the segmentation method on the performance of a CAD system two additional experiments were carried out. The first experiment studied the detection performance of the CAD system for the different segmentation methods. Free-response receiver operating characteristics analysis showed that the detection performance was nearly identical for the three segmentation methods. In the second experiment the ability of the classifier to discriminate between malignant and benign lesions was studied. For region based evaluation the area Az under the receiver operating characteristics curve was 0.74 for dynamic programming, 0.72 for the discrete contour model, and 0.67 for region growing. The difference in Az values obtained by the dynamic programming method and region growing was statistically significant. The differences between other methods were not significant.

Rapid fingerprinting and classification of extra virgin olive oil by microjet sampling and extractive electrospray ionization mass spectrometry.

PubMed

Law, Wai Siang; Chen, Huan Wen; Balabin, Roman; Berchtold, Christian; Meier, Lukas; Zenobi, Renato

2010-04-01

Microjet sampling in combination with extractive electrospray ionization (EESI) mass spectrometry (MS) was applied to the rapid characterization and classification of extra virgin olive oil (EVOO) without any sample pretreatment. When modifying the composition of the primary ESI spray solvent, mass spectra of an identical EVOO sample showed differences. This demonstrates the capability of this technique to extract molecules with varying polarities, hence generating rich molecular information of the EVOO. Moreover, with the aid of microjet sampling, compounds of different volatilities (e.g.E-2-hexenal, trans-trans-2,4-heptadienal, tyrosol and caffeic acid) could be sampled simultaneously. EVOO data was also compared with that of other edible oils. Principal Component Analysis (PCA) was performed to discriminate EVOO and EVOO adulterated with edible oils. Microjet sampling EESI-MS was found to be a simple, rapid (less than 2 min analysis time per sample) and powerful method to obtain MS fingerprints of EVOO without requiring any complicated sample pretreatment steps.

Multivariate classification of edible salts: Simultaneous Laser-Induced Breakdown Spectroscopy and Laser-Ablation Inductively Coupled Plasma Mass Spectrometry Analysis

NASA Astrophysics Data System (ADS)

Lee, Yonghoon; Nam, Sang-Ho; Ham, Kyung-Sik; Gonzalez, Jhanis; Oropeza, Dayana; Quarles, Derrick; Yoo, Jonghyun; Russo, Richard E.

2016-04-01

Laser-Induced Breakdown Spectroscopy (LIBS) and Laser-Ablation Inductively Coupled Plasma Mass Spectrometry (LA-ICP-MS), both based on laser ablation sampling, can be employed simultaneously to obtain different chemical fingerprints from a sample. We demonstrated that this analysis approach can provide complementary information for improved classification of edible salts. LIBS could detect several of the minor metallic elements along with Na and Cl, while LA-ICP-MS spectra were used to measure non-metallic and trace heavy metal elements. Principal component analysis using LIBS and LA-ICP-MS spectra showed that their major spectral variations classified the sample salts in different ways. Three classification models were developed by using partial least squares-discriminant analysis based on the LIBS, LA-ICP-MS, and their fused data. From the cross-validation performances and confusion matrices of these models, the minor metallic elements (Mg, Ca, and K) detected by LIBS and the non-metallic (I) and trace heavy metal (Ba, W, and Pb) elements detected by LA-ICP-MS provided complementary chemical information to distinguish particular salt samples.

Value of the BI-RADS classification in MR-Mammography for diagnosis of benign and malignant breast tumors.

PubMed

Sohns, Christian; Scherrer, Martin; Staab, Wieland; Obenauer, Silvia

2011-12-01

To assess whether the BI-RADS classification in MR-Mammography (MRM) can distinguish between benign and malignant lesions. 207 MRM investigations were categorised according to BI-RADS. The results were compared to histology. All MRM studies were interpreted by two examiners. Statistical significance for the accuracy of MRM was calculated. A significant correlation between specific histology and MRM-tumour-morphology could not be reported. Mass (68%) was significant for malignancy. Significance raised with irregular shape (88%), spiculated margin (97%), rim enhancement (98%), fast initial increase (90%), post initial plateau (65%), and intermediate T2 result (82%). Highly significant for benignity was an oval mass (79%), slow initial increase (94%) and a hyperintense T2 result (77%), also an inconspicuous MRM result (77%) was often seen in benign histology. Symmetry (90%) and further post initial increase (90%) were significant, whereas a regional distribution (74%) was lowly significant for benignity. On basis of the BI-RADS classification an objective comparability and statement of diagnosis could be made highly significant. Due to the fact of false-negative and false-positive MRM-results, histology is necessary.

Sensitivity and specificity of criteria for classifying body mass index in adolescents.

PubMed

Farias Júnior, José Cazuza de; Konrad, Lisandra Maria; Rabacow, Fabiana Maluf; Grup, Susane; Araújo, Valbério Candido

2009-02-01

To estimate the prevalence of overweight among adolescents using different body mass index (BMI) classification criteria, and to determine sensitivity and specificity values for these criteria. Weight, height, and tricipital and subscapular skinfolds in 934 adolescents (462 males and 472 females) aged 14-18 years (mean age 16.2; SD=1.0) of the city of Florianópolis, Southern Brazil, in 2001. Percent fat estimated based on skinfold measurements (> or =25% in males and > or =30% in females) was used as a gold-standard for determining specificity and sensitivity of BMI classification criteria among adolescents. The different cutoff points used for classifying BMI in general resulted in similar prevalence of overweight (p>0.05). Sensitivity of the evaluated criteria was high for males (85.4% to 91.7%) and low for females (33.8 to 52.8%). Specificity of all criteria was high for both sexes (83.6% to 98.8%). Estimates of prevalence of obesity among adolescents using different BMI classification criteria were similar and highly specific for both sexes, but sensitivity for females was low.

Shape Classification Using Wasserstein Distance for Brain Morphometry Analysis.

PubMed

Su, Zhengyu; Zeng, Wei; Wang, Yalin; Lu, Zhong-Lin; Gu, Xianfeng

2015-01-01

Brain morphometry study plays a fundamental role in medical imaging analysis and diagnosis. This work proposes a novel framework for brain cortical surface classification using Wasserstein distance, based on uniformization theory and Riemannian optimal mass transport theory. By Poincare uniformization theorem, all shapes can be conformally deformed to one of the three canonical spaces: the unit sphere, the Euclidean plane or the hyperbolic plane. The uniformization map will distort the surface area elements. The area-distortion factor gives a probability measure on the canonical uniformization space. All the probability measures on a Riemannian manifold form the Wasserstein space. Given any 2 probability measures, there is a unique optimal mass transport map between them, the transportation cost defines the Wasserstein distance between them. Wasserstein distance gives a Riemannian metric for the Wasserstein space. It intrinsically measures the dissimilarities between shapes and thus has the potential for shape classification. To the best of our knowledge, this is the first. work to introduce the optimal mass transport map to general Riemannian manifolds. The method is based on geodesic power Voronoi diagram. Comparing to the conventional methods, our approach solely depends on Riemannian metrics and is invariant under rigid motions and scalings, thus it intrinsically measures shape distance. Experimental results on classifying brain cortical surfaces with different intelligence quotients demonstrated the efficiency and efficacy of our method.

Shape Classification Using Wasserstein Distance for Brain Morphometry Analysis

PubMed Central

Su, Zhengyu; Zeng, Wei; Wang, Yalin; Lu, Zhong-Lin; Gu, Xianfeng

2015-01-01

Brain morphometry study plays a fundamental role in medical imaging analysis and diagnosis. This work proposes a novel framework for brain cortical surface classification using Wasserstein distance, based on uniformization theory and Riemannian optimal mass transport theory. By Poincare uniformization theorem, all shapes can be conformally deformed to one of the three canonical spaces: the unit sphere, the Euclidean plane or the hyperbolic plane. The uniformization map will distort the surface area elements. The area-distortion factor gives a probability measure on the canonical uniformization space. All the probability measures on a Riemannian manifold form the Wasserstein space. Given any 2 probability measures, there is a unique optimal mass transport map between them, the transportation cost defines the Wasserstein distance between them. Wasserstein distance gives a Riemannian metric for the Wasserstein space. It intrinsically measures the dissimilarities between shapes and thus has the potential for shape classification. To the best of our knowledge, this is the first work to introduce the optimal mass transport map to general Riemannian manifolds. The method is based on geodesic power Voronoi diagram. Comparing to the conventional methods, our approach solely depends on Riemannian metrics and is invariant under rigid motions and scalings, thus it intrinsically measures shape distance. Experimental results on classifying brain cortical surfaces with different intelligence quotients demonstrated the efficiency and efficacy of our method. PMID:26221691

Comparing the Utility of the 2000 and 2005 Carnegie Classification Systems in Research on Students' College Experiences and Outcomes

ERIC Educational Resources Information Center

McCormick, Alexander C.; Pike, Gary R.; Kuh, George D.; Chen, Pu-Shih Daniel

2009-01-01

This study compares the explanatory power of the 2000 edition of Carnegie Classification, the 2005 revision of the classification, and selected variables underlying Carnegie's expanded 2005 classification system using data from the National Survey of Student Engagement's spring 2004 administration. Results indicate that the 2000 and 2005…

Auto-SEIA: simultaneous optimization of image processing and machine learning algorithms

NASA Astrophysics Data System (ADS)

Negro Maggio, Valentina; Iocchi, Luca

2015-02-01

Object classification from images is an important task for machine vision and it is a crucial ingredient for many computer vision applications, ranging from security and surveillance to marketing. Image based object classification techniques properly integrate image processing and machine learning (i.e., classification) procedures. In this paper we present a system for automatic simultaneous optimization of algorithms and parameters for object classification from images. More specifically, the proposed system is able to process a dataset of labelled images and to return a best configuration of image processing and classification algorithms and of their parameters with respect to the accuracy of classification. Experiments with real public datasets are used to demonstrate the effectiveness of the developed system.

Ballistics Trajectory and Impact Analysis for Insensitive Munitions and Hazard Classification Project Criteria

NASA Astrophysics Data System (ADS)

Baker, Ernest; van der Voort, Martijn; NATO Munitions Safety Information Analysis Centre Team

2017-06-01

Ballistics trajectory and impact conditions calculations were conducted in order to investigate the origin of the projection criteria for Insensitive Munitions (IM) and Hazard Classification (HC). The results show that the existing IM and HC projection criteria distance-mass relations are based on launch energy rather than impact conditions. The distance-mass relations were reproduced using TRAJCAN trajectory analysis by using launch energies of 8, 20 and 79J and calculating the maximum impact distance reached by a natural fragment (steel) launched from 1 m height. The analysis shows that at the maximum throw distances, the impact energy is generally much smaller than the launch energy. Using maximum distance projections, new distance-mass relations were developed that match the criteria based on impact energy at 15m and beyond rather than launch energy. Injury analysis was conducted using penetration injury and blunt injury models. The smallest projectile masses in the distance-mass relations are in the transition region from penetration injury to blunt injury. For this reason, blunt injury dominates the assessment of injury or lethality. State of the art blunt injury models predict only minor injury for a 20J impact. For a 79J blunt impact, major injury is likely to occur. MSIAC recommends changing the distance-mass relation that distinguishes a munitions burning response to a 20 J impact energy criterion at 15 m and updating of the UN Orange Book.

Breast mass segmentation in mammography using plane fitting and dynamic programming.

PubMed

Song, Enmin; Jiang, Luan; Jin, Renchao; Zhang, Lin; Yuan, Yuan; Li, Qiang

2009-07-01

Segmentation is an important and challenging task in a computer-aided diagnosis (CAD) system. Accurate segmentation could improve the accuracy in lesion detection and characterization. The objective of this study is to develop and test a new segmentation method that aims at improving the performance level of breast mass segmentation in mammography, which could be used to provide accurate features for classification. This automated segmentation method consists of two main steps and combines the edge gradient, the pixel intensity, as well as the shape characteristics of the lesions to achieve good segmentation results. First, a plane fitting method was applied to a background-trend corrected region-of-interest (ROI) of a mass to obtain the edge candidate points. Second, dynamic programming technique was used to find the "optimal" contour of the mass from the edge candidate points. Area-based similarity measures based on the radiologist's manually marked annotation and the segmented region were employed as criteria to evaluate the performance level of the segmentation method. With the evaluation criteria, the new method was compared with 1) the dynamic programming method developed by Timp and Karssemeijer, and 2) the normalized cut segmentation method, based on 337 ROIs extracted from a publicly available image database. The experimental results indicate that our segmentation method can achieve a higher performance level than the other two methods, and the improvements in segmentation performance level were statistically significant. For instance, the mean overlap percentage for the new algorithm was 0.71, whereas those for Timp's dynamic programming method and the normalized cut segmentation method were 0.63 (P < .001) and 0.61 (P < .001), respectively. We developed a new segmentation method by use of plane fitting and dynamic programming, which achieved a relatively high performance level. The new segmentation method would be useful for improving the accuracy of computerized detection and classification of breast cancer in mammography.

Source identification of western Oregon Douglas-fir wood cores using mass spectrometry and random forest classification1

PubMed Central

Finch, Kristen; Espinoza, Edgard; Jones, F. Andrew; Cronn, Richard

2017-01-01

Premise of the study: We investigated whether wood metabolite profiles from direct analysis in real time (time-of-flight) mass spectrometry (DART-TOFMS) could be used to determine the geographic origin of Douglas-fir wood cores originating from two regions in western Oregon, USA. Methods: Three annual ring mass spectra were obtained from 188 adult Douglas-fir trees, and these were analyzed using random forest models to determine whether samples could be classified to geographic origin, growth year, or growth year and geographic origin. Specific wood molecules that contributed to geographic discrimination were identified. Results: Douglas-fir mass spectra could be differentiated into two geographic classes with an accuracy between 70% and 76%. Classification models could not accurately classify sample mass spectra based on growth year. Thirty-two molecules were identified as key for classifying western Oregon Douglas-fir wood cores to geographic origin. Discussion: DART-TOFMS is capable of detecting minute but regionally informative differences in wood molecules over a small geographic scale, and these differences made it possible to predict the geographic origin of Douglas-fir wood with moderate accuracy. Studies involving DART-TOFMS, alone and in combination with other technologies, will be relevant for identifying the geographic origin of illegally harvested wood. PMID:28529831

Integration of multi-array sensors and support vector machines for the detection and classification of organophosphate nerve agents

NASA Astrophysics Data System (ADS)

Land, Walker H., Jr.; Sadik, Omowunmi A.; Embrechts, Mark J.; Leibensperger, Dale; Wong, Lut; Wanekaya, Adam; Uematsu, Michiko

2003-08-01

Due to the increased threats of chemical and biological weapons of mass destruction (WMD) by international terrorist organizations, a significant effort is underway to develop tools that can be used to detect and effectively combat biochemical warfare. Furthermore, recent events have highlighted awareness that chemical and biological agents (CBAs) may become the preferred, cheap alternative WMD, because these agents can effectively attack large populations while leaving infrastructures intact. Despite the availability of numerous sensing devices, intelligent hybrid sensors that can detect and degrade CBAs are virtually nonexistent. This paper reports the integration of multi-array sensors with Support Vector Machines (SVMs) for the detection of organophosphates nerve agents using parathion and dichlorvos as model stimulants compounds. SVMs were used for the design and evaluation of new and more accurate data extraction, preprocessing and classification. Experimental results for the paradigms developed using Structural Risk Minimization, show a significant increase in classification accuracy when compared to the existing AromaScan baseline system. Specifically, the results of this research has demonstrated that, for the Parathion versus Dichlorvos pair, when compared to the AromaScan baseline system: (1) a 23% improvement in the overall ROC Az index using the S2000 kernel, with similar improvements with the Gaussian and polynomial (of degree 2) kernels, (2) a significant 173% improvement in specificity with the S2000 kernel. This means that the number of false negative errors were reduced by 173%, while making no false positive errors, when compared to the AromaScan base line performance. (3) The Gaussian and polynomial kernels demonstrated similar specificity at 100% sensitivity. All SVM classifiers provided essentially perfect classification performance for the Dichlorvos versus Trichlorfon pair. For the most difficult classification task, the Parathion versus Paraoxon pair, the following results were achieved (using the three SVM kernels: (1) ROC Az indices from approximately 93% to greater than 99%, (2) partial Az values from ~79% to 93%, (3) specificities from 76% to ~84% at 100 and 98% sensitivity, and (4) PPVs from 73% to ~84% at 100% and 98% sensitivities. These are excellent results, considering only one atom differentiates these nerve agents.

