Fabric wrinkle characterization and classification using modified wavelet coefficients and optimized support-vector-machine classifier

USDA-ARS?s Scientific Manuscript database

This paper presents a novel wrinkle evaluation method that uses modified wavelet coefficients and an optimized support-vector-machine (SVM) classification scheme to characterize and classify wrinkle appearance of fabric. Fabric images were decomposed with the wavelet transform (WT), and five parame...

The use of the modified Cholesky decomposition in divergence and classification calculations

NASA Technical Reports Server (NTRS)

Van Rooy, D. L.; Lynn, M. S.; Snyder, C. H.

1973-01-01

This report analyzes the use of the modified Cholesky decomposition technique as applied to the feature selection and classification algorithms used in the analysis of remote sensing data (e.g., as in LARSYS). This technique is approximately 30% faster in classification and a factor of 2-3 faster in divergence, as compared with LARSYS. Also numerical stability and accuracy are slightly improved. Other methods necessary to deal with numerical stability problems are briefly discussed.

The Value of Ensari's Proposal in Evaluating the Mucosal Pathology of Childhood Celiac Disease: Old Classification versus New Version.

PubMed

Güreşci, Servet; Hızlı, Samil; Simşek, Gülçin Güler

2012-09-01

Small intestinal biopsy remains the gold standard in diagnosing celiac disease (CD); however, the wide spectrum of histopathological states and differential diagnosis of CD is still a diagnostic problem for pathologists. Recently, Ensari reviewed the literature and proposed an update of the histopathological diagnosis and classification for CD. In this study, the histopathological materials of 54 children in whom CD was diagnosed at our hospital were reviewed to compare the previous Marsh and Modified Marsh-Oberhuber classifications with this new proposal. In this study, we show that the Ensari classification is as accurate as the Marsh and Modified Marsh classifications in describing the consecutive states of mucosal damage seen in CD. Ensari's classification is simple, practical and facilitative in diagnosing and subtyping of mucosal pathology of CD.

76 FR 69119 - Commonwealth of the Northern Mariana Islands Transitional Worker Classification: Correction

Federal Register 2010, 2011, 2012, 2013, 2014

2011-11-08

...] RIN 1615-AB76 Commonwealth of the Northern Mariana Islands Transitional Worker Classification... Transitional Worker Classification. In that rule, we had sought to modify the title of a paragraph, but... the final rule Commonwealth of the Northern Mariana Islands Transitional Worker Classification...

Classification of Instructional Programs - 2000. Public Comment Draft. [Third Revision].

ERIC Educational Resources Information Center

Morgan, Robert L.; Hunt, E. Stephen

This third revision of the Classification of Instructional Programs (CIP) updates and modifies education program classifications, descriptions, and titles at the secondary, postsecondary, and adult education levels. This edition has also been adopted by Canada as its standard for major field of study classification. The volume includes the…

The Value of Ensari’s Proposal in Evaluating the Mucosal Pathology of Childhood Celiac Disease: Old Classification versus New Version

PubMed Central

Güreşci, Servet; Hızlı, Şamil; Şimşek, Gülçin Güler

2012-01-01

Objective: Small intestinal biopsy remains the gold standard in diagnosing celiac disease (CD); however, the wide spectrum of histopathological states and differential diagnosis of CD is still a diagnostic problem for pathologists. Recently, Ensari reviewed the literature and proposed an update of the histopathological diagnosis and classification for CD. Materials and Methods: In this study, the histopathological materials of 54 children in whom CD was diagnosed at our hospital were reviewed to compare the previous Marsh and Modified Marsh-Oberhuber classifications with this new proposal. Results: In this study, we show that the Ensari classification is as accurate as the Marsh and Modified Marsh classifications in describing the consecutive states of mucosal damage seen in CD. Conclusions: Ensari’s classification is simple, practical and facilitative in diagnosing and subtyping of mucosal pathology of CD. PMID:25207015

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 Retrospective Analysis of Pressure Ulcer Incidence and Modified Braden Scale Score Risk Classifications.

PubMed

Chen, Hong-Lin; Cao, Ying-Juan; Wang, Jing; Huai, Bao-Sha

2015-09-01

The Braden Scale is the most widely used pressure ulcer risk assessment in the world, but the currently used 5 risk classification groups do not accurately discriminate among their risk categories. To optimize risk classification based on Braden Scale scores, a retrospective analysis of all consecutively admitted patients in an acute care facility who were at risk for pressure ulcer development was performed between January 2013 and December 2013. Predicted pressure ulcer incidence first was calculated by logistic regression model based on original Braden score. Risk classification then was modified based on the predicted pressure ulcer incidence and compared between different risk categories in the modified (3-group) classification and the traditional (5-group) classification using chi-square test. Two thousand, six hundred, twenty-five (2,625) patients (mean age 59.8 ± 16.5, range 1 month to 98 years, 1,601 of whom were men) were included in the study; 81 patients (3.1%) developed a pressure ulcer. The predicted pressure ulcer incidence ranged from 0.1% to 49.7%. When the predicted pressure ulcer incidence was greater than 10.0% (high risk), the corresponding Braden scores were less than 11; when the predicted incidence ranged from 1.0% to 10.0% (moderate risk), the corresponding Braden scores ranged from 12 to 16; and when the predicted incidence was less than 1.0% (mild risk), the corresponding Braden scores were greater than 17. In the modified classification, observed pressure ulcer incidence was significantly different between each of the 3 risk categories (P less than 0.05). However, in the traditional classification, the observed incidence was not significantly different between the high-risk category and moderate-risk category (P less than 0.05) and between the mild-risk category and no-risk category (P less than 0.05). If future studies confirm the validity of these findings, pressure ulcer prevention protocols of care based on Braden Scale scores can be simplified.

Evaluation criteria for software classification inventories, accuracies, and maps

NASA Technical Reports Server (NTRS)

Jayroe, R. R., Jr.

1976-01-01

Statistical criteria are presented for modifying the contingency table used to evaluate tabular classification results obtained from remote sensing and ground truth maps. This classification technique contains information on the spatial complexity of the test site, on the relative location of classification errors, on agreement of the classification maps with ground truth maps, and reduces back to the original information normally found in a contingency table.

Kinetics evaluation and thermal decomposition characteristics of co-pyrolysis of municipal sewage sludge and hazelnut shell.

PubMed

Zhao, Bing; Xu, Xinyang; Li, Haibo; Chen, Xi; Zeng, Fanqiang

2018-01-01

Hazelnut shell, as novel biomass, has lower ash content and abundant hydrocarbon, which can be utilized resourcefully with municipal sewage sludge (MSS) by co-pyrolyisis to decrease total content of pollution. The co-pyrolysis of MSS and hazelnut shell blend was analyzed by a method of multi-heating rates and different blend ratios with TG-DTG-MS under N 2 atmosphere. The apparent activation energy of co-pyrolysis was calculated by three iso-conversional methods. Satava-Sestak method was used to determine mechanism function G(α) of co-pyrolysis, and Lorentzian function was used to simulate multi-peaks curves. The results showed there were four thermal decomposition stages, and the biomass were cracked and evolved at different temperature ranges. The apparent activation energy increased from 123.99 to 608.15kJ/mol. The reaction mechanism of co-pyrolysis is random nucleation and nuclei growth. The apparent activation energy and mechanism function afford a theoretical groundwork for co-pyrolysis technology. Copyright © 2017 Elsevier Ltd. All rights reserved.

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…

77 FR 58868 - Public Land Order No. 7798; Partial Modification of Power Site Classification No. 126; Washington

Federal Register 2010, 2011, 2012, 2013, 2014

2012-09-24

...; WAOR-19641] Public Land Order No. 7798; Partial Modification of Power Site Classification No. 126... partially modifies a withdrawal which established Power Site Classification No. 126, insofar as it affects... under Power Site Classification No. 126 for water power purposes will not be injured by U.S. Forest...

Reconstruction Using Locoregional Flaps for Large Skull Base Defects.

PubMed

Hatano, Takaharu; Motomura, Hisashi; Ayabe, Shinobu

2015-06-01

We present a modified locoregional flap for the reconstruction of large anterior skull base defects that should be reconstructed with a free flap according to Yano's algorithm. No classification of skull base defects had been proposed for a long time. Yano et al suggested a new classification in 2012. The lb defect of Yano's classification extends horizontally from the cribriform plate to the orbital roof. According to Yano's algorithm for subsequent skull base reconstructive procedures, a lb defect should be reconstructed with a free flap such as an anterolateral thigh free flap or rectus abdominis myocutaneous free flap. However, our modified locoregional flap has also enabled reconstruction of lb defects. In this case series, we used a locoregional flap for lb defects. No major postoperative complications occurred. We present our modified locoregional flap that enables reconstruction of lb defects.

Farmers prevailing perception profiles regarding GM crops: A classification proposal.

PubMed

Almeida, Carla; Massarani, Luisa

2018-04-01

Genetically modified organisms have been at the centre of a major public controversy, involving different interests and actors. While much attention has been devoted to consumer views on genetically modified food, there have been few attempts to understand the perceptions of genetically modified technology among farmers. By investigating perceptions of genetically modified organisms among Brazilian farmers, we intend to contribute towards filling this gap and thereby add the views of this stakeholder group to the genetically modified debate. A comparative analysis of our data and data from other studies indicate there is a complex variety of views on genetically modified organisms among farmers. Despite this diversity, we found variations in such views occur within limited parameters, concerned principally with expectations or concrete experiences regarding the advantages of genetically modified crops, perceptions of risks associated with them, and ethical questions they raise. We then propose a classification of prevailing profiles to represent the spectrum of perceptions of genetically modified organisms among farmers.

Computational Sensing and in vitro Classification of GMOs and Biomolecular Events

DTIC Science & Technology

2008-12-01

COMPUTATIONAL SENSING AND IN VITRO CLASSIFICATION OF GMOs AND BIOMOLECULAR EVENTS Elebeoba May1∗, Miler T. Lee2†, Patricia Dolan1, Paul Crozier1...modified organisms ( GMOs ) in the pres- ence of non-lethal agents. Using an information and coding- theoretic framework we develop a de novo method for...high through- put screening, distinguishing genetically modified organisms ( GMOs ), molecular computing, differentiating biological mark- ers

Classification of Instructional Programs: 2000 Edition.

ERIC Educational Resources Information Center

Morgan, Robert L.; Hunt, E. Stephen

This third revision of the Classification of Instructional Programs (CIP) updates and modifies education program classifications, providing a taxonomic scheme that supports the accurate tracking, assessment, and reporting of field of study and program completions activity. This edition has also been adopted as the standard field of study taxonomy…

A Modified Mean Gray Wolf Optimization Approach for Benchmark and Biomedical Problems.

PubMed

Singh, Narinder; Singh, S B

2017-01-01

A modified variant of gray wolf optimization algorithm, namely, mean gray wolf optimization algorithm has been developed by modifying the position update (encircling behavior) equations of gray wolf optimization algorithm. The proposed variant has been tested on 23 standard benchmark well-known test functions (unimodal, multimodal, and fixed-dimension multimodal), and the performance of modified variant has been compared with particle swarm optimization and gray wolf optimization. Proposed algorithm has also been applied to the classification of 5 data sets to check feasibility of the modified variant. The results obtained are compared with many other meta-heuristic approaches, ie, gray wolf optimization, particle swarm optimization, population-based incremental learning, ant colony optimization, etc. The results show that the performance of modified variant is able to find best solutions in terms of high level of accuracy in classification and improved local optima avoidance.

The impact of ICD-9 revascularization procedure codes on estimates of racial disparities in ischemic stroke.

PubMed

Boan, Andrea D; Voeks, Jenifer H; Feng, Wuwei Wayne; Bachman, David L; Jauch, Edward C; Adams, Robert J; Ovbiagele, Bruce; Lackland, Daniel T

2014-01-01

The use of International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9) diagnostic codes can identify racial disparities in ischemic stroke hospitalizations; however, inclusion of revascularization procedure codes as acute stroke events may affect the magnitude of the risk difference. This study assesses the impact of excluding revascularization procedure codes in the ICD-9 definition of ischemic stroke, compared with the traditional inclusive definition, on racial disparity estimates for stroke incidence and recurrence. Patients discharged with a diagnosis of ischemic stroke (ICD-9 codes 433.00-434.91 and 436) were identified from a statewide inpatient discharge database from 2010 to 2012. Race-age specific disparity estimates of stroke incidence and recurrence and 1-year cumulative recurrent stroke rates were compared between the routinely used traditional classification and a modified classification of stroke that excluded primary ICD-9 cerebral revascularization procedures codes (38.12, 00.61, and 00.63). The traditional classification identified 7878 stroke hospitalizations, whereas the modified classification resulted in 18% fewer hospitalizations (n = 6444). The age-specific black to white rate ratios were significantly higher in the modified than in the traditional classification for stroke incidence (rate ratio, 1.50; 95% confidence interval [CI], 1.43-1.58 vs. rate ratio, 1.24; 95% CI, 1.18-1.30, respectively). In whites, the 1-year cumulative recurrence rate was significantly reduced by 46% (45-64 years) and 49% (≥ 65 years) in the modified classification, largely explained by a higher rate of cerebral revascularization procedures among whites. There were nonsignificant reductions of 14% (45-64 years) and 19% (≥ 65 years) among blacks. Including cerebral revascularization procedure codes overestimates hospitalization rates for ischemic stroke and significantly underestimates the racial disparity estimates in stroke incidence and recurrence. Copyright © 2014 National Stroke Association. Published by Elsevier Inc. All rights reserved.

Modified Cheeger and Ratio Cut Methods Using the Ginzburg-Landau Functional for Classification of High-Dimensional Data

DTIC Science & Technology

2016-02-01

Modified Cheeger and Ratio Cut Methods Using the Ginzburg-Landau Functional for Classification of High-Dimensional Data Ekaterina Merkurjev*, Andrea...bertozzi@math.ucla.edu, xiaoran@isi.edu, lerman@isi.edu. Abstract Recent advances in clustering have included continuous relaxations of the Cheeger cut ...fully nonlinear Cheeger cut problem, as well as the ratio cut optimization task. Both problems are connected to total variation minimization, and the

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

Code of Federal Regulations, 2012 CFR

2012-07-01

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

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

Code of Federal Regulations, 2011 CFR

2011-07-01

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

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

Code of Federal Regulations, 2014 CFR

2014-07-01

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

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

Code of Federal Regulations, 2013 CFR

2013-07-01

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

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

Code of Federal Regulations, 2010 CFR

2010-07-01

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

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.

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.

Using genetically modified tomato crop plants with purple leaves for absolute weed/crop classification.

PubMed

Lati, Ran N; Filin, Sagi; Aly, Radi; Lande, Tal; Levin, Ilan; Eizenberg, Hanan

2014-07-01

Weed/crop classification is considered the main problem in developing precise weed-management methodologies, because both crops and weeds share similar hues. Great effort has been invested in the development of classification models, most based on expensive sensors and complicated algorithms. However, satisfactory results are not consistently obtained due to imaging conditions in the field. We report on an innovative approach that combines advances in genetic engineering and robust image-processing methods to detect weeds and distinguish them from crop plants by manipulating the crop's leaf color. We demonstrate this on genetically modified tomato (germplasm AN-113) which expresses a purple leaf color. An autonomous weed/crop classification is performed using an invariant-hue transformation that is applied to images acquired by a standard consumer camera (visible wavelength) and handles variations in illumination intensities. The integration of these methodologies is simple and effective, and classification results were accurate and stable under a wide range of imaging conditions. Using this approach, we simplify the most complicated stage in image-based weed/crop classification models. © 2013 Society of Chemical Industry.

Inverse scattering transform and soliton classification of the coupled modified Korteweg-de Vries equation

NASA Astrophysics Data System (ADS)

Wu, Jianping; Geng, Xianguo

2017-12-01

The inverse scattering transform of the coupled modified Korteweg-de Vries equation is studied by the Riemann-Hilbert approach. In the direct scattering process, the spectral analysis of the Lax pair is performed, from which a Riemann-Hilbert problem is established for the equation. In the inverse scattering process, by solving Riemann-Hilbert problems corresponding to the reflectionless cases, three types of multi-soliton solutions are obtained. The multi-soliton classification is based on the zero structures of the Riemann-Hilbert problem. In addition, some figures are given to illustrate the soliton characteristics of the coupled modified Korteweg-de Vries equation.

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.

TNM and Modified Dukes staging along with the demographic characteristics of patients with colorectal carcinoma

PubMed Central

Akkoca, Ayşe Neslin; Yanık, Serdar; Özdemir, Zeynep Tuğba; Cihan, Fatma Gökşin; Sayar, Süleyman; Cincin, Tarık Gandi; Çam, Akın; Özer, Cahit

2014-01-01

Aim: Colon adenocarcinoma, is the most common cancer in gastrointesinal system (GIS). The whole world is an important cause of morbidity and mortality. TNM and modified Dukes classification which has great importance in the diagnosis and treatment of Colorectal cancer (CRC). TNM and Modified Dukes classification results of histopathological examination and the demographic characteristics of patients and their relation were investigated. Materials and methods: Lower gastrointestinal operation results of 85 patients were examined accepted to clinical Pathology between January 1997-November 2013. Colon cancer had been diagnosed at 85 patients with pathology materials and staging was done according to the TNM and Modified Duke classification. The demographic characteristics of patients, differentiation grade, lymph node involvement, serous involvement were evaluated retrospectively. Results: In this study 37 patients (43.52%) were men and 48 (56.47%) were women. Ages of patients were between 19 and 87 with a mean age of 57.31 ± 15.31. Lymph node, differentiation, serosa involvement, Modified Dukes and TNM classification was assessed according to sex and age. TNM classification by sex was not statistically significant (p > 0.05). There was no statistically significant relationship between age and differentiation (p = 0.085). Value of differentiation increased towards from 1 to 3 inversely proportional to age. So young patients defined as well-differentiated at the conclusion. Negative relationship was evaluated between age and TNM Class variables. As a result, the relationship between age and TNM was not significant (p > 0.05). However, with increasing age the degree of staging was also found to increase. TNM classification was associated with the differentiation and it was significant (p = 0.043). Conclusion: Colon cancer, when contracted at an early stage, it is suitable for surgery and curative treatment can be done with minimal morbidity and mortality. However, some of the patients have advanced disease at diagnosis and their 5-year survival rate is only 8%. Every year there is prolongation of overall survival of colon cancer. It is so common cancer type so that determination of prognostic factors, disease staging and treatment strategy which affects survival is significant. PMID:25356145

Interobserver and intraobserver reliability of the modified Waldenström classification system for staging of Legg-Calvé-Perthes disease.

PubMed

Hyman, Joshua E; Trupia, Evan P; Wright, Margaret L; Matsumoto, Hiroko; Jo, Chan-Hee; Mulpuri, Kishore; Joseph, Benjamin; Kim, Harry K W

2015-04-15

The absence of a reliable classification system for Legg-Calvé-Perthes disease has contributed to difficulty in establishing consistent management strategies and in interpreting outcome studies. The purpose of this study was to assess interobserver and intraobserver reliability of the modified Waldenström classification system among a large and diverse group of pediatric orthopaedic surgeons. Twenty surgeons independently completed the first two rounds of staging: two assessments of forty deidentified radiographs of patients with Legg-Calvé-Perthes disease in various stages. Ten of the twenty surgeons completed another two rounds of staging after the addition of a second pair of radiographs in sequence. Kappa values were calculated within and between each of the rounds. Interobserver kappa values for the classification for surveys 1, 2, 3, and 4 were 0.81, 0.82, 0.76, and 0.80, respectively (with 0.61 to 0.80 considered substantial agreement and 0.81 to 1.0, nearly perfect agreement). Intraobserver agreement for the classification was an average of 0.88 (range, 0.77 to 0.96) between surveys 1 and 2 and an average of 0.87 (range, 0.81 to 0.94) between surveys 3 and 4. The modified Waldenström classification system for staging of Legg-Calvé-Perthes disease demonstrated substantial to almost perfect agreement between and within observers across multiple rounds of study. In doing so, the results of this study provide a foundation for future validation studies, in which the classification stage will be associated with clinical outcomes. Copyright © 2015 by The Journal of Bone and Joint Surgery, Incorporated.

Modified Mahalanobis Taguchi System for Imbalance Data Classification

PubMed Central

2017-01-01

The Mahalanobis Taguchi System (MTS) is considered one of the most promising binary classification algorithms to handle imbalance data. Unfortunately, MTS lacks a method for determining an efficient threshold for the binary classification. In this paper, a nonlinear optimization model is formulated based on minimizing the distance between MTS Receiver Operating Characteristics (ROC) curve and the theoretical optimal point named Modified Mahalanobis Taguchi System (MMTS). To validate the MMTS classification efficacy, it has been benchmarked with Support Vector Machines (SVMs), Naive Bayes (NB), Probabilistic Mahalanobis Taguchi Systems (PTM), Synthetic Minority Oversampling Technique (SMOTE), Adaptive Conformal Transformation (ACT), Kernel Boundary Alignment (KBA), Hidden Naive Bayes (HNB), and other improved Naive Bayes algorithms. MMTS outperforms the benchmarked algorithms especially when the imbalance ratio is greater than 400. A real life case study on manufacturing sector is used to demonstrate the applicability of the proposed model and to compare its performance with Mahalanobis Genetic Algorithm (MGA). PMID:28811820

A modified method for MRF segmentation and bias correction of MR image with intensity inhomogeneity.

PubMed

Xie, Mei; Gao, Jingjing; Zhu, Chongjin; Zhou, Yan

2015-01-01

Markov random field (MRF) model is an effective method for brain tissue classification, which has been applied in MR image segmentation for decades. However, it falls short of the expected classification in MR images with intensity inhomogeneity for the bias field is not considered in the formulation. In this paper, we propose an interleaved method joining a modified MRF classification and bias field estimation in an energy minimization framework, whose initial estimation is based on k-means algorithm in view of prior information on MRI. The proposed method has a salient advantage of overcoming the misclassifications from the non-interleaved MRF classification for the MR image with intensity inhomogeneity. In contrast to other baseline methods, experimental results also have demonstrated the effectiveness and advantages of our algorithm via its applications in the real and the synthetic MR images.

The Classification of Swanson for Congenital Anomalies of Upper Limb Modified by the Japanese Society for Surgery of the Hand (JSSH).

PubMed

Iba, Kousuke; Horii, Emiko; Ogino, Toshihiko; Kazuki, Kenichi; Kashiwa, Katsuhiko

2015-01-01

The aim of this study is to introduce the classification of Swanson for congenital anomalies of upper limb modified by the Japanese Society for Surgery of the Hand (the JSSH modification) in English. The Swanson classification has been widely accepted by most hand surgeons. However, several authors have suggested that complex cases, particularly those involving the complex spectrum of cleft hand and symbrachydactyly, are difficult to classify into the classification schemes. In the JSSH modification, brachysyndactyly, so-called atypical cleft hand and transverse deficiency are included under the same concept of transverse deficiency. Cleft hand, central polydactyly, and syndactyly are included in the same category of abnormal induction of digital rays. We believe that the JSSH modification system is effective in providing hand surgeons with the clinical features and conditions for congenital anomalies.

Treatment outcomes of saddle nose correction.

PubMed

Hyun, Sang Min; Jang, Yong Ju

2013-01-01

Many valuable classification schemes for saddle nose have been suggested that integrate clinical deformity and treatment; however, there is no consensus regarding the most suitable classification and surgical method for saddle nose correction. To present clinical characteristics and treatment outcome of saddle nose deformity and to propose a modified classification system to better characterize the variety of different saddle nose deformities. The retrospective study included 91 patients who underwent rhinoplasty for correction of saddle nose from April 1, 2003, through December 31, 2011, with a minimum follow-up of 8 months. Saddle nose was classified into 4 types according to a modified classification. Aesthetic outcomes were classified as excellent, good, fair, or poor. Patients underwent minor cosmetic concealment by dorsal augmentation (n = 8) or major septal reconstruction combined with dorsal augmentation (n = 83). Autologous costal cartilages were used in 40 patients (44%), and homologous costal cartilages were used in 5 patients (6%). According to postoperative assessment, 29 patients had excellent, 42 patients had good, 18 patients had fair, and 2 patients had poor aesthetic outcomes. No statistical difference in surgical outcome according to saddle nose classification was observed. Eight patients underwent revision rhinoplasty, owing to recurrence of saddle, wound infection, or warping of the costal cartilage for dorsal augmentation. We introduce a modified saddle nose classification scheme that is simpler and better able to characterize different deformities. Among 91 patients with saddle nose, 20 (22%) had unsuccessful outcomes (fair or poor) and 8 (9%) underwent subsequent revision rhinoplasty. Thus, management of saddle nose deformities remains challenging. 4.

The Influence of Tactile Perception on Classification of Bone Tissue at Dental Implant Insertion.

PubMed

Linck, Gláucia Kelly Silva Barbosa; Ferreira, Geovane Miranda; De Oliveira, Rubelisa Cândido Gomes; Lindh, Christina; Leles, Cláudio Rodrigues; Ribeiro-Rotta, Rejane Faria

2016-06-01

Various ways of using the Lekholm and Zarb (L&Z) classification have added to the lack of scientific evidence of the effectiveness of this clinical method in the evaluation of implant treatment. The study aims to assess subjective jawbone classifications in patients referred for implant treatment, using L&Z classification with and without surgeon's hand perception at implant insertion. The association between bone type classifications and quantitative parameters of primary implant stability was also assessed. One hundred thirty-five implants were inserted using conventional loading protocol. Three surgeons classified bone quality at implant sites using two methods: one based on periapical and panoramic images (modified L&Z) and one based on the same images associated with the surgeon's tactile perception during drilling (original L&Z). Peak insertion torque and implant stability quotient (ISQ) were recorded. The modified and original L&Z were strongly correlated (rho = 0.79; p < .001); Wilcoxon signed-rank test showed no significant difference in the distribution of bone type classification between pairs using the two methods (p = .538). Spearman correlation tested the association between primary stability parameters and bone type classifications (-0.34 to -0.57 [p < .001]). Tactile surgical perception has a minor influence on rating of subjective bone type for dental implant treatment using the L&Z classification. © 2015 Wiley Periodicals, Inc.

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

Protein classification using modified n-grams and skip-grams.

PubMed

Islam, S M Ashiqul; Heil, Benjamin J; Kearney, Christopher Michel; Baker, Erich J

2018-05-01

Classification by supervised machine learning greatly facilitates the annotation of protein characteristics from their primary sequence. However, the feature generation step in this process requires detailed knowledge of attributes used to classify the proteins. Lack of this knowledge risks the selection of irrelevant features, resulting in a faulty model. In this study, we introduce a supervised protein classification method with a novel means of automating the work-intensive feature generation step via a Natural Language Processing (NLP)-dependent model, using a modified combination of n-grams and skip-grams (m-NGSG). A meta-comparison of cross-validation accuracy with twelve training datasets from nine different published studies demonstrates a consistent increase in accuracy of m-NGSG when compared to contemporary classification and feature generation models. We expect this model to accelerate the classification of proteins from primary sequence data and increase the accessibility of protein characteristic prediction to a broader range of scientists. m-NGSG is freely available at Bitbucket: https://bitbucket.org/sm_islam/mngsg/src. A web server is available at watson.ecs.baylor.edu/ngsg. erich_baker@baylor.edu. Supplementary data are available at Bioinformatics online.

Yarn-dyed fabric defect classification based on convolutional neural network

NASA Astrophysics Data System (ADS)

Jing, Junfeng; Dong, Amei; Li, Pengfei

2017-07-01

Considering that the manual inspection of the yarn-dyed fabric can be time consuming and less efficient, a convolutional neural network (CNN) solution based on the modified AlexNet structure for the classification of the yarn-dyed fabric defect is proposed. CNN has powerful ability of feature extraction and feature fusion which can simulate the learning mechanism of the human brain. In order to enhance computational efficiency and detection accuracy, the local response normalization (LRN) layers in AlexNet are replaced by the batch normalization (BN) layers. In the process of the network training, through several convolution operations, the characteristics of the image are extracted step by step, and the essential features of the image can be obtained from the edge features. And the max pooling layers, the dropout layers, the fully connected layers are also employed in the classification model to reduce the computation cost and acquire more precise features of fabric defect. Finally, the results of the defect classification are predicted by the softmax function. The experimental results show the capability of defect classification via the modified Alexnet model and indicate its robustness.

Using clustering and a modified classification algorithm for automatic text summarization

NASA Astrophysics Data System (ADS)

Aries, Abdelkrime; Oufaida, Houda; Nouali, Omar

2013-01-01

In this paper we describe a modified classification method destined for extractive summarization purpose. The classification in this method doesn't need a learning corpus; it uses the input text to do that. First, we cluster the document sentences to exploit the diversity of topics, then we use a learning algorithm (here we used Naive Bayes) on each cluster considering it as a class. After obtaining the classification model, we calculate the score of a sentence in each class, using a scoring model derived from classification algorithm. These scores are used, then, to reorder the sentences and extract the first ones as the output summary. We conducted some experiments using a corpus of scientific papers, and we have compared our results to another summarization system called UNIS.1 Also, we experiment the impact of clustering threshold tuning, on the resulted summary, as well as the impact of adding more features to the classifier. We found that this method is interesting, and gives good performance, and the addition of new features (which is simple using this method) can improve summary's accuracy.

Clinical application of modified bag-of-features coupled with hybrid neural-based classifier in dengue fever classification using gene expression data.

PubMed

Chatterjee, Sankhadeep; Dey, Nilanjan; Shi, Fuqian; Ashour, Amira S; Fong, Simon James; Sen, Soumya

2018-04-01

Dengue fever detection and classification have a vital role due to the recent outbreaks of different kinds of dengue fever. Recently, the advancement in the microarray technology can be employed for such classification process. Several studies have established that the gene selection phase takes a significant role in the classifier performance. Subsequently, the current study focused on detecting two different variations, namely, dengue fever (DF) and dengue hemorrhagic fever (DHF). A modified bag-of-features method has been proposed to select the most promising genes in the classification process. Afterward, a modified cuckoo search optimization algorithm has been engaged to support the artificial neural (ANN-MCS) to classify the unknown subjects into three different classes namely, DF, DHF, and another class containing convalescent and normal cases. The proposed method has been compared with other three well-known classifiers, namely, multilayer perceptron feed-forward network (MLP-FFN), artificial neural network (ANN) trained with cuckoo search (ANN-CS), and ANN trained with PSO (ANN-PSO). Experiments have been carried out with different number of clusters for the initial bag-of-features-based feature selection phase. After obtaining the reduced dataset, the hybrid ANN-MCS model has been employed for the classification process. The results have been compared in terms of the confusion matrix-based performance measuring metrics. The experimental results indicated a highly statistically significant improvement with the proposed classifier over the traditional ANN-CS model.

MERRF Classification: Implications for Diagnosis and Clinical Trials.

PubMed

Finsterer, Josef; Zarrouk-Mahjoub, Sinda; Shoffner, John M

2018-03-01

Given the etiologic heterogeneity of disease classification using clinical phenomenology, we employed contemporary criteria to classify variants associated with myoclonic epilepsy with ragged-red fibers (MERRF) syndrome and to assess the strength of evidence of gene-disease associations. Standardized approaches are used to clarify the definition of MERRF, which is essential for patient diagnosis, patient classification, and clinical trial design. Systematic literature and database search with application of standardized assessment of gene-disease relationships using modified Smith criteria and of variants reported to be associated with MERRF using modified Yarham criteria. Review of available evidence supports a gene-disease association for two MT-tRNAs and for POLG. Using modified Smith criteria, definitive evidence of a MERRF gene-disease association is identified for MT-TK. Strong gene-disease evidence is present for MT-TL1 and POLG. Functional assays that directly associate variants with oxidative phosphorylation impairment were critical to mtDNA variant classification. In silico analysis was of limited utility to the assessment of individual MT-tRNA variants. With the use of contemporary classification criteria, several mtDNA variants previously reported as pathogenic or possibly pathogenic are reclassified as neutral variants. MERRF is primarily an MT-TK disease, with pathogenic variants in this gene accounting for ~90% of MERRF patients. Although MERRF is phenotypically and genotypically heterogeneous, myoclonic epilepsy is the clinical feature that distinguishes MERRF from other categories of mitochondrial disorders. Given its low frequency in mitochondrial disorders, myoclonic epilepsy is not explained simply by an impairment of cellular energetics. Although MERRF phenocopies can occur in other genes, additional data are needed to establish a MERRF disease-gene association. This approach to MERRF emphasizes standardized classification rather than clinical phenomenology, thus improving patient diagnosis and clinical trial design. Copyright © 2017 Elsevier Inc. All rights reserved.

A Modified Decision Tree Algorithm Based on Genetic Algorithm for Mobile User Classification Problem

PubMed Central

Liu, Dong-sheng; Fan, Shu-jiang

2014-01-01

In order to offer mobile customers better service, we should classify the mobile user firstly. Aimed at the limitations of previous classification methods, this paper puts forward a modified decision tree algorithm for mobile user classification, which introduced genetic algorithm to optimize the results of the decision tree algorithm. We also take the context information as a classification attributes for the mobile user and we classify the context into public context and private context classes. Then we analyze the processes and operators of the algorithm. At last, we make an experiment on the mobile user with the algorithm, we can classify the mobile user into Basic service user, E-service user, Plus service user, and Total service user classes and we can also get some rules about the mobile user. Compared to C4.5 decision tree algorithm and SVM algorithm, the algorithm we proposed in this paper has higher accuracy and more simplicity. PMID:24688389

Neural network approaches versus statistical methods in classification of multisource remote sensing data

NASA Technical Reports Server (NTRS)

Benediktsson, Jon A.; Swain, Philip H.; Ersoy, Okan K.

1990-01-01

Neural network learning procedures and statistical classificaiton methods are applied and compared empirically in classification of multisource remote sensing and geographic data. Statistical multisource classification by means of a method based on Bayesian classification theory is also investigated and modified. The modifications permit control of the influence of the data sources involved in the classification process. Reliability measures are introduced to rank the quality of the data sources. The data sources are then weighted according to these rankings in the statistical multisource classification. Four data sources are used in experiments: Landsat MSS data and three forms of topographic data (elevation, slope, and aspect). Experimental results show that two different approaches have unique advantages and disadvantages in this classification application.

Automated lidar-derived canopy height estimates for the Upper Mississippi River System

USGS Publications Warehouse

Hlavacek, Enrika

2015-01-01

Land cover/land use (LCU) classifications serve as important decision support products for researchers and land managers. The LCU classifications produced by the U.S. Geological Survey’s Upper Midwest Environmental Sciences Center (UMESC) include canopy height estimates that are assigned through manual aerial photography interpretation techniques. In an effort to improve upon these techniques, this project investigated the use of high-density lidar data for the Upper Mississippi River System to determine canopy height. An ArcGIS tool was developed to automatically derive height modifier information based on the extent of land cover features for forest classes. The measurement of canopy height included a calculation of the average height from lidar point cloud data as well as the inclusion of a local maximum filter to identify individual tree canopies. Results were compared to original manually interpreted height modifiers and to field survey data from U.S. Forest Service Forest Inventory and Analysis plots. This project demonstrated the effectiveness of utilizing lidar data to more efficiently assign height modifier attributes to LCU classifications produced by the UMESC.

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.

39 CFR 3020.91 - Modification.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Change the Mail Classification Schedule § 3020.91 Modification. The Postal Service shall submit corrections to product descriptions in the Mail Classification Schedule that do not constitute a proposal to modify the market dominant product list or the competitive product list as defined in § 3020.30 by filing...

39 CFR 3020.91 - Modification.

Code of Federal Regulations, 2011 CFR

2011-07-01

... Change the Mail Classification Schedule § 3020.91 Modification. The Postal Service shall submit corrections to product descriptions in the Mail Classification Schedule that do not constitute a proposal to modify the market dominant product list or the competitive product list as defined in § 3020.30 by filing...

Effects of two classification strategies on a Benthic Community Index for streams in the Northern Lakes and Forests Ecoregion

USGS Publications Warehouse

Butcher, Jason T.; Stewart, Paul M.; Simon, Thomas P.

2003-01-01

Ninety-four sites were used to analyze the effects of two different classification strategies on the Benthic Community Index (BCI). The first, a priori classification, reflected the wetland status of the streams; the second, a posteriori classification, used a bio-environmental analysis to select classification variables. Both classifications were examined by measuring classification strength and testing differences in metric values with respect to group membership. The a priori (wetland) classification strength (83.3%) was greater than the a posteriori (bio-environmental) classification strength (76.8%). Both classifications found one metric that had significant differences between groups. The original index was modified to reflect the wetland classification by re-calibrating the scoring criteria for percent Crustacea and Mollusca. A proposed refinement to the original Benthic Community Index is suggested. This study shows the importance of using hypothesis-driven classifications, as well as exploratory statistical analysis, to evaluate alternative ways to reveal environmental variability in biological assessment tools.

An Empirical Test of the Modified C Index and SII, O*NET, and DHOC Occupational Code Classifications

ERIC Educational Resources Information Center

Dik, Bryan J.; Hu, Ryan S. C.; Hansen, Jo-Ida C.

2007-01-01

The present study investigated new approaches for assessing Holland's congruence hypothesis by (a) developing and applying four sets of decision rules for assigning Holland codes of varying lengths for purposes of computing Eggerth and Andrew's modified C index; (b) testing the modified C index computed using these four approaches against Brown…

Gait recognition based on Gabor wavelets and modified gait energy image for human identification

NASA Astrophysics Data System (ADS)

Huang, Deng-Yuan; Lin, Ta-Wei; Hu, Wu-Chih; Cheng, Chih-Hsiang

2013-10-01

This paper proposes a method for recognizing human identity using gait features based on Gabor wavelets and modified gait energy images (GEIs). Identity recognition by gait generally involves gait representation, extraction, and classification. In this work, a modified GEI convolved with an ensemble of Gabor wavelets is proposed as a gait feature. Principal component analysis is then used to project the Gabor-wavelet-based gait features into a lower-dimension feature space for subsequent classification. Finally, support vector machine classifiers based on a radial basis function kernel are trained and utilized to recognize human identity. The major contributions of this paper are as follows: (1) the consideration of the shadow effect to yield a more complete segmentation of gait silhouettes; (2) the utilization of motion estimation to track people when walkers overlap; and (3) the derivation of modified GEIs to extract more useful gait information. Extensive performance evaluation shows a great improvement of recognition accuracy due to the use of shadow removal, motion estimation, and gait representation using the modified GEIs and Gabor wavelets.

A new pre-classification method based on associative matching method

NASA Astrophysics Data System (ADS)

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

2010-01-01

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

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

PubMed

Siuly; Li, Yan; Paul Wen, Peng

2014-03-01

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

Lexicon-enhanced sentiment analysis framework using rule-based classification scheme.

PubMed

Asghar, Muhammad Zubair; Khan, Aurangzeb; Ahmad, Shakeel; Qasim, Maria; Khan, Imran Ali

2017-01-01

With the rapid increase in social networks and blogs, the social media services are increasingly being used by online communities to share their views and experiences about a particular product, policy and event. Due to economic importance of these reviews, there is growing trend of writing user reviews to promote a product. Nowadays, users prefer online blogs and review sites to purchase products. Therefore, user reviews are considered as an important source of information in Sentiment Analysis (SA) applications for decision making. In this work, we exploit the wealth of user reviews, available through the online forums, to analyze the semantic orientation of words by categorizing them into +ive and -ive classes to identify and classify emoticons, modifiers, general-purpose and domain-specific words expressed in the public's feedback about the products. However, the un-supervised learning approach employed in previous studies is becoming less efficient due to data sparseness, low accuracy due to non-consideration of emoticons, modifiers, and presence of domain specific words, as they may result in inaccurate classification of users' reviews. Lexicon-enhanced sentiment analysis based on Rule-based classification scheme is an alternative approach for improving sentiment classification of users' reviews in online communities. In addition to the sentiment terms used in general purpose sentiment analysis, we integrate emoticons, modifiers and domain specific terms to analyze the reviews posted in online communities. To test the effectiveness of the proposed method, we considered users reviews in three domains. The results obtained from different experiments demonstrate that the proposed method overcomes limitations of previous methods and the performance of the sentiment analysis is improved after considering emoticons, modifiers, negations, and domain specific terms when compared to baseline methods.

A Novel Hybrid Classification Model of Genetic Algorithms, Modified k-Nearest Neighbor and Developed Backpropagation Neural Network

PubMed Central

Salari, Nader; Shohaimi, Shamarina; Najafi, Farid; Nallappan, Meenakshii; Karishnarajah, Isthrinayagy

2014-01-01

Among numerous artificial intelligence approaches, k-Nearest Neighbor algorithms, genetic algorithms, and artificial neural networks are considered as the most common and effective methods in classification problems in numerous studies. In the present study, the results of the implementation of a novel hybrid feature selection-classification model using the above mentioned methods are presented. The purpose is benefitting from the synergies obtained from combining these technologies for the development of classification models. Such a combination creates an opportunity to invest in the strength of each algorithm, and is an approach to make up for their deficiencies. To develop proposed model, with the aim of obtaining the best array of features, first, feature ranking techniques such as the Fisher's discriminant ratio and class separability criteria were used to prioritize features. Second, the obtained results that included arrays of the top-ranked features were used as the initial population of a genetic algorithm to produce optimum arrays of features. Third, using a modified k-Nearest Neighbor method as well as an improved method of backpropagation neural networks, the classification process was advanced based on optimum arrays of the features selected by genetic algorithms. The performance of the proposed model was compared with thirteen well-known classification models based on seven datasets. Furthermore, the statistical analysis was performed using the Friedman test followed by post-hoc tests. The experimental findings indicated that the novel proposed hybrid model resulted in significantly better classification performance compared with all 13 classification methods. Finally, the performance results of the proposed model was benchmarked against the best ones reported as the state-of-the-art classifiers in terms of classification accuracy for the same data sets. The substantial findings of the comprehensive comparative study revealed that performance of the proposed model in terms of classification accuracy is desirable, promising, and competitive to the existing state-of-the-art classification models. PMID:25419659

The use of the modified Cholesky decomposition in divergence and classification calculations

NASA Technical Reports Server (NTRS)

Vanroony, D. L.; Lynn, M. S.; Snyder, C. H.

1973-01-01

The use of the Cholesky decomposition technique is analyzed as applied to the feature selection and classification algorithms used in the analysis of remote sensing data (e.g. as in LARSYS). This technique is approximately 30% faster in classification and a factor of 2-3 faster in divergence, as compared with LARSYS. Also numerical stability and accuracy are slightly improved. Other methods necessary to deal with numerical stablity problems are briefly discussed.

Applications of remote sensing, volume 3

NASA Technical Reports Server (NTRS)

Landgrebe, D. A. (Principal Investigator)

1977-01-01

The author has identified the following significant results. Of the four change detection techniques (post classification comparison, delta data, spectral/temporal, and layered spectral temporal), the post classification comparison was selected for further development. This was based upon test performances of the four change detection method, straightforwardness of the procedures, and the output products desired. A standardized modified, supervised classification procedure for analyzing the Texas coastal zone data was compiled. This procedure was developed in order that all quadrangles in the study are would be classified using similar analysis techniques to allow for meaningful comparisons and evaluations of the classifications.

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

NASA Astrophysics Data System (ADS)

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

2015-05-01

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

Cost-effectiveness of a classification-based system for sub-acute and chronic low back pain.

PubMed

Apeldoorn, Adri T; Bosmans, Judith E; Ostelo, Raymond W; de Vet, Henrica C W; van Tulder, Maurits W

2012-07-01

Identifying relevant subgroups in patients with low back pain (LBP) is considered important to guide physical therapy practice and to improve outcomes. The aim of the present study was to assess the cost-effectiveness of a modified version of Delitto's classification-based treatment approach compared with usual physical therapy care in patients with sub-acute and chronic LBP with 1 year follow-up. All patients were classified using the modified version of Delitto's classification-based system and then randomly assigned to receive either classification-based treatment or usual physical therapy care. The main clinical outcomes measured were; global perceived effect, intensity of pain, functional disability and quality of life. Costs were measured from a societal perspective. Multiple imputations were used for missing data. Uncertainty surrounding cost differences and incremental cost-effectiveness ratios was estimated using bootstrapping. Cost-effectiveness planes and cost-effectiveness acceptability curves were estimated. In total, 156 patients were included. The outcome analyses showed a significantly better outcome on global perceived effect favoring the classification-based approach, and no differences between the groups on pain, disability and quality-adjusted life-years. Mean total societal costs for the classification-based group were 2,287, and for the usual physical therapy care group 2,020. The difference was 266 (95% CI -720 to 1,612) and not statistically significant. Cost-effectiveness analyses showed that the classification-based approach was not cost-effective in comparison with usual physical therapy care for any clinical outcome measure. The classification-based treatment approach as used in this study was not cost-effective in comparison with usual physical therapy care in a population of patients with sub-acute and chronic LBP.

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.

Classification of Spanish white wines using their electrophoretic profiles obtained by capillary zone electrophoresis with amperometric detection.

PubMed

Arribas, Alberto Sánchez; Martínez-Fernández, Marta; Moreno, Mónica; Bermejo, Esperanza; Zapardiel, Antonio; Chicharro, Manuel

2014-06-01

A method was developed for the simultaneous detection of eight polyphenols (t-resveratrol, (+)-catechin, quercetin and p-coumaric, caffeic, sinapic, ferulic, and gallic acids) by CZE with electrochemical detection. Separation of these polyphenols was achieved within 25 min using a 200 mM borate buffer (pH 9.4) containing 10% methanol as separation electrolyte. Amperometric detection of polyphenols was carried out with a glassy carbon electrode (GCE) modified with a multiwalled carbon nanotubes (CNT) layer obtained from a dispersion of CNT in polyethylenimine. The excellent electrochemical properties of this modified electrode allowed the detection and quantification of the selected polyphenols in white wines without any pretreatment step, showing remarkable signal stability despite the presence of potential fouling substances in wine. The electrophoretic profiles of white wines, obtained using this methodology, have proven to be useful for the classification of these wines by means of chemometric multivariate techniques. Principal component analysis and discriminant analysis allowed accurate classification of wine samples on the basis of their grape varietal (verdejo and airén) using the information contained in selected zones of the electropherogram. The utility of the proposed CZE methodology based on the electrochemical response of CNT-modified electrodes appears to be promising in the field of wine industry and it is expected to be successfully extended to classification of a wider range of wines made of other grape varietals. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Discrimination of genetically modified sugar beets based on terahertz spectroscopy

NASA Astrophysics Data System (ADS)

Chen, Tao; Li, Zhi; Yin, Xianhua; Hu, Fangrong; Hu, Cong

2016-01-01

The objective of this paper was to apply terahertz (THz) spectroscopy combined with chemometrics techniques for discrimination of genetically modified (GM) and non-GM sugar beets. In this paper, the THz spectra of 84 sugar beet samples (36 GM sugar beets and 48 non-GM ones) were obtained by using terahertz time-domain spectroscopy (THz-TDS) system in the frequency range from 0.2 to 1.2 THz. Three chemometrics methods, principal component analysis (PCA), discriminant analysis (DA) and discriminant partial least squares (DPLS), were employed to classify sugar beet samples into two groups: genetically modified organisms (GMOs) and non-GMOs. The DPLS method yielded the best classification result, and the percentages of successful classification for GM and non-GM sugar beets were both 100%. Results of the present study demonstrate the usefulness of THz spectroscopy together with chemometrics methods as a powerful tool to distinguish GM and non-GM sugar beets.

Classification of lung cancer patients and controls by chromatography of modified nucleosides in serum

USGS Publications Warehouse

McEntire, John E.; Kuo, Kenneth C.; Smith, Mark E.; Stalling, David L.; Richens, Jack W.; Zumwalt, Robert W.; Gehrke, Charles W.; Papermaster, Ben W.

1989-01-01

A wide spectrum of modified nucleosides has been quantified by high-performance liquid chromatography in serum of 49 male lung cancer patients, 35 patients with other cancers, and 48 patients hospitalized for nonneoplastic diseases. Data for 29 modified nucleoside peaks were normalized to an internal standard and analyzed by discriminant analysis and stepwise discriminant analysis. A model based on peaks selected by a stepwise discriminant procedure correctly classified 79% of the cancer and 75% of the noncancer subjects. It also demonstrated 84% sensitivity and 79% specificity when comparing lung cancer to noncancer subjects, and 80% sensitivity and 55% specificity in comparing lung cancer to other cancers. The nucleoside peaks having the greatest influence on the models varied dependent on the subgroups compared, confirming the importance of quantifying a wide array of nucleosides. These data support and expand previous studies which reported the utility of measuring modified nucleoside levels in serum and show that precise measurement of an array of 29 modified nucleosides in serum by high-performance liquid chromatography with UV scanning with subsequent data modeling may provide a clinically useful approach to patient classification in diagnosis and subsequent therapeutic monitoring.

Assessment of a Learning Strategy among Spine Surgeons.

PubMed

Gotfryd, Alberto Ofenhejm; Corredor, Jose Alfredo; Teixeira, William Jacobsen; Martins, Delio Eulálio; Milano, Jeronimo; Iutaka, Alexandre Sadao

2017-02-01

Pilot test, observational study. To evaluate objectively the knowledge transfer provided by theoretical and practical activities during AOSpine courses for spine surgeons. During two AOSpine principles courses, 62 participants underwent precourse assessment, which consisted of questions about their professional experience, preferences regarding adolescent idiopathic scoliosis (AIS) classification, and classifying the curves by means of the Lenke classification of two AIS clinical cases. Two learning strategies were used during the course. A postcourse questionnaire was applied to reclassify the same deformity cases. Differences in the correct answers of clinical cases between pre- and postcourse were analyzed, revealing the number of participants whose accuracy in classification improved after the course. Analysis showed a decrease in the number of participants with wrong answers in both cases after the course. In the first case, statistically significant differences were observed in both curve pattern (83.3%, p   =  0.005) and lumbar spine modifier (46.6%, p   =  0.049). No statistically significant improvement was seen in the sagittal thoracic modifier (33.3%, p   =  0.309). In the second case, statistical improvement was obtained in curve pattern (27.4%, p   =  0.018). No statistically significant improvement was seen regarding lumbar spine modifier (9.8%, p   =  0.121) and sagittal thoracic modifier (12.9%, p   =  0.081). This pilot test showed objectively that learning strategies used during AOSpine courses improved the participants' knowledge. Teaching strategies must be continually improved to ensure an optimal level of knowledge transfer.

Assessment of a Learning Strategy among Spine Surgeons

PubMed Central

Gotfryd, Alberto Ofenhejm; Teixeira, William Jacobsen; Martins, Delio Eulálio; Milano, Jeronimo; Iutaka, Alexandre Sadao

2017-01-01

Study Design Pilot test, observational study. Objective To evaluate objectively the knowledge transfer provided by theoretical and practical activities during AOSpine courses for spine surgeons. Methods During two AOSpine principles courses, 62 participants underwent precourse assessment, which consisted of questions about their professional experience, preferences regarding adolescent idiopathic scoliosis (AIS) classification, and classifying the curves by means of the Lenke classification of two AIS clinical cases. Two learning strategies were used during the course. A postcourse questionnaire was applied to reclassify the same deformity cases. Differences in the correct answers of clinical cases between pre- and postcourse were analyzed, revealing the number of participants whose accuracy in classification improved after the course. Results Analysis showed a decrease in the number of participants with wrong answers in both cases after the course. In the first case, statistically significant differences were observed in both curve pattern (83.3%, p  =  0.005) and lumbar spine modifier (46.6%, p  =  0.049). No statistically significant improvement was seen in the sagittal thoracic modifier (33.3%, p  =  0.309). In the second case, statistical improvement was obtained in curve pattern (27.4%, p  =  0.018). No statistically significant improvement was seen regarding lumbar spine modifier (9.8%, p  =  0.121) and sagittal thoracic modifier (12.9%, p  =  0.081). Conclusion This pilot test showed objectively that learning strategies used during AOSpine courses improved the participants' knowledge. Teaching strategies must be continually improved to ensure an optimal level of knowledge transfer. PMID:28451507

Detection of Genetically Modified Sugarcane by Using Terahertz Spectroscopy and Chemometrics

NASA Astrophysics Data System (ADS)

Liu, J.; Xie, H.; Zha, B.; Ding, W.; Luo, J.; Hu, C.

2018-03-01

A methodology is proposed to identify genetically modified sugarcane from non-genetically modified sugarcane by using terahertz spectroscopy and chemometrics techniques, including linear discriminant analysis (LDA), support vector machine-discriminant analysis (SVM-DA), and partial least squares-discriminant analysis (PLS-DA). The classification rate of the above mentioned methods is compared, and different types of preprocessing are considered. According to the experimental results, the best option is PLS-DA, with an identification rate of 98%. The results indicated that THz spectroscopy and chemometrics techniques are a powerful tool to identify genetically modified and non-genetically modified sugarcane.

An Addendum to "A New Tool for Climatic Analysis Using Köppen Climate Classification"

ERIC Educational Resources Information Center

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

2014-01-01

The Köppen climatic classification system in a modified format is the most widely applied system in use today. Mapping and analysis of hundreds of arid and semiarid climate stations has made the use of the additional fourth letter in BW/BS climates essential. The addition of "s," "w," or "f" to the standard…

ABCD classification system: a novel classification for subaxial cervical spine injuries.

PubMed

Shousha, Mootaz

2014-04-20

The classification system was derived through a retrospective analysis of 73 consecutive cases of subaxial cervical spine injury as well as thorough literature review. To define a new classification system for subaxial cervical spine injuries. There exist several methods to classify subaxial cervical spine injuries but no single system has emerged as clearly superior to the others. On the basis of a 2-column anatomical model, the first part of the proposed classification is an anatomical description of the injury. It delivers the information whether the injury is bony, ligamentous, or a combined one. The first 4 alphabetical letters have been used for simplicity. Each column is represented by an alphabetical letter from A to D. Each letter has a radiological meaning (A = Absent injury, B = Bony lesion, C = Combined bony and ligamentous, D = Disc or ligamentous injury).The second part of the classification is represented by 3 modifiers. These are the neurological status of the patient (N), the degree of spinal canal stenosis (S), and the degree of instability (I). For simplicity, each modifier was graded in an ascending pattern of severity from zero to 2. The last part is optional and denotes which radiological examination has been used to define the injury type. The new ABCD classification was applicable for all patients. The most common type was anterior ligamentous and posterior combined injury "DC" (37.9%), followed by "DD" injury in 12% of the cases. Through this work a new classification for cervical spine injuries is proposed. The aim is to establish criteria for a common language in description of cervical injuries aiming for simplification, especially for junior residents. Each letter and each sign has a meaning to deliver the largest amount of information. Both the radiological as well as the clinical data are represented in this scheme. However, further evaluation of this classification is needed. 3.

Organ transplant AN-DRGs: modifying the exceptions hierarchy in casemix classification.

PubMed

Antioch, K; Zhang, X

2000-01-01

The study described in this article sought to develop AN-DRG Version 3 classification revisions for organ transplantation through statistical analyses of recommendations formulated by the Australian Casemix Clinical Committee. Two separate analyses of variance were undertaken for AN-DRG Version 2 and for the proposed Version 3 AN-DRGs, using average length of stay as the dependent variable. The committee made four key recommendations which were accepted and incorporated into AN-DRG Versions 3 and 3.1. This article focuses on the classification revisions for organ transplantation.

Semi-supervised morphosyntactic classification of Old Icelandic.

PubMed

Urban, Kryztof; Tangherlini, Timothy R; Vijūnas, Aurelijus; Broadwell, Peter M

2014-01-01

We present IceMorph, a semi-supervised morphosyntactic analyzer of Old Icelandic. In addition to machine-read corpora and dictionaries, it applies a small set of declension prototypes to map corpus words to dictionary entries. A web-based GUI allows expert users to modify and augment data through an online process. A machine learning module incorporates prototype data, edit-distance metrics, and expert feedback to continuously update part-of-speech and morphosyntactic classification. An advantage of the analyzer is its ability to achieve competitive classification accuracy with minimum training data.

Hierarchical Gene Selection and Genetic Fuzzy System for Cancer Microarray Data Classification

PubMed Central

Nguyen, Thanh; Khosravi, Abbas; Creighton, Douglas; Nahavandi, Saeid

2015-01-01

This paper introduces a novel approach to gene selection based on a substantial modification of analytic hierarchy process (AHP). The modified AHP systematically integrates outcomes of individual filter methods to select the most informative genes for microarray classification. Five individual ranking methods including t-test, entropy, receiver operating characteristic (ROC) curve, Wilcoxon and signal to noise ratio are employed to rank genes. These ranked genes are then considered as inputs for the modified AHP. Additionally, a method that uses fuzzy standard additive model (FSAM) for cancer classification based on genes selected by AHP is also proposed in this paper. Traditional FSAM learning is a hybrid process comprising unsupervised structure learning and supervised parameter tuning. Genetic algorithm (GA) is incorporated in-between unsupervised and supervised training to optimize the number of fuzzy rules. The integration of GA enables FSAM to deal with the high-dimensional-low-sample nature of microarray data and thus enhance the efficiency of the classification. Experiments are carried out on numerous microarray datasets. Results demonstrate the performance dominance of the AHP-based gene selection against the single ranking methods. Furthermore, the combination of AHP-FSAM shows a great accuracy in microarray data classification compared to various competing classifiers. The proposed approach therefore is useful for medical practitioners and clinicians as a decision support system that can be implemented in the real medical practice. PMID:25823003

Hierarchical gene selection and genetic fuzzy system for cancer microarray data classification.

PubMed

Nguyen, Thanh; Khosravi, Abbas; Creighton, Douglas; Nahavandi, Saeid

2015-01-01

This paper introduces a novel approach to gene selection based on a substantial modification of analytic hierarchy process (AHP). The modified AHP systematically integrates outcomes of individual filter methods to select the most informative genes for microarray classification. Five individual ranking methods including t-test, entropy, receiver operating characteristic (ROC) curve, Wilcoxon and signal to noise ratio are employed to rank genes. These ranked genes are then considered as inputs for the modified AHP. Additionally, a method that uses fuzzy standard additive model (FSAM) for cancer classification based on genes selected by AHP is also proposed in this paper. Traditional FSAM learning is a hybrid process comprising unsupervised structure learning and supervised parameter tuning. Genetic algorithm (GA) is incorporated in-between unsupervised and supervised training to optimize the number of fuzzy rules. The integration of GA enables FSAM to deal with the high-dimensional-low-sample nature of microarray data and thus enhance the efficiency of the classification. Experiments are carried out on numerous microarray datasets. Results demonstrate the performance dominance of the AHP-based gene selection against the single ranking methods. Furthermore, the combination of AHP-FSAM shows a great accuracy in microarray data classification compared to various competing classifiers. The proposed approach therefore is useful for medical practitioners and clinicians as a decision support system that can be implemented in the real medical practice.

Improving ECG Classification Accuracy Using an Ensemble of Neural Network Modules

PubMed Central

Javadi, Mehrdad; Ebrahimpour, Reza; Sajedin, Atena; Faridi, Soheil; Zakernejad, Shokoufeh

2011-01-01

This paper illustrates the use of a combined neural network model based on Stacked Generalization method for classification of electrocardiogram (ECG) beats. In conventional Stacked Generalization method, the combiner learns to map the base classifiers' outputs to the target data. We claim adding the input pattern to the base classifiers' outputs helps the combiner to obtain knowledge about the input space and as the result, performs better on the same task. Experimental results support our claim that the additional knowledge according to the input space, improves the performance of the proposed method which is called Modified Stacked Generalization. In particular, for classification of 14966 ECG beats that were not previously seen during training phase, the Modified Stacked Generalization method reduced the error rate for 12.41% in comparison with the best of ten popular classifier fusion methods including Max, Min, Average, Product, Majority Voting, Borda Count, Decision Templates, Weighted Averaging based on Particle Swarm Optimization and Stacked Generalization. PMID:22046232

Assimilation of a knowledge base and physical models to reduce errors in passive-microwave classifications of sea ice

NASA Technical Reports Server (NTRS)

Maslanik, J. A.; Key, J.

1992-01-01

An expert system framework has been developed to classify sea ice types using satellite passive microwave data, an operational classification algorithm, spatial and temporal information, ice types estimated from a dynamic-thermodynamic model, output from a neural network that detects the onset of melt, and knowledge about season and region. The rule base imposes boundary conditions upon the ice classification, modifies parameters in the ice algorithm, determines a `confidence' measure for the classified data, and under certain conditions, replaces the algorithm output with model output. Results demonstrate the potential power of such a system for minimizing overall error in the classification and for providing non-expert data users with a means of assessing the usefulness of the classification results for their applications.

The Psychosomatic Disorders Pertaining to Dental Practice with Revised Working Type Classification

PubMed Central

2014-01-01

Psychosomatic disorders are defined as disorders characterized by physiological changes that originate partially from emotional factors. This article aims to discuss the psychosomatic disorders of the oral cavity with a revised working type classification. The author has added one more subset to the existing classification, i.e., disorders caused by altered perception of dentofacial form and function, which include body dysmorphic disorder. The author has also inserted delusional halitosis under the miscellaneous disorders classification of psychosomatic disorders and revised the already existing classification proposed for the psychosomatic disorders pertaining to dental practice. After the inclusion of the subset (disorders caused by altered perception of dentofacial form and function), the terminology "psychosomatic disorders of the oral cavity" is modified to "psychosomatic disorders pertaining to dental practice". PMID:24478896

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

PubMed

Shamim, Thorakkal

2014-01-01

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

Does the Modified Gartland Classification Clarify Decision Making?

PubMed

Leung, Sophia; Paryavi, Ebrahim; Herman, Martin J; Sponseller, Paul D; Abzug, Joshua M

2018-01-01

The modified Gartland classification system for pediatric supracondylar fractures is often utilized as a communication tool to aid in determining whether or not a fracture warrants operative intervention. This study sought to determine the interobserver and intraobserver reliability of the Gartland classification system, as well as to determine whether there was agreement that a fracture warranted operative intervention regardless of the classification system. A total of 200 anteroposterior and lateral radiographs of pediatric supracondylar humerus fractures were retrospectively reviewed by 3 fellowship-trained pediatric orthopaedic surgeons and 2 orthopaedic residents and then classified as type I, IIa, IIb, or III. The surgeons then recorded whether they would treat the fracture nonoperatively or operatively. The κ coefficients were calculated to determine interobserver and intraobserver reliability. Overall, the Wilkins-modified Gartland classification has low-moderate interobserver reliability (κ=0.475) and high intraobserver reliability (κ=0.777). A low interobserver reliability was found when differentiating between type IIa and IIb (κ=0.240) among attendings. There was moderate-high interobserver reliability for the decision to operate (κ=0.691) and high intraobserver reliability (κ=0.760). Decreased interobserver reliability was present for decision to operate among residents. For fractures classified as type I, the decision to operate was made 3% of the time and 27% for type IIa. The decision was made to operate 99% of the time for type IIb and 100% for type III. There is almost full agreement for the nonoperative treatment of Type I fractures and operative treatment for type III fractures. There is agreement that type IIb fractures should be treated operatively and that the majority of type IIa fractures should be treated nonoperatively. However, the interobserver reliability for differentiating between type IIa and IIb fractures is low. Our results validate the Gartland classfication system as a method to help direct treatment of pediatric supracondylar humerus fractures, although the modification of the system, IIa versus IIb, seems to have limited reliability and utility. Terminology based on decision to treat may lead to a more clinically useful classification system in the evaluation and treatment of pediatric supracondylar humerus fractures. Level III-diagnostic studies.