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

NASA Technical Reports Server (NTRS)

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

1977-01-01

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

Review of Medical Image Classification using the Adaptive Neuro-Fuzzy Inference System

PubMed Central

Hosseini, Monireh Sheikh; Zekri, Maryam

2012-01-01

Image classification is an issue that utilizes image processing, pattern recognition and classification methods. Automatic medical image classification is a progressive area in image classification, and it is expected to be more developed in the future. Because of this fact, automatic diagnosis can assist pathologists by providing second opinions and reducing their workload. This paper reviews the application of the adaptive neuro-fuzzy inference system (ANFIS) as a classifier in medical image classification during the past 16 years. ANFIS is a fuzzy inference system (FIS) implemented in the framework of an adaptive fuzzy neural network. It combines the explicit knowledge representation of an FIS with the learning power of artificial neural networks. The objective of ANFIS is to integrate the best features of fuzzy systems and neural networks. A brief comparison with other classifiers, main advantages and drawbacks of this classifier are investigated. PMID:23493054

Coregistered photoacoustic and ultrasound imaging and classification of ovarian cancer: ex vivo and in vivo studies

NASA Astrophysics Data System (ADS)

Salehi, Hassan S.; Li, Hai; Merkulov, Alex; Kumavor, Patrick D.; Vavadi, Hamed; Sanders, Melinda; Kueck, Angela; Brewer, Molly A.; Zhu, Quing

2016-04-01

Most ovarian cancers are diagnosed at advanced stages due to the lack of efficacious screening techniques. Photoacoustic tomography (PAT) has a potential to image tumor angiogenesis and detect early neovascular changes of the ovary. We have developed a coregistered PAT and ultrasound (US) prototype system for real-time assessment of ovarian masses. Features extracted from PAT and US angular beams, envelopes, and images were input to a logistic classifier and a support vector machine (SVM) classifier to diagnose ovaries as benign or malignant. A total of 25 excised ovaries of 15 patients were studied and the logistic and SVM classifiers achieved sensitivities of 70.4 and 87.7%, and specificities of 95.6 and 97.9%, respectively. Furthermore, the ovaries of two patients were noninvasively imaged using the PAT/US system before surgical excision. By using five significant features and the logistic classifier, 12 out of 14 images (86% sensitivity) from a malignant ovarian mass and all 17 images (100% specificity) from a benign mass were accurately classified; the SVM correctly classified 10 out of 14 malignant images (71% sensitivity) and all 17 benign images (100% specificity). These initial results demonstrate the clinical potential of the PAT/US technique for ovarian cancer diagnosis.

5 CFR 9701.221 - Classification requirements.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 5 Administrative Personnel 3 2010-01-01 2010-01-01 false Classification requirements. 9701.221 Section 9701.221 Administrative Personnel DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT... HUMAN RESOURCES MANAGEMENT SYSTEM Classification Classification Process § 9701.221 Classification...

Nursing Classification Systems

PubMed Central

Henry, Suzanne Bakken; Mead, Charles N.

1997-01-01

Abstract Our premise is that from the perspective of maximum flexibility of data usage by computer-based record (CPR) systems, existing nursing classification systems are necessary, but not sufficient, for representing important aspects of “what nurses do.” In particular, we have focused our attention on those classification systems that represent nurses' clinical activities through the abstraction of activities into categories of nursing interventions. In this theoretical paper, we argue that taxonomic, combinatorial vocabularies capable of coding atomic-level nursing activities are required to effectively capture in a reproducible and reversible manner the clinical decisions and actions of nurses, and that, without such vocabularies and associated grammars, potentially important clinical process data is lost during the encoding process. Existing nursing intervention classification systems do not fulfill these criteria. As background to our argument, we first present an overview of the content, methods, and evaluation criteria used in previous studies whose focus has been to evaluate the effectiveness of existing coding and classification systems. Next, using the Ingenerf typology of taxonomic vocabularies, we categorize the formal type and structure of three existing nursing intervention classification systems—Nursing Interventions Classification, Omaha System, and Home Health Care Classification. Third, we use records from home care patients to show examples of lossy data transformation, the loss of potentially significant atomic data, resulting from encoding using each of the three systems. Last, we provide an example of the application of a formal representation methodology (conceptual graphs) which we believe could be used as a model to build the required combinatorial, taxonomic vocabulary for representing nursing interventions. PMID:9147341

Gender classification in low-resolution surveillance video: in-depth comparison of random forests and SVMs

NASA Astrophysics Data System (ADS)

Geelen, Christopher D.; Wijnhoven, Rob G. J.; Dubbelman, Gijs; de With, Peter H. N.

2015-03-01

This research considers gender classification in surveillance environments, typically involving low-resolution images and a large amount of viewpoint variations and occlusions. Gender classification is inherently difficult due to the large intra-class variation and interclass correlation. We have developed a gender classification system, which is successfully evaluated on two novel datasets, which realistically consider the above conditions, typical for surveillance. The system reaches a mean accuracy of up to 90% and approaches our human baseline of 92.6%, proving a high-quality gender classification system. We also present an in-depth discussion of the fundamental differences between SVM and RF classifiers. We conclude that balancing the degree of randomization in any classifier is required for the highest classification accuracy. For our problem, an RF-SVM hybrid classifier exploiting the combination of HSV and LBP features results in the highest classification accuracy of 89.9 0.2%, while classification computation time is negligible compared to the detection time of pedestrians.

Spiking of serum specimens with exogenous reporter peptides for mass spectrometry based protease profiling as diagnostic tool.

PubMed

Findeisen, Peter; Peccerella, Teresa; Post, Stefan; Wenz, Frederik; Neumaier, Michael

2008-04-01

Serum is a difficult matrix for the identification of biomarkers by mass spectrometry (MS). This is due to high-abundance proteins and their complex processing by a multitude of endogenous proteases making rigorous standardisation difficult. Here, we have investigated the use of defined exogenous reporter peptides as substrates for disease-specific proteases with respect to improved standardisation and disease classification accuracy. A recombinant N-terminal fragment of the Adenomatous Polyposis Coli (APC) protein was digested with trypsin to yield a peptide mixture for subsequent Reporter Peptide Spiking (RPS) of serum. Different preanalytical handling of serum samples was simulated by storage of serum samples for up to 6 h at ambient temperature, followed by RPS, further incubation under standardised conditions and testing for stability of protease-generated MS profiles. To demonstrate the superior classification accuracy achieved by RPS, a pilot profiling experiment was performed using serum specimens from pancreatic cancer patients (n = 50) and healthy controls (n = 50). After RPS six different peak categories could be defined, two of which (categories C and D) are modulated by endogenous proteases. These latter are relevant for improved classification accuracy as shown by enhanced disease-specific classification from 78% to 87% in unspiked and spiked samples, respectively. Peaks of these categories presented with unchanged signal intensities regardless of preanalytical conditions. The use of RPS generally improved the signal intensities of protease-generated peptide peaks. RPS circumvents preanalytical variabilities and improves classification accuracies. Our approach will be helpful to introduce MS-based proteomic profiling into routine laboratory testing.

Fourier Transform Infrared (FT-IR) and Laser Ablation Inductively Coupled Plasma-Mass Spectrometry (LA-ICP-MS) Imaging of Cerebral Ischemia: Combined Analysis of Rat Brain Thin Cuts Toward Improved Tissue Classification.

PubMed

Balbekova, Anna; Lohninger, Hans; van Tilborg, Geralda A F; Dijkhuizen, Rick M; Bonta, Maximilian; Limbeck, Andreas; Lendl, Bernhard; Al-Saad, Khalid A; Ali, Mohamed; Celikic, Minja; Ofner, Johannes

2018-02-01

Microspectroscopic techniques are widely used to complement histological studies. Due to recent developments in the field of chemical imaging, combined chemical analysis has become attractive. This technique facilitates a deepened analysis compared to single techniques or side-by-side analysis. In this study, rat brains harvested one week after induction of photothrombotic stroke were investigated. Adjacent thin cuts from rats' brains were imaged using Fourier transform infrared (FT-IR) microspectroscopy and laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS). The LA-ICP-MS data were normalized using an internal standard (a thin gold layer). The acquired hyperspectral data cubes were fused and subjected to multivariate analysis. Brain regions affected by stroke as well as unaffected gray and white matter were identified and classified using a model based on either partial least squares discriminant analysis (PLS-DA) or random decision forest (RDF) algorithms. The RDF algorithm demonstrated the best results for classification. Improved classification was observed in the case of fused data in comparison to individual data sets (either FT-IR or LA-ICP-MS). Variable importance analysis demonstrated that both molecular and elemental content contribute to the improved RDF classification. Univariate spectral analysis identified biochemical properties of the assigned tissue types. Classification of multisensor hyperspectral data sets using an RDF algorithm allows access to a novel and in-depth understanding of biochemical processes and solid chemical allocation of different brain regions.

Utilization of patient classification systems in Swedish hospitals and the degree of satisfaction among nursing staff.

PubMed

Perroca, Marcia Galan; Ek, Anna-Christina

2007-07-01

Although patient classification tools have been used in Sweden since the 1980s, few studies have examined how they are utilized and monitored. This paper investigates the patient classification systems implemented in hospitals in the country as well as the level of satisfaction of nurses with the implemented instrument. A postal survey method was used in which a total of 128 questionnaires were sent to nurse managers. Twenty-three hospitals were identified with patient classification systems currently in operation. The Zebra and Beakta systems are the most commonly used instruments. Nurse managers appear to be satisfied with the patient classification systems in use on their wards as a whole except for their inability to measure the quality of care provided, the time spent to use the instruments and the fact that the administration do not estimate nursing staff requirements using the system.

Bacteriocins from Gram-Negative Bacteria: A Classification?

NASA Astrophysics Data System (ADS)

Rebuffat, Sylvie

Bacteria produce an arsenal of toxic peptides and proteins, which are termed bacteriocins and play a role in mediating the dynamics of microbial populations and communities. Bacteriocins from Gram-negative bacteria arise mainly from Enterobacteriaceae. They assemble into two main families: high molecular mass modular proteins (30-80 kDa) termed colicins and low molecular mass peptides (between 1 and 10 kDa) termed microcins. The production of colicins is mediated by the SOS response regulon, which plays a role in the response of many bacteria to DNA damages. Microcins are highly stable hydrophobic peptides that are produced under stress conditions, particularly nutrient depletion. Colicins and microcins are found essentially in Escherichia coli, but several other Gram-negative species also produce bacteriocin-like substances. This chapter presents the basis of a classification of colicins and microcins.

Development of neural network techniques for finger-vein pattern classification

NASA Astrophysics Data System (ADS)

Wu, Jian-Da; Liu, Chiung-Tsiung; Tsai, Yi-Jang; Liu, Jun-Ching; Chang, Ya-Wen

2010-02-01

A personal identification system using finger-vein patterns and neural network techniques is proposed in the present study. In the proposed system, the finger-vein patterns are captured by a device that can transmit near infrared through the finger and record the patterns for signal analysis and classification. The biometric system for verification consists of a combination of feature extraction using principal component analysis and pattern classification using both back-propagation network and adaptive neuro-fuzzy inference systems. Finger-vein features are first extracted by principal component analysis method to reduce the computational burden and removes noise residing in the discarded dimensions. The features are then used in pattern classification and identification. To verify the effect of the proposed adaptive neuro-fuzzy inference system in the pattern classification, the back-propagation network is compared with the proposed system. The experimental results indicated the proposed system using adaptive neuro-fuzzy inference system demonstrated a better performance than the back-propagation network for personal identification using the finger-vein patterns.

A Hybrid Classification System for Heart Disease Diagnosis Based on the RFRS Method.

PubMed

Liu, Xiao; Wang, Xiaoli; Su, Qiang; Zhang, Mo; Zhu, Yanhong; Wang, Qiugen; Wang, Qian

2017-01-01

Heart disease is one of the most common diseases in the world. The objective of this study is to aid the diagnosis of heart disease using a hybrid classification system based on the ReliefF and Rough Set (RFRS) method. The proposed system contains two subsystems: the RFRS feature selection system and a classification system with an ensemble classifier. The first system includes three stages: (i) data discretization, (ii) feature extraction using the ReliefF algorithm, and (iii) feature reduction using the heuristic Rough Set reduction algorithm that we developed. In the second system, an ensemble classifier is proposed based on the C4.5 classifier. The Statlog (Heart) dataset, obtained from the UCI database, was used for experiments. A maximum classification accuracy of 92.59% was achieved according to a jackknife cross-validation scheme. The results demonstrate that the performance of the proposed system is superior to the performances of previously reported classification techniques.

Designing a Classification System for Internet Offenders: Doing Cognitive Distortions

ERIC Educational Resources Information Center

Hundersmarck, Steven F.; Durkin, Keith F.; Delong, Ronald L.

2007-01-01

Televised features such as NBC's "To Catch a Predator" have highlighted the growing problem posed by Internet sexual predators. This paper reports on the authors' attempts in designing a classification system for Internet offenders. The classification system was designed based on existing theory, understanding the nature of Internet offenders and…

78 FR 64925 - Request for Comments on Proposed Elimination of Patents Search Templates

Federal Register 2010, 2011, 2012, 2013, 2014

2013-10-30

... is a detailed, collaborative, and dynamic system that will enable patent examiners and the public to... launched in January 2013. CPC is a detailed, dynamic classification system that is based on the IPC and... updating. Further, the USPTO launched a new classification system, the Cooperative Patent Classification...

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

ERIC Educational Resources Information Center

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

2010-01-01

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

Towards a consensus on a hearing preservation classification system.

PubMed

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

2013-01-01

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

Classifying diseases and remedies in ethnomedicine and ethnopharmacology.

PubMed

Staub, Peter O; Geck, Matthias S; Weckerle, Caroline S; Casu, Laura; Leonti, Marco

2015-11-04

Ethnopharmacology focuses on the understanding of local and indigenous use of medicines and therefore an emic approach is inevitable. Often, however, standard biomedical disease classifications are used to describe and analyse local diseases and remedies. Standard classifications might be a valid tool for cross-cultural comparisons and bioprospecting purposes but are not suitable to understand the local perception of disease and use of remedies. Different standard disease classification systems exist but their suitability for cross-cultural comparisons of ethnomedical data has never been assessed. Depending on the research focus, (I) ethnomedical, (II) cross-cultural, and (III) bioprospecting, we provide suggestions for the use of specific classification systems. We analyse three different standard biomedical classification systems (the International Classification of Diseases (ICD); the Economic Botany Data Collection Standard (EBDCS); and the International Classification of Primary Care (ICPC)), and discuss their value for categorizing diseases of ethnomedical systems and their suitability for cross-cultural research in ethnopharmacology. Moreover, based on the biomedical uses of all approved plant derived biomedical drugs, we propose a biomedical therapy-based classification system as a guide for the discovery of drugs from ethnopharmacological sources. Widely used standards, such as the International Classification of Diseases (ICD) by the WHO and the Economic Botany Data Collection Standard (EBDCS) are either technically challenging due to a categorisation system based on clinical examinations, which are usually not possible during field research (ICD) or lack clear biomedical criteria combining disorders and medical effects in an imprecise and confusing way (EBDCS). The International Classification of Primary Care (ICPC), also accepted by the WHO, has more in common with ethnomedical reality than the ICD or the EBDCS, as the categories are designed according to patient's perceptions and are less influenced by clinical medicine. Since diagnostic tools are not required, medical ethnobotanists and ethnopharmacologists can easily classify reported symptoms and complaints with the ICPC in one of the "chapters" based on 17 body systems, psychological and social problems. Also the biomedical uses of plant-derived drugs are classifiable into 17 broad organ- and therapy-based use-categories but can easily be divided into more specific subcategories. Depending on the research focus (I-III) we propose the following classification systems: I. Ethnomedicine: Ethnomedicine is culture-bound and local classifications have to be understood from an emic perspective. Consequently, the application of prefabricated, "one-size fits all" biomedical classification schemes is of limited value. II. Cross-cultural analysis: The ICPC is a suitable standard that can be applied but modified as required. III. Bioprospecting: We suggest a biomedical therapy-driven classification system with currently 17 use-categories based on biomedical uses of all approved plant derived natural product drugs. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Categorization in the wild.

PubMed

Glushko, Robert J; Maglio, Paul P; Matlock, Teenie; Barsalou, Lawrence W

2008-04-01

In studying categorization, cognitive science has focused primarily on cultural categorization, ignoring individual and institutional categorization. Because recent technological developments have made individual and institutional classification systems much more available and powerful, our understanding of the cognitive and social mechanisms that produce these systems is increasingly important. Furthermore, key aspects of categorization that have received little previous attention emerge from considering diverse types of categorization together, such as the social factors that create stability in classification systems, and the interoperability that shared conceptual systems establish between agents. Finally, the profound impact of recent technological developments on classification systems indicates that basic categorization mechanisms are highly adaptive, producing new classification systems as the situations in which they operate change.

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

PubMed

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

2011-01-01

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

phenoSeeder - A Robot System for Automated Handling and Phenotyping of Individual Seeds.

PubMed

Jahnke, Siegfried; Roussel, Johanna; Hombach, Thomas; Kochs, Johannes; Fischbach, Andreas; Huber, Gregor; Scharr, Hanno

2016-11-01

The enormous diversity of seed traits is an intriguing feature and critical for the overwhelming success of higher plants. In particular, seed mass is generally regarded to be key for seedling development but is mostly approximated by using scanning methods delivering only two-dimensional data, often termed seed size. However, three-dimensional traits, such as the volume or mass of single seeds, are very rarely determined in routine measurements. Here, we introduce a device named phenoSeeder, which enables the handling and phenotyping of individual seeds of very different sizes. The system consists of a pick-and-place robot and a modular setup of sensors that can be versatilely extended. Basic biometric traits detected for individual seeds are two-dimensional data from projections, three-dimensional data from volumetric measures, and mass, from which seed density is also calculated. Each seed is tracked by an identifier and, after phenotyping, can be planted, sorted, or individually stored for further evaluation or processing (e.g. in routine seed-to-plant tracking pipelines). By investigating seeds of Arabidopsis (Arabidopsis thaliana), rapeseed (Brassica napus), and barley (Hordeum vulgare), we observed that, even for apparently round-shaped seeds of rapeseed, correlations between the projected area and the mass of seeds were much weaker than between volume and mass. This indicates that simple projections may not deliver good proxies for seed mass. Although throughput is limited, we expect that automated seed phenotyping on a single-seed basis can contribute valuable information for applications in a wide range of wild or crop species, including seed classification, seed sorting, and assessment of seed quality. © 2016 American Society of Plant Biologists. All Rights Reserved.

phenoSeeder - A Robot System for Automated Handling and Phenotyping of Individual Seeds1[OPEN

PubMed Central

Roussel, Johanna; Kochs, Johannes; Huber, Gregor; Scharr, Hanno

2016-01-01

The enormous diversity of seed traits is an intriguing feature and critical for the overwhelming success of higher plants. In particular, seed mass is generally regarded to be key for seedling development but is mostly approximated by using scanning methods delivering only two-dimensional data, often termed seed size. However, three-dimensional traits, such as the volume or mass of single seeds, are very rarely determined in routine measurements. Here, we introduce a device named phenoSeeder, which enables the handling and phenotyping of individual seeds of very different sizes. The system consists of a pick-and-place robot and a modular setup of sensors that can be versatilely extended. Basic biometric traits detected for individual seeds are two-dimensional data from projections, three-dimensional data from volumetric measures, and mass, from which seed density is also calculated. Each seed is tracked by an identifier and, after phenotyping, can be planted, sorted, or individually stored for further evaluation or processing (e.g. in routine seed-to-plant tracking pipelines). By investigating seeds of Arabidopsis (Arabidopsis thaliana), rapeseed (Brassica napus), and barley (Hordeum vulgare), we observed that, even for apparently round-shaped seeds of rapeseed, correlations between the projected area and the mass of seeds were much weaker than between volume and mass. This indicates that simple projections may not deliver good proxies for seed mass. Although throughput is limited, we expect that automated seed phenotyping on a single-seed basis can contribute valuable information for applications in a wide range of wild or crop species, including seed classification, seed sorting, and assessment of seed quality. PMID:27663410

Assessing three fuel classification systems and their maps using Forest Inventory and Analysis (FIA) surface fuel measurements

Treesearch

Robert E. Keane; Jason M. Herynk; Chris Toney; Shawn P. Urbanski; Duncan C. Lutes; Roger D. Ottmar

2015-01-01

Fuel classifications are integral tools in fire management and planning because they are used as inputs to fire behavior and effects simulation models. Fuel Loading Models (FLMs) and Fuel Characteristic Classification System (FCCSs) fuelbeds are the most popular classifications used throughout wildland fire science and management, but they have yet to be thoroughly...

5 CFR 9901.222 - Review of classification decisions.

Code of Federal Regulations, 2011 CFR

2011-01-01

....222 Section 9901.222 Administrative Personnel DEPARTMENT OF DEFENSE HUMAN RESOURCES MANAGEMENT AND LABOR RELATIONS SYSTEMS (DEPARTMENT OF DEFENSE-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF DEFENSE NATIONAL SECURITY PERSONNEL SYSTEM (NSPS) Classification Classification Process § 9901.222 Review of...

5 CFR 9701.222 - Reconsideration of classification decisions.

Code of Federal Regulations, 2010 CFR

2010-01-01

... decisions. 9701.222 Section 9701.222 Administrative Personnel DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM (DEPARTMENT OF HOMELAND SECURITY-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM Classification Classification Process § 9701.222...

Maxillectomy defects: a suggested classification scheme.

PubMed

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

2013-06-01

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

Interplay of biopharmaceutics, biopharmaceutics drug disposition and salivary excretion classification systems

PubMed Central

Idkaidek, Nasir M.

2013-01-01

The aim of this commentary is to investigate the interplay of Biopharmaceutics Classification System (BCS), Biopharmaceutics Drug Disposition Classification System (BDDCS) and Salivary Excretion Classification System (SECS). BCS first classified drugs based on permeability and solubility for the purpose of predicting oral drug absorption. Then BDDCS linked permeability with hepatic metabolism and classified drugs based on metabolism and solubility for the purpose of predicting oral drug disposition. On the other hand, SECS classified drugs based on permeability and protein binding for the purpose of predicting the salivary excretion of drugs. The role of metabolism, rather than permeability, on salivary excretion is investigated and the results are not in agreement with BDDCS. Conclusion The proposed Salivary Excretion Classification System (SECS) can be used as a guide for drug salivary excretion based on permeability (not metabolism) and protein binding. PMID:24493977

A Classification Methodology and Retrieval Model to Support Software Reuse

DTIC Science & Technology

1988-01-01

Dewey Decimal Classification ( DDC 18), an enumerative scheme, occupies 40 pages [Buchanan 19791. Langridge [19731 states that the facets listed in the...sense of historical importance or wide spread use. The schemes are: Dewey Decimal Classification ( DDC ), Universal Decimal Classification (UDC...Classification Systems ..... ..... 2.3.3 Library Classification__- .52 23.3.1 Dewey Decimal Classification -53 2.33.2 Universal Decimal Classification 55 2333

A new tool for post-AGB SED classification

NASA Astrophysics Data System (ADS)

Bendjoya, P.; Suarez, O.; Galluccio, L.; Michel, O.

We present the results of an unsupervised classification method applied on a set of 344 spectral energy distributions (SED) of post-AGB stars extracted from the Torun catalogue of Galactic post-AGB stars. This method aims to find a new unbiased method for post-AGB star classification based on the information contained in the IR region of the SED (fluxes, IR excess, colours). We used the data from IRAS and MSX satellites, and from the 2MASS survey. We applied a classification method based on the construction of the dataset of a minimal spanning tree (MST) with the Prim's algorithm. In order to build this tree, different metrics have been tested on both flux and color indices. Our method is able to classify the set of 344 post-AGB stars in 9 distinct groups according to their SEDs.

The impact of OCR accuracy on automated cancer classification of pathology reports.

PubMed

Zuccon, Guido; Nguyen, Anthony N; Bergheim, Anton; Wickman, Sandra; Grayson, Narelle

2012-01-01

To evaluate the effects of Optical Character Recognition (OCR) on the automatic cancer classification of pathology reports. Scanned images of pathology reports were converted to electronic free-text using a commercial OCR system. A state-of-the-art cancer classification system, the Medical Text Extraction (MEDTEX) system, was used to automatically classify the OCR reports. Classifications produced by MEDTEX on the OCR versions of the reports were compared with the classification from a human amended version of the OCR reports. The employed OCR system was found to recognise scanned pathology reports with up to 99.12% character accuracy and up to 98.95% word accuracy. Errors in the OCR processing were found to minimally impact on the automatic classification of scanned pathology reports into notifiable groups. However, the impact of OCR errors is not negligible when considering the extraction of cancer notification items, such as primary site, histological type, etc. The automatic cancer classification system used in this work, MEDTEX, has proven to be robust to errors produced by the acquisition of freetext pathology reports from scanned images through OCR software. However, issues emerge when considering the extraction of cancer notification items.

Autonomous target recognition using remotely sensed surface vibration measurements

NASA Astrophysics Data System (ADS)

Geurts, James; Ruck, Dennis W.; Rogers, Steven K.; Oxley, Mark E.; Barr, Dallas N.

1993-09-01

The remotely measured surface vibration signatures of tactical military ground vehicles are investigated for use in target classification and identification friend or foe (IFF) systems. The use of remote surface vibration sensing by a laser radar reduces the effects of partial occlusion, concealment, and camouflage experienced by automatic target recognition systems using traditional imagery in a tactical battlefield environment. Linear Predictive Coding (LPC) efficiently represents the vibration signatures and nearest neighbor classifiers exploit the LPC feature set using a variety of distortion metrics. Nearest neighbor classifiers achieve an 88 percent classification rate in an eight class problem, representing a classification performance increase of thirty percent from previous efforts. A novel confidence figure of merit is implemented to attain a 100 percent classification rate with less than 60 percent rejection. The high classification rates are achieved on a target set which would pose significant problems to traditional image-based recognition systems. The targets are presented to the sensor in a variety of aspects and engine speeds at a range of 1 kilometer. The classification rates achieved demonstrate the benefits of using remote vibration measurement in a ground IFF system. The signature modeling and classification system can also be used to identify rotary and fixed-wing targets.

Framework for evaluating disease severity measures in older adults with comorbidity.

PubMed

Boyd, Cynthia M; Weiss, Carlos O; Halter, Jeff; Han, K Carol; Ershler, William B; Fried, Linda P

2007-03-01

Accounting for the influence of concurrent conditions on health and functional status for both research and clinical decision-making purposes is especially important in older adults. Although approaches to classifying severity of individual diseases and conditions have been developed, the utility of these classification systems has not been evaluated in the presence of multiple conditions. We present a framework for evaluating severity classification systems for common chronic diseases. The framework evaluates the: (a) goal or purpose of the classification system; (b) physiological and/or functional criteria for severity graduation; and (c) potential reliability and validity of the system balanced against burden and costs associated with classification. Approaches to severity classification of individual diseases were not originally conceived for the study of comorbidity. Therefore, they vary greatly in terms of objectives, physiological systems covered, level of severity characterization, reliability and validity, and costs and burdens. Using different severity classification systems to account for differing levels of disease severity in a patient with multiple diseases, or, assessing global disease burden may be challenging. Most approaches to severity classification are not adequate to address comorbidity. Nevertheless, thoughtful use of some existing approaches and refinement of others may advance the study of comorbidity and diagnostic and therapeutic approaches to patients with multimorbidity.

Some crucial corona and prominence observations

NASA Technical Reports Server (NTRS)

Tandberg-Hanssen, E. A.

1986-01-01

A number of theories and hypotheses are currently being developed to explain the often complex behavior of corona and prominence plasmas. In order to test the theories and hypotheses certain crucial observations are necessary. Some of these observations are examined and a few conclusions are drawn. Corona mass balance, corona and prominence classifications, prominence formation and stability, and coronal mass ejection are dicussed.

Rapid classification of enzymes in cleaning products by hydrolysis, mass spectrometry and linear discriminant analysis.

PubMed

Beneito-Cambra, Miriam; Herrero-Martínez, José Manuel; Simó-Alfonso, Ernesto F; Ramis-Ramos, Guillermo

2008-11-01

A method for the rapid classification of proteases, lipases, amylases and cellulases used as enhancers in cleaning products, based on precipitation with acetone, hydrolysis with HCl, dilution of the hydrolysates with ethanol, and direct infusion into the electrospray ion source of an ion-trap mass spectrometer, has been developed. The abundances of the ([M+H]+ ions of the amino acids, from the hydrolysates of both the enzyme industrial concentrates and the detergent bases spiked with them, were used to construct linear discriminant analysis models, capable of distinguishing between the enzyme classes. For this purpose, the variables were normalized as follows: (A) the ion abundance of each amino acid was divided by the sum of the ion abundances of all the amino acids in the corresponding mass spectrum; (B) the ratios of pairs of ion abundances were obtained by dividing the ion abundance of each amino acid by each one of the ion abundances of the other 17 amino acids in the corresponding mass spectrum. Using normalization procedure B, excellent class-resolution between proteases, lipases, amylases and cellulases was achieved. In all cases, enzymes in industrial concentrates and manufactured cleaning products were correctly classified with >98% assignment probability.

Discrimination of Aspergillus isolates at the species and strain level by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry fingerprinting.

PubMed

Hettick, Justin M; Green, Brett J; Buskirk, Amanda D; Kashon, Michael L; Slaven, James E; Janotka, Erika; Blachere, Francoise M; Schmechel, Detlef; Beezhold, Donald H

2008-09-15

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) was used to generate highly reproducible mass spectral fingerprints for 12 species of fungi of the genus Aspergillus and 5 different strains of Aspergillus flavus. Prior to MALDI-TOF MS analysis, the fungi were subjected to three 1-min bead beating cycles in an acetonitrile/trifluoroacetic acid solvent. The mass spectra contain abundant peaks in the range of 5 to 20kDa and may be used to discriminate between species unambiguously. A discriminant analysis using all peaks from the MALDI-TOF MS data yielded error rates for classification of 0 and 18.75% for resubstitution and cross-validation methods, respectively. If a subset of 28 significant peaks is chosen, resubstitution and cross-validation error rates are 0%. Discriminant analysis of the MALDI-TOF MS data for 5 strains of A. flavus using all peaks yielded error rates for classification of 0 and 5% for resubstitution and cross-validation methods, respectively. These data indicate that MALDI-TOF MS data may be used for unambiguous identification of members of the genus Aspergillus at both the species and strain levels.

A consensus view of fold space: Combining SCOP, CATH, and the Dali Domain Dictionary

PubMed Central

Day, Ryan; Beck, David A.C.; Armen, Roger S.; Daggett, Valerie

2003-01-01

We have determined consensus protein-fold classifications on the basis of three classification methods, SCOP, CATH, and Dali. These classifications make use of different methods of defining and categorizing protein folds that lead to different views of protein-fold space. Pairwise comparisons of domains on the basis of their fold classifications show that much of the disagreement between the classification systems is due to differing domain definitions rather than assigning the same domain to different folds. However, there are significant differences in the fold assignments between the three systems. These remaining differences can be explained primarily in terms of the breadth of the fold classifications. Many structures may be defined as having one fold in one system, whereas far fewer are defined as having the analogous fold in another system. By comparing these folds for a nonredundant set of proteins, the consensus method breaks up broad fold classifications and combines restrictive fold classifications into metafolds, creating, in effect, an averaged view of fold space. This averaged view requires that the structural similarities between proteins having the same metafold be recognized by multiple classification systems. Thus, the consensus map is useful for researchers looking for fold similarities that are relatively independent of the method used to compare proteins. The 30 most populated metafolds, representing the folds of about half of a nonredundant subset of the PDB, are presented here. The full list of metafolds is presented on the Web. PMID:14500873

A consensus view of fold space: combining SCOP, CATH, and the Dali Domain Dictionary.

PubMed

Day, Ryan; Beck, David A C; Armen, Roger S; Daggett, Valerie

2003-10-01

We have determined consensus protein-fold classifications on the basis of three classification methods, SCOP, CATH, and Dali. These classifications make use of different methods of defining and categorizing protein folds that lead to different views of protein-fold space. Pairwise comparisons of domains on the basis of their fold classifications show that much of the disagreement between the classification systems is due to differing domain definitions rather than assigning the same domain to different folds. However, there are significant differences in the fold assignments between the three systems. These remaining differences can be explained primarily in terms of the breadth of the fold classifications. Many structures may be defined as having one fold in one system, whereas far fewer are defined as having the analogous fold in another system. By comparing these folds for a nonredundant set of proteins, the consensus method breaks up broad fold classifications and combines restrictive fold classifications into metafolds, creating, in effect, an averaged view of fold space. This averaged view requires that the structural similarities between proteins having the same metafold be recognized by multiple classification systems. Thus, the consensus map is useful for researchers looking for fold similarities that are relatively independent of the method used to compare proteins. The 30 most populated metafolds, representing the folds of about half of a nonredundant subset of the PDB, are presented here. The full list of metafolds is presented on the Web.