The performance of different classification criteria sets for spondyloarthritis in the worldwide ASAS-COMOSPA study.

PubMed

Bakker, Pauline; Moltó, Anna; Etcheto, Adrien; Van den Bosch, Filip; Landewé, Robert; van Gaalen, Floris; Dougados, Maxime; van der Heijde, Désirée

2017-05-16

In this study, we sought to compare the performance of spondyloarthritis (SpA) classification criteria sets in an international SpA cohort with patients included from five continents around the world. Data from the (ASAS) COMOrbidities in SPondyloArthritis (ASAS-COMOSPA) study were used. ASAS-COMOSPA is a multinational, cross-sectional study with consecutive patients diagnosed with SpA by rheumatologists worldwide. Patients were classified according to the European Spondyloarthropathy Study Group (ESSG), modified European Spondyloarthropathy Study Group (mESSG), Amor, modified Amor, Assessment of SpondyloArthritis international Society (ASAS) axial Spondyloarthritis (axSpA), ASAS peripheral spondyloarthritis (pSpA) and ClASsification criteria for Psoriatic Arthritis (CASPAR) criteria. Overlap between the classification criteria sets was assessed for patients with and without back pain. Furthermore, patients fulfilling different arms of the ASAS axSpA criteria (imaging arm, clinical arm, both arms) were compared on the presence of SpA features. A total of 3942 patients (5 continents, 26 countries) were included. The mean age was 43.6 years, 65.0% were male, 56.2% were human leucocyte antigen B27-positive and 64.4% had radiographic sacroiliitis (based on modified New York criteria). Of the patients, 85.5% were classified by the ASAS SpA criteria (87.7% ASAS axSpA, 12.3% ASAS pSpA). Fulfilment of the Amor, ESSG and CASPAR criteria was present in 83.3%, 88.4% and 21.6% of patients, respectively. Of the patients with back pain (n = 3227), most were classified by all three of Amor, ESSG and ASAS axSpA criteria (71.4%). Patients fulfilling the imaging arm and the clinical arm of the ASAS axSpA criteria had similar presentations of SpA features. In patients without back pain, overlap between classification criteria sets was seen, although to a lesser extent. Most patients with a clinical diagnosis of axial SpA in the worldwide ASAS-COMOSPA study fulfil several classification criteria sets, and a substantial overlap between different criteria sets is seen, which suggests a high level of credibility of the criteria. Large inter-regional differences in the fulfilment of classification criteria were not found. Patients fulfilling the clinical arm were remarkably similar to patients fulfilling the imaging arm with respect to the presence of most SpA features.

Shore zone land use and land cover: Central Atlantic Regional Ecological Test Site

USGS Publications Warehouse

Dolan, R.; Hayden, B.P.; Vincent, C.L.

1974-01-01

Anderson's 1972 United States Geological Survey classification in modified form was applied to the barrier-island coastline within the CARETS region. High-altitude, color-infrared photography of December, 1972, and January, 1973, served as the primary data base in this study. The CARETS shore zone studied was divided into six distinct geographical regions; area percentages for each class in the modified Anderson classification are presented. Similarities and differences between regions are discussed within the framework of man's modification of these landscapes. The results of this study are presented as a series of 19 maps of land-use categories. Recommendations are made for a remote-sensing system for monitoring the CARETS shore zone within the context of the dynamics of the landscapes studied.

Classification of product inspection items using nonlinear features

NASA Astrophysics Data System (ADS)

Talukder, Ashit; Casasent, David P.; Lee, H.-W.

1998-03-01

Automated processing and classification of real-time x-ray images of randomly oriented touching pistachio nuts is discussed. The ultimate objective is the development of a system for automated non-invasive detection of defective product items on a conveyor belt. This approach involves two main steps: preprocessing and classification. Preprocessing locates individual items and segments ones that touch using a modified watershed algorithm. The second stage involves extraction of features that allow discrimination between damaged and clean items (pistachio nuts). This feature extraction and classification stage is the new aspect of this paper. We use a new nonlinear feature extraction scheme called the maximum representation and discriminating feature (MRDF) extraction method to compute nonlinear features that are used as inputs to a classifier. The MRDF is shown to provide better classification and a better ROC (receiver operating characteristic) curve than other methods.

Genetic variability of HEV isolates: inconsistencies of current classification.

PubMed

Oliveira-Filho, Edmilson F; König, Matthias; Thiel, Heinz-Jürgen

2013-07-26

Many HEV and HEV-like sequences have been reported during the last years, including isolates which may represent a number of potential new genera, new genotypes or new subtypes within the family Hepeviridae. Using the most common classification system, difficulties in the establishment of subtypes have been reported. Moreover the relevance of subtype classification for epidemiology can be questioned. In this study we have performed phylogenetic analyses based on whole capsid gene and complete HEV genomic sequences in order to evaluate the current classification of HEV at genotype and subtype levels. The results of our analyses modify the current taxonomy of genotype 3 and refine the established system for typing of HEV. In addition we suggest a classification for hepeviruses recently isolated from bats, ferrets, rats and wild boar. Copyright © 2013 Elsevier B.V. All rights reserved.

Congenital Differences of the Upper Extremity: Classification and Treatment Principles

PubMed Central

2011-01-01

For hand surgeons, the treatment of children with congenital differences of the upper extremity is challenging because of the diverse spectrum of conditions encountered, but the task is also rewarding because it provides surgeons with the opportunity to impact a child's growth and development. An ideal classification of congenital differences of the upper extremity would reflect the full spectrum of morphologic abnormalities and encompass etiology, a guide to treatment, and provide prognoses. In this report, I review current classification systems and discuss their contradictions and limitations. In addition, I present a modified classification system and provide treatment principles. As our understanding of the etiology of congenital differences of the upper extremity increases and as experience of treating difficult cases accumulates, even an ideal classification system and optimal treatment strategies will undoubtedly continue to evolve. PMID:21909463

Statistical classification techniques for engineering and climatic data samples

NASA Technical Reports Server (NTRS)

Temple, E. C.; Shipman, J. R.

1981-01-01

Fisher's sample linear discriminant function is modified through an appropriate alteration of the common sample variance-covariance matrix. The alteration consists of adding nonnegative values to the eigenvalues of the sample variance covariance matrix. The desired results of this modification is to increase the number of correct classifications by the new linear discriminant function over Fisher's function. This study is limited to the two-group discriminant problem.

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.

Feasibility and Reliability of the Modified Berg Balance Scale in Persons with Severe Intellectual and Visual Disabilities

ERIC Educational Resources Information Center

Waninge, A.; van Wijck, R.; Steenbergen, B.; van der Schans, C. P.

2011-01-01

Background: The purpose of this study was to determine the feasibility and reliability of the modified Berg Balance Scale (mBBS) in persons with severe intellectual and visual disabilities (severe multiple disabilities, SMD) assigned Gross Motor Function Classification System (GMFCS) grades I and II. Method: Thirty-nine participants with SMD and…

A risk-based classification scheme for genetically modified foods. I: Conceptual development.

PubMed

Chao, Eunice; Krewski, Daniel

2008-12-01

The predominant paradigm for the premarket assessment of genetically modified (GM) foods reflects heightened public concern by focusing on foods modified by recombinant deoxyribonucleic acid (rDNA) techniques, while foods modified by other methods of genetic modification are generally not assessed for safety. To determine whether a GM product requires less or more regulatory oversight and testing, we developed and evaluated a risk-based classification scheme (RBCS) for crop-derived GM foods. The results of this research are presented in three papers. This paper describes the conceptual development of the proposed RBCS that focuses on two categories of adverse health effects: (1) toxic and antinutritional effects, and (2) allergenic effects. The factors that may affect the level of potential health risks of GM foods are identified. For each factor identified, criteria for differentiating health risk potential are developed. The extent to which a GM food satisfies applicable criteria for each factor is rated separately. A concern level for each category of health effects is then determined by aggregating the ratings for the factors using predetermined aggregation rules. An overview of the proposed scheme is presented, as well as the application of the scheme to a hypothetical GM food.

Axial spondyloarthritis criteria and modified NY criteria: issues and controversies.

PubMed

Deodhar, Atul

2014-06-01

The Assessment of Spondyloarthritis International Society (ASAS) classification criteria for axial spondyloarthritis (axSpA) developed in 2009 was a major step forward, since the 1984 modified New York (mNY) criteria for classification of ankylosing spondylitis (AS) were too insensitive to identify patients with early signs of axial inflammation. In the absence of "diagnostic" criteria for either axSpA or AS, both of these "classification" criteria are routinely used in clinical practice to diagnose patients. However, there is a real danger of "misdiagnosis" if classification criteria are applied erroneously by ticking "yes" or "no" boxes in an undiagnosed patient. This concern was raised and discussed at the FDA Arthritis Advisory Committee meeting in June 2013, and the committee warned that if TNF inhibitors are approved to treat axSpA, such misdiagnosis could lead to serious consequences. To gauge the SPARTAN members' familiarity with these criteria and these issues surrounding them, as well as to investigate how they are using these criteria in daily practice, two questionnaires (one each for mNY and ASAS axSpA criteria) were sent to the "full" members of SPARTAN before the annual meeting. The results showed that more than 60% of the responders used these criteria most of the time in practice to help them diagnose a patient, and nearly three fourth of responders agreed with the FDA Advisory Committee and would like to see some objective signs before prescribing TNF inhibitors to axSpA patients. A majority of responders looked at the sacroiliac joint x-rays themselves to diagnose sacroiliitis, even though they had difficulty in grading the x-rays. In a live vote at the meeting, 88% of the members suggested that SPARTAN should engage in either modifying the existing criteria or develop new diagnostic criteria for axial spondyloarthritis.

Evaluation of thyroid eye disease: quality-of-life questionnaire (TED-QOL) in Korean patients.

PubMed

Son, Byeong Jae; Lee, Sang Yeul; Yoon, Jin Sook

2014-04-01

To assess impaired quality of life (QOL) of Korean patients with thyroid eye disease (TED) using the TED-QOL questionnaire, to evaluate the adaptability of the questionnaire, and to assess the correlation between TED-QOL and scales of disease severity. Prospective, cross-sectional study. Total of 90 consecutive adult patients with TED and Graves' disease were included in this study. TED-QOL was translated into Korean and administered to the patients. The results were compared with clinical severity scores (clinical activity score, VISA (vision loss (optic neuropathy); inflammation; strabismus/motility; appearance/exposure) classification, modified NOSPECS (no signs or symptoms; only signs; soft tissue; proptosis; extraocular muscle; cornea; sight loss) score, Gorman diplopia scale, and European Group of Graves' Orbitopathy Classification). Clinical scores indicating inflammation and strabismus in patients with TED were positively correlated with overall and visual function-related QOL (Spearman coefficient 0.21-0.38, p < 0.05). Clinical scores associated with appearance were positively correlated with appearance-related QOL (Spearman coefficient 0.26-0.27, p < 0.05). In multivariate analysis, age, soft-tissue inflammation, motility disorder of modified NOSPECS, and motility disorder of VISA classification had positive correlation with overall and function-related QOL. Sex, soft-tissue inflammation, proptosis of modified NOSPECS, and appearance of VISA classification had correlation with appearance-related QOL. In addition, validity of TED-QOL was proved sufficient based on the outcomes of patient interviews and correlation between the subscales of TED-QOL. TED-QOL showed significant correlations with various objective clinical parameters of TED. TED-QOL was a simple and useful tool for rapid evaluation of QOL in daily outpatient clinics, which could be readily translated into different languages to be widely applicable to various populations. Copyright © 2014 Canadian Ophthalmological Society. Published by Elsevier Inc. All rights reserved.

Speaker normalization and adaptation using second-order connectionist networks.

PubMed

Watrous, R L

1993-01-01

A method for speaker normalization and adaption using connectionist networks is developed. A speaker-specific linear transformation of observations of the speech signal is computed using second-order network units. Classification is accomplished by a multilayer feedforward network that operates on the normalized speech data. The network is adapted for a new talker by modifying the transformation parameters while leaving the classifier fixed. This is accomplished by backpropagating classification error through the classifier to the second-order transformation units. This method was evaluated for the classification of ten vowels for 76 speakers using the first two formant values of the Peterson-Barney data. The results suggest that rapid speaker adaptation resulting in high classification accuracy can be accomplished by this method.

Modified Bat Algorithm for Feature Selection with the Wisconsin Diagnosis Breast Cancer (WDBC) Dataset

PubMed

Jeyasingh, Suganthi; Veluchamy, Malathi

2017-05-01

Early diagnosis of breast cancer is essential to save lives of patients. Usually, medical datasets include a large variety of data that can lead to confusion during diagnosis. The Knowledge Discovery on Database (KDD) process helps to improve efficiency. It requires elimination of inappropriate and repeated data from the dataset before final diagnosis. This can be done using any of the feature selection algorithms available in data mining. Feature selection is considered as a vital step to increase the classification accuracy. This paper proposes a Modified Bat Algorithm (MBA) for feature selection to eliminate irrelevant features from an original dataset. The Bat algorithm was modified using simple random sampling to select the random instances from the dataset. Ranking was with the global best features to recognize the predominant features available in the dataset. The selected features are used to train a Random Forest (RF) classification algorithm. The MBA feature selection algorithm enhanced the classification accuracy of RF in identifying the occurrence of breast cancer. The Wisconsin Diagnosis Breast Cancer Dataset (WDBC) was used for estimating the performance analysis of the proposed MBA feature selection algorithm. The proposed algorithm achieved better performance in terms of Kappa statistic, Mathew’s Correlation Coefficient, Precision, F-measure, Recall, Mean Absolute Error (MAE), Root Mean Square Error (RMSE), Relative Absolute Error (RAE) and Root Relative Squared Error (RRSE). Creative Commons Attribution License

Improved Fuzzy K-Nearest Neighbor Using Modified Particle Swarm Optimization

NASA Astrophysics Data System (ADS)

Jamaluddin; Siringoringo, Rimbun

2017-12-01

Fuzzy k-Nearest Neighbor (FkNN) is one of the most powerful classification methods. The presence of fuzzy concepts in this method successfully improves its performance on almost all classification issues. The main drawbackof FKNN is that it is difficult to determine the parameters. These parameters are the number of neighbors (k) and fuzzy strength (m). Both parameters are very sensitive. This makes it difficult to determine the values of ‘m’ and ‘k’, thus making FKNN difficult to control because no theories or guides can deduce how proper ‘m’ and ‘k’ should be. This study uses Modified Particle Swarm Optimization (MPSO) to determine the best value of ‘k’ and ‘m’. MPSO is focused on the Constriction Factor Method. Constriction Factor Method is an improvement of PSO in order to avoid local circumstances optima. The model proposed in this study was tested on the German Credit Dataset. The test of the data/The data test has been standardized by UCI Machine Learning Repository which is widely applied to classification problems. The application of MPSO to the determination of FKNN parameters is expected to increase the value of classification performance. Based on the experiments that have been done indicating that the model offered in this research results in a better classification performance compared to the Fk-NN model only. The model offered in this study has an accuracy rate of 81%, while. With using Fk-NN model, it has the accuracy of 70%. At the end is done comparison of research model superiority with 2 other classification models;such as Naive Bayes and Decision Tree. This research model has a better performance level, where Naive Bayes has accuracy 75%, and the decision tree model has 70%

The use of the Modified Telephone Interview for Cognitive Status (TICS-M) in the detection of amnestic mild cognitive impairment.

PubMed

Cook, Sarah E; Marsiske, Michael; McCoy, Karin J M

2009-06-01

Many screening tools for detecting cognitive decline require in-person assessment, which is often not cost-effective or feasible for those with physical limitations. The Modified Telephone Interview for Cognitive Status has been used for screening dementia, but little is known about its usefulness in detecting amnestic mild cognitive impairment. Community-dwelling participants (mean age=74.9, mean education = 16.1 years) were administered the Modified Telephone Interview for Cognitive Status during initial screening and subsequently given a multidomain neuropsychological battery. Participants were classified by consensus panel as cognitively normal older adult (noMCI, N=54) or amnestic mild cognitive impairment (N=17) based on neuropsychological performance and Clinical Dementia Rating Scale interview, but independent of Modified Telephone Interview for Cognitive Status score. There was a significant difference between groups in Modified Telephone Interview for Cognitive Status score (t=8.04, P<.01, noMCI range 32-43, mean [SD]=37.4 [2.5], amnestic mild cognitive impairment range 25-37, mean [SD]=31.2 [3.5]). Discriminant function analysis revealed that TICS-M alone correctly classified 85.9% of participants into their respective diagnostic classification (sensitivity=82.4%, specificity=87.0%). Receiver operating characteristics analysis resulted in cutoff score of 34 that optimized sensitivity and specificity of amnestic mild cognitive impairment classification. The Modified Telephone Interview for Cognitive Status is a brief, cost-effective screening measure for identifying those with and without amnestic mild cognitive impairment.

Classification of Dark Modified KdV Equation

NASA Astrophysics Data System (ADS)

Xiong, Na; Lou, Sen-Yue; Li, Biao; Chen, Yong

2017-07-01

The dark Korteweg-de Vries (KdV) systems are defined and classified by Kupershmidt sixteen years ago. However, there is no other classifications for other kinds of nonlinear systems. In this paper, a complete scalar classification for dark modified KdV (MKdV) systems is obtained by requiring the existence of higher order differential polynomial symmetries. Different to the nine classes of the dark KdV case, there exist twelve independent classes of the dark MKdV equations. Furthermore, for the every class of dark MKdV system, there is a free parameter. Only for a fixed parameter, the dark MKdV can be related to dark KdV via suitable Miura transformation. The recursion operators of two classes of dark MKdV systems are also given. Supported by the Global Change Research Program of China under Grant No. 2015Cb953904, National Natural Science Foundation of China under Grant Nos. 11675054, 11435005, 11175092, and 11205092 and Shanghai Knowledge Service Platform for Trustworthy Internet of Things (No. ZF1213) and K. C. Wong Magna Fund in Ningbo University

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

PubMed

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

2015-04-29

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

MISR RCCM Products

Atmospheric Science Data Center

2017-10-11

... new inland water class for RCCM calculation and changed threshold and surface classification datasets accordingly. Modified land second ... 06/21/2000 First version of RCCM. Pre-launch threshold values are used. New ancillary files: ...

The effect of the atmosphere on the classification of satellite observations to identify surface features

NASA Technical Reports Server (NTRS)

Fraser, R. S.; Bahethi, O. P.; Al-Abbas, A. H.

1977-01-01

The effect of differences in atmospheric turbidity on the classification of Landsat 1 observations of a rural scene is presented. The observations are classified by an unsupervised clustering technique. These clusters serve as a training set for use of a maximum-likelihood algorithm. The measured radiances in each of the four spectral bands are then changed by amounts measured by Landsat 1. These changes can be associated with a decrease in atmospheric turbidity by a factor of 1.3. The classification of 22% of the pixels changes as a result of the modification. The modified observations are then reclassified as an independent set. Only 3% of the pixels have a different classification than the unmodified set. Hence, if classification errors of rural areas are not to exceed 15%, a new training set has to be developed whenever the difference in turbidity between the training and test sets reaches unity.

Wildlife management by habitat units: A preliminary plan of action

NASA Technical Reports Server (NTRS)

Frentress, C. D.; Frye, R. G.

1975-01-01

Procedures for yielding vegetation type maps were developed using LANDSAT data and a computer assisted classification analysis (LARSYS) to assist in managing populations of wildlife species by defined area units. Ground cover in Travis County, Texas was classified on two occasions using a modified version of the unsupervised approach to classification. The first classification produced a total of 17 classes. Examination revealed that further grouping was justified. A second analysis produced 10 classes which were displayed on printouts which were later color-coded. The final classification was 82 percent accurate. While the classification map appeared to satisfactorily depict the existing vegetation, two classes were determined to contain significant error. The major sources of error could have been eliminated by stratifying cluster sites more closely among previously mapped soil associations that are identified with particular plant associations and by precisely defining class nomenclature using established criteria early in the analysis.

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

NASA Astrophysics Data System (ADS)

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

1999-01-01

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

Classification and reduction of pilot error

NASA Technical Reports Server (NTRS)

Rogers, W. H.; Logan, A. L.; Boley, G. D.

1989-01-01

Human error is a primary or contributing factor in about two-thirds of commercial aviation accidents worldwide. With the ultimate goal of reducing pilot error accidents, this contract effort is aimed at understanding the factors underlying error events and reducing the probability of certain types of errors by modifying underlying factors such as flight deck design and procedures. A review of the literature relevant to error classification was conducted. Classification includes categorizing types of errors, the information processing mechanisms and factors underlying them, and identifying factor-mechanism-error relationships. The classification scheme developed by Jens Rasmussen was adopted because it provided a comprehensive yet basic error classification shell or structure that could easily accommodate addition of details on domain-specific factors. For these purposes, factors specific to the aviation environment were incorporated. Hypotheses concerning the relationship of a small number of underlying factors, information processing mechanisms, and error types types identified in the classification scheme were formulated. ASRS data were reviewed and a simulation experiment was performed to evaluate and quantify the hypotheses.

High-resolution 3-T MRI of the triangular fibrocartilage complex in the wrist: injury pattern and MR features.

PubMed

Zhan, Huili; Zhang, Huibo; Bai, Rongjie; Qian, Zhanhua; Liu, Yue; Zhang, Heng; Yin, Yuming

2017-12-01

To investigate if using high-resolution 3-T MRI can identify additional injuries of the triangular fibrocartilage complex (TFCC) beyond the Palmer classification. Eighty-six patients with surgically proven TFCC injury were included in this study. All patients underwent high-resolution 3-T MRI of the injured wrist. The MR imaging features of TFCC were analyzed according to the Palmer classification. According to the Palmer classification, 69 patients could be classified as having Palmer injuries (52 had traumatic tears and 17 had degenerative tears). There were 17 patients whose injuries could not be classified according to the Palmer classification: 13 had volar or dorsal capsular TFC detachment and 4 had a horizontal tear of the articular disk. Using high-resolution 3-T MRI, we have not only found all the TFCC injuries described in the Palmer classification, additional injury types were found in this study, including horizontal tear of the TFC and capsular TFC detachment. We propose the modified Palmer classification and add the injury types that were not included in the original Palmer classification.

Yarn-dyed fabric defect classification based on convolutional neural network

NASA Astrophysics Data System (ADS)

Jing, Junfeng; Dong, Amei; Li, Pengfei; Zhang, Kaibing

2017-09-01

Considering that manual inspection of the yarn-dyed fabric can be time consuming and inefficient, we propose a yarn-dyed fabric defect classification method by using a convolutional neural network (CNN) based on a modified AlexNet. CNN shows powerful ability in performing feature extraction and fusion by simulating the learning mechanism of human brain. The local response normalization layers in AlexNet are replaced by the batch normalization layers, which can enhance both the computational efficiency and classification accuracy. In the training process of the network, the characteristics of the defect are extracted step by step and the essential features of the image can be obtained from the fusion of the edge details with several convolution operations. Then the max-pooling layers, the dropout layers, and the fully connected layers are employed in the classification model to reduce the computation cost and extract more precise features of the defective fabric. Finally, the results of the defect classification are predicted by the softmax function. The experimental results show promising performance with an acceptable average classification rate and strong robustness on yarn-dyed fabric defect classification.

U.S. Geological Survey ArcMap Sediment Classification tool

USGS Publications Warehouse

O'Malley, John

2007-01-01

The U.S. Geological Survey (USGS) ArcMap Sediment Classification tool is a custom toolbar that extends the Environmental Systems Research Institute, Inc. (ESRI) ArcGIS 9.2 Desktop application to aid in the analysis of seabed sediment classification. The tool uses as input either a point data layer with field attributes containing percentage of gravel, sand, silt, and clay or four raster data layers representing a percentage of sediment (0-100%) for the various sediment grain size analysis: sand, gravel, silt and clay. This tool is designed to analyze the percent of sediment at a given location and classify the sediments according to either the Folk (1954, 1974) or Shepard (1954) as modified by Schlee(1973) classification schemes. The sediment analysis tool is based upon the USGS SEDCLASS program (Poppe, et al. 2004).

A Consensus for Classification and Pathologic Reporting of Pseudomyxoma Peritonei and Associated Appendiceal Neoplasia: The Results of the Peritoneal Surface Oncology Group International (PSOGI) Modified Delphi Process.

PubMed

Carr, Norman J; Cecil, Thomas D; Mohamed, Faheez; Sobin, Leslie H; Sugarbaker, Paul H; González-Moreno, Santiago; Taflampas, Panos; Chapman, Sara; Moran, Brendan J

2016-01-01

Pseudomyxoma peritonei (PMP) is a complex disease with unique biological behavior that usually arises from appendiceal mucinous neoplasia. The classification of PMP and its primary appendiceal neoplasia is contentious, and an international modified Delphi consensus process was instigated to address terminology and definitions. A classification of mucinous appendiceal neoplasia was developed, and it was agreed that "mucinous adenocarcinoma" should be reserved for lesions with infiltrative invasion. The term "low-grade appendiceal mucinous neoplasm" was supported and it was agreed that "cystadenoma" should no longer be recommended. A new term of "high-grade appendiceal mucinous neoplasm" was proposed for lesions without infiltrative invasion but with high-grade cytologic atypia. Serrated polyp with or without dysplasia was preferred for tumors with serrated features confined to the mucosa with an intact muscularis mucosae. Consensus was achieved on the pathologic classification of PMP, defined as the intraperitoneal accumulation of mucus due to mucinous neoplasia characterized by the redistribution phenomenon. Three categories of PMP were agreed-low grade, high grade, and high grade with signet ring cells. Acellular mucin should be classified separately. It was agreed that low-grade and high-grade mucinous carcinoma peritonei should be considered synonymous with disseminated peritoneal adenomucinosis and peritoneal mucinous carcinomatosis, respectively. A checklist for the pathologic reporting of PMP and appendiceal mucinous neoplasms was also developed. By adopting the classifications and definitions that were agreed, different centers will be able to use uniform terminology that will allow meaningful comparison of their results.

Controlling basins of attraction in a neural network-based telemetry monitor

NASA Technical Reports Server (NTRS)

Bell, Benjamin; Eilbert, James L.

1988-01-01

The size of the basins of attraction around fixed points in recurrent neural nets (NNs) can be modified by a training process. Controlling these attractive regions by presenting training data with various amount of noise added to the prototype signal vectors is discussed. Application of this technique to signal processing results in a classification system whose sensitivity can be controlled. This new technique is applied to the classification of temporal sequences in telemetry data.

Evaluation of modified crystal violet chromoendoscopy procedure using new mucosal pit pattern classification for detection of Barrett's dysplastic lesions.

PubMed

Yuki, T; Amano, Y; Kushiyama, Y; Takahashi, Y; Ose, T; Moriyama, I; Fukuhara, H; Ishimura, N; Koshino, K; Furuta, K; Ishihara, S; Adachi, K; Kinoshita, Y

2006-05-01

Pit pattern diagnosis is important for endoscopic detection of dysplastic Barrett's lesions, though using magnification endoscopy can be difficult and laborious. We investigated the usefulness of a modified crystal violet chromoendoscopy procedure and utilised a new pit pattern classification for diagnosis of dysplastic Barrett's lesions. A total of 1,030 patients suspected of having a columnar lined oesophagus were examined, of whom 816 demonstrated a crystal violet-stained columnar lined oesophagus. The early group of patients underwent 0.05% crystal violet chromoendoscopy, while the later group was examined using 0.03% crystal violet with 3.0% acetate. A targeted biopsy of the columnar lined oesophagus was performed using crystal violet staining after making a diagnosis of closed or open type pit pattern with a newly proposed system of classification. The relationship between type of pit pattern and histologically identified dysplastic Barrett's lesions was evaluated. Dysplastic Barrett's lesions were identified in biopsy samples with an open type pit pattern with a sensitivity of 96.0%. Further, Barrett's mucosa with the intestinal predominant mucin phenotype was closely associated with the open type pit pattern (sensitivity 81.9%, specificity 95.6%). The new pit pattern classification for diagnosis of Barrett's mucosa was found to be useful for identification of cases with dysplastic lesions and possible malignant potential using a crystal violet chromoendoscopic procedure.

Classification of wetlands and deepwater habitats of the United States

USGS Publications Warehouse

Cowardin, L.M.; Carter, V.; Golet, F.C.; LaRoe, E.T.

1985-01-01

This classification, to be used in a new inventory of wetlands and deepwater habitats of the United States, is intended to describe ecological taxa, arrange them in a system useful to resource managers, furnish units for mapping, and provide uniformity of concepts and terms. Wetlands are defined by plants (hydrophytes), soils (hydric soils), and frequency of flooding. Ecologically related areas of deep water, traditionally not considered wetlands, are included in the classification as deepwater habitats.Systems form the highest level of the classification hierarchy; five are defined-Marine, Estuarine, Riverine, Lacustrine, and Palustrine. Marine and Estuarine Systems each have two Subsystems, Subtidal and Intertidal; the Riverine System has four Subsystems, Tidal, Lower Perennial, Upper Perennial, and Intermittent; the Lacustrine has two, Littoral and Limnetic; and the Palustrine has no Subsystems.Within the Subsystems, Classes are based on substrate material and flooding regime, or on vegetative life form. The same Classes may appear under one or more of the Systems or Subsystems. Six Classes are based on substrate and flooding regime: (1) Rock Bottom with a substrate of bedrock, boulders, or stones; (2) Unconsolidated Bottom with a substrate of cobbles, gravel, sand, mud, or organic material; (3) Rocky Shore with the same substrates as Rock Bottom; (4) Unconsolidated Shore with the same substrates as Unconsolidated Bottom; (5) Streambed with any of the substrates; and (6) Reef with a substrate composed of the living and dead remains of invertebrates (corals, mollusks, or worms). The bottom Classes, (1) and (2) above, are flooded all or most of the time and the shore Classes, (3) and (4), are exposed most of the time. The Class Streambed is restricted to channels of intermittent streams and tidal channels that are dewatered at low tide. The life form of the dominant vegetation defines the five Classes based on vegetative form: (1) Aquatic Bed, dominated by plants that grow principally on or below the surface of the water; (2) Moss-Lichen Wetland, dominated by mosses or lichens; (3) Emergent Wetland, dominated by emergent herbaceous angiosperms; (4) Scrub-Shrub Wetland, dominated by shrubs or small trees; and (5) Forested Wetland, dominated by large trees.The Dominance Type, which is named for the dominant plant or animal forms, is the lowest level of the classification hierarchy. Only examples are provided for this level; Dominance Types must be developed by individual users of the classification.Modifying terms applied to the Classes or Subclasses are essential for use of the system. In tidal areas, the type and duration of flooding are described by four Water Regime Modifiers: subtidal, irregularly exposed, regularly flooded, and irregularly flooded. In nontidal areas, eight Regimes are used: permanently flooded, intermittently exposed, semipermanently flooded, seasonally flooded, saturated, temporarily flooded, intermittently flooded, and artificially flooded. A hierarchical system of Water Chemistry Modifiers, adapted from the Venice System, is used to describe the salinity of the water. Fresh waters are further divided on the basis of pH. Use of a hierarchical system of soil modifiers taken directly from U.S. soil taxonomy is also required. Special modifiers are used where appropriate: excavated, impounded, diked, partly drained, farmed, and artificial.Regional differences important to wetland ecology are described through a regionalization that combines a system developed for inland areas by R. G. Bailey in 1976 with our Marine and Estuarine provinces.The structure of the classification allows it to be used at any of several hierarchical levels. Special data required for detailed application of the system are frequently unavailable, and thus data gathering may be prerequisite to classification. Development of rules by the user will be required for specific map scales. Dominance Types and relationships of plant and anima

Classification of wetlands and deepwater habitats of the United States

USGS Publications Warehouse

Cowardin, L.M.; Carter, V.; Golet, F.C.; LaRoe, E.T.

1979-01-01

This classification, to be used in a new inventory of wetlands and deepwater habitats of the United States, is intended to describe ecological taxa, arrange them in a system useful to resource managers, furnish units for mapping, and provide uniformity of concepts and terms. Wetlands are defined by plants (hydrophytes), soils (hydric soils), and frequency of flooding. Ecologically related areas of deep water, traditionally not considered wetlands, are included in the classification as deepwater habitats.Systems form the highest level of the classification hierarchy; five are defined--Marine, Estuarine, Riverine, Lacustrine, and Palustrine. Marine and Estuarine systems each have two subsystems, Subtidal and Intertidal; the Riverine system has four subsystems, Tidal, Lower Perennial, Upper Perennial, and Intermittent; the Lacustrine has two, Littoral and Limnetic; and the Palustrine has no subsystem.Within the subsystems, classes are based on substrate material and flooding regime, or on vegetative life form. The same classes may appear under one or more of the systems or subsystems. Six classes are based on substrate and flooding regime: (1) Rock Bottom with a substrate of bedrock, boulders, or stones; (2) Unconsolidated Bottom with a substrate of cobbles, gravel, sand, mud, or organic material; (3) Rocky Shore with the same substrate as Rock Bottom; (4) Unconsolidated Shore with the same substrate as Unconsolidated Bottom; (5) Streambed with any of the substrates; and (6) Reef with a substrate composed of the living and dead remains of invertebrates (corals, mollusks, or worms). The bottom classes, (1) and (2) above, are flooded all or most of the time and the shore classes, (3) and (4), are exposed most of the time. The class Streambed is restricted to channels of intermittent streams and tidal channels that are dewatered at low tide. The life form of the dominant vegetation defines the five classes based on vegetative form: (1) Aquatic Bed, dominated by plants that grow principally on or below the surface of the water; (2) Moss-Lichen Wetland, dominated by mosses or lichens; (3) Emergent Wetland, dominated by emergent herbaceous angiosperms; (4) Scrub-Shrub Wetland, dominated by shrubs or small trees; and (5) Forested Wetland, dominated by large trees.The dominance type, which is named for the dominant plant or animal forms, is the lowest level of the classification hierarchy. Only examples are provided for this level; dominance types must be developed by individual users of the classification.Modifying terms applied to the classes or subclasses are essential for use of the system. In tidal areas, the type and duration of flooding are described by four water regime modifiers: subtidal, irregularly exposed, regularly flooded, and irregularly flooded. In nontidal areas, six regimes are used: permanently flooded, intermittently exposed, semipermanently flooded, seasonally flooded, saturated, temporarily flooded, intermittently flooded, and artificially flooded. A hierarchical system of water chemistry modifiers, adapted from the Venice System, is used to describe the salinity of the water. Fresh waters are further divided on the basis of pH. Use of a hierarchical system of soil modifiers taken directly from U.S. soil taxonomy is also required. Special modifiers are used where appropriate: excavated, impounded, diked, partly drained, farmed, and artificial.Regional differences important to wetland ecology are described through a regionalization that combines a system developed for inland areas by R. G. Bailey in 1976 with our Marine and Estuarine provinces.The structure of the classification allows it to be used at any of several hierarchical levels. Special data required for detailed application of the system are frequently unavailable, and thus data gathering may be prerequisite to classification. Development of rules by the user will be required for specific map scales. Dominance types and relationships of plant and animal co

Sequence-sensitive exemplar and decision-bound accounts of speeded-classification performance in a modified Garner-tasks paradigm.

PubMed

Little, Daniel R; Wang, Tony; Nosofsky, Robert M

2016-09-01

Among the most fundamental results in the area of perceptual classification are the "correlated facilitation" and "filtering interference" effects observed in Garner's (1974) speeded categorization tasks: In the case of integral-dimension stimuli, relative to a control task, single-dimension classification is faster when there is correlated variation along a second dimension, but slower when there is orthogonal variation that cannot be filtered out (e.g., by attention). These fundamental effects may result from participants' use of a trial-by-trial bypass strategy in the control and correlated tasks: The observer changes the previous category response whenever the stimulus changes, and maintains responses if the stimulus repeats. Here we conduct modified versions of the Garner tasks that eliminate the availability of a pure bypass strategy. The fundamental facilitation and interference effects remain, but are still largely explainable in terms of pronounced sequential effects in all tasks. We develop sequence-sensitive versions of exemplar-retrieval and decision-bound models aimed at capturing the detailed, trial-by-trial response-time distribution data. The models combine assumptions involving: (i) strengthened perceptual/memory representations of stimuli that repeat across consecutive trials, and (ii) a bias to change category responses on trials in which the stimulus changes. These models can predict our observed effects and provide a more complete account of the underlying bases of performance in our modified Garner tasks. Copyright © 2016 Elsevier Inc. All rights reserved.

In silico prediction of multiple-category classification model for cytochrome P450 inhibitors and non-inhibitors using machine-learning method.

PubMed

Lee, J H; Basith, S; Cui, M; Kim, B; Choi, S

2017-10-01

The cytochrome P450 (CYP) enzyme superfamily is involved in phase I metabolism which chemically modifies a variety of substrates via oxidative reactions to make them more water-soluble and easier to eliminate. Inhibition of these enzymes leads to undesirable effects, including toxic drug accumulations and adverse drug-drug interactions. Hence, it is necessary to develop in silico models that can predict the inhibition potential of compounds for different CYP isoforms. This study focused on five major CYP isoforms, including CYP1A2, 2C9, 2C19, 2D6 and 3A4, that are responsible for more than 90% of the metabolism of clinical drugs. The main aim of this study is to develop a multiple-category classification model (MCM) for the major CYP isoforms using a Laplacian-modified naïve Bayesian method. The dataset composed of more than 4500 compounds was collected from the PubChem Bioassay database. VolSurf+ descriptors and FCFP_8 fingerprint were used as input features to build classification models. The results demonstrated that the developed MCM using Laplacian-modified naïve Bayesian method was successful in classifying inhibitors and non-inhibitors for each CYP isoform. Moreover, the accuracy, sensitivity and specificity values for both training and test sets were above 80% and also yielded satisfactory area under the receiver operating characteristic curve and Matthews correlation coefficient values.

Feasibility of a Day-Camp Model of Modified Constraint-Induced Movement Therapy with and without Botulinum Toxin A Injection for Children with Hemiplegia

ERIC Educational Resources Information Center

Eliasson, Ann-Christin; Shaw, Karin; Ponten, Eva; Boyd, Roslyn; Krumlinde-Sundholm, Lena

2009-01-01

The objective of the study was to investigate the feasibility of modified constraint-induced (CI) therapy provided in a 2-week day-camp model with and without intramuscular botulinum toxin type A (BoNT-A) injections for children with congenital cerebral palsy. Sixteen children with congenital hemiplegia, Manual Ability Classification System (MACS)…

Segmentation and classification of brain images using firefly and hybrid kernel-based support vector machine

NASA Astrophysics Data System (ADS)

Selva Bhuvaneswari, K.; Geetha, P.

2017-05-01

Magnetic resonance imaging segmentation refers to a process of assigning labels to set of pixels or multiple regions. It plays a major role in the field of biomedical applications as it is widely used by the radiologists to segment the medical images input into meaningful regions. In recent years, various brain tumour detection techniques are presented in the literature. The entire segmentation process of our proposed work comprises three phases: threshold generation with dynamic modified region growing phase, texture feature generation phase and region merging phase. by dynamically changing two thresholds in the modified region growing approach, the first phase of the given input image can be performed as dynamic modified region growing process, in which the optimisation algorithm, firefly algorithm help to optimise the two thresholds in modified region growing. After obtaining the region growth segmented image using modified region growing, the edges can be detected with edge detection algorithm. In the second phase, the texture feature can be extracted using entropy-based operation from the input image. In region merging phase, the results obtained from the texture feature-generation phase are combined with the results of dynamic modified region growing phase and similar regions are merged using a distance comparison between regions. After identifying the abnormal tissues, the classification can be done by hybrid kernel-based SVM (Support Vector Machine). The performance analysis of the proposed method will be carried by K-cross fold validation method. The proposed method will be implemented in MATLAB with various images.

[The pathomorphology of chronic apical periodontitis].

PubMed

Taatz, H; Stiefel, A

1977-01-01

The clinical, roentgenological and histopathological diagnoses of thirty apical processes are compared. The paper also discusses certain histopathological characteristics. As a result of these investigations, a proposal is made to modify the classification of chronic apical processes.

13 CFR 124.403 - How is a business plan updated and modified?

Code of Federal Regulations, 2011 CFR

2011-01-01

... aggregate dollar value of 8(a) contracts to be sought, broken down by sole source and competitive... primary industry classification falls within that Major Group. Any adjustment will take into account...

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-01-01

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

On the Discriminant Analysis in the 2-Populations Case

NASA Astrophysics Data System (ADS)

Rublík, František

2008-01-01

The empirical Bayes Gaussian rule, which in the normal case yields good values of the probability of total error, may yield high values of the maximum probability error. From this point of view the presented modified version of the classification rule of Broffitt, Randles and Hogg appears to be superior. The modification included in this paper is termed as a WR method, and the choice of its weights is discussed. The mentioned methods are also compared with the K nearest neighbours classification rule.

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

PubMed

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

2015-01-01

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

Classification of ligand molecules in PDB with graph match-based structural superposition.

PubMed

Shionyu-Mitsuyama, Clara; Hijikata, Atsushi; Tsuji, Toshiyuki; Shirai, Tsuyoshi

2016-12-01

The fast heuristic graph match algorithm for small molecules, COMPLIG, was improved by adding a structural superposition process to verify the atom-atom matching. The modified method was used to classify the small molecule ligands in the Protein Data Bank (PDB) by their three-dimensional structures, and 16,660 types of ligands in the PDB were classified into 7561 clusters. In contrast, a classification by a previous method (without structure superposition) generated 3371 clusters from the same ligand set. The characteristic feature in the current classification system is the increased number of singleton clusters, which contained only one ligand molecule in a cluster. Inspections of the singletons in the current classification system but not in the previous one implied that the major factors for the isolation were differences in chirality, cyclic conformations, separation of substructures, and bond length. Comparisons between current and previous classification systems revealed that the superposition-based classification was effective in clustering functionally related ligands, such as drugs targeted to specific biological processes, owing to the strictness of the atom-atom matching.

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

NASA Astrophysics Data System (ADS)

Wan, Yi

2011-06-01

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

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.

Gastric precancerous diseases classification using CNN with a concise model.

PubMed

Zhang, Xu; Hu, Weiling; Chen, Fei; Liu, Jiquan; Yang, Yuanhang; Wang, Liangjing; Duan, Huilong; Si, Jianmin

2017-01-01

Gastric precancerous diseases (GPD) may deteriorate into early gastric cancer if misdiagnosed, so it is important to help doctors recognize GPD accurately and quickly. In this paper, we realize the classification of 3-class GPD, namely, polyp, erosion, and ulcer using convolutional neural networks (CNN) with a concise model called the Gastric Precancerous Disease Network (GPDNet). GPDNet introduces fire modules from SqueezeNet to reduce the model size and parameters about 10 times while improving speed for quick classification. To maintain classification accuracy with fewer parameters, we propose an innovative method called iterative reinforced learning (IRL). After training GPDNet from scratch, we apply IRL to fine-tune the parameters whose values are close to 0, and then we take the modified model as a pretrained model for the next training. The result shows that IRL can improve the accuracy about 9% after 6 iterations. The final classification accuracy of our GPDNet was 88.90%, which is promising for clinical GPD recognition.

Single-Dose Oritavancin Treatment of Acute Bacterial Skin and Skin Structure Infections: SOLO Trial Efficacy by Eron Severity and Management Setting.

PubMed

Deck, Daniel H; Jordan, Jennifer M; Holland, Thomas L; Fan, Weihong; Wikler, Matthew A; Sulham, Katherine A; Ralph Corey, G

2016-09-01

Introduction of new antibiotics enabling single-dose administration, such as oritavancin may significantly impact site of care decisions for patients with acute bacterial skin and skin structure infections (ABSSSI). This analysis compared the efficacy of single-dose oritavancin with multiple-dose vancomycin in patients categorized according to disease severity via modified Eron classification and management setting. SOLO I and II were phase 3 studies evaluating single-dose oritavancin versus 7-10 days of vancomycin for treatment of ABSSSI. Patient characteristics were collected at baseline and retrospectively analyzed. Study protocols were amended, allowing outpatient management at the discretion of investigators. In this post hoc analysis, patients were categorized according to a modified Eron severity classification and management setting (outpatient vs. inpatient) and the efficacy compared. Overall, 1910 patients in the SOLO trials were categorized into Class I (520, 26.5%), II (790, 40.3%), and III (600, 30.6%). Of the 767 patients (40%) in the SOLO trials who were managed entirely in the outpatient setting 40.3% were categorized as Class II and 30.6% were Class III. Clinical efficacy was similar between oritavancin and vancomycin treatment groups, regardless of severity classification and across inpatient and outpatient settings. Class III patients had lower response rates (oritavancin 73.3%, vancomycin 76.6%) at early clinical evaluation when compared to patients in Class I (82.6%) or II (86.1%); however, clinical cure rates at the post-therapy evaluation were similar for Class III patients (oritavancin 79.8%, vancomycin 79.9%) when compared to Class I and II patients (79.1-85.7%). Single-dose oritavancin therapy results in efficacy comparable to multiple-dose vancomycin in patients categorized according to modified Eron disease severity classification regardless of whether management occurred in the inpatient or outpatient setting. The Medicines Company, Parsippany, NJ, USA. ClinicalTrials.gov identifiers, NCT01252719 (SOLO I) and NCT01252732 (SOLO II).

[Variants of choice of surgical treatment of chronic pancreatitis in consideration of morphological changes in the pancreas].

PubMed

Priadko, A S; Maĭstrenko, N A; Romashchenko, P N

2014-01-01

The results of examination and treatment of 445 patients with chronic pancreatitis were analyzed. It was established, that 298 (67%) patients had indications for treatment in the conditions of surgical hospital. The patients were divided into three groups according to the modified pancreatitis classification of Marseilles-Rome 1988. There were the calcifying form (n = 78), obstructive form (n = 81), inflammatory form (n = 139). The application of modern methods of diagnostics and treatment of chronic pancreatitis allowed modifying the classification by selection of subgroups for each form of the disease. It was stated, that the substantiation of variants of surgical treatment of chronic pancreatitis in consideration of morphological changes in the pancreas could improve the possibilities of medical care plan for patients with minimal complications and good quality of life in long-term period of time.

Reliability of the modified Tufts Lumbar Degenerative Disc Classification between neurosurgeons and neuroradiologists.

PubMed

Burke, Shane M; Hwang, Steven W; Mehan, William A; Bedi, Harprit S; Ogbuji, Richard; Riesenburger, Ron I

2016-07-01

Cross-specialty inter-rater reliability has not been explicitly reported for imaging characteristics that are thought to be important in lumbar intervertebral disc degeneration. Sufficient cross-specialty reliability is an essential consideration if radiographic stratification of symptomatic patients to specific treatment modalities is to ever be realized. Therefore the purpose of this study was to directly compare the assessment of such characteristics between neurosurgeons and neuroradiologists. Sixty consecutive patients with a diagnosis of lumbago and appropriate imaging were selected for inclusion. Lumbar MRI were evaluated using the Tufts Degenerative Disc Classification by two neurosurgeons and two neuroradiologists. Inter-rater reliability was assessed using Cohen's κ values both within and between specialties. A sensitivity analysis was performed for a modified grading system, which excluded high intensity zones (HIZ), due to poor cross-specialty inter-rater reliability of HIZ between specialties. The reliability of HIZ between neurosurgeons and neuroradiologists was fair in two of the four cross-specialty comparisons in this study (neurosurgeon 1 versus both radiologists κ=0.364 and κ=0.290). Removing HIZ from the classification improved inter-rater reliability for all comparisons within and between specialties (0.465⩽κ⩽0.576). In addition, intra-rater reliability remained in the moderate to substantial range (0.523⩽κ⩽0.649). Given our findings and corroboration with previous studies, identification of HIZ seems to have a markedly variable reliability. Thus we recommend modification of the original Tufts Degenerative Disc Classification by removing HIZ in order to make the overall grade provided by this classification more reproducible when scored by practitioners of different training backgrounds. Copyright © 2015 Elsevier Ltd. All rights reserved.

The impact of catchment source group classification on the accuracy of sediment fingerprinting outputs.

PubMed

Pulley, Simon; Foster, Ian; Collins, Adrian L

2017-06-01

The objective classification of sediment source groups is at present an under-investigated aspect of source tracing studies, which has the potential to statistically improve discrimination between sediment sources and reduce uncertainty. This paper investigates this potential using three different source group classification schemes. The first classification scheme was simple surface and subsurface groupings (Scheme 1). The tracer signatures were then used in a two-step cluster analysis to identify the sediment source groupings naturally defined by the tracer signatures (Scheme 2). The cluster source groups were then modified by splitting each one into a surface and subsurface component to suit catchment management goals (Scheme 3). The schemes were tested using artificial mixtures of sediment source samples. Controlled corruptions were made to some of the mixtures to mimic the potential causes of tracer non-conservatism present when using tracers in natural fluvial environments. It was determined how accurately the known proportions of sediment sources in the mixtures were identified after unmixing modelling using the three classification schemes. The cluster analysis derived source groups (2) significantly increased tracer variability ratios (inter-/intra-source group variability) (up to 2122%, median 194%) compared to the surface and subsurface groupings (1). As a result, the composition of the artificial mixtures was identified an average of 9.8% more accurately on the 0-100% contribution scale. It was found that the cluster groups could be reclassified into a surface and subsurface component (3) with no significant increase in composite uncertainty (a 0.1% increase over Scheme 2). The far smaller effects of simulated tracer non-conservatism for the cluster analysis based schemes (2 and 3) was primarily attributed to the increased inter-group variability producing a far larger sediment source signal that the non-conservatism noise (1). Modified cluster analysis based classification methods have the potential to reduce composite uncertainty significantly in future source tracing studies. Copyright © 2016 Elsevier Ltd. All rights reserved.

Developing the FARSEEING Taxonomy of Technologies: Classification and description of technology use (including ICT) in falls prevention studies.

PubMed

Boulton, Elisabeth; Hawley-Hague, Helen; Vereijken, Beatrix; Clifford, Amanda; Guldemond, Nick; Pfeiffer, Klaus; Hall, Alex; Chesani, Federico; Mellone, Sabato; Bourke, Alan; Todd, Chris

2016-06-01

Recent Cochrane reviews on falls and fall prevention have shown that it is possible to prevent falls in older adults living in the community and in care facilities. Technologies aimed at fall detection, assessment, prediction and prevention are emerging, yet there has been no consistency in describing or reporting on interventions using technologies. With the growth of eHealth and data driven interventions, a common language and classification is required. The FARSEEING Taxonomy of Technologies was developed as a tool for those in the field of biomedical informatics to classify and characterise components of studies and interventions. The Taxonomy Development Group (TDG) comprised experts from across Europe. Through face-to-face meetings and contributions via email, five domains were developed, modified and agreed: Approach; Base; Components of outcome measures; Descriptors of technologies; and Evaluation. Each domain included sub-domains and categories with accompanying definitions. The classification system was tested against published papers and further amendments undertaken, including development of an online tool. Six papers were classified by the TDG with levels of consensus recorded. Testing the taxonomy with papers highlighted difficulties in definitions across international healthcare systems, together with differences of TDG members' backgrounds. Definitions were clarified and amended accordingly, but some difficulties remained. The taxonomy and manual were large documents leading to a lengthy classification process. The development of the online application enabled a much simpler classification process, as categories and definitions appeared only when relevant. Overall consensus for the classified papers was 70.66%. Consensus scores increased as modifications were made to the taxonomy. The FARSEEING Taxonomy of Technologies presents a common language, which should now be adopted in the field of biomedical informatics. In developing the taxonomy as an online tool, it has become possible to continue to develop and modify the classification system to incorporate new technologies and interventions. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Modified Treatment Algorithm for Pseudogynecomastia After Massive Weight Loss.

PubMed

Ziegler, Ulrich E; Lorenz, Udo; Daigeler, Adrien; Ziegler, Selina N; Zeplin, Philip H

2018-06-19

Pseudogynecomastia is the increased aggregation of fatty tissue in the area of the male breast with resultant female appearance. Two forms can appear: pseudogynecomastia after massive weight loss (pseudogynecomastia obese [PO]) and pseudogynecomastia, which is caused only by adipose tissue (pseudogynecomastia fat). For PO, only the Gusenoff classification with corresponding operative treatment options exists. However, this classification is limited by the fact that it underestimates the extensive variability of residual fat tissue and skin excess, both crucial factors for operative planning. For this reason, we propose a modification of the treatment algorithm for the Gusenoff classification based on our results to achieve more masculine results. A total of 43 male patients with PO were included in this retrospective study (grade 1a, n = 1; grade 1b, n = 1; grade 2, n = 17; grade 3, n = 24). Forty-two mastectomies with a free nipple-areola complex (NAC) transposition (grades 2 and 3) and 1 with a subcutaneous mastectomy (grade 1a) with periareolar lifting were performed. A retrospective chart review was performed to obtain data regarding age, body mass index, body mass index loss, weight loss, reason for weight loss, comorbidities, nicotine, and additional procedures, postoperative sensitive on the NAC transplants and complications. None of the free-nipple grafts were lost. Forty (95%) of 42 patients with mastectomy had a resensitivity on the NAC. For pseudogynecomastia, the treatment algorithm of the Gusenoff classification should be modified and adapted according to our recommendations to achieve more optimal masculine results.

Modification of the Fitzpatrick system of skin phototype classification for the Indian population, and its correlation with narrowband diffuse reflectance spectrophotometry.

PubMed

Sharma, V K; Gupta, V; Jangid, B L; Pathak, M

2018-04-01

The Fitzpatrick classification for skin phototyping is widely used, but its usefulness in dark-skinned populations has been questioned by some researchers. Recently, skin colour measurement has been proposed for phototyping skin colour objectively. To modify the Fitzpatrick system of skin phototyping for the Indian population and to study its correlation with skin colour using narrowband diffuse reflectance spectrophotometry METHODS: Answer choices for three items (eye colour, hair colour, colour of unexposed skin) out of 10 in the original Fitzpatrick questionnaire were modified, followed by self-administration of the original and the modified Fitzpatrick questionnaire by 70 healthy Indian volunteers. Skin colour (melanin and erythema indices) was measured from two photoexposed and two photoprotected sites using a narrowband reflectance spectrophotometer. The mean ± SD scores for the original and modified Fitzpatrick questionnaires were 25.40 ± 4.49 and 23.89 ± 4.82, respectively (r = 0.97, P < 0.001). The two items related to tanning habits were deemed irrelevant based on the subjects' response and were removed from the modified questionnaire. The Melanin Index (MI) of all sites correlated moderately well with both the modified (r = 0.61-0.64, P < 0.001) and original Fitzpatrick questionnaire scores (r = 0.64-0.67, P < 0.001), while the Erythema Index showed poor correlation with both. An MI value of ≧42 was found to be the cut-off between skin phototypes I-III and IV, and ≥ 47 between IV and V-VI. Our modification of the Fitzpatrick questionnaire makes it more relevant to the Indian population. Spectrophotometry can be a useful objective tool for skin phototyping. © 2018 British Association of Dermatologists.

Classification and correlates of eating disorders among Blacks: findings from the National Survey of American Life.

PubMed

Taylor, Jacquelyn Y; Caldwell, Cleopatra Howard; Baser, Raymond E; Matusko, Niki; Faison, Nakesha; Jackson, James S

2013-02-01

To assess classification adjustments and examine correlates of eating disorders among Blacks. The National Survey of American Life (NSAL) was conducted from 2001-2003 and consisted of adults (n=5,191) and adolescents (n=1,170). The World Mental Health Composite International Diagnostic Interview (WMH-CIDI-World Health Organization 2004-modified) and DSM-IV-TR eating disorder criteria were used. Sixty-six percent of African American and 59% Caribbean Black adults were overweight or obese, while 30% and 29% of adolescents were overweight or obese. Although lifetime rates of anorexia nervosa and bulimia nervosa were low, binge eating disorder was high for both ethnic groups among adults and adolescents. Eliminating certain classification criteria resulted in higher rates of eating disorders for all groups. Culturally sensitive criteria should be incorporated into future versions of Diagnostic Statistical Manual (DSM) classifications for eating disorders that consider within-group ethnic variations.

Telephone-quality pathological speech classification using empirical mode decomposition.

PubMed

Kaleem, M F; Ghoraani, B; Guergachi, A; Krishnan, S

2011-01-01

This paper presents a computationally simple and effective methodology based on empirical mode decomposition (EMD) for classification of telephone quality normal and pathological speech signals. EMD is used to decompose continuous normal and pathological speech signals into intrinsic mode functions, which are analyzed to extract physically meaningful and unique temporal and spectral features. Using continuous speech samples from a database of 51 normal and 161 pathological speakers, which has been modified to simulate telephone quality speech under different levels of noise, a linear classifier is used with the feature vector thus obtained to obtain a high classification accuracy, thereby demonstrating the effectiveness of the methodology. The classification accuracy reported in this paper (89.7% for signal-to-noise ratio 30 dB) is a significant improvement over previously reported results for the same task, and demonstrates the utility of our methodology for cost-effective remote voice pathology assessment over telephone channels.

Immune Protection of Nonhuman Primates Against Ebola Virus with Single Low-Dose Adenovirus Vectors Encoding Modified GPs

DTIC Science & Technology

2006-06-01

21. Geisbert TW, Hensley LE , Larsen T, Young HA, Reed DS, et al. (2003) Pathogenesis of Ebola hemorrhagic fever in cynomolgus macaques: Evidence that...Shedlock DJ, Xu L, et al. (2006) Immune protection of nonhuman primates against Ebola virus with single low-dose adenovirus vectors encoding modified...CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT SAR 18. NUMBER OF PAGES 9 19a. NAME OF RESPONSIBLE PERSON a. REPORT unclassified b. ABSTRACT

Remote sensing of aquatic vegetation distribution in Taihu Lake using an improved classification tree with modified thresholds.

PubMed

Zhao, Dehua; Jiang, Hao; Yang, Tangwu; Cai, Ying; Xu, Delin; An, Shuqing

2012-03-01

Classification trees (CT) have been used successfully in the past to classify aquatic vegetation from spectral indices (SI) obtained from remotely-sensed images. However, applying CT models developed for certain image dates to other time periods within the same year or among different years can reduce the classification accuracy. In this study, we developed CT models with modified thresholds using extreme SI values (CT(m)) to improve the stability of the models when applying them to different time periods. A total of 903 ground-truth samples were obtained in September of 2009 and 2010 and classified as emergent, floating-leaf, or submerged vegetation or other cover types. Classification trees were developed for 2009 (Model-09) and 2010 (Model-10) using field samples and a combination of two images from winter and summer. Overall accuracies of these models were 92.8% and 94.9%, respectively, which confirmed the ability of CT analysis to map aquatic vegetation in Taihu Lake. However, Model-10 had only 58.9-71.6% classification accuracy and 31.1-58.3% agreement (i.e., pixels classified the same in the two maps) for aquatic vegetation when it was applied to image pairs from both a different time period in 2010 and a similar time period in 2009. We developed a method to estimate the effects of extrinsic (EF) and intrinsic (IF) factors on model uncertainty using Modis images. Results indicated that 71.1% of the instability in classification between time periods was due to EF, which might include changes in atmospheric conditions, sun-view angle and water quality. The remainder was due to IF, such as phenological and growth status differences between time periods. The modified version of Model-10 (i.e. CT(m)) performed better than traditional CT with different image dates. When applied to 2009 images, the CT(m) version of Model-10 had very similar thresholds and performance as Model-09, with overall accuracies of 92.8% and 90.5% for Model-09 and the CT(m) version of Model-10, respectively. CT(m) decreased the variability related to EF and IF and thereby improved the applicability of the models to different time periods. In both practice and theory, our results suggested that CT(m) was more stable than traditional CT models and could be used to map aquatic vegetation in time periods other than the one for which the model was developed. Copyright © 2011 Elsevier Ltd. All rights reserved.

Evaluation of carotid plaque vulnerability in vivo: Correlation between dynamic contrast-enhanced MRI and MRI-modified AHA classification.

PubMed

Ge, Xiaoqian; Zhou, Zien; Zhao, Huilin; Li, Xiao; Sun, Beibei; Suo, Shiteng; Hackett, Maree L; Wan, Jieqing; Xu, Jianrong; Liu, Xiaosheng

2017-09-01

To noninvasively monitor carotid plaque vulnerability by exploring the relationship between pharmacokinetic parameters (PPs) of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and plaque types based on MRI-modified American Heart Association (AHA) classification, as well as to assess the ability of PPs in discrimination between stable and vulnerable plaques suspected on MRI. Of 70 consecutive patients with carotid plaques who volunteered for 3.0T MRI (3D time-of-flight [TOF], T 1 -weighted, T 2 -weighted, 3D magnetization-prepared rapid acquisition gradient-echo [MP-RAGE] and DCE-MRI), 66 participants were available for analysis. After plaque classification according to MRI-modified AHA Lesion-Type (LT), PPs (K trans , k ep , v e , and v p ) of DCE-MRI were measured. The Extended Tofts model was used for calculation of PPs. For participants with multiple carotid plaques, the plaque with the worst MRI-modified AHA LT was chosen for analysis. Correlations between PPs and plaque types and the ability of these parameters to distinguish stable and vulnerable plaques suspected on MRI were assessed. Significant positive correlation between K trans and LT III to VI was found (ρ = 0.532, P < 0.001), as was the correlation between k ep and LT III to VI (ρ = 0.409, P < 0.001). Stable and vulnerable plaques suspected on MRI could potentially be distinguished by K trans (sensitivity 83%, specificity 100%) and k ep (sensitivity 77%, specificity 91%). K trans and k ep from DCE-MRI can provide quantitative information to monitor plaque vulnerability in vivo and differentiate vulnerable plaques suspected on MRI from stable ones. These two parameters could be adopted as imaging biomarkers for plaque characterization and risk stratification. 1 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:870-876. © 2017 International Society for Magnetic Resonance in Medicine.

Three approaches to the classification of inland wetlands. [Dismal Swamp, Tennessee, and Florida

NASA Technical Reports Server (NTRS)

Gammon, P. T.; Malone, D.; Brooks, P. D.; Carter, V.

1977-01-01

In the Dismal Swamp project, seasonal, color-infrared aerial photographs and LANDSAT digital data were interpreted for a detailed analysis of the vegetative communities in a large, highly altered wetland. In Western Tennessee, seasonal high altitude color-infrared aerial photographs provided the hydrologic and vegetative information needed to map inland wetlands, using a classification system developed for the Tennessee Valley Region. In Florida, color-infrared aerial photographs were analyzed to produce wetland maps using three existing classification systems to evaluate the information content and mappability of each system. The methods used in each of the three projects can be extended or modified for use in the mapping of inland wetlands in other parts of the United States.

Terrain classification in navigation of an autonomous mobile robot

NASA Astrophysics Data System (ADS)

Dodds, David R.

1991-03-01

In this paper we describe a method of path planning that integrates terrain classification (by means of fractals) the certainty grid method of spatial representation Kehtarnavaz Griswold collision-zones Dubois Prade fuzzy temporal and spatial knowledge and non-point sized qualitative navigational planning. An initially planned (" end-to-end" ) path is piece-wise modified to accommodate known and inferred moving obstacles and includes attention to time-varying multiple subgoals which may influence a section of path at a time after the robot has begun traversing that planned path.

Rationale for classification of combustible gases, vapors and dusts with reference to the National Electrical Code

NASA Astrophysics Data System (ADS)

1982-07-01

Serious reservations about the entire classification procedure of chemical compounds present in electrical equipment environments and the precepts on which it is based are discussed. Although some tests were conducted on selected key compounds, the committee primarily considered the chemical similarity of compounds and other known flammability properties and relied heavily on the experience and intuition of its members. The committee also recommended that the NEC grouping of dusts be changed in some ways and has reclassified dusts according to the modified version of the code.

BATS AND BT INSECT RESISTANCE ON AGRICULTURAL LANDSCAPES

EPA Science Inventory

A landscape model that utilizes land cover classification data, insect life history, insect movement, and bat foraging pressure is developed that addresses the implementation of genetically modified crops in the Winter Garden region of Texas. The principal strategy for delaying r...

Modeling urban land development as a continuum to address fine-grained habitat heterogeneity

Treesearch

P.N. Manley; S.A. Parks; Lori Campbell; M.D. Schlesinger

2009-01-01

Natural landscapes are increasingly subjected to impacts associated with urbanization, resulting in loss and degradation of native ecosystems and biodiversity. Traditional classification approaches to the characterization of urbanization may prove inadequate in some human-modified...

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.

Combining various types of classifiers and features extracted from magnetic resonance imaging data in schizophrenia recognition.

PubMed

Janousova, Eva; Schwarz, Daniel; Kasparek, Tomas

2015-06-30

We investigated a combination of three classification algorithms, namely the modified maximum uncertainty linear discriminant analysis (mMLDA), the centroid method, and the average linkage, with three types of features extracted from three-dimensional T1-weighted magnetic resonance (MR) brain images, specifically MR intensities, grey matter densities, and local deformations for distinguishing 49 first episode schizophrenia male patients from 49 healthy male subjects. The feature sets were reduced using intersubject principal component analysis before classification. By combining the classifiers, we were able to obtain slightly improved results when compared with single classifiers. The best classification performance (81.6% accuracy, 75.5% sensitivity, and 87.8% specificity) was significantly better than classification by chance. We also showed that classifiers based on features calculated using more computation-intensive image preprocessing perform better; mMLDA with classification boundary calculated as weighted mean discriminative scores of the groups had improved sensitivity but similar accuracy compared to the original MLDA; reducing a number of eigenvectors during data reduction did not always lead to higher classification accuracy, since noise as well as the signal important for classification were removed. Our findings provide important information for schizophrenia research and may improve accuracy of computer-aided diagnostics of neuropsychiatric diseases. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Kardashev's Classification at 50+: A Fine Vehicle With Room for Improvement

NASA Astrophysics Data System (ADS)

Ćirković, M. M.

2015-12-01

We review the history and status of the famous classification of extraterrestrial civilizations given by the great Russian astrophysicist Nikolai Semenovich Kardashev, roughly half a century after it has been proposed. While Kardashev's classification (or Kardashev's scale) has often been seen as oversimplified, and multiple improvements, refinements, and alternatives to it have been suggested, it is still one of the major tools for serious theoretical investigation of SETI issues. During these 50+ years, several attempts at modifying or reforming the classification have been made; we review some of them here, together with presenting some of the scenarios which present difficulties to the standard version. Recent results in both theoretical and observational SETI studies, especially the {Ĝ infrared survey (2014-2015), have persuasively shown that the emphasis on detectability inherent in Kardashev's classification obtains new significance and freshness. Several new movements and conceptual frameworks, such as the Dysonian SETI, tally extremely well with these developments. So, the apparent simplicity of the classification is highly deceptive: Kardashev's work offers a wealth of still insufficiently studied methodological and epistemological ramifications and it remains, in both letter and spirit, perhaps the worthiest legacy of the SETI "founding fathers".

Applying matching pursuit decomposition time-frequency processing to UGS footstep classification

NASA Astrophysics Data System (ADS)

Larsen, Brett W.; Chung, Hugh; Dominguez, Alfonso; Sciacca, Jacob; Kovvali, Narayan; Papandreou-Suppappola, Antonia; Allee, David R.

2013-06-01

The challenge of rapid footstep detection and classification in remote locations has long been an important area of study for defense technology and national security. Also, as the military seeks to create effective and disposable unattended ground sensors (UGS), computational complexity and power consumption have become essential considerations in the development of classification techniques. In response to these issues, a research project at the Flexible Display Center at Arizona State University (ASU) has experimented with footstep classification using the matching pursuit decomposition (MPD) time-frequency analysis method. The MPD provides a parsimonious signal representation by iteratively selecting matched signal components from a pre-determined dictionary. The resulting time-frequency representation of the decomposed signal provides distinctive features for different types of footsteps, including footsteps during walking or running activities. The MPD features were used in a Bayesian classification method to successfully distinguish between the different activities. The computational cost of the iterative MPD algorithm was reduced, without significant loss in performance, using a modified MPD with a dictionary consisting of signals matched to cadence temporal gait patterns obtained from real seismic measurements. The classification results were demonstrated with real data from footsteps under various conditions recorded using a low-cost seismic sensor.

Automatic classification of protein structures using physicochemical parameters.

PubMed

Mohan, Abhilash; Rao, M Divya; Sunderrajan, Shruthi; Pennathur, Gautam

2014-09-01

Protein classification is the first step to functional annotation; SCOP and Pfam databases are currently the most relevant protein classification schemes. However, the disproportion in the number of three dimensional (3D) protein structures generated versus their classification into relevant superfamilies/families emphasizes the need for automated classification schemes. Predicting function of novel proteins based on sequence information alone has proven to be a major challenge. The present study focuses on the use of physicochemical parameters in conjunction with machine learning algorithms (Naive Bayes, Decision Trees, Random Forest and Support Vector Machines) to classify proteins into their respective SCOP superfamily/Pfam family, using sequence derived information. Spectrophores™, a 1D descriptor of the 3D molecular field surrounding a structure was used as a benchmark to compare the performance of the physicochemical parameters. The machine learning algorithms were modified to select features based on information gain for each SCOP superfamily/Pfam family. The effect of combining physicochemical parameters and spectrophores on classification accuracy (CA) was studied. Machine learning algorithms trained with the physicochemical parameters consistently classified SCOP superfamilies and Pfam families with a classification accuracy above 90%, while spectrophores performed with a CA of around 85%. Feature selection improved classification accuracy for both physicochemical parameters and spectrophores based machine learning algorithms. Combining both attributes resulted in a marginal loss of performance. Physicochemical parameters were able to classify proteins from both schemes with classification accuracy ranging from 90-96%. These results suggest the usefulness of this method in classifying proteins from amino acid sequences.

SVM classification of microaneurysms with imbalanced dataset based on borderline-SMOTE and data cleaning techniques

NASA Astrophysics Data System (ADS)

Wang, Qingjie; Xin, Jingmin; Wu, Jiayi; Zheng, Nanning

2017-03-01

Microaneurysms are the earliest clinic signs of diabetic retinopathy, and many algorithms were developed for the automatic classification of these specific pathology. However, the imbalanced class distribution of dataset usually causes the classification accuracy of true microaneurysms be low. Therefore, by combining the borderline synthetic minority over-sampling technique (BSMOTE) with the data cleaning techniques such as Tomek links and Wilson's edited nearest neighbor rule (ENN) to resample the imbalanced dataset, we propose two new support vector machine (SVM) classification algorithms for the microaneurysms. The proposed BSMOTE-Tomek and BSMOTE-ENN algorithms consist of: 1) the adaptive synthesis of the minority samples in the neighborhood of the borderline, and 2) the remove of redundant training samples for improving the efficiency of data utilization. Moreover, the modified SVM classifier with probabilistic outputs is used to divide the microaneurysm candidates into two groups: true microaneurysms and false microaneurysms. The experiments with a public microaneurysms database shows that the proposed algorithms have better classification performance including the receiver operating characteristic (ROC) curve and the free-response receiver operating characteristic (FROC) curve.

Fact Sheet: Revisions to the Occupational Safety and Health Administration Hazard Communication Standards (HCS)

EPA Pesticide Factsheets

On March 26, 2012, Occupational Safety and Health Administration (OSHA) modified its HCS to conform to the United Nations’ (UN) Globally Harmonized System of Classification and Labeling of Chemicals (GHS), to improve consistency and quality of information.

Sphincter lesions observed on ultrasound after transanal endoscopic surgery.

PubMed

Mora López, Laura; Serra-Aracil, Xavier; Navarro Soto, Salvador

2015-12-14

To assess the morphological impact of transanal endoscopic surgery on the sphincter apparatus using the modified Starck classification. A prospective, observational study of 118 consecutive patients undergoing Transanal Endoscopic Operation/Transanal Endoscopic Microsurgery (TEO/TEM) from March 2013 to May 2014 was performed. All the patients underwent an endoanal ultrasound prior to surgery and one and four months postoperatively in order to measure sphincter width, identify sphincter defects and to quantify them in terms of the level, depth and size of the affected anal canal. To assess the lesions, we used the "modified" Starck classification, which incorporates the variable "sphincter fragmentation". The results were correlated with the Wexner incontinence questionnaire. Of the 118 patients, twelve (sphincter lesions) were excluded. The results of the 106 patients were as follows after one month: 31 (29.2%) lesions found on ultrasound after one month, median overall Starck score of 4 (range 3-6); 10 (9.4%) defects in the internal anal sphincter (IAS) and 3 (2.8%) in the external anal sphincter (EAS); 17 patients (16%) had fragmentation of the sphincter apparatus with both sphincters affected in one case. At four months: 7 (6.6%) defects, all in the IAS, overall median Starck score of 4 (range 3-6). Mean IAS widths were 3.5 mm (SD 1.14) preoperatively, 4.38 mm (SD 2.1) one month postoperatively and 4.03 mm (SD 1.46) four months postoperatively. The only statistically significant difference in sphincter width in the IAS measurements was between preoperatively and one month postoperatively. No incontinence was reported, even in cases of ultrasound abnormalities. TEO/TEM may produce ultrasound abnormalities but this is not accompanied by clinical changes in continence. The modified Starck classification is useful for describing and managing these disorders.

Gene selection for cancer classification with the help of bees.

PubMed

Moosa, Johra Muhammad; Shakur, Rameen; Kaykobad, Mohammad; Rahman, Mohammad Sohel

2016-08-10

Development of biologically relevant models from gene expression data notably, microarray data has become a topic of great interest in the field of bioinformatics and clinical genetics and oncology. Only a small number of gene expression data compared to the total number of genes explored possess a significant correlation with a certain phenotype. Gene selection enables researchers to obtain substantial insight into the genetic nature of the disease and the mechanisms responsible for it. Besides improvement of the performance of cancer classification, it can also cut down the time and cost of medical diagnoses. This study presents a modified Artificial Bee Colony Algorithm (ABC) to select minimum number of genes that are deemed to be significant for cancer along with improvement of predictive accuracy. The search equation of ABC is believed to be good at exploration but poor at exploitation. To overcome this limitation we have modified the ABC algorithm by incorporating the concept of pheromones which is one of the major components of Ant Colony Optimization (ACO) algorithm and a new operation in which successive bees communicate to share their findings. The proposed algorithm is evaluated using a suite of ten publicly available datasets after the parameters are tuned scientifically with one of the datasets. Obtained results are compared to other works that used the same datasets. The performance of the proposed method is proved to be superior. The method presented in this paper can provide subset of genes leading to more accurate classification results while the number of selected genes is smaller. Additionally, the proposed modified Artificial Bee Colony Algorithm could conceivably be applied to problems in other areas as well.

Evaluating the potential for site-specific modification of LiDAR DEM derivatives to improve environmental planning-scale wetland identification using Random Forest classification

NASA Astrophysics Data System (ADS)

O'Neil, Gina L.; Goodall, Jonathan L.; Watson, Layne T.

2018-04-01

Wetlands are important ecosystems that provide many ecological benefits, and their quality and presence are protected by federal regulations. These regulations require wetland delineations, which can be costly and time-consuming to perform. Computer models can assist in this process, but lack the accuracy necessary for environmental planning-scale wetland identification. In this study, the potential for improvement of wetland identification models through modification of digital elevation model (DEM) derivatives, derived from high-resolution and increasingly available light detection and ranging (LiDAR) data, at a scale necessary for small-scale wetland delineations is evaluated. A novel approach of flow convergence modelling is presented where Topographic Wetness Index (TWI), curvature, and Cartographic Depth-to-Water index (DTW), are modified to better distinguish wetland from upland areas, combined with ancillary soil data, and used in a Random Forest classification. This approach is applied to four study sites in Virginia, implemented as an ArcGIS model. The model resulted in significant improvement in average wetland accuracy compared to the commonly used National Wetland Inventory (84.9% vs. 32.1%), at the expense of a moderately lower average non-wetland accuracy (85.6% vs. 98.0%) and average overall accuracy (85.6% vs. 92.0%). From this, we concluded that modifying TWI, curvature, and DTW provides more robust wetland and non-wetland signatures to the models by improving accuracy rates compared to classifications using the original indices. The resulting ArcGIS model is a general tool able to modify these local LiDAR DEM derivatives based on site characteristics to identify wetlands at a high resolution.

Nonlinear features for product inspection

NASA Astrophysics Data System (ADS)

Talukder, Ashit; Casasent, David P.

1999-03-01

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

Automated Decision Tree Classification of Corneal Shape

PubMed Central

Twa, Michael D.; Parthasarathy, Srinivasan; Roberts, Cynthia; Mahmoud, Ashraf M.; Raasch, Thomas W.; Bullimore, Mark A.

2011-01-01

Purpose The volume and complexity of data produced during videokeratography examinations present a challenge of interpretation. As a consequence, results are often analyzed qualitatively by subjective pattern recognition or reduced to comparisons of summary indices. We describe the application of decision tree induction, an automated machine learning classification method, to discriminate between normal and keratoconic corneal shapes in an objective and quantitative way. We then compared this method with other known classification methods. Methods The corneal surface was modeled with a seventh-order Zernike polynomial for 132 normal eyes of 92 subjects and 112 eyes of 71 subjects diagnosed with keratoconus. A decision tree classifier was induced using the C4.5 algorithm, and its classification performance was compared with the modified Rabinowitz–McDonnell index, Schwiegerling’s Z3 index (Z3), Keratoconus Prediction Index (KPI), KISA%, and Cone Location and Magnitude Index using recommended classification thresholds for each method. We also evaluated the area under the receiver operator characteristic (ROC) curve for each classification method. Results Our decision tree classifier performed equal to or better than the other classifiers tested: accuracy was 92% and the area under the ROC curve was 0.97. Our decision tree classifier reduced the information needed to distinguish between normal and keratoconus eyes using four of 36 Zernike polynomial coefficients. The four surface features selected as classification attributes by the decision tree method were inferior elevation, greater sagittal depth, oblique toricity, and trefoil. Conclusions Automated decision tree classification of corneal shape through Zernike polynomials is an accurate quantitative method of classification that is interpretable and can be generated from any instrument platform capable of raw elevation data output. This method of pattern classification is extendable to other classification problems. PMID:16357645

Virtual Reality Simulation for the Operating Room

PubMed Central

Gallagher, Anthony G.; Ritter, E Matt; Champion, Howard; Higgins, Gerald; Fried, Marvin P.; Moses, Gerald; Smith, C Daniel; Satava, Richard M.

2005-01-01

Summary Background Data: To inform surgeons about the practical issues to be considered for successful integration of virtual reality simulation into a surgical training program. The learning and practice of minimally invasive surgery (MIS) makes unique demands on surgical training programs. A decade ago Satava proposed virtual reality (VR) surgical simulation as a solution for this problem. Only recently have robust scientific studies supported that vision Methods: A review of the surgical education, human-factor, and psychology literature to identify important factors which will impinge on the successful integration of VR training into a surgical training program. Results: VR is more likely to be successful if it is systematically integrated into a well-thought-out education and training program which objectively assesses technical skills improvement proximate to the learning experience. Validated performance metrics should be relevant to the surgical task being trained but in general will require trainees to reach an objectively determined proficiency criterion, based on tightly defined metrics and perform at this level consistently. VR training is more likely to be successful if the training schedule takes place on an interval basis rather than massed into a short period of extensive practice. High-fidelity VR simulations will confer the greatest skills transfer to the in vivo surgical situation, but less expensive VR trainers will also lead to considerably improved skills generalizations. Conclusions: VR for improved performance of MIS is now a reality. However, VR is only a training tool that must be thoughtfully introduced into a surgical training curriculum for it to successfully improve surgical technical skills. PMID:15650649

39 CFR 3020.75 - Review.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 39 Postal Service 1 2010-07-01 2010-07-01 false Review. 3020.75 Section 3020.75 Postal Service POSTAL REGULATORY COMMISSION PERSONNEL PRODUCT LISTS Proposal of the Commission To Modify the Product Lists Described Within the Mail Classification Schedule § 3020.75 Review. The Commission shall review...

Ranking procedure for partial discriminant analysis

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

Beckman, R.J.; Johnson, M.E.

1981-09-01

A rank procedure developed by Broffitt, Randles, and Hogg (1976) is modified to control the conditional probability of misclassification given that classification has been attempted. This modification leads to a useful solution to the two-population partial discriminant analysis problem for even moderately sized training sets.

78 FR 20461 - Flumioxazin; Pesticide Tolerances

Federal Register 2010, 2011, 2012, 2013, 2014

2013-04-05

..., or pesticide manufacturer. The following list of North American Industrial Classification System... response to the notice of filing. Based upon review of the data supporting the petition, EPA has modified... drinking water and in residential settings, but does not include occupational exposure. Section 408(b)(2)(C...

76 FR 50898 - Metconazole; Pesticide Tolerances

Federal Register 2010, 2011, 2012, 2013, 2014

2011-08-17

.../oppefed1/models/water/index.htm . Based on the Pesticide Root Zone Model/Exposure Analysis Modeling System... affected. The North American Industrial Classification System (NAICS) codes have been provided to assist... supporting the petition, EPA has modified the levels at which tolerances are being established for the...

78 FR 25396 - Glyphosate; Pesticide Tolerances

Federal Register 2010, 2011, 2012, 2013, 2014

2013-05-01

.../water/index.htm . Based on the Pesticide Root Zone Model/Exposure Analysis Modeling System (PRZM/EXAMS.... The following list of North American Industrial Classification System (NAICS) codes is not intended to... the data supporting the petition, EPA has modified the levels at which tolerances are being...

Validation of the new diagnosis grouping system for pediatric emergency department visits using the International Classification of Diseases, 10th Revision.

PubMed

Lee, Jin Hee; Hong, Ki Jeong; Kim, Do Kyun; Kwak, Young Ho; Jang, Hye Young; Kim, Hahn Bom; Noh, Hyun; Park, Jungho; Song, Bongkyu; Jung, Jae Yun

2013-12-01

A clinically sensible diagnosis grouping system (DGS) is needed for describing pediatric emergency diagnoses for research, medical resource preparedness, and making national policy for pediatric emergency medical care. The Pediatric Emergency Care Applied Research Network (PECARN) developed the DGS successfully. We developed the modified PECARN DGS based on the different pediatric population of South Korea and validated the system to obtain the accurate and comparable epidemiologic data of pediatric emergent conditions of the selected population. The data source used to develop and validate the modified PECARN DGS was the National Emergency Department Information System of South Korea, which was coded by the International Classification of Diseases, 10th Revision (ICD-10) code system. To develop the modified DGS based on ICD-10 code, we matched the selected ICD-10 codes with those of the PECARN DGS by the General Equivalence Mappings (GEMs). After converting ICD-10 codes to ICD-9 codes by GEMs, we matched ICD-9 codes into PECARN DGS categories using the matrix developed by PECARN group. Lastly, we conducted the expert panel survey using Delphi method for the remaining diagnosis codes that were not matched. A total of 1879 ICD-10 codes were used in development of the modified DGS. After 1078 (57.4%) of 1879 ICD-10 codes were assigned to the modified DGS by GEM and PECARN conversion tools, investigators assigned each of the remaining 801 codes (42.6%) to DGS subgroups by 2 rounds of electronic Delphi surveys. And we assigned the remaining 29 codes (4%) into the modified DGS at the second expert consensus meeting. The modified DGS accounts for 98.7% and 95.2% of diagnoses of the 2008 and 2009 National Emergency Department Information System data set. This modified DGS also exhibited strong construct validity using the concepts of age, sex, site of care, and seasons. This also reflected the 2009 outbreak of H1N1 influenza in Korea. We developed and validated clinically feasible and sensible DGS system for describing pediatric emergent conditions in Korea. The modified PECARN DGS showed good comprehensiveness and demonstrated reliable construct validity. This modified DGS based on PECARN DGS framework may be effectively implemented for research, reporting, and resource planning in pediatric emergency system of South Korea.

A risk-based classification scheme for genetically modified foods. II: Graded testing.

PubMed

Chao, Eunice; Krewski, Daniel

2008-12-01

This paper presents a graded approach to the testing of crop-derived genetically modified (GM) foods based on concern levels in a proposed risk-based classification scheme (RBCS) and currently available testing methods. A graded approach offers the potential for more efficient use of testing resources by focusing less on lower concern GM foods, and more on higher concern foods. In this proposed approach to graded testing, products that are classified as Level I would have met baseline testing requirements that are comparable to what is widely applied to premarket assessment of GM foods at present. In most cases, Level I products would require no further testing, or very limited confirmatory analyses. For products classified as Level II or higher, additional testing would be required, depending on the type of the substance, prior dietary history, estimated exposure level, prior knowledge of toxicity of the substance, and the nature of the concern related to unintended changes in the modified food. Level III testing applies only to the assessment of toxic and antinutritional effects from intended changes and is tailored to the nature of the substance in question. Since appropriate test methods are not currently available for all effects of concern, future research to strengthen the testing of GM foods is discussed.

[Classification of local anesthesia methods].

PubMed

Petricas, A Zh; Medvedev, D V; Olkhovskaya, E B

The traditional classification methods of dental local anesthesia must be modified. In this paper we proved that the vascular mechanism is leading component of spongy injection. It is necessary to take into account the high effectiveness and relative safety of spongy anesthesia, as well as versatility, ease of implementation and the growing prevalence in the world. The essence of the proposed modification is to distinguish the methods in diffusive (including surface anesthesia, infiltration and conductive anesthesia) and vascular-diffusive (including intraosseous, intraligamentary, intraseptal and intrapulpal anesthesia). For the last four methods the common term «spongy (intraosseous) anesthesia» may be used.

Cupping artifact correction and automated classification for high-resolution dedicated breast CT images.

PubMed

Yang, Xiaofeng; Wu, Shengyong; Sechopoulos, Ioannis; Fei, Baowei

2012-10-01

To develop and test an automated algorithm to classify the different tissues present in dedicated breast CT images. The original CT images are first corrected to overcome cupping artifacts, and then a multiscale bilateral filter is used to reduce noise while keeping edge information on the images. As skin and glandular tissues have similar CT values on breast CT images, morphologic processing is used to identify the skin mask based on its position information. A modified fuzzy C-means (FCM) classification method is then used to classify breast tissue as fat and glandular tissue. By combining the results of the skin mask with the FCM, the breast tissue is classified as skin, fat, and glandular tissue. To evaluate the authors' classification method, the authors use Dice overlap ratios to compare the results of the automated classification to those obtained by manual segmentation on eight patient images. The correction method was able to correct the cupping artifacts and improve the quality of the breast CT images. For glandular tissue, the overlap ratios between the authors' automatic classification and manual segmentation were 91.6% ± 2.0%. A cupping artifact correction method and an automatic classification method were applied and evaluated for high-resolution dedicated breast CT images. Breast tissue classification can provide quantitative measurements regarding breast composition, density, and tissue distribution.

Cupping artifact correction and automated classification for high-resolution dedicated breast CT images

PubMed Central

Yang, Xiaofeng; Wu, Shengyong; Sechopoulos, Ioannis; Fei, Baowei

2012-01-01

Purpose: To develop and test an automated algorithm to classify the different tissues present in dedicated breast CT images. Methods: The original CT images are first corrected to overcome cupping artifacts, and then a multiscale bilateral filter is used to reduce noise while keeping edge information on the images. As skin and glandular tissues have similar CT values on breast CT images, morphologic processing is used to identify the skin mask based on its position information. A modified fuzzy C-means (FCM) classification method is then used to classify breast tissue as fat and glandular tissue. By combining the results of the skin mask with the FCM, the breast tissue is classified as skin, fat, and glandular tissue. To evaluate the authors’ classification method, the authors use Dice overlap ratios to compare the results of the automated classification to those obtained by manual segmentation on eight patient images. Results: The correction method was able to correct the cupping artifacts and improve the quality of the breast CT images. For glandular tissue, the overlap ratios between the authors’ automatic classification and manual segmentation were 91.6% ± 2.0%. Conclusions: A cupping artifact correction method and an automatic classification method were applied and evaluated for high-resolution dedicated breast CT images. Breast tissue classification can provide quantitative measurements regarding breast composition, density, and tissue distribution. PMID:23039675

77 FR 3617 - Etoxazole; Pesticide Tolerances

Federal Register 2010, 2011, 2012, 2013, 2014

2012-01-25

... affected. The North American Industrial Classification System (NAICS) codes have been provided to assist... the data supporting the petition, EPA has modified the levels at which some of the tolerances are... drinking water and in residential settings, but does not include occupational exposure. Section 408(b)(2)(C...

76 FR 18899 - Indaziflam; Pesticide Tolerances

Federal Register 2010, 2011, 2012, 2013, 2014

2011-04-06

... Model/Exposure Analysis Modeling System (PRZM/EXAMS) and Screening Concentration in Ground Water (SCI... Classification System (NAICS) codes have been provided to assist you and others in determining whether this... response to the notice of filing. Based upon review of the data supporting the petitions, EPA has modified...

Investigating the Effects of Higher Spatial Resolution on Benthic Classification Accuracy at Midway Atoll

DTIC Science & Technology

2008-09-01

2 X Components: 1 Y Components: 1 Product MBR Geographic Coordinates Number of Coordinates: 4 Coordinate: 1 Latitude...bottom (other than live coral) bldgs., docks, etc.) 4. linear reef- B. SHORELINE -INTERTIDAL modifiers 5. pinnacle reef- c. submerged vegetation- sand

Supramolecular structure of polymer binders and composites: targeted control based on the hierarchy

NASA Astrophysics Data System (ADS)

Matveeva, Larisa; Belentsov, Yuri

2017-10-01

The article discusses the problem of targeted control over properties by modifying the supramolecular structure of polymer binders and composites based on their hierarchy. Control over the structure formation of polymers and introduction of modifying additives should be tailored to the specific hierarchical structural levels. Characteristics of polymer materials are associated with structural defects, which also display a hierarchical pattern. Classification of structural defects in polymers is presented. The primary structural level (nano level) of supramolecular formations is of great importance to the reinforcement and regulation of strength characteristics.

Modified DCTNet for audio signals classification

NASA Astrophysics Data System (ADS)

Xian, Yin; Pu, Yunchen; Gan, Zhe; Lu, Liang; Thompson, Andrew

2016-10-01

In this paper, we investigate DCTNet for audio signal classification. Its output feature is related to Cohen's class of time-frequency distributions. We introduce the use of adaptive DCTNet (A-DCTNet) for audio signals feature extraction. The A-DCTNet applies the idea of constant-Q transform, with its center frequencies of filterbanks geometrically spaced. The A-DCTNet is adaptive to different acoustic scales, and it can better capture low frequency acoustic information that is sensitive to human audio perception than features such as Mel-frequency spectral coefficients (MFSC). We use features extracted by the A-DCTNet as input for classifiers. Experimental results show that the A-DCTNet and Recurrent Neural Networks (RNN) achieve state-of-the-art performance in bird song classification rate, and improve artist identification accuracy in music data. They demonstrate A-DCTNet's applicability to signal processing problems.

Case definition and classification of leukodystrophies and leukoencephalopathies.

PubMed

Vanderver, Adeline; Prust, Morgan; Tonduti, Davide; Mochel, Fanny; Hussey, Heather M; Helman, Guy; Garbern, James; Eichler, Florian; Labauge, Pierre; Aubourg, Patrick; Rodriguez, Diana; Patterson, Marc C; Van Hove, Johan L K; Schmidt, Johanna; Wolf, Nicole I; Boespflug-Tanguy, Odile; Schiffmann, Raphael; van der Knaap, Marjo S

2015-04-01

An approved definition of the term leukodystrophy does not currently exist. The lack of a precise case definition hampers efforts to study the epidemiology and the relevance of genetic white matter disorders to public health. Thirteen experts at multiple institutions participated in iterative consensus building surveys to achieve definition and classification of disorders as leukodystrophies using a modified Delphi approach. A case definition for the leukodystrophies was achieved, and a total of 30 disorders were classified under this definition. In addition, a separate set of disorders with heritable white matter abnormalities but not meeting criteria for leukodystrophy, due to presumed primary neuronal involvement and prominent systemic manifestations, was classified as genetic leukoencephalopathies (gLE). A case definition of leukodystrophies and classification of heritable white matter disorders will permit more detailed epidemiologic studies of these disorders. Copyright © 2015 Elsevier Inc. All rights reserved.

28 CFR 524.23 - Program reviews.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 28 Judicial Administration 2 2010-07-01 2010-07-01 false Program reviews. 524.23 Section 524.23... TRANSFER CLASSIFICATION OF INMATES Youth Corrections Act (YCA) Programs § 524.23 Program reviews. Staff shall conduct periodic reviews of the inmate's program plan and shall modify the plan in accordance with...

The Use of Tactile Cues to Modify the Perception of Self-Motion

DTIC Science & Technology

2008-12-01

SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT UU 18. NUMBER OF PAGES 6 19a. NAME OF RESPONSIBLE PERSON a. REPORT unclassified b...fills the subject’s entire field- of-view provides a strong vection stimulus. Horizontal eye movements were monitored with electrooculography ( EOG

76 FR 56635 - Tuberculosis in Cattle and Bison; State and Zone Designations; Michigan

Federal Register 2010, 2011, 2012, 2013, 2014

2011-09-14

..., modified accredited advanced, and accredited-free tuberculosis risk classification zones for the State of... status now meet our requirements for accredited-free status. In addition, Iosco and Ogemaw Counties, of... advanced, now meet the requirements for accredited-free status. We also have determined that Presque Isle...

78 FR 77377 - Small Business Investment Companies-Investments in Passive Businesses

Federal Register 2010, 2011, 2012, 2013, 2014

2013-12-23

..., each of which must be a non-passive small business. The proposed rule would modify this exception to.... This modification would place SBICs on an equal footing with their non-SBIC counterparts in the venture... their equivalents under the North American Industrial Classification System (NAICS); correct erroneous...

Browsing Your Virtual Library: The Case of Expanding Universe.

ERIC Educational Resources Information Center

Daniels, Wayne; Enright, Jeanne; Mackenzie, Scott

1997-01-01

Describes "Expanding Universe: a classified search tool for amateur astronomy," a Web site maintained by the Metropolitan Toronto Reference Library which uses a modified form of the Dewey Decimal Classification to organize a large file of astronomy hotlinks. Highlights include structure, HTML coding, design requirements, and future…

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

Carbohydrate terminology and classification.

PubMed

Cummings, J H; Stephen, A M

2007-12-01

Dietary carbohydrates are a group of chemically defined substances with a range of physical and physiological properties and health benefits. As with other macronutrients, the primary classification of dietary carbohydrate is based on chemistry, that is character of individual monomers, degree of polymerization (DP) and type of linkage (alpha or beta), as agreed at the Food and Agriculture Organization/World Health Organization Expert Consultation in 1997. This divides carbohydrates into three main groups, sugars (DP 1-2), oligosaccharides (short-chain carbohydrates) (DP 3-9) and polysaccharides (DP> or =10). Within this classification, a number of terms are used such as mono- and disaccharides, polyols, oligosaccharides, starch, modified starch, non-starch polysaccharides, total carbohydrate, sugars, etc. While effects of carbohydrates are ultimately related to their primary chemistry, they are modified by their physical properties. These include water solubility, hydration, gel formation, crystalline state, association with other molecules such as protein, lipid and divalent cations and aggregation into complex structures in cell walls and other specialized plant tissues. A classification based on chemistry is essential for a system of measurement, predication of properties and estimation of intakes, but does not allow a simple translation into nutritional effects since each class of carbohydrate has overlapping physiological properties and effects on health. This dichotomy has led to the use of a number of terms to describe carbohydrate in foods, for example intrinsic and extrinsic sugars, prebiotic, resistant starch, dietary fibre, available and unavailable carbohydrate, complex carbohydrate, glycaemic and whole grain. This paper reviews these terms and suggests that some are more useful than others. A clearer understanding of what is meant by any particular word used to describe carbohydrate is essential to progress in translating the growing knowledge of the physiological properties of carbohydrate into public health messages.

A proposed radiographic classification scheme for congenital thoracic vertebral malformations in brachycephalic "screw-tailed" dog breeds.

PubMed

Gutierrez-Quintana, Rodrigo; Guevar, Julien; Stalin, Catherine; Faller, Kiterie; Yeamans, Carmen; Penderis, Jacques

2014-01-01

Congenital vertebral malformations are common in brachycephalic "screw-tailed" dog breeds such as French bulldogs, English bulldogs, Boston terriers, and pugs. The aim of this retrospective study was to determine whether a radiographic classification scheme developed for use in humans would be feasible for use in these dog breeds. Inclusion criteria were hospital admission between September 2009 and April 2013, neurologic examination findings available, diagnostic quality lateral and ventro-dorsal digital radiographs of the thoracic vertebral column, and at least one congenital vertebral malformation. Radiographs were retrieved and interpreted by two observers who were unaware of neurologic status. Vertebral malformations were classified based on a classification scheme modified from a previous human study and a consensus of both observers. Twenty-eight dogs met inclusion criteria (12 with neurologic deficits, 16 with no neurologic deficits). Congenital vertebral malformations affected 85/362 (23.5%) of thoracic vertebrae. Vertebral body formation defects were the most common (butterfly vertebrae 6.6%, ventral wedge-shaped vertebrae 5.5%, dorsal hemivertebrae 0.8%, and dorso-lateral hemivertebrae 0.5%). No lateral hemivertebrae or lateral wedge-shaped vertebrae were identified. The T7 vertebra was the most commonly affected (11/28 dogs), followed by T8 (8/28 dogs) and T12 (8/28 dogs). The number and type of vertebral malformations differed between groups (P = 0.01). Based on MRI, dorsal, and dorso-lateral hemivertebrae were the cause of spinal cord compression in 5/12 (41.6%) of dogs with neurologic deficits. Findings indicated that a modified human radiographic classification system of vertebral malformations is feasible for use in future studies of brachycephalic "screw-tailed" dogs. © 2014 American College of Veterinary Radiology.

EXhype: A tool for mineral classification using hyperspectral data

NASA Astrophysics Data System (ADS)

Adep, Ramesh Nityanand; shetty, Amba; Ramesh, H.

2017-02-01

Various supervised classification algorithms have been developed to classify earth surface features using hyperspectral data. Each algorithm is modelled based on different human expertises. However, the performance of conventional algorithms is not satisfactory to map especially the minerals in view of their typical spectral responses. This study introduces a new expert system named 'EXhype (Expert system for hyperspectral data classification)' to map minerals. The system incorporates human expertise at several stages of it's implementation: (i) to deal with intra-class variation; (ii) to identify absorption features; (iii) to discriminate spectra by considering absorption features, non-absorption features and by full spectra comparison; and (iv) finally takes a decision based on learning and by emphasizing most important features. It is developed using a knowledge base consisting of an Optimal Spectral Library, Segmented Upper Hull method, Spectral Angle Mapper (SAM) and Artificial Neural Network. The performance of the EXhype is compared with a traditional, most commonly used SAM algorithm using Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data acquired over Cuprite, Nevada, USA. A virtual verification method is used to collect samples information for accuracy assessment. Further, a modified accuracy assessment method is used to get a real users accuracies in cases where only limited or desired classes are considered for classification. With the modified accuracy assessment method, SAM and EXhype yields an overall accuracy of 60.35% and 90.75% and the kappa coefficient of 0.51 and 0.89 respectively. It was also found that the virtual verification method allows to use most desired stratified random sampling method and eliminates all the difficulties associated with it. The experimental results show that EXhype is not only producing better accuracy compared to traditional SAM but, can also rightly classify the minerals. It is proficient in avoiding misclassification between target classes when applied on minerals.

An Efficient Optimization Method for Solving Unsupervised Data Classification Problems.

PubMed

Shabanzadeh, Parvaneh; Yusof, Rubiyah

2015-01-01

Unsupervised data classification (or clustering) analysis is one of the most useful tools and a descriptive task in data mining that seeks to classify homogeneous groups of objects based on similarity and is used in many medical disciplines and various applications. In general, there is no single algorithm that is suitable for all types of data, conditions, and applications. Each algorithm has its own advantages, limitations, and deficiencies. Hence, research for novel and effective approaches for unsupervised data classification is still active. In this paper a heuristic algorithm, Biogeography-Based Optimization (BBO) algorithm, was adapted for data clustering problems by modifying the main operators of BBO algorithm, which is inspired from the natural biogeography distribution of different species. Similar to other population-based algorithms, BBO algorithm starts with an initial population of candidate solutions to an optimization problem and an objective function that is calculated for them. To evaluate the performance of the proposed algorithm assessment was carried on six medical and real life datasets and was compared with eight well known and recent unsupervised data classification algorithms. Numerical results demonstrate that the proposed evolutionary optimization algorithm is efficient for unsupervised data classification.

Classification of driving workload affected by highway alignment conditions based on classification and regression tree algorithm.

PubMed

Hu, Jiangbi; Wang, Ronghua

2018-02-17

Guaranteeing a safe and comfortable driving workload can contribute to reducing traffic injuries. In order to provide safe and comfortable threshold values, this study attempted to classify driving workload from the aspects of human factors mainly affected by highway geometric conditions and to determine the thresholds of different workload classifications. This article stated a hypothesis that the values of driver workload change within a certain range. Driving workload scales were stated based on a comprehensive literature review. Through comparative analysis of different psychophysiological measures, heart rate variability (HRV) was chosen as the representative measure for quantifying driving workload by field experiments. Seventy-two participants (36 car drivers and 36 large truck drivers) and 6 highways with different geometric designs were selected to conduct field experiments. A wearable wireless dynamic multiparameter physiological detector (KF-2) was employed to detect physiological data that were simultaneously correlated to the speed changes recorded by a Global Positioning System (GPS) (testing time, driving speeds, running track, and distance). Through performing statistical analyses, including the distribution of HRV during the flat, straight segments and P-P plots of modified HRV, a driving workload calculation model was proposed. Integrating driving workload scales with values, the threshold of each scale of driving workload was determined by classification and regression tree (CART) algorithms. The driving workload calculation model was suitable for driving speeds in the range of 40 to 120 km/h. The experimental data of 72 participants revealed that driving workload had a significant effect on modified HRV, revealing a change in driving speed. When the driving speed was between 100 and 120 km/h, drivers showed an apparent increase in the corresponding modified HRV. The threshold value of the normal driving workload K was between -0.0011 and 0.056 for a car driver and between -0.00086 and 0.067 for a truck driver. Heart rate variability was a direct and effective index for measuring driving workload despite being affected by multiple highway alignment elements. The driving workload model and the thresholds of driving workload classifications can be used to evaluate the quality of highway geometric design. A higher quality of highway geometric design could keep driving workload within a safer and more comfortable range. This study provided insight into reducing traffic injuries from the perspective of disciplinary integration of highway engineering and human factor engineering.

Fully Convolutional Networks for Ground Classification from LIDAR Point Clouds

NASA Astrophysics Data System (ADS)

Rizaldy, A.; Persello, C.; Gevaert, C. M.; Oude Elberink, S. J.

2018-05-01

Deep Learning has been massively used for image classification in recent years. The use of deep learning for ground classification from LIDAR point clouds has also been recently studied. However, point clouds need to be converted into an image in order to use Convolutional Neural Networks (CNNs). In state-of-the-art techniques, this conversion is slow because each point is converted into a separate image. This approach leads to highly redundant computation during conversion and classification. The goal of this study is to design a more efficient data conversion and ground classification. This goal is achieved by first converting the whole point cloud into a single image. The classification is then performed by a Fully Convolutional Network (FCN), a modified version of CNN designed for pixel-wise image classification. The proposed method is significantly faster than state-of-the-art techniques. On the ISPRS Filter Test dataset, it is 78 times faster for conversion and 16 times faster for classification. Our experimental analysis on the same dataset shows that the proposed method results in 5.22 % of total error, 4.10 % of type I error, and 15.07 % of type II error. Compared to the previous CNN-based technique and LAStools software, the proposed method reduces the total error and type I error (while type II error is slightly higher). The method was also tested on a very high point density LIDAR point clouds resulting in 4.02 % of total error, 2.15 % of type I error and 6.14 % of type II error.

Classification bias in commercial business lists for retail food stores in the U.S.

PubMed

Han, Euna; Powell, Lisa M; Zenk, Shannon N; Rimkus, Leah; Ohri-Vachaspati, Punam; Chaloupka, Frank J

2012-04-18

Aspects of the food environment such as the availability of different types of food stores have recently emerged as key modifiable factors that may contribute to the increased prevalence of obesity. Given that many of these studies have derived their results based on secondary datasets and the relationship of food stores with individual weight outcomes has been reported to vary by store type, it is important to understand the extent to which often-used secondary data correctly classify food stores. We evaluated the classification bias of food stores in Dun & Bradstreet (D&B) and InfoUSA commercial business lists. We performed a full census in 274 randomly selected census tracts in the Chicago metropolitan area and collected detailed store attributes inside stores for classification. Store attributes were compared by classification match status and store type. Systematic classification bias by census tract characteristics was assessed in multivariate regression. D&B had a higher classification match rate than InfoUSA for supermarkets and grocery stores, while InfoUSA was higher for convenience stores. Both lists were more likely to correctly classify large supermarkets, grocery stores, and convenience stores with more cash registers and different types of service counters (supermarkets and grocery stores only). The likelihood of a correct classification match for supermarkets and grocery stores did not vary systemically by tract characteristics whereas convenience stores were more likely to be misclassified in predominately Black tracts. Researches can rely on classification of food stores in commercial datasets for supermarkets and grocery stores whereas classifications for convenience and specialty food stores are subject to some systematic bias by neighborhood racial/ethnic composition.

Classification bias in commercial business lists for retail food stores in the U.S.

PubMed Central

2012-01-01

Background Aspects of the food environment such as the availability of different types of food stores have recently emerged as key modifiable factors that may contribute to the increased prevalence of obesity. Given that many of these studies have derived their results based on secondary datasets and the relationship of food stores with individual weight outcomes has been reported to vary by store type, it is important to understand the extent to which often-used secondary data correctly classify food stores. We evaluated the classification bias of food stores in Dun & Bradstreet (D&B) and InfoUSA commercial business lists. Methods We performed a full census in 274 randomly selected census tracts in the Chicago metropolitan area and collected detailed store attributes inside stores for classification. Store attributes were compared by classification match status and store type. Systematic classification bias by census tract characteristics was assessed in multivariate regression. Results D&B had a higher classification match rate than InfoUSA for supermarkets and grocery stores, while InfoUSA was higher for convenience stores. Both lists were more likely to correctly classify large supermarkets, grocery stores, and convenience stores with more cash registers and different types of service counters (supermarkets and grocery stores only). The likelihood of a correct classification match for supermarkets and grocery stores did not vary systemically by tract characteristics whereas convenience stores were more likely to be misclassified in predominately Black tracts. Conclusion Researches can rely on classification of food stores in commercial datasets for supermarkets and grocery stores whereas classifications for convenience and specialty food stores are subject to some systematic bias by neighborhood racial/ethnic composition. PMID:22512874

3D Target Localization of Modified 3D MUSIC for a Triple-Channel K-Band Radar.

PubMed

Li, Ying-Chun; Choi, Byunggil; Chong, Jong-Wha; Oh, Daegun

2018-05-20

In this paper, a modified 3D multiple signal classification (MUSIC) algorithm is proposed for joint estimation of range, azimuth, and elevation angles of K-band radar with a small 2 × 2 horn antenna array. Three channels of the 2 × 2 horn antenna array are utilized as receiving channels, and the other one is a transmitting antenna. The proposed modified 3D MUSIC is designed to make use of a stacked autocorrelation matrix, whose element matrices are related to each other in the spatial domain. An augmented 2D steering vector based on the stacked autocorrelation matrix is proposed for the modified 3D MUSIC, instead of the conventional 3D steering vector. The effectiveness of the proposed modified 3D MUSIC is verified through implementation with a K-band frequency-modulated continuous-wave (FMCW) radar with the 2 × 2 horn antenna array through a variety of experiments in a chamber.

Framewise phoneme classification with bidirectional LSTM and other neural network architectures.

PubMed

Graves, Alex; Schmidhuber, Jürgen

2005-01-01

In this paper, we present bidirectional Long Short Term Memory (LSTM) networks, and a modified, full gradient version of the LSTM learning algorithm. We evaluate Bidirectional LSTM (BLSTM) and several other network architectures on the benchmark task of framewise phoneme classification, using the TIMIT database. Our main findings are that bidirectional networks outperform unidirectional ones, and Long Short Term Memory (LSTM) is much faster and also more accurate than both standard Recurrent Neural Nets (RNNs) and time-windowed Multilayer Perceptrons (MLPs). Our results support the view that contextual information is crucial to speech processing, and suggest that BLSTM is an effective architecture with which to exploit it.

Primate immunodeficiency virus classification and nomenclature: Review

DOE PAGES

Foley, Brian T.; Leitner, Thomas; Paraskevis, Dimitrios; ...

2016-10-24

The International Committee for the Taxonomy and Nomenclature of Viruses does not rule on virus classifications below the species level. The definition of species for viruses cannot be clearly defined for all types of viruses. The complex and interesting epidemiology of Human Immunodeficiency Viruses demands a detailed and informative nomenclature system, while at the same time it presents challenges such that many of the rules need to be flexibly applied or modified over time. As a result, this review outlines the nomenclature system for primate lentiviruses and provides an update on new findings since the last review was written inmore » 2000.« less

Optimization of Support Vector Machine (SVM) for Object Classification

NASA Technical Reports Server (NTRS)

Scholten, Matthew; Dhingra, Neil; Lu, Thomas T.; Chao, Tien-Hsin

2012-01-01

The Support Vector Machine (SVM) is a powerful algorithm, useful in classifying data into species. The SVMs implemented in this research were used as classifiers for the final stage in a Multistage Automatic Target Recognition (ATR) system. A single kernel SVM known as SVMlight, and a modified version known as a SVM with K-Means Clustering were used. These SVM algorithms were tested as classifiers under varying conditions. Image noise levels varied, and the orientation of the targets changed. The classifiers were then optimized to demonstrate their maximum potential as classifiers. Results demonstrate the reliability of SVM as a method for classification. From trial to trial, SVM produces consistent results.

[The psychosomatics of chronic back pain. Classification, aetiology and therapy].

PubMed

Henningsen, P

2004-05-01

An overview is given on the current classification, description and treatment of chronic pain with causally relevant psychological factors. It is based on the "practice guidelines on somatoform disorders" and on a thematically related meta-analysis. The classificatory problems, especially of the demarcation of somatoform and other chronic pain, are presented. Additional descriptive dimensions of the relevant psychosocial factors are: pain description, other organically unexplained pain- and non-pain-symptoms, anxiety and depression, disease conviction and illness behaviour, personality and childhood abuse. A modified psychotherapy for (somatoform) chronic pain is outlined. Finally, this aetiologically oriented psychosomatic-psychiatric approach is compared to psychological coping models for chronic pain.

Towards an International Classification for Patient Safety: the conceptual framework.

PubMed

Sherman, Heather; Castro, Gerard; Fletcher, Martin; Hatlie, Martin; Hibbert, Peter; Jakob, Robert; Koss, Richard; Lewalle, Pierre; Loeb, Jerod; Perneger, Thomas; Runciman, William; Thomson, Richard; Van Der Schaaf, Tjerk; Virtanen, Martti

2009-02-01

Global advances in patient safety have been hampered by the lack of a uniform classification of patient safety concepts. This is a significant barrier to developing strategies to reduce risk, performing evidence-based research and evaluating existing healthcare policies relevant to patient safety. Since 2005, the World Health Organization's World Alliance for Patient Safety has undertaken the Project to Develop an International Classification for Patient Safety (ICPS) to devise a classification which transforms patient safety information collected from disparate systems into a common format to facilitate aggregation, analysis and learning across disciplines, borders and time. A drafting group, comprised of experts from the fields of patient safety, classification theory, health informatics, consumer/patient advocacy, law and medicine, identified and defined key patient safety concepts and developed an internationally agreed conceptual framework for the ICPS based upon existing patient safety classifications. The conceptual framework was iteratively improved through technical expert meetings and a two-stage web-based modified Delphi survey of over 250 international experts. This work culminated in a conceptual framework consisting of ten high level classes: incident type, patient outcomes, patient characteristics, incident characteristics, contributing factors/hazards, organizational outcomes, detection, mitigating factors, ameliorating actions and actions taken to reduce risk. While the framework for the ICPS is in place, several challenges remain. Concepts need to be defined, guidance for using the classification needs to be provided, and further real-world testing needs to occur to progressively refine the ICPS to ensure it is fit for purpose.

Towards an International Classification for Patient Safety: the conceptual framework

PubMed Central

Sherman, Heather; Castro, Gerard; Fletcher, Martin; Hatlie, Martin; Hibbert, Peter; Jakob, Robert; Koss, Richard; Lewalle, Pierre; Loeb, Jerod; Perneger, Thomas; Runciman, William; Thomson, Richard; Van Der Schaaf, Tjerk; Virtanen, Martti

2009-01-01

Global advances in patient safety have been hampered by the lack of a uniform classification of patient safety concepts. This is a significant barrier to developing strategies to reduce risk, performing evidence-based research and evaluating existing healthcare policies relevant to patient safety. Since 2005, the World Health Organization's World Alliance for Patient Safety has undertaken the Project to Develop an International Classification for Patient Safety (ICPS) to devise a classification which transforms patient safety information collected from disparate systems into a common format to facilitate aggregation, analysis and learning across disciplines, borders and time. A drafting group, comprised of experts from the fields of patient safety, classification theory, health informatics, consumer/patient advocacy, law and medicine, identified and defined key patient safety concepts and developed an internationally agreed conceptual framework for the ICPS based upon existing patient safety classifications. The conceptual framework was iteratively improved through technical expert meetings and a two-stage web-based modified Delphi survey of over 250 international experts. This work culminated in a conceptual framework consisting of ten high level classes: incident type, patient outcomes, patient characteristics, incident characteristics, contributing factors/hazards, organizational outcomes, detection, mitigating factors, ameliorating actions and actions taken to reduce risk. While the framework for the ICPS is in place, several challenges remain. Concepts need to be defined, guidance for using the classification needs to be provided, and further real-world testing needs to occur to progressively refine the ICPS to ensure it is fit for purpose. PMID:19147595

Reformulation of Traditional Chamomile Oil: Quality Controls and Fingerprint Presentation Based on Cluster Analysis of Attenuated Total Reflectance–Infrared Spectral Data

PubMed Central

Sakhteman, Amirhossein; Faridi, Pouya; Daneshamouz, Saeid; Akbarizadeh, Amin Reza; Borhani-Haghighi, Afshin; Mohagheghzadeh, Abdolali

2017-01-01

Herbal oils have been widely used in Iran as medicinal compounds dating back to thousands of years in Iran. Chamomile oil is widely used as an example of traditional oil. We remade chamomile oils and tried to modify it with current knowledge and facilities. Six types of oil (traditional and modified) were prepared. Microbial limit tests and physicochemical tests were performed on them. Also, principal component analysis, hierarchical cluster analysis, and partial least squares discriminant analysis were done on the spectral data of attenuated total reflectance–infrared in order to obtain insight based on classification pattern of the samples. The results show that we can use modified versions of the chamomile oils (modified Clevenger-type apparatus method and microwave method) with the same content of traditional ones and with less microbial contaminations and better physicochemical properties. PMID:28585466

Reformulation of Traditional Chamomile Oil: Quality Controls and Fingerprint Presentation Based on Cluster Analysis of Attenuated Total Reflectance-Infrared Spectral Data.

PubMed

Zargaran, Arman; Sakhteman, Amirhossein; Faridi, Pouya; Daneshamouz, Saeid; Akbarizadeh, Amin Reza; Borhani-Haghighi, Afshin; Mohagheghzadeh, Abdolali

2017-10-01

Herbal oils have been widely used in Iran as medicinal compounds dating back to thousands of years in Iran. Chamomile oil is widely used as an example of traditional oil. We remade chamomile oils and tried to modify it with current knowledge and facilities. Six types of oil (traditional and modified) were prepared. Microbial limit tests and physicochemical tests were performed on them. Also, principal component analysis, hierarchical cluster analysis, and partial least squares discriminant analysis were done on the spectral data of attenuated total reflectance-infrared in order to obtain insight based on classification pattern of the samples. The results show that we can use modified versions of the chamomile oils (modified Clevenger-type apparatus method and microwave method) with the same content of traditional ones and with less microbial contaminations and better physicochemical properties.

Molecular diagnostics in the management of rhabdomyosarcoma.

PubMed

Arnold, Michael A; Barr, Fredric G

2017-02-01

A classification of rhabdomyosarcoma (RMS) with prognostic relevance has primarily relied on clinical features and histologic classification as either embryonal or alveolar RMS. The PAX3-FOXO1 and PAX7-FOXO1 gene fusions occur in 80% of cases with the alveolar subtype and are more predictive of outcome than histologic classification. Identifying additional molecular hallmarks that further subclassify RMS is an active area of research. Areas Covered: The authors review the current state of the PAX3-FOXO1 and PAX7-FOXO1 fusions as prognostic biomarkers. Emerging biomarkers, including mRNA expression profiling, MYOD1 mutations, RAS pathway mutations and gene fusions involving NCOA2 or VGLL2 are also reviewed. Expert commentary: Strategies for modifying RMS risk stratification based on molecular biomarkers are emerging with the potential to transform the clinical management of RMS, ultimately improving patient outcomes by tailoring therapy to predicted patient risk and identifying targets for novel therapies.

[Therapeutic strategy for different types of epicanthus].

PubMed

Gaofeng, Li; Jun, Tan; Zihan, Wu; Wei, Ding; Huawei, Ouyang; Fan, Zhang; Mingcan, Luo

2015-11-01

To explore the reasonable therapeutic strategy for different types of epicanthus. Patients with epicanthus were classificated according to the shape, extent and inner canthal distance and treated with different methods appropriately. Modified asymmetric Z plasty with two curve method was used in lower eyelid type epicanthus, inner canthus type epicanthus and severe upper eyelid type epicanthus. Moderate upper epicanthus underwent '-' shape method. Mild Upper epicanthus in two conditions which underwent nasal augumentation and double eyelid formation with normal inner canthal distance need no correction surgery. The other mild epicanthus underwent '-' shape method. A total of 66 cases underwent the classification and the appropriate treatment. All wounds healed well. During 3 to 12 months follow-up period, all epicanthus were corrected completely with natural contour and unconspicuous scars. All patients were satisfied with the results. Classification of epicanthus hosed on the shape, extent and inner canthal distance and correction with appropriate methods is a reasonable therapeutic strategy.

Classification of Company Performance using Weighted Probabilistic Neural Network

NASA Astrophysics Data System (ADS)

Yasin, Hasbi; Waridi Basyiruddin Arifin, Adi; Warsito, Budi

2018-05-01

Classification of company performance can be judged by looking at its financial status, whether good or bad state. Classification of company performance can be achieved by some approach, either parametric or non-parametric. Neural Network is one of non-parametric methods. One of Artificial Neural Network (ANN) models is Probabilistic Neural Network (PNN). PNN consists of four layers, i.e. input layer, pattern layer, addition layer, and output layer. The distance function used is the euclidean distance and each class share the same values as their weights. In this study used PNN that has been modified on the weighting process between the pattern layer and the addition layer by involving the calculation of the mahalanobis distance. This model is called the Weighted Probabilistic Neural Network (WPNN). The results show that the company's performance modeling with the WPNN model has a very high accuracy that reaches 100%.

Estimating the concordance probability in a survival analysis with a discrete number of risk groups.

PubMed

Heller, Glenn; Mo, Qianxing

2016-04-01

A clinical risk classification system is an important component of a treatment decision algorithm. A measure used to assess the strength of a risk classification system is discrimination, and when the outcome is survival time, the most commonly applied global measure of discrimination is the concordance probability. The concordance probability represents the pairwise probability of lower patient risk given longer survival time. The c-index and the concordance probability estimate have been used to estimate the concordance probability when patient-specific risk scores are continuous. In the current paper, the concordance probability estimate and an inverse probability censoring weighted c-index are modified to account for discrete risk scores. Simulations are generated to assess the finite sample properties of the concordance probability estimate and the weighted c-index. An application of these measures of discriminatory power to a metastatic prostate cancer risk classification system is examined.

Classification of Traffic Related Short Texts to Analyse Road Problems in Urban Areas

NASA Astrophysics Data System (ADS)

Saldana-Perez, A. M. M.; Moreno-Ibarra, M.; Tores-Ruiz, M.

2017-09-01

The Volunteer Geographic Information (VGI) can be used to understand the urban dynamics. In the classification of traffic related short texts to analyze road problems in urban areas, a VGI data analysis is done over a social media's publications, in order to classify traffic events at big cities that modify the movement of vehicles and people through the roads, such as car accidents, traffic and closures. The classification of traffic events described in short texts is done by applying a supervised machine learning algorithm. In the approach users are considered as sensors which describe their surroundings and provide their geographic position at the social network. The posts are treated by a text mining process and classified into five groups. Finally, the classified events are grouped in a data corpus and geo-visualized in the study area, to detect the places with more vehicular problems.

Human Error Assessment and Reduction Technique (HEART) and Human Factor Analysis and Classification System (HFACS)

NASA Technical Reports Server (NTRS)

Alexander, Tiffaney Miller

2017-01-01

Research results have shown that more than half of aviation, aerospace and aeronautics mishaps incidents are attributed to human error. As a part of Safety within space exploration ground processing operations, the identification and/or classification of underlying contributors and causes of human error must be identified, in order to manage human error. This research provides a framework and methodology using the Human Error Assessment and Reduction Technique (HEART) and Human Factor Analysis and Classification System (HFACS), as an analysis tool to identify contributing factors, their impact on human error events, and predict the Human Error probabilities (HEPs) of future occurrences. This research methodology was applied (retrospectively) to six (6) NASA ground processing operations scenarios and thirty (30) years of Launch Vehicle related mishap data. This modifiable framework can be used and followed by other space and similar complex operations.

Human Error Assessment and Reduction Technique (HEART) and Human Factor Analysis and Classification System (HFACS)

NASA Technical Reports Server (NTRS)

Alexander, Tiffaney Miller

2017-01-01

Research results have shown that more than half of aviation, aerospace and aeronautics mishaps/incidents are attributed to human error. As a part of Safety within space exploration ground processing operations, the identification and/or classification of underlying contributors and causes of human error must be identified, in order to manage human error. This research provides a framework and methodology using the Human Error Assessment and Reduction Technique (HEART) and Human Factor Analysis and Classification System (HFACS), as an analysis tool to identify contributing factors, their impact on human error events, and predict the Human Error probabilities (HEPs) of future occurrences. This research methodology was applied (retrospectively) to six (6) NASA ground processing operations scenarios and thirty (30) years of Launch Vehicle related mishap data. This modifiable framework can be used and followed by other space and similar complex operations.

Human Error Assessment and Reduction Technique (HEART) and Human Factor Analysis and Classification System (HFACS)

NASA Technical Reports Server (NTRS)

Alexander, Tiffaney Miller

2017-01-01

Research results have shown that more than half of aviation, aerospace and aeronautics mishaps incidents are attributed to human error. As a part of Quality within space exploration ground processing operations, the identification and or classification of underlying contributors and causes of human error must be identified, in order to manage human error.This presentation will provide a framework and methodology using the Human Error Assessment and Reduction Technique (HEART) and Human Factor Analysis and Classification System (HFACS), as an analysis tool to identify contributing factors, their impact on human error events, and predict the Human Error probabilities (HEPs) of future occurrences. This research methodology was applied (retrospectively) to six (6) NASA ground processing operations scenarios and thirty (30) years of Launch Vehicle related mishap data. This modifiable framework can be used and followed by other space and similar complex operations.

[Gastroenterology in the G-DRG-System 2004].

PubMed

Bunzemeier, H; Frühmorgen, P; Caspary, W F; Roeder, N

2003-11-01

After a year of preliminary voluntarily introduction of casemix funding in hospitals in 2003 nearly every German hospital will be confronted with lump sump payments on the basis of the G-DRG system for their inpatient care starting from January 2004. To analyse weaknesses referring to gastroenterology services within the G-DRG version 1.0 the German Association for Disorders of the Digestive System and Metabolism (DGVS) and the DRG-Research-Group from the University of Muenster conducted a DRG evaluation project. In the analysis patient data from 16 hospitals were included. As a result of the project recommendations for G-DRG adjustments were generated. Those recommendations were implemented in the advancement to G-DRG version 2004. Also the International Classification of Diseases (ICD-10) was modified to ICD-10 German Modification. The classification of procedures OPS-301 was revised. The main adjustments to the G-DRG system and both classifications will be presented in this paper.