Analysis of biliary anatomy according to different classification systems.

PubMed

Deka, Pranjal; Islam, Mahibul; Jindal, Deepti; Kumar, Niteen; Arora, Ankur; Negi, Sanjay Singh

2014-01-01

Variations in biliary anatomy are common, and different classifications have been described. These classification systems have not been compared to each other in a single cohort. We report such variations in biliary anatomy on magnetic resonance cholangiopancreatography (MRCP) using six different classification systems. In 299 patients undergoing MRCP for various indications, biliary anatomy was classified as described by Couinaud (1957), Huang (1996), Karakas (2008), Choi (2003), Champetier (1994), and Ohkubo (2004). Correlation with direct cholangiography and vascular anatomy was done. Bile duct dimensions were measured. Cystic duct junction and pancreaticobiliary ductal junction (PBDJ) were classified. Normal biliary anatomy was noted in 57.8 %. The most common variants were Couinaud type D2, Choi type 3A, Huang type A1, Champetier type a, Ohkubo types D and J, and Karakas type 2a. The Ohkubo classification was the most appropriate; 3.1 % of right ducts and 6.3 % of left ducts with variant anatomy could not be classified using the Ohkubo classification. There was a good agreement between MRCP and direct cholangiography (ĸ = 0.9). Anomalous PBDJ was noted in 8.7 %. Variant biliary anatomy was not associated with gender (p = 0.194) or variant vascular anatomy (p = 0.24). Although each classification system has its merits and demerits, some anatomical variations cannot be classified using any of the previously described classifications. The Ohkubo classification system is the most applicable as it considers most clinically relevant variations pertinent to hepatobiliary surgery.

A Mapping from the Human Factors Analysis and Classification System (DOD-HFACS) to the Domains of Human Systems Integration (HSI)

DTIC Science & Technology

2009-11-01

Equation Chapter 1 Section 1 A MAPPING FROM THE HUMAN FACTORS ANALYSIS AND CLASSIFICATION SYSTEM (DOD...OMB control number. 1. REPORT DATE NOV 2009 2. REPORT TYPE 3. DATES COVERED 4. TITLE AND SUBTITLE A Mapping from the Human Factors Analysis ...7 The Human Factors Analysis and Classification System .................................................. 7 Mapping of DoD

Three-column classification and Schatzker classification: a three- and two-dimensional computed tomography characterisation and analysis of tibial plateau fractures.

PubMed

Patange Subba Rao, Sheethal Prasad; Lewis, James; Haddad, Ziad; Paringe, Vishal; Mohanty, Khitish

2014-10-01

The aim of the study was to evaluate inter-observer reliability and intra-observer reproducibility between the three-column classification and Schatzker classification systems using 2D and 3D CT models. Fifty-two consecutive patients with tibial plateau fractures were evaluated by five orthopaedic surgeons. All patients were classified into Schatzker and three-column classification systems using x-rays and 2D and 3D CT images. The inter-observer reliability was evaluated in the first round and the intra-observer reliability was determined during the second round 2 weeks later. The average intra-observer reproducibility for the three-column classification was from substantial to excellent in all sub classifications, as compared with Schatzker classification. The inter-observer kappa values increased from substantial to excellent in three-column classification and to moderate in Schatzker classification The average values for three-column classification for all the categories are as follows: (I-III) k2D = 0.718, 95% CI 0.554-0.864, p < 0.0001 and average 3D = 0.874, 95% CI 0.754-0.890, p < 0.0001. For Schatzker classification system, the average values for all six categories are as follows: (I-VI) k2D = 0.536, 95% CI 0.365-0.685, p < 0.0001 and average k3D = 0.552 95% CI 0.405-0.700, p < 0.0001. The values are statistically significant. Statistically significant inter-observer values in both rounds were noted with the three-column classification, making it statistically an excellent agreement. The intra-observer reproducibility for the three-column classification improved as compared with the Schatzker classification. The three-column classification seems to be an effective way to characterise and classify fractures of tibial plateau.

Stand up time in tunnel base on rock mass rating Bieniawski 1989

NASA Astrophysics Data System (ADS)

Nata, Refky Adi; M. S., Murad

2017-11-01

RMR (Rock Mass Rating), or also known as the geo mechanics classification has been modified and made as the International Standard in determination of rock mass weighting. Rock Mass Rating Classification has been developed by Bieniawski (since 1973, 1976, and 1989). The goals of this research are investigate the class of rocks base on classification rock mass rating Bieniawski 1989, to investigate the long mass of the establishment rocks, and also to investigate the distance of the opening tunnel without a support especially in underground mine. On the research measuring: strength intact rock material, RQD (Rock Quality Designation), spacing of discontinuities, condition of discontinuities, groundwater, and also adjustment for discontinuity orientations. On testing samples in the laboratory for coal obtained strong press UCS of 30.583 MPa. Based on the classification according to Bieniawski has a weight of 4. As for silt stone obtained strong press of 35.749 MPa, gained weight also by 4. From the results of the measurements obtained for coal RQD value average 97.38 %, so it has a weight of 20. While in siltstone RQD value average 90.10 % so it has weight 20 also. On the coal the average distance measured in field is 22.6 cm so as to obtain a weight of 10, while for siltstone has an average is 148 cm, so it has weight = 15. Presistence in the field vary, on coal = 57.28 cm, so it has weight is 6 and persistence on siltstone 47 cm then does it weight to 6. Base on table Rock Mass Rating according to Bieniawski 1989, aperture on coal = 0.41 mm. That is located in the range 0.1-1 mm, so it has weight is 4. Besides that, for the siltstone aperture = 21.43 mm. That is located in the range > 5 mm, so the weight = 0. Roughness condition in coal and siltstone classified into rough so it has weight 5. Infilling condition in coal and siltstone classified into none so it has weight 6. Weathering condition in coal and siltstone classified into highly weathered so it has weight 1. Groundwater condition in coal classified into dripping so it has weight 4. and siltstone classified into completely dry so it has weight 15. Discontinuity orientation in coal parallel axis of the tunnel. The range is 251°-290° so unfavorable. It has weight = -10. In siltstone also discontinuity parallel axis of the tunnel. The range located between 241°-300°. Base on weighting parameters according to Bieniawski 1989, concluded for rocks are there in class II with value is 62, and able to establishment until 6 months. For the distance of the opening tunnel without a support as far as 8 meters.

Geotechnical Risk Classification for Underground Mines / Klasyfikacja Poziomu Zagrożenia Geotechnicznego W Kopalniach Podziemnych

NASA Astrophysics Data System (ADS)

Mishra, Ritesh Kumar; Rinne, Mikael

2015-03-01

Underground mining activities are prone to major hazards largely owing to geotechnical reasons. Mining combined with the confined working space and uncertain geotechnical data leads to hazards having the potential of catastrophic consequences. These incidents have the potential of causing multiple fatalities and large financial damages. Use of formal risk assessment in the past has demonstrated an important role in the prediction and prevention of accidents in risk prone industries such as petroleum, nuclear and aviation. This paper proposes a classification system for underground mining operations based on their geotechnical risk levels. The classification is done based on the type of mining method employed and the rock mass in which it is carried out. Mining methods have been classified in groups which offer similar geotechnical risk. The rock mass classification has been proposed based on bulk rock mass properties which are collected as part of the routine mine planning. This classification has been subdivided for various stages of mine planning to suit the extent of available data. Alpha-numeric coding has been proposed to identify a mining operation based on the competency of rock and risk of geotechnical failures. This alpha numeric coding has been further extended to identify mining activity under `Geotechnical Hazard Potential (GHP)'. GHP has been proposed to be used as a preliminary tool of risk assessment and risk ranking for a mining activity. The aim of such classification is to be used as a guideline for the justification of a formal geotechnical risk assessment. Górnictwo podziemne pociąga za sobą różnorakie zagrożenia spowodowane przez uwarunkowania geotechniczne. Urabianie złoża w połączeniu z pracą w zamkniętej przestrzeni oraz z niepewnymi danymi geotechnicznymi powodować może zagrożenia, które w konsekwencji prowadzić mogą do wypadków, a te potencjalnie powodować mogą skutki śmiertelne dla osób oraz poważne straty finansowe. Wykorzystanie przepisowych metod oceny ryzyka w przeszłości wykazało ich istotną rolę w przewidywaniu i zapobieganiu wypadkom i zagrożeniom w dziedzinach najbardziej na nie narażonych, a więc w przemyśle naftowym, jądrowym oraz w lotnictwie. W niniejszej pracy zaproponowano system klasyfikacji operacji w górnictwie podziemnym w oparciu o poziom zagrożenia geotechnicznego. Klasyfikacji dokonano uwzględniając zastosowana metodę urabiania oraz rodzaj urabianego górotworu. Przedstawiono kategorie metod urabiania o podobnym poziomie zagrożenia geotechnicznego. Zaproponowano klasyfikację górotworu na podstawie właściwości wytrzymałościowych określanych rutynowo na etapie planowania kopalni. Klasyfikacja ta podzielona jest na kilka pod-etapów odpowiadającym etapom planowania kopalni, tak by uwzględnić zakres dostępnych na każdym etapie danych. Zastosowano kodowanie alfanumeryczne dla wskazania metody urabiania w oparciu o dane o zwięzłości skały i ryzyko zagrożenia geotechnicznego. Kodowanie alfanumeryczne zostało następnie rozszerzone dla identyfikacji operacji górniczych w ramach kategorii "Poziom zagrożenia geotechnicznego". Wskaźnik ten wykorzystywany jest jako wstępne narzędzie oceny ryzyka wystąpienia zagrożenia oraz klasyfikacji poziomu zagrożenia związanego z działalnością górniczą. Celem takiej klasyfikacji jest jej wykorzystanie jako wytycznych i uzasadnienia dla stosowania formalnych metod oceny ryzyka geotechnicznego.

A land use and land cover classification system for use with remote sensor data

USGS Publications Warehouse

Anderson, James R.; Hardy, Ernest E.; Roach, John T.; Witmer, Richard E.

1976-01-01

The framework of a national land use and land cover classification system is presented for use with remote sensor data. The classification system has been developed to meet the needs of Federal and State agencies for an up-to-date overview of land use and land cover throughout the country on a basis that is uniform in categorization at the more generalized first and second levels and that will be receptive to data from satellite and aircraft remote sensors. The proposed system uses the features of existing widely used classification systems that are amenable to data derived from remote sensing sources. It is intentionally left open-ended so that Federal, regional, State, and local agencies can have flexibility in developing more detailed land use classifications at the third and fourth levels in order to meet their particular needs and at the same time remain compatible with each other and the national system. Revision of the land use classification system as presented in U.S. Geological Survey Circular 671 was undertaken in order to incorporate the results of extensive testing and review of the categorization and definitions.

Classification of stillbirths is an ongoing dilemma.

PubMed

Nappi, Luigi; Trezza, Federica; Bufo, Pantaleo; Riezzo, Irene; Turillazzi, Emanuela; Borghi, Chiara; Bonaccorsi, Gloria; Scutiero, Gennaro; Fineschi, Vittorio; Greco, Pantaleo

2016-10-01

To compare different classification systems in a cohort of stillbirths undergoing a comprehensive workup; to establish whether a particular classification system is most suitable and useful in determining cause of death, purporting the lowest percentage of unexplained death. Cases of stillbirth at gestational age 22-41 weeks occurring at the Department of Gynecology and Obstetrics of Foggia University during a 4 year period were collected. The World Health Organization (WHO) diagnosis of stillbirth was used. All the data collection was based on the recommendations of an Italian diagnostic workup for stillbirth. Two expert obstetricians reviewed all cases and classified causes according to five classification systems. Relevant Condition at Death (ReCoDe) and Causes Of Death and Associated Conditions (CODAC) classification systems performed best in retaining information. The ReCoDe system provided the lowest rate of unexplained stillbirth (14%) compared to de Galan-Roosen (16%), CODAC (16%), Tulip (18%), Wigglesworth (62%). Classification of stillbirth is influenced by the multiplicity of possible causes and factors related to fetal death. Fetal autopsy, placental histology and cytogenetic analysis are strongly recommended to have a complete diagnostic evaluation. Commonly employed classification systems performed differently in our experience, the most satisfactory being the ReCoDe. Given the rate of "unexplained" cases, none can be considered optimal and further efforts are necessary to work out a clinically useful system.

DORS: DDC Online Retrieval System.

ERIC Educational Resources Information Center

Liu, Songqiao; Svenonius, Elaine

1991-01-01

Describes the Dewey Online Retrieval System (DORS), which was developed at the University of California, Los Angeles (UCLA), to experiment with classification-based search strategies in online catalogs. Classification structures in automated information retrieval are discussed; and specifications for a classification retrieval interface are…

Automated simultaneous multiple feature classification of MTI data

NASA Astrophysics Data System (ADS)

Harvey, Neal R.; Theiler, James P.; Balick, Lee K.; Pope, Paul A.; Szymanski, John J.; Perkins, Simon J.; Porter, Reid B.; Brumby, Steven P.; Bloch, Jeffrey J.; David, Nancy A.; Galassi, Mark C.

2002-08-01

Los Alamos National Laboratory has developed and demonstrated a highly capable system, GENIE, for the two-class problem of detecting a single feature against a background of non-feature. In addition to the two-class case, however, a commonly encountered remote sensing task is the segmentation of multispectral image data into a larger number of distinct feature classes or land cover types. To this end we have extended our existing system to allow the simultaneous classification of multiple features/classes from multispectral data. The technique builds on previous work and its core continues to utilize a hybrid evolutionary-algorithm-based system capable of searching for image processing pipelines optimized for specific image feature extraction tasks. We describe the improvements made to the GENIE software to allow multiple-feature classification and describe the application of this system to the automatic simultaneous classification of multiple features from MTI image data. We show the application of the multiple-feature classification technique to the problem of classifying lava flows on Mauna Loa volcano, Hawaii, using MTI image data and compare the classification results with standard supervised multiple-feature classification techniques.

A statistical approach to root system classification

PubMed Central

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

2013-01-01

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

A statistical approach to root system classification.

PubMed

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

2013-01-01

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

Inter-rater reliability of a modified version of Delitto et al.’s classification-based system for low back pain: a pilot study

PubMed Central

Apeldoorn, Adri T.; van Helvoirt, Hans; Ostelo, Raymond W.; Meihuizen, Hanneke; Kamper, Steven J.; van Tulder, Maurits W.; de Vet, Henrica C. W.

2016-01-01

Study design Observational inter-rater reliability study. Objectives To examine: (1) the inter-rater reliability of a modified version of Delitto et al.’s classification-based algorithm for patients with low back pain; (2) the influence of different levels of familiarity with the system; and (3) the inter-rater reliability of algorithm decisions in patients who clearly fit into a subgroup (clear classifications) and those who do not (unclear classifications). Methods Patients were examined twice on the same day by two of three participating physical therapists with different levels of familiarity with the system. Patients were classified into one of four classification groups. Raters were blind to the others’ classification decision. In order to quantify the inter-rater reliability, percentages of agreement and Cohen’s Kappa were calculated. Results A total of 36 patients were included (clear classification n = 23; unclear classification n = 13). The overall rate of agreement was 53% and the Kappa value was 0·34 [95% confidence interval (CI): 0·11–0·57], which indicated only fair inter-rater reliability. Inter-rater reliability for patients with a clear classification (agreement 52%, Kappa value 0·29) was not higher than for patients with an unclear classification (agreement 54%, Kappa value 0·33). Familiarity with the system (i.e. trained with written instructions and previous research experience with the algorithm) did not improve the inter-rater reliability. Conclusion Our pilot study challenges the inter-rater reliability of the classification procedure in clinical practice. Therefore, more knowledge is needed about factors that affect the inter-rater reliability, in order to improve the clinical applicability of the classification scheme. PMID:27559279

Poisoning by Herbs and Plants: Rapid Toxidromic Classification and Diagnosis.

PubMed

Diaz, James H

2016-03-01

The American Association of Poison Control Centers has continued to report approximately 50,000 telephone calls or 8% of incoming calls annually related to plant exposures, mostly in children. Although the frequency of plant ingestions in children is related to the presence of popular species in households, adolescents may experiment with hallucinogenic plants; and trekkers and foragers may misidentify poisonous plants as edible. Since plant exposures have continued at a constant rate, the objectives of this review were (1) to review the epidemiology of plant poisonings; and (2) to propose a rapid toxidromic classification system for highly toxic plant ingestions for field use by first responders in comparison to current classification systems. Internet search engines were queried to identify and select peer-reviewed articles on plant poisonings using the key words in order to classify plant poisonings into four specific toxidromes: cardiotoxic, neurotoxic, cytotoxic, and gastrointestinal-hepatotoxic. A simple toxidromic classification system of plant poisonings may permit rapid diagnoses of highly toxic versus less toxic and nontoxic plant ingestions both in households and outdoors; direct earlier management of potentially serious poisonings; and reduce costly inpatient evaluations for inconsequential plant ingestions. The current textbook classification schemes for plant poisonings were complex in comparison to the rapid classification system; and were based on chemical nomenclatures and pharmacological effects, and not on clearly presenting toxidromes. Validation of the rapid toxidromic classification system as compared to existing chemical classification systems for plant poisonings will require future adoption and implementation of the toxidromic system by its intended users. Copyright © 2016 Wilderness Medical Society. Published by Elsevier Inc. All rights reserved.

Forest site classification in the interior uplands

Treesearch

Glendon W. Smalley

1989-01-01

Classification and evaluation of forest sites is an essential step in managing central hardwood forests. In Note 4.01, The Importance of Site Quality, the usefulness of land classification systems was discussed. The present Note describes one of those systems in more detail. It is an easy-to-use system developed for the Cumberland Plateau and Highland Rim-Pennyroyal...

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

ERIC Educational Resources Information Center

Williams, Florence M.

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

Prior-to-Secondary School Course Classification System: School Codes for the Exchange of Data (SCED). NFES 2011-801

ERIC Educational Resources Information Center

National Forum on Education Statistics, 2011

2011-01-01

In this handbook, "Prior-to-Secondary School Course Classification System: School Codes for the Exchange of Data" (SCED), the National Center for Education Statistics (NCES) and the National Forum on Education Statistics have extended the existing secondary course classification system with codes and descriptions for courses offered at…

Linking the integrated management of childhood illness (IMCI) and health information system (HIS) classifications: issues and options.

PubMed Central

Rowe, A. K.; Hirnschall, G.; Lambrechts, T.; Bryce, J.

1999-01-01

Differences in the terms used to classify diseases in the Integrated Management of Childhood Illness (IMCI) guidelines and for health information system (HIS) disease surveillance could easily create confusion among health care workers. If the equivalent terms in the two classifications are not clear to health workers who are following the guidelines, they may have problems in performing the dual activities of case management and disease surveillance. These difficulties could adversely affect an individual's performance as well as the overall effectiveness of the IMCI strategy or HIS surveillance, or both. We interviewed key informants to determine the effect of these differences between the IMCI and HIS classifications on the countries that were implementing the IMCI guidelines. Four general approaches for addressing the problem were identified: translating the IMCI classifications into HIS classifications; changing the HIS list to include the IMCI classifications; using both the IMCI and HIS classification systems at the time of consultations; and doing nothing. No single approach can satisfy the needs of all countries. However, if the short-term or medium-term goal of IMCI planners is to find a solution that will reduce the problem for health workers and is also easy to implement, the approach most likely to succeed is translation of IMCI classifications into HIS classifications. Where feasible, a modification of the health information system to include the IMCI classifications may also be considered. PMID:10680246

The ICI classification for calcaneal injuries: a validation study.

PubMed

Frima, Herman; Eshuis, Rienk; Mulder, Paul; Leenen, Luke

2012-06-01

The integral classification of injuries (ICI), by Zwipp et al. has been developed as a classification system for injuries of the bones, joints, cartilage and ligaments of the foot. It follows the principles of the comprehensive classification of fractures by Müller et al. The ICI was developed for 'everyday use' and scientific purposes. Our aim was to perform a validation study for this classification system applied to the calcaneal injuries. A panel of five experienced trauma and orthopaedic surgeons evaluated the ICI score in 20 calcaneal injuries. After 2 months, a second classification was performed in a different order. Inter- and intra-observer variability were evaluated by kappa statistics. Panel members were not able to evaluate capsule and ligamental injuries based on X-ray and computed tomography (CT) films. Two injuries were excluded for logistical reasons. The inter-observer agreement based on 18 injuries of bone and joints was slight; kappa 0.14 (90% confidence interval (CI): 0.05-0.22). The intra-observer agreement was fair; kappa 0.31 (90% CI: 0.22-0.41). Overall, the panel rated the system as very complicated and not practical. The ICI is a complicated classification system with slight to fair inter- and intra-observer variabilities. It might not be a practical classification system for calcaneal injuries in 'everyday use' or scientific purposes. Copyright © 2011 Elsevier Ltd. All rights reserved.

The Communication Function Classification System: cultural adaptation, validity, and reliability of the Farsi version for patients with cerebral palsy.

PubMed

Soleymani, Zahra; Joveini, Ghodsiye; Baghestani, Ahmad Reza

2015-03-01

This study developed a Farsi language Communication Function Classification System and then tested its reliability and validity. Communication Function Classification System is designed to classify the communication functions of individuals with cerebral palsy. Up until now, there has been no instrument for assessment of this communication function in Iran. The English Communication Function Classification System was translated into Farsi and cross-culturally modified by a panel of experts. Professionals and parents then assessed the content validity of the modified version. A backtranslation of the Farsi version was confirmed by the developer of the English Communication Function Classification System. Face validity was assessed by therapists and parents of 10 patients. The Farsi Communication Function Classification System was administered to 152 individuals with cerebral palsy (age, 2 to 18 years; median age, 10 years; mean age, 9.9 years; standard deviation, 4.3 years). Inter-rater reliability was analyzed between parents, occupational therapists, and speech and language pathologists. The test-retest reliability was assessed for 75 patients with a 14 day interval between tests. The inter-rater reliability of the Communication Function Classification System was 0.81 between speech and language pathologists and occupational therapists, 0.74 between parents and occupational therapists, and 0.88 between parents and speech and language pathologists. The test-retest reliability was 0.96 for occupational therapists, 0.98 for speech and language pathologists, and 0.94 for parents. The findings suggest that the Farsi version of Communication Function Classification System is a reliable and valid measure that can be used in clinical settings to assess communication function in patients with cerebral palsy. Copyright © 2015 Elsevier Inc. All rights reserved.

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

NASA Astrophysics Data System (ADS)

Jürgens, Björn; Herrero-Solana, Victor

2017-04-01

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

37 CFR 2.85 - Classification schedules.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 37 Patents, Trademarks, and Copyrights 1 2013-07-01 2013-07-01 false Classification schedules. 2..., DEPARTMENT OF COMMERCE RULES OF PRACTICE IN TRADEMARK CASES Classification § 2.85 Classification schedules. (a) International classification system. Section 6.1 of this chapter sets forth the international...

37 CFR 2.85 - Classification schedules.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 37 Patents, Trademarks, and Copyrights 1 2012-07-01 2012-07-01 false Classification schedules. 2..., DEPARTMENT OF COMMERCE RULES OF PRACTICE IN TRADEMARK CASES Classification § 2.85 Classification schedules. (a) International classification system. Section 6.1 of this chapter sets forth the international...

37 CFR 2.85 - Classification schedules.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 37 Patents, Trademarks, and Copyrights 1 2014-07-01 2014-07-01 false Classification schedules. 2..., DEPARTMENT OF COMMERCE RULES OF PRACTICE IN TRADEMARK CASES Classification § 2.85 Classification schedules. (a) International classification system. Section 6.1 of this chapter sets forth the international...

37 CFR 2.85 - Classification schedules.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 37 Patents, Trademarks, and Copyrights 1 2011-07-01 2011-07-01 false Classification schedules. 2..., DEPARTMENT OF COMMERCE RULES OF PRACTICE IN TRADEMARK CASES Classification § 2.85 Classification schedules. (a) International classification system. Section 6.1 of this chapter sets forth the international...

37 CFR 2.85 - Classification schedules.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 37 Patents, Trademarks, and Copyrights 1 2010-07-01 2010-07-01 false Classification schedules. 2..., DEPARTMENT OF COMMERCE RULES OF PRACTICE IN TRADEMARK CASES Classification § 2.85 Classification schedules. (a) International classification system. Section 6.1 of this chapter sets forth the international...

76 FR 76896 - International Anti-Fouling System Certificate

Federal Register 2010, 2011, 2012, 2013, 2014

2011-12-09

...-fouling System (IAFS) Certificate to the list of certificates a recognized classification society may..., 2001. This final rule will enable recognized classification societies to apply to the Coast Guard for... the Coast Guard to authorize recognized classification societies to issue IAFS Certificates...

Classification of O Stars in the Yellow-Green: The Exciting Star VES 735

NASA Astrophysics Data System (ADS)

Kerton, C. R.; Ballantyne, D. R.; Martin, P. G.

1999-05-01

Acquiring data for spectral classification of heavily reddened stars using traditional criteria in the blue-violet region of the spectrum can be prohibitively time consuming using small to medium sized telescopes. One such star is the Vatican Observatory emission-line star VES 735, which we have found excites the H II region KR 140. In order to classify VES 735, we have constructed an atlas of stellar spectra of O stars in the yellow-green (4800-5420 Å). We calibrate spectral type versus the line ratio He I lambda4922:He II lambda5411, showing that this ratio should be useful for the classification of heavily reddened O stars associated with H II regions. Application to VES 735 shows that the spectral type is O8.5. The absolute magnitude suggests luminosity class V. Comparison of the rate of emission of ionizing photons and the bolometric luminosity of VES 735, inferred from radio and infrared measurements of the KR 140 region, to recent stellar models gives consistent evidence for a main-sequence star of mass 25 M_solar and age less than a few million years with a covering factor 0.4-0.5 by the nebular material. Spectra taken in the red (6500-6700 Å) show that the stellar Hα emission is double-peaked about the systemic velocity and slightly variable. Hβ is in absorption, so that the emission-line classification is ``(e)''. However, unlike the case of the more well-known O(e) star zeta Oph, the emission from VES 735 appears to be long-lived rather than episodic.

Classification systems in nursing: formalizing nursing knowledge and implications for nursing information systems.

PubMed

Goossen, W T; Epping, P J; Abraham, I L

1996-03-01

The development of nursing information systems (NIS) is often hampered by the fact that nursing lacks a unified nursing terminology and classification system. Currently there exist various initiatives in this area. We address the question as to how current initiatives in the development of nursing terminology and classification systems can contribute towards the development of NIS. First, the rationale behind the formalization of nursing knowledge is discussed. Next, using a framework for nursing information processing, the most important developments in the field of nursing on formalization, terminology and classification are critically reviewed. The initiatives discussed include nursing terminology projects in several countries, and the International Classification of Nursing Practice. Suggestions for further developments in the area are discussed. Finally, implications for NIS are presented, as well as the relationships of these components to other sections of an integrated computerized patient record.

A systematic literature review of automated clinical coding and classification systems

PubMed Central

Williams, Margaret; Fenton, Susan H; Jenders, Robert A; Hersh, William R

2010-01-01

Clinical coding and classification processes transform natural language descriptions in clinical text into data that can subsequently be used for clinical care, research, and other purposes. This systematic literature review examined studies that evaluated all types of automated coding and classification systems to determine the performance of such systems. Studies indexed in Medline or other relevant databases prior to March 2009 were considered. The 113 studies included in this review show that automated tools exist for a variety of coding and classification purposes, focus on various healthcare specialties, and handle a wide variety of clinical document types. Automated coding and classification systems themselves are not generalizable, nor are the results of the studies evaluating them. Published research shows these systems hold promise, but these data must be considered in context, with performance relative to the complexity of the task and the desired outcome. PMID:20962126

A systematic literature review of automated clinical coding and classification systems.

PubMed

Stanfill, Mary H; Williams, Margaret; Fenton, Susan H; Jenders, Robert A; Hersh, William R

2010-01-01

Clinical coding and classification processes transform natural language descriptions in clinical text into data that can subsequently be used for clinical care, research, and other purposes. This systematic literature review examined studies that evaluated all types of automated coding and classification systems to determine the performance of such systems. Studies indexed in Medline or other relevant databases prior to March 2009 were considered. The 113 studies included in this review show that automated tools exist for a variety of coding and classification purposes, focus on various healthcare specialties, and handle a wide variety of clinical document types. Automated coding and classification systems themselves are not generalizable, nor are the results of the studies evaluating them. Published research shows these systems hold promise, but these data must be considered in context, with performance relative to the complexity of the task and the desired outcome.

Reflecting on the structure of soil classification systems: insights from a proposal for integrating subsoil data into soil information systems

NASA Astrophysics Data System (ADS)

Dondeyne, Stefaan; Juilleret, Jérôme; Vancampenhout, Karen; Deckers, Jozef; Hissler, Christophe

2017-04-01

Classification of soils in both World Reference Base for soil resources (WRB) and Soil Taxonomy hinges on the identification of diagnostic horizons and characteristics. However as these features often occur within the first 100 cm, these classification systems convey little information on subsoil characteristics. An integrated knowledge of the soil, soil-to-substratum and deeper substratum continuum is required when dealing with environmental issues such as vegetation ecology, water quality or the Critical Zone in general. Therefore, we recently proposed a classification system of the subsolum complementing current soil classification systems. By reflecting on the structure of the subsoil classification system which is inspired by WRB, we aim at fostering a discussion on some potential future developments of WRB. For classifying the subsolum we define Regolite, Saprolite, Saprock and Bedrock as four Subsolum Reference Groups each corresponding to different weathering stages of the subsoil. Principal qualifiers can be used to categorize intergrades of these Subsoil Reference Groups while morphologic and lithologic characteristics can be presented with supplementary qualifiers. We argue that adopting a low hierarchical structure - akin to WRB and in contrast to a strong hierarchical structure as in Soil Taxonomy - offers the advantage of having an open classification system avoiding the need for a priori knowledge of all possible combinations which may be encountered in the field. Just as in WRB we also propose to use principal and supplementary qualifiers as a second level of classification. However, in contrast to WRB we propose to reserve the principal qualifiers for intergrades and to regroup the supplementary qualifiers into thematic categories (morphologic or lithologic). Structuring the qualifiers in this manner should facilitate the integration and handling of both soil and subsoil classification units into soil information systems and calls for paying attention to these structural issues in future developments of WRB.

Osteochondritis dissecans of the humeral capitellum: reliability of four classification systems using radiographs and computed tomography.

PubMed

Claessen, Femke M A P; van den Ende, Kimberly I M; Doornberg, Job N; Guitton, Thierry G; Eygendaal, Denise; van den Bekerom, Michel P J

2015-10-01

The radiographic appearance of osteochondritis dissecans (OCD) of the humeral capitellum varies according to the stage of the lesion. It is important to evaluate the stage of OCD lesion carefully to guide treatment. We compared the interobserver reliability of currently used classification systems for OCD of the humeral capitellum to identify the most reliable classification system. Thirty-two musculoskeletal radiologists and orthopaedic surgeons specialized in elbow surgery from several countries evaluated anteroposterior and lateral radiographs and corresponding computed tomography (CT) scans of 22 patients to classify the stage of OCD of the humeral capitellum according to the classification systems developed by (1) Minami, (2) Berndt and Harty, (3) Ferkel and Sgaglione, and (4) Anderson on a Web-based study platform including a Digital Imaging and Communications in Medicine viewer. Magnetic resonance imaging was not evaluated as part of this study. We measured agreement among observers using the Siegel and Castellan multirater κ. All OCD classification systems, except for Berndt and Harty, which had poor agreement among observers (κ = 0.20), had fair interobserver agreement: κ was 0.27 for the Minami, 0.23 for Anderson, and 0.22 for Ferkel and Sgaglione classifications. The Minami Classification was significantly more reliable than the other classifications (P < .001). The Minami Classification was the most reliable for classifying different stages of OCD of the humeral capitellum. However, it is unclear whether radiographic evidence of OCD of the humeral capitellum, as categorized by the Minami Classification, guides treatment in clinical practice as a result of this fair agreement. Copyright © 2015 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Elsevier Inc. All rights reserved.

Deep learning application: rubbish classification with aid of an android device

NASA Astrophysics Data System (ADS)

Liu, Sijiang; Jiang, Bo; Zhan, Jie

2017-06-01

Deep learning is a very hot topic currently in pattern recognition and artificial intelligence researches. Aiming at the practical problem that people usually don't know correct classifications some rubbish should belong to, based on the powerful image classification ability of the deep learning method, we have designed a prototype system to help users to classify kinds of rubbish. Firstly the CaffeNet Model was adopted for our classification network training on the ImageNet dataset, and the trained network was deployed on a web server. Secondly an android app was developed for users to capture images of unclassified rubbish, upload images to the web server for analyzing backstage and retrieve the feedback, so that users can obtain the classification guide by an android device conveniently. Tests on our prototype system of rubbish classification show that: an image of one single type of rubbish with origin shape can be better used to judge its classification, while an image containing kinds of rubbish or rubbish with changed shape may fail to help users to decide rubbish's classification. However, the system still shows promising auxiliary function for rubbish classification if the network training strategy can be optimized further.