Rule groupings in expert systems using nearest neighbour decision rules, and convex hulls

NASA Technical Reports Server (NTRS)

Anastasiadis, Stergios

1991-01-01

Expert System shells are lacking in many areas of software engineering. Large rule based systems are not semantically comprehensible, difficult to debug, and impossible to modify or validate. Partitioning a set of rules found in CLIPS (C Language Integrated Production System) into groups of rules which reflect the underlying semantic subdomains of the problem, will address adequately the concerns stated above. Techniques are introduced to structure a CLIPS rule base into groups of rules that inherently have common semantic information. The concepts involved are imported from the field of A.I., Pattern Recognition, and Statistical Inference. Techniques focus on the areas of feature selection, classification, and a criteria of how 'good' the classification technique is, based on Bayesian Decision Theory. A variety of distance metrics are discussed for measuring the 'closeness' of CLIPS rules and various Nearest Neighbor classification algorithms are described based on the above metric.

New nonlinear features for inspection, robotics, and face recognition

NASA Astrophysics Data System (ADS)

Casasent, David P.; Talukder, Ashit

1999-10-01

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

[Modern bacterial taxonomy: techniques review--application to bacteria that nodulate leguminous plants (BNL)].

PubMed

Zakhia, Frédéric; de Lajudie, Philippe

2006-03-01

Taxonomy is the science that studies the relationships between organisms. It comprises classification, nomenclature, and identification. Modern bacterial taxonomy is polyphasic. This means that it is based on several molecular techniques, each one retrieving the information at different cellular levels (proteins, fatty acids, DNA...). The obtained results are combined and analysed to reach a "consensus taxonomy" of a microorganism. Until 1970, a small number of classification techniques were available for microbiologists (mainly phenotypic characterization was performed: a legume species nodulation ability for a Rhizobium, for example). With the development of techniques based on polymerase chain reaction for characterization, the bacterial taxonomy has undergone great changes. In particular, the classification of the legume nodulating bacteria has been repeatedly modified over the last 20 years. We present here a review of the currently used molecular techniques in bacterial characterization, with examples of application of these techniques for the study of the legume nodulating bacteria.

Toward the classification of differential calculi on κ-Minkowski space and related field theories

NASA Astrophysics Data System (ADS)

Jurić, Tajron; Meljanac, Stjepan; Pikutić, Danijel; Štrajn, Rina

2015-07-01

Classification of differential forms on κ-Minkowski space, particularly, the classification of all bicovariant differential calculi of classical dimension is presented. By imposing super-Jacobi identities we derive all possible differential algebras compatible with the κ-Minkowski algebra for time-like, space-like and light-like deformations. Embedding into the super-Heisenberg algebra is constructed using non-commutative (NC) coordinates and one-forms. Particularly, a class of differential calculi with an undeformed exterior derivative and one-forms is considered. Corresponding NC differential calculi are elaborated. Related class of new Drinfeld twists is proposed. It contains twist leading to κ-Poincaré Hopf algebra for light-like deformation. Corresponding super-algebra and deformed super-Hopf algebras, as well as the symmetries of differential algebras are presented and elaborated. Using the NC differential calculus, we analyze NC field theory, modified dispersion relations, and discuss further physical applications.

Diagnosis of diabetes diseases using an Artificial Immune Recognition System2 (AIRS2) with fuzzy K-nearest neighbor.

PubMed

Chikh, Mohamed Amine; Saidi, Meryem; Settouti, Nesma

2012-10-01

The use of expert systems and artificial intelligence techniques in disease diagnosis has been increasing gradually. Artificial Immune Recognition System (AIRS) is one of the methods used in medical classification problems. AIRS2 is a more efficient version of the AIRS algorithm. In this paper, we used a modified AIRS2 called MAIRS2 where we replace the K- nearest neighbors algorithm with the fuzzy K-nearest neighbors to improve the diagnostic accuracy of diabetes diseases. The diabetes disease dataset used in our work is retrieved from UCI machine learning repository. The performances of the AIRS2 and MAIRS2 are evaluated regarding classification accuracy, sensitivity and specificity values. The highest classification accuracy obtained when applying the AIRS2 and MAIRS2 using 10-fold cross-validation was, respectively 82.69% and 89.10%.

Classifying Adverse Events in the Dental Office.

PubMed

Kalenderian, Elsbeth; Obadan-Udoh, Enihomo; Maramaldi, Peter; Etolue, Jini; Yansane, Alfa; Stewart, Denice; White, Joel; Vaderhobli, Ram; Kent, Karla; Hebballi, Nutan B; Delattre, Veronique; Kahn, Maria; Tokede, Oluwabunmi; Ramoni, Rachel B; Walji, Muhammad F

2017-06-30

Dentists strive to provide safe and effective oral healthcare. However, some patients may encounter an adverse event (AE) defined as "unnecessary harm due to dental treatment." In this research, we propose and evaluate two systems for categorizing the type and severity of AEs encountered at the dental office. Several existing medical AE type and severity classification systems were reviewed and adapted for dentistry. Using data collected in previous work, two initial dental AE type and severity classification systems were developed. Eight independent reviewers performed focused chart reviews, and AEs identified were used to evaluate and modify these newly developed classifications. A total of 958 charts were independently reviewed. Among the reviewed charts, 118 prospective AEs were found and 101 (85.6%) were verified as AEs through a consensus process. At the end of the study, a final AE type classification comprising 12 categories, and an AE severity classification comprising 7 categories emerged. Pain and infection were the most common AE types representing 73% of the cases reviewed (56% and 17%, respectively) and 88% were found to cause temporary, moderate to severe harm to the patient. Adverse events found during the chart review process were successfully classified using the novel dental AE type and severity classifications. Understanding the type of AEs and their severity are important steps if we are to learn from and prevent patient harm in the dental office.

Optical Neural Classification Of Binary Patterns

NASA Astrophysics Data System (ADS)

Gustafson, Steven C.; Little, Gordon R.

1988-05-01

Binary pattern classification that may be implemented using optical hardware and neural network algorithms is considered. Pattern classification problems that have no concise description (as in classifying handwritten characters) or no concise computation (as in NP-complete problems) are expected to be particularly amenable to this approach. For example, optical processors that efficiently classify binary patterns in accordance with their Boolean function complexity might be designed. As a candidate for such a design, an optical neural network model is discussed that is designed for binary pattern classification and that consists of an optical resonator with a dynamic multiplex-recorded reflection hologram and a phase conjugate mirror with thresholding and gain. In this model, learning or training examples of binary patterns may be recorded on the hologram such that one bit in each pattern marks the pattern class. Any input pattern, including one with an unknown class or marker bit, will be modified by a large number of parallel interactions with the reflection hologram and nonlinear mirror. After perhaps several seconds and 100 billion interactions, a steady-state pattern may develop with a marker bit that represents a minimum-Boolean-complexity classification of the input pattern. Computer simulations are presented that illustrate progress in understanding the behavior of this model and in developing a processor design that could have commanding and enduring performance advantages compared to current pattern classification techniques.

Sink or Float. Modified Primary. Revised. Anchorage School District Elementary Science Program.

ERIC Educational Resources Information Center

Defendorf, Jean, Ed.

This publication provides information and activities for teaching about water, whether certain objects will sink or float, and process skills including observing, classifying, inferring, measuring, predicting, and collecting and interpreting data. There are 14 lessons in the unit. The first four lessons deal with the classification of objects and…

21 CFR 888.3150 - Elbow joint metal/polymer constrained cemented prosthesis.

Code of Federal Regulations, 2010 CFR

2010-04-01

... use with bone cement (§ 888.3027). (b) Classification. Class II. The special controls for this device...) “Guidance Document for Testing Orthopedic Implants with Modified Metallic Surfaces Apposing Bone or Bone... Biomaterials (Nonporous) for Surgical Implant with Respect to Effect of Material on Muscle and Bone,” (v) F...

21 CFR 888.3150 - Elbow joint metal/polymer constrained cemented prosthesis.

Code of Federal Regulations, 2012 CFR

2012-04-01

... use with bone cement (§ 888.3027). (b) Classification. Class II. The special controls for this device...) “Guidance Document for Testing Orthopedic Implants with Modified Metallic Surfaces Apposing Bone or Bone... Biomaterials (Nonporous) for Surgical Implant with Respect to Effect of Material on Muscle and Bone,” (v) F...

21 CFR 888.3150 - Elbow joint metal/polymer constrained cemented prosthesis.

Code of Federal Regulations, 2014 CFR

2014-04-01

... use with bone cement (§ 888.3027). (b) Classification. Class II. The special controls for this device...) “Guidance Document for Testing Orthopedic Implants with Modified Metallic Surfaces Apposing Bone or Bone... Biomaterials (Nonporous) for Surgical Implant with Respect to Effect of Material on Muscle and Bone,” (v) F...

21 CFR 888.3150 - Elbow joint metal/polymer constrained cemented prosthesis.

Code of Federal Regulations, 2013 CFR

2013-04-01

... use with bone cement (§ 888.3027). (b) Classification. Class II. The special controls for this device...) “Guidance Document for Testing Orthopedic Implants with Modified Metallic Surfaces Apposing Bone or Bone... Biomaterials (Nonporous) for Surgical Implant with Respect to Effect of Material on Muscle and Bone,” (v) F...

21 CFR 888.3150 - Elbow joint metal/polymer constrained cemented prosthesis.

Code of Federal Regulations, 2011 CFR

2011-04-01

... use with bone cement (§ 888.3027). (b) Classification. Class II. The special controls for this device...) “Guidance Document for Testing Orthopedic Implants with Modified Metallic Surfaces Apposing Bone or Bone... Biomaterials (Nonporous) for Surgical Implant with Respect to Effect of Material on Muscle and Bone,” (v) F...

76 FR 59901 - Isaria fumosorosea Apopka Strain 97; Exemption From the Requirement of a Tolerance

Federal Register 2010, 2011, 2012, 2013, 2014

2011-09-28

... persist, it would not survive the conditions water is subjected to in wastewater treatment systems or... Classification System (NAICS) codes have been provided to assist you and others in determining whether this... notice of filing. Based upon review of the data supporting the petition, EPA has modified the...

Development of Classification Thinking in Future Teachers: Technologies of Reflective Discussion

ERIC Educational Resources Information Center

Cao, Yonghui; Kurbanova, Ajslu T.; Salikhova, Nailia R.

2017-01-01

The main objective of the research is to create and approbate a new way of reflection formation in future teachers, which would increase the level of classifying thinking to the theoretical one. The "Formation of equivalence groups" technique was modified to conduct the experiment. It was carried out both individually and in…

A risk-based classification scheme for genetically modified foods. III: Evaluation using a panel of reference foods.

PubMed

Chao, Eunice; Krewski, Daniel

2008-12-01

This paper presents an exploratory evaluation of four functional components of a proposed risk-based classification scheme (RBCS) for crop-derived genetically modified (GM) foods in a concordance study. Two independent raters assigned concern levels to 20 reference GM foods using a rating form based on the proposed RBCS. The four components of evaluation were: (1) degree of concordance, (2) distribution across concern levels, (3) discriminating ability of the scheme, and (4) ease of use. At least one of the 20 reference foods was assigned to each of the possible concern levels, demonstrating the ability of the scheme to identify GM foods of different concern with respect to potential health risk. There was reasonably good concordance between the two raters for the three separate parts of the RBCS. The raters agreed that the criteria in the scheme were sufficiently clear in discriminating reference foods into different concern levels, and that with some experience, the scheme was reasonably easy to use. Specific issues and suggestions for improvements identified in the concordance study are discussed.

Design of fuzzy classifier for diabetes disease using Modified Artificial Bee Colony algorithm.

PubMed

Beloufa, Fayssal; Chikh, M A

2013-10-01

In this study, diagnosis of diabetes disease, which is one of the most important diseases, is conducted with artificial intelligence techniques. We have proposed a novel Artificial Bee Colony (ABC) algorithm in which a mutation operator is added to an Artificial Bee Colony for improving its performance. When the current best solution cannot be updated, a blended crossover operator (BLX-α) of genetic algorithm is applied, in order to enhance the diversity of ABC, without compromising with the solution quality. This modified version of ABC is used as a new tool to create and optimize automatically the membership functions and rules base directly from data. We take the diabetes dataset used in our work from the UCI machine learning repository. The performances of the proposed method are evaluated through classification rate, sensitivity and specificity values using 10-fold cross-validation method. The obtained classification rate of our method is 84.21% and it is very promising when compared with the previous research in the literature for the same problem. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Heart murmur detection based on wavelet transformation and a synergy between artificial neural network and modified neighbor annealing methods.

PubMed

Eslamizadeh, Gholamhossein; Barati, Ramin

2017-05-01

Early recognition of heart disease plays a vital role in saving lives. Heart murmurs are one of the common heart problems. In this study, Artificial Neural Network (ANN) is trained with Modified Neighbor Annealing (MNA) to classify heart cycles into normal and murmur classes. Heart cycles are separated from heart sounds using wavelet transformer. The network inputs are features extracted from individual heart cycles, and two classification outputs. Classification accuracy of the proposed model is compared with five multilayer perceptron trained with Levenberg-Marquardt, Extreme-learning-machine, back-propagation, simulated-annealing, and neighbor-annealing algorithms. It is also compared with a Self-Organizing Map (SOM) ANN. The proposed model is trained and tested using real heart sounds available in the Pascal database to show the applicability of the proposed scheme. Also, a device to record real heart sounds has been developed and used for comparison purposes too. Based on the results of this study, MNA can be used to produce considerable results as a heart cycle classifier. Copyright © 2017 Elsevier B.V. All rights reserved.

Use of Magnetic Resonance Imaging as Well as Clinical Disease Activity in the Clinical Classification of Multiple Sclerosis and Assessment of Its Course

PubMed Central

Dhib-Jalbut, Suhayl; Dowling, Peter; Durelli, Luca; Ford, Corey; Giovannoni, Gavin; Halper, June; Harris, Colleen; Herbert, Joseph; Li, David; Lincoln, John A.; Lisak, Robert; Lublin, Fred D.; Lucchinetti, Claudia F.; Moore, Wayne; Naismith, Robert T.; Oehninger, Carlos; Simon, Jack; Sormani, Maria Pia

2012-01-01

It has recently been suggested that the Lublin-Reingold clinical classification of multiple sclerosis (MS) be modified to include the use of magnetic resonance imaging (MRI). An international consensus conference sponsored by the Consortium of Multiple Sclerosis Centers (CMSC) was held from March 5 to 7, 2010, to review the available evidence on the need for such modification of the Lublin-Reingold criteria and whether the addition of MRI or other biomarkers might lead to a better understanding of MS pathophysiology and disease course over time. The conference participants concluded that evidence of new MRI gadolinium-enhancing (Gd+) T1-weighted lesions and unequivocally new or enlarging T2-weighted lesions (subclinical activity, subclinical relapses) should be added to the clinical classification of MS in distinguishing relapsing inflammatory from progressive forms of the disease. The consensus was that these changes to the classification system would provide more rigorous definitions and categorization of MS course, leading to better insights as to the evolution and treatment of MS. PMID:24453741

Algorithmic framework for group analysis of differential equations and its application to generalized Zakharov-Kuznetsov equations

NASA Astrophysics Data System (ADS)

Huang, Ding-jiang; Ivanova, Nataliya M.

2016-02-01

In this paper, we explain in more details the modern treatment of the problem of group classification of (systems of) partial differential equations (PDEs) from the algorithmic point of view. More precisely, we revise the classical Lie algorithm of construction of symmetries of differential equations, describe the group classification algorithm and discuss the process of reduction of (systems of) PDEs to (systems of) equations with smaller number of independent variables in order to construct invariant solutions. The group classification algorithm and reduction process are illustrated by the example of the generalized Zakharov-Kuznetsov (GZK) equations of form ut +(F (u)) xxx +(G (u)) xyy +(H (u)) x = 0. As a result, a complete group classification of the GZK equations is performed and a number of new interesting nonlinear invariant models which have non-trivial invariance algebras are obtained. Lie symmetry reductions and exact solutions for two important invariant models, i.e., the classical and modified Zakharov-Kuznetsov equations, are constructed. The algorithmic framework for group analysis of differential equations presented in this paper can also be applied to other nonlinear PDEs.

A Bio Medical Waste Identification and Classification Algorithm Using Mltrp and Rvm.

PubMed

Achuthan, Aravindan; Ayyallu Madangopal, Vasumathi

2016-10-01

We aimed to extract the histogram features for text analysis and, to classify the types of Bio Medical Waste (BMW) for garbage disposal and management. The given BMW was preprocessed by using the median filtering technique that efficiently reduced the noise in the image. After that, the histogram features of the filtered image were extracted with the help of proposed Modified Local Tetra Pattern (MLTrP) technique. Finally, the Relevance Vector Machine (RVM) was used to classify the BMW into human body parts, plastics, cotton and liquids. The BMW image was collected from the garbage image dataset for analysis. The performance of the proposed BMW identification and classification system was evaluated in terms of sensitivity, specificity, classification rate and accuracy with the help of MATLAB. When compared to the existing techniques, the proposed techniques provided the better results. This work proposes a new texture analysis and classification technique for BMW management and disposal. It can be used in many real time applications such as hospital and healthcare management systems for proper BMW disposal.

G0-WISHART Distribution Based Classification from Polarimetric SAR Images

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

National Register of Research Projects, 1986/87. Part 2A: Natural sciences. Physical, engineering and related sciences (modified projects)

NASA Astrophysics Data System (ADS)

1988-08-01

This Register is intended to serve as a source of information on research which is being conducted in all fields (both natural and human sciences) in the Republic of South Africa. New and current research projects that were commenced or modified during 1986 and 1987, on which information was received by the compilers until January 1988, are included, with the exception of confidential projects. Project titles and keywords are presented in the language as supplied, and the classifications are based on those provided by the primary sources.

Identifying Objective Physiological Markers and Modifiable Behaviors for Self-Reported Stress and Mental Health Status Using Wearable Sensors and Mobile Phones: Observational Study.

PubMed

Sano, Akane; Taylor, Sara; McHill, Andrew W; Phillips, Andrew Jk; Barger, Laura K; Klerman, Elizabeth; Picard, Rosalind

2018-06-08

Wearable and mobile devices that capture multimodal data have the potential to identify risk factors for high stress and poor mental health and to provide information to improve health and well-being. We developed new tools that provide objective physiological and behavioral measures using wearable sensors and mobile phones, together with methods that improve their data integrity. The aim of this study was to examine, using machine learning, how accurately these measures could identify conditions of self-reported high stress and poor mental health and which of the underlying modalities and measures were most accurate in identifying those conditions. We designed and conducted the 1-month SNAPSHOT study that investigated how daily behaviors and social networks influence self-reported stress, mood, and other health or well-being-related factors. We collected over 145,000 hours of data from 201 college students (age: 18-25 years, male:female=1.8:1) at one university, all recruited within self-identified social groups. Each student filled out standardized pre- and postquestionnaires on stress and mental health; during the month, each student completed twice-daily electronic diaries (e-diaries), wore two wrist-based sensors that recorded continuous physical activity and autonomic physiology, and installed an app on their mobile phone that recorded phone usage and geolocation patterns. We developed tools to make data collection more efficient, including data-check systems for sensor and mobile phone data and an e-diary administrative module for study investigators to locate possible errors in the e-diaries and communicate with participants to correct their entries promptly, which reduced the time taken to clean e-diary data by 69%. We constructed features and applied machine learning to the multimodal data to identify factors associated with self-reported poststudy stress and mental health, including behaviors that can be possibly modified by the individual to improve these measures. We identified the physiological sensor, phone, mobility, and modifiable behavior features that were best predictors for stress and mental health classification. In general, wearable sensor features showed better classification performance than mobile phone or modifiable behavior features. Wearable sensor features, including skin conductance and temperature, reached 78.3% (148/189) accuracy for classifying students into high or low stress groups and 87% (41/47) accuracy for classifying high or low mental health groups. Modifiable behavior features, including number of naps, studying duration, calls, mobility patterns, and phone-screen-on time, reached 73.5% (139/189) accuracy for stress classification and 79% (37/47) accuracy for mental health classification. New semiautomated tools improved the efficiency of long-term ambulatory data collection from wearable and mobile devices. Applying machine learning to the resulting data revealed a set of both objective features and modifiable behavioral features that could classify self-reported high or low stress and mental health groups in a college student population better than previous studies and showed new insights into digital phenotyping. ©Akane Sano, Sara Taylor, Andrew W McHill, Andrew JK Phillips, Laura K Barger, Elizabeth Klerman, Rosalind Picard. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 08.06.2018.

Modified TAROT for cross-selling personal financial products

NASA Astrophysics Data System (ADS)

Tee, Ya-Mei; LEE, Lai-Soon; LEE, Chew-Ging; SEOW, Hsin-Vonn

2014-09-01

The Top Application characteristics Remainder Offer characteristics Tree (TAROT) was first introduced in 2007. This is a modified Classification and Regression Trees (CART) used to help decide which question(s) to ask potential applicants to customise an offer of a personal financial product so that it would have a high probability of take up. In this piece of work the authors are presenting, they have further modified the TAROT to cross TAROT, using its properties and modeling steps to deal with the issue of cross-selling. Since the bank already has ready customers, it would be ideal to cross-sell the financial products seeing that one can ask one (or more) further question(s) based on the initial offer to identify and customise another financial product to offer.

A developmental and genetic classification for midbrain-hindbrain malformations

PubMed Central

Millen, Kathleen J.; Dobyns, William B.

2009-01-01

Advances in neuroimaging, developmental biology and molecular genetics have increased the understanding of developmental disorders affecting the midbrain and hindbrain, both as isolated anomalies and as part of larger malformation syndromes. However, the understanding of these malformations and their relationships with other malformations, within the central nervous system and in the rest of the body, remains limited. A new classification system is proposed, based wherever possible, upon embryology and genetics. Proposed categories include: (i) malformations secondary to early anteroposterior and dorsoventral patterning defects, or to misspecification of mid-hindbrain germinal zones; (ii) malformations associated with later generalized developmental disorders that significantly affect the brainstem and cerebellum (and have a pathogenesis that is at least partly understood); (iii) localized brain malformations that significantly affect the brain stem and cerebellum (pathogenesis partly or largely understood, includes local proliferation, cell specification, migration and axonal guidance); and (iv) combined hypoplasia and atrophy of putative prenatal onset degenerative disorders. Pertinent embryology is discussed and the classification is justified. This classification will prove useful for both physicians who diagnose and treat patients with these disorders and for clinical scientists who wish to understand better the perturbations of developmental processes that produce them. Importantly, both the classification and its framework remain flexible enough to be easily modified when new embryologic processes are described or new malformations discovered. PMID:19933510

Stillbirth classification in population-based data and role of fetal growth restriction: the example of RECODE

PubMed Central

2013-01-01

Background Stillbirth classifications use various strategies to synthesise information associated with fetal demise with the aim of identifying key causes for the death. RECODE is a hierarchical classification of death-related conditions, which grants a major place to fetal growth restriction (FGR). Our objective was to explore how placement of FGR in the hierarchy affected results from the classification. Methods In the Rhône-Alpes region, all stillbirths were recorded in a local registry from 2000 to 2010 in three districts (N = 969). Small for gestational age (SGA) was defined as a birthweight below the 10th percentile. We applied RECODE and then modified the hierarchy, including FGR as the penultimate category (RECODE-R). Results 49.0% of stillbirths were SGA. From RECODE to RECODE-R, stillbirths attributable to FGR decreased from 38% to 14%, in favour of other related conditions. Nearly half of SGA stillbirths (49%) were reclassified. There was a non-significant tendency toward moderate SGA, singletons and full-term stillbirths to older mothers being reclassified. Conclusions The position of FGR in hierarchical stillbirth classification has a major impact on the first condition associated with stillbirth. RECODE-R calls less attention to monitoring SGA fetuses but illustrates the diversity of death-related conditions for small fetuses. PMID:24090495

Module modified acute physiology and chronic health evaluation II: predicting the mortality of neuro-critical disease.

PubMed

Su, Yingying; Wang, Miao; Liu, Yifei; Ye, Hong; Gao, Daiquan; Chen, Weibi; Zhang, Yunzhou; Zhang, Yan

2014-12-01

This study aimed to conduct and assess a module modified acute physiology and chronic health evaluation (MM-APACHE) II model, based on disease categories modified-acute physiology and chronic health evaluation (DCM-APACHE) II model, in predicting mortality more accurately in neuro-intensive care units (N-ICUs). In total, 1686 patients entered into this prospective study. Acute physiology and chronic health evaluation (APACHE) II scores of all patients on admission and worst 24-, 48-, 72-hour scores were obtained. Neurological diagnosis on admission was classified into five categories: cerebral infarction, intracranial hemorrhage, neurological infection, spinal neuromuscular (SNM) disease, and other neurological diseases. The APACHE II scores of cerebral infarction, intracranial hemorrhage, and neurological infection patients were used for building the MM-APACHE II model. There were 1386 cases for cerebral infarction disease, intracranial hemorrhage disease, and neurological infection disease. The logistic linear regression showed that 72-hour APACHE II score (Wals  =  173.04, P < 0.001) and disease classification (Wals  =  12.51, P  =  0.02) were of importance in forecasting hospital mortality. Module modified acute physiology and chronic health evaluation II model, built on the variables of the 72-hour APACHE II score and disease category, had good discrimination (area under the receiver operating characteristic curve (AU-ROC  =  0.830)) and calibration (χ2  =  12.518, P  =  0.20), and was better than the Knaus APACHE II model (AU-ROC  =  0.778). The APACHE II severity of disease classification system cannot provide accurate prognosis for all kinds of the diseases. A MM-APACHE II model can accurately predict hospital mortality for cerebral infarction, intracranial hemorrhage, and neurologic infection patients in N-ICU.

Development of a computer-based clinical decision support tool for selecting appropriate rehabilitation interventions for injured workers.

PubMed

Gross, Douglas P; Zhang, Jing; Steenstra, Ivan; Barnsley, Susan; Haws, Calvin; Amell, Tyler; McIntosh, Greg; Cooper, Juliette; Zaiane, Osmar

2013-12-01

To develop a classification algorithm and accompanying computer-based clinical decision support tool to help categorize injured workers toward optimal rehabilitation interventions based on unique worker characteristics. Population-based historical cohort design. Data were extracted from a Canadian provincial workers' compensation database on all claimants undergoing work assessment between December 2009 and January 2011. Data were available on: (1) numerous personal, clinical, occupational, and social variables; (2) type of rehabilitation undertaken; and (3) outcomes following rehabilitation (receiving time loss benefits or undergoing repeat programs). Machine learning, concerned with the design of algorithms to discriminate between classes based on empirical data, was the foundation of our approach to build a classification system with multiple independent and dependent variables. The population included 8,611 unique claimants. Subjects were predominantly employed (85 %) males (64 %) with diagnoses of sprain/strain (44 %). Baseline clinician classification accuracy was high (ROC = 0.86) for selecting programs that lead to successful return-to-work. Classification performance for machine learning techniques outperformed the clinician baseline classification (ROC = 0.94). The final classifiers were multifactorial and included the variables: injury duration, occupation, job attachment status, work status, modified work availability, pain intensity rating, self-rated occupational disability, and 9 items from the SF-36 Health Survey. The use of machine learning classification techniques appears to have resulted in classification performance better than clinician decision-making. The final algorithm has been integrated into a computer-based clinical decision support tool that requires additional validation in a clinical sample.

The Classification Accuracy of the Minnesota Multiphasic Personality Inventory--Adolescent: Effects of Modifying the Normative Sample

ERIC Educational Resources Information Center

Hand, Cynthia G.; Archer, Robert P.; Handel, Richard W.; Forbey, Johnathan D.

2007-01-01

Numerous studies have reported that the Minnesota Multiphasic Personality Inventory-Adolescent (MMPI-A) produces a high frequency of within-normal-limits basic scale profiles for adolescents with significant clinical pathology (e.g., Archer, 2005). The current study builds on the observation that the MMPI-A normative sample included participants…

Super p53 for Treatment of Ovarian Cancer

DTIC Science & Technology

2016-07-01

WSLP ( polymer ) has been successfully synthesized, and a subset of adenoviral constructs have been cloned (p53, p53-CC, EGFP control). Major results...therapy, carboplatin, paclitaxel, polymeric drug delivery, polymer -adenovirus hybrid 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18...modified p53, tumor suppressor, high grade serous carcinoma, combination therapy, carboplatin, paclitaxel, polymeric drug delivery, polymer

An empirical investigation of sparse distributed memory using discrete speech recognition

NASA Technical Reports Server (NTRS)

Danforth, Douglas G.

1990-01-01

Presented here is a step by step analysis of how the basic Sparse Distributed Memory (SDM) model can be modified to enhance its generalization capabilities for classification tasks. Data is taken from speech generated by a single talker. Experiments are used to investigate the theory of associative memories and the question of generalization from specific instances.

Testing of the Support Vector Machine for Binary-Class Classification

NASA Technical Reports Server (NTRS)

Scholten, Matthew

2011-01-01

The Support Vector Machine is a powerful algorithm, useful in classifying data in to species. The Support Vector Machines implemented in this research were used as classifiers for the final stage in a Multistage Autonomous Target Recognition system. A single kernel SVM known as SVMlight, and a modified version known as a Support Vector Machine with K-Means Clustering were used. These SVM algorithms were tested as classifiers under varying conditions. Image noise levels varied, and the orientation of the targets changed. The classifiers were then optimized to demonstrate their maximum potential as classifiers. Results demonstrate the reliability of SMV as a method for classification. From trial to trial, SVM produces consistent results

Modified constraint-induced therapy for children with hemiplegic cerebral palsy: a randomized trial.

PubMed

Wallen, Margaret; Ziviani, Jenny; Naylor, Olivia; Evans, Ruth; Novak, Iona; Herbert, Robert D

2011-12-01

Conventional constraint-based therapies are intensive and demanding to implement, particularly for children. Modified forms of constraint-based therapies that are family-centred may be more acceptable and feasible for families of children with cerebral palsy (CP)-but require rigorous evaluation using randomized trials. The aim of this study was to determine the effects of modified constraint-induced therapy compared with intensive occupational therapy on activities of daily living and upper limb outcomes in children with hemiplegic CP. In this assessor-blinded pragmatic randomized trial, 50 children (27 males, 23 females; age range 19 mo-7 y 10 mo) with hemiplegic CP were randomized using a concealed allocation procedure to one of two 8-week interventions: intensive occupational therapy (n = 25), or modified constraint-induced therapy (n = 25). Manual Ability Classification System (MACS) levels of the participants were, level I n = 2, II n = 37, III n = 8, and level IV n = 1; Gross Motor Function Classification System (GMFCS) levels were, level I n = 33, level II n = 15, and level III n = 1. Participants were recruited through three specialist CP centres in Australia and randomized between January 2008 and April 2010. Children randomized to modified constraint-induced therapy wore a mitt on the unaffected hand for 2 hours each day, during which time the children participated in targeted therapy. The primary outcome was the Canadian Occupational Performance Measure (COPM--measured on a 10-point scale) at completion of therapy. Other outcome measures were Goal Attainment Scaling, Assisting Hand Assessment, Pediatric Motor Activity Log, Modified Ashworth Scale, Modified Tardieu Scale, and a parent questionnaire. Assessments were carried out at 10 weeks and 6 months following randomization. All participants were included in the analysis. Between-group differences for all outcomes were neither clinically important nor statistically significant. The mean difference in COPM was 0.3 (95% confidence interval [CI] -0.8 to 1.4; p=0.61) and mean difference in COPM satisfaction was 0.1 (95% CI -1.1 to 1.2; p=0.90). Minor adverse events were reported by five of the 25 participants in the modified constraint-induced therapy group and by one of the 25 in the intensive occupational therapy group. All adverse events were related to participants' lack of acceptance of therapy. Modified constraint-induced therapy is no more effective than intensive occupational therapy for improving completion of activities of daily living or upper limb function in children with hemiplegic CP. © The Authors. Developmental Medicine & Child Neurology © 2011 Mac Keith Press.

Reliability analysis of the AOSpine thoracolumbar spine injury classification system by a worldwide group of naïve spinal surgeons.

PubMed

Kepler, Christopher K; Vaccaro, Alexander R; Koerner, John D; Dvorak, Marcel F; Kandziora, Frank; Rajasekaran, Shanmuganathan; Aarabi, Bizhan; Vialle, Luiz R; Fehlings, Michael G; Schroeder, Gregory D; Reinhold, Maximilian; Schnake, Klaus John; Bellabarba, Carlo; Cumhur Öner, F

2016-04-01

The aims of this study were (1) to demonstrate the AOSpine thoracolumbar spine injury classification system can be reliably applied by an international group of surgeons and (2) to delineate those injury types which are difficult for spine surgeons to classify reliably. A previously described classification system of thoracolumbar injuries which consists of a morphologic classification of the fracture, a grading system for the neurologic status and relevant patient-specific modifiers was applied to 25 cases by 100 spinal surgeons from across the world twice independently, in grading sessions 1 month apart. The results were analyzed for classification reliability using the Kappa coefficient (κ). The overall Kappa coefficient for all cases was 0.56, which represents moderate reliability. Kappa values describing interobserver agreement were 0.80 for type A injuries, 0.68 for type B injuries and 0.72 for type C injuries, all representing substantial reliability. The lowest level of agreement for specific subtypes was for fracture subtype A4 (Kappa = 0.19). Intraobserver analysis demonstrated overall average Kappa statistic for subtype grading of 0.68 also representing substantial reproducibility. In a worldwide sample of spinal surgeons without previous exposure to the recently described AOSpine Thoracolumbar Spine Injury Classification System, we demonstrated moderate interobserver and substantial intraobserver reliability. These results suggest that most spine surgeons can reliably apply this system to spine trauma patients as or more reliably than previously described systems.

The revised WHO dengue case classification: does the system need to be modified?

PubMed

Hadinegoro, Sri Rezeki S

2012-05-01

There has been considerable debate regarding the value of both the 1997 and 2009 World Health Organization (WHO) dengue case classification criteria for its diagnosis and management. Differentiation between classic dengue fever (DF) and dengue haemorrhagic fever (DHF) or severe dengue is a key aspect of dengue case classification. The geographic expansion of dengue and its increased incidence in older age groups have contributed to the limited applicability of the 1997 case definitions. Clinical experience of dengue suggests that the illness presents as a spectrum of disease instead of distinct phases. However, despite the rigid grouping of dengue into DF, DHF and dengue shock syndrome (DSS), overlap between the different manifestations has often been observed, which has affected clinical management and triage of patients. The findings of the DENCO study evaluating the 1997 case definitions formed the basis of the revised 2009 WHO case definitions, which classified the illness into dengue with and without warning signs and severe dengue. Although the revised scheme is more sensitive to the diagnosis of severe dengue, and beneficial to triage and case management, there remain issues with its applicability. It is considered by many to be too broad, requiring more specific definition of warning signs. Quantitative research into the predictive value of these warning signs on patient outcomes and the cost-effectiveness of the new classification system is required to ascertain whether the new classification system requires further modification, or whether elements of both classification systems can be combined.

Genetic engineering applied to agriculture has a long row to hoe.

PubMed

Miller, Henry I

2018-01-02

In spite of the lack of scientific justification for skepticism about crops modified with molecular techniques of genetic engineering, they have been the most scrutinized agricultural products in human history. The assumption that "genetically engineered" or "genetically modified" is a meaningful - and dangerous - classification has led to excessive and dilatory regulation. The modern molecular techniques are an extension, or refinement, of older, less precise, less predictable methods of genetic modification, but as long as today's activists and regulators remain convinced that so called "GMOs" represent a distinct and dangerous category of research and products, genetic engineering will fall short of its potential.

Development and initial validation of the Classification of Early-Onset Scoliosis (C-EOS).

PubMed

Williams, Brendan A; Matsumoto, Hiroko; McCalla, Daren J; Akbarnia, Behrooz A; Blakemore, Laurel C; Betz, Randal R; Flynn, John M; Johnston, Charles E; McCarthy, Richard E; Roye, David P; Skaggs, David L; Smith, John T; Snyder, Brian D; Sponseller, Paul D; Sturm, Peter F; Thompson, George H; Yazici, Muharrem; Vitale, Michael G

2014-08-20

Early-onset scoliosis is a heterogeneous condition, with highly variable manifestations and natural history. No standardized classification system exists to describe and group patients, to guide optimal care, or to prognosticate outcomes within this population. A classification system for early-onset scoliosis is thus a necessary prerequisite to the timely evolution of care of these patients. Fifteen experienced surgeons participated in a nominal group technique designed to achieve a consensus-based classification system for early-onset scoliosis. A comprehensive list of factors important in managing early-onset scoliosis was generated using a standardized literature review, semi-structured interviews, and open forum discussion. Three group meetings and two rounds of surveying guided the selection of classification components, subgroupings, and cut-points. Initial validation of the system was conducted using an interobserver reliability assessment based on the classification of a series of thirty cases. Nominal group technique was used to identify three core variables (major curve angle, etiology, and kyphosis) with high group content validity scores. Age and curve progression ranked slightly lower. Participants evaluated the cases of thirty patients with early-onset scoliosis for reliability testing. The mean kappa value for etiology (0.64) was substantial, while the mean kappa values for major curve angle (0.95) and kyphosis (0.93) indicated almost perfect agreement. The final classification consisted of a continuous age prefix, etiology (congenital or structural, neuromuscular, syndromic, and idiopathic), major curve angle (1, 2, 3, or 4), and kyphosis (-, N, or +) variables, and an optional progression modifier (P0, P1, or P2). Utilizing formal consensus-building methods in a large group of surgeons experienced in treating early-onset scoliosis, a novel classification system for early-onset scoliosis was developed with all core components demonstrating substantial to excellent interobserver reliability. This classification system will serve as a foundation to guide ongoing research efforts and standardize communication in the clinical setting. Copyright © 2014 by The Journal of Bone and Joint Surgery, Incorporated.

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.

An enhancement of binary particle swarm optimization for gene selection in classifying cancer classes

PubMed Central

2013-01-01

Background Gene expression data could likely be a momentous help in the progress of proficient cancer diagnoses and classification platforms. Lately, many researchers analyze gene expression data using diverse computational intelligence methods, for selecting a small subset of informative genes from the data for cancer classification. Many computational methods face difficulties in selecting small subsets due to the small number of samples compared to the huge number of genes (high-dimension), irrelevant genes, and noisy genes. Methods We propose an enhanced binary particle swarm optimization to perform the selection of small subsets of informative genes which is significant for cancer classification. Particle speed, rule, and modified sigmoid function are introduced in this proposed method to increase the probability of the bits in a particle’s position to be zero. The method was empirically applied to a suite of ten well-known benchmark gene expression data sets. Results The performance of the proposed method proved to be superior to other previous related works, including the conventional version of binary particle swarm optimization (BPSO) in terms of classification accuracy and the number of selected genes. The proposed method also requires lower computational time compared to BPSO. PMID:23617960

Examining Factors That Influence Donor Motivation among Former Student-Athletes and NCAA DI Classification

ERIC Educational Resources Information Center

Burchette, Brett M.

2013-01-01

The purpose of this study was to identify motivational factors that contribute to the philanthropic decision making of the former NCAA Division I student-athlete. A 47-item survey instrument was modified from a prior study and distributed electronically to 8,461 male and female former student-athletes at three participating NCAA Division I…

Enhanced Thermal Transport of Surfaces with Superhydrophobic Coatings

DTIC Science & Technology

2015-07-01

transport, superhydrophobic, jumping droplet, cooling, nanostructure, self - assembled monolayer 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF...modified from a hydrophilic chemistry (oxide) to a hydrophobic surface using a fluorinated (or protonated) self - assembled monolayer (SAM). Chemical...seconds and dried with filtered nitrogen. 2.3 SAM Deposition The final step involved the deposition of a self - assembled monolayer onto the silvered

An Evaluation of Risk Factors Related to Employment Outcomes for Youth with Disabilities

ERIC Educational Resources Information Center

Sima, Adam P.; Wehman, Paul H.; Chan, Fong; West, Michael D.; Leucking, Richard G.

2015-01-01

This study explores non-modifiable risk factors associated with poor post-school competitive employment outcomes for students with disabilities. A classification tree analysis was used with a sample of 2,900 students who were in the second National Longitudinal Transition Study-2 (NLTS2) up to 6 years following school exit to identify groups of…

Use of LANDSAT imagery for wildlife habitat mapping in northeast and eastcentral Alaska. [winter and summer moose range

NASA Technical Reports Server (NTRS)

Lent, P. C. (Principal Investigator)

1976-01-01

The author has identified the following significant results. Winter and summer moose range maps of three selected areas were produced (1:63,360 scale). The analytic approach is very similar to modified clustering. Preliminary results indicate that this method is not only more accurate but considerably less expensive than supervised classification techniques.

Balancing research and funding using value of information and portfolio tools for nanomaterial risk classification

NASA Astrophysics Data System (ADS)

Bates, Matthew E.; Keisler, Jeffrey M.; Zussblatt, Niels P.; Plourde, Kenton J.; Wender, Ben A.; Linkov, Igor

2016-02-01

Risk research for nanomaterials is currently prioritized by means of expert workshops and other deliberative processes. However, analytical techniques that quantify and compare alternative research investments are increasingly recommended. Here, we apply value of information and portfolio decision analysis—methods commonly applied in financial and operations management—to prioritize risk research for multiwalled carbon nanotubes and nanoparticulate silver and titanium dioxide. We modify the widely accepted CB Nanotool hazard evaluation framework, which combines nano- and bulk-material properties into a hazard score, to operate probabilistically with uncertain inputs. Literature is reviewed to develop uncertain estimates for each input parameter, and a Monte Carlo simulation is applied to assess how different research strategies can improve hazard classification. The relative cost of each research experiment is elicited from experts, which enables identification of efficient research portfolios—combinations of experiments that lead to the greatest improvement in hazard classification at the lowest cost. Nanoparticle shape, diameter, solubility and surface reactivity were most frequently identified within efficient portfolios in our results.

Classification, prevention and management of entero-atmospheric fistula: a state-of-the-art review.

PubMed

Di Saverio, Salomone; Tarasconi, Antonio; Walczak, Dominik A; Cirocchi, Roberto; Mandrioli, Matteo; Birindelli, Arianna; Tugnoli, Gregorio

2016-02-01

Entero-atmospheric fistula (EAF) is an enteric fistula occurring in the setting of an open abdomen, thus creating a communication between the GI tract and the external atmosphere. Management and nursing of patients suffering EAF carries several challenges, and prevention of EAF should be the first and best treatment option. Here, we present a novel modified classification of EAF and review the current state of the art in its prevention and management including nutritional issues and feeding strategies. We also provide an overview on surgical management principles, highlighting several surgical techniques for dealing with EAF that have been reported in the literature throughout the years. The treatment strategy for EAF should be multidisciplinary and multifaceted. Surgical treatment is most often multistep and should be tailored to the single patient, based on the type and characteristics of the EAF, following its correct identification and classification. The specific experience of surgeons and nursing staff in the management of EAF could be enhanced, applying distinct simulation-based ex vivo training models.

Balancing research and funding using value of information and portfolio tools for nanomaterial risk classification.

PubMed

Bates, Matthew E; Keisler, Jeffrey M; Zussblatt, Niels P; Plourde, Kenton J; Wender, Ben A; Linkov, Igor

2016-02-01

Risk research for nanomaterials is currently prioritized by means of expert workshops and other deliberative processes. However, analytical techniques that quantify and compare alternative research investments are increasingly recommended. Here, we apply value of information and portfolio decision analysis-methods commonly applied in financial and operations management-to prioritize risk research for multiwalled carbon nanotubes and nanoparticulate silver and titanium dioxide. We modify the widely accepted CB Nanotool hazard evaluation framework, which combines nano- and bulk-material properties into a hazard score, to operate probabilistically with uncertain inputs. Literature is reviewed to develop uncertain estimates for each input parameter, and a Monte Carlo simulation is applied to assess how different research strategies can improve hazard classification. The relative cost of each research experiment is elicited from experts, which enables identification of efficient research portfolios-combinations of experiments that lead to the greatest improvement in hazard classification at the lowest cost. Nanoparticle shape, diameter, solubility and surface reactivity were most frequently identified within efficient portfolios in our results.

Multiple-factor classification of a human-modified forest landscape in the Hsuehshan Mountain Range, Taiwan.

PubMed

Berg, Kevan J; Icyeh, Lahuy; Lin, Yih-Ren; Janz, Arnold; Newmaster, Steven G

2016-12-01

Human actions drive landscape heterogeneity, yet most ecosystem classifications omit the role of human influence. This study explores land use history to inform a classification of forestland of the Tayal Mrqwang indigenous people of Taiwan. Our objectives were to determine the extent to which human action drives landscape heterogeneity. We used interviews, field sampling, and multivariate analysis to relate vegetation patterns to environmental gradients and human modification across 76 sites. We identified eleven forest classes. In total, around 70 % of plots were at lower elevations and had a history of shifting cultivation, terrace farming, and settlement that resulted in alder, laurel, oak, pine, and bamboo stands. Higher elevation mixed conifer forests were least disturbed. Arboriculture and selective harvesting were drivers of other conspicuous forest patterns. The findings show that past land uses play a key role in shaping forests, which is important to consider when setting targets to guide forest management.

Chemometric and multivariate statistical analysis of time-of-flight secondary ion mass spectrometry spectra from complex Cu-Fe sulfides.

PubMed

Kalegowda, Yogesh; Harmer, Sarah L

2012-03-20

Time-of-flight secondary ion mass spectrometry (TOF-SIMS) spectra of mineral samples are complex, comprised of large mass ranges and many peaks. Consequently, characterization and classification analysis of these systems is challenging. In this study, different chemometric and statistical data evaluation methods, based on monolayer sensitive TOF-SIMS data, have been tested for the characterization and classification of copper-iron sulfide minerals (chalcopyrite, chalcocite, bornite, and pyrite) at different flotation pulp conditions (feed, conditioned feed, and Eh modified). The complex mass spectral data sets were analyzed using the following chemometric and statistical techniques: principal component analysis (PCA); principal component-discriminant functional analysis (PC-DFA); soft independent modeling of class analogy (SIMCA); and k-Nearest Neighbor (k-NN) classification. PCA was found to be an important first step in multivariate analysis, providing insight into both the relative grouping of samples and the elemental/molecular basis for those groupings. For samples exposed to oxidative conditions (at Eh ~430 mV), each technique (PCA, PC-DFA, SIMCA, and k-NN) was found to produce excellent classification. For samples at reductive conditions (at Eh ~ -200 mV SHE), k-NN and SIMCA produced the most accurate classification. Phase identification of particles that contain the same elements but a different crystal structure in a mixed multimetal mineral system has been achieved.

A Descriptive Genetic Classification for Glaciovolcanoes

NASA Astrophysics Data System (ADS)

Edwards, B. R.; Russell, K.; Porritt, L. A.

2014-12-01

We review the recently published descriptive genetic classification for glaciovolcanoes (Russell et al., Quat Sci Rv, 2014). The new classification uses 'tuya' as a root word for all glaciovolcanic edifices, and with modifiers that make the classification descriptive (e.g., andesitic, lava-dominated, flat topped tuya). Although tuyas can range in composition from basaltic to rhyolitic, many of the characteristics diagnostic of glaciovolcanic environments are largely independent of lava composition (e.g., edifice morphology, columnar jointing patterns, glass distributions, pyroclast shapes). Tuya subtypes are first classified on the basis of variations in edifice-scale morphologies (e.g., conical tuya) then, on the proportions of the essential lithofacies (e.g., tephra-dominated conical tuya), and lastly on magma composition (e.g., basaltic, tephra-dominated, conical tuya). The lithofacies associations within tuyas broadly record the interplay between magmatic and glaciohydraulic conditions extent during the active phases of the eruption, including the dominant style of eruption (e.g., explosive vs. effusive). We present nine distinct, endmember models for glaciovolcanic edifices that simultaneously record changes in eruption conditions (explosive, transitional, effusive) for different general glaciohydraulic conditions (closed/sealed, leaky/partly sealed, open/well-drained). To date we have identified potential examples for 7 of the 9 models. Use of a simplified, descriptive classification scheme for glaciovolcanoes will facilitate communications amongst volcanologists and planetary scientists and the use of tuyas for recovering critical paleo-environmental information, particularly the local glaciohydraulics extent during eruptions.

Computer-aided Prognosis of Neuroblastoma on Whole-slide Images: Classification of Stromal Development

PubMed Central

Sertel, O.; Kong, J.; Shimada, H.; Catalyurek, U.V.; Saltz, J.H.; Gurcan, M.N.

2009-01-01

We are developing a computer-aided prognosis system for neuroblastoma (NB), a cancer of the nervous system and one of the most malignant tumors affecting children. Histopathological examination is an important stage for further treatment planning in routine clinical diagnosis of NB. According to the International Neuroblastoma Pathology Classification (the Shimada system), NB patients are classified into favorable and unfavorable histology based on the tissue morphology. In this study, we propose an image analysis system that operates on digitized H&E stained whole-slide NB tissue samples and classifies each slide as either stroma-rich or stroma-poor based on the degree of Schwannian stromal development. Our statistical framework performs the classification based on texture features extracted using co-occurrence statistics and local binary patterns. Due to the high resolution of digitized whole-slide images, we propose a multi-resolution approach that mimics the evaluation of a pathologist such that the image analysis starts from the lowest resolution and switches to higher resolutions when necessary. We employ an offine feature selection step, which determines the most discriminative features at each resolution level during the training step. A modified k-nearest neighbor classifier is used to determine the confidence level of the classification to make the decision at a particular resolution level. The proposed approach was independently tested on 43 whole-slide samples and provided an overall classification accuracy of 88.4%. PMID:20161324

Risk factors and classification of stillbirth in a Middle Eastern population: a retrospective study.

PubMed

Kunjachen Maducolil, Mariam; Abid, Hafsa; Lobo, Rachael Marian; Chughtai, Ambreen Qayyum; Afzal, Arjumand Muhammad; Saleh, Huda Abdullah Hussain; Lindow, Stephen W

2017-12-21

To estimate the incidence of stillbirth, explore the associated maternal and fetal factors and to evaluate the most appropriate classification of stillbirth for a multiethnic population. This is a retrospective population-based study of stillbirth in a large tertiary unit. Data of each stillbirth with a gestational age >/=24 weeks in the year 2015 were collected from electronic medical records and analyzed. The stillbirth rate for our multiethnic population is 7.81 per 1000 births. Maternal medical factors comprised 52.4% in which the rates of hypertensive disorders, diabetes and other medical disorders were 22.5%, 20.8% and 8.3%, respectively. The most common fetal factor was intrauterine growth restriction (IUGR) (22.5%) followed by congenital anomalies (21.6%). All cases were categorized using the Wigglesworth, Aberdeen, Tulip, ReCoDe and International Classification of Diseases-perinatal mortality (ICD-PM) classifications and the rates of unclassified stillbirths were 59.2%, 46.6%, 16.6%, 11.6% and 7.5%, respectively. An autopsy was performed in 9.1% of cases reflecting local religious and cultural sensitivities. This study highlighted the modifiable risk factors among the Middle Eastern population. The most appropriate classification was the ICD-PM. The low rates of autopsy prevented a detailed evaluation of stillbirths, therefore it is suggested that a minimally invasive autopsy [postmortem magnetic resonance imaging (MRI)] may improve the quality of care.

Patient characteristics in low back pain subgroups based on an existing classification system. A descriptive cohort study in chiropractic practice.

PubMed

Eirikstoft, Heidi; Kongsted, Alice

2014-02-01

Sub-grouping of low back pain (LBP) is believed to improve prediction of prognosis and treatment effects. The objectives of this study were: (1) to examine whether chiropractic patients could be sub-grouped according to an existing pathoanatomically-based classification system, (2) to describe patient characteristics within each subgroup, and (3) to determine the proportion of patients in whom clinicians considered the classification to be unchanged after approximately 10 days. A cohort of 923 LBP patients was included during their first consultation. Patients completed an extensive questionnaire and were examined according to a standardised protocol. Based on the clinical examination, patients were classified into diagnostic subgroups. After approximately 10 days, chiropractors reported whether they considered the subgroup had changed. The most frequent subgroups were reducible and partly reducible disc syndromes followed by facet joint pain, dysfunction and sacroiliac (SI)-joint pain. Classification was inconclusive in 5% of the patients. Differences in pain, activity limitation, and psychological factors were small across subgroups. Within 10 days, 82% were reported to belong to the same subgroup as at the first visit. In conclusion, LBP patients could be classified according to a standardised protocol, and chiropractors considered most patient classifications to be unchanged within 10 days. Differences in patient characteristics between subgroups were very small, and the clinical relevance of the classification system should be investigated by testing its value as a prognostic factor or a treatment effect modifier. It is recommended that this classification system be combined with psychological and social factors if it is to be useful. Copyright © 2013 Elsevier Ltd. All rights reserved.

The 2016 WHO Classification of Tumours of the Urinary System and Male Genital Organs-Part A: Renal, Penile, and Testicular Tumours.

PubMed

Moch, Holger; Cubilla, Antonio L; Humphrey, Peter A; Reuter, Victor E; Ulbright, Thomas M

2016-07-01

The fourth edition of the World Health Organization (WHO) classification of urogenital tumours (WHO "blue book"), published in 2016, contains significant revisions. These revisions were performed after consideration by a large international group of pathologists with special expertise in this area. A subgroup of these persons met at the WHO Consensus Conference in Zurich, Switzerland, in 2015 to finalize the revisions. This review summarizes the most significant differences between the newly published classification and the prior version for renal, penile, and testicular tumours. Newly recognized epithelial renal tumours are hereditary leiomyomatosis and renal cell carcinoma (RCC) syndrome-associated RCC, succinate dehydrogenase-deficient RCC, tubulocystic RCC, acquired cystic disease-associated RCC, and clear cell papillary RCC. The WHO/International Society of Urological Pathology renal tumour grading system was recommended, and the definition of renal papillary adenoma was modified. The new WHO classification of penile squamous cell carcinomas is based on the presence of human papillomavirus and defines histologic subtypes accordingly. Germ cell neoplasia in situ (GCNIS) of the testis is the WHO-recommended term for precursor lesions of invasive germ cell tumours, and testicular germ cell tumours are now separated into two fundamentally different groups: those derived from GCNIS and those unrelated to GCNIS. Spermatocytic seminoma has been designated as a spermatocytic tumour and placed within the group of non-GCNIS-related tumours in the 2016 WHO classification. The 2016 World Health Organization (WHO) classification contains new renal tumour entities. The classification of penile squamous cell carcinomas is based on the presence of human papillomavirus. Germ cell neoplasia in situ of the testis is the WHO-recommended term for precursor lesions of invasive germ cell tumours. Copyright © 2016 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Multiclass Classification by Adaptive Network of Dendritic Neurons with Binary Synapses Using Structural Plasticity

PubMed Central

Hussain, Shaista; Basu, Arindam

2016-01-01

The development of power-efficient neuromorphic devices presents the challenge of designing spike pattern classification algorithms which can be implemented on low-precision hardware and can also achieve state-of-the-art performance. In our pursuit of meeting this challenge, we present a pattern classification model which uses a sparse connection matrix and exploits the mechanism of nonlinear dendritic processing to achieve high classification accuracy. A rate-based structural learning rule for multiclass classification is proposed which modifies a connectivity matrix of binary synaptic connections by choosing the best “k” out of “d” inputs to make connections on every dendritic branch (k < < d). Because learning only modifies connectivity, the model is well suited for implementation in neuromorphic systems using address-event representation (AER). We develop an ensemble method which combines several dendritic classifiers to achieve enhanced generalization over individual classifiers. We have two major findings: (1) Our results demonstrate that an ensemble created with classifiers comprising moderate number of dendrites performs better than both ensembles of perceptrons and of complex dendritic trees. (2) In order to determine the moderate number of dendrites required for a specific classification problem, a two-step solution is proposed. First, an adaptive approach is proposed which scales the relative size of the dendritic trees of neurons for each class. It works by progressively adding dendrites with fixed number of synapses to the network, thereby allocating synaptic resources as per the complexity of the given problem. As a second step, theoretical capacity calculations are used to convert each neuronal dendritic tree to its optimal topology where dendrites of each class are assigned different number of synapses. The performance of the model is evaluated on classification of handwritten digits from the benchmark MNIST dataset and compared with other spike classifiers. We show that our system can achieve classification accuracy within 1 − 2% of other reported spike-based classifiers while using much less synaptic resources (only 7%) compared to that used by other methods. Further, an ensemble classifier created with adaptively learned sizes can attain accuracy of 96.4% which is at par with the best reported performance of spike-based classifiers. Moreover, the proposed method achieves this by using about 20% of the synapses used by other spike algorithms. We also present results of applying our algorithm to classify the MNIST-DVS dataset collected from a real spike-based image sensor and show results comparable to the best reported ones (88.1% accuracy). For VLSI implementations, we show that the reduced synaptic memory can save upto 4X area compared to conventional crossbar topologies. Finally, we also present a biologically realistic spike-based version for calculating the correlations required by the structural learning rule and demonstrate the correspondence between the rate-based and spike-based methods of learning. PMID:27065782

Optimized circulation and weather type classifications relating large-scale atmospheric conditions to local PM10 concentrations in Bavaria

NASA Astrophysics Data System (ADS)

Weitnauer, C.; Beck, C.; Jacobeit, J.

2013-12-01

In the last decades the critical increase of the emission of air pollutants like nitrogen dioxide, sulfur oxides and particulate matter especially in urban areas has become a problem for the environment as well as human health. Several studies confirm a risk of high concentration episodes of particulate matter with an aerodynamic diameter < 10 μm (PM10) for the respiratory tract or cardiovascular diseases. Furthermore it is known that local meteorological and large scale atmospheric conditions are important influencing factors on local PM10 concentrations. With climate changing rapidly, these connections need to be better understood in order to provide estimates of climate change related consequences for air quality management purposes. For quantifying the link between large-scale atmospheric conditions and local PM10 concentrations circulation- and weather type classifications are used in a number of studies by using different statistical approaches. Thus far only few systematic attempts have been made to modify consisting or to develop new weather- and circulation type classifications in order to improve their ability to resolve local PM10 concentrations. In this contribution existing weather- and circulation type classifications, performed on daily 2.5 x 2.5 gridded parameters of the NCEP/NCAR reanalysis data set, are optimized with regard to their discriminative power for local PM10 concentrations at 49 Bavarian measurement sites for the period 1980 to 2011. Most of the PM10 stations are situated in urban areas covering urban background, traffic and industry related pollution regimes. The range of regimes is extended by a few rural background stations. To characterize the correspondence between the PM10 measurements of the different stations by spatial patterns, a regionalization by an s-mode principal component analysis is realized on the high-pass filtered data. The optimization of the circulation- and weather types is implemented using two representative classification approaches, a k-means cluster analysis and an objective version of the Grosswetter types. They have been run with varying spatial and temporal settings as well as modified numbers of classes. As an evaluation metric for their performance several skill scores are used. Taking into account the outcome further attempts towards the optimization of circulation type classifications are made. These are varying meteorological input parameters (e.g. geopotential height, zonal and meridional wind, specific humidity, temperature) on several pressure levels (1000, 850 and 500 hPa) and combinations of these variables. All classification variants are again evaluated. Based on these analyses it is further intended to develop robust downscaling models for estimating possible future - climate change induced - variations of local PM10 concentrations in Bavaria from scenario runs of global CMIP5 climate models.

[Scores and stages in pneumology].

PubMed

Kuhn, Max

2013-10-01

Useful scales and classifications for patients with pulmonary diseases are discussed. The modified Medical Research Council breathlessness scale (mMRC) is a measure of disability in lung patients. The GOLD classifications, the COPD-Assessment Test (CAT) and the BODE Index are important to classify the severity of COPD and to measure the disability of these patients. The Geneva score is a clinical prediction rule used in determining the pre-test probability of pulmonary embolism. The Pulmonary Embolism Severity Index (PESI) is a scoring system used to predict 30 day mortality in patients with pulmonary embolism. The Epworth Sleepiness Scale is intended to measure daytime sleepiness in patients with sleep apnea syndrome. The Asthma Controll Test (ACT) determines if asthma symptoms are well controlled.

A Visual Basic program to plot sediment grain-size data on ternary diagrams

USGS Publications Warehouse

Poppe, L.J.; Eliason, A.H.

2008-01-01

Sedimentologic datasets are typically large and compiled into tables or databases, but pure numerical information can be difficult to understand and interpret. Thus, scientists commonly use graphical representations to reduce complexities, recognize trends and patterns in the data, and develop hypotheses. Of the graphical techniques, one of the most common methods used by sedimentologists is to plot the basic gravel, sand, silt, and clay percentages on equilateral triangular diagrams. This means of presenting data is simple and facilitates rapid classification of sediments and comparison of samples.The original classification scheme developed by Shepard (1954) used a single ternary diagram with sand, silt, and clay in the corners and 10 categories to graphically show the relative proportions among these three grades within a sample. This scheme, however, did not allow for sediments with significant amounts of gravel. Therefore, Shepard's classification scheme was later modified by the addition of a second ternary diagram with two categories to account for gravel and gravelly sediment (Schlee, 1973). The system devised by Folk (1954, 1974)\\ is also based on two triangular diagrams, but it has 21 categories and uses the term mud (defined as silt plus clay). Patterns within the triangles of both systems differ, as does the emphasis placed on gravel. For example, in the system described by Shepard, gravelly sediments have more than 10% gravel; in Folk's system, slightly gravelly sediments have as little as 0.01% gravel. Folk's classification scheme stresses gravel because its concentration is a function of the highest current velocity at the time of deposition as is the maximum grain size of the detritus that is available; Shepard's classification scheme emphasizes the ratios of sand, silt, and clay because they reflect sorting and reworking (Poppe et al., 2005).The program described herein (SEDPLOT) generates verbal equivalents and ternary diagrams to characterize sediment grain-size distributions. It is written in Microsoft Visual Basic 6.0 and provides a window to facilitate program execution. The inputs for the sediment fractions are percentages of gravel, sand, silt, and clay in the Wentworth (1922) grade scale, and the program permits the user to select output in either the Shepard (1954) classification scheme, modified as described above, or the Folk (1954, 1974) scheme. Users select options primarily with mouse-click events and through interactive dialogue boxes. This program is intended as a companion to other Visual Basic software we have developed to process sediment data (Poppe et al., 2003, 2004).

Infant Mortality: Development of a Proposed Update to the Dollfus Classification of Infant Deaths

PubMed Central

Dove, Melanie S.; Minnal, Archana; Damesyn, Mark; Curtis, Michael P.