Classification systems for natural resource management

USGS Publications Warehouse

Kleckner, Richard L.

1981-01-01

Resource managers employ various types of resource classification systems in their management activities such as inventory, mapping, and data analysis. Classification is the ordering or arranging of objects into groups or sets on the basis of their relationships, and as such, provide the resource managers with a structure for organizing their needed information. In addition of conforming to certain logical principles, resource classifications should be flexible, widely applicable to a variety of environmental conditions, and useable with minimal training. The process of classification may be approached from the bottom up (aggregation) or the top down (subdivision) or a combination of both, depending on the purpose of the classification. Most resource classification systems in use today focus on a single resource and are used for a single, limited purpose. However, resource managers now must employ the concept of multiple use in their management activities. What they need is an integrated, ecologically based approach to resource classification which would fulfill multiple-use mandates. In an effort to achieve resource-data compatibility and data sharing among Federal agencies, and interagency agreement has been signed by five Federal agencies to coordinate and cooperate in the area of resource classification and inventory.

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.

48 CFR 245.201-73 - Security classification.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 48 Federal Acquisition Regulations System 3 2011-10-01 2011-10-01 false Security classification... Procedures 245.201-73 Security classification. Follow the procedures at PGI 245.201-73 for security classification. ...

48 CFR 245.201-73 - Security classification.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 48 Federal Acquisition Regulations System 3 2012-10-01 2012-10-01 false Security classification... Procedures 245.201-73 Security classification. Follow the procedures at PGI 245.201-73 for security classification. ...

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

PubMed Central

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

2011-01-01

Purpose The aim of this study was to investigate the interobserver agreement of the Lenke and King classifications for adolescent idiopathic scoliosis, and to compare the results of surgery performed based on classification of the scoliosis according to each of these classification systems. Methods The study was conducted in Shohada Hospital in Tabriz, Iran, between 2009 and 2010. First, a reliability assessment was undertaken to assess interobserver agreement of the Lenke and King classifications for adolescent idiopathic scoliosis. Second, postoperative efficacy and safety of surgery performed based on the Lenke and King classifications were compared. Kappa coefficients of agreement were calculated to assess the agreement. Outcomes were compared using bivariate tests and repeated measures analysis of variance. Results A low to moderate interobserver agreement was observed for the King classification; the Lenke classification yielded mostly high agreement coefficients. The outcome of surgery was not found to be substantially different between the two systems. Conclusion Based on the results, the Lenke classification method seems advantageous. This takes into consideration the Lenke classification’s priority in providing details of curvatures in different anatomical surfaces to explain precise intensity of scoliosis, that it has higher interobserver agreement scores, and also that it leads to noninferior postoperative results compared with the King classification method. PMID:22267934

Clinical Application of Six Current Classification Systems for Iatrogenic Bile Duct Injuries after Cholecystectomy.

PubMed

Velidedeoglu, Mehmet; Arikan, Akif Enes; Uludag, Sezgin Server; Olgun, Deniz Cebi; Kilic, Fahrettin; Kapan, Metin

2015-05-01

Due to being a severe complication, iatrogenic bile duct injury is still a challenging issue for surgeons in gallbladder surgery. However, a commonly accepted classification describing the type of injury has not been available yet. This study aims to evaluate ability of six current classification systems to discriminate bile duct injury patterns. Twelve patients, who were referred to our clinic because of iatrogenic bile duct injury after laparoscopic cholecystectomy were reviewed retrospectively. We described type of injury for each patient according to current six different classifications. 9 patients underwent definitive biliary reconstruction. Bismuth, Strasberg-Bismuth, Stewart-Way and Neuhaus classifications do not consider vascular involvement, Siewert system does, but only for the tangential lesions without structural loss of duct and lesion with a structural defect of hepatic or common bile duct. Siewert, Neuhaus and Stewart-Way systems do not discriminate between lesions at or above bifurcation of the hepatic duct. The Hannover classification may resolve the missing aspects of other systems by describing additional vascular involvement and location of the lesion at or above bifurcation.

a Gsa-Svm Hybrid System for Classification of Binary Problems

NASA Astrophysics Data System (ADS)

Sarafrazi, Soroor; Nezamabadi-pour, Hossein; Barahman, Mojgan

2011-06-01

This paperhybridizesgravitational search algorithm (GSA) with support vector machine (SVM) and made a novel GSA-SVM hybrid system to improve the classification accuracy in binary problems. GSA is an optimization heuristic toolused to optimize the value of SVM kernel parameter (in this paper, radial basis function (RBF) is chosen as the kernel function). The experimental results show that this newapproach can achieve high classification accuracy and is comparable to or better than the particle swarm optimization (PSO)-SVM and genetic algorithm (GA)-SVM, which are two hybrid systems for classification.

A review on exudates detection methods for diabetic retinopathy.

PubMed

Joshi, Shilpa; Karule, P T

2018-01-01

The presence of exudates on the retina is the most characteristic symptom of diabetic retinopathy. As exudates are among early clinical signs of DR, their detection would be an essential asset to the mass screening task and serve as an important step towards automatic grading and monitoring of the disease. Reliable identification and classification of exudates are of inherent interest in an automated diabetic retinopathy screening system. Here we review the numerous early studies that used for automatic exudates detection with the aim of providing decision support in addition to reducing the workload of an ophthalmologist. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

A Clinical Approach to the Diagnosis of Acid-Base Disorders

PubMed Central

Bear, Robert A.

1986-01-01

The ability to diagnose and manage acid-base disorders rapidly and effectively is essential to the care of critically ill patients. This article presents an approach to the diagnosis of pure and mixed acid-base disorders, metabolic or respiratory. The approach taken is based on using the law of mass-action equation as it applies to the bicarbonate buffer system (Henderson equation), using sub-classifications for diagnostic purposes of causes of metabolic acidosis and metabolic alkalosis, and using a knowledge of the well-defined and predictable compensatory responses that attempt to limit the change in pH in each of the primary acid-base disorders. PMID:21267134

43 CFR 2461.2 - Classifications.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 43 Public Lands: Interior 2 2011-10-01 2011-10-01 false Classifications. 2461.2 Section 2461.2..., DEPARTMENT OF THE INTERIOR LAND RESOURCE MANAGEMENT (2000) BUREAU INITIATED CLASSIFICATION SYSTEM Multiple-Use Classification Procedures § 2461.2 Classifications. Not less than 60 days after publication of the...

43 CFR 2461.2 - Classifications.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 43 Public Lands: Interior 2 2014-10-01 2014-10-01 false Classifications. 2461.2 Section 2461.2..., DEPARTMENT OF THE INTERIOR LAND RESOURCE MANAGEMENT (2000) BUREAU INITIATED CLASSIFICATION SYSTEM Multiple-Use Classification Procedures § 2461.2 Classifications. Not less than 60 days after publication of the...

28 CFR 524.73 - Classification procedures.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 28 Judicial Administration 2 2014-07-01 2014-07-01 false Classification procedures. 524.73 Section..., CLASSIFICATION, AND TRANSFER CLASSIFICATION OF INMATES Central Inmate Monitoring (CIM) System § 524.73 Classification procedures. (a) Initial assignment. Except as provided for in paragraphs (a) (1) through (4) of...

43 CFR 2461.2 - Classifications.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 43 Public Lands: Interior 2 2012-10-01 2012-10-01 false Classifications. 2461.2 Section 2461.2..., DEPARTMENT OF THE INTERIOR LAND RESOURCE MANAGEMENT (2000) BUREAU INITIATED CLASSIFICATION SYSTEM Multiple-Use Classification Procedures § 2461.2 Classifications. Not less than 60 days after publication of the...

43 CFR 2461.2 - Classifications.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 43 Public Lands: Interior 2 2013-10-01 2013-10-01 false Classifications. 2461.2 Section 2461.2..., DEPARTMENT OF THE INTERIOR LAND RESOURCE MANAGEMENT (2000) BUREAU INITIATED CLASSIFICATION SYSTEM Multiple-Use Classification Procedures § 2461.2 Classifications. Not less than 60 days after publication of the...

28 CFR 524.73 - Classification procedures.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 28 Judicial Administration 2 2012-07-01 2012-07-01 false Classification procedures. 524.73 Section..., CLASSIFICATION, AND TRANSFER CLASSIFICATION OF INMATES Central Inmate Monitoring (CIM) System § 524.73 Classification procedures. (a) Initial assignment. Except as provided for in paragraphs (a) (1) through (4) of...

28 CFR 524.73 - Classification procedures.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 28 Judicial Administration 2 2013-07-01 2013-07-01 false Classification procedures. 524.73 Section..., CLASSIFICATION, AND TRANSFER CLASSIFICATION OF INMATES Central Inmate Monitoring (CIM) System § 524.73 Classification procedures. (a) Initial assignment. Except as provided for in paragraphs (a) (1) through (4) of...

28 CFR 524.73 - Classification procedures.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 28 Judicial Administration 2 2011-07-01 2011-07-01 false Classification procedures. 524.73 Section..., CLASSIFICATION, AND TRANSFER CLASSIFICATION OF INMATES Central Inmate Monitoring (CIM) System § 524.73 Classification procedures. (a) Initial assignment. Except as provided for in paragraphs (a) (1) through (4) of...

5 CFR 9901.223 - Appeal to DoD for review of classification decisions.

Code of Federal Regulations, 2011 CFR

2011-01-01

... RESOURCES MANAGEMENT AND LABOR RELATIONS SYSTEMS (DEPARTMENT OF DEFENSE-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF DEFENSE NATIONAL SECURITY PERSONNEL SYSTEM (NSPS) Classification Classification Process § 9901... an appeal. A management official may disallow an employee's representative when— (1) An individual's...

Global Similarity Predicts Dissociation of Classification and Recognition: Evidence Questioning the Implicit-Explicit Learning Distinction in Amnesia

ERIC Educational Resources Information Center

Jamieson, Randall K.; Holmes, Signy; Mewhort, D. J. K.

2010-01-01

Dissociation of classification and recognition in amnesia is widely taken to imply 2 functional systems: an implicit procedural-learning system that is spared in amnesia and an explicit episodic-learning system that is compromised. We argue that both tasks reflect the global similarity of probes to memory. In classification, subjects sort…

Assessment of fatty degeneration of the gluteal muscles in patients with THA using MRI: reliability and accuracy of the Goutallier and quartile classification systems.

PubMed

Engelken, Florian; Wassilew, Georgi I; Köhlitz, Torsten; Brockhaus, Sebastian; Hamm, Bernd; Perka, Carsten; Diederichs, und Gerd

2014-01-01

The purpose of this study was to quantify the performance of the Goutallier classification for assessing fatty degeneration of the gluteus muscles from magnetic resonance (MR) images and to compare its performance to a newly proposed system. Eighty-four hips with clinical signs of gluteal insufficiency and 50 hips from asymptomatic controls were analyzed using a standard classification system (Goutallier) and a new scoring system (Quartile). Interobserver reliability and intraobserver repeatability were determined, and accuracy was assessed by comparing readers' scores with quantitative estimates of the proportion of intramuscular fat based on MR signal intensities (gold standard). The existing Goutallier classification system and the new Quartile system performed equally well in assessing fatty degeneration of the gluteus muscles, both showing excellent levels of interrater and intrarater agreement. While the Goutallier classification system has the advantage of being widely known, the benefit of the Quartile system is that it is based on more clearly defined grades of fatty degeneration. Copyright © 2014 Elsevier Inc. All rights reserved.

From Classification to Epilepsy Ontology and Informatics

PubMed Central

Zhang, Guo-Qiang; Sahoo, Satya S; Lhatoo, Samden D

2012-01-01

Summary The 2010 International League Against Epilepsy (ILAE) classification and terminology commission report proposed a much needed departure from previous classifications to incorporate advances in molecular biology, neuroimaging, and genetics. It proposed an interim classification and defined two key requirements that need to be satisfied. The first is the ability to classify epilepsy in dimensions according to a variety of purposes including clinical research, patient care, and drug discovery. The second is the ability of the classification system to evolve with new discoveries. Multi-dimensionality and flexibility are crucial to the success of any future classification. In addition, a successful classification system must play a central role in the rapidly growing field of epilepsy informatics. An epilepsy ontology, based on classification, will allow information systems to facilitate data-intensive studies and provide a proven route to meeting the two foregoing key requirements. Epilepsy ontology will be a structured terminology system that accommodates proposed and evolving ILAE classifications, the NIH/NINDS Common Data Elements, the ICD systems and explicitly specifies all known relationships between epilepsy concepts in a proper framework. This will aid evidence based epilepsy diagnosis, investigation, treatment and research for a diverse community of clinicians and researchers. Benefits range from systematization of electronic patient records to multi-modal data repositories for research and training manuals for those involved in epilepsy care. Given the complexity, heterogeneity and pace of research advances in the epilepsy domain, such an ontology must be collaboratively developed by key stakeholders in the epilepsy community and experts in knowledge engineering and computer science. PMID:22765502

UBV Photometry of Selected Eclipsing Binaries in the Magellanic Clouds.

NASA Astrophysics Data System (ADS)

Davidge, Timothy John

1987-12-01

UBV photoelectric observations of five eclipsing binaries in the Magellanic Clouds are presented and discussed in detail. The systems studied are HV162O and HV1669 in the Small Magellanic Cloud and HV2241, HV2765, and HV5943 in the Large Magellanic Cloud. Classification spectra indicate that the components of these systems are of spectral type late O or early B. The systems are located in moderately crowded areas. Therefore, CCD observations were used to construct models of the star fields around the variables. These were used to correct the photoelectric measurements for contamination. Light curve solutions were found with the Wilson -Devinney program. A two dimensional search of parameter space involving the mass ratio and the surface potential of the secondary component was employed. This procedure was tested by numerical simulation and was found to predict the light curve elements, including the mass ratios, within their estimated uncertainties. It appears likely that none of the systems are in contact, a surprising result considering the high frequency of early type contact binaries in the solar neighborhood. The light curve solutions were then used to compute the absolute dimensions of the components. Only one system, HV2241, has a radial velocity curve, allowing its absolute dimensions to be well established. Less accurate absolute dimensions were calculated for the remaining systems using photometric information. The components were then placed on H-R diagrams and compared with theoretical models of stellar evolution. The positions of the components on these diagrams appear to support the existence of convective core overshooting. The evolutionary status of the systems was also discussed. The system with the most accurately determined absolute dimensions, HV2241, appears to have undergone, or is nearing the end of, Case A mass transfer. Two other systems, HV1620 and HV1669, may also be involved in mass transfer. Finally, the use of eclipsing binaries as distance indicators was investigated. The distance modulus of the LMC was computed in two ways. One approach used the absolute dimensions found with the radial velocity data while the other employed the method of photometric parallaxes. The latter technique was also used to calculate the distance modulus of the SMC.

MRI classification system (MRICS) for children with cerebral palsy: development, reliability, and recommendations.

PubMed

Himmelmann, Kate; Horber, Veronka; De La Cruz, Javier; Horridge, Karen; Mejaski-Bosnjak, Vlatka; Hollody, Katalin; Krägeloh-Mann, Ingeborg

2017-01-01

To develop and evaluate a classification system for magnetic resonance imaging (MRI) findings of children with cerebral palsy (CP) that can be used in CP registers. The classification system was based on pathogenic patterns occurring in different periods of brain development. The MRI classification system (MRICS) consists of five main groups: maldevelopments, predominant white matter injury, predominant grey matter injury, miscellaneous, and normal findings. A detailed manual for the descriptions of these patterns was developed, including test cases (www.scpenetwork.eu/en/my-scpe/rtm/neuroimaging/cp-neuroimaging/). A literature review was performed and MRICS was compared with other classification systems. An exercise was carried out to check applicability and interrater reliability. Professionals working with children with CP or in CP registers were invited to participate in the exercise and chose to classify either 18 MRIs or MRI reports of children with CP. Classification systems in the literature were compatible with MRICS and harmonization possible. Interrater reliability was found to be good overall (k=0.69; 0.54-0.82) among the 41 participants and very good (k=0.81; 0.74-0.92) using the classification based on imaging reports. Surveillance of Cerebral Palsy in Europe (SCPE) proposes the MRICS as a reliable tool. Together with its manual it is simple to apply for CP registers. © 2016 Mac Keith Press.

Balancing Scientific Publication and National Security Concerns: Issues for Congress

DTIC Science & Technology

2003-01-10

because of its potential relevance to biological weapons of mass destruction. Whether the current method of only using classification to limit the...terrorist groups in developing weapons of mass destruction. In 2000, researchers at the Co-operative Research Centre for the Biological Control of Pest...development of chemical, biological , or nuclear weapons is not made accessible to terrorists or countries of proliferation concern. The resolution

VizieR Online Data Catalog: Photometric study of fourteen low-mass binaries (Korda+, 2017)

NASA Astrophysics Data System (ADS)

Korda, D.; Zasche, P.; Wolf, M.; Kucakova, H.; Honkova, K.; Vrastil, J.

2018-05-01

All new photometric observations of 14 binaries were carried out in the Ondrejov Observatory in the Czech Republic with the 0.65 m reflecting-type telescope and the G2-3200 CCD camera. Observations were collected from 2015 February to 2016 November in the I, R, and V filters (Bessell 1990PASP..102.1181B). Some of the older observations obtained only in the R filter were used for refining the individual orbital periods. The stars were primarily chosen from the catalog of Hoffman et al. (2008, J/AJ/136/1067). For the selection of suitable stars, we used several criteria. Each binary's classification as a low-mass binary was performed using the photometric indices J-H and H-K, which are known from the 2MASS survey (Cutri et al. 2003, Cat. II/246; J-H>0.25 and H-K>0.07 Pecaut & Mamajek (2013, J/ApJS/208/9; www.pas.rochester.edu/~emamajek/EEMdwarfUBVIJHKcolorsTeff.txt)). Furthermore, we selected binary systems that have short orbital periods (P<1.5 days) and we chose the declination to be higher than +30°. The last criterion was that these systems cannot have been analyzed in detail before. We chose 11 systems in Hoffman's catalog (2008, J/AJ/136/1067), 2 more were found in the measured field (one of them is on the edge of criteria), and 1 star was added later. (6 data files).

43 CFR 2450.4 - Protests: Initial classification decision.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 43 Public Lands: Interior 2 2011-10-01 2011-10-01 false Protests: Initial classification decision... CLASSIFICATION SYSTEM Petition-Application Procedures § 2450.4 Protests: Initial classification decision. (a) For a period of 30 days after the proposed classification decision has been served upon the parties...

49 CFR 173.53 - Provisions for using old classifications of explosives.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 49 Transportation 2 2010-10-01 2010-10-01 false Provisions for using old classifications of... SHIPPERS-GENERAL REQUIREMENTS FOR SHIPMENTS AND PACKAGINGS Definitions, Classification and Packaging for Class 1 § 173.53 Provisions for using old classifications of explosives. Where the classification system...

Case base classification on digital mammograms: improving the performance of case base classifier

NASA Astrophysics Data System (ADS)

Raman, Valliappan; Then, H. H.; Sumari, Putra; Venkatesa Mohan, N.

2011-10-01

Breast cancer continues to be a significant public health problem in the world. Early detection is the key for improving breast cancer prognosis. The aim of the research presented here is in twofold. First stage of research involves machine learning techniques, which segments and extracts features from the mass of digital mammograms. Second level is on problem solving approach which includes classification of mass by performance based case base classifier. In this paper we build a case-based Classifier in order to diagnose mammographic images. We explain different methods and behaviors that have been added to the classifier to improve the performance of the classifier. Currently the initial Performance base Classifier with Bagging is proposed in the paper and it's been implemented and it shows an improvement in specificity and sensitivity.

Star clusters in the Magellanic Clouds - I. Parametrization and classification of 1072 clusters in the LMC

NASA Astrophysics Data System (ADS)

Nayak, P. K.; Subramaniam, A.; Choudhury, S.; Indu, G.; Sagar, Ram

2016-12-01

We have introduced a semi-automated quantitative method to estimate the age and reddening of 1072 star clusters in the Large Magellanic Cloud (LMC) using the Optical Gravitational Lensing Experiment III survey data. This study brings out 308 newly parametrized clusters. In a first of its kind, the LMC clusters are classified into groups based on richness/mass as very poor, poor, moderate and rich clusters, similar to the classification scheme of open clusters in the Galaxy. A major cluster formation episode is found to happen at 125 ± 25 Myr in the inner LMC. The bar region of the LMC appears prominently in the age range 60-250 Myr and is found to have a relatively higher concentration of poor and moderate clusters. The eastern and the western ends of the bar are found to form clusters initially, which later propagates to the central part. We demonstrate that there is a significant difference in the distribution of clusters as a function of mass, using a movie based on the propagation (in space and time) of cluster formation in various groups. The importance of including the low-mass clusters in the cluster formation history is demonstrated. The catalogue with parameters, classification, and cleaned and isochrone fitted colour-magnitude diagrams of 1072 clusters, which are available as online material, can be further used to understand the hierarchical formation of clusters in selected regions of the LMC.

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

PubMed

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

2011-11-01

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

Speech Enhancement based on the Dominant Classification Between Speech and Noise Using Feature Data in Spectrogram of Observation Signal

NASA Astrophysics Data System (ADS)

Nomura, Yukihiro; Lu, Jianming; Sekiya, Hiroo; Yahagi, Takashi

This paper presents a speech enhancement using the classification between the dominants of speech and noise. In our system, a new classification scheme between the dominants of speech and noise is proposed. The proposed classifications use the standard deviation of the spectrum of observation signal in each band. We introduce two oversubtraction factors for the dominants of speech and noise, respectively. And spectral subtraction is carried out after the classification. The proposed method is tested on several noise types from the Noisex-92 database. From the investigation of segmental SNR, Itakura-Saito distance measure, inspection of spectrograms and listening tests, the proposed system is shown to be effective to reduce background noise. Moreover, the enhanced speech using our system generates less musical noise and distortion than that of conventional systems.

Model-based Clustering of High-Dimensional Data in Astrophysics

NASA Astrophysics Data System (ADS)

Bouveyron, C.

2016-05-01

The nature of data in Astrophysics has changed, as in other scientific fields, in the past decades due to the increase of the measurement capabilities. As a consequence, data are nowadays frequently of high dimensionality and available in mass or stream. Model-based techniques for clustering are popular tools which are renowned for their probabilistic foundations and their flexibility. However, classical model-based techniques show a disappointing behavior in high-dimensional spaces which is mainly due to their dramatical over-parametrization. The recent developments in model-based classification overcome these drawbacks and allow to efficiently classify high-dimensional data, even in the "small n / large p" situation. This work presents a comprehensive review of these recent approaches, including regularization-based techniques, parsimonious modeling, subspace classification methods and classification methods based on variable selection. The use of these model-based methods is also illustrated on real-world classification problems in Astrophysics using R packages.

A Functional Classification of Occupations.

ERIC Educational Resources Information Center

McKinlay, Donald Bruce

The need for more and better manpower information is hampered by the lack of adequate occupational data classification systems. The diversity of interests in occupations probably accounts for the absence of consensus regarding either the general outlines or the specific details of a standardized occupational classification system which would…

Dewey Decimal Classification: A Quagmire.

ERIC Educational Resources Information Center

Gamaluddin, Ahmad Fouad

1980-01-01

A survey of 660 Pennsylvania school librarians indicates that, though there is limited professional interest in the Library of Congress Classification system, Dewey Decimal Classification (DDC) appears to be firmly entrenched. This article also discusses the relative merits of DDC, the need for a uniform system, librarianship preparation, and…

5 CFR 9901.223 - Appeal to DoD for review of classification decisions.

Code of Federal Regulations, 2010 CFR

2010-01-01

... RESOURCES MANAGEMENT AND LABOR RELATIONS SYSTEMS (DEPARTMENT OF DEFENSE-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF DEFENSE NATIONAL SECURITY PERSONNEL SYSTEM (NSPS) Classification Classification Process § 9901... process. (1) Employee appeals to DoD must be submitted through the employee's servicing Human Resources...

Evaluation of Urinary Tract Dilation Classification System for Grading Postnatal Hydronephrosis.

PubMed

Hodhod, Amr; Capolicchio, John-Paul; Jednak, Roman; El-Sherif, Eid; El-Doray, Abd El-Alim; El-Sherbiny, Mohamed

2016-03-01

We assessed the reliability and validity of the Urinary Tract Dilation classification system as a new grading system for postnatal hydronephrosis. We retrospectively reviewed charts of patients who presented with hydronephrosis from 2008 to 2013. We included patients diagnosed prenatally and those with hydronephrosis discovered incidentally during the first year of life. We excluded cases involving urinary tract infection, neurogenic bladder and chromosomal anomalies, those associated with extraurinary congenital malformations and those with followup of less than 24 months without resolution. Hydronephrosis was graded postnatally using the Society for Fetal Urology system, and then the management protocol was chosen. All units were regraded using the Urinary Tract Dilation classification system and compared to the Society for Fetal Urology system to assess reliability. Univariate and multivariate analyses were performed to assess the validity of the Urinary Tract Dilation classification system in predicting hydronephrosis resolution and surgical intervention. A total of 490 patients (730 renal units) were eligible to participate. The Urinary Tract Dilation classification system was reliable in the assessment of hydronephrosis (parallel forms 0.92). Hydronephrosis resolved in 357 units (49%), and 86 units (12%) were managed by surgical intervention. The remainder of renal units demonstrated stable or improved hydronephrosis. Multivariate analysis revealed that the likelihood of surgical intervention was predicted independently by Urinary Tract Dilation classification system risk group, while Society for Fetal Urology grades were predictive of likelihood of resolution. The Urinary Tract Dilation classification system is reliable for evaluation of postnatal hydronephrosis and is valid in predicting surgical intervention. Copyright © 2016 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

Profile of patients with chronic obstructive pulmonary disease classified as physically active and inactive according to different thresholds of physical activity in daily life

PubMed Central

Furlanetto, Karina C.; Pinto, Isabela F. S.; Sant’Anna, Thais; Hernandes, Nidia A.; Pitta, Fabio

2016-01-01

ABSTRACT Objective To compare the profiles of patients with chronic obstructive pulmonary disease (COPD) considered physically active or inactive according to different classifications of the level of physical activity in daily life (PADL). Method Pulmonary function, dyspnea, functional status, body composition, exercise capacity, respiratory and peripheral muscle strength, and presence of comorbidities were assessed in 104 patients with COPD. The level of PADL was quantified with a SenseWear Armband activity monitor. Three classifications were used to classify the patients as physically active or inactive: 30 minutes of activity/day with intensity >3.2 METs, if age ≥65 years, and >4 METs, if age <65 years; 30 minutes of activity/day with intensity >3.0 METs, regardless of patient age; and 80 minutes of activity/day with intensity >3.0 METs, regardless of patient age. Results In all classifications, when compared with the inactive group, the physically active group had better values of anthropometric variables (higher fat-free mass, lower body weight, body mass index and fat percentage), exercise capacity (6-minute walking distance), lung function (forced vital capacity) and functional status (personal care domain of the London Chest Activity of Daily Living). Furthermore, patients classified as physically active in two classifications also had better peripheral and expiratory muscle strength, airflow obstruction, functional status, and quality of life, as well as lower prevalence of heart disease and mortality risk. Conclusion In all classification methods, physically active patients with COPD have better exercise capacity, lung function, body composition, and functional status compared to physically inactive patients. PMID:27683835

Topographic, bioclimatic, and vegetation characteristics of three ecoregion classification systems in North America: Comparisons along continent-wide transects

USGS Publications Warehouse

Thompson, R.S.; Shafer, S.L.; Anderson, K.H.; Strickland, L.E.; Pelltier, R.T.; Bartlein, P.J.; Kerwin, M.W.

2005-01-01

Ecoregion classification systems are increasingly used for policy and management decisions, particularly among conservation and natural resource managers. A number of ecoregion classification systems are currently available, with each system defining ecoregions using different classification methods and different types of data. As a result, each classification system describes a unique set of ecoregions. To help potential users choose the most appropriate ecoregion system for their particular application, we used three latitudinal transects across North America to compare the boundaries and environmental characteristics of three ecoregion classification systems [Ku??chler, World Wildlife Fund (WWF), and Bailey]. A variety of variables were used to evaluate the three systems, including woody plant species richness, normalized difference in vegetation index (NDVI), and bioclimatic variables (e.g., mean temperature of the coldest month) along each transect. Our results are dominated by geographic patterns in temperature, which are generally aligned north-south, and in moisture, which are generally aligned east-west. In the west, the dramatic changes in physiography, climate, and vegetation impose stronger controls on ecoregion boundaries than in the east. The Ku??chler system has the greatest number of ecoregions on all three transects, but does not necessarily have the highest degree of internal consistency within its ecoregions with regard to the bioclimatic and species richness data. In general, the WWF system appears to track climatic and floristic variables the best of the three systems, but not in all regions on all transects. ?? 2005 Springer Science+Business Media, Inc.

Medicare Program; Inpatient Rehabilitation Facility Prospective Payment System for Federal Fiscal Year 2018. Final rule.

PubMed

2017-08-03

This final rule updates the prospective payment rates for inpatient rehabilitation facilities (IRFs) for federal fiscal year (FY) 2018 as required by the statute. As required by section 1886(j)(5) of the Social Security Act (the Act), this rule includes the classification and weighting factors for the IRF prospective payment system's (IRF PPS) case-mix groups and a description of the methodologies and data used in computing the prospective payment rates for FY 2018. This final rule also revises the International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) diagnosis codes that are used to determine presumptive compliance under the "60 percent rule," removes the 25 percent payment penalty for inpatient rehabilitation facility patient assessment instrument (IRF-PAI) late transmissions, removes the voluntary swallowing status item (Item 27) from the IRF-PAI, summarizes comments regarding the criteria used to classify facilities for payment under the IRF PPS, provides for a subregulatory process for certain annual updates to the presumptive methodology diagnosis code lists, adopts the use of height/weight items on the IRF-PAI to determine patient body mass index (BMI) greater than 50 for cases of single-joint replacement under the presumptive methodology, and revises and updates measures and reporting requirements under the IRF quality reporting program (QRP).

Computer-aided detection of bladder mass within non-contrast-enhanced region of CT Urography (CTU)

NASA Astrophysics Data System (ADS)

Cha, Kenny H.; Hadjiiski, Lubomir M.; Chan, Heang-Ping; Caoili, Elaine M.; Cohan, Richard H.; Weizer, Alon; Zhou, Chuan

2016-03-01

We are developing a computer-aided detection system for bladder cancer in CT urography (CTU). We have previously developed methods for detection of bladder masses within the contrast-enhanced region of the bladder. In this study, we investigated methods for detection of bladder masses within the non-contrast enhanced region. The bladder was first segmented using a newly developed deep-learning convolutional neural network in combination with level sets. The non-contrast-enhanced region was separated from the contrast-enhanced region with a maximum-intensityprojection- based method. The non-contrast region was smoothed and a gray level threshold was employed to segment the bladder wall and potential masses. The bladder wall was transformed into a straightened thickness profile, which was analyzed to identify lesion candidates as a prescreening step. The lesion candidates were segmented using our autoinitialized cascaded level set (AI-CALS) segmentation method, and 27 morphological features were extracted for each candidate. Stepwise feature selection with simplex optimization and leave-one-case-out resampling were used for training and validation of a false positive (FP) classifier. In each leave-one-case-out cycle, features were selected from the training cases and a linear discriminant analysis (LDA) classifier was designed to merge the selected features into a single score for classification of the left-out test case. A data set of 33 cases with 42 biopsy-proven lesions in the noncontrast enhanced region was collected. During prescreening, the system obtained 83.3% sensitivity at an average of 2.4 FPs/case. After feature extraction and FP reduction by LDA, the system achieved 81.0% sensitivity at 2.0 FPs/case, and 73.8% sensitivity at 1.5 FPs/case.

Accurate crop classification using hierarchical genetic fuzzy rule-based systems

NASA Astrophysics Data System (ADS)

Topaloglou, Charalampos A.; Mylonas, Stelios K.; Stavrakoudis, Dimitris G.; Mastorocostas, Paris A.; Theocharis, John B.