2015-01-01

Objective Identifying infant deaths with common underlying causes and potential intervention points is critical to infant mortality surveillance and the development of prevention strategies. We constructed an International Classification of Diseases 10th Revision (ICD-10) parallel to the Dollfus cause-of-death classification scheme first published in 1990, which organized infant deaths by etiology and their amenability to prevention efforts. Methods Infant death records for 1996, dual-coded to the ICD Ninth Revision (ICD-9) and ICD-10, were obtained from the CDC public-use multiple-cause-of-death file on comparability between ICD-9 and ICD-10. We used the underlying cause of death to group 27,821 infant deaths into the nine categories of the ICD-9-based update to Dollfus' original coding scheme, published by Sowards in 1999. Comparability ratios were computed to measure concordance between ICD versions. Results The Dollfus classification system updated with ICD-10 codes had limited agreement with the 1999 modified classification system. Although prematurity, congenital malformations, Sudden Infant Death Syndrome, and obstetric conditions were the first through fourth most common causes of infant death under both systems, most comparability ratios were significantly different from one system to the other. Conclusion The Dollfus classification system can be adapted for use with ICD-10 codes to create a comprehensive, etiology-based profile of infant deaths. The potential benefits of using Dollfus logic to guide perinatal mortality reduction strategies, particularly to maternal and child health programs and other initiatives focused on improving infant health, warrant further examination of this method's use in perinatal mortality surveillance. PMID:26556935

Prediction of the Chloride Resistance of Concrete Modified with High Calcium Fly Ash Using Machine Learning

PubMed Central

Marks, Michał; Glinicki, Michał A.; Gibas, Karolina

2015-01-01

The aim of the study was to generate rules for the prediction of the chloride resistance of concrete modified with high calcium fly ash using machine learning methods. The rapid chloride permeability test, according to the Nordtest Method Build 492, was used for determining the chloride ions’ penetration in concrete containing high calcium fly ash (HCFA) for partial replacement of Portland cement. The results of the performed tests were used as the training set to generate rules describing the relation between material composition and the chloride resistance. Multiple methods for rule generation were applied and compared. The rules generated by algorithm J48 from the Weka workbench provided the means for adequate classification of plain concretes and concretes modified with high calcium fly ash as materials of good, acceptable or unacceptable resistance to chloride penetration. PMID:28793740

Application of local binary pattern and human visual Fibonacci texture features for classification different medical images

NASA Astrophysics Data System (ADS)

Sanghavi, Foram; Agaian, Sos

2017-05-01

The goal of this paper is to (a) test the nuclei based Computer Aided Cancer Detection system using Human Visual based system on the histopathology images and (b) Compare the results of the proposed system with the Local Binary Pattern and modified Fibonacci -p pattern systems. The system performance is evaluated using different parameters such as accuracy, specificity, sensitivity, positive predictive value, and negative predictive value on 251 prostate histopathology images. The accuracy of 96.69% was observed for cancer detection using the proposed human visual based system compared to 87.42% and 94.70% observed for Local Binary patterns and the modified Fibonacci p patterns.

Micro/nano-particles and Cells: Manipulation, Transport, and Self-assembly

DTIC Science & Technology

2014-10-23

SECURITY CLASSIFICATION OF: Technologies that control nano- and micron- sized inert as well as biological materials are crucial to realizing engineered...that control nano- and micron- sized inert as well as biological materials are crucial to realizing engineered systems that can assemble, transport, and...nano-scale particles offer several advantages as building blocks of artificial materials . The relative ease of modifying their charge states

The Servicemembers Civil Relief Act (P.L. 108-189)

DTIC Science & Technology

2004-04-20

Remedies 22 Inappropriate use of the Act 22 Certification 22 Interlocutory orders 22 VII Further Relief 22 Anticipatory relief 22 Extension of power of...distribution unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT UU 18. NUMBER...that has been subject to differing interpretations by courts and modifies or expands certain benefits The SCRA provides protections for

Beyond Nomothetic Classification of Behavioural Difficulties: Using Valued Outcomes Analysis to Deal with the Behaviour Problems that Occur in the Classroom

ERIC Educational Resources Information Center

Bitsika, Vicki

2005-01-01

The number of students who are labeled as having some form of behavioural disorder which requires specialized assistance in the regular school setting is growing. Current approaches to working with these students are often based on the standardized application of treatments designed to modify general symptoms rather than specific behaviours. It is…

Simulated bi-SQUID Arrays Performing Direction Finding

DTIC Science & Technology

2015-09-01

First, we applied the multiple signal classification ( MUSIC ) algorithm on linearly polarized signals. We included multiple signals in the output...both of the same frequency and different fre- quencies. Next, we explored a modified MUSIC algorithm called dimensionality reduction MUSIC (DR- MUSIC ... MUSIC algorithm is able to determine the AoA from the simulated SQUID data for linearly polarized signals. The MUSIC algorithm could accurately find

A modified tree classification for use in growth studies and timber marking in Black Hills ponderosa pine

Treesearch

E. M. Hornibrook

1939-01-01

A satisfactory silvicultural management of ponderosa pine stands requires a judicious selection of trees to be left in the reserve stand. The timber marker must know what type of tree has the greatest growth potentialities and what type of tree will respond but slightly upon being released. The silvicultural problem in marking therefore is one of recognizing the...

HMM-ModE: implementation, benchmarking and validation with HMMER3

PubMed Central

2014-01-01

Background HMM-ModE is a computational method that generates family specific profile HMMs using negative training sequences. The method optimizes the discrimination threshold using 10 fold cross validation and modifies the emission probabilities of profiles to reduce common fold based signals shared with other sub-families. The protocol depends on the program HMMER for HMM profile building and sequence database searching. The recent release of HMMER3 has improved database search speed by several orders of magnitude, allowing for the large scale deployment of the method in sequence annotation projects. We have rewritten our existing scripts both at the level of parsing the HMM profiles and modifying emission probabilities to upgrade HMM-ModE using HMMER3 that takes advantage of its probabilistic inference with high computational speed. The method is benchmarked and tested on GPCR dataset as an accurate and fast method for functional annotation. Results The implementation of this method, which now works with HMMER3, is benchmarked with the earlier version of HMMER, to show that the effect of local-local alignments is marked only in the case of profiles containing a large number of discontinuous match states. The method is tested on a gold standard set of families and we have reported a significant reduction in the number of false positive hits over the default HMM profiles. When implemented on GPCR sequences, the results showed an improvement in the accuracy of classification compared with other methods used to classify the familyat different levels of their classification hierarchy. Conclusions The present findings show that the new version of HMM-ModE is a highly specific method used to differentiate between fold (superfamily) and function (family) specific signals, which helps in the functional annotation of protein sequences. The use of modified profile HMMs of GPCR sequences provides a simple yet highly specific method for classification of the family, being able to predict the sub-family specific sequences with high accuracy even though sequences share common physicochemical characteristics between sub-families. PMID:25073805

Assessment of text documentation accompanying uncoded diagnoses in computerized health insurance claims in Japan.

PubMed

Tanihara, Shinichi

2015-01-01

Uncoded diagnoses in health insurance claims (HICs) may introduce bias into Japanese health statistics dependent on computerized HICs. This study's aim was to identify the causes and characteristics of uncoded diagnoses. Uncoded diagnoses from computerized HICs (outpatient, inpatient, and the diagnosis procedure-combination per-diem payment system [DPC/PDPS]) submitted to the National Health Insurance Organization of Kumamoto Prefecture in May 2010 were analyzed. The text documentation accompanying the uncoded diagnoses was used to classify diagnoses in accordance with the International Classification of Diseases-10 (ICD-10). The text documentation was also classified into four categories using the standard descriptions of diagnoses defined in the master files of the computerized HIC system: 1) standard descriptions of diagnoses, 2) standard descriptions with a modifier, 3) non-standard descriptions of diagnoses, and 4) unclassifiable text documentation. Using these classifications, the proportions of uncoded diagnoses by ICD-10 disease category were calculated. Of the uncoded diagnoses analyzed (n = 363 753), non-standard descriptions of diagnoses for outpatient, inpatient, and DPC/PDPS HICs comprised 12.1%, 14.6%, and 1.0% of uncoded diagnoses, respectively. The proportion of uncoded diagnoses with standard descriptions with a modifier for Diseases of the eye and adnexa was significantly higher than the overall proportion of uncoded diagnoses among every HIC type. The pattern of uncoded diagnoses differed by HIC type and disease category. Evaluating the proportion of uncoded diagnoses in all medical facilities and developing effective coding methods for diagnoses with modifiers, prefixes, and suffixes should reduce number of uncoded diagnoses in computerized HICs and improve the quality of HIC databases.

Mechanisms of starch digestion by α-amylase-Structural basis for kinetic properties.

PubMed

Dhital, Sushil; Warren, Frederick J; Butterworth, Peter J; Ellis, Peter R; Gidley, Michael J

2017-03-24

Recent studies of the mechanisms determining the rate and extent of starch digestion by α-amylase are reviewed in the light of current widely-used classifications for (a) the proportions of rapidly-digestible (RDS), slowly-digestible (SDS), and resistant starch (RS) based on in vitro digestibility, and (b) the types of resistant starch (RS 1,2,3,4…) based on physical and/or chemical form. Based on methodological advances and new mechanistic insights, it is proposed that both classification systems should be modified. Kinetic analysis of digestion profiles provides a robust set of parameters that should replace the classification of starch as a combination of RDS, SDS, and RS from a single enzyme digestion experiment. This should involve determination of the minimum number of kinetic processes needed to describe the full digestion profile, together with the proportion of starch involved in each process, and the kinetic properties of each process. The current classification of resistant starch types as RS1,2,3,4 should be replaced by one which recognizes the essential kinetic nature of RS (enzyme digestion rate vs. small intestinal passage rate), and that there are two fundamental origins for resistance based on (i) rate-determining access/binding of enzyme to substrate and (ii) rate-determining conversion of substrate to product once bound.

FHR patterns that become significant in connection with ST waveform changes and metabolic acidosis at birth.

PubMed

Rosén, Karl G; Norén, Håkan; Carlsson, Ann

2018-04-18

Recent developments have produced new CTG classification systems and the question is to what extent these may affect the model of FHR + ST interpretation? The two new systems (FIGO2015 and SSOG2017) classify FHR + ST events differently from the current CTG classification system used in the STAN interpretation algorithm (STAN2007). Identify the predominant FHR patterns in connection with ST events in cases of cord artery metabolic acidosis missed by the different CTG classification systems. Indicate to what extent STAN clinical guidelines could be modified enhancing the sensitivity. Provide a pathophysiological rationale. Forty-four cases with umbilical cord artery metabolic acidosis were retrieved from a European multicenter database. Significant FHR + ST events were evaluated post hoc in consensus by an expert panel. Eighteen cases were not identified as in need of intervention and regarded as negative in the sensitivity analysis. In 12 cases, ST changes occurred but the CTG was regarded as reassuring. Visual analysis of the FHR + ST tracings revealed specific FHR patterns: Conclusion: These findings indicate FHR + ST analysis may be undertaken regardless of CTG classification system provided there is a more physiologically oriented approach to FHR assessment in connection with an ST event.

Revised terminology and concepts for organization of seizures and epilepsies: report of the ILAE Commission on Classification and Terminology, 2005-2009.

PubMed

Berg, Anne T; Berkovic, Samuel F; Brodie, Martin J; Buchhalter, Jeffrey; Cross, J Helen; van Emde Boas, Walter; Engel, Jerome; French, Jacqueline; Glauser, Tracy A; Mathern, Gary W; Moshé, Solomon L; Nordli, Douglas; Plouin, Perrine; Scheffer, Ingrid E

2010-04-01

The International League Against Epilepsy (ILAE) Commission on Classification and Terminology has revised concepts, terminology, and approaches for classifying seizures and forms of epilepsy. Generalized and focal are redefined for seizures as occurring in and rapidly engaging bilaterally distributed networks (generalized) and within networks limited to one hemisphere and either discretely localized or more widely distributed (focal). Classification of generalized seizures is simplified. No natural classification for focal seizures exists; focal seizures should be described according to their manifestations (e.g., dyscognitive, focal motor). The concepts of generalized and focal do not apply to electroclinical syndromes. Genetic, structural-metabolic, and unknown represent modified concepts to replace idiopathic, symptomatic, and cryptogenic. Not all epilepsies are recognized as electroclinical syndromes. Organization of forms of epilepsy is first by specificity: electroclinical syndromes, nonsyndromic epilepsies with structural-metabolic causes, and epilepsies of unknown cause. Further organization within these divisions can be accomplished in a flexible manner depending on purpose. Natural classes (e.g., specific underlying cause, age at onset, associated seizure type), or pragmatic groupings (e.g., epileptic encephalopathies, self-limited electroclinical syndromes) may serve as the basis for organizing knowledge about recognized forms of epilepsy and facilitate identification of new forms.

Is a diagnosis of metabolic syndrome applicable to children?

PubMed

Pergher, Rafael Nardini Queiroz; Melo, Maria Edna de; Halpern, Alfredo; Mancini, Marcio Corrêa

2010-01-01

To present the components of the metabolic syndrome in children and adolescents and to discuss how they are assessed in the pediatric population in addition to presenting the major metabolic syndrome classifications for the age group. A review of literature published from 1986 to 2008 and found on MEDLINE databases. The prevalence of childhood obesity has been increasing globally over recent decades and as a result its complications, such as diabetes mellitus, arterial hypertension and dyslipidemia, have also increased. The concept of metabolic syndrome, already common with adults, is now beginning to be applied to children through classifications using the criteria for adults modified for the younger age group. Notwithstanding, these classifications differ in terms of the cutoff points used and whether they employ body mass index or waist circumference to define obesity. The review presents these classifications, highlighting the points on which they differ and the debate about them. If childhood obesity goes untreated, it will have severe consequences in the future. A number of models for classifying metabolic syndrome in children have been published, but there is considerable diversions between them. The criteria for classifying metabolic syndrome in children therefore need to be standardized in order to identify those people at greatest risk of future complications.

Application of principal component analysis to distinguish patients with schizophrenia from healthy controls based on fractional anisotropy measurements.

PubMed

Caprihan, A; Pearlson, G D; Calhoun, V D

2008-08-15

Principal component analysis (PCA) is often used to reduce the dimension of data before applying more sophisticated data analysis methods such as non-linear classification algorithms or independent component analysis. This practice is based on selecting components corresponding to the largest eigenvalues. If the ultimate goal is separation of data in two groups, then these set of components need not have the most discriminatory power. We measured the distance between two such populations using Mahalanobis distance and chose the eigenvectors to maximize it, a modified PCA method, which we call the discriminant PCA (DPCA). DPCA was applied to diffusion tensor-based fractional anisotropy images to distinguish age-matched schizophrenia subjects from healthy controls. The performance of the proposed method was evaluated by the one-leave-out method. We show that for this fractional anisotropy data set, the classification error with 60 components was close to the minimum error and that the Mahalanobis distance was twice as large with DPCA, than with PCA. Finally, by masking the discriminant function with the white matter tracts of the Johns Hopkins University atlas, we identified left superior longitudinal fasciculus as the tract which gave the least classification error. In addition, with six optimally chosen tracts the classification error was zero.

Plaque Burden Influences Accurate Classification of Fibrous Cap Atheroma by In-Vivo Optical Coherence Tomography in a Porcine Model of Advanced Coronary Atherosclerosis.

PubMed

Poulsen, Christian B; Pedrigi, Ryan M; Pareek, Nilesh; Kilic, Ismail D; Holm, Niels Ramsing; Bentzon, Jacob F; Bøtker, Hans Erik; Falk, Erling; Krams, Rob; de Silva, Ranil

2018-04-03

In-vivo validation of coronary optical coherence tomography (OCT) against histology and the effects of plaque burden (PB) on plaque classification remain unreported. We investigated this in a porcine model with human-like coronary atherosclerosis. Five female Yucatan D374Y-PCSK9 transgenic hypercholesterolemic mini-pigs were implanted with a coronary shear-modifying stent to induce advanced atherosclerosis. OCT frames (n=201) were obtained 34 weeks after implantation. Coronary arteries were perfusion-fixed, serially sectioned and co-registered with OCT using a validated algorithm. Lesions were adjudicated using the Virmani classification and PB assessed from histology. OCT had a high sensitivity, but modest specificity (92.9% and 74.6%), for identifying fibrous cap atheroma (FCA). The reduced specificity for OCT was due to misclassification of plaques with histologically defined pathological intimal thickening (PIT) as FCA (46.1% of the frames with histological PIT were misclassified). PIT lesions misclassified as FCA by OCT had a statistically higher PB than in other OCT frames (median 32.0% versus 13.4%; p<0.0001). Misclassification of PIT lesions by OCT occurred when PB exceeded approximately 20%. Compared with histology, in-vivo OCT classification of FCA had high sensitivity but reduced specificity due to misclassification of PITs with high PB.

The DeBakey classification exactly reflects late outcome and re-intervention probability in acute aortic dissection with a slightly modified type II definition.

PubMed

Tsagakis, Konstantinos; Tossios, Paschalis; Kamler, Markus; Benedik, Jaroslav; Natour, Dorgam; Eggebrecht, Holger; Piotrowski, Jarowit; Jakob, Heinz

2011-11-01

The DeBakey classification was used to discriminate the extent of acute aortic dissection (AD) and was correlated to long-term outcome and re-intervention rate. A slight modification of type II subgroup definition was applied by incorporating the aortic arch, when full resectability of the dissection process was given. Between January 2001 and March 2010, 118 patients (64% male, mean age 59 years) underwent surgery for acute AD. As many as 74 were operated on for type I and 44 for type II AD. Complete resection of all entry sites was performed, including antegrade stent grafting for proximal descending lesions. Patients were comparable with respect to demographics and preoperative hemodynamic status. They underwent isolated ascending replacement, hemiarch, or total arch replacement in 7%, 26%, and 67% in type I, versus 27%, 37%, and 36% in type II, respectively. Additional descending stent grafting was performed in 33/74 (45%) type I patients. In-hospital mortality was 14%, 16% (12/74) in type I versus 9% (4/44, type II), p=0.405. After 5 years, the estimated survival rate was 63% in type I versus 80% in type II, p=0.135. In type II, no distal aortic re-intervention was required. In type I, the freedom of distal re-interventions was 82% in patients with additional stent grafting versus 53% in patients without, p=0.022. The slightly modified DeBakey classification exactly reflects late outcome and aortic re-intervention probability. Thus, in type II patients, the aorta seems to be healed without any probability of later re-operation or re-intervention. Copyright © 2011 European Association for Cardio-Thoracic Surgery. Published by Elsevier B.V. All rights reserved.

Histopathological features of coeliac disease in a sample of Sudanese patients.

PubMed

Mokhtar, M A N; Mekki, S O; Mudawi, H M Y; Sulaiman, S H; Tahir, M A; Tigani, M A; Omer, I A; Yousif, B M; Fragalla, I A; Mohammed, Z; Dafaalla, M

2016-12-01

Coeliac disease can occur at any age but is more common in children. Its diagnosis requires correlation between clinical presentations, serological results, endoscopic findings and histopathological classification using the modified Marsh grading system. This study of coeliac disease with biopsies received in the department of histopathology at Soba University Hospital, and Fedail Hospital aimed to gain insight into the demographic profile, clinical presentations and histopathological classification of patients with coeliac disease. This was a descriptive study carried out at Soba University Hospital and Fedail Hospital during the period from January 2010-December 2013. Haematoxylin & Eosin and CD3-stained slides of small intestinal biopsies of coeliac disease patients were reviewed for various histological features (1) intraepithelial lymphocytes (IEL) count per 100 enterocytes, (2) crypt hyperplasia and (3) degree of villous atrophy. Based on the histopathological findings, the cases were categorized according to the modified Marsh classification. Demographic and clinical data were obtained from the patient request forms. The data were analyzed using Statistical Package for Social Sciences Software (SPSS). The study included 60 patients. Their age ranged from 2 to 70 years with a mean of 19.5 years (±15.7 SD). The most common age group was below 10 years old (41.6%). Male and female are equally affected. The most common clinical presentation was chronic diarrhoea (55.0%), followed by iron deficiency anemia (41.7%). The degree of villous atrophy ranged from complete atrophy (45.0%), marked atrophy (38.3%) to mild atrophy (16.6%). Marsh grade IIIC was the most common grade. The younger age-groups had a higher prevalence of iron deficiency anaemia and higher Marsh grade.

[Histological diagnosis and complications of celiac disease. Update according to the new S2k guidelines].

PubMed

Aust, D E; Bläker, H

2015-03-01

Celiac disease is a relatively common immunological systemic disease triggered by the protein gluten in genetically predisposed individuals. Classical symptoms like chronic diarrhea, steatorrhea, weight loss and growth retardation are nowadays relatively uncommon. Diagnostic workup includes serological tests for IgA antibodies against tissue transglutaminase 2 (anti-TG2-IgA) and total IgA and histology of duodenal biopsies. Histomorphological classification should be done according to the modified Marsh-Oberhuber classification. Diagnosis of celiac disease should be based on serological, clinical, and histological findings. The only treatment is a life-long gluten-free diet. Unchanged or recurrent symptoms under gluten-free diet may indicate refractory celiac disease. Enteropathy-associated T-cell lymphoma and adenocarcinomas of the small intestine are known complications of celiac disease.

Detection, localization and classification of multiple dipole-like magnetic sources using magnetic gradient tensor data

NASA Astrophysics Data System (ADS)

Gang, Yin; Yingtang, Zhang; Hongbo, Fan; Zhining, Li; Guoquan, Ren

2016-05-01

We have developed a method for automatic detection, localization and classification (DLC) of multiple dipole sources using magnetic gradient tensor data. First, we define modified tilt angles to estimate the approximate horizontal locations of the multiple dipole-like magnetic sources simultaneously and detect the number of magnetic sources using a fixed threshold. Secondly, based on the isotropy of the normalized source strength (NSS) response of a dipole, we obtain accurate horizontal locations of the dipoles. Then the vertical locations are calculated using magnitude magnetic transforms of magnetic gradient tensor data. Finally, we invert for the magnetic moments of the sources using the measured magnetic gradient tensor data and forward model. Synthetic and field data sets demonstrate effectiveness and practicality of the proposed method.

Automated Analysis, Classification, and Display of Waveforms

NASA Technical Reports Server (NTRS)

Kwan, Chiman; Xu, Roger; Mayhew, David; Zhang, Frank; Zide, Alan; Bonggren, Jeff

2004-01-01

A computer program partly automates the analysis, classification, and display of waveforms represented by digital samples. In the original application for which the program was developed, the raw waveform data to be analyzed by the program are acquired from space-shuttle auxiliary power units (APUs) at a sampling rate of 100 Hz. The program could also be modified for application to other waveforms -- for example, electrocardiograms. The program begins by performing principal-component analysis (PCA) of 50 normal-mode APU waveforms. Each waveform is segmented. A covariance matrix is formed by use of the segmented waveforms. Three eigenvectors corresponding to three principal components are calculated. To generate features, each waveform is then projected onto the eigenvectors. These features are displayed on a three-dimensional diagram, facilitating the visualization of the trend of APU operations.

[Management of children with headache in a Pediatric Emergency Department before and after the introduction of the Second International Classification of Headache Disorders (ICHD-II)].

PubMed

Gioachin, Anna; Fiumana, Elisa; Tarocco, Anna; Verzola, Adriano; Forini, Elena; Guerra, Valentina; Salani, Manuela; Faggioli, Raffaella

2013-03-01

The aim of this study was to evaluate how the management of children admitted with headache to a Pediatric Emergency Department, was modified by the introduction of the Second International Classification of Headache Disorders ( ICHD-II) published in 2004. The complexity and average costs of the services provided to patients in 2002 and 2011 were compared. The results revealed a decrease in the number of tests performed and in-hospital admissions. However, tests were more complex, and an increase in requests of specialist advice was observed. We hypothesized that this change may be related to the introduction of ICHD-II, which suggests a more rational approach to the child with headache and a better use of hospital resources.

Applying the International Classification of Functioning, Disability and Health to guide home health care services planning and delivery in Thailand.

PubMed

Pimdee, Atipong; Nualnetr, Nomjit

2017-01-01

Home health care is an essential service for home-bound patients in Thailand. In this action research study, we used the International Classification of Functioning, Disability and Health (ICF) framework to modify home health care services provided by a university hospital. Staff responsible for delivering the services (physical therapist, nurses, and Thai traditional medicine practitioners) participated in the development of an ICF-based assessment tool and home health care service procedure. After an 8-month trial of implementing these changes, professional satisfaction and empowerment were high among the home health care team members. Patients and their caregivers were also satisfied with the services. In conclusion, the ICF is an effective means of guiding home health care.

Study of phase clustering method for analyzing large volumes of meteorological observation data

NASA Astrophysics Data System (ADS)

Volkov, Yu. V.; Krutikov, V. A.; Botygin, I. A.; Sherstnev, V. S.; Sherstneva, A. I.

2017-11-01

The article describes an iterative parallel phase grouping algorithm for temperature field classification. The algorithm is based on modified method of structure forming by using analytic signal. The developed method allows to solve tasks of climate classification as well as climatic zoning for any time or spatial scale. When used to surface temperature measurement series, the developed algorithm allows to find climatic structures with correlated changes of temperature field, to make conclusion on climate uniformity in a given area and to overview climate changes over time by analyzing offset in type groups. The information on climate type groups specific for selected geographical areas is expanded by genetic scheme of class distribution depending on change in mutual correlation level between ground temperature monthly average.

Visible spectroscopy as a tool for the assessment of storage conditions of fresh pork packaged in modified atmosphere.

PubMed

Spanos, Dimitrios; Christensen, Mette; Tørngren, Mari Ann; Baron, Caroline P

2016-03-01

The storage conditions of fresh meat are known to impact its colour and microbial shelf life. In the present study, visible spectroscopy was evaluated as a method to assess meat storage conditions and its optimisation. Fresh pork steaks (longissimus thoracis et lumborum and semimembranosus) were placed in modified atmosphere packaging using gas mixtures containing 0, 40, 50, and 80% oxygen, and stored with or without light for up to 9days. Principal component analysis of visible reflectance spectra (400-700nm) showed that the colour of the different meat cuts was affected by presence of oxygen, illumination, and storage time. Differences in the oxygen levels did not contribute to the observed variance. Predictive models based on partial least squares regression-discriminant analysis exhibited high potency in the classification of the storage parameters of meat cuts packaged in modified atmosphere. The study demonstrates the applicability of visible spectroscopy as a tool to assess the storage conditions of meat cuts packaged in modified atmosphere. Copyright © 2015 Elsevier Ltd. All rights reserved.

Iris double recognition based on modified evolutionary neural network

NASA Astrophysics Data System (ADS)

Liu, Shuai; Liu, Yuan-Ning; Zhu, Xiao-Dong; Huo, Guang; Liu, Wen-Tao; Feng, Jia-Kai

2017-11-01

Aiming at multicategory iris recognition under illumination and noise interference, this paper proposes a method of iris double recognition based on a modified evolutionary neural network. An equalization histogram and Laplace of Gaussian operator are used to process the iris to suppress illumination and noise interference and Haar wavelet to convert the iris feature to binary feature encoding. Calculate the Hamming distance for the test iris and template iris , and compare with classification threshold, determine the type of iris. If the iris cannot be identified as a different type, there needs to be a secondary recognition. The connection weights in back-propagation (BP) neural network use modified evolutionary neural network to adaptively train. The modified neural network is composed of particle swarm optimization with mutation operator and BP neural network. According to different iris libraries in different circumstances of experimental results, under illumination and noise interference, the correct recognition rate of this algorithm is higher, the ROC curve is closer to the coordinate axis, the training and recognition time is shorter, and the stability and the robustness are better.

Physiotherapy movement based classification approaches to low back pain: comparison of subgroups through review and developer/expert survey.

PubMed

Karayannis, Nicholas V; Jull, Gwendolen A; Hodges, Paul W

2012-02-20

Several classification schemes, each with its own philosophy and categorizing method, subgroup low back pain (LBP) patients with the intent to guide treatment. Physiotherapy derived schemes usually have a movement impairment focus, but the extent to which other biological, psychological, and social factors of pain are encompassed requires exploration. Furthermore, within the prevailing 'biological' domain, the overlap of subgrouping strategies within the orthopaedic examination remains unexplored. The aim of this study was "to review and clarify through developer/expert survey, the theoretical basis and content of physical movement classification schemes, determine their relative reliability and similarities/differences, and to consider the extent of incorporation of the bio-psycho-social framework within the schemes". A database search for relevant articles related to LBP and subgrouping or classification was conducted. Five dominant movement-based schemes were identified: Mechanical Diagnosis and Treatment (MDT), Treatment Based Classification (TBC), Pathoanatomic Based Classification (PBC), Movement System Impairment Classification (MSI), and O'Sullivan Classification System (OCS) schemes. Data were extracted and a survey sent to the classification scheme developers/experts to clarify operational criteria, reliability, decision-making, and converging/diverging elements between schemes. Survey results were integrated into the review and approval obtained for accuracy. Considerable diversity exists between schemes in how movement informs subgrouping and in the consideration of broader neurosensory, cognitive, emotional, and behavioural dimensions of LBP. Despite differences in assessment philosophy, a common element lies in their objective to identify a movement pattern related to a pain reduction strategy. Two dominant movement paradigms emerge: (i) loading strategies (MDT, TBC, PBC) aimed at eliciting a phenomenon of centralisation of symptoms; and (ii) modified movement strategies (MSI, OCS) targeted towards documenting the movement impairments associated with the pain state. Schemes vary on: the extent to which loading strategies are pursued; the assessment of movement dysfunction; and advocated treatment approaches. A biomechanical assessment predominates in the majority of schemes (MDT, PBC, MSI), certain psychosocial aspects (fear-avoidance) are considered in the TBC scheme, certain neurophysiologic (central versus peripherally mediated pain states) and psychosocial (cognitive and behavioural) aspects are considered in the OCS scheme.

Draft Specification of the Common APSE (Ada Programming Support Environments) Interface Set (CAIS). Version 1.1.

DTIC Science & Technology

1983-09-30

Ideally, all APSE tools DD, vLAm 147 COTON or I NOv 66is oSwLEtEaUCASII SN )02 IF St. 06,SECURITY CLASSIFICATION Of THIS 1PAG9 (ft;..Data X-014 I.N...has finished all the modifications/entries that are desired, the user presses a special key (function key or enter key) which causes the modified

Congenital spinal malformations in small animals.

PubMed

Westworth, Diccon R; Sturges, Beverly K

2010-09-01

Congenital anomalies of the spine are common in small animals. The type of deformity, location, severity, time of onset of associated clinical signs, and progression of neurologic dysfunction varies widely. To promote clearer understanding, the authors present the various spinal malformations using modified human classification schemes and use current widely accepted definitions and terminology. The diagnostic approach, including utilization of advanced imaging, and surgical management is emphasized. Copyright 2010. Published by Elsevier Inc.

Characterization of Biofouling Marine Caulobacters and Their Adhesive Holdfast

DTIC Science & Technology

1988-06-30

SAD-A 197 211 _, 111 3 CEILL GJU JREPORT DOCUMENTATION PAGE la. REPORT SECURITY CLASSIFiCATION ’b RESTRICTIVE MARKIN6, S U 1 2a. SECURITY...what types of surfaces to which the Caulobacters will attach. This was approached by the preparation of glass surfaces covalently modified with a...finding that dimethyldichlorosilane treated glass (ie classical "silanizing") was reasonably effective in discouraging attachment, a convenience for many

Development and Testing of a Multiple Frequency Continuous Wave Radar for Target Detection and Classification

DTIC Science & Technology

2007-03-01

1 2’ VIH " 1 ’ 󈧏) (34) where is the modified Bessel function of zero order. Here is the conditional variance and is the conditional probability...10, the probability of detection is the area under the signal-plus-noise curve above the detection threshold co M vF (V 2+ A2)]10 ( vAPd= fnp~ju,( vIH

Filing Reprints: A Simple System For The Family Physician

PubMed Central

Berner, Mark

1978-01-01

This flexible method of filing medical literature without using cards is based on the International Classification of Health Problems in Primary Care. 1Articles, reprints, notes of lectures and rounds, etc. are filed in manilla folders according to a few simple guidelines. This system has proved to be practical and efficient, can be modified for individual needs, and once established requires little time to maintain. PMID:20469289

Air Force Personnel Research Issues: A Manager’s Handbook

DTIC Science & Technology

2007-09-01

training and recruiting issues. Revisions were published in the classification regulation in April 1982. Eventually, aptitude requirements were modified...system that had been used by the Army. In 1950, the first regulation was published for promotions and demotions (AFR 39-30), but the location of...promotion authority for different enlisted grades changed many times over the years. Selection boards were first mentioned in a 1959 regulation , but

Development of a Novel Treatment for Food Allergy Using a New Genetically Defined Mouse Model of the Disease

DTIC Science & Technology

2012-07-01

peanut allergy, and whether treatment with losartan , an angiotensin II (ATII) receptor blocker that inhibits TGFbeta signaling, reduces the development...increased effector responses, or both. We will also examine how treatment with losartan modifies the allergic phenotype in LDS mice. 15...SUBJECT TERMS Loeys Dietz Syndrome, food allergy, eosinophilic esophagitis, anaphylaxis, TGFbeta, losartan 16. SECURITY CLASSIFICATION OF: 17

The Effect of Interactive Simulations on Exercise Adherence with Overweight and Obese Adults

DTIC Science & Technology

2009-12-01

integrated video game play capabilities was developed. Unique software was written and further modified to integrate the exercise equipment/ video game ...exercise bicycle with video gaming console 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER OF PAGES 19a. NAME OF... video game play on exercise adherence, exercise motivation , and self-efficacy in overweight and obese Army personnel. Despite being younger. less

Categorization of ureteroscopy complications and investigation of associated factors by using the modified Clavien classification system.

PubMed

Öğreden, Ercan; Oğuz, Ural; Demirelli, Erhan; Benli, Erdal; Sancak, Eyüp Burak; Gülpinar, Murat Tolga; Akbaş, Alpaslan; Reşorlu, Berkan; Ayyildiz, Ali; Yalçin, Orhan

2016-04-19

The purpose of the present study was to review the complications of ureteroscopy (URS) by using the modified Clavien classification system (MCCS) and to investigate the factors associated with complications. Data regarding 811 patients who underwent URS for ureteral calculus were analyzed. Peroperative and postoperative complications were recorded. The patients were divided into seven groups depending on the severity of the complications. The association of sex, stone size, number, and localization with each MCCS grade was also evaluated. The average age was 45 years. The success of the procedure after one session was 93.5%. Complications were recorded in 57.9% of the patients. According to the MCCS, grade I, II, IIIa, IIIb, IVa, IVb, and V complications were documented in 29.8%, 7.1%, 8.6%, 11%, 0%, 1.2%, and 0% of the patients, respectively. The factors associated with the complications graded by MCCS were sex, stone size, number of stones, and localization. In addition, in multivariate analysis, history of previous surgeries for urolithiasis, orifice dilatation, and instrument size were associated with complications. According to MCCS, sex, history of previous surgeries for urolithiasis, orifice dilatation, size of the instrument, stone size, number of stones, and localization are associated with different grades of complications in URS.

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

USGS Publications Warehouse

Latifovic, Rasim; Zhu, Zhi-Liang

2004-01-01

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

Modified Cut-Off Value of the Urine Protein-To-Creatinine Ratio Is Helpful for Identifying Patients at High Risk for Chronic Kidney Disease: Validation of the Revised Japanese Guideline.

PubMed

Yamamoto, Hiroyuki; Yamamoto, Kyoko; Yoshida, Katsumi; Shindoh, Chiyohiko; Takeda, Kyoko; Monden, Masami; Izumo, Hiroko; Niinuma, Hiroyuki; Nishi, Yutaro; Niwa, Koichiro; Komatsu, Yasuhiro

2015-11-01

Chronic kidney disease (CKD) is a global public health issue, and strategies for its early detection and intervention are imperative. The latest Japanese CKD guideline recommends that patients without diabetes should be classified using the urine protein-to-creatinine ratio (PCR) instead of the urine albumin-to-creatinine ratio (ACR); however, no validation studies are available. This study aimed to validate the PCR-based CKD risk classification compared with the ACR-based classification and to explore more accurate classification methods. We analyzed two previously reported datasets that included diabetic and/or cardiovascular patients who were classified into early CKD stages. In total, 860 patients (131 diabetic patients and 729 cardiovascular patients, including 193 diabetic patients) were enrolled. We assessed the CKD risk classification of each patient according to the estimated glomerular filtration rate and the ACR-based or PCR-based classification. The use of the cut-off value recommended in the current guideline (PCR 0.15 g/g creatinine) resulted in risk misclassification rates of 26.0% and 16.6% for the two datasets. The misclassification was primarily caused by underestimation. Moderate to substantial agreement between each classification was achieved: Cohen's kappa, 0.56 (95% confidence interval, 0.45-0.69) and 0.72 (0.67-0.76) in each dataset, respectively. To improve the accuracy, we tested various candidate PCR cut-off values, showing that a PCR cut-off value of 0.08-0.10 g/g creatinine resulted in improvement in the misclassification rates and kappa values. Modification of the PCR cut-off value would improve its efficacy to identify high-risk populations who will benefit from early intervention.

[Multidisciplinar international classification of the severity of acute pancreatitis: Italian version 2013].

PubMed

Uomo, G; Patchen Dellinger, E; Forsmark, C E; Layer, P; Lévy, P; Maravì-Poma, E; Shimosegawa, T; Siriwardena, A K; Whitcomb, D C; Windsor, J A; Petrov, M S

2013-12-01

The aim of this paper was to present the 2013 Italian edition of a new international classification of acute pancreatitis severity. The Atlanta definitions of acute pancreatitis severity are ingrained in the lexicon of pancreatologists but suboptimal because these definitions are based on empiric description of occurrences that are merely associated with severity. A personal invitation to contribute to the development of a new international classification of acute pancreatitis severity was sent to all surgeons, gastroenterologists, internists, intensivists, and radiologists who are currently active in clinical research on acute pancreatitis. A global web-based survey was conducted and a dedicated international symposium was organized to bring contributors from different disciplines together and discuss the concept and definitions. The new international classification is based on the actual local and systemic determinants of severity, rather than description of events that are correlated with severity. The local determinant relates to whether there is (peri)pancreatic necrosis or not, and if present, whether it is sterile or infected. The systemic determinant relates to whether there is organ failure or not, and if present, whether it is transient or persistent. The presence of one determinant can modify the effect of another such that the presence of both infected (peri)pancreatic necrosis and persistent organ failure have a greater effect on severity than either determinant alone. The derivation of a classification based on the above principles results in 4 categories of severity-mild, moderate, severe, and critical. This classification provides a set of concise up-to-date definitions of all the main entities pertinent to classifying the severity of acute pancreatitis in clinical practice and research.

Active learning methods for interactive image retrieval.

PubMed

Gosselin, Philippe Henri; Cord, Matthieu

2008-07-01

Active learning methods have been considered with increased interest in the statistical learning community. Initially developed within a classification framework, a lot of extensions are now being proposed to handle multimedia applications. This paper provides algorithms within a statistical framework to extend active learning for online content-based image retrieval (CBIR). The classification framework is presented with experiments to compare several powerful classification techniques in this information retrieval context. Focusing on interactive methods, active learning strategy is then described. The limitations of this approach for CBIR are emphasized before presenting our new active selection process RETIN. First, as any active method is sensitive to the boundary estimation between classes, the RETIN strategy carries out a boundary correction to make the retrieval process more robust. Second, the criterion of generalization error to optimize the active learning selection is modified to better represent the CBIR objective of database ranking. Third, a batch processing of images is proposed. Our strategy leads to a fast and efficient active learning scheme to retrieve sets of online images (query concept). Experiments on large databases show that the RETIN method performs well in comparison to several other active strategies.

A semi-automated method for bone age assessment using cervical vertebral maturation.

PubMed

Baptista, Roberto S; Quaglio, Camila L; Mourad, Laila M E H; Hummel, Anderson D; Caetano, Cesar Augusto C; Ortolani, Cristina Lúcia F; Pisa, Ivan T

2012-07-01

To propose a semi-automated method for pattern classification to predict individuals' stage of growth based on morphologic characteristics that are described in the modified cervical vertebral maturation (CVM) method of Baccetti et al. A total of 188 lateral cephalograms were collected, digitized, evaluated manually, and grouped into cervical stages by two expert examiners. Landmarks were located on each image and measured. Three pattern classifiers based on the Naïve Bayes algorithm were built and assessed using a software program. The classifier with the greatest accuracy according to the weighted kappa test was considered best. The classifier showed a weighted kappa coefficient of 0.861 ± 0.020. If an adjacent estimated pre-stage or poststage value was taken to be acceptable, the classifier would show a weighted kappa coefficient of 0.992 ± 0.019. Results from this study show that the proposed semi-automated pattern classification method can help orthodontists identify the stage of CVM. However, additional studies are needed before this semi-automated classification method for CVM assessment can be implemented in clinical practice.

Prognostic factors and outcome of treatment in Perthes' disease: a prospective study of 368 patients with five-year follow-up.

PubMed

Wiig, O; Terjesen, T; Svenningsen, S

2008-10-01

This nationwide prospective study was designed to determine prognostic factors and evaluate the outcome of different treatments of Perthes' disease. A total of 28 hospitals in Norway were instructed to report all new cases of Perthes' disease over a period of five years and 425 patients were reported and followed for five years. Of these, 368 with unilateral disease were included in the present study. The hips were classified radiologically according to a modified two-group Catterall classification and the lateral pillar classification. A total of 358 patients (97%) attended the five-year follow-up, when a modified three-group Stulberg classification was used as a radiological outcome measure. For patients over six years of age at diagnosis and with more than 50% necrosis of the femoral head (152 patients), the surgeons at the different hospitals had chosen one of three methods of treatment: physiotherapy (55 patients), the Scottish Rite abduction orthosis (26), and proximal femoral varus osteotomy (71). Of these hips, 146 (96%) were available for the five-year follow-up. The strongest predictor of outcome was femoral head involvement of more or less than 50% (odds ratio (OR) = 7.76, 95% confidence interval (CI) 2.82 to 21.37), followed by age at diagnosis (OR = 0.98, 95% CI 0.92 to 0.99) and the lateral pillar classification (OR = 0.62, 95% CI 0.40 to 0.98). In children over six years at diagnosis with more than 50% of femoral head necrosis, proximal femoral varus osteotomy gave a significantly better outcome than orthosis (p = 0.001) or physiotherapy (p = 0.001). There was no significant difference between the physiotherapy and orthosis groups (p = 0.36), and we found no difference in outcome after any of the treatments in children under six years (p = 0.73). We recommend proximal femoral varus osteotomy in children aged six years and over at the time of diagnosis with hips having more than 50% femoral head necrosis. The abduction orthosis should be abandoned in Perthes' disease.

Impact of oesophagitis classification in evaluating healing of erosive oesophagitis after therapy with proton pump inhibitors: a pooled analysis.

PubMed

Yaghoobi, Mohammad; Padol, Sara; Yuan, Yuhong; Hunt, Richard H

2010-05-01

The results of clinical trials with proton pump inhibitors (PPIs) are usually based on the Hetzel-Dent (HD), Savary-Miller (SM), or Los Angeles (LA) classifications to describe the severity and assess the healing of erosive oesophagitis. However, it is not known whether these classifications are comparable. The aim of this study was to review systematically the literature to compare the healing rates of erosive oesophagitis with PPIs in clinical trials assessed by the HD, SM, or LA classifications. A recursive, English language literature search in PubMed and Cochrane databases to December 2006 was performed. Double-blind randomized control trials comparing a PPI with another PPI, an H2-RA or placebo using endoscopic assessment of the healing of oesophagitis by the HD, SM or LA, or their modified classifications at 4 or 8 weeks, were included in the study. The healing rates on treatment with the same PPI(s), and same endoscopic grade(s) were pooled and compared between different classifications using Fisher's exact test or chi2 test where appropriate. Forty-seven studies from 965 potential citations met inclusion criteria. Seventy-eight PPI arms were identified, with 27 using HD, 29 using SM, and 22 using LA for five marketed PPIs. There was insufficient data for rabeprazole and esomeprazole (week 4 only) to compare because they were evaluated by only one classification. When data from all PPIs were pooled, regardless of baseline oesophagitis grades, the LA healing rate was significantly higher than SM and HD at both 4 and 8 weeks (74, 71, and 68% at 4 weeks and 89, 84, and 83% at 8 weeks, respectively). The distribution of different grades in study population was available only for pantoprazole where it was not significantly different between LA and SM subgroups. When analyzing data for PPI and dose, the LA classification showed a higher healing rate for omeprazole 20 mg/day and pantoprazole 40 mg/day (significant at 8 weeks), whereas healing by SM classification was significantly higher for omeprazole 40 mg/day (no data for LA) and lansoprazole 30 mg/day at 4 and 8 weeks. The healing rate by individual oesophagitis grade was not always available or robust enough for meaningful analysis. However, a difference between classifications remained. There is a significant, but not always consistent, difference in oesophagitis healing rates with the same PPI(s) reported by the LA, SM, or HD classifications. The possible difference between grading classifications should be considered when interpreting or comparing healing rates for oesophagitis from different studies.

Leptospirosis

PubMed Central

Levett, Paul N.

2001-01-01

Leptospirosis is a worldwide zoonotic infection with a much greater incidence in tropical regions and has now been identified as one of the emerging infectious diseases. The epidemiology of leptospirosis has been modified by changes in animal husbandry, climate, and human behavior. Resurgent interest in leptospirosis has resulted from large outbreaks that have received significant publicity. The development of simpler, rapid assays for diagnosis has been based largely on the recognition that early initiation of antibiotic therapy is important in acute disease but also on the need for assays which can be used more widely. In this review, the complex taxonomy of leptospires, previously based on serology and recently modified by a genotypic classification, is discussed, and the clinical and epidemiological value of molecular diagnosis and typing is also evaluated. PMID:11292640

99mTc MDP SPECT-CT-Based Modified Mirels Classification for Evaluation of Risk of Fracture in Skeletal Metastasis: A Pilot Study.

PubMed

Riaz, Saima; Bashir, Humayun; Niazi, Imran Khalid; Butt, Sumera; Qamar, Faisal

2018-06-01

Mirels' scoring system quantifies the risk of sustaining a pathologic fracture in osseous metastases of weight bearing long bones. Conventional Mirels' scoring is based on radiographs. Our pilot study proposes Tc MDP bone SPECT-CT based modified Mirels' scoring system and its comparison with conventional Mirels' scoring. Cortical lysis was noted in 8(24%) by SPECT-CT versus 2 (6.3%) on X-rays. Additional SPECT-CT parameters were; circumferential involvement [1/4 (31%), 1/2 (3%), 3/4 (37.5%), 4/4 (28%)] and extra-osseous soft tissue [3%]. Our pilot study suggests the potential role of SPECT-CT in predicting risk of fracture in osseous metastases.

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.

Determinant-based classification of acute pancreatitis severity: an international multidisciplinary consultation.

PubMed

Dellinger, E Patchen; Forsmark, Christopher E; Layer, Peter; Lévy, Philippe; Maraví-Poma, Enrique; Petrov, Maxim S; Shimosegawa, Tooru; Siriwardena, Ajith K; Uomo, Generoso; Whitcomb, David C; Windsor, John A

2012-12-01

To develop a new international classification of acute pancreatitis severity on the basis of a sound conceptual framework, comprehensive review of published evidence, and worldwide consultation. The Atlanta definitions of acute pancreatitis severity are ingrained in the lexicon of pancreatologists but suboptimal because these definitions are based on empiric description of occurrences that are merely associated with severity. A personal invitation to contribute to the development of a new international classification of acute pancreatitis severity was sent to all surgeons, gastroenterologists, internists, intensivists, and radiologists who are currently active in clinical research on acute pancreatitis. The invitation was not limited to members of certain associations or residents of certain countries. A global Web-based survey was conducted and a dedicated international symposium was organized to bring contributors from different disciplines together and discuss the concept and definitions. The new international classification is based on the actual local and systemic determinants of severity, rather than description of events that are correlated with severity. The local determinant relates to whether there is (peri)pancreatic necrosis or not, and if present, whether it is sterile or infected. The systemic determinant relates to whether there is organ failure or not, and if present, whether it is transient or persistent. The presence of one determinant can modify the effect of another such that the presence of both infected (peri)pancreatic necrosis and persistent organ failure have a greater effect on severity than either determinant alone. The derivation of a classification based on the above principles results in 4 categories of severity-mild, moderate, severe, and critical. This classification is the result of a consultative process amongst pancreatologists from 49 countries spanning North America, South America, Europe, Asia, Oceania, and Africa. It provides a set of concise up-to-date definitions of all the main entities pertinent to classifying the severity of acute pancreatitis in clinical practice and research. This ensures that the determinant-based classification can be used in a uniform manner throughout the world.

Analysis of radical cystectomy and urinary diversion complications with the Clavien classification system in an Italian real life cohort.

PubMed

De Nunzio, C; Cindolo, L; Leonardo, C; Antonelli, A; Ceruti, C; Franco, G; Falsaperla, M; Gallucci, M; Alvarez-Maestro, M; Minervini, A; Pagliarulo, V; Parma, P; Perdonà, S; Porreca, A; Rocco, B; Schips, L; Serni, S; Serrago, M; Simeone, C; Simone, G; Spadavecchia, R; Celia, A; Bove, P; Zaramella, S; Crivellaro, S; Nucciotti, R; Salvaggio, A; Frea, B; Pizzuti, V; Salsano, L; Tubaro, A

2013-07-01

Standardized methods of reporting complications after radical cystectomy (RC) and urinary diversions (UD) are necessary to evaluate the morbidity associated with this operation to evaluate the modified Clavien classification system (CCS) in grading perioperative complications of RC and UD in a real life cohort of patients with bladder cancer. A consecutive series of patients treated with RC and UD from April 2011 to March 2012 at 19 centers in Italy was evaluated. Complications were recorded according to the modified CCS. Results were presented as complication rates per grade. Univariate and binary logistic regression analysis were used for statistical analysis. 467 patients were enrolled. Median age was 70 years (range 35-89). UD consisted in orthotopic neobladder in 112 patients, ileal conduit in 217 patients and cutaneous ureterostomy in 138 patients. 415 complications were observed in 302 patients and were classified as Clavien type I (109 patients) or II (220 patients); Clavien type IIIa (45 patients), IIIb (22 patients); IV (11 patients) and V (8 patients). Patients with cutaneous ureterostomy presented a lower rate (8%) of CCS type ≥IIIa (p = 0.03). A longer operative time was an independent risk factor of CCS ≥III (OR: 1.005; CI: 1.002-1.007 per minute; p = 0.0001). In our study, RC is associated with a significant morbidity (65%) and a reduced mortality (1.7%) when compared to previous experiences. The modified CCS represents an easily applicable tool to classify the complications of RC and UD in a more objective and detailed way. Copyright © 2013 Elsevier Ltd. All rights reserved.

Vitamin D and ferritin correlation with chronic neck pain using standard statistics and a novel artificial neural network prediction model.

PubMed

Eloqayli, Haytham; Al-Yousef, Ali; Jaradat, Raid

2018-02-15

Despite the high prevalence of chronic neck pain, there is limited consensus about the primary etiology, risk factors, diagnostic criteria and therapeutic outcome. Here, we aimed to determine if Ferritin and Vitamin D are modifiable risk factors with chronic neck pain using slandered statistics and artificial intelligence neural network (ANN). Fifty-four patients with chronic neck pain treated between February 2016 and August 2016 in King Abdullah University Hospital and 54 patients age matched controls undergoing outpatient or minor procedures were enrolled. Patients and control demographic parameters, height, weight and single measurement of serum vitamin D, Vitamin B12, ferritin, calcium, phosphorus, zinc were obtained. An ANN prediction model was developed. The statistical analysis reveals that patients with chronic neck pain have significantly lower serum Vitamin D and Ferritin (p-value <.05). 90% of patients with chronic neck pain were females. Multilayer Feed Forward Neural Network with Back Propagation(MFFNN) prediction model were developed and designed based on vitamin D and ferritin as input variables and CNP as output. The ANN model output results show that, 92 out of 108 samples were correctly classified with 85% classification accuracy. Although Iron and vitamin D deficiency cannot be isolated as the sole risk factors of chronic neck pain, they should be considered as two modifiable risk. The high prevalence of chronic neck pain, hypovitaminosis D and low ferritin amongst women is of concern. Bioinformatics predictions with artificial neural network can be of future benefit in classification and prediction models for chronic neck pain. We hope this initial work will encourage a future larger cohort study addressing vitamin D and iron correction as modifiable factors and the application of artificial intelligence models in clinical practice.

Code-based Diagnostic Algorithms for Idiopathic Pulmonary Fibrosis. Case Validation and Improvement.

PubMed

Ley, Brett; Urbania, Thomas; Husson, Gail; Vittinghoff, Eric; Brush, David R; Eisner, Mark D; Iribarren, Carlos; Collard, Harold R

2017-06-01

Population-based studies of idiopathic pulmonary fibrosis (IPF) in the United States have been limited by reliance on diagnostic code-based algorithms that lack clinical validation. To validate a well-accepted International Classification of Diseases, Ninth Revision, code-based algorithm for IPF using patient-level information and to develop a modified algorithm for IPF with enhanced predictive value. The traditional IPF algorithm was used to identify potential cases of IPF in the Kaiser Permanente Northern California adult population from 2000 to 2014. Incidence and prevalence were determined overall and by age, sex, and race/ethnicity. A validation subset of cases (n = 150) underwent expert medical record and chest computed tomography review. A modified IPF algorithm was then derived and validated to optimize positive predictive value. From 2000 to 2014, the traditional IPF algorithm identified 2,608 cases among 5,389,627 at-risk adults in the Kaiser Permanente Northern California population. Annual incidence was 6.8/100,000 person-years (95% confidence interval [CI], 6.1-7.7) and was higher in patients with older age, male sex, and white race. The positive predictive value of the IPF algorithm was only 42.2% (95% CI, 30.6 to 54.6%); sensitivity was 55.6% (95% CI, 21.2 to 86.3%). The corrected incidence was estimated at 5.6/100,000 person-years (95% CI, 2.6-10.3). A modified IPF algorithm had improved positive predictive value but reduced sensitivity compared with the traditional algorithm. A well-accepted International Classification of Diseases, Ninth Revision, code-based IPF algorithm performs poorly, falsely classifying many non-IPF cases as IPF and missing a substantial proportion of IPF cases. A modification of the IPF algorithm may be useful for future population-based studies of IPF.

Very Massive Stars and the Eddington Limit

NASA Astrophysics Data System (ADS)

Crowther, P. A.; Hirschi, R.; Walborn, N. R.; Yusof, N.

2012-12-01

We use contemporary evolutionary models for very massive stars (VMS) to assess whether the Eddington limit constrains the upper stellar mass limit. We also consider the interplay between mass and age for the wind properties and spectral morphology of VMS, with reference to the recently modified classification scheme for O2-3.5 If*/WN stars. Finally, the death of VMS in the local universe is considered in the context of pair instability supernovae.

Synthesis and Structure Property Studies of Toughened Epoxy Resins Via Functionalized Polysiloxanes.

DTIC Science & Technology

1987-09-30

34 87S N4 SYNTHESIS RNO STRUCTURE PROPERTY STUDIES OF OP NDD mEPOXY RESINS YIN FU.. (U) VIROINIR POLYTECHNIC INST OM STNTE UNIY RCKSBURG DEPT OF C.. J...Classification) Synthesis and Structure Property Studies of Toughened Epoxy Resins Via Functionalized Polysiloxanes 12. PERSONALAUTHOR(S) J. 5. HitTIe... Resins , Toughening 19. ABSTRACT (Continue on reverse if necessary and identify by block number) Epoxy resins chemically modified with functionally

Immune Centroids Over-Sampling Method for Multi-Class Classification

DTIC Science & Technology

2015-05-22

recognize to specific antigens . The response of a receptor to an antigen can activate its hosting B-cell. Activated B-cell then proliferates and...modifying N.K. Jerne’s theory. The theory states that in a pre-existing group of lympho- cytes ( specifically B cells), a specific antigen only...the clusters of each small class, which have high data density, called global immune centroids over-sampling (denoted as Global-IC). Specifically

Swimming behavior of zebrafish is accurately classified by direct modeling and behavioral space analysis

NASA Astrophysics Data System (ADS)

Feng, Ruopei; Chemla, Yann; Gruebele, Martin

Larval zebrafish is a popular organism in the search for the correlation between locomotion behavior and neural pathways because of their highly stereotyped and temporally episodic swimming motion. This correlation is usually investigated using electrophysiological recordings of neural activities in partially immobilized fish. Seeking for a way to study animal behavior without constraints or intruding electrodes, which can in turn modify their behavior, our lab has introduced a parameter-free approach which allows automated classification of the locomotion behaviors of freely swimming fish. We looked into several types of swimming bouts including free swimming and two modes of escape responses and established a new classification of these behaviors. Combined with a neurokinematic model, our analysis showed the capability to probe intrinsic properties of the underlying neural pathways of freely swimming larval zebrafish by inspecting swimming movies only.

Symmetry classification of time-fractional diffusion equation

NASA Astrophysics Data System (ADS)

Naeem, I.; Khan, M. D.

2017-01-01

In this article, a new approach is proposed to construct the symmetry groups for a class of fractional differential equations which are expressed in the modified Riemann-Liouville fractional derivative. We perform a complete group classification of a nonlinear fractional diffusion equation which arises in fractals, acoustics, control theory, signal processing and many other applications. Introducing the suitable transformations, the fractional derivatives are converted to integer order derivatives and in consequence the nonlinear fractional diffusion equation transforms to a partial differential equation (PDE). Then the Lie symmetries are computed for resulting PDE and using inverse transformations, we derive the symmetries for fractional diffusion equation. All cases are discussed in detail and results for symmetry properties are compared for different values of α. This study provides a new way of computing symmetries for a class of fractional differential equations.

Digital classification of Landsat data for vegetation and land-cover mapping in the Blackfoot River watershed, southeastern Idaho

USGS Publications Warehouse

Pettinger, L.R.

1982-01-01

This paper documents the procedures, results, and final products of a digital analysis of Landsat data used to produce a vegetation and landcover map of the Blackfoot River watershed in southeastern Idaho. Resource classes were identified at two levels of detail: generalized Level I classes (for example, forest land and wetland) and detailed Levels II and III classes (for example, conifer forest, aspen, wet meadow, and riparian hardwoods). Training set statistics were derived using a modified clustering approach. Environmental stratification that separated uplands from lowlands improved discrimination between resource classes having similar spectral signatures. Digital classification was performed using a maximum likelihood algorithm. Classification accuracy was determined on a single-pixel basis from a random sample of 25-pixel blocks. These blocks were transferred to small-scale color-infrared aerial photographs, and the image area corresponding to each pixel was interpreted. Classification accuracy, expressed as percent agreement of digital classification and photo-interpretation results, was 83.0:t 2.1 percent (0.95 probability level) for generalized (Level I) classes and 52.2:t 2.8 percent (0.95 probability level) for detailed (Levels II and III) classes. After the classified images were geometrically corrected, two types of maps were produced of Level I and Levels II and III resource classes: color-coded maps at a 1:250,000 scale, and flatbed-plotter overlays at a 1:24,000 scale. The overlays are more useful because of their larger scale, familiar format to users, and compatibility with other types of topographic and thematic maps of the same scale.

Global hierarchical classification of deepwater and wetland environments from remote sensing products

NASA Astrophysics Data System (ADS)

Fluet-Chouinard, E.; Lehner, B.; Aires, F.; Prigent, C.; McIntyre, P. B.

2017-12-01

Global surface water maps have improved in spatial and temporal resolutions through various remote sensing methods: open water extents with compiled Landsat archives and inundation with topographically downscaled multi-sensor retrievals. These time-series capture variations through time of open water and inundation without discriminating between hydrographic features (e.g. lakes, reservoirs, river channels and wetland types) as other databases have done as static representation. Available data sources present the opportunity to generate a comprehensive map and typology of aquatic environments (deepwater and wetlands) that improves on earlier digitized inventories and maps. The challenge of classifying surface waters globally is to distinguishing wetland types with meaningful characteristics or proxies (hydrology, water chemistry, soils, vegetation) while accommodating limitations of remote sensing data. We present a new wetland classification scheme designed for global application and produce a map of aquatic ecosystem types globally using state-of-the-art remote sensing products. Our classification scheme combines open water extent and expands it with downscaled multi-sensor inundation data to capture the maximal vegetated wetland extent. The hierarchical structure of the classification is modified from the Cowardin Systems (1979) developed for the USA. The first level classification is based on a combination of landscape positions and water source (e.g. lacustrine, riverine, palustrine, coastal and artificial) while the second level represents the hydrologic regime (e.g. perennial, seasonal, intermittent and waterlogged). Class-specific descriptors can further detail the wetland types with soils and vegetation cover. Our globally consistent nomenclature and top-down mapping allows for direct comparison across biogeographic regions, to upscale biogeochemical fluxes as well as other landscape level functions.

Classification of oxidative stress based on its intensity

PubMed Central

Lushchak, Volodymyr I.

2014-01-01

In living organisms production of reactive oxygen species (ROS) is counterbalanced by their elimination and/or prevention of formation which in concert can typically maintain a steady-state (stationary) ROS level. However, this balance may be disturbed and lead to elevated ROS levels called oxidative stress. To our best knowledge, there is no broadly acceptable system of classification of oxidative stress based on its intensity due to which proposed here system may be helpful for interpretation of experimental data. Oxidative stress field is the hot topic in biology and, to date, many details related to ROS-induced damage to cellular components, ROS-based signaling, cellular responses and adaptation have been disclosed. However, it is common situation when researchers experience substantial difficulties in the correct interpretation of oxidative stress development especially when there is a need to characterize its intensity. Careful selection of specific biomarkers (ROS-modified targets) and some system may be helpful here. A classification of oxidative stress based on its intensity is proposed here. According to this classification there are four zones of function in the relationship between “Dose/concentration of inducer” and the measured “Endpoint”: I – basal oxidative stress (BOS); II – low intensity oxidative stress (LOS); III – intermediate intensity oxidative stress (IOS); IV – high intensity oxidative stress (HOS). The proposed classification will be helpful to describe experimental data where oxidative stress is induced and systematize it based on its intensity, but further studies will be in need to clear discriminate between stress of different intensity. PMID:26417312

Disease-modifying treatments for early and advanced multiple sclerosis: a new treatment paradigm.

PubMed

Giovannoni, Gavin

2018-06-01

The treatment of multiple sclerosis is evolving rapidly with 11 classes of disease-modifying therapies (DMTs). This article provides an overview of a new classification system for DMTs and treatment paradigm for using these DMTs effectively and safely. A summary of research into the use of more active approaches to early and effective treatment of multiple sclerosis with defined treatment targets of no evident disease activity (NEDA). New insights are discussed that is allowing the field to begin to tackle more advanced multiple sclerosis, including people with multiple sclerosis using wheelchairs. However, the need to modify expectations of what can be achieved in more advanced multiple sclerosis are discussed; in particular, the focus on neuronal systems with reserve capacity, for example, upper limb, bulbar and visual function. The review describes a new more active way of managing multiple sclerosis and concludes with a call to action in solving the problem of slow adoption of innovations and the global problem of untreated, or undertreated, multiple sclerosis.

Evolutionary Construction of Block-Based Neural Networks in Consideration of Failure

NASA Astrophysics Data System (ADS)

Takamori, Masahito; Koakutsu, Seiichi; Hamagami, Tomoki; Hirata, Hironori

In this paper we propose a modified gene coding and an evolutionary construction in consideration of failure in evolutionary construction of Block-Based Neural Networks. In the modified gene coding, we arrange the genes of weights on a chromosome in consideration of the position relation of the genes of weight and structure. By the modified gene coding, the efficiency of search by crossover is increased. Thereby, it is thought that improvement of the convergence rate of construction and shortening of construction time can be performed. In the evolutionary construction in consideration of failure, the structure which is adapted for failure is built in the state where failure occured. Thereby, it is thought that BBNN can be reconstructed in a short time at the time of failure. To evaluate the proposed method, we apply it to pattern classification and autonomous mobile robot control problems. The computational experiments indicate that the proposed method can improve convergence rate of construction and shorten of construction and reconstruction time.

Melts of Octaacetyl Sucrose as Oral-Modified Release Dosage Forms for Delivery of Poorly Soluble Compound in Stable Amorphous Form.

PubMed

Haznar-Garbacz, Dorota; Kaminska, Ewa; Zakowiecki, Daniel; Lachmann, Marek; Kaminski, Kamil; Garbacz, Grzegorz; Dorożyński, Przemysław; Kulinowski, Piotr

2018-02-01

The presented work describes the formulation and characterization of modified release glassy solid dosage forms (GSDFs) containing an amorphous nifedipine, as a model BCS (Biopharmaceutical Classification System) class II drug. The GSDFs were prepared by melting nifedipine together with octaacetyl sucrose. Dissolution profiles, measured under standard and biorelevant conditions, were compared to those obtained from commercially available formulations containing nifedipine such as modified release (MR) tablets and osmotic release oral system (OROS). The results indicate that the dissolution profiles of the GSDFs with nifedipine are neither affected by the pH of the dissolution media, type and concentration of surfactants, nor by simulated mechanical stress of biorelevant intensity. Furthermore, it was found that the dissolution profiles of the novel dosage forms were similar to the profiles obtained from the nifedipine OROS. The formulation of GSDFs is relatively simple, and the dosage forms were found to have favorable dissolution characteristics.

[Determinant-based classification of acute pancreatitis severity. International multidisciplinary classification of acute pancreatitis severity: the 2013 German edition].

PubMed

Layer, P; Dellinger, E P; Forsmark, C E; Lévy, P; Maraví-Poma, E; Shimosegawa, T; Siriwardena, A K; Uomo, G; Whitcomb, D C; Windsor, J A; Petrov, M S

2013-06-01

The aim of this study was to develop a new international classification of acute pancreatitis severity on the basis of a sound conceptual framework, comprehensive review of published evidence, and worldwide consultation. The Atlanta definitions of acute pancreatitis severity are ingrained in the lexicon of pancreatologists but suboptimal because these definitions are based on empiric descriptions of occurrences that are merely associated with severity. A personal invitation to contribute to the development of a new international classification of acute pancreatitis severity was sent to all surgeons, gastroenterologists, internists, intensive medicine specialists, and radiologists who are currently active in clinical research on acute pancreatitis. The invitation was not limited to members of certain associations or residents of certain countries. A global Web-based survey was conducted and a dedicated international symposium was organised to bring contributors from different disciplines together and discuss the concept and definitions. The new international classification is based on the actual local and systemic determinants of severity, rather than descriptions of events that are correlated with severity. The local determinant relates to whether there is (peri)pancreatic necrosis or not, and if present, whether it is sterile or infected. The systemic determinant relates to whether there is organ failure or not, and if present, whether it is transient or persistent. The presence of one determinant can modify the effect of another such that the presence of both infected (peri)pancreatic necrosis and persistent organ failure have a greater effect on severity than either determinant alone. The derivation of a classification based on the above principles results in 4 categories of severity - mild, moderate, severe, and critical. This classification is the result of a consultative process amongst pancreatologists from 49 countries spanning North America, South America, Europe, Asia, Oceania, and Africa. It provides a set of concise up-to-date definitions of all the main entities pertinent to classifying the severity of acute pancreatitis in clinical practice and research. This ensures that the determinant-based classification can be used in a uniform manner throughout the world. © Georg Thieme Verlag KG Stuttgart · New York.

Laparoscopic management of recurrent ureteropelvic junction obstruction following pyeloplasty: a single surgical team experience with 38 cases

PubMed Central

Chiancone, Francesco; Fedelini, Maurizio; Pucci, Luigi; Meccariello, Clemente; Fedelini, Paolo

2017-01-01

ABSTRACT Purpose To describe and analyze our experience with Anderson-Hynes transperitoneal laparoscopic pyeloplasty (LP) in the treatment of recurrent ureteropelvic junction obstruction (UPJO). Materials and methods 38 consecutive patients who underwent transperitoneal laparoscopic redo-pyeloplasty between January 2007 and January 2015 at our department were included in the analysis. 36 patients were previously treated with dismembered pyeloplasty and 2 patients underwent a retrograde endopyelotomy. All patients were symptomatic and all patients had a T1/2>20 minutes at pre-operative DTPA (diethylene-triamine-pentaacetate) renal scan. All data were collected in a prospectively maintained database and retrospectively analyzed. Intraoperative and postoperative complications have been reported according to the Satava and the Clavien-Dindo system. Treatment success was evaluated by a 12 month-postoperative renal scan. Total success was defined as T1/2≤10 minutes while relative success was defined as T1/2between 10 to 20 minutes. Post-operative hydronephrosis and flank pain were also evaluated. Results Mean operating time was 103.16±30 minutes. The mean blood loss was 122.37±73.25mL. The mean postoperative hospital stay was 4.47±0.86 days. No intraoperative complications occurred. 6 out of 38 patients (15.8%) experienced postoperative complications. The success rate was 97.4% for flank pain and 97.4% for hydronephrosis. Post-operative renal scan showed radiological failure in one out of 38 (2.6%) patients, relative success in 2 out of 38 (5.3%) patients and total success in 35 out of 38 (92.1%) of patients. Conclusion Laparoscopic redo-pyeloplasty is a feasible procedure for the treatment of recurrent ureteropelvic junction obstruction (UPJO), with a low rate of post-operative complications and a high success rate in high laparoscopic volume centers. PMID:28191792

Polythelia pilosa: a particular form of accessory mammary tissue.

PubMed

Camacho, F; González-Cámpora, R

1998-01-01

The old Kajawa classification which considered eight possible forms of aberrant mammary tissue has been recently modified into a simpler one that considers this condition only when there is glandular parenchyma or when the aberrant tissue is not a glandular tissue but a nipple, an areola or both. This new classification disregards 'polythelia pilosa' defined as an 'isolated patch of hairs only'. To demonstrate that polythelia pilosa is at least a marker of subjacent accessory mammary tissue and, consequently, that the term should be incorporated into the current classification. Among 72 cases of aberrant or accessory mammary tissue, we have studied 14 cases (7 men and 7 women) that were clinically diagnosed as 'visible isolated patches of hairs, apparently without pigmentation nor structures of areola or nipple'. We excised such isolated patches in 3 women. The histopathological examination showed an acanthotic and hyperpigmented epithelium with central depression closed by keratin plugs; in the dermis there were follicles with hairs surrounded by hypertrophic sebaceous glands. In the deepest portion, abundant secretory glomerules and excretory ducts of apocrine gland type could be observed. Since the biopsy of isolated patches of hairs demonstrated structures of either areolar or apocrine glandular tissue, we think that the term 'polythelia pilosa' should be reinstated into the classification as it is at least a marker of true aberrant mammary structures in men and hirsute women.

Interobserver agreement in analysis of cardiotocograms recorded during trial of labor after cesarean.

PubMed

Caning, M M; Thisted, D L A; Amer-Wählin, I; Laier, G H; Krebs, L

2018-05-17

To examine interobserver agreement in intrapartum cardiotocography (CTG) classification in women undergoing trial of labor after a cesarean section (TOLAC) at term with or without complete uterine rupture. Nineteen blinded and independent Danish obstetricians assessed CTG tracings from 47 women (174 individual pages) with a complete uterine rupture during TOLAC and 37 women (133 individual pages) with no uterine rupture during TOLAC. Individual pages with CTG tracings lasting at least 20 min were evaluated by three different assessors and counted as an individual case. The tracings were analyzed according to the modified version of the Federation of Gynaecology and Obstetrics (FIGO) guidelines elaborated for the use of STAN (ST-analysis). Occurrence of defined abnormalities was recorded and the tracings were classified as normal, suspicious, pathological, or preterminal. The interobserver agreement was evaluated using Fleiss' kappa. Agreement on classification of a preterminal CTG was almost perfect. The interobserver agreement on normal, suspicious or pathological CTG was moderate to substantial. Regarding the presence of severe variable decelerations, the agreement was moderate. No statistical difference was found in the interobserver agreement between classification of tracings from women undergoing TOLAC with and without complete uterine rupture. The interobserver agreement on classification of CTG tracings from high-risk deliveries during TOLAC is best for assessment of a preterminal CTG and the poorest for the identification of severe variable decelerations.

European consensus meeting of ARM-Net members concerning diagnosis and early management of newborns with anorectal malformations.

PubMed

van der Steeg, H J J; Schmiedeke, E; Bagolan, P; Broens, P; Demirogullari, B; Garcia-Vazquez, A; Grasshoff-Derr, S; Lacher, M; Leva, E; Makedonsky, I; Sloots, C E J; Schwarzer, N; Aminoff, D; Schipper, M; Jenetzky, E; van Rooij, I A L M; Giuliani, S; Crétolle, C; Holland Cunz, S; Midrio, P; de Blaauw, I

2015-03-01

The ARM-Net (anorectal malformation network) consortium held a consensus meeting in which the classification of ARM and preoperative workup were evaluated with the aim of improving monitoring of treatment and outcome. The Krickenbeck classification of ARM and preoperative workup suggested by Levitt and Peña, used as a template, were discussed, and a collaborative consensus was achieved. The Krickenbeck classification is appropriate in describing ARM for clinical use. The preoperative workup was slightly modified. In males with a visible fistula, no cross-table lateral X-ray is needed and an anoplasty or (mini-) posterior sagittal anorectoplasty can directly be performed. In females with a small vestibular fistula (Hegar size <5 mm), a primary repair or colostomy is recommended; the repair may be delayed if the fistula admits a Hegar size >5 mm, and in the meantime, gentle painless dilatations can be performed. In both male and female perineal fistula and either a low birth weight (<2,000 g) or severe associated congenital anomalies, prolonged preoperative painless dilatations might be indicated to decrease perioperative morbidity caused by general anesthesia. The Krickenbeck classification is appropriate in describing ARM for clinical use. Some minor modifications to the preoperative workup by Levitt and Peña have been introduced in order to refine terminology and establish a comprehensive preoperative workup.

A modified artificial immune system based pattern recognition approach -- an application to clinic diagnostics

PubMed Central

Zhao, Weixiang; Davis, Cristina E.

2011-01-01

Objective This paper introduces a modified artificial immune system (AIS)-based pattern recognition method to enhance the recognition ability of the existing conventional AIS-based classification approach and demonstrates the superiority of the proposed new AIS-based method via two case studies of breast cancer diagnosis. Methods and materials Conventionally, the AIS approach is often coupled with the k nearest neighbor (k-NN) algorithm to form a classification method called AIS-kNN. In this paper we discuss the basic principle and possible problems of this conventional approach, and propose a new approach where AIS is integrated with the radial basis function – partial least square regression (AIS-RBFPLS). Additionally, both the two AIS-based approaches are compared with two classical and powerful machine learning methods, back-propagation neural network (BPNN) and orthogonal radial basis function network (Ortho-RBF network). Results The diagnosis results show that: (1) both the AIS-kNN and the AIS-RBFPLS proved to be a good machine leaning method for clinical diagnosis, but the proposed AIS-RBFPLS generated an even lower misclassification ratio, especially in the cases where the conventional AIS-kNN approach generated poor classification results because of possible improper AIS parameters. For example, based upon the AIS memory cells of “replacement threshold = 0.3”, the average misclassification ratios of two approaches for study 1 are 3.36% (AIS-RBFPLS) and 9.07% (AIS-kNN), and the misclassification ratios for study 2 are 19.18% (AIS-RBFPLS) and 28.36% (AIS-kNN); (2) the proposed AIS-RBFPLS presented its robustness in terms of the AIS-created memory cells, showing a smaller standard deviation of the results from the multiple trials than AIS-kNN. For example, using the result from the first set of AIS memory cells as an example, the standard deviations of the misclassification ratios for study 1 are 0.45% (AIS-RBFPLS) and 8.71% (AIS-kNN) and those for study 2 are 0.49% (AIS-RBFPLS) and 6.61% (AIS-kNN); and (3) the proposed AIS-RBFPLS classification approaches also yielded better diagnosis results than two classical neural network approaches of BPNN and Ortho-RBF network. Conclusion In summary, this paper proposed a new machine learning method for complex systems by integrating the AIS system with RBFPLS. This new method demonstrates its satisfactory effect on classification accuracy for clinical diagnosis, and also indicates its wide potential applications to other diagnosis and detection problems. PMID:21515033

Dynamic assessment of school-age children's narrative ability: an experimental investigation of classification accuracy.

PubMed

Peña, Elizabeth D; Gillam, Ronald B; Malek, Melynn; Ruiz-Felter, Roxanna; Resendiz, Maria; Fiestas, Christine; Sabel, Tracy

2006-10-01

Two experiments examined reliability and classification accuracy of a narration-based dynamic assessment task. The first experiment evaluated whether parallel results were obtained from stories created in response to 2 different wordless picture books. If so, the tasks and measures would be appropriate for assessing pretest and posttest change within a dynamic assessment format. The second experiment evaluated the extent to which children with language impairments performed differently than typically developing controls on dynamic assessment of narrative language. In the first experiment, 58 1st- and 2nd-grade children told 2 stories about wordless picture books. Stories were rated on macrostructural and microstructural aspects of language form and content, and the ratings were subjected to reliability analyses. In the second experiment, 71 children participated in dynamic assessment. There were 3 phases: a pretest phase, in which children created a story that corresponded to 1 of the wordless picture books from Experiment 1; a teaching phase, in which children attended 2 short mediation sessions that focused on storytelling ability; and a posttest phase, in which children created a story that corresponded to a second wordless picture book from Experiment 1. Analyses compared the pretest and posttest stories that were told by 2 groups of children who received mediated learning (typical and language impaired groups) and a no-treatment control group of typically developing children from Experiment 1. The results of the first experiment indicated that the narrative measures applied to stories about 2 different wordless picture books had good internal consistency. In Experiment 2, typically developing children who received mediated learning demonstrated a greater amount of pretest to posttest change than children in the language impaired and control groups. Classification analysis indicated better specificity and sensitivity values for measures of response to intervention (modifiability) and posttest storytelling than for measures of pretest storytelling. Observation of modifiability was the single best indicator of language impairment. Posttest measures and modifiability together yielded no misclassifications. The first experiment supported the use of 2 wordless picture books as stimulus materials for collecting narratives before and after mediation within a dynamic assessment paradigm. The second experiment supported the use of dynamic assessment for accurately identifying language impairments in school-age children.

Early Detection for Dengue Using Local Indicator of Spatial Association (LISA) Analysis.

PubMed

Parra-Amaya, Mayra Elizabeth; Puerta-Yepes, María Eugenia; Lizarralde-Bejarano, Diana Paola; Arboleda-Sánchez, Sair

2016-03-29

Dengue is a viral disease caused by a flavivirus that is transmitted by mosquitoes of the genus Aedes . There is currently no specific treatment or commercial vaccine for its control and prevention; therefore, mosquito population control is the only alternative for preventing the occurrence of dengue. For this reason, entomological surveillance is recommended by World Health Organization (WHO) to measure dengue risk in endemic areas; however, several works have shown that the current methodology (aedic indices) is not sufficient for predicting dengue. In this work, we modified indices proposed for epidemic periods. The raw value of the epidemiological wave could be useful for detecting risk in epidemic periods; however, risk can only be detected if analyses incorporate the maximum epidemiological wave. Risk classification was performed according to Local Indicators of Spatial Association (LISA) methodology. The modified indices were analyzed using several hypothetical scenarios to evaluate their sensitivity. We found that modified indices could detect spatial and differential risks in epidemic and endemic years, which makes them a useful tool for the early detection of a dengue outbreak. In conclusion, the modified indices could predict risk at the spatio-temporal level in endemic years and could be incorporated in surveillance activities in endemic places.

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.

A New Method of Synthetic Aperture Radar Image Reconstruction Using Modified Convolution Back-Projection Algorithm.

DTIC Science & Technology

1986-08-01

SECURITY CLASSIFICATION AUTHORITY 3 DISTRIBUTIONAVAILABILITY OF REPORT N/A \\pproved for public release, 21b. OECLASS FI) CAT ) ON/OOWNGRAOING SCMEOLLE...from this set of projections. The Convolution Back-Projection (CBP) algorithm is widely used technique in Computer Aide Tomography ( CAT ). In this work...University of Illinois at Urbana-Champaign. 1985 Ac % DTICEl_ FCTE " AUG 1 11986 Urbana. Illinois U,) I A NEW METHOD OF SYNTHETIC APERTURE RADAR IMAGE

Experimental and Numerical Characterization of Polymer Nanocomposites for Solid Rocket Motor Internal Insulation

DTIC Science & Technology

2006-09-30

Nanophase, Thermoplastic Elastomer, EPDM Rubber , Surface Modified MMT Clay, Carbon Nanofibers 16. SECURITY CLASSIFICATION OF: a. REPORT u b. ABSTRACT U...diene rubber ( EPDM ) is the baseline insulation material for solid rocket motor cases. A novel class of insulation materials was developed by the Air...Figure 1. Upon analysis of the control sample, it was observed that the EPDM rubber was totally burned forming a small amount of char, which was easily

An assessment of the barriers to the consumers' uptake of genetically modified foods: a neural network analysis.

PubMed

Rodríguez-Entrena, Macario; Salazar-Ordóñez, Melania; Becerra-Alonso, David

2016-03-30

This paper studies which of the attitudinal, cognitive and socio-economic factors determine the willingness to purchase genetically modified (GM) food, enabling the forecasting of consumers' behaviour in Andalusia, southern Spain. This classification has been made by a standard multilayer perceptron neural network trained with extreme learning machine. Later, an ordered logistic regression was applied to determine whether the neural network can outperform this traditional econometric approach. The results show that the highest relative contributions lie in the variables related to perceived risks of GM food, while the perceived benefits have a lower influence. In addition, an innovative attitude towards food presents a strong link, as does the perception of food safety. The variables with the least relative contribution are subjective knowledge about GM food and the consumers' age. The neural network approach outperforms the correct classification percentage from the ordered logistic regression. The perceived risks must be considered as a critical factor. A strategy to improve the GM food acceptance is to develop a transparent and balanced information framework that makes the potential risk understandable by society, and make them aware of the risk assessments for GM food in the EU. For its success, it is essential to improve the trust in EU institutions and scientific regulatory authorities. © 2015 Society of Chemical Industry.

A Novel Wearable Forehead EOG Measurement System for Human Computer Interfaces

PubMed Central

Heo, Jeong; Yoon, Heenam; Park, Kwang Suk

2017-01-01

Amyotrophic lateral sclerosis (ALS) patients whose voluntary muscles are paralyzed commonly communicate with the outside world using eye movement. There have been many efforts to support this method of communication by tracking or detecting eye movement. An electrooculogram (EOG), an electro-physiological signal, is generated by eye movements and can be measured with electrodes placed around the eye. In this study, we proposed a new practical electrode position on the forehead to measure EOG signals, and we developed a wearable forehead EOG measurement system for use in Human Computer/Machine interfaces (HCIs/HMIs). Four electrodes, including the ground electrode, were placed on the forehead. The two channels were arranged vertically and horizontally, sharing a positive electrode. Additionally, a real-time eye movement classification algorithm was developed based on the characteristics of the forehead EOG. Three applications were employed to evaluate the proposed system: a virtual keyboard using a modified Bremen BCI speller and an automatic sequential row-column scanner, and a drivable power wheelchair. The mean typing speeds of the modified Bremen brain–computer interface (BCI) speller and automatic row-column scanner were 10.81 and 7.74 letters per minute, and the mean classification accuracies were 91.25% and 95.12%, respectively. In the power wheelchair demonstration, the user drove the wheelchair through an 8-shape course without collision with obstacles. PMID:28644398

A Novel Wearable Forehead EOG Measurement System for Human Computer Interfaces.

PubMed

Heo, Jeong; Yoon, Heenam; Park, Kwang Suk

2017-06-23

Amyotrophic lateral sclerosis (ALS) patients whose voluntary muscles are paralyzed commonly communicate with the outside world using eye movement. There have been many efforts to support this method of communication by tracking or detecting eye movement. An electrooculogram (EOG), an electro-physiological signal, is generated by eye movements and can be measured with electrodes placed around the eye. In this study, we proposed a new practical electrode position on the forehead to measure EOG signals, and we developed a wearable forehead EOG measurement system for use in Human Computer/Machine interfaces (HCIs/HMIs). Four electrodes, including the ground electrode, were placed on the forehead. The two channels were arranged vertically and horizontally, sharing a positive electrode. Additionally, a real-time eye movement classification algorithm was developed based on the characteristics of the forehead EOG. Three applications were employed to evaluate the proposed system: a virtual keyboard using a modified Bremen BCI speller and an automatic sequential row-column scanner, and a drivable power wheelchair. The mean typing speeds of the modified Bremen brain-computer interface (BCI) speller and automatic row-column scanner were 10.81 and 7.74 letters per minute, and the mean classification accuracies were 91.25% and 95.12%, respectively. In the power wheelchair demonstration, the user drove the wheelchair through an 8-shape course without collision with obstacles.

New climatic classification of Nepal

NASA Astrophysics Data System (ADS)

Karki, Ramchandra; Talchabhadel, Rocky; Aalto, Juha; Baidya, Saraju Kumar

2016-08-01

Although it is evident that Nepal has an extremely wide range of climates within a short latitudinal distance, there is a lack of comprehensive research in this field. The climatic zoning in a topographically complex country like Nepal has important implications for the selection of scientific station network design and climate model verification, as well as for studies examining the effects of climate change in terms of shifting climatic boundaries and vegetation in highly sensitive environments. This study presents a new high-resolution climate map of Nepal on the basis of long-term (1981-2010) monthly precipitation data for 240 stations and mean air temperature data for 74 stations, using original and modified Köppen-Geiger climate classification systems. Climatic variables used in Köppen-Geiger system were calculated (i) at each station and (ii) interpolated to 1-km spatial resolution using kriging which accounted for latitude, longitude, and elevation. The original Köppen-Geiger scheme could not identify all five types of climate (including tropical) observed in Nepal. Hence, the original scheme was slightly modified by changing the boundary of coldest month mean air temperature value from 18 °C to 14.5 °C in order to delineate the realistic climatic condition of Nepal. With this modification, all five types of climate (including tropical) were identified. The most common dominant type of climate for Nepal is temperate with dry winter and hot summer (Cwa).

A SVM framework for fault detection of the braking system in a high speed train

NASA Astrophysics Data System (ADS)

Liu, Jie; Li, Yan-Fu; Zio, Enrico

2017-03-01

In April 2015, the number of operating High Speed Trains (HSTs) in the world has reached 3603. An efficient, effective and very reliable braking system is evidently very critical for trains running at a speed around 300 km/h. Failure of a highly reliable braking system is a rare event and, consequently, informative recorded data on fault conditions are scarce. This renders the fault detection problem a classification problem with highly unbalanced data. In this paper, a Support Vector Machine (SVM) framework, including feature selection, feature vector selection, model construction and decision boundary optimization, is proposed for tackling this problem. Feature vector selection can largely reduce the data size and, thus, the computational burden. The constructed model is a modified version of the least square SVM, in which a higher cost is assigned to the error of classification of faulty conditions than the error of classification of normal conditions. The proposed framework is successfully validated on a number of public unbalanced datasets. Then, it is applied for the fault detection of braking systems in HST: in comparison with several SVM approaches for unbalanced datasets, the proposed framework gives better results.

Patient-Specific Deep Architectural Model for ECG Classification

PubMed Central

Luo, Kan; Cuschieri, Alfred

2017-01-01

Heartbeat classification is a crucial step for arrhythmia diagnosis during electrocardiographic (ECG) analysis. The new scenario of wireless body sensor network- (WBSN-) enabled ECG monitoring puts forward a higher-level demand for this traditional ECG analysis task. Previously reported methods mainly addressed this requirement with the applications of a shallow structured classifier and expert-designed features. In this study, modified frequency slice wavelet transform (MFSWT) was firstly employed to produce the time-frequency image for heartbeat signal. Then the deep learning (DL) method was performed for the heartbeat classification. Here, we proposed a novel model incorporating automatic feature abstraction and a deep neural network (DNN) classifier. Features were automatically abstracted by the stacked denoising auto-encoder (SDA) from the transferred time-frequency image. DNN classifier was constructed by an encoder layer of SDA and a softmax layer. In addition, a deterministic patient-specific heartbeat classifier was achieved by fine-tuning on heartbeat samples, which included a small subset of individual samples. The performance of the proposed model was evaluated on the MIT-BIH arrhythmia database. Results showed that an overall accuracy of 97.5% was achieved using the proposed model, confirming that the proposed DNN model is a powerful tool for heartbeat pattern recognition. PMID:29065597

JointMMCC: Joint Maximum-Margin Classification and Clustering of Imaging Data

PubMed Central

Filipovych, Roman; Resnick, Susan M.; Davatzikos, Christos

2012-01-01

A number of conditions are characterized by pathologies that form continuous or nearly-continuous spectra spanning from the absence of pathology to very pronounced pathological changes (e.g., normal aging, Mild Cognitive Impairment, Alzheimer's). Moreover, diseases are often highly heterogeneous with a number of diagnostic subcategories or subconditions lying within the spectra (e.g., Autism Spectrum Disorder, schizophrenia). Discovering coherent subpopulations of subjects within the spectrum of pathological changes may further our understanding of diseases, and potentially identify subconditions that require alternative or modified treatment options. In this paper, we propose an approach that aims at identifying coherent subpopulations with respect to the underlying MRI in the scenario where the condition is heterogeneous and pathological changes form a continuous spectrum. We describe a Joint Maximum-Margin Classification and Clustering (JointMMCC) approach that jointly detects the pathologic population via semi-supervised classification, as well as disentangles heterogeneity of the pathological cohort by solving a clustering subproblem. We propose an efficient solution to the non-convex optimization problem associated with JointMMCC. We apply our proposed approach to an MRI study of aging, and identify coherent subpopulations (i.e., clusters) of cognitively less stable adults. PMID:22328179

Intelligent image processing for vegetation classification using multispectral LANDSAT data

NASA Astrophysics Data System (ADS)

Santos, Stewart R.; Flores, Jorge L.; Garcia-Torales, G.

2015-09-01

We propose an intelligent computational technique for analysis of vegetation imaging, which are acquired with multispectral scanner (MSS) sensor. This work focuses on intelligent and adaptive artificial neural network (ANN) methodologies that allow segmentation and classification of spectral remote sensing (RS) signatures, in order to obtain a high resolution map, in which we can delimit the wooded areas and quantify the amount of combustible materials present into these areas. This could provide important information to prevent fires and deforestation of wooded areas. The spectral RS input data, acquired by the MSS sensor, are considered in a random propagation remotely sensed scene with unknown statistics for each Thematic Mapper (TM) band. Performing high-resolution reconstruction and adding these spectral values with neighbor pixels information from each TM band, we can include contextual information into an ANN. The biggest challenge in conventional classifiers is how to reduce the number of components in the feature vector, while preserving the major information contained in the data, especially when the dimensionality of the feature space is high. Preliminary results show that the Adaptive Modified Neural Network method is a promising and effective spectral method for segmentation and classification in RS images acquired with MSS sensor.

Use of a modified Comprehensive Pain Evaluation Questionnaire: Characteristics and functional status of patients on entry to a tertiary care pain clinic

PubMed Central

Nelli, Jennifer M; Nicholson, Keith; Lakha, S Fatima; Louffat, Ada F; Chapparo, Luis; Furlan, Julio; Mailis-Gagnon, Angela

2012-01-01

BACKGROUND: With increasing knowledge of chronic pain, clinicians have attempted to assess chronic pain patients with lengthy assessment tools. OBJECTIVES: To describe the functional and emotional status of patients presenting to a tertiary care pain clinic; to assess the reliability and validity of a diagnostic classification system for chronic pain patients modelled after the Multidimensional Pain Inventory; to provide psychometric data on a modified Comprehensive Pain Evaluation Questionnaire (CPEQ); and to evaluate the relationship between the modified CPEQ construct scores and clusters with Diagnostic and Statistical Manual, Fourth Edition – Text Revision Pain Disorder diagnoses. METHODS: Data on 300 new patients over the course of nine months were collected using standardized assessment procedures plus a modified CPEQ at the Comprehensive Pain Program, Toronto Western Hospital, Toronto, Ontario. RESULTS: Cluster analysis of the modified CPEQ revealed three patient profiles, labelled Adaptive Copers, Dysfunctional, and Interpersonally Distressed, which closely resembled those previously reported. The distribution of modified CPEQ construct T scores across profile subtypes was similar to that previously reported for the original CPEQ. A novel finding was that of a strong relationship between the modified CPEQ clusters and constructs with Diagnostic and Statistical Manual, Fourth Edition – Text Revision Pain Disorder diagnoses. DISCUSSION AND CONCLUSIONS: The CPEQ, either the original or modified version, yields reproducible results consistent with the results of other studies. This technique may usefully classify chronic pain patients, but more work is needed to determine the meaning of the CPEQ clusters, what psychological or biomedical variables are associated with CPEQ constructs or clusters, and whether this instrument may assist in treatment planning or predict response to treatment. PMID:22518368

Modified rapid immunohistochemical staining for intraoperative diagnosis of malignant brain tumors.

PubMed

Suzuki, Akane; Maruyama, Takashi; Nitta, Masayuki; Komori, Takashi; Ikuta, Soko; Kawamata, Takakazu; Muragaki, Yoshihiro

2017-10-01

Rapid immunohistochemistry (R-IHC) has been developing mainly as a support technique in the rapid diagnosis of central nervous system tumors; however, there have been problems regarding instability in specimen preparation and immunostaining. To overcome the weakness of this technology, the instability of immunostaining, we developed a modified R-IHC. This was achieved by switching to 4% paraformaldehyde as the fixative solution and utilizing a commercially available Polymer Refine Detection Kit, as a high-sensitivity kit, in place of the secondary antibodies. In this study, we tested the modified R-IHC by evaluating rapid immunostaining on new staining items in 94 brain tumor removal cases, which took place at Tokyo Women's Medical University from 2014 to 2015. The results showed that, based on GFAP and p53 markers, the modified method obtained a higher stability in specimens than the standard rapid immunostaining method. It also achieved stainability on the same level as that of a permanent specimen. The modified method tested 86.6% (46/53) and 82.8% (24/29) in pHH3 and ATRX, respectively, in the percentage of correct classification (PCC) against the permanent specimens, and 100% (7/7) in the PCC against malignant lymphomas and gliomas that used CD20/CD3 for discrimination. We concluded that the modified R-IHC method indicated a higher stainability and PCC against the permanent specimens in comparison to the standard method in GFAP, p53, CD20/CD3, pHH3, and ATRX.

Constructing and Deconstructing Concepts.

PubMed

Doan, Charles A; Vigo, Ronaldo

2016-09-01

Several empirical investigations have explored whether observers prefer to sort sets of multidimensional stimuli into groups by employing one-dimensional or family-resemblance strategies. Although one-dimensional sorting strategies have been the prevalent finding for these unsupervised classification paradigms, several researchers have provided evidence that the choice of strategy may depend on the particular demands of the task. To account for this disparity, we propose that observers extract relational patterns from stimulus sets that facilitate the development of optimal classification strategies for relegating category membership. We conducted a novel constrained categorization experiment to empirically test this hypothesis by instructing participants to either add or remove objects from presented categorical stimuli. We employed generalized representational information theory (GRIT; Vigo, 2011b , 2013a , 2014 ) and its associated formal models to predict and explain how human beings chose to modify these categorical stimuli. Additionally, we compared model performance to predictions made by a leading prototypicality measure in the literature.

Climate of Hungary in the twentieth century according to Feddema

NASA Astrophysics Data System (ADS)

Ács, Ferenc; Breuer, Hajnalka; Skarbit, Nóra

2015-01-01

Feddema's (Physical Geography 26:442-466, 2005) bioclimatic classification scheme is applied to Hungary for the twentieth century using the Climatic Research Unit (CRU) data series. The method is tested in two modes. In the first, its original form is used which is suitable for global scale analysis. In the second, the criteria used in the method are slightly modified for mesoscale classification purposes. In both versions, potential evapotranspiration (PET) is calculated using McKenney and Rosenberg's (Meteorol 64:81-110, 1993) formula. We showed that McKenney and Rosenberg's formula could be applied to Hungary. According to Feddema's global scale application, local climates of the three main geographical regions, the Great Hungarian Plain, the North Hungarian Mountains, and Transdanubia, can be distinguished. However, the spatial distribution pattern within the regions is poorly reproduced, if at all. According to Feddema's mesoscale application, a picture of climatic subregions could be observed.

New fuzzy support vector machine for the class imbalance problem in medical datasets classification.

PubMed

Gu, Xiaoqing; Ni, Tongguang; Wang, Hongyuan

2014-01-01

In medical datasets classification, support vector machine (SVM) is considered to be one of the most successful methods. However, most of the real-world medical datasets usually contain some outliers/noise and data often have class imbalance problems. In this paper, a fuzzy support machine (FSVM) for the class imbalance problem (called FSVM-CIP) is presented, which can be seen as a modified class of FSVM by extending manifold regularization and assigning two misclassification costs for two classes. The proposed FSVM-CIP can be used to handle the class imbalance problem in the presence of outliers/noise, and enhance the locality maximum margin. Five real-world medical datasets, breast, heart, hepatitis, BUPA liver, and pima diabetes, from the UCI medical database are employed to illustrate the method presented in this paper. Experimental results on these datasets show the outperformed or comparable effectiveness of FSVM-CIP.

Enhanced risk management by an emerging multi-agent architecture

NASA Astrophysics Data System (ADS)

Lin, Sin-Jin; Hsu, Ming-Fu

2014-07-01

Classification in imbalanced datasets has attracted much attention from researchers in the field of machine learning. Most existing techniques tend not to perform well on minority class instances when the dataset is highly skewed because they focus on minimising the forecasting error without considering the relative distribution of each class. This investigation proposes an emerging multi-agent architecture, grounded on cooperative learning, to solve the class-imbalanced classification problem. Additionally, this study deals further with the obscure nature of the multi-agent architecture and expresses comprehensive rules for auditors. The results from this study indicate that the presented model performs satisfactorily in risk management and is able to tackle a highly class-imbalanced dataset comparatively well. Furthermore, the knowledge visualised process, supported by real examples, can assist both internal and external auditors who must allocate limited detecting resources; they can take the rules as roadmaps to modify the auditing programme.

Use of LANDSAT for land use and habitat inventories for the New Jersey Pinelands

NASA Technical Reports Server (NTRS)

Tracy, C.

1981-01-01

The New Jersey Heritage program surveyed available mapping information on landcover and vegetative communities and found that most commonly used sources, such as local land use maps and aerial photographs, were useful for individual sites, but either varied in their classifications or could not be used over extensive areas. A demonstration project using LANDSAT satellite information for the Great Egg Harbor/Tuckahoe watersheds was initiated with the goals of application (providing an inventory of vegetative communities and land use) flexibility (providing a method of collecting data which can be updated or modified in the future); and efficiency (allowing for an acceptable cost level by having staff undertake the project and avoid the more costly methods from air photo interpretation or on-site surveying. The classification procedure used is described and the spatial distributions of the 10 landcover classes determined are listed.

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

PubMed

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

2014-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Testing a tool for the classification of study designs in systematic reviews of interventions and exposures showed moderate reliability and low accuracy.

PubMed

Hartling, Lisa; Bond, Kenneth; Santaguida, P Lina; Viswanathan, Meera; Dryden, Donna M

2011-08-01

To develop and test a study design classification tool. We contacted relevant organizations and individuals to identify tools used to classify study designs and ranked these using predefined criteria. The highest ranked tool was a design algorithm developed, but no longer advocated, by the Cochrane Non-Randomized Studies Methods Group; this was modified to include additional study designs and decision points. We developed a reference classification for 30 studies; 6 testers applied the tool to these studies. Interrater reliability (Fleiss' κ) and accuracy against the reference classification were assessed. The tool was further revised and retested. Initial reliability was fair among the testers (κ=0.26) and the reference standard raters κ=0.33). Testing after revisions showed improved reliability (κ=0.45, moderate agreement) with improved, but still low, accuracy. The most common disagreements were whether the study design was experimental (5 of 15 studies), and whether there was a comparison of any kind (4 of 15 studies). Agreement was higher among testers who had completed graduate level training versus those who had not. The moderate reliability and low accuracy may be because of lack of clarity and comprehensiveness of the tool, inadequate reporting of the studies, and variability in tester characteristics. The results may not be generalizable to all published studies, as the test studies were selected because they had posed challenges for previous reviewers with respect to their design classification. Application of such a tool should be accompanied by training, pilot testing, and context-specific decision rules. Copyright © 2011 Elsevier Inc. All rights reserved.

Heart rate variability (HRV): an indicator of stress

NASA Astrophysics Data System (ADS)

Kaur, Balvinder; Durek, Joseph J.; O'Kane, Barbara L.; Tran, Nhien; Moses, Sophia; Luthra, Megha; Ikonomidou, Vasiliki N.

2014-05-01

Heart rate variability (HRV) can be an important indicator of several conditions that affect the autonomic nervous system, including traumatic brain injury, post-traumatic stress disorder and peripheral neuropathy [3], [4], [10] & [11]. Recent work has shown that some of the HRV features can potentially be used for distinguishing a subject's normal mental state from a stressed one [4], [13] & [14]. In all of these past works, although processing is done in both frequency and time domains, few classification algorithms have been explored for classifying normal from stressed RRintervals. In this paper we used 30 s intervals from the Electrocardiogram (ECG) time series collected during normal and stressed conditions, produced by means of a modified version of the Trier social stress test, to compute HRV-driven features and subsequently applied a set of classification algorithms to distinguish stressed from normal conditions. To classify RR-intervals, we explored classification algorithms that are commonly used for medical applications, namely 1) logistic regression (LR) [16] and 2) linear discriminant analysis (LDA) [6]. Classification performance for various levels of stress over the entire test was quantified using precision, accuracy, sensitivity and specificity measures. Results from both classifiers were then compared to find an optimal classifier and HRV features for stress detection. This work, performed under an IRB-approved protocol, not only provides a method for developing models and classifiers based on human data, but also provides a foundation for a stress indicator tool based on HRV. Further, these classification tools will not only benefit many civilian applications for detecting stress, but also security and military applications for screening such as: border patrol, stress detection for deception [3],[17], and wounded-warrior triage [12].

Classification of asteroid spectra using a neural network

NASA Technical Reports Server (NTRS)

Howell, E. S.; Merenyi, E.; Lebofsky, L. A.

1994-01-01

The 52-color asteroid survey (Bell et al., 1988) together with the 8-color asteroid survey (Zellner et al., 1985) provide a data set of asteroid spectra spanning 0.3-2.5 micrometers. An artificial neural network clusters these asteroid spectra based on their similarity to each other. We have also trained the neural network with a categorization learning output layer in a supervised mode to associate the established clusters with taxonomic classes. Results of our classification agree with Tholen's classification based on the 8-color data alone. When extending the spectral range using the 52-color survey data, we find that some modification of the Tholen classes is indicated to produce a cleaner, self-consistent set of taxonomic classes. After supervised training using our modified classes, the network correctly classifies both the training examples, and additional spectra into the correct class with an average of 90% accuracy. Our classification supports the separation of the K class from the S class, as suggested by Bell et al. (1987), based on the near-infrared spectrum. We define two end-member subclasses which seem to have compositional significance within the S class: the So class, which is olivine-rich and red, and the Sp class, which is pyroxene-rich and less red. The remaining S-class asteroids have intermediate compositions of both olivine and pyroxene and moderately red continua. The network clustering suggests some additional structure within the E-, M-, and P-class asteroids, even in the absence of albedo information, which is the only discriminant between these in the Tholen classification. New relationships are seen between the C class and related G, B, and F classes. However, in both cases, the number of spectra is too small to interpret or determine the significance of these separations.

Diagnosis and treatment of dyspeptic patients in Japan.

PubMed

Manabe, Noriaki; Haruma, Ken

2011-04-01

Although functional gastrointestinal (GI) disorders has been paid more attention recently in Japan, similar to Western countries, the clinical characteristics of dyspeptic patients, current diagnostic approach to dyspeptic patients and current standard treatments for dyspeptic patients are not well known in Japan. This review, in the most part, summarizes two topics about Japanese dyspeptic patients. The first topic is the pros and cons of the diagnosis of Japanese dyspeptic patients using Rome III classification on the basis of our data and the second topic deals with standard treatments for dyspeptic patients-especially by primary care doctors in Japan. We conducted a PubMed search using the following key words alone or in combination: functional dyspepsia (FD), medical treatment, Rome III classification and Japanese. The Rome III classification for FD does not adequately identify a large proportion of Japanese dyspeptic patients, primarily due to their earlier presentation for medical evaluation. There are many kinds of options for the treatment of FD in Japan: proton-pump inhibitors, histamine H(2) receptor antagonists, mucoprotective agents, Japanese traditional herbal medicines, Helicobacter pylori eradication therapy and prokinetics. Under the current situation, Japanese primary care doctors choose drugs according to each subtype of FD, which means that they prescribe medicine according to the pathogenesis of each patient. While the Rome III classification seems logical, some aspects need further evaluation for Japanese dyspeptic patients. Japanese primary care doctors choose drugs appropriately based on the pathogenesis of FD. However, efforts to further elucidate underlying pathophysiologic mechanisms and identify the appropriate patient population using modified Rome classification will be required. © 2011 Journal of Gastroenterology and Hepatology Foundation and Blackwell Publishing Asia Pty Ltd.

Evaluation of forest cover estimates for Haiti using supervised classification of Landsat data

NASA Astrophysics Data System (ADS)

Churches, Christopher E.; Wampler, Peter J.; Sun, Wanxiao; Smith, Andrew J.

2014-08-01

This study uses 2010-2011 Landsat Thematic Mapper (TM) imagery to estimate total forested area in Haiti. The thematic map was generated using radiometric normalization of digital numbers by a modified normalization method utilizing pseudo-invariant polygons (PIPs), followed by supervised classification of the mosaicked image using the Food and Agriculture Organization (FAO) of the United Nations Land Cover Classification System. Classification results were compared to other sources of land-cover data produced for similar years, with an emphasis on the statistics presented by the FAO. Three global land cover datasets (GLC2000, Globcover, 2009, and MODIS MCD12Q1), and a national-scale dataset (a land cover analysis by Haitian National Centre for Geospatial Information (CNIGS)) were reclassified and compared. According to our classification, approximately 32.3% of Haiti's total land area was tree covered in 2010-2011. This result was confirmed using an error-adjusted area estimator, which predicted a tree covered area of 32.4%. Standardization to the FAO's forest cover class definition reduces the amount of tree cover of our supervised classification to 29.4%. This result was greater than the reported FAO value of 4% and the value for the recoded GLC2000 dataset of 7.0%, but is comparable to values for three other recoded datasets: MCD12Q1 (21.1%), Globcover (2009) (26.9%), and CNIGS (19.5%). We propose that at coarse resolutions, the segmented and patchy nature of Haiti's forests resulted in a systematic underestimation of the extent of forest cover. It appears the best explanation for the significant difference between our results, FAO statistics, and compared datasets is the accuracy of the data sources and the resolution of the imagery used for land cover analyses. Analysis of recoded global datasets and results from this study suggest a strong linear relationship (R2 = 0.996 for tree cover) between spatial resolution and land cover estimates.

The Importance of Temporal and Spatial Vegetation Structure Information in Biotope Mapping Schemes: A Case Study in Helsingborg, Sweden

NASA Astrophysics Data System (ADS)

Gao, Tian; Qiu, Ling; Hammer, Mårten; Gunnarsson, Allan

2012-02-01

Temporal and spatial vegetation structure has impact on biodiversity qualities. Yet, current schemes of biotope mapping do only to a limited extend incorporate these factors in the mapping. The purpose of this study is to evaluate the application of a modified biotope mapping scheme that includes temporal and spatial vegetation structure. A refined scheme was developed based on a biotope classification, and applied to a green structure system in Helsingborg city in southern Sweden. It includes four parameters of vegetation structure: continuity of forest cover, age of dominant trees, horizontal structure, and vertical structure. The major green structure sites were determined by interpretation of panchromatic aerial photographs assisted with a field survey. A set of biotope maps was constructed on the basis of each level of modified classification. An evaluation of the scheme included two aspects in particular: comparison of species richness between long-continuity and short-continuity forests based on identification of woodland continuity using ancient woodland indicators (AWI) species and related historical documents, and spatial distribution of animals in the green space in relation to vegetation structure. The results indicate that (1) the relationship between forest continuity: according to verification of historical documents, the richness of AWI species was higher in long-continuity forests; Simpson's diversity was significantly different between long- and short-continuity forests; the total species richness and Shannon's diversity were much higher in long-continuity forests shown a very significant difference. (2) The spatial vegetation structure and age of stands influence the richness and abundance of the avian fauna and rabbits, and distance to the nearest tree and shrub was a strong determinant of presence for these animal groups. It is concluded that continuity of forest cover, age of dominant trees, horizontal and vertical structures of vegetation should now be included in urban biotope classifications.

Detection and classification of Breast Cancer in Wavelet Sub-bands of Fractal Segmented Cancerous Zones.

PubMed

Shirazinodeh, Alireza; Noubari, Hossein Ahmadi; Rabbani, Hossein; Dehnavi, Alireza Mehri

2015-01-01

Recent studies on wavelet transform and fractal modeling applied on mammograms for the detection of cancerous tissues indicate that microcalcifications and masses can be utilized for the study of the morphology and diagnosis of cancerous cases. It is shown that the use of fractal modeling, as applied to a given image, can clearly discern cancerous zones from noncancerous areas. In this paper, for fractal modeling, the original image is first segmented into appropriate fractal boxes followed by identifying the fractal dimension of each windowed section using a computationally efficient two-dimensional box-counting algorithm. Furthermore, using appropriate wavelet sub-bands and image Reconstruction based on modified wavelet coefficients, it is shown that it is possible to arrive at enhanced features for detection of cancerous zones. In this paper, we have attempted to benefit from the advantages of both fractals and wavelets by introducing a new algorithm. By using a new algorithm named F1W2, the original image is first segmented into appropriate fractal boxes, and the fractal dimension of each windowed section is extracted. Following from that, by applying a maximum level threshold on fractal dimensions matrix, the best-segmented boxes are selected. In the next step, the segmented Cancerous zones which are candidates are then decomposed by utilizing standard orthogonal wavelet transform and db2 wavelet in three different resolution levels, and after nullifying wavelet coefficients of the image at the first scale and low frequency band of the third scale, the modified reconstructed image is successfully utilized for detection of breast cancer regions by applying an appropriate threshold. For detection of cancerous zones, our simulations indicate the accuracy of 90.9% for masses and 88.99% for microcalcifications detection results using the F1W2 method. For classification of detected mictocalcification into benign and malignant cases, eight features are identified and utilized in radial basis function neural network. Our simulation results indicate the accuracy of 92% classification using F1W2 method.

Deriving common comorbidity indices from the MedDRA classification and exploring their performance on key outcomes in patients with rheumatoid arthritis.

PubMed

Putrik, Polina; Ramiro, Sofia; Lie, Elisabeth; Michaud, Kaleb; Kvamme, Maria K; Keszei, Andras P; Kvien, Tore K; Uhlig, Till; Boonen, Annelies

2018-03-01

To develop algorithms for calculating the Rheumatic Diseases Comorbidity Index (RDCI), Charlson-Deyo Index (CDI) and Functional Comorbidity Index (FCI) from the Medical Dictionary for Regulatory Activities (MedDRA), and to assess how these MedDRA-derived indices predict clinical outcomes, utility and health resource utilization (HRU). Two independent researchers linked the preferred terms of the MedDRA classification into the conditions included in the RDCI, the CDI and the FCI. Next, using data from the Norwegian Register-DMARD study (a register of patients with inflammatory joint diseases treated with DMARDs), the explanatory value of these indices was studied in models adjusted for age, gender and DAS28. Model fit statistics were compared in generalized estimating equation (prediction of outcome over time) models using as outcomes: modified HAQ, HAQ, physical and mental component summary of SF-36, SF6D and non-RA related HRU. Among 4126 patients with RA [72% female, mean (s.d.) age 56 (14) years], median (interquartile range) of RDCI at baseline was 0.0 (1.0) [range 0-6], CDI 0.0 (0.0) [0-7] and FCI 0.0 (1.0) [0-6]. All the comorbidity indices were associated with each outcome, and differences in their performance were moderate. The RDCI and FCI performed better on clinical outcomes: modified HAQ and HAQ, hospitalization, physical and mental component summary, and SF6D. Any non-RA related HRU was best predicted by RDCI followed by CDI. An algorithm is now available to compute three commonly used comorbidity indices from MedDRA classification. Indices performed comparably well in predicting a variety of outcomes, with the CDI performing slightly worse when predicting outcomes reflecting functioning and health. © The Author 2017. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Glatz Prototype Seat Impact Testing

DTIC Science & Technology

2013-07-03

airbag restraint, H-60A/L, crashworthiness, crashworthy, helicopter, rotorcraft, occupant restraint 16. SECURITY CLASSIFICATION OF: 17...data for Cell C, incorporating the H-60 Comp data, the new Glatz prototype data, and data from the airbag restraint program with a modified H-60A/L seat...1711 GLATZ VDT6290 Glatz 24.37 40.52 YES 922 42.40 1732 AIRBAG VDT6287 H-60A/L w/crotch strap mod 21.39* 40.56 YES 1267 21.27 1373 *Issue with

Adapting GNU random forest program for Unix and Windows

NASA Astrophysics Data System (ADS)

Jirina, Marcel; Krayem, M. Said; Jirina, Marcel, Jr.

2013-10-01

The Random Forest is a well-known method and also a program for data clustering and classification. Unfortunately, the original Random Forest program is rather difficult to use. Here we describe a new version of this program originally written in Fortran 77. The modified program in Fortran 95 needs to be compiled only once and information for different tasks is passed with help of arguments. The program was tested with 24 data sets from UCI MLR and results are available on the net.

Detection and Evaluation of Early Breast Cancer via Magnetic Resonance Imaging: Studies of Mouse Models and Clinical Implementation

DTIC Science & Technology

2009-03-01

compartment modeling on breast 3D DCE-MRI data, to relate kinetic curves to the underlying physiology of the lesions (14–18). However, for low time...classification provided high sensitivity and low specificity in diagnosing malignant lesions. The results demonstrated that the modified EMM fit the 3D...lesion localization and characterization.11 However, for low time resolution 3D DCEMRI data, the accuracy of physiological parameters ob- tained from

Automatic classification of animal vocalizations

NASA Astrophysics Data System (ADS)

Clemins, Patrick J.

2005-11-01

Bioacoustics, the study of animal vocalizations, has begun to use increasingly sophisticated analysis techniques in recent years. Some common tasks in bioacoustics are repertoire determination, call detection, individual identification, stress detection, and behavior correlation. Each research study, however, uses a wide variety of different measured variables, called features, and classification systems to accomplish these tasks. The well-established field of human speech processing has developed a number of different techniques to perform many of the aforementioned bioacoustics tasks. Melfrequency cepstral coefficients (MFCCs) and perceptual linear prediction (PLP) coefficients are two popular feature sets. The hidden Markov model (HMM), a statistical model similar to a finite autonoma machine, is the most commonly used supervised classification model and is capable of modeling both temporal and spectral variations. This research designs a framework that applies models from human speech processing for bioacoustic analysis tasks. The development of the generalized perceptual linear prediction (gPLP) feature extraction model is one of the more important novel contributions of the framework. Perceptual information from the species under study can be incorporated into the gPLP feature extraction model to represent the vocalizations as the animals might perceive them. By including this perceptual information and modifying parameters of the HMM classification system, this framework can be applied to a wide range of species. The effectiveness of the framework is shown by analyzing African elephant and beluga whale vocalizations. The features extracted from the African elephant data are used as input to a supervised classification system and compared to results from traditional statistical tests. The gPLP features extracted from the beluga whale data are used in an unsupervised classification system and the results are compared to labels assigned by experts. The development of a framework from which to build animal vocalization classifiers will provide bioacoustics researchers with a consistent platform to analyze and classify vocalizations. A common framework will also allow studies to compare results across species and institutions. In addition, the use of automated classification techniques can speed analysis and uncover behavioral correlations not readily apparent using traditional techniques.

Clinical classification of age-related macular degeneration.

PubMed

Ferris, Frederick L; Wilkinson, C P; Bird, Alan; Chakravarthy, Usha; Chew, Emily; Csaky, Karl; Sadda, SriniVas R

2013-04-01

To develop a clinical classification system for age-related macular degeneration (AMD). Evidence-based investigation, using a modified Delphi process. Twenty-six AMD experts, 1 neuro-ophthalmologist, 2 committee chairmen, and 1 methodologist. Each committee member completed an online assessment of statements summarizing current AMD classification criteria, indicating agreement or disagreement with each statement on a 9-step scale. The group met, reviewed the survey results, discussed the important components of a clinical classification system, and defined new data analyses needed to refine a classification system. After the meeting, additional data analyses from large studies were provided to the committee to provide risk estimates related to the presence of various AMD lesions. Delphi review of the 9-item set of statements resulting from the meeting. Consensus was achieved in generating a basic clinical classification system based on fundus lesions assessed within 2 disc diameters of the fovea in persons older than 55 years. The committee agreed that a single term, age-related macular degeneration, should be used for the disease. Persons with no visible drusen or pigmentary abnormalities should be considered to have no signs of AMD. Persons with small drusen (<63 μm), also termed drupelets, should be considered to have normal aging changes with no clinically relevant increased risk of late AMD developing. Persons with medium drusen (≥ 63-<125 μm), but without pigmentary abnormalities thought to be related to AMD, should be considered to have early AMD. Persons with large drusen or with pigmentary abnormalities associated with at least medium drusen should be considered to have intermediate AMD. Persons with lesions associated with neovascular AMD or geographic atrophy should be considered to have late AMD. Five-year risks of progressing to late AMD are estimated to increase approximately 100 fold, ranging from a 0.5% 5-year risk for normal aging changes to a 50% risk for the highest intermediate AMD risk group. The proposed basic clinical classification scale seems to be of value in predicting the risk of late AMD. Incorporating consistent nomenclature into the practice patterns of all eye care providers may improve communication and patient care. Copyright © 2013 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

[International multidisciplinary classification of acute pancreatitis severity: the 2013 Spanish edition].

PubMed

Maraví-Poma, E; Patchen Dellinger, E; Forsmark, C E; Layer, P; Lévy, P; Shimosegawa, T; Siriwardena, A K; Uomo, G; Whitcomb, D C; Windsor, J A; Petrov, M S

2014-05-01

To develop a new classification of acute pancreatitis severity on the basis of a sound conceptual framework, comprehensive review of the published evidence, and worldwide consultation. The Atlanta definitions of acute pancreatitis severity are ingrained in the lexicon of specialist in pancreatic diseases, but are suboptimal because these definitions are based on the empiric description of events not associated with severity. A personal invitation to contribute to the development of a new classification of acute pancreatitis severity was sent to all surgeons, gastroenterologists, internists, intensivists and radiologists currently active in the field of clinical acute pancreatitis. The invitation was not limited to members of certain associations or residents of certain countries. A global web-based survey was conducted, and a dedicated international symposium was organized to bring contributors from different disciplines together and discuss the concept and definitions. The new classification of severity is based on the actual local and systemic determinants of severity, rather than on the description of events that are non-causally associated with severity. The local determinant relates to whether there is (peri) pancreatic necrosis or not, and if present, whether it is sterile or infected. The systemic determinant relates to whether there is organ failure or not, and if present, whether it is transient or persistent. The presence of one determinant can modify the effect of another, whereby the presence of both infected (peri) pancreatic necrosis and persistent organ failure has a greater impact upon severity than either determinant alone. The derivation of a classification based on the above principles results in four categories of severity: mild, moderate, severe, and critical. This classification is the result of a consultative process among specialists in pancreatic diseases from 49 countries spanning North America, South America, Europe, Asia, Oceania and Africa. It provides a set of concise up to date definitions of all the main entities pertinent to classifying the severity of acute pancreatitis in clinical practice and research. This ensures that the determinant-based classification can be used in a uniform manner throughout the world. Copyright © 2013 Elsevier España, S.L. and SEMICYUC. All rights reserved.

Classification of Foreign Body Reactions due to Industrial Silicone Injection.

PubMed

Harlim, Ago; Kanoko, Mpu; Aisah, Siti

2018-05-02

A foreign body reaction (FBR) is a typical tissue response to a biomaterial that has been injected or implanted in human body tissue. There has been a lack of data on the classification of foreign body reaction to silicone injection, which can describe the pattern of body tissue responses to silicone. Determine the foreign body reaction to silicone injection. We modified the classification proposed by Duranti and colleagues, which has categorized a FBR to hyaluronic acid injection into a new classification of an FBR to silicone injection. A cohort study of 31 women suffering from silicone-induced granulomas on their chin was conducted. Granulomatous tissue and submental skin were stained with hematoxylin-eosin and evaluated. Our data revealed that there were at least 7 categories of FBRs to silicone injection that could be developed. Categories 1 to 4 showed inflammatory activity, and categories 5 to 8 showed tissue repair by fibrosis. Using histopathological staining, we are able to sequence the steps of body reactions to silicone injection. Initial inflammatory reaction is then replaced by fibrosis process repairing the damaged tissues. The process depends on the host immune tolerance.This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal.

Risk factors associated with oroantral perforation during surgical removal of maxillary third molar teeth.

PubMed

Hasegawa, Takumi; Tachibana, Akira; Takeda, Daisuke; Iwata, Eiji; Arimoto, Satomi; Sakakibara, Akiko; Akashi, Masaya; Komori, Takahide

2016-12-01

The relationship between radiographic findings and the occurrence of oroantral perforation is controversial. Few studies have quantitatively analyzed the risk factors contributing to oroantral perforation, and no study has reported multivariate analysis of the relationship(s) between these various factors. This retrospective study aims to fill this void. Various risk factors for oroantral perforation during maxillary third molar extraction were investigated by univariate and multivariate analysis. The proximity of the roots to the maxillary sinus floor (root-sinus [RS] classification) was assessed using panoramic radiography and classified as types 1-5. The relationship between the maxillary second and third molars was classified according to a modified version of the Archer classification. The relative depth of the maxillary third molar in the bone was classified as class A-C, and its angulation relative to the long axis of the second molar was also recorded. Performance of an incision (OR 5.16), mesioangular tooth angulation (OR 6.05), and type 3 RS classification (i.e., significant superimposition of the roots of all posterior maxillary teeth with the sinus floor; OR 10.18) were all identified as risk factors with significant association to an outcome of oroantral perforation. To our knowledge, this is the first multivariate analysis of the risk factors for oroantral perforation during surgical extraction of the maxillary third molar. This RS classification may offer a new predictive parameter for estimating the risk of oroantral perforation.

Hybrid Modified K-Means with C4.5 for Intrusion Detection Systems in Multiagent Systems

PubMed Central

Laftah Al-Yaseen, Wathiq; Ali Othman, Zulaiha; Ahmad Nazri, Mohd Zakree

2015-01-01

Presently, the processing time and performance of intrusion detection systems are of great importance due to the increased speed of traffic data networks and a growing number of attacks on networks and computers. Several approaches have been proposed to address this issue, including hybridizing with several algorithms. However, this paper aims at proposing a hybrid of modified K-means with C4.5 intrusion detection system in a multiagent system (MAS-IDS). The MAS-IDS consists of three agents, namely, coordinator, analysis, and communication agent. The basic concept underpinning the utilized MAS is dividing the large captured network dataset into a number of subsets and distributing these to a number of agents depending on the data network size and core CPU availability. KDD Cup 1999 dataset is used for evaluation. The proposed hybrid modified K-means with C4.5 classification in MAS is developed in JADE platform. The results show that compared to the current methods, the MAS-IDS reduces the IDS processing time by up to 70%, while improving the detection accuracy. PMID:26161437

Hybrid Modified K-Means with C4.5 for Intrusion Detection Systems in Multiagent Systems.

PubMed

Laftah Al-Yaseen, Wathiq; Ali Othman, Zulaiha; Ahmad Nazri, Mohd Zakree

2015-01-01

Presently, the processing time and performance of intrusion detection systems are of great importance due to the increased speed of traffic data networks and a growing number of attacks on networks and computers. Several approaches have been proposed to address this issue, including hybridizing with several algorithms. However, this paper aims at proposing a hybrid of modified K-means with C4.5 intrusion detection system in a multiagent system (MAS-IDS). The MAS-IDS consists of three agents, namely, coordinator, analysis, and communication agent. The basic concept underpinning the utilized MAS is dividing the large captured network dataset into a number of subsets and distributing these to a number of agents depending on the data network size and core CPU availability. KDD Cup 1999 dataset is used for evaluation. The proposed hybrid modified K-means with C4.5 classification in MAS is developed in JADE platform. The results show that compared to the current methods, the MAS-IDS reduces the IDS processing time by up to 70%, while improving the detection accuracy.

The modified Hodge test is a useful tool for ruling out Klebsiella pneumoniae carbapenemase.

PubMed

Cury, Ana Paula; Andreazzi, Denise; Maffucci, Márcia; Caiaffa-Junior, Hélio Hehl; Rossi, Flávia

2012-12-01

Enterobacteriaceae bacteria harboring Klebsiella pneumoniae carbapenemase are a serious worldwide threat. The molecular identification of these pathogens is not routine in Brazilian hospitals, and a rapid phenotypic screening test is desirable. This study aims to evaluate the modified Hodge test as a phenotypic screening test for Klebsiella pneumoniae carbapenemase. From April 2009 to July 2011, all Enterobacteriaceae bacteria that were not susceptible to ertapenem according to Vitek2 analysis were analyzed with the modified Hodge test. All positive isolates and a random subset of negative isolates were also assayed for the presence of blaKPC. Isolates that were positive in modified Hodge tests were sub-classified as true-positives (E. coli touched the ertapenem disk) or inconclusive (distortion of the inhibition zone of E. coli, but growth did not reach the ertapenem disk). Negative results were defined as samples with no distortion of the inhibition zone around the ertapenem disk. Among the 1521 isolates of Enterobacteriaceae bacteria that were not susceptible to ertapenem, 30% were positive for blaKPC, and 35% were positive according to the modified Hodge test (81% specificity). Under the proposed sub-classification, true positives showed a 98% agreement with the blaKPC results. The negative predictive value of the modified Hodge test for detection was 100%. KPC producers showed high antimicrobial resistance rates, but 90% and 77% of these isolates were susceptible to aminoglycoside and tigecycline, respectively. Standardizing the modified Hodge test interpretation may improve the specificity of KPC detection. In this study, negative test results ruled out 100% of the isolates harboring Klebsiella pneumoniae carbapenemase 2. The test may therefore be regarded as a good epidemiological tool.