2014-10-01

This paper investigates the effectiveness of an advanced classification system for accurate crop classification using very high resolution (VHR) satellite imagery. Specifically, a recently proposed genetic fuzzy rule-based classification system (GFRBCS) is employed, namely, the Hierarchical Rule-based Linguistic Classifier (HiRLiC). HiRLiC's model comprises a small set of simple IF-THEN fuzzy rules, easily interpretable by humans. One of its most important attributes is that its learning algorithm requires minimum user interaction, since the most important learning parameters affecting the classification accuracy are determined by the learning algorithm automatically. HiRLiC is applied in a challenging crop classification task, using a SPOT5 satellite image over an intensively cultivated area in a lake-wetland ecosystem in northern Greece. A rich set of higher-order spectral and textural features is derived from the initial bands of the (pan-sharpened) image, resulting in an input space comprising 119 features. The experimental analysis proves that HiRLiC compares favorably to other interpretable classifiers of the literature, both in terms of structural complexity and classification accuracy. Its testing accuracy was very close to that obtained by complex state-of-the-art classification systems, such as the support vector machines (SVM) and random forest (RF) classifiers. Nevertheless, visual inspection of the derived classification maps shows that HiRLiC is characterized by higher generalization properties, providing more homogeneous classifications that the competitors. Moreover, the runtime requirements for producing the thematic map was orders of magnitude lower than the respective for the competitors.

43 CFR 2462.1 - Publication of notice of, and public hearings on, proposed classification.

Code of Federal Regulations, 2011 CFR

2011-10-01

... hearings on, proposed classification. 2462.1 Section 2462.1 Public Lands: Interior Regulations Relating to... (2000) BUREAU INITIATED CLASSIFICATION SYSTEM Disposal Classification Procedure: Over 2,560 Acres § 2462.1 Publication of notice of, and public hearings on, proposed classification. The authorized officer...

43 CFR 2462.2 - Publication of notice of classification.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 43 Public Lands: Interior 2 2011-10-01 2011-10-01 false Publication of notice of classification... CLASSIFICATION SYSTEM Disposal Classification Procedure: Over 2,560 Acres § 2462.2 Publication of notice of classification. After having considered the comments received as the result of publication, the authorized...

28 CFR 524.76 - Appeals of CIM classification.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 28 Judicial Administration 2 2010-07-01 2010-07-01 false Appeals of CIM classification. 524.76..., CLASSIFICATION, AND TRANSFER CLASSIFICATION OF INMATES Central Inmate Monitoring (CIM) System § 524.76 Appeals of CIM classification. An inmate may at any time appeal (through the Administrative Remedy Program) the...

77 FR 37879 - Cooperative Patent Classification External User Day

Federal Register 2010, 2011, 2012, 2013, 2014

2012-06-25

... Classification External User Day AGENCY: United States Patent and Trademark Office, Commerce. ACTION: Notice... Classification (CPC) External User Day event at its Alexandria Campus. CPC is a partnership between the USPTO and... classification system that will incorporate the best classification practices of the two Offices. This CPC event...

32 CFR 1648.6 - Registrants transferred for classification.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 32 National Defense 6 2014-07-01 2014-07-01 false Registrants transferred for classification. 1648... SYSTEM CLASSIFICATION BY LOCAL BOARD § 1648.6 Registrants transferred for classification. (a) Before a..., be transferred for classification to a local board nearer to his current address than is the local...

32 CFR 1648.6 - Registrants transferred for classification.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 32 National Defense 6 2013-07-01 2013-07-01 false Registrants transferred for classification. 1648... SYSTEM CLASSIFICATION BY LOCAL BOARD § 1648.6 Registrants transferred for classification. (a) Before a..., be transferred for classification to a local board nearer to his current address than is the local...

32 CFR 1648.6 - Registrants transferred for classification.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 32 National Defense 6 2010-07-01 2010-07-01 false Registrants transferred for classification. 1648... SYSTEM CLASSIFICATION BY LOCAL BOARD § 1648.6 Registrants transferred for classification. (a) Before a..., be transferred for classification to a local board nearer to his current address than is the local...

32 CFR 1648.6 - Registrants transferred for classification.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 32 National Defense 6 2011-07-01 2011-07-01 false Registrants transferred for classification. 1648... SYSTEM CLASSIFICATION BY LOCAL BOARD § 1648.6 Registrants transferred for classification. (a) Before a..., be transferred for classification to a local board nearer to his current address than is the local...

32 CFR 1648.6 - Registrants transferred for classification.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 32 National Defense 6 2012-07-01 2012-07-01 false Registrants transferred for classification. 1648... SYSTEM CLASSIFICATION BY LOCAL BOARD § 1648.6 Registrants transferred for classification. (a) Before a..., be transferred for classification to a local board nearer to his current address than is the local...

Ototoxicity (cochleotoxicity) classifications: A review.

PubMed

Crundwell, Gemma; Gomersall, Phil; Baguley, David M

2016-01-01

Drug-mediated ototoxicity, specifically cochleotoxicity, is a concern for patients receiving medications for the treatment of serious illness. A number of classification schemes exist, most of which are based on pure-tone audiometry, in order to assist non-audiological/non-otological specialists in the identification and monitoring of iatrogenic hearing loss. This review identifies the primary classification systems used in cochleototoxicity monitoring. By bringing together classifications published in discipline-specific literature, the paper aims to increase awareness of their relative strengths and limitations in the assessment and monitoring of ototoxic hearing loss and to indicate how future classification systems may improve upon the status-quo. Literature review. PubMed identified 4878 articles containing the search term ototox*. A systematic search identified 13 key classification systems. Cochleotoxicity classification systems can be divided into those which focus on hearing change from a baseline audiogram and those that focus on the functional impact of the hearing loss. Common weaknesses of these grading scales included a lack of sensitivity to small adverse changes in hearing thresholds, a lack of high-frequency audiometry (>8 kHz), and lack of indication of which changes are likely to be clinically significant for communication and quality of life.

Global similarity predicts dissociation of classification and recognition: evidence questioning the implicit-explicit learning distinction in amnesia.

PubMed

Jamieson, Randall K; Holmes, Signy; Mewhort, D J K

2010-11-01

Dissociation of classification and recognition in amnesia is widely taken to imply 2 functional systems: an implicit procedural-learning system that is spared in amnesia and an explicit episodic-learning system that is compromised. We argue that both tasks reflect the global similarity of probes to memory. In classification, subjects sort unstudied grammatical exemplars from lures, whereas in recognition, they sort studied grammatical exemplars from lures. Hence, global similarity is necessarily greater in recognition than in classification. Moreover, a grammatical exemplar's similarity to studied exemplars is a nonlinear function of the integrity of the data in memory. Assuming that data integrity is better for control subjects than for subjects with amnesia, the nonlinear relation combined with the advantage for recognition over classification predicts the dissociation of recognition and classification. To illustrate the dissociation of recognition and classification in healthy undergraduates, we manipulated study time to vary the integrity of the data in memory and brought the dissociation under experimental control. We argue that the dissociation reflects a general cost in memory rather than a selective impairment of separate procedural and episodic systems. (c) 2010 APA, all rights reserved

Classification of natural ponds and lakes in the glaciated prairie region

USGS Publications Warehouse

Stewart, Robert E.; Kantrud, Harold A.

1971-01-01

The wetland classification system for the United States adopted by the Bureau of Sport Fisheries and Wildlife in 1953 is described by Martin et al (1953) and by Shaw and Fredine (1956).  That classification has been followed by many biologists in recent years and is especially useful in categorizing in a general manner the wetlands throughout the country over a span of years.  It has become apparent, however, that for research and intensive management a dynamic classification system that more precisely reflects seasonal, regional, and local variations in the environment is needed.  To establish a detailed wetland classification system for all of  North America will require intensive ecological investigation of wetlands in each of the major biogeographical regions.

Practice patterns when treating patients with low back pain: a survey of physical therapists.

PubMed

Davies, Claire; Nitz, Arthur J; Mattacola, Carl G; Kitzman, Patrick; Howell, Dana; Viele, Kert; Baxter, David; Brockopp, Dorothy

2014-08-01

Low back pain (LBP), is a common musculoskeletal problem, affecting 75-85% of adults in their lifetime. Direct costs of LBP in the USA were estimated over 85 billion dollars in 2005 resulting in a significant economic burden for the healthcare system. LBP classification systems and outcome measures are available to guide physical therapy assessments and intervention. However, little is known about which, if any, physical therapists use in clinical practice. The purpose of this study was to identify the use of and barriers to LBP classification systems and outcome measures among physical therapists in one state. A mixed methods study using a cross-sectional cohort design with descriptive qualitative methods was performed. A survey collected both quantitative and qualitative data relevant to classification systems and outcome measures used by physical therapists working with patients with LBP. Physical therapists responded using classification systems designed to direct treatment predominantly. The McKenzie method was the most frequent approach to classify LBP. Barriers to use of classification systems and outcome measures were lack of knowledge, too limiting and time. Classification systems are being used for decision-making in physical therapy practice for patients with LBP. Lack of knowledge and training seems to be the main barrier to the use of classification systems in practice. The Oswestry Disability Index and Numerical Pain Scale were the most commonly used outcome measures. The main barrier to their use was lack of time. Continuing education and reading the literature were identified as important tools to teach evidence-based practice to physical therapists in practice.

Multiresolution Local Binary Pattern texture analysis for false positive reduction in computerized detection of breast masses on mammograms

NASA Astrophysics Data System (ADS)

Choi, Jae Young; Kim, Dae Hoe; Choi, Seon Hyeong; Ro, Yong Man

2012-03-01

We investigated the feasibility of using multiresolution Local Binary Pattern (LBP) texture analysis to reduce falsepositive (FP) detection in a computerized mass detection framework. A new and novel approach for extracting LBP features is devised to differentiate masses and normal breast tissue on mammograms. In particular, to characterize the LBP texture patterns of the boundaries of masses, as well as to preserve the spatial structure pattern of the masses, two individual LBP texture patterns are then extracted from the core region and the ribbon region of pixels of the respective ROI regions, respectively. These two texture patterns are combined to produce the so-called multiresolution LBP feature of a given ROI. The proposed LBP texture analysis of the information in mass core region and its margin has clearly proven to be significant and is not sensitive to the precise location of the boundaries of masses. In this study, 89 mammograms were collected from the public MAIS database (DB). To perform a more realistic assessment of FP reduction process, the LBP texture analysis was applied directly to a total of 1,693 regions of interest (ROIs) automatically segmented by computer algorithm. Support Vector Machine (SVM) was applied for the classification of mass ROIs from ROIs containing normal tissue. Receiver Operating Characteristic (ROC) analysis was conducted to evaluate the classification accuracy and its improvement using multiresolution LBP features. With multiresolution LBP features, the classifier achieved an average area under the ROC curve, , z A of 0.956 during testing. In addition, the proposed LBP features outperform other state-of-the-arts features designed for false positive reduction.

Long-Wavelength Elastic Wave Propagation Across Naturally Fractured Rock Masses

NASA Astrophysics Data System (ADS)

Mohd-Nordin, Mohd Mustaqim; Song, Ki-Il; Cho, Gye-Chun; Mohamed, Zainab

2014-03-01

Geophysical site investigation techniques based on elastic waves have been widely used to characterize rock masses. However, characterizing jointed rock masses by using such techniques remains challenging because of a lack of knowledge about elastic wave propagation in multi-jointed rock masses. In this paper, the roughness of naturally fractured rock joint surfaces is estimated by using a three-dimensional (3D) image-processing technique. The classification of the joint roughness coefficient (JRC) is enhanced by introducing the scan line technique. The peak-to-valley height is selected as a key indicator for JRC classification. Long-wavelength P-wave and torsional S-wave propagation across rock masses containing naturally fractured joints are simulated through the quasi-static resonant column (QSRC) test. In general, as the JRC increases, the S-wave velocity increases within the range of stress levels considered in this paper, whereas the P-wave velocity and the damping ratio of the shear wave decrease. In particular, the two-dimensional joint specimen underestimates the S-wave velocity while overestimating the P-wave velocity. This suggests that 3D joint surfaces should be implicated to obtain the reliable elastic wave velocity in jointed rock masses. The contact characteristic and degree of roughness and waviness of the joint surface are identified as a factor influencing P-wave and S-wave propagation in multi-jointed rock masses. The results indicate a need for a better understanding of the sensitivity of contact area alterations to the elastic wave velocity induced by changes in normal stress. This paper's framework can be a reference for future research on elastic wave propagation in naturally multi-jointed rock masses.

Review, evaluation, and discussion of the challenges of missing value imputation for mass spectrometry-based label-free global proteomics

DOE PAGES

Webb-Robertson, Bobbie-Jo M.; Wiberg, Holli K.; Matzke, Melissa M.; ...

2015-04-09

In this review, we apply selected imputation strategies to label-free liquid chromatography–mass spectrometry (LC–MS) proteomics datasets to evaluate the accuracy with respect to metrics of variance and classification. We evaluate several commonly used imputation approaches for individual merits and discuss the caveats of each approach with respect to the example LC–MS proteomics data. In general, local similarity-based approaches, such as the regularized expectation maximization and least-squares adaptive algorithms, yield the best overall performances with respect to metrics of accuracy and robustness. However, no single algorithm consistently outperforms the remaining approaches, and in some cases, performing classification without imputation sometimes yieldedmore » the most accurate classification. Thus, because of the complex mechanisms of missing data in proteomics, which also vary from peptide to protein, no individual method is a single solution for imputation. In summary, on the basis of the observations in this review, the goal for imputation in the field of computational proteomics should be to develop new approaches that work generically for this data type and new strategies to guide users in the selection of the best imputation for their dataset and analysis objectives.« less

Near-Earth Solar Wind Flows and Related Geomagnetic Activity During more than Four Solar Cycles (1963-2011)

NASA Technical Reports Server (NTRS)

Richardson, Ian G.; Cane, Hilary V.

2012-01-01

In past studies, we classified the near-Earth solar wind into three basic flow types based on inspection of solar wind plasma and magnetic field parameters in the OMNI database and additional data (e.g., geomagnetic indices, energetic particle, and cosmic ray observations). These flow types are: (1) High-speed streams associated with coronal holes at the Sun, (2) Slow, interstream solar wind, and (3) Transient flows originating with coronal mass ejections at the Sun, including interplanetary coronal mass ejections and the associated upstream shocks and post-shock regions. The solar wind classification in these previous studies commenced with observations in 1972. In the present study, as well as updating this classification to the end of 2011, we have extended the classification back to 1963, the beginning of near-Earth solar wind observations, thereby encompassing the complete solar cycles 20 to 23 and the ascending phase of cycle 24. We discuss the cycle-to-cycle variations in near-Earth solar wind structures and l1e related geomagnetic activity over more than four solar cycles, updating some of the results of our earlier studies.

The software application and classification algorithms for welds radiograms analysis

NASA Astrophysics Data System (ADS)

Sikora, R.; Chady, T.; Baniukiewicz, P.; Grzywacz, B.; Lopato, P.; Misztal, L.; Napierała, L.; Piekarczyk, B.; Pietrusewicz, T.; Psuj, G.

2013-01-01

The paper presents a software implementation of an Intelligent System for Radiogram Analysis (ISAR). The system has to support radiologists in welds quality inspection. The image processing part of software with a graphical user interface and a welds classification part are described with selected classification results. Classification was based on a few algorithms: an artificial neural network, a k-means clustering, a simplified k-means and a rough sets theory.

Comparing drug classification systems.

PubMed

Mahoney, Anne; Evans, Jonathan

2008-11-06

An essential quality of drug classification systems is the ability to assign medications to a structured hierarchy for categories such as mechanism of action, physiological effects, and therapeutic indications. No single classification system can meet all of these needs; however, there should be consistency among those that group by the same underlying principals. We discovered discrepancies in how drugs with multiple therapeutic indications are classified among four widely used schemas.

A classification of large amplitude oscillations of a spring-pendulum system

NASA Technical Reports Server (NTRS)

Broucke, R.

1977-01-01

We present a detailed classification of large amplitude oscillations of a non-integrable autonomous system with two degrees of freedom: the spring pendulum system. The classification is made with the method of invariant curves. The results show the importance of three types of motion: periodic, quasi-periodic and semi-ergodic. The numerical results are given for nine different values of the energy constant.

48 CFR 204.7107 - Contract accounting classification reference number (ACRN) and agency accounting identifier (AAI).

Code of Federal Regulations, 2011 CFR

2011-10-01

... 48 Federal Acquisition Regulations System 3 2011-10-01 2011-10-01 false Contract accounting classification reference number (ACRN) and agency accounting identifier (AAI). 204.7107 Section 204.7107 Federal... ADMINISTRATIVE MATTERS Uniform Contract Line Item Numbering System 204.7107 Contract accounting classification...