Modifiable and non-modifiable factors associated with employment outcomes following spinal cord injury: A systematic review

PubMed Central

Trenaman, Logan; Miller, William C; Querée, Matthew; Escorpizo, Reuben

2015-01-01

Context Employment rates in individuals with spinal cord injury (SCI) are approximately 35%, which is considerably lower than that of the general population. In order to improve employment outcomes a clear understanding of what factors influence employment outcomes is needed. Objective To systematically review factors that are consistently and independently associated with employment outcomes in individuals with SCI, and to understand the magnitude of their influence. Methods Through an electronic search of MEDLINE/PubMed, EMBASE, CINAHL, PsycINFO, Social Science Abstracts and Social Work databases, we identified studies published between 1952–2014 that investigated factors associated with employment outcomes following SCI. Exclusion criteria included: (1) reviews (2) studies not published in English (3) studies not controlling for potential confounders through a regression analysis, or (4) studies not providing an effect measure in the form of OR, RR, or HR. Data were categorized based on the International Classification of Functioning, Disability and Health framework, with each domain sub-categorized by modifiability. First author, year of publication, sample size, explanatory and outcome variables, and effect measures were extracted. Results Thirty-nine studies met the inclusion criteria. Twenty modifiable and twelve non-modifiable factors have been investigated in the context of employment following SCI. Education, vocational rehabilitation, functional independence, social support, and financial disincentives were modifiable factors that have been consistently and independently associated with employment outcomes. Conclusion A number of key modifiable factors have been identified and can inform interventions aimed at improving employment outcomes for individuals with SCI. Future research should focus on determining which factors have the greatest effect on employment outcomes, in addition to developing and evaluating interventions targeted at these factors. PMID:25989899

Early Detection for Dengue Using Local Indicator of Spatial Association (LISA) Analysis

PubMed Central

Parra-Amaya, Mayra Elizabeth; Puerta-Yepes, María Eugenia; Lizarralde-Bejarano, Diana Paola; Arboleda-Sánchez, Sair

2016-01-01

Dengue is a viral disease caused by a flavivirus that is transmitted by mosquitoes of the genus Aedes. There is currently no specific treatment or commercial vaccine for its control and prevention; therefore, mosquito population control is the only alternative for preventing the occurrence of dengue. For this reason, entomological surveillance is recommended by World Health Organization (WHO) to measure dengue risk in endemic areas; however, several works have shown that the current methodology (aedic indices) is not sufficient for predicting dengue. In this work, we modified indices proposed for epidemic periods. The raw value of the epidemiological wave could be useful for detecting risk in epidemic periods; however, risk can only be detected if analyses incorporate the maximum epidemiological wave. Risk classification was performed according to Local Indicators of Spatial Association (LISA) methodology. The modified indices were analyzed using several hypothetical scenarios to evaluate their sensitivity. We found that modified indices could detect spatial and differential risks in epidemic and endemic years, which makes them a useful tool for the early detection of a dengue outbreak. In conclusion, the modified indices could predict risk at the spatio-temporal level in endemic years and could be incorporated in surveillance activities in endemic places. PMID:28933396

Automated Outcome Classification of Computed Tomography Imaging Reports for Pediatric Traumatic Brain Injury.

PubMed

Yadav, Kabir; Sarioglu, Efsun; Choi, Hyeong Ah; Cartwright, Walter B; Hinds, Pamela S; Chamberlain, James M

2016-02-01

The authors have previously demonstrated highly reliable automated classification of free-text computed tomography (CT) imaging reports using a hybrid system that pairs linguistic (natural language processing) and statistical (machine learning) techniques. Previously performed for identifying the outcome of orbital fracture in unprocessed radiology reports from a clinical data repository, the performance has not been replicated for more complex outcomes. To validate automated outcome classification performance of a hybrid natural language processing (NLP) and machine learning system for brain CT imaging reports. The hypothesis was that our system has performance characteristics for identifying pediatric traumatic brain injury (TBI). This was a secondary analysis of a subset of 2,121 CT reports from the Pediatric Emergency Care Applied Research Network (PECARN) TBI study. For that project, radiologists dictated CT reports as free text, which were then deidentified and scanned as PDF documents. Trained data abstractors manually coded each report for TBI outcome. Text was extracted from the PDF files using optical character recognition. The data set was randomly split evenly for training and testing. Training patient reports were used as input to the Medical Language Extraction and Encoding (MedLEE) NLP tool to create structured output containing standardized medical terms and modifiers for negation, certainty, and temporal status. A random subset stratified by site was analyzed using descriptive quantitative content analysis to confirm identification of TBI findings based on the National Institute of Neurological Disorders and Stroke (NINDS) Common Data Elements project. Findings were coded for presence or absence, weighted by frequency of mentions, and past/future/indication modifiers were filtered. After combining with the manual reference standard, a decision tree classifier was created using data mining tools WEKA 3.7.5 and Salford Predictive Miner 7.0. Performance of the decision tree classifier was evaluated on the test patient reports. The prevalence of TBI in the sampled population was 159 of 2,217 (7.2%). The automated classification for pediatric TBI is comparable to our prior results, with the notable exception of lower positive predictive value. Manual review of misclassified reports, 95.5% of which were false-positives, revealed that a sizable number of false-positive errors were due to differing outcome definitions between NINDS TBI findings and PECARN clinical important TBI findings and report ambiguity not meeting definition criteria. A hybrid NLP and machine learning automated classification system continues to show promise in coding free-text electronic clinical data. For complex outcomes, it can reliably identify negative reports, but manual review of positive reports may be required. As such, it can still streamline data collection for clinical research and performance improvement. © 2016 by the Society for Academic Emergency Medicine.

Automated Outcome Classification of Computed Tomography Imaging Reports for Pediatric Traumatic Brain Injury

PubMed Central

Yadav, Kabir; Sarioglu, Efsun; Choi, Hyeong-Ah; Cartwright, Walter B.; Hinds, Pamela S.; Chamberlain, James M.

2016-01-01

Background The authors have previously demonstrated highly reliable automated classification of free text computed tomography (CT) imaging reports using a hybrid system that pairs linguistic (natural language processing) and statistical (machine learning) techniques. Previously performed for identifying the outcome of orbital fracture in unprocessed radiology reports from a clinical data repository, the performance has not been replicated for more complex outcomes. Objectives To validate automated outcome classification performance of a hybrid natural language processing (NLP) and machine learning system for brain CT imaging reports. The hypothesis was that our system has performance characteristics for identifying pediatric traumatic brain injury (TBI). Methods This was a secondary analysis of a subset of 2,121 CT reports from the Pediatric Emergency Care Applied Research Network (PECARN) TBI study. For that project, radiologists dictated CT reports as free text, which were then de-identified and scanned as PDF documents. Trained data abstractors manually coded each report for TBI outcome. Text was extracted from the PDF files using optical character recognition. The dataset was randomly split evenly for training and testing. Training patient reports were used as input to the Medical Language Extraction and Encoding (MedLEE) NLP tool to create structured output containing standardized medical terms and modifiers for negation, certainty, and temporal status. A random subset stratified by site was analyzed using descriptive quantitative content analysis to confirm identification of TBI findings based upon the National Institute of Neurological Disorders and Stroke Common Data Elements project. Findings were coded for presence or absence, weighted by frequency of mentions, and past/future/indication modifiers were filtered. After combining with the manual reference standard, a decision tree classifier was created using data mining tools WEKA 3.7.5 and Salford Predictive Miner 7.0. Performance of the decision tree classifier was evaluated on the test patient reports. Results The prevalence of TBI in the sampled population was 159 out of 2,217 (7.2%). The automated classification for pediatric TBI is comparable to our prior results, with the notable exception of lower positive predictive value (PPV). Manual review of misclassified reports, 95.5% of which were false positives, revealed that a sizable number of false-positive errors were due to differing outcome definitions between NINDS TBI findings and PECARN clinical important TBI findings, and report ambiguity not meeting definition criteria. Conclusions A hybrid NLP and machine learning automated classification system continues to show promise in coding free-text electronic clinical data. For complex outcomes, it can reliably identify negative reports, but manual review of positive reports may be required. As such, it can still streamline data collection for clinical research and performance improvement. PMID:26766600

A classification of morphoseismic features in the New Madrid seismic zone

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

Knox, R.; Stewart, D.

1993-03-01

The New Madrid Seismic Zone (NMSZ) contains thousands of surface features distributed over 5,000 square miles in four states. These are attributable to some combination of (1) seismically-induced liquefaction (SIL), (2) secondary deformation, and (3) seismically-induced slope failures. Most of these features were produced by the 1811--12 series of great earthquakes, but some predate and some postdate 1811--12. Subsequent non-seismic factors, such as hydrologically-induced liquefaction (HIL), mechanically-induced liquefaction (MIL), human activities, mass wasting, eolian and fluvial processes have modified all of these features. Morphoseismic features are new landforms produced by earthquakes, or are pre-existing landforms modified by them. Involved aremore » complex interrelationships among several variables, including: (1) intensity and duration of seismic ground motion, (2) surface wave harmonics, (3) depth to water table, (4) depth to basement, (5) particle size, composition, and sorting of sediment making up the liquefied (LZ) and non-liquefied zones (NLZ), (6) topographic parameters, and (7) attitudes of beds and lenses susceptible to liquefaction. Morphoseismic features are depicted as results of a time-flow sequence initiated by primary basement disturbances which produce three major categories of surface response: secondary deformation, liquefaction and slope failure. Nine subcategories incorporate features produced by or resulting in: extruded sand, intruded sand, lateral spreading, faulting, subsidence of large areas, uplift of large areas, altered streams, coherent landslides, and incoherent landslides. The total morphoseismic features identified by this classification are 34 in number.« less

A hydrologically explicit, spatially exact, classification of landforms for Canada at 1:500,000 scale.

NASA Astrophysics Data System (ADS)

MacMillan, Robert A.; Geng, Xiaoyuan; Smith, Scott; Zawadzka, Joanna; Hengl, Tom

2016-04-01

A new approach for classifying landform types has been developed and applied to all of Canada using a 250 m DEM. The resulting LandMapR classification has been designed to provide a stable and consistent spatial fabric to act as initial proto-polygons to be used in updating the current 1:1 M scale Soil Landscapes of Canada map to 1:500,000 scale. There is a desire to make the current SLC polygon fabric more consistent across the country, more correctly aligned to observable hydrological and landscape features, more spatially exact, more detailed and more interpretable. The approach is essentially a modification of the Hammond (1954) criteria for classifying macro landform types as implemented for computerized analysis by Dikau (1989, 1991) and Brabyn (1998). The major modification is that the key input variables of local relief and relative position in the landscape are computed for specific hillslopes that occur between individual, explicitly defined, channels and divides. While most approaches, including Dikau et al., (1991) and SOTER (Dobos et al., 2005) compute relative relief and landscape position within a neighborhood analysis window (NAW) of some fixed size (9,600 m and 1 km respectively) the LandMapR method assesses these variables based on explicit analysis of flow paths between locally defined divides and channels (or lakes). We have modified the Hammond criteria by splitting the lowest relief class of 0-30 m into 4 classes of 0-0 m, 0-1 m, 1-10 m and 10-30 m) in order to be able to better differentiate subtle landform features in areas of low relief. Essentially this enables recognition of lakes and open water (0 relief and 0 slope), shorelines and littoral zones (0-1 m), nearly flat, low-relief landforms (1-10 m) and low relief undulating plains (10-30 m). We also modified the Hammond approach for separating upper versus lower landform positions used to differentiate flat areas in uplands from flat lowlands. We instead differentiate 3 relative slope positions of channel valley, toe slope and upper slope consistently and exhaustively and so can identify any flat areas that occur in any of these three landform positions. We did not find it necessary to use slope gradient as a criteria for defining and delineating classes because relief acts as a surrogate for slope and each relief class exhibits a narrow and definable range of slope gradients. Dominant slope gradient (or other attributes) can be computed, post classification, for each defined polygon, if there is a need to further classify by slope or other attribute. This simplifies classification and also reduces pixilation in the classification arising from considering too many local criteria in the class definitions. The resulting polygons provide an extremely detailed classification of relief and landform position at the level of individual hillslopes across all of Canada. The polygon boundaries explicitly follow major identifiable drainage networks and work their way upslope to delineate interfluves that occupy upslope positions at all levels of relief. The detailed LandMapR polygon classifications nest consistently within more general regions defined by the original Hammond-Dikau procedures. Initial visual analysis reveals a strong and consistent spatial relationship between observable changes in slope, vegetation and drainage regime and LandMapR landform polygon boundaries. More detailed quantitative assessment of the accuracy and utility of the LandMapR polygon classes is planned.

Validation of the Valve Academic Research Consortium Bleeding Definition in Patients With Severe Aortic Stenosis Undergoing Transcatheter Aortic Valve Implantation.

PubMed

Stortecky, Stefan; Stefanini, Giulio G; Pilgrim, Thomas; Heg, Dik; Praz, Fabien; Luterbacher, Fabienne; Piccolo, Raffaele; Khattab, Ahmed A; Räber, Lorenz; Langhammer, Bettina; Huber, Christoph; Meier, Bernhard; Jüni, Peter; Wenaweser, Peter; Windecker, Stephan

2015-09-25

The Valve Academic Research Consortium (VARC) has proposed a standardized definition of bleeding in patients undergoing transcatheter aortic valve interventions (TAVI). The VARC bleeding definition has not been validated or compared to other established bleeding definitions so far. Thus, we aimed to investigate the impact of bleeding and compare the predictivity of VARC bleeding events with established bleeding definitions. Between August 2007 and April 2012, 489 consecutive patients with severe aortic stenosis were included into the Bern-TAVI-Registry. Every bleeding complication was adjudicated according to the definitions of VARC, BARC, TIMI, and GUSTO. Periprocedural blood loss was added to the definition of VARC, providing a modified VARC definition. A total of 152 bleeding events were observed during the index hospitalization. Bleeding severity according to VARC was associated with a gradual increase in mortality, which was comparable to the BARC, TIMI, GUSTO, and the modified VARC classifications. The predictive precision of a multivariable model for mortality at 30 days was significantly improved by adding the most serious bleeding of VARC (area under the curve [AUC], 0.773; 95% confidence interval [CI], 0.706 to 0.839), BARC (AUC, 0.776; 95% CI, 0.694 to 0.857), TIMI (AUC, 0.768; 95% CI, 0.692 to 0.844), and GUSTO (AUC, 0.791; 95% CI, 0.714 to 0.869), with the modified VARC definition resulting in the best predictivity (AUC, 0.814; 95% CI, 0.759 to 0.870). The VARC bleeding definition offers a severity stratification that is associated with a gradual increase in mortality and prognostic information comparable to established bleeding definitions. Adding the information of periprocedural blood loss to VARC may increase the sensitivity and the predictive power of this classification. © 2015 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.

Current food classifications in epidemiological studies do not enable solid nutritional recommendations for preventing diet-related chronic diseases: the impact of food processing.

PubMed

Fardet, Anthony; Rock, Edmond; Bassama, Joseph; Bohuon, Philippe; Prabhasankar, Pichan; Monteiro, Carlos; Moubarac, Jean-Claude; Achir, Nawel

2015-11-01

To date, observational studies in nutrition have categorized foods into groups such as dairy, cereals, fruits, and vegetables. However, the strength of the association between food groups and chronic diseases is far from convincing. In most international expert surveys, risks are most commonly scored as probable, limited, or insufficient rather than convincing. In this position paper, we hypothesize that current food classifications based on botanical or animal origins can be improved to yield solid recommendations. We propose using a food classification that employs food processes to rank foods in epidemiological studies. Indeed, food health potential results from both nutrient density and food structure (i.e., the matrix effect), both of which can potentially be positively or negatively modified by processing. For example, cereal-based foods may be more or less refined, fractionated, and recombined with added salt, sugars, and fats, yielding a panoply of products with very different nutritional values. The same is true for other food groups. Finally, we propose that from a nutritional perspective, food processing will be an important issue to consider in the coming years, particularly in terms of strengthening the links between food and health and for proposing improved nutritional recommendations or actions. © 2015 American Society for Nutrition.

Mutual information-based analysis of JPEG2000 contexts.

PubMed

Liu, Zhen; Karam, Lina J

2005-04-01

Context-based arithmetic coding has been widely adopted in image and video compression and is a key component of the new JPEG2000 image compression standard. In this paper, the contexts used in JPEG2000 are analyzed using the mutual information, which is closely related to the compression performance. We first show that, when combining the contexts, the mutual information between the contexts and the encoded data will decrease unless the conditional probability distributions of the combined contexts are the same. Given I, the initial number of contexts, and F, the final desired number of contexts, there are S(I, F) possible context classification schemes where S(I, F) is called the Stirling number of the second kind. The optimal classification scheme is the one that gives the maximum mutual information. Instead of using an exhaustive search, the optimal classification scheme can be obtained through a modified generalized Lloyd algorithm with the relative entropy as the distortion metric. For binary arithmetic coding, the search complexity can be reduced by using dynamic programming. Our experimental results show that the JPEG2000 contexts capture the correlations among the wavelet coefficients very well. At the same time, the number of contexts used as part of the standard can be reduced without loss in the coding performance.

A System for Heart Sounds Classification

PubMed Central

Redlarski, Grzegorz; Gradolewski, Dawid; Palkowski, Aleksander

2014-01-01

The future of quick and efficient disease diagnosis lays in the development of reliable non-invasive methods. As for the cardiac diseases – one of the major causes of death around the globe – a concept of an electronic stethoscope equipped with an automatic heart tone identification system appears to be the best solution. Thanks to the advancement in technology, the quality of phonocardiography signals is no longer an issue. However, appropriate algorithms for auto-diagnosis systems of heart diseases that could be capable of distinguishing most of known pathological states have not been yet developed. The main issue is non-stationary character of phonocardiography signals as well as a wide range of distinguishable pathological heart sounds. In this paper a new heart sound classification technique, which might find use in medical diagnostic systems, is presented. It is shown that by combining Linear Predictive Coding coefficients, used for future extraction, with a classifier built upon combining Support Vector Machine and Modified Cuckoo Search algorithm, an improvement in performance of the diagnostic system, in terms of accuracy, complexity and range of distinguishable heart sounds, can be made. The developed system achieved accuracy above 93% for all considered cases including simultaneous identification of twelve different heart sound classes. The respective system is compared with four different major classification methods, proving its reliability. PMID:25393113

[New colposcopic terminology: Rio de Janeiro--2011].

PubMed

Zlatkov, V; Kostova, P

2014-01-01

The purpose of this work is to review the new colposcopic classification of the International Federation for Cervical Pathology and Colposcopy (IFCPC) from 2011 and the possibilities for its application in diagnostic and treatment processes and research. It fulfills the necessity for a modern and widely applicable nomenclature of the findings and it is based on the latest knowledge in this area. Colposcopic terminology of the vagina, as part of the pathology of the lower genital tract, is included as well, while the vulva and perineum terminology is not yet finally adopted. Furthermore, the various cervical excisional techniques are evaluated and described. According to experts, the popularity of colposcopy will not diminish and it will continue to be used as a routine technique in daily practice. In a critical sense, despite its descriptive and punctual character, the accepted terminology classification does not give a new interpretation of the severity of changes, and as such, it does not significantly modify the diagnostic and therapeutic approach. The lack of a scoring system that would allow the dynamic comparison of the severity of symptoms and the categories over time is a serious weakness. This limits the new colposcopic classification as no more than a working sheet that descriptively assesses the findings of the lower genital tract.

Current Food Classifications in Epidemiological Studies Do Not Enable Solid Nutritional Recommendations for Preventing Diet-Related Chronic Diseases: The Impact of Food Processing12

PubMed Central

Fardet, Anthony; Rock, Edmond; Bassama, Joseph; Bohuon, Philippe; Prabhasankar, Pichan; Monteiro, Carlos; Moubarac, Jean-Claude; Achir, Nawel

2015-01-01

To date, observational studies in nutrition have categorized foods into groups such as dairy, cereals, fruits, and vegetables. However, the strength of the association between food groups and chronic diseases is far from convincing. In most international expert surveys, risks are most commonly scored as probable, limited, or insufficient rather than convincing. In this position paper, we hypothesize that current food classifications based on botanical or animal origins can be improved to yield solid recommendations. We propose using a food classification that employs food processes to rank foods in epidemiological studies. Indeed, food health potential results from both nutrient density and food structure (i.e., the matrix effect), both of which can potentially be positively or negatively modified by processing. For example, cereal-based foods may be more or less refined, fractionated, and recombined with added salt, sugars, and fats, yielding a panoply of products with very different nutritional values. The same is true for other food groups. Finally, we propose that from a nutritional perspective, food processing will be an important issue to consider in the coming years, particularly in terms of strengthening the links between food and health and for proposing improved nutritional recommendations or actions. PMID:26567188

Computed aided system for separation and classification of the abnormal erythrocytes in human blood

NASA Astrophysics Data System (ADS)

Wąsowicz, Michał; Grochowski, Michał; Kulka, Marek; Mikołajczyk, Agnieszka; Ficek, Mateusz; Karpieńko, Katarzyna; Cićkiewicz, Maciej

2017-12-01

The human peripheral blood consists of cells (red cells, white cells, and platelets) suspended in plasma. In the following research the team assessed an influence of nanodiamond particles on blood elements over various periods of time. The material used in the study consisted of samples taken from ten healthy humans of various age, different blood types and both sexes. The markings were leaded by adding to the blood unmodified diamonds and oxidation modified. The blood was put under an impact of two diamond concentrations: 20μl and 100μl. The amount of abnormal cells increased with time. The percentage of echinocytes as a result of interaction with nanodiamonds in various time intervals for individual specimens was scarce. The impact of the two diamond types had no clinical importance on red blood cells. It is supposed that as a result of longlasting exposure a dehydratation of red cells takes place, because of the function of the cells. The analysis of an influence of nanodiamond particles on blood elements was supported by computer system designed for automatic counting and classification of the Red Blood Cells (RBC). The system utilizes advanced image processing methods for RBCs separation and counting and Eigenfaces method coupled with the neural networks for RBCs classification into normal and abnormal cells purposes.

Management of proximal humeral fractures in the nineteenth century: an historical review of preradiographic sources.

PubMed

Brorson, Stig

2011-04-01

The diagnosis and treatment of fractures of the proximal humerus have troubled patients and medical practitioners since antiquity. Preradiographic diagnosis relied on surface anatomy, pain localization, crepitus, and impaired function. During the nineteenth century, a more thorough understanding of the pathoanatomy and pathophysiology of proximal humeral fractures was obtained, and new methods of reduction and bandaging were developed. I reviewed nineteenth-century principles of (1) diagnosis, (2) classification, (3) reduction, (4) bandaging, and (5) concepts of displacement in fractures of the proximal humerus. A narrative review of nineteenth-century surgical texts is presented. Sources were identified by searching bibliographic databases, orthopaedic sourcebooks, textbooks in medical history, and a subsequent hand search. Substantial progress in understanding fractures of the proximal humerus is found in nineteenth-century textbooks. A rational approach to understanding fractures of the proximal humerus was made possible by an appreciation of the underlying functional anatomy and subsequent pathoanatomy. Thus, new principles of diagnosis, pathoanatomic classifications, modified methods of reduction, functional bandaging, and advanced concepts of displacement were proposed, challenging the classic management adhered to for more than 2000 years. The principles for modern pathoanatomic and pathophysiologic understanding of proximal humeral fractures and the principles for classification, nonsurgical treatment, and bandaging were established in the preradiographic era.

Computer-aided analysis of Skylab multispectral scanner data in mountainous terrain for land use, forestry, water resource, and geologic applications

NASA Technical Reports Server (NTRS)

Hoffer, R. M. (Principal Investigator)

1975-01-01

The author has identified the following significant results. One of the most significant results of this Skylab research involved the geometric correction and overlay of the Skylab multispectral scanner data with the LANDSAT multispectral scanner data, and also with a set of topographic data, including elevation, slope, and aspect. The Skylab S192 multispectral scanner data had distinct differences in noise level of the data in the various wavelength bands. Results of the temporal evaluation of the SL-2 and SL-3 photography were found to be particularly important for proper interpretation of the computer-aided analysis of the SL-2 and SL-3 multispectral scanner data. There was a quality problem involving the ringing effect introduced by digital filtering. The modified clustering technique was found valuable when working with multispectral scanner data involving many wavelength bands and covering large geographic areas. Analysis of the SL-2 scanner data involved classification of major cover types and also forest cover types. Comparison of the results obtained wth Skylab MSS data and LANDSAT MSS data indicated that the improved spectral resolution of the Skylab scanner system enabled a higher classification accuracy to be obtained for forest cover types, although the classification performance for major cover types was not significantly different.

Evaluation of image features and classification methods for Barrett's cancer detection using VLE imaging

NASA Astrophysics Data System (ADS)

Klomp, Sander; van der Sommen, Fons; Swager, Anne-Fré; Zinger, Svitlana; Schoon, Erik J.; Curvers, Wouter L.; Bergman, Jacques J.; de With, Peter H. N.

2017-03-01

Volumetric Laser Endomicroscopy (VLE) is a promising technique for the detection of early neoplasia in Barrett's Esophagus (BE). VLE generates hundreds of high resolution, grayscale, cross-sectional images of the esophagus. However, at present, classifying these images is a time consuming and cumbersome effort performed by an expert using a clinical prediction model. This paper explores the feasibility of using computer vision techniques to accurately predict the presence of dysplastic tissue in VLE BE images. Our contribution is threefold. First, a benchmarking is performed for widely applied machine learning techniques and feature extraction methods. Second, three new features based on the clinical detection model are proposed, having superior classification accuracy and speed, compared to earlier work. Third, we evaluate automated parameter tuning by applying simple grid search and feature selection methods. The results are evaluated on a clinically validated dataset of 30 dysplastic and 30 non-dysplastic VLE images. Optimal classification accuracy is obtained by applying a support vector machine and using our modified Haralick features and optimal image cropping, obtaining an area under the receiver operating characteristic of 0.95 compared to the clinical prediction model at 0.81. Optimal execution time is achieved using a proposed mean and median feature, which is extracted at least factor 2.5 faster than alternative features with comparable performance.

A phylogeny and revised classification of Squamata, including 4161 species of lizards and snakes

PubMed Central

2013-01-01

Background The extant squamates (>9400 known species of lizards and snakes) are one of the most diverse and conspicuous radiations of terrestrial vertebrates, but no studies have attempted to reconstruct a phylogeny for the group with large-scale taxon sampling. Such an estimate is invaluable for comparative evolutionary studies, and to address their classification. Here, we present the first large-scale phylogenetic estimate for Squamata. Results The estimated phylogeny contains 4161 species, representing all currently recognized families and subfamilies. The analysis is based on up to 12896 base pairs of sequence data per species (average = 2497 bp) from 12 genes, including seven nuclear loci (BDNF, c-mos, NT3, PDC, R35, RAG-1, and RAG-2), and five mitochondrial genes (12S, 16S, cytochrome b, ND2, and ND4). The tree provides important confirmation for recent estimates of higher-level squamate phylogeny based on molecular data (but with more limited taxon sampling), estimates that are very different from previous morphology-based hypotheses. The tree also includes many relationships that differ from previous molecular estimates and many that differ from traditional taxonomy. Conclusions We present a new large-scale phylogeny of squamate reptiles that should be a valuable resource for future comparative studies. We also present a revised classification of squamates at the family and subfamily level to bring the taxonomy more in line with the new phylogenetic hypothesis. This classification includes new, resurrected, and modified subfamilies within gymnophthalmid and scincid lizards, and boid, colubrid, and lamprophiid snakes. PMID:23627680

A novel evaluation of two related and two independent algorithms for eye movement classification during reading.

PubMed

Friedman, Lee; Rigas, Ioannis; Abdulin, Evgeny; Komogortsev, Oleg V

2018-05-15

Nystrӧm and Holmqvist have published a method for the classification of eye movements during reading (ONH) (Nyström & Holmqvist, 2010). When we applied this algorithm to our data, the results were not satisfactory, so we modified the algorithm (now the MNH) to better classify our data. The changes included: (1) reducing the amount of signal filtering, (2) excluding a new type of noise, (3) removing several adaptive thresholds and replacing them with fixed thresholds, (4) changing the way that the start and end of each saccade was determined, (5) employing a new algorithm for detecting PSOs, and (6) allowing a fixation period to either begin or end with noise. A new method for the evaluation of classification algorithms is presented. It was designed to provide comprehensive feedback to an algorithm developer, in a time-efficient manner, about the types and numbers of classification errors that an algorithm produces. This evaluation was conducted by three expert raters independently, across 20 randomly chosen recordings, each classified by both algorithms. The MNH made many fewer errors in determining when saccades start and end, and it also detected some fixations and saccades that the ONH did not. The MNH fails to detect very small saccades. We also evaluated two additional algorithms: the EyeLink Parser and a more current, machine-learning-based algorithm. The EyeLink Parser tended to find more saccades that ended too early than did the other methods, and we found numerous problems with the output of the machine-learning-based algorithm.

The new ILAE report on terminology and concepts for organization of epileptic seizures: a clinician's critical view and contribution.

PubMed

Panayiotopoulos, Chrysostomos P

2011-12-01

The International League Against Epilepsy (ILAE) standardized classification and terminology for "epileptic seizures" of 1981 and "epilepsies and epileptic syndromes" of 1989 provide a fundamental framework for organizing and differentiating the epilepsies. However, a revision of these classifications is mandated by recent major technologic and scientific advances. Since 1997, the relevant ILAE Commissions have made significant efforts to achieve better and internationally uniform classifications as reflected in their reports of 2001, 2006, and 2010. Their initial aim to construct a "new scientific classification from application of methods used in biology that determines separate species and natural classes" proved elusive and, therefore, the last Commission in their report of 2010 confined their revisions to "new terminology and concepts" instead of "proposing a new classification (in the sense of organization) of epilepsies." It is unfortunate that most of the proposals in this report are modified interpretations and nomenclature of previous ILAE classifications; new terms are not better than the old ones, and recent advances have not been incorporated. Hence, the new ILAE report met with considerable protest from several expert epileptologists. This critical review refers mainly to the epileptic seizures, the classification of which may be an easier and less controversial task in the ILAE revisions. A revised classification should incorporate advanced knowledge of seizure pathophysiology, and clinical, interictal, and ictal manifestations. Such an attempt was made and detailed in the 2006 report of the ILAE Classification Core Group. However, these changes were largely discarded in the new ILAE report of 2010, without justification. This is inexplicable considering that the scientific advances that were available to the two Commissions were the same or had improved between 2006 and 2010. Of major concern is that "No specific classification is recommended for focal seizures which should be described according to their manifestations." Such a proposition defies the essence and the principle of any classification that requires an organization and a common language for communication. Free text descriptions are fine in a manual of differential diagnosis but not as a classification system. Another striking weakness is that even the accepted types of epileptic seizure are listed by name only, without defining them. The result is avoidable confusion. Furthermore, the report fails to consider reflex epileptic seizures. Status epilepticus is the most conspicuous omission despite immense advances of our understanding of it and its relevance on the classification. It appears that the new ILAE report does not fulfill its intent to improve the previous classifications and it may be premature to submit anything similar to this for approval by the ILAE General Assembly. The ILAE Commission could benefit by asking experts in basic and clinical science to provide a concise statement in their field of expertise as, for example, what are focal, myoclonic, or absence seizures, and their subtypes, their manifestations, and their possible pathophysiology. Areas of certainties and uncertainties, agreements and disagreements should be identified and stated clearly, with documentation of the reasons for it. Probably this is the only way forward for a truly scientific, sound, and clinically meaningful organizational system for the epileptic seizures and the epilepsies. Wiley Periodicals, Inc. © 2011 International League Against Epilepsy.

My Treatment Approach to Rheumatoid Arthritis

PubMed Central

Davis, John M.; Matteson, Eric L.

2012-01-01

The past decade has brought important advances in the understanding of rheumatoid arthritis and its management and treatment. New classification criteria for rheumatoid arthritis, better definitions of treatment outcome and remission, and the introduction of biologic response-modifying drugs designed to inhibit the inflammatory process have greatly altered the approach to managing this disease. More aggressive management of rheumatoid arthritis early after diagnosis and throughout the course of the disease has resulted in improvement in patient functioning and quality of life, reduction in comorbid conditions, and enhanced survival. PMID:22766086

Worldwide epidemiology of fibromyalgia.

PubMed

Queiroz, Luiz Paulo

2013-08-01

Studying the epidemiology of fibromyalgia (FM) is very important to understand the impact of this disorder on persons, families and society. The recent modified 2010 classification criteria of the American College of Rheumatology (ACR), without the need of tender points palpation, allows that larger and nationwide surveys may be done, worldwide. This article reviews the prevalence and incidence studies done in the general population, in several countries/continents, the prevalence of FM in special groups/settings, the association of FM with some sociodemographic characteristics of the population, and the comorbidity of FM with others disorders, especially with headaches.

[Complex surgical procedures in orthopedics and trauma surgery. A contribution to the proposal procedure for the DRG system in 2009].

PubMed

Flohé, S; Nabring, J; Luetkes, P; Nast-Kolb, D; Windolf, J

2008-10-01

Since the DRG system was introduced in 2003/2004 the system for remuneration has been continually modified in conjunction with input from specialized medical associations. As part of this development of the payment system, the criteria for classification of a diagnosis-related group were further expanded and new functions were added. This contribution addresses the importance of the complex surgical procedures as criteria for subdivision of the DRG case-based lump sums in orthopedics and trauma surgery.

Sustainability Council of New Zealand Trust v. The Environmental Protection Authority: Gene editing technologies and the law.

PubMed

Kershen, Drew L

2015-01-01

In May 2014, a New Zealand court rendered the first judicial opinion in the world about the legal classification of gene-editing techniques. The court ruled that ZFN-1 and TALEs are techniques of genetic modification and thus within the New Zealand statute and regulations governing genetically modified organisms. This article explains the facts of this legal matter, the reasoning of the court, and provides commentary about the implications of this decision for New Zealand and other jurisdictions around the world.

Software errors and complexity: An empirical investigation

NASA Technical Reports Server (NTRS)

Basili, Victor R.; Perricone, Berry T.

1983-01-01

The distributions and relationships derived from the change data collected during the development of a medium scale satellite software project show that meaningful results can be obtained which allow an insight into software traits and the environment in which it is developed. Modified and new modules were shown to behave similarly. An abstract classification scheme for errors which allows a better understanding of the overall traits of a software project is also shown. Finally, various size and complexity metrics are examined with respect to errors detected within the software yielding some interesting results.

Software errors and complexity: An empirical investigation

NASA Technical Reports Server (NTRS)

Basili, V. R.; Perricone, B. T.

1982-01-01

The distributions and relationships derived from the change data collected during the development of a medium scale satellite software project show that meaningful results can be obtained which allow an insight into software traits and the environment in which it is developed. Modified and new modules were shown to behave similarly. An abstract classification scheme for errors which allows a better understanding of the overall traits of a software project is also shown. Finally, various size and complexity metrics are examined with respect to errors detected within the software yielding some interesting results.

An Investigation of the Hot Corrosion Protectivity Behavior of Platinum Modified Aluminide Coatings on Nickel-Based Superalloys

DTIC Science & Technology

1987-03-01

is unlimited. WCRT LAIISIPIcaiIo IP THIS P431 IEPORT DOCUMENTATION PAGE* is REIPOT SECURilY CLASSIFICATION 1b RISTRtC7IVI MARKINGS la FURITY... grow until it forms a continuous surface layer. At this point, there is a parabolic decrease in the rate of oxidation and the surface stabilizes. If...surface as PtA1 2 and Pt 2 A13. Consequently, the platinum concentration gradient that develops is highest at the surface, but, rapidly diminishes as the

Effect of the Modified Glasgow Coma Scale Score Criteria for Mild Traumatic Brain Injury on Mortality Prediction: Comparing Classic and Modified Glasgow Coma Scale Score Model Scores of 13

PubMed Central

Mena, Jorge Humberto; Sanchez, Alvaro Ignacio; Rubiano, Andres M.; Peitzman, Andrew B.; Sperry, Jason L.; Gutierrez, Maria Isabel; Puyana, Juan Carlos

2011-01-01

Objective The Glasgow Coma Scale (GCS) classifies Traumatic Brain Injuries (TBI) as Mild (14–15); Moderate (9–13) or Severe (3–8). The ATLS modified this classification so that a GCS score of 13 is categorized as mild TBI. We investigated the effect of this modification on mortality prediction, comparing patients with a GCS of 13 classified as moderate TBI (Classic Model) to patients with GCS of 13 classified as mild TBI (Modified Model). Methods We selected adult TBI patients from the Pennsylvania Outcome Study database (PTOS). Logistic regressions adjusting for age, sex, cause, severity, trauma center level, comorbidities, and isolated TBI were performed. A second evaluation included the time trend of mortality. A third evaluation also included hypothermia, hypotension, mechanical ventilation, screening for drugs, and severity of TBI. Discrimination of the models was evaluated using the area under receiver operating characteristic curve (AUC). Calibration was evaluated using the Hoslmer-Lemershow goodness of fit (GOF) test. Results In the first evaluation, the AUCs were 0.922 (95 %CI, 0.917–0.926) and 0.908 (95 %CI, 0.903–0.912) for classic and modified models, respectively. Both models showed poor calibration (p<0.001). In the third evaluation, the AUCs were 0.946 (95 %CI, 0.943 – 0.949) and 0.938 (95 %CI, 0.934 –0.940) for the classic and modified models, respectively, with improvements in calibration (p=0.30 and p=0.02 for the classic and modified models, respectively). Conclusion The lack of overlap between ROC curves of both models reveals a statistically significant difference in their ability to predict mortality. The classic model demonstrated better GOF than the modified model. A GCS of 13 classified as moderate TBI in a multivariate logistic regression model performed better than a GCS of 13 classified as mild. PMID:22071923

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.

Multispectral studies of selected crater- and basin-filling lunar Maria from Galileo Earth-Moon encounter 1

NASA Technical Reports Server (NTRS)

Williams, D. A.; Greeley, R.; Neukum, G.; Wagner, R.

1993-01-01

New visible and near-infrared multispectral data of the Moon were obtained by the Galileo spacecraft in December, 1990. These data were calibrated with Earth-based spectral observations of the nearside to compare compositional information to previously uncharacterized mare basalts filling craters and basins on the western near side and eastern far side. A Galileo-based spectral classification scheme, modified from the Earth-based scheme developed by Pieters, designates the different spectral classifications of mare basalt observed using the 0.41/0.56 micron reflectance ratio (titanium content), 0.56 micron reflectance values (albedo), and 0.76/0.99 micron reflectance ratio (absorption due to Fe(2+) in mafic minerals and glass). In addition, age determinations from crater counts and results of a linear spectral mixing model were used to assess the volcanic histories of specific regions of interest. These interpreted histories were related to models of mare basalt petrogenesis in an attempt to better understand the evolution of lunar volcanism.

Apples to committee consensus: the challenge of gender identity classification.

PubMed

Rettew, David C

2012-01-01

The debate surrounding the inclusion of gender dysphoria/gender variant behavior (GD/GV) as a psychiatric diagnosis exposes many of the fundamental shortcomings and inconsistencies of our current diagnostic classification system. Proposals raised by the authors of this special issue, including basing diagnosis on cause rather than overt behavior, reclassifying GD/GV behavior as a physical rather than mental condition, and basing diagnosis on impairment or distress, offer some solutions but have limitations themselves given the available database. In contrast to most accepted psychiatric conditions where emphasis is placed on ultimately changing internal thoughts, feelings, and behaviors, consensus treatment for most GD/GV individuals, at least from adolescence onward, focuses on modifying the external body and external environment to maximize positive outcomes. This series of articles illustrating the diversity of opinions on when and if gender incongruence should be considered pathological reflects the relative lack of scientific indicators of disease in this area, similar to many other domains of mental functioning.

A statistical approach to combining multisource information in one-class classifiers

DOE PAGES

Simonson, Katherine M.; Derek West, R.; Hansen, Ross L.; ...

2017-06-08

A new method is introduced in this paper for combining information from multiple sources to support one-class classification. The contributing sources may represent measurements taken by different sensors of the same physical entity, repeated measurements by a single sensor, or numerous features computed from a single measured image or signal. The approach utilizes the theory of statistical hypothesis testing, and applies Fisher's technique for combining p-values, modified to handle nonindependent sources. Classifier outputs take the form of fused p-values, which may be used to gauge the consistency of unknown entities with one or more class hypotheses. The approach enables rigorousmore » assessment of classification uncertainties, and allows for traceability of classifier decisions back to the constituent sources, both of which are important for high-consequence decision support. Application of the technique is illustrated in two challenge problems, one for skin segmentation and the other for terrain labeling. Finally, the method is seen to be particularly effective for relatively small training samples.« less

A statistical approach to combining multisource information in one-class classifiers

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

Simonson, Katherine M.; Derek West, R.; Hansen, Ross L.

A new method is introduced in this paper for combining information from multiple sources to support one-class classification. The contributing sources may represent measurements taken by different sensors of the same physical entity, repeated measurements by a single sensor, or numerous features computed from a single measured image or signal. The approach utilizes the theory of statistical hypothesis testing, and applies Fisher's technique for combining p-values, modified to handle nonindependent sources. Classifier outputs take the form of fused p-values, which may be used to gauge the consistency of unknown entities with one or more class hypotheses. The approach enables rigorousmore » assessment of classification uncertainties, and allows for traceability of classifier decisions back to the constituent sources, both of which are important for high-consequence decision support. Application of the technique is illustrated in two challenge problems, one for skin segmentation and the other for terrain labeling. Finally, the method is seen to be particularly effective for relatively small training samples.« less

Integrative Genomic Analysis of Cholangiocarcinoma Identifies Distinct IDH-Mutant Molecular Profiles.

PubMed

Farshidfar, Farshad; Zheng, Siyuan; Gingras, Marie-Claude; Newton, Yulia; Shih, Juliann; Robertson, A Gordon; Hinoue, Toshinori; Hoadley, Katherine A; Gibb, Ewan A; Roszik, Jason; Covington, Kyle R; Wu, Chia-Chin; Shinbrot, Eve; Stransky, Nicolas; Hegde, Apurva; Yang, Ju Dong; Reznik, Ed; Sadeghi, Sara; Pedamallu, Chandra Sekhar; Ojesina, Akinyemi I; Hess, Julian M; Auman, J Todd; Rhie, Suhn K; Bowlby, Reanne; Borad, Mitesh J; Zhu, Andrew X; Stuart, Josh M; Sander, Chris; Akbani, Rehan; Cherniack, Andrew D; Deshpande, Vikram; Mounajjed, Taofic; Foo, Wai Chin; Torbenson, Michael S; Kleiner, David E; Laird, Peter W; Wheeler, David A; McRee, Autumn J; Bathe, Oliver F; Andersen, Jesper B; Bardeesy, Nabeel; Roberts, Lewis R; Kwong, Lawrence N

2017-03-14

Cholangiocarcinoma (CCA) is an aggressive malignancy of the bile ducts, with poor prognosis and limited treatment options. Here, we describe the integrated analysis of somatic mutations, RNA expression, copy number, and DNA methylation by The Cancer Genome Atlas of a set of predominantly intrahepatic CCA cases and propose a molecular classification scheme. We identified an IDH mutant-enriched subtype with distinct molecular features including low expression of chromatin modifiers, elevated expression of mitochondrial genes, and increased mitochondrial DNA copy number. Leveraging the multi-platform data, we observed that ARID1A exhibited DNA hypermethylation and decreased expression in the IDH mutant subtype. More broadly, we found that IDH mutations are associated with an expanded histological spectrum of liver tumors with molecular features that stratify with CCA. Our studies reveal insights into the molecular pathogenesis and heterogeneity of cholangiocarcinoma and provide classification information of potential therapeutic significance. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

A New Classification of Endodontic-Periodontal Lesions

PubMed Central

Al-Fouzan, Khalid S.

2014-01-01

The interrelationship between periodontal and endodontic disease has always aroused confusion, queries, and controversy. Differentiating between a periodontal and an endodontic problem can be difficult. A symptomatic tooth may have pain of periodontal and/or pulpal origin. The nature of that pain is often the first clue in determining the etiology of such a problem. Radiographic and clinical evaluation can help clarify the nature of the problem. In some cases, the influence of pulpal pathology may cause the periodontal involvement and vice versa. The simultaneous existence of pulpal problems and inflammatory periodontal disease can complicate diagnosis and treatment planning. An endo-perio lesion can have a varied pathogenesis which ranges from simple to relatively complex one. The differential diagnosis of endodontic and periodontal diseases can sometimes be difficult, but it is of vital importance to make a correct diagnosis for providing the appropriate treatment. This paper aims to discuss a modified clinical classification to be considered for accurately diagnosing and treating endo-perio lesion. PMID:24829580

A new classification of endodontic-periodontal lesions.

PubMed

Al-Fouzan, Khalid S

2014-01-01

The interrelationship between periodontal and endodontic disease has always aroused confusion, queries, and controversy. Differentiating between a periodontal and an endodontic problem can be difficult. A symptomatic tooth may have pain of periodontal and/or pulpal origin. The nature of that pain is often the first clue in determining the etiology of such a problem. Radiographic and clinical evaluation can help clarify the nature of the problem. In some cases, the influence of pulpal pathology may cause the periodontal involvement and vice versa. The simultaneous existence of pulpal problems and inflammatory periodontal disease can complicate diagnosis and treatment planning. An endo-perio lesion can have a varied pathogenesis which ranges from simple to relatively complex one. The differential diagnosis of endodontic and periodontal diseases can sometimes be difficult, but it is of vital importance to make a correct diagnosis for providing the appropriate treatment. This paper aims to discuss a modified clinical classification to be considered for accurately diagnosing and treating endo-perio lesion.

Exhaustive Classification of the Invariant Solutions for a Specific Nonlinear Model Describing Near Planar and Marginally Long-Wave Unstable Interfaces for Phase Transition

NASA Astrophysics Data System (ADS)

Ahangari, Fatemeh

2018-05-01

Problems of thermodynamic phase transition originate inherently in solidification, combustion and various other significant fields. If the transition region among two locally stable phases is adequately narrow, the dynamics can be modeled by an interface motion. This paper is devoted to exhaustive analysis of the invariant solutions for a modified Kuramoto-Sivashinsky equation in two spatial and one temporal dimensions is presented. This nonlinear partial differential equation asymptotically characterizes near planar interfaces, which are marginally long-wave unstable. For this purpose, by applying the classical symmetry method for this model the classical symmetry operators are attained. Moreover, the structure of the Lie algebra of symmetries is discussed and the optimal system of subalgebras, which yields the preliminary classification of group invariant solutions is constructed. Mainly, the Lie invariants corresponding to the infinitesimal symmetry generators as well as associated similarity reduced equations are also pointed out. Furthermore, the nonclassical symmetries of this nonlinear PDE are also comprehensively investigated.

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

NASA Astrophysics Data System (ADS)

Wang, Cong; Gai, Guosheng; Yang, Yufen

2018-03-01

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

A Hybrid Swarm Intelligence Algorithm for Intrusion Detection Using Significant Features.

PubMed

Amudha, P; Karthik, S; Sivakumari, S

2015-01-01

Intrusion detection has become a main part of network security due to the huge number of attacks which affects the computers. This is due to the extensive growth of internet connectivity and accessibility to information systems worldwide. To deal with this problem, in this paper a hybrid algorithm is proposed to integrate Modified Artificial Bee Colony (MABC) with Enhanced Particle Swarm Optimization (EPSO) to predict the intrusion detection problem. The algorithms are combined together to find out better optimization results and the classification accuracies are obtained by 10-fold cross-validation method. The purpose of this paper is to select the most relevant features that can represent the pattern of the network traffic and test its effect on the success of the proposed hybrid classification algorithm. To investigate the performance of the proposed method, intrusion detection KDDCup'99 benchmark dataset from the UCI Machine Learning repository is used. The performance of the proposed method is compared with the other machine learning algorithms and found to be significantly different.

A Hybrid Swarm Intelligence Algorithm for Intrusion Detection Using Significant Features

PubMed Central

Amudha, P.; Karthik, S.; Sivakumari, S.

2015-01-01

Intrusion detection has become a main part of network security due to the huge number of attacks which affects the computers. This is due to the extensive growth of internet connectivity and accessibility to information systems worldwide. To deal with this problem, in this paper a hybrid algorithm is proposed to integrate Modified Artificial Bee Colony (MABC) with Enhanced Particle Swarm Optimization (EPSO) to predict the intrusion detection problem. The algorithms are combined together to find out better optimization results and the classification accuracies are obtained by 10-fold cross-validation method. The purpose of this paper is to select the most relevant features that can represent the pattern of the network traffic and test its effect on the success of the proposed hybrid classification algorithm. To investigate the performance of the proposed method, intrusion detection KDDCup'99 benchmark dataset from the UCI Machine Learning repository is used. The performance of the proposed method is compared with the other machine learning algorithms and found to be significantly different. PMID:26221625

An engineering rock classification to evaluate seismic rock-fall susceptibility and its application to the Wasatch Front

USGS Publications Warehouse

Harp, E.L.; Noble, M.A.

1993-01-01

Investigations of earthquakes world wide show that rock falls are the most abundant type of landslide that is triggered by earthquakes. An engineering classification originally used in tunnel design, known as the rock mass quality designation (Q), was modified for use in rating the susceptibility of rock slopes to seismically-induced failure. Analysis of rock-fall concentrations and Q-values for the 1980 earthquake sequence near Mammoth Lakes, California, defines a well-constrained upper bound that shows the number of rock falls per site decreases rapidly with increasing Q. Because of the similarities of lithology and slope between the Eastern Sierra Nevada Range near Mammoth Lakes and the Wasatch Front near Salt Lake City, Utah, the probabilities derived from analysis of the Mammoth Lakes region were used to predict rock-fall probabilities for rock slopes near Salt Lake City in response to a magnitude 6.0 earthquake. These predicted probabilities were then used to generalize zones of rock-fall susceptibility. -from Authors

Incremental concept learning with few training examples and hierarchical classification

NASA Astrophysics Data System (ADS)

Bouma, Henri; Eendebak, Pieter T.; Schutte, Klamer; Azzopardi, George; Burghouts, Gertjan J.

2015-10-01

Object recognition and localization are important to automatically interpret video and allow better querying on its content. We propose a method for object localization that learns incrementally and addresses four key aspects. Firstly, we show that for certain applications, recognition is feasible with only a few training samples. Secondly, we show that novel objects can be added incrementally without retraining existing objects, which is important for fast interaction. Thirdly, we show that an unbalanced number of positive training samples leads to biased classifier scores that can be corrected by modifying weights. Fourthly, we show that the detector performance can deteriorate due to hard-negative mining for similar or closely related classes (e.g., for Barbie and dress, because the doll is wearing a dress). This can be solved by our hierarchical classification. We introduce a new dataset, which we call TOSO, and use it to demonstrate the effectiveness of the proposed method for the localization and recognition of multiple objects in images.

ESHRE/ESGE female genital tract anomalies classification system-the potential impact of discarding arcuate uterus on clinical practice.

PubMed

Knez, J; Saridogan, E; Van Den Bosch, T; Mavrelos, D; Ambler, G; Jurkovic, D

2018-04-01

What would be a potential impact of implementing the new ESHRE/European Society of Gynaecological Endoscopy (ESGE) female genital anomalies classification system on the management of women with previous diagnosis of arcuate uteri based on the modified American Society for Reproductive Medicine (ASRM) criteria? A significant number of women with previous diagnosis of arcuate uteri are reclassified as having partial septate uteri according to the new ESHRE/ESGE classification system which may increase the number of remedial surgical procedures. The ESHRE/ESGE classification system has defined measurement techniques, reference points and specific cut-offs to facilitate the differentiation between normal and septate uteri. These criteria have been arbitrarily defined and they rely on the measurement of uterine wall thickness and depth of distortion of uterine fundus. This was a retrospective cohort study. We searched our ultrasound clinic database from January 2011 to December 2014 to identify all women diagnosed with arcuate uterus on three-dimensional ultrasound according to the modified ASRM criteria. For each woman, the ultrasound images were stored in our clinical database and they were re-examined according to ESHRE/ESGE specifications. The presence and location of all acquired uterine anomalies, such as fibroids or adenomyosis was noted. We applied the two diagnostic approaches as specified by the ESHRE/ESGE classification: the main option (MO) and the alternative option (AO). We used the Kappa statistic to quantify the agreement between the two approaches. We also compared the number of previous miscarriages in women with normal and partial septate uteri according to the ESHRE/ESGE classification. Non-parametric Mann-Whitney and Kruskal-Wallis tests were used for the analyses and receiver-operating characteristic curves were constructed to assess the predictive values of the calculated uterine distortion indices for the detection of women at risk of suffering multiple pregnancy losses. We included 270 women diagnosed with arcuate uterus in the study. In all, 77 women (28.5%, 95% confidence interval (CI) 23.1-33.9) had evidence of fibroids or adenomyosis. These abnormalities precluded the application of either proposed ESHRE/ESGE techniques to assess uterine morphology in 25 women (9.3%, 95% CI 5.8-12.7). When using the MO, 138/237 (58.2%, 95% CI 51.9-64.3) women were diagnosed with partial septate uterus compared to 61/230 (26.5%, 95% CI 21.2-32.6) women when using the AO. In 222 women in whom we were able to apply both MO and AO, there was agreement in the diagnosis of septate uterus between the two techniques in 146/222 cases (65.8%, 95% CI 59.3-71.7; Kappa 0.42, 95%CI 0.35-0.5). There was no statistical difference in the proportion of women with history of previous multiple miscarriages between those diagnosed with normal or partial septate uteri using either MO (6.2%, 95% CI 2.9-12.9 vs. 9.5%, 95% CI 5.6-15.6; P = 0.47) or AO (7.2%, 95% CI 4.2-12.1 vs. 11.7%, 95% CI 5.8-22.2; P = 0.29). This study was retrospective in nature and the definition of arcuate uterus used in the study is not universally accepted. The reproductive history data were collected retrospectively and therefore may be prone to bias. There are methodological weaknesses in the new ESHRE/ESGE classification system which would need to be addressed in future revisions. There was no significant difference in the past reproductive outcomes between women diagnosed with normal and anomalous uteri and the clinicians should exercise caution when offering surgical correction to women diagnosed with partial septate uteri using the new ESHRE/ESGE classification. No study funding was received and no competing interests are present. N/A.

Classification scheme for sedimentary and igneous rocks in Gale crater, Mars

NASA Astrophysics Data System (ADS)

Mangold, N.; Schmidt, M. E.; Fisk, M. R.; Forni, O.; McLennan, S. M.; Ming, D. W.; Sautter, V.; Sumner, D.; Williams, A. J.; Clegg, S. M.; Cousin, A.; Gasnault, O.; Gellert, R.; Grotzinger, J. P.; Wiens, R. C.

2017-03-01

Rocks analyzed by the Curiosity rover in Gale crater include a variety of clastic sedimentary rocks and igneous float rocks transported by fluvial and impact processes. To facilitate the discussion of the range of lithologies, we present in this article a petrological classification framework adapting terrestrial classification schemes to Mars compositions (such as Fe abundances typically higher than for comparable lithologies on Earth), to specific Curiosity observations (such as common alkali-rich rocks), and to the capabilities of the rover instruments. Mineralogy was acquired only locally for a few drilled rocks, and so it does not suffice as a systematic classification tool, in contrast to classical terrestrial rock classification. The core of this classification involves (1) the characterization of rock texture as sedimentary, igneous or undefined according to grain/crystal sizes and shapes using imaging from the ChemCam Remote Micro-Imager (RMI), Mars Hand Lens Imager (MAHLI) and Mastcam instruments, and (2) the assignment of geochemical modifiers based on the abundances of Fe, Si, alkali, and S determined by the Alpha Particle X-ray Spectrometer (APXS) and ChemCam instruments. The aims are to help understand Gale crater geology by highlighting the various categories of rocks analyzed by the rover. Several implications are proposed from the cross-comparisons of rocks of various texture and composition, for instance between in place outcrops and float rocks. All outcrops analyzed by the rover are sedimentary; no igneous outcrops have been observed. However, some igneous rocks are clasts in conglomerates, suggesting that part of them are derived from the crater rim. The compositions of in-place sedimentary rocks contrast significantly with the compositions of igneous float rocks. While some of the differences between sedimentary rocks and igneous floats may be related to physical sorting and diagenesis of the sediments, some of the sedimentary rocks (e.g., potassic rocks) cannot be paired with any igneous rocks analyzed so far. In contrast, many float rocks, which cannot be classified from their poorly defined texture, plot on chemistry diagrams close to float rocks defined as igneous from their textures, potentially constraining their nature.

Classification scheme for sedimentary and igneous rocks in Gale crater, Mars

DOE PAGES

Mangold, Nicolas; Schmidt, Mariek E.; Fisk, Martin R.; ...

2016-11-05

Rocks analyzed by the Curiosity rover in Gale crater include a variety of clastic sedimentary rocks and igneous float rocks transported by fluvial and impact processes. Here, to facilitate the discussion of the range of lithologies, we present in this article a petrological classification framework adapting terrestrial classification schemes to Mars compositions (such as Fe abundances typically higher than for comparable lithologies on Earth), to specific Curiosity observations (such as common alkali-rich rocks), and to the capabilities of the rover instruments. Mineralogy was acquired only locally for a few drilled rocks, and so it does not suffice as a systematicmore » classification tool, in contrast to classical terrestrial rock classification. The core of this classification involves (1) the characterization of rock texture as sedimentary, igneous or undefined according to grain/crystal sizes and shapes using imaging from the ChemCam Remote Micro-Imager (RMI), Mars Hand Lens Imager (MAHLI) and Mastcam instruments, and (2) the assignment of geochemical modifiers based on the abundances of Fe, Si, alkali, and S determined by the Alpha Particle X-ray Spectrometer (APXS) and ChemCam instruments. The aims are to help understand Gale crater geology by highlighting the various categories of rocks analyzed by the rover. Several implications are proposed from the cross-comparisons of rocks of various texture and composition, for instance between in place outcrops and float rocks. All outcrops analyzed by the rover are sedimentary; no igneous outcrops have been observed. However, some igneous rocks are clasts in conglomerates, suggesting that part of them are derived from the crater rim. The compositions of in-place sedimentary rocks contrast significantly with the compositions of igneous float rocks. While some of the differences between sedimentary rocks and igneous floats may be related to physical sorting and diagenesis of the sediments, some of the sedimentary rocks (e.g., potassic rocks) cannot be paired with any igneous rocks analyzed so far. Finally, in contrast, many float rocks, which cannot be classified from their poorly defined texture, plot on chemistry diagrams close to float rocks defined as igneous from their textures, potentially constraining their nature.« less

Classification scheme for sedimentary and igneous rocks in Gale crater, Mars

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

Mangold, Nicolas; Schmidt, Mariek E.; Fisk, Martin R.

Rocks analyzed by the Curiosity rover in Gale crater include a variety of clastic sedimentary rocks and igneous float rocks transported by fluvial and impact processes. Here, to facilitate the discussion of the range of lithologies, we present in this article a petrological classification framework adapting terrestrial classification schemes to Mars compositions (such as Fe abundances typically higher than for comparable lithologies on Earth), to specific Curiosity observations (such as common alkali-rich rocks), and to the capabilities of the rover instruments. Mineralogy was acquired only locally for a few drilled rocks, and so it does not suffice as a systematicmore » classification tool, in contrast to classical terrestrial rock classification. The core of this classification involves (1) the characterization of rock texture as sedimentary, igneous or undefined according to grain/crystal sizes and shapes using imaging from the ChemCam Remote Micro-Imager (RMI), Mars Hand Lens Imager (MAHLI) and Mastcam instruments, and (2) the assignment of geochemical modifiers based on the abundances of Fe, Si, alkali, and S determined by the Alpha Particle X-ray Spectrometer (APXS) and ChemCam instruments. The aims are to help understand Gale crater geology by highlighting the various categories of rocks analyzed by the rover. Several implications are proposed from the cross-comparisons of rocks of various texture and composition, for instance between in place outcrops and float rocks. All outcrops analyzed by the rover are sedimentary; no igneous outcrops have been observed. However, some igneous rocks are clasts in conglomerates, suggesting that part of them are derived from the crater rim. The compositions of in-place sedimentary rocks contrast significantly with the compositions of igneous float rocks. While some of the differences between sedimentary rocks and igneous floats may be related to physical sorting and diagenesis of the sediments, some of the sedimentary rocks (e.g., potassic rocks) cannot be paired with any igneous rocks analyzed so far. Finally, in contrast, many float rocks, which cannot be classified from their poorly defined texture, plot on chemistry diagrams close to float rocks defined as igneous from their textures, potentially constraining their nature.« less

Feasibility and validity of using WHO adolescent job aid algorithms by health workers for reproductive morbidities among adolescent girls in rural North India.

PubMed

Archana, Siddaiah; Nongkrynh, B; Anand, K; Pandav, C S

2015-09-21

High prevalence of reproductive morbidities is seen among adolescents in India. Health workers play an important role in providing health services in the community, including the adolescent reproductive health services. A study was done to assess the feasibility of training female health workers (FHWs) in the classification and management of selected adolescent girls' reproductive health problems according to modified WHO algorithms. The study was conducted between Jan-Sept 2011 in Northern India. Thirteen FHWs were trained regarding adolescent girls' reproductive health as per WHO Adolescent Job-Aid booklet. A pre and post-test assessment of the knowledge of the FHWs was carried out. All FHWs were given five modified WHO algorithms to classify and manage common reproductive morbidities among adolescent girls. All the FHWs applied the algorithms on at least ten adolescent girls at their respective sub-centres. Simultaneously, a medical doctor independently applied the same algorithms in all girls. Classification of the condition was followed by relevant management and advice provided in the algorithm. Focus group discussion with the FHWs was carried out to receive their feedback. After training the median score of the FHWs increased from 19.2 to 25.2 (p - 0.0071). Out of 144 girls examined by the FHWs 108 were classified as true positives and 30 as true negatives and agreement as measured by kappa was 0.7 (0.5-0.9). Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were 94.3% (88.2-97.4), 78.9% (63.6-88.9), 92.5% (86.0-96.2), and 83.3% (68.1-92.1) respectively. A consistent and significant difference between pre and post training knowledge scores of the FHWs were observed and hence it was possible to use the modified Job Aid algorithms with ease. Limitation of this study was the munber of FHWs trained was small. Issues such as time management during routine work, timing of training, overhead cost of training etc were not taken into account. Training was successful in increasing the knowledge of the FHWs about adolescent girls' reproductive health issues. The FHWs were able to satisfactorily classify the common adolescent girls' problems using the modified WHO algorithms.

We are all angels: acting, reclaiming and moving beyond survivorship.

PubMed

Anderson, Ariane B

2014-01-01

This article aspires to an embodiment of dynamic living versus mere survival. The term cancer survivor, including a survivor who is in remission, has been legitimated (Berger and Luckmann, The social construction of reality, p. 94 1967) by language which creates knowledge of what a cancer survivor is and does. Because we act under descriptions (Hacking, The social construction of what?, p. 103 1999), those of us who have passed through illnesses such as cancer not only have been given the name and the idea of survivor, we have assumed and conform to some or most of the characteristics assigned to it; examples of some of those characteristics are discussed throughout this project. Whether or not we choose to enact all that falls under the grammar of the classification of survivor, we still live with, create, and experience ourselves and others as legitimated by such a classification. The term survivor operates through a number of institutions (medical, capitalism, and media) resulting in individuals' awareness of such classifications about themselves and others. Many, if not most, who are aware of being classified as survivors may wish to modify or resist the constraining aspects of those classifications and their descriptions. Through layered accounts of interviews and prose, I interact with this term as one who is both caught in and wants to go against the stream of classification and description. I want to transcend what I know, yet I am aware that whatever story I make and tell is a part of the whole-my story is part of two other survivor's stories which I include in the following telling of my own. All of our stories matter. Still, I want to look beyond what is in front of me, move beyond it, dream. I do so with a desire to tell my story as part of other survivors' stories.

Randomized Prediction Games for Adversarial Machine Learning.

PubMed

Rota Bulo, Samuel; Biggio, Battista; Pillai, Ignazio; Pelillo, Marcello; Roli, Fabio

In spam and malware detection, attackers exploit randomization to obfuscate malicious data and increase their chances of evading detection at test time, e.g., malware code is typically obfuscated using random strings or byte sequences to hide known exploits. Interestingly, randomization has also been proposed to improve security of learning algorithms against evasion attacks, as it results in hiding information about the classifier to the attacker. Recent work has proposed game-theoretical formulations to learn secure classifiers, by simulating different evasion attacks and modifying the classification function accordingly. However, both the classification function and the simulated data manipulations have been modeled in a deterministic manner, without accounting for any form of randomization. In this paper, we overcome this limitation by proposing a randomized prediction game, namely, a noncooperative game-theoretic formulation in which the classifier and the attacker make randomized strategy selections according to some probability distribution defined over the respective strategy set. We show that our approach allows one to improve the tradeoff between attack detection and false alarms with respect to the state-of-the-art secure classifiers, even against attacks that are different from those hypothesized during design, on application examples including handwritten digit recognition, spam, and malware detection.In spam and malware detection, attackers exploit randomization to obfuscate malicious data and increase their chances of evading detection at test time, e.g., malware code is typically obfuscated using random strings or byte sequences to hide known exploits. Interestingly, randomization has also been proposed to improve security of learning algorithms against evasion attacks, as it results in hiding information about the classifier to the attacker. Recent work has proposed game-theoretical formulations to learn secure classifiers, by simulating different evasion attacks and modifying the classification function accordingly. However, both the classification function and the simulated data manipulations have been modeled in a deterministic manner, without accounting for any form of randomization. In this paper, we overcome this limitation by proposing a randomized prediction game, namely, a noncooperative game-theoretic formulation in which the classifier and the attacker make randomized strategy selections according to some probability distribution defined over the respective strategy set. We show that our approach allows one to improve the tradeoff between attack detection and false alarms with respect to the state-of-the-art secure classifiers, even against attacks that are different from those hypothesized during design, on application examples including handwritten digit recognition, spam, and malware detection.

A soft computing based approach using modified selection strategy for feature reduction of medical systems.

PubMed

Zuhtuogullari, Kursat; Allahverdi, Novruz; Arikan, Nihat

2013-01-01

The systems consisting high input spaces require high processing times and memory usage. Most of the attribute selection algorithms have the problems of input dimensions limits and information storage problems. These problems are eliminated by means of developed feature reduction software using new modified selection mechanism with middle region solution candidates adding. The hybrid system software is constructed for reducing the input attributes of the systems with large number of input variables. The designed software also supports the roulette wheel selection mechanism. Linear order crossover is used as the recombination operator. In the genetic algorithm based soft computing methods, locking to the local solutions is also a problem which is eliminated by using developed software. Faster and effective results are obtained in the test procedures. Twelve input variables of the urological system have been reduced to the reducts (reduced input attributes) with seven, six, and five elements. It can be seen from the obtained results that the developed software with modified selection has the advantages in the fields of memory allocation, execution time, classification accuracy, sensitivity, and specificity values when compared with the other reduction algorithms by using the urological test data.

[Clinical and radiographic evaluation of a new percutaneous technique for moderate to severe hallux valgus deformity].

PubMed

Vélez-de Lachica, J C; Valdez-Jiménez, L A; Inzunza-Sánchez, J M

2017-01-01

Hallux valgus is considered the most common musculoskeletal deformity, with a prevalence of 88%. There are more than 130 surgical techniques for its treatment; currently, percutaneous ones are popular; however, they do not take into account the metatarsal-phalangeal correction angle. The aim of this study is to propose a modified technique for the correction of the percutaneous metatarsal-phalangeal and inter-metatarsal angles and to evaluate its clinical and radiological results. An experimental, prospective and longitudinal study in 10 patients with moderate to severe hallux valgus according to the classification of Coughlin and Mann were collected; the results were evaluated with the AOFAS scale at 15, 30, 60 and 90 days. The McBride technique and the technique of percutaneous anchor with the proposed amendment were performed. The AOFAS scale was applied as described, finding a progressive increase of the rating; the average correction of the inter-metatarsal angle was 8.8 degrees and of the metatarsal-phalangeal, 9.12. The modified technique of percutaneous anchor showed clear clinical and radiographic improvements in the short term. Our modified technique is proposed for future projects, including a large sample with long-term follow-up.

A Soft Computing Based Approach Using Modified Selection Strategy for Feature Reduction of Medical Systems

PubMed Central

Zuhtuogullari, Kursat; Allahverdi, Novruz; Arikan, Nihat

2013-01-01

The systems consisting high input spaces require high processing times and memory usage. Most of the attribute selection algorithms have the problems of input dimensions limits and information storage problems. These problems are eliminated by means of developed feature reduction software using new modified selection mechanism with middle region solution candidates adding. The hybrid system software is constructed for reducing the input attributes of the systems with large number of input variables. The designed software also supports the roulette wheel selection mechanism. Linear order crossover is used as the recombination operator. In the genetic algorithm based soft computing methods, locking to the local solutions is also a problem which is eliminated by using developed software. Faster and effective results are obtained in the test procedures. Twelve input variables of the urological system have been reduced to the reducts (reduced input attributes) with seven, six, and five elements. It can be seen from the obtained results that the developed software with modified selection has the advantages in the fields of memory allocation, execution time, classification accuracy, sensitivity, and specificity values when compared with the other reduction algorithms by using the urological test data. PMID:23573172

Monitoring the Depth of Anesthesia Using a New Adaptive Neurofuzzy System.

PubMed

Shalbaf, Ahmad; Saffar, Mohsen; Sleigh, Jamie W; Shalbaf, Reza

2018-05-01

Accurate and noninvasive monitoring of the depth of anesthesia (DoA) is highly desirable. Since the anesthetic drugs act mainly on the central nervous system, the analysis of brain activity using electroencephalogram (EEG) is very useful. This paper proposes a novel automated method for assessing the DoA using EEG. First, 11 features including spectral, fractal, and entropy are extracted from EEG signal and then, by applying an algorithm according to exhaustive search of all subsets of features, a combination of the best features (Beta-index, sample entropy, shannon permutation entropy, and detrended fluctuation analysis) is selected. Accordingly, we feed these extracted features to a new neurofuzzy classification algorithm, adaptive neurofuzzy inference system with linguistic hedges (ANFIS-LH). This structure can successfully model systems with nonlinear relationships between input and output, and also classify overlapped classes accurately. ANFIS-LH, which is based on modified classical fuzzy rules, reduces the effects of the insignificant features in input space, which causes overlapping and modifies the output layer structure. The presented method classifies EEG data into awake, light, general, and deep states during anesthesia with sevoflurane in 17 patients. Its accuracy is 92% compared to a commercial monitoring system (response entropy index) successfully. Moreover, this method reaches the classification accuracy of 93% to categorize EEG signal to awake and general anesthesia states by another database of propofol and volatile anesthesia in 50 patients. To sum up, this method is potentially applicable to a new real-time monitoring system to help the anesthesiologist with continuous assessment of DoA quickly and accurately.

Prognostic significance of KIT exon 11 deletion mutation in intermediate-risk gastrointestinal stromal tumor.

PubMed

Quek, Richard; Farid, Mohamad; Kanjanapan, Yada; Lim, Cindy; Tan, Iain Beehuat; Kesavan, Sittampalam; Lim, Tony Kiat Hon; Oon, Lynette Lin-Ean; Goh, Brian Kp; Chan, Weng Hoong; Teo, Melissa; Chung, Alexander Yf; Ong, Hock Soo; Wong, Wai Keong; Tan, Patrick; Yip, Desmond

2017-06-01

Benefit of adjuvant imatinib therapy following curative resection in patients with intermediate-risk gastrointestinal stromal tumor (GIST) is unclear. GIST-specific exon mutations, in particular exon 11 deletions, have been shown to be prognostic. We hypothesize that specific KIT mutations may improve risk stratification in patients with intermediate-risk GIST, identifying a subgroup of patients who may benefit from adjuvant therapy. In total, 142 GIST patients with complete clinicopathologic and mutational data from two sites were included. Risk classification was based on the modified National Institute of Health (NIH) criteria. In this cohort, 74% (n = 105) of patients harbored a KIT mutation; 61% (n = 86) were found in exon 11 of which nearly 70% were KIT exon 11 deletions (n = 60). A total of 18% (n = 25) of cases were classified as having intermediate-risk disease. Univariate analysis confirmed tumor size, mitotic index, nongastric origin, presence of tumor rupture and modified NIH criteria were adversely prognostic for relapse-free survival (RFS). Among KIT/PDGFRA mutants, KIT exon 11 deletions had a significantly worse prognosis (hazard ratio 2.31; 95% confidence interval, 1.30-4.10; P = 0.003). Multivariate analysis confirmed KIT exon 11 deletion (P = 0.003) and clinical risk classification (P < 0.001) as independent adverse prognostic factors for RFS. Intermediate-risk patients harboring KIT exon 11 deletions had RFS outcomes similar to high-risk patients. The presence of KIT exon 11 deletion mutation in patients with intermediate-risk GIST is associated with an inferior clinical outcome with RFS similar to high-risk patients. © 2016 John Wiley & Sons Australia, Ltd.

Antidepressant Use After Aneurysmal Subarachnoid Hemorrhage: A Population-Based Case-Control Study.

PubMed

Huttunen, Jukka; Lindgren, Antti; Kurki, Mitja I; Huttunen, Terhi; Frösen, Juhana; von Und Zu Fraunberg, Mikael; Koivisto, Timo; Kälviäinen, Reetta; Räikkönen, Katri; Viinamäki, Heimo; Jääskeläinen, Juha E; Immonen, Arto

2016-09-01

To elucidate the predictors of antidepressant use after subarachnoid hemorrhage from saccular intracranial aneurysm (sIA-SAH) in a population-based cohort with matched controls. The Kuopio sIA database includes all unruptured and ruptured sIA cases admitted to the Kuopio University Hospital from its defined catchment population in Eastern Finland, with 3 matched controls for each patient. The use of all prescribed medicines has been fused from the Finnish national registry of prescribed medicines. In the present study, 2 or more purchases of antidepressant medication indicated antidepressant use. The risk factors of the antidepressant use were analyzed in 940 patients alive 12 months after sIA-SAH, and the classification tree analysis was used to create a predicting model for antidepressant use after sIA-SAH. The 940 12-month survivors of sIA-SAH had significantly more antidepressant use (odds ratio, 2.6; 95% confidence interval, 2.2-3.1) than their 2676 matched controls (29% versus 14%). Classification tree analysis, based on independent risk factors, was used for the best prediction model of antidepressant use after sIA-SAH. Modified Rankin Scale until 12 months was the most potent predictor, followed by condition (Hunt and Hess Scale) and age on admission for sIA-SAH. The sIA-SAH survivors use significantly more often antidepressants, indicative of depression, than their matched population controls. Even with a seemingly good recovery (modified Rankin Scale score, 0) at 12 months after sIA-SAH, there is a significant risk of depression requiring antidepressant medication. © 2016 American Heart Association, Inc.

Symmetry enriched U(1) quantum spin liquids

NASA Astrophysics Data System (ADS)

Zou, Liujun; Wang, Chong; Senthil, T.

2018-05-01

We classify and characterize three-dimensional U (1 ) quantum spin liquids [deconfined U (1 ) gauge theories] with global symmetries. These spin liquids have an emergent gapless photon and emergent electric/magnetic excitations (which we assume are gapped). We first discuss in great detail the case with time-reversal and SO(3 ) spin rotational symmetries. We find there are 15 distinct such quantum spin liquids based on the properties of bulk excitations. We show how to interpret them as gauged symmetry-protected topological states (SPTs). Some of these states possess fractional response to an external SO (3 ) gauge field, due to which we dub them "fractional topological paramagnets." We identify 11 other anomalous states that can be grouped into three anomaly classes. The classification is further refined by weakly coupling these quantum spin liquids to bosonic symmetry protected topological (SPT) phases with the same symmetry. This refinement does not modify the bulk excitation structure but modifies universal surface properties. Taking this refinement into account, we find there are 168 distinct such U (1 ) quantum spin liquids. After this warm-up, we provide a general framework to classify symmetry enriched U (1 ) quantum spin liquids for a large class of symmetries. As a more complex example, we discuss U (1 ) quantum spin liquids with time-reversal and Z2 symmetries in detail. Based on the properties of the bulk excitations, we find there are 38 distinct such spin liquids that are anomaly-free. There are also 37 anomalous U (1 ) quantum spin liquids with this symmetry. Finally, we briefly discuss the classification of U (1 ) quantum spin liquids enriched by some other symmetries.

Identification of aspects of functioning, disability and health relevant to patients experiencing vertigo: a qualitative study using the international classification of functioning, disability and health

PubMed Central

2012-01-01

Purpose Aims of this study were to identify aspects of functioning and health relevant to patients with vertigo expressed by ICF categories and to explore the potential of the ICF to describe the patient perspective in vertigo. Methods We conducted a series of qualitative semi-structured face-to-face interviews using a descriptive approach. Data was analyzed using the meaning condensation procedure and then linked to categories of the International Classification of Functioning, Disability and Health (ICF). Results From May to July 2010 12 interviews were carried out until saturation was reached. Four hundred and seventy-one single concepts were extracted which were linked to 142 different ICF categories. 40 of those belonged to the component body functions, 62 to the component activity and participation, and 40 to the component environmental factors. Besides the most prominent aspect “dizziness” most participants reported problems within “Emotional functions (b152), problems related to mobility and carrying out the daily routine. Almost all participants reported “Immediate family (e310)” as a relevant modifying environmental factor. Conclusions From the patients’ perspective, vertigo has impact on multifaceted aspects of functioning and disability, mainly body functions and activities and participation. Modifying contextual factors have to be taken into account to cover the complex interaction between the health condition of vertigo on the individuals’ daily life. The results of this study will contribute to developing standards for the measurement of functioning, disability and health relevant for patients suffering from vertigo. PMID:22738067

Gesteme-free context-aware adaptation of robot behavior in human-robot cooperation.

PubMed

Nessi, Federico; Beretta, Elisa; Gatti, Cecilia; Ferrigno, Giancarlo; De Momi, Elena

2016-11-01

Cooperative robotics is receiving greater acceptance because the typical advantages provided by manipulators are combined with an intuitive usage. In particular, hands-on robotics may benefit from the adaptation of the assistant behavior with respect to the activity currently performed by the user. A fast and reliable classification of human activities is required, as well as strategies to smoothly modify the control of the manipulator. In this scenario, gesteme-based motion classification is inadequate because it needs the observation of a wide signal percentage and the definition of a rich vocabulary. In this work, a system able to recognize the user's current activity without a vocabulary of gestemes, and to accordingly adapt the manipulator's dynamic behavior is presented. An underlying stochastic model fits variations in the user's guidance forces and the resulting trajectories of the manipulator's end-effector with a set of Gaussian distribution. The high-level switching between these distributions is captured with hidden Markov models. The dynamic of the KUKA light-weight robot, a torque-controlled manipulator, is modified with respect to the classified activity using sigmoidal-shaped functions. The presented system is validated over a pool of 12 näive users in a scenario that addresses surgical targeting tasks on soft tissue. The robot's assistance is adapted in order to obtain a stiff behavior during activities that require critical accuracy constraint, and higher compliance during wide movements. Both the ability to provide the correct classification at each moment (sample accuracy) and the capability of correctly identify the correct sequence of activity (sequence accuracy) were evaluated. The proposed classifier is fast and accurate in all the experiments conducted (80% sample accuracy after the observation of ∼450ms of signal). Moreover, the ability of recognize the correct sequence of activities, without unwanted transitions is guaranteed (sequence accuracy ∼90% when computed far away from user desired transitions). Finally, the proposed activity-based adaptation of the robot's dynamic does not lead to a not smooth behavior (high smoothness, i.e. normalized jerk score <0.01). The provided system is able to dynamic assist the operator during cooperation in the presented scenario. Copyright © 2016 Elsevier B.V. All rights reserved.

Mallampati test as a predictor of laryngoscopic view.

PubMed

Adamus, Milan; Fritscherova, Sarka; Hrabalek, Lumir; Gabrhelik, Tomas; Zapletalova, Jana; Janout, Vladimir

2010-12-01

To determine the accuracy of the modified Mallampati test for predicting difficult tracheal intubation. A cross-sectional, clinical, observational, non-blinded study. A quality analysis of anesthetic care. Operating theatres and department of anesthesiology in a university hospital. Following the local ethics committee approval and patients' informed consent to anesthesia, all adult patients (> 18 yrs) presenting for any type of non-emergency surgical procedures under general anesthesia requiring endotracheal intubation were enrolled. Prior to anesthesia, Samsoon and Young's modification of the Mallampati test (modified Mallampati test) was performed. Following induction, the anesthesiologist described the laryngoscopic view using the Cormack-Lehane scale. Classes 3 or 4 of the modified Mallampati test were considered a predictor of difficult intubation. Grades 3 or 4 of the Cormack-Lehane classification of the laryngoscopic view were defined as impaired glottic exposure. The sensitivity, specificity, positive and negative predictive value, relative risk, likelihood ratio and accuracy of the modified Mallampati test were calculated on 2x2 contingency tables. Of the total 1,518 patients enrolled, 48 had difficult intubation (3.2%). We failed to detect as many as 35.4% patients in whom glottis exposure during direct laryngoscopy was inadequate (sensitivity 0.646). Compared to the original article by Mallampati, we found lower specificity (0.824 vs. 0.995), lower positive predictive value (0.107 vs. 0.933), higher negative predictive value (0.986 vs. 0.928), lower likelihood ratio (3.68 vs. 91.0) and accuracy (0.819 vs. 0.929). When used as a single examination, the modified Mallampati test is of limited value in predicting difficult intubation.

A new EMI system for detection and classification of challenging targets

NASA Astrophysics Data System (ADS)

Shubitidze, F.; Fernández, J. P.; Barrowes, B. E.; O'Neill, K.

2013-06-01

Advanced electromagnetic induction (EMI) sensors currently feature multi-axis illumination of targets and tri-axial vector sensing (e.g., MetalMapper), or exploit multi-static array data acquisition (e.g., TEMTADS). They produce data of high density, quality, and diversity, and have been combined with advanced EMI models to provide superb classification performance relative to the previous generation of single-axis, monostatic sensors. However, these advances yet have to improve significantly our ability to classify small, deep, and otherwise challenging targets. Particularly, recent live-site discrimination studies at Camp Butner, NC and Camp Beale, CA have revealed that it is more challenging to detect and discriminate small munitions (with calibers ranging from 20 mm to 60 mm) than larger ones. In addition, a live-site test at the Massachusetts Military Reservation, MA highlighted the difficulties for current sensors to classify large, deep, and overlapping targets with high confidence. There are two main approaches to overcome these problems: 1) adapt advanced EMI models to the existing systems and 2) improve the detection limits of current sensors by modifying their hardware. In this paper we demonstrate a combined software/hardware approach that will provide extended detection range and spatial resolution to next-generation EMI systems; we analyze and invert EMI data to extract classification features for small and deep targets; and we propose a new system that features a large transmitter coil.

ON A POSSIBLE SIZE/COLOR RELATIONSHIP IN THE KUIPER BELT

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

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

2013-10-01

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

Classification and Clustering Methods for Multiple Environmental Factors in Gene-Environment Interaction: Application to the Multi-Ethnic Study of Atherosclerosis.

PubMed

Ko, Yi-An; Mukherjee, Bhramar; Smith, Jennifer A; Kardia, Sharon L R; Allison, Matthew; Diez Roux, Ana V

2016-11-01

There has been an increased interest in identifying gene-environment interaction (G × E) in the context of multiple environmental exposures. Most G × E studies analyze one exposure at a time, but we are exposed to multiple exposures in reality. Efficient analysis strategies for complex G × E with multiple environmental factors in a single model are still lacking. Using the data from the Multiethnic Study of Atherosclerosis, we illustrate a two-step approach for modeling G × E with multiple environmental factors. First, we utilize common clustering and classification strategies (e.g., k-means, latent class analysis, classification and regression trees, Bayesian clustering using Dirichlet Process) to define subgroups corresponding to distinct environmental exposure profiles. Second, we illustrate the use of an additive main effects and multiplicative interaction model, instead of the conventional saturated interaction model using product terms of factors, to study G × E with the data-driven exposure subgroups defined in the first step. We demonstrate useful analytical approaches to translate multiple environmental exposures into one summary class. These tools not only allow researchers to consider several environmental exposures in G × E analysis but also provide some insight into how genes modify the effect of a comprehensive exposure profile instead of examining effect modification for each exposure in isolation.

Selecting Feature Subsets Based on SVM-RFE and the Overlapping Ratio with Applications in Bioinformatics.

PubMed

Lin, Xiaohui; Li, Chao; Zhang, Yanhui; Su, Benzhe; Fan, Meng; Wei, Hai

2017-12-26

Feature selection is an important topic in bioinformatics. Defining informative features from complex high dimensional biological data is critical in disease study, drug development, etc. Support vector machine-recursive feature elimination (SVM-RFE) is an efficient feature selection technique that has shown its power in many applications. It ranks the features according to the recursive feature deletion sequence based on SVM. In this study, we propose a method, SVM-RFE-OA, which combines the classification accuracy rate and the average overlapping ratio of the samples to determine the number of features to be selected from the feature rank of SVM-RFE. Meanwhile, to measure the feature weights more accurately, we propose a modified SVM-RFE-OA (M-SVM-RFE-OA) algorithm that temporally screens out the samples lying in a heavy overlapping area in each iteration. The experiments on the eight public biological datasets show that the discriminative ability of the feature subset could be measured more accurately by combining the classification accuracy rate with the average overlapping degree of the samples compared with using the classification accuracy rate alone, and shielding the samples in the overlapping area made the calculation of the feature weights more stable and accurate. The methods proposed in this study can also be used with other RFE techniques to define potential biomarkers from big biological data.

Perceived functioning and disability in adults with myotonic dystrophy type 1: a survey according to the International Classification Of Functioning, Disability and Health.

PubMed

Kierkegaard, Marie; Harms-Ringdahl, Karin; Widén Holmqvist, Lotta; Tollbäck, Anna

2009-06-01

The purpose of this study was to describe and analyse self-rated perceived functioning, disability and environmental facilitators/barriers with regard to disease severity, using the International Classification of Functioning, Disability and Health (ICF) checklist, in adults with myotonic dystrophy type 1. Cross-sectional design. Forty-one women and 29 men with myotonic dystrophy type 1. A modified ICF checklist was used for self-rating of perceived problems in 29 body-function categories, difficulties in 52 activity and participation categories, and facilitators/barriers in 23 environmental-factor categories according to the verbal anchors of the ICF qualifiers. Disease severity classification was based on the muscular impairment rating scale. Of the persons with myotonic dystrophy type 1, 80% perceived problems of excessive daytime sleepiness, 76% of muscle power, and 66% of energy and drive functions, while over 59% perceived difficulties in physically demanding mobility activities. Disabilities in mobility, self-care and domestic life were more frequently reported by persons with severe disease. Support from the immediate family, medicines and social security services were perceived as facilitators for 50-60% of the participants. Disabilities and important environmental facilitators in adults with myotonic dystrophy type 1 were identified, and this clinically-relevant information can be used for developing health services for people with this condition.

[Cardiorespiratory fitness and cardiometabolic risk in young adults].

PubMed

Secchi, Jeremías D; García, Gastón C

2013-01-01

The assessment of VO₂max allow classify subjects according to the health risk. However the factors that may affect the classifications have been little studied. The main purpose was to determine whether the type of VO₂max prediction equation and the Fitnessgram criterion-referenced standards modified the proportion of young adults classified with a level of aerobic capacity cardiometabolic risk indicative. The study design was observational, cross-sectional and relational. Young adults (n= 240) participated voluntarily. The VO₂max was estimated by 20-m shuttle run test applying 9 predictive equations. The differences in the classifications were analyzed with the Cochran Q and McNemar tests. The level of aerobic capacity indicative of cardiometabolic risk ranged between 7.1% and 70.4% depending on the criterion-referenced standards and predictive equation used (p<0.001). A higher percentage of women were classified with an unhealthy level in all equations (women: 29.4% to 85.3% vs 4.8% to 51% in men), regardless of the criterion-referenced standards (p<0.001). Both sexes and irrespective of the equation applied the old criterion-referenced standards classified a lower proportion of subjects (men: 4.8% to 48.1% and women: 39.4% a 68.4%) with unhealthy aerobic capacity (p ≤ 0.004). The type of VO₂max prediction equation and Fitnessgram criterion-referenced standards changed classifications young adults with a level of aerobic capacity of cardiometabolic risk indicative.

Characterization and classification of lupus patients based on plasma thermograms

PubMed Central

Chaires, Jonathan B.; Mekmaysy, Chongkham S.; DeLeeuw, Lynn; Sivils, Kathy L.; Harley, John B.; Rovin, Brad H.; Kulasekera, K. B.; Jarjour, Wael N.

2017-01-01

Objective Plasma thermograms (thermal stability profiles of blood plasma) are being utilized as a new diagnostic approach for clinical assessment. In this study, we investigated the ability of plasma thermograms to classify systemic lupus erythematosus (SLE) patients versus non SLE controls using a sample of 300 SLE and 300 control subjects from the Lupus Family Registry and Repository. Additionally, we evaluated the heterogeneity of thermograms along age, sex, ethnicity, concurrent health conditions and SLE diagnostic criteria. Methods Thermograms were visualized graphically for important differences between covariates and summarized using various measures. A modified linear discriminant analysis was used to segregate SLE versus control subjects on the basis of the thermograms. Classification accuracy was measured based on multiple training/test splits of the data and compared to classification based on SLE serological markers. Results Median sensitivity, specificity, and overall accuracy based on classification using plasma thermograms was 86%, 83%, and 84% compared to 78%, 95%, and 86% based on a combination of five antibody tests. Combining thermogram and serology information together improved sensitivity from 78% to 86% and overall accuracy from 86% to 89% relative to serology alone. Predictive accuracy of thermograms for distinguishing SLE and osteoarthritis / rheumatoid arthritis patients was comparable. Both gender and anemia significantly interacted with disease status for plasma thermograms (p<0.001), with greater separation between SLE and control thermograms for females relative to males and for patients with anemia relative to patients without anemia. Conclusion Plasma thermograms constitute an additional biomarker which may help improve diagnosis of SLE patients, particularly when coupled with standard diagnostic testing. Differences in thermograms according to patient sex, ethnicity, clinical and environmental factors are important considerations for application of thermograms in a clinical setting. PMID:29149219

Spinal-Exercise Prescription in Sport: Classifying Physical Training and Rehabilitation by Intention and Outcome

PubMed Central

Spencer, Simon; Wolf, Alex; Rushton, Alison

2016-01-01

Context: Identification of strategies to prevent spinal injury, optimize rehabilitation, and enhance performance is a priority for practitioners. Different exercises produce different effects on neuromuscular performance. Clarity of the purpose of a prescribed exercise is central to a successful outcome. Spinal exercises need to be classified according to the objective of the exercise and planned physical outcome. Objective: To define the modifiable spinal abilities that underpin optimal function during skilled athletic performance, clarify the effect of spinal pain and pathologic conditions, and classify spinal exercises according to the objective of the exercise and intended physical outcomes to inform training and rehabilitation. Design: Qualitative study. Data Collection and Analysis: We conducted a qualitative consensus method of 4 iterative phases. An exploratory panel carried out an extended review of the English-language literature using CINAHL, EMBASE, MEDLINE, and PubMed to identify key themes and subthemes to inform the definitions of exercise categories, physical abilities, and physical outcomes. An expert project group reviewed panel findings. A draft classification was discussed with physiotherapists (n = 49) and international experts. Lead physiotherapy and strength and conditioning teams (n = 17) reviewed a revised classification. Consensus was defined as unanimous agreement. Results: After the literature review and subsequent analysis, we defined spinal abilities in 4 categories: mobility, motor control, work capacity, and strength. Exercises were subclassified by functionality as nonfunctional or functional and by spinal displacement as either static (neutral spinal posture with no segmental displacement) or dynamic (dynamic segmental movement). The proposed terminology and classification support commonality of language for practitioners. Conclusions: The spinal-exercise classification will support clinical reasoning through a framework of spinal-exercise objectives that clearly define the nature of the exercise prescription required to deliver intended physical outcomes. PMID:27661792

An international delphi survey for the definition of the variables for the development of new classification criteria for periodic fever aphtous stomatitis pharingitis cervical adenitis (PFAPA).

PubMed

Vanoni, Federica; Federici, Silvia; Antón, Jordi; Barron, Karyl S; Brogan, Paul; De Benedetti, Fabrizio; Dedeoglu, Fatma; Demirkaya, Erkan; Hentgen, Veronique; Kallinich, Tilmann; Laxer, Ronald; Russo, Ricardo; Toplak, Natasa; Uziel, Yosef; Martini, Alberto; Ruperto, Nicolino; Gattorno, Marco; Hofer, Michael

2018-04-18

Diagnosis of Periodic fever, aphthous stomatitis, pharyngitis and cervical adenitis (PFAPA) is currently based on a set of criteria proposed in 1999 modified from Marshall's criteria. Nevertheless no validated evidence based set of classification criteria for PFAPA has been established so far. The aim of this study was to identify candidate classification criteria PFAPA syndrome using international consensus formation through a Delphi questionnaire survey. A first open-ended questionnaire was sent to adult and pediatric clinicians/researchers, asking to identify the variables thought most likely to be helpful and relevant for the diagnosis of PFAPA. In a second survey, respondents were asked to select, from the list of variables coming from the first survey, the 10 features that they felt were most important, and to rank them in descending order from most important to least important. The response rate to the first and second Delphi was respectively 109/124 (88%) and 141/162 (87%). The number of participants that completed the first and second Delphi was 69/124 (56%) and 110/162 (68%). From the first Delphi we obtained a list of 92 variables, of which 62 were selected in the second Delphi. Variables reaching the top five position of the rank were regular periodicity, aphthous stomatitis, response to corticosteroids, cervical adenitis, and well-being between flares. Our process led to identification of features that were felt to be the most important as candidate classification criteria for PFAPA by a large sample of international rheumatologists. The performance of these items will be tested further in the next phase of the study, through analysis of real patient data.

Incidence of Radiologically Isolated Syndrome: A Population-Based Study.

PubMed

Forslin, Y; Granberg, T; Jumah, A Antwan; Shams, S; Aspelin, P; Kristoffersen-Wiberg, M; Martola, J; Fredrikson, S

2016-06-01

Incidental MR imaging findings resembling MS in asymptomatic individuals, fulfilling the Okuda criteria, are termed "radiologically isolated syndrome." Those with radiologically isolated syndrome are at high risk of their condition converting to MS. The epidemiology of radiologically isolated syndrome remains largely unknown, and there are no population-based studies, to our knowledge. Our aim was to study the population-based incidence of radiologically isolated syndrome in a high-incidence region for MS and to evaluate the effect on radiologically isolated syndrome incidence when revising the original radiologically isolated syndrome criteria by using the latest radiologic classification for dissemination in space. All 2272 brain MR imaging scans in 1907 persons obtained during 2013 in the Swedish county of Västmanland, with a population of 259,000 inhabitants, were blindly evaluated by a senior radiologist and a senior neuroradiologist. The Okuda criteria for radiologically isolated syndrome were applied by using both the Barkhof and Swanton classifications for dissemination in space. Assessments of clinical data were performed by a radiology resident and a senior neurologist. The cumulative incidence of radiologically isolated syndrome was 2 patients (0.1%), equaling an incidence rate of 0.8 cases per 100,000 person-years, in a region with an incidence rate of MS of 10.2 cases per 100,000 person-years. There was no difference in the radiologically isolated syndrome incidence rate when applying a modified version of the Okuda criteria by using the newer Swanton classification for dissemination in space. Radiologically isolated syndrome is uncommon in a high-incidence region for MS. Adapting the Okuda criteria to use the dissemination in space-Swanton classification may be feasible. Future studies on radiologically isolated syndrome may benefit from a collaborative approach to ensure adequate numbers of participants. © 2016 by American Journal of Neuroradiology.

Effect of maternal age and cardiac disease severity on outcome of pregnancy in women with congenital heart disease.

PubMed

Furenäs, Eva; Eriksson, Peter; Wennerholm, Ulla-Britt; Dellborg, Mikael

2017-09-15

There is an increasing prevalence of women with congenital heart defects reaching childbearing age. In western countries women tend to give birth at a higher age compared to some decades ago. We evaluated the CARdiac disease in PREGnancy (CARPREG) and modified World Health Organization (mWHO) risk classifications for cardiac complications during pregnancies in women with congenital heart defects and analyzed the impact of age on risk of obstetric and fetal outcome. A single-center observational study of cardiac, obstetric, and neonatal complications with data from cardiac and obstetric records of pregnancies in women with congenital heart disease. Outcomes of 496 pregnancies in 232 women, including induced abortion, miscarriage, stillbirth, and live birth were analyzed regarding complications, maternal age, mode of delivery, and two risk classifications: CARPREG and mWHO. There were 28 induced abortions, 59 fetal loss, 409 deliveries with 412 neonates. Cardiac (14%), obstetric (14%), and neonatal (15%) complications were noted, including one maternal death and five stillbirths. The rate of cesarean section was 19%. Age above 35years was of borderline importance for cardiac complications (p=0.054) and was not a significant additional risk factor for obstetric or neonatal complications. Both risk classifications had moderate clinical utility, with area under the curve (AUC) 0.71 for CARPREG and 0.65 for mWHO on cardiac complications. Pregnancy complications in women with congenital heart disease are common but severe complications are rare. Advanced maternal age does not seem to affect complication rate. Existing risk classification systems are insufficient in predicting complications. Copyright © 2017 Elsevier B.V. All rights reserved.

Application of the Coastal and Marine Ecological Classification Standard to ROV Video Data for Enhanced Analysis of Deep-Sea Habitats in the Gulf of Mexico

NASA Astrophysics Data System (ADS)

Ruby, C.; Skarke, A. D.; Mesick, S.

2016-02-01

The Coastal and Marine Ecological Classification Standard (CMECS) is a network of common nomenclature that provides a comprehensive framework for organizing physical, biological, and chemical information about marine ecosystems. It was developed by the National Oceanic and Atmospheric Administration (NOAA) Coastal Services Center, in collaboration with other feral agencies and academic institutions, as a means for scientists to more easily access, compare, and integrate marine environmental data from a wide range of sources and time frames. CMECS has been endorsed by the Federal Geographic Data Committee (FGDC) as a national metadata standard. The research presented here is focused on the application of CMECS to deep-sea video and environmental data collected by the NOAA ROV Deep Discoverer and the NOAA Ship Okeanos Explorer in the Gulf of Mexico in 2011-2014. Specifically, a spatiotemporal index of the physical, chemical, biological, and geological features observed in ROV video records was developed in order to allow scientist, otherwise unfamiliar with the specific content of existing video data, to rapidly determine the abundance and distribution of features of interest, and thus evaluate the applicability of those video data to their research. CMECS units (setting, component, or modifier) for seafloor images extracted from high-definition ROV video data were established based upon visual assessment as well as analysis of coincident environmental sensor (temperature, conductivity), navigation (ROV position, depth, attitude), and log (narrative dive summary) data. The resulting classification units were integrated into easily searchable textual and geo-databases as well as an interactive web map. The spatial distribution and associations of deep-sea habitats as indicated by CMECS classifications are described and optimized methodological approaches for application of CMECS to deep-sea video and environmental data are presented.

Local pulmonary structure classification for computer-aided nodule detection

NASA Astrophysics Data System (ADS)

Bahlmann, Claus; Li, Xianlin; Okada, Kazunori

2006-03-01

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

Planum Sphenoidale and Tuberculum Sellae Meningiomas: Operative Nuances of a Modern Surgical Technique with Outcome and Proposal of a New Classification System.

PubMed

Mortazavi, Martin M; Brito da Silva, Harley; Ferreira, Manuel; Barber, Jason K; Pridgeon, James S; Sekhar, Laligam N

2016-02-01

The resection of planum sphenoidale and tuberculum sellae meningiomas is challenging. A universally accepted classification system predicting surgical risk and outcome is still lacking. We report a modern surgical technique specific for planum sphenoidale and tuberculum sellae meningiomas with associated outcome. A new classification system that can guide the surgical approach and may predict surgical risk is proposed. We conducted a retrospective review of the patients who between 2005 and March 2015 underwent a craniotomy or endoscopic surgery for the resection of meningiomas involving the suprasellar region. Operative nuances of a modified frontotemporal craniotomy and orbital osteotomy technique for meningioma removal and reconstruction are described. Twenty-seven patients were found to have tumors arising mainly from the planum sphenoidale or the tuberculum sellae; 25 underwent frontotemporal craniotomy and tumor removal with orbital osteotomy and bilateral optic canal decompression, and 2 patients underwent endonasal transphenoidal resection. The most common presenting symptom was visual disturbance (77%). Vision improved in 90% of those who presented with visual decline, and there was no permanent visual deterioration. Cerebrospinal fluid leak occurred in one of the 25 cranial cases (4%) and in 1 of 2 transphenoidal cases (50%), and in both cases it resolved with treatment. There was no surgical mortality. An orbitotomy and early decompression of the involved optic canal are important for achieving gross total resection, maximizing visual improvement, and avoiding recurrence. The visual outcomes were excellent. A new classification system that can allow the comparison of different series and approaches and indicate cases that are more suitable for an endoscopic transsphenoidal approach is presented. Copyright © 2016 Elsevier Inc. All rights reserved.

Dystonia: an update on phenomenology, classification, pathogenesis and treatment.

PubMed

Balint, Bettina; Bhatia, Kailash P

2014-08-01

This article will highlight recent advances in dystonia with focus on clinical aspects such as the new classification, syndromic approach, new gene discoveries and genotype-phenotype correlations. Broadening of phenotype of some of the previously described hereditary dystonias and environmental risk factors and trends in treatment will be covered. Based on phenomenology, a new consensus update on the definition, phenomenology and classification of dystonia and a syndromic approach to guide diagnosis have been proposed. Terminology has changed and 'isolated dystonia' is used wherein dystonia is the only motor feature apart from tremor, and the previously called heredodegenerative dystonias and dystonia plus syndromes are now subsumed under 'combined dystonia'. The recently discovered genes ANO3, GNAL and CIZ1 appear not to be a common cause of adult-onset cervical dystonia. Clinical and genetic heterogeneity underlie myoclonus-dystonia, dopa-responsive dystonia and deafness-dystonia syndrome. ALS2 gene mutations are a newly recognized cause for combined dystonia. The phenotypic and genotypic spectra of ATP1A3 mutations have considerably broadened. Two new genome-wide association studies identified new candidate genes. A retrospective analysis suggested complicated vaginal delivery as a modifying risk factor in DYT1. Recent studies confirm lasting therapeutic effects of deep brain stimulation in isolated dystonia, good treatment response in myoclonus-dystonia, and suggest that early treatment correlates with a better outcome. Phenotypic classification continues to be important to recognize particular forms of dystonia and this includes syndromic associations. There are a number of genes underlying isolated or combined dystonia and there will be further new discoveries with the advances in genetic technologies such as exome and whole-genome sequencing. The identification of new genes will facilitate better elucidation of pathogenetic mechanisms and possible corrective therapies.

Diagnosis and Classification of 17 Diseases from 1404 Subjects via Pattern Analysis of Exhaled Molecules

PubMed Central

2016-01-01

We report on an artificially intelligent nanoarray based on molecularly modified gold nanoparticles and a random network of single-walled carbon nanotubes for noninvasive diagnosis and classification of a number of diseases from exhaled breath. The performance of this artificially intelligent nanoarray was clinically assessed on breath samples collected from 1404 subjects having one of 17 different disease conditions included in the study or having no evidence of any disease (healthy controls). Blind experiments showed that 86% accuracy could be achieved with the artificially intelligent nanoarray, allowing both detection and discrimination between the different disease conditions examined. Analysis of the artificially intelligent nanoarray also showed that each disease has its own unique breathprint, and that the presence of one disease would not screen out others. Cluster analysis showed a reasonable classification power of diseases from the same categories. The effect of confounding clinical and environmental factors on the performance of the nanoarray did not significantly alter the obtained results. The diagnosis and classification power of the nanoarray was also validated by an independent analytical technique, i.e., gas chromatography linked with mass spectrometry. This analysis found that 13 exhaled chemical species, called volatile organic compounds, are associated with certain diseases, and the composition of this assembly of volatile organic compounds differs from one disease to another. Overall, these findings could contribute to one of the most important criteria for successful health intervention in the modern era, viz. easy-to-use, inexpensive (affordable), and miniaturized tools that could also be used for personalized screening, diagnosis, and follow-up of a number of diseases, which can clearly be extended by further development. PMID:28000444

Structured reporting platform improves CAD-RADS assessment.

PubMed

Szilveszter, Bálint; Kolossváry, Márton; Karády, Júlia; Jermendy, Ádám L; Károlyi, Mihály; Panajotu, Alexisz; Bagyura, Zsolt; Vecsey-Nagy, Milán; Cury, Ricardo C; Leipsic, Jonathon A; Merkely, Béla; Maurovich-Horvat, Pál

2017-11-01

Structured reporting in cardiac imaging is strongly encouraged to improve quality through consistency. The Coronary Artery Disease - Reporting and Data System (CAD-RADS) was recently introduced to facilitate interdisciplinary communication of coronary CT angiography (CTA) results. We aimed to assess the agreement between manual and automated CAD-RADS classification using a structured reporting platform. Five readers prospectively interpreted 500 coronary CT angiographies using a structured reporting platform that automatically calculates the CAD-RADS score based on stenosis and plaque parameters manually entered by the reader. In addition, all readers manually assessed CAD-RADS blinded to the automatically derived results, which was used as the reference standard. We evaluated factors influencing reader performance including CAD-RADS training, clinical load, time of the day and level of expertise. Total agreement between manual and automated classification was 80.2%. Agreement in stenosis categories was 86.7%, whereas the agreement in modifiers was 95.8% for "N", 96.8% for "S", 95.6% for "V" and 99.4% for "G". Agreement for V improved after CAD-RADS training (p = 0.047). Time of the day and clinical load did not influence reader performance (p > 0.05 both). Less experienced readers had a higher total agreement as compared to more experienced readers (87.0% vs 78.0%, respectively; p = 0.011). Even though automated CAD-RADS classification uses data filled in by the readers, it outperforms manual classification by preventing human errors. Structured reporting platforms with automated calculation of the CAD-RADS score might improve data quality and support standardization of clinical decision making. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Hyperspectral Image Classification using a Self-Organizing Map

NASA Technical Reports Server (NTRS)

Martinez, P.; Gualtieri, J. A.; Aguilar, P. L.; Perez, R. M.; Linaje, M.; Preciado, J. C.; Plaza, A.

2001-01-01

The use of hyperspectral data to determine the abundance of constituents in a certain portion of the Earth's surface relies on the capability of imaging spectrometers to provide a large amount of information at each pixel of a certain scene. Today, hyperspectral imaging sensors are capable of generating unprecedented volumes of radiometric data. The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), for example, routinely produces image cubes with 224 spectral bands. This undoubtedly opens a wide range of new possibilities, but the analysis of such a massive amount of information is not an easy task. In fact, most of the existing algorithms devoted to analyzing multispectral images are not applicable in the hyperspectral domain, because of the size and high dimensionality of the images. The application of neural networks to perform unsupervised classification of hyperspectral data has been tested by several authors and also by us in some previous work. We have also focused on analyzing the intrinsic capability of neural networks to parallelize the whole hyperspectral unmixing process. The results shown in this work indicate that neural network models are able to find clusters of closely related hyperspectral signatures, and thus can be used as a powerful tool to achieve the desired classification. The present work discusses the possibility of using a Self Organizing neural network to perform unsupervised classification of hyperspectral images. In sections 3 and 4, the topology of the proposed neural network and the training algorithm are respectively described. Section 5 provides the results we have obtained after applying the proposed methodology to real hyperspectral data, described in section 2. Different parameters in the learning stage have been modified in order to obtain a detailed description of their influence on the final results. Finally, in section 6 we provide the conclusions at which we have arrived.

Can we improve accuracy and reliability of MRI interpretation in children with optic pathway glioma? Proposal for a reproducible imaging classification.

PubMed

Lambron, Julien; Rakotonjanahary, Josué; Loisel, Didier; Frampas, Eric; De Carli, Emilie; Delion, Matthieu; Rialland, Xavier; Toulgoat, Frédérique

2016-02-01

Magnetic resonance (MR) images from children with optic pathway glioma (OPG) are complex. We initiated this study to evaluate the accuracy of MR imaging (MRI) interpretation and to propose a simple and reproducible imaging classification for MRI. We randomly selected 140 MRIs from among 510 MRIs performed on 104 children diagnosed with OPG in France from 1990 to 2004. These images were reviewed independently by three radiologists (F.T., 15 years of experience in neuroradiology; D.L., 25 years of experience in pediatric radiology; and J.L., 3 years of experience in radiology) using a classification derived from the Dodge and modified Dodge classifications. Intra- and interobserver reliabilities were assessed using the Bland-Altman method and the kappa coefficient. These reviews allowed the definition of reliable criteria for MRI interpretation. The reviews showed intraobserver variability and large discrepancies among the three radiologists (kappa coefficient varying from 0.11 to 1). These variabilities were too large for the interpretation to be considered reproducible over time or among observers. A consensual analysis, taking into account all observed variabilities, allowed the development of a definitive interpretation protocol. Using this revised protocol, we observed consistent intra- and interobserver results (kappa coefficient varying from 0.56 to 1). The mean interobserver difference for the solid portion of the tumor with contrast enhancement was 0.8 cm(3) (limits of agreement = -16 to 17). We propose simple and precise rules for improving the accuracy and reliability of MRI interpretation for children with OPG. Further studies will be necessary to investigate the possible prognostic value of this approach.

The ICNP-BaT--a multilingual web-based tool to support the collaborative translation of the International Classification for Nursing Practice (ICNP).

PubMed

Schrader, Ulrich; Tackenberg, Peter; Widmer, Rudolf; Portenier, Lucien; König, Peter

2007-01-01

To ease and speed up the translation of the ICNP version 1 into the German language a web service was developed to support the collaborative work of all Austrian, Swiss, and German translators and subsequently of the evaluators of the resultant translation. The web service does help to support a modified Delphi technique. Since the web service is multilingual by design it can facilitate the translation of the ICNP into other languages as well. The process chosen can be adopted by other projects involved in translating terminologies.

Accuracy Analysis of DSMC Chemistry Models Applied to a Normal Shock Wave

DTIC Science & Technology

2012-06-20

CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18 . NUMBER OF PAGES 19a. NAME OF RESPONSIBLE PERSON A. Ketsdever a. REPORT Unclassified b. ABSTRACT...coefficient from [4] is assumed to be 2×10−19 m3/s at 5000 K and 7− 18 m3/s at 10,000K ; the QK prediction using the present VHS collision parameters...is 9−20 m3/s at 5000 K and 2− 18 m3/s at 10000K. Note that the QK for the present work was modified for use with AHO energy levels for consistency

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

Foley, Brian T.; Leitner, Thomas; Paraskevis, Dimitrios

The International Committee for the Taxonomy and Nomenclature of Viruses does not rule on virus classifications below the species level. The definition of species for viruses cannot be clearly defined for all types of viruses. The complex and interesting epidemiology of Human Immunodeficiency Viruses demands a detailed and informative nomenclature system, while at the same time it presents challenges such that many of the rules need to be flexibly applied or modified over time. As a result, this review outlines the nomenclature system for primate lentiviruses and provides an update on new findings since the last review was written inmore » 2000.« less

National register of research projects, 1986/87. Part 4: Human sciences. Economic, political, language, art and other sciences

NASA Astrophysics Data System (ADS)

1988-08-01

This Register is intended to serve as a source of information on research which is being conducted in all fields (both natural and human sciences) in the Republic of South Africa. New and current research projects that were commenced or modified during 1986 and 1987, on which information was received by the compilers until January 1988, are included, with the exception of confidential projects. Project titles and keywords are presented in the language as supplied, and the classifications are based on those provided by the primary sources.

Is the lumbar modifier useful in surgical decision making?: defining two distinct Lenke 1A curve patterns.

PubMed

Miyanji, Firoz; Pawelek, Jeff B; Van Valin, Scott E; Upasani, Vidyadhar V; Newton, Peter O

2008-11-01

Retrospective review of adolescent idiopathic scoliosis (AIS) patients. To investigate the clinical deformity and radiographic features of Lenke 1A and 1B curves to determine if the "A" and "B" lumbar modifiers actually describe 2 distinct curve patterns. The Lenke classification system attempts to address some of the shortcomings of the King-Moe classification system by providing a more comprehensive, reliable, and treatment-based categorization of all AIS deformities. Although this classification is useful in determining which regions of the spine should be fused, it does not necessarily divide AIS curves into distinct patterns. A critical analysis of the clinical deformity, radiographic features, and surgical treatment of AIS patients with Lenke 1A and 1B right thoracic curves was performed. Lenke 1A curves were differentiated according to the L4 coronal plane tilt. Analysis of variance and Pearson chi analysis were used to perform statistical comparisons between the individual curve patterns (P < or = 0.05). Ninety-three patients with preoperative and 2-year postoperative data were included in this analysis (65 Lenke 1A, and 28 Lenke 1B). Thirty-three patients were subdivided as 1A-L (L4 tilted to the left) and 32 patients were subdivided as 1A-R (L4 tilted to the right). The interobserver reliability for determining the direction of L4 tilt was excellent (kappa = 0.94, P < or = 0.001). Patients with 1A-L curves were similar to patients with 1B curves with respect to the L4 tilt and the location of the stable vertebra (most often in the thoracolumbar junction). In contrast, patients with 1A-R curves had a more distal stable vertebra (most often L3 or L4). The surgical treatment also differed between these 2 groups with regards to the lowest instrumented vertebra (LIV). 1A-L and 1B curves were similar with a median LIV of T12, whereas the 1A-R curves had a more distal median LIV of L2 (P = 0.01). Two Lenke 1A curve patterns can be described based on the direction of the L4 tilt. This distinction has ramifications regarding selection of fusion levels and assessing surgical outcomes. The A and B lumbar modifiers do not describe 2 distinct curve types within the Lenke 1 group; however, the tilt direction of L4 does allow subdivision of the Lenke 1A curves into 2 distinguishable patterns (1A-R and 1A-L). The 1A-L curves are similar to 1B curves and different in form and treatment from the 1A-R pattern.

Histopathological grading of breast ductal carcinoma in situ: validation of a web-based survey through intra-observer reproducibility analysis.

PubMed

Schuh, Fernando; Biazús, Jorge Villanova; Resetkova, Erika; Benfica, Camila Zanella; Ventura, Alessandra de Freitas; Uchoa, Diego; Graudenz, Márcia; Edelweiss, Maria Isabel Albano

2015-07-10

Histopathological grading diagnosis of ductal carcinoma in situ (DCIS) of the breast may be very difficult even for experts, and it is important for therapeutic decisions. The challenge may be due to the inaccurate and/or subjective application of the diagnosis criteria. The aim of this study was to investigate the intra-observer agreement between a traditional method and a developed web-based questionnaire for scoring breast DCIS. A cross-sectional study was carried out to evaluate the diagnostic agreement of an electronic questionnaire and its point scoring system with the subjective reading of digital images for 3 different DCIS grading systems: Holland, Van Nuys and modified Black nuclear grade system. Three pathologists analyzed the same set of digitized images from 43 DCIS cases using two different web-based programs. In the first phase, they accessed a website with a newly created questionnaire and scoring system developed to allow the determination of the histological grade of the cases. After at least 6 months, the pathologists read again the same images, but without the help of the questionnaire, indicating subjectively the diagnoses. The intra-observer agreement analysis was employed to validate this innovative web-based survey. Overall, diagnostic reproducibility was similar for all histologic grading classification systems, with kappa values of 0.57 ± 0.10, 0.67 ± 0.09 and 0.67 ± 0.09 for Holland, Van Nuys classification and modified Black nuclear grade system respectively. Only two 2-step diagnostic disagreements were found, one for Holland and another for Van Nuys. Both cases were superestimated by the web-based survey. The diagnostic agreement between the web-based questionnaire and a traditional method, both using digital images, is moderate to good for Holland, Van Nuys and modified Black nuclear grade system. The use of a scoring point system does not appear to pose a major risk of presenting large (2-step) diagnostic disagreements. These findings indicate that the use of this point scoring system in this web-based survey to grade objectively DCIS lesions is a useful diagnostic tool.

[Application of biotope mapping model integrated with vegetation cover continuity attributes in urban biodiversity conservation].

PubMed

Gao, Tian; Qiu, Ling; Chen, Cun-gen

2010-09-01

Based on the biotope classification system with vegetation structure as the framework, a modified biotope mapping model integrated with vegetation cover continuity attributes was developed, and applied to the study of the greenbelts in Helsingborg in southern Sweden. An evaluation of the vegetation cover continuity in the greenbelts was carried out by the comparisons of the vascular plant species richness in long- and short-continuity forests, based on the identification of woodland continuity by using ancient woodland indicator species (AWIS). In the test greenbelts, long-continuity woodlands had more AWIS. Among the forests where the dominant trees were more than 30-year-old, the long-continuity ones had a higher biodiversity of vascular plants, compared with the short-continuity ones with the similar vegetation structure. The modified biotope mapping model integrated with the continuity features of vegetation cover could be an important tool in investigating urban biodiversity, and provide corresponding strategies for future urban biodiversity conservation.

Epigenetic modulators, modifiers and mediators in cancer aetiology and progression

PubMed Central

Feinberg, Andrew P.; Koldobskiy, Michael A.; Göndör, Anita

2016-01-01

This year is the tenth anniversary of the publication in this journal of a model suggesting the existence of ‘tumour progenitor genes’. These genes are epigenetically disrupted at the earliest stages of malignancies, even before mutations, and thus cause altered differentiation throughout tumour evolution. The past decade of discovery in cancer epigenetics has revealed a number of similarities between cancer genes and stem cell reprogramming genes, widespread mutations in epigenetic regulators, and the part played by chromatin structure in cellular plasticity in both development and cancer. In the light of these discoveries, we suggest here a framework for cancer epigenetics involving three types of genes: ‘epigenetic mediators’, corresponding to the tumour progenitor genes suggested earlier; ‘epigenetic modifiers’ of the mediators, which are frequently mutated in cancer; and ‘epigenetic modulators’ upstream of the modifiers, which are responsive to changes in the cellular environment and often linked to the nuclear architecture. We suggest that this classification is helpful in framing new diagnostic and therapeutic approaches to cancer. PMID:26972587

Stars with relativistic speeds in the Hills scenario

NASA Astrophysics Data System (ADS)

Dremova, G. N.; Dremov, V. V.; Tutukov, A. V.

2017-07-01

The dynamical capture of a binary system consisting of a supermassive black hole (SMBH) and an ordinary star in the gravitational field of a central (more massive) SMBH is considered in the three-body problem in the framework of a modified Hills scenario. The results of numerical simulations predict the existence of objects whose spatial speeds are comparable to the speed of light. The conditions for and constraints imposed on the ejection speeds realized in a classical scenario and the modified Hills scenario are analyzed. The star is modeled using an N-body approach, making it possible to treat it as a structured object, enabling estimation of the probability that the object survives when it is ejected with relativistic speed as a function of the mass of the star, the masses of both SMBHs, and the pericenter distance. It is possible that the modern kinematic classification for stars with anomalously high spatial velocities will be augmented with a new class—stars with relativistic speeds.

Optimal feature selection using a modified differential evolution algorithm and its effectiveness for prediction of heart disease.

PubMed

Vivekanandan, T; Sriman Narayana Iyengar, N Ch

2017-11-01

Enormous data growth in multiple domains has posed a great challenge for data processing and analysis techniques. In particular, the traditional record maintenance strategy has been replaced in the healthcare system. It is vital to develop a model that is able to handle the huge amount of e-healthcare data efficiently. In this paper, the challenging tasks of selecting critical features from the enormous set of available features and diagnosing heart disease are carried out. Feature selection is one of the most widely used pre-processing steps in classification problems. A modified differential evolution (DE) algorithm is used to perform feature selection for cardiovascular disease and optimization of selected features. Of the 10 available strategies for the traditional DE algorithm, the seventh strategy, which is represented by DE/rand/2/exp, is considered for comparative study. The performance analysis of the developed modified DE strategy is given in this paper. With the selected critical features, prediction of heart disease is carried out using fuzzy AHP and a feed-forward neural network. Various performance measures of integrating the modified differential evolution algorithm with fuzzy AHP and a feed-forward neural network in the prediction of heart disease are evaluated in this paper. The accuracy of the proposed hybrid model is 83%, which is higher than that of some other existing models. In addition, the prediction time of the proposed hybrid model is also evaluated and has shown promising results. Copyright © 2017 Elsevier Ltd. All rights reserved.

Detecting red blotch disease in grape leaves using hyperspectral imaging

NASA Astrophysics Data System (ADS)

Mehrubeoglu, Mehrube; Orlebeck, Keith; Zemlan, Michael J.; Autran, Wesley

2016-05-01

Red blotch disease is a viral disease that affects grapevines. Symptoms appear as irregular blotches on grape leaves with pink and red veins on the underside of the leaves. Red blotch disease causes a reduction in the accumulation of sugar in grapevines affecting the quality of grapes and resulting in delayed harvest. Detecting and monitoring this disease early is important for grapevine management. This work focuses on the use of hyperspectral imaging for detection and mapping red blotch disease in grape leaves. Grape leaves with known red blotch disease have been imaged with a portable hyperspectral imaging system both on and off the vine to investigate the spectral signature of red blotch disease as well as to identify the diseased areas on the leaves. Modified reflectance calculated at spectral bands corresponding to 566 nm (green) and 628 nm (red), and modified reflectance ratios computed at two sets of bands (566 nm / 628 nm, 680 nm / 738 nm) were selected as effective features to differentiate red blotch from healthy-looking and dry leaf. These two modified reflectance and two ratios of modified reflectance values were then used to train the support vector machine classifier in a supervised learning scheme. Once the SVM classifier was defined, two-class classification was achieved for grape leaf hyperspectral images. Identification of the red blotch disease on grape leaves as well as mapping different stages of the disease using hyperspectral imaging are presented in this paper.

Improved classification accuracy of powdery mildew infection levels of wine grapes by spatial-spectral analysis of hyperspectral images.

PubMed

Knauer, Uwe; Matros, Andrea; Petrovic, Tijana; Zanker, Timothy; Scott, Eileen S; Seiffert, Udo

2017-01-01

Hyperspectral imaging is an emerging means of assessing plant vitality, stress parameters, nutrition status, and diseases. Extraction of target values from the high-dimensional datasets either relies on pixel-wise processing of the full spectral information, appropriate selection of individual bands, or calculation of spectral indices. Limitations of such approaches are reduced classification accuracy, reduced robustness due to spatial variation of the spectral information across the surface of the objects measured as well as a loss of information intrinsic to band selection and use of spectral indices. In this paper we present an improved spatial-spectral segmentation approach for the analysis of hyperspectral imaging data and its application for the prediction of powdery mildew infection levels (disease severity) of intact Chardonnay grape bunches shortly before veraison. Instead of calculating texture features (spatial features) for the huge number of spectral bands independently, dimensionality reduction by means of Linear Discriminant Analysis (LDA) was applied first to derive a few descriptive image bands. Subsequent classification was based on modified Random Forest classifiers and selective extraction of texture parameters from the integral image representation of the image bands generated. Dimensionality reduction, integral images, and the selective feature extraction led to improved classification accuracies of up to [Formula: see text] for detached berries used as a reference sample (training dataset). Our approach was validated by predicting infection levels for a sample of 30 intact bunches. Classification accuracy improved with the number of decision trees of the Random Forest classifier. These results corresponded with qPCR results. An accuracy of 0.87 was achieved in classification of healthy, infected, and severely diseased bunches. However, discrimination between visually healthy and infected bunches proved to be challenging for a few samples, perhaps due to colonized berries or sparse mycelia hidden within the bunch or airborne conidia on the berries that were detected by qPCR. An advanced approach to hyperspectral image classification based on combined spatial and spectral image features, potentially applicable to many available hyperspectral sensor technologies, has been developed and validated to improve the detection of powdery mildew infection levels of Chardonnay grape bunches. The spatial-spectral approach improved especially the detection of light infection levels compared with pixel-wise spectral data analysis. This approach is expected to improve the speed and accuracy of disease detection once the thresholds for fungal biomass detected by hyperspectral imaging are established; it can also facilitate monitoring in plant phenotyping of grapevine and additional crops.

A Method of Sky Ripple Residual Nonuniformity Reduction for a Cooled Infrared Imager and Hardware Implementation.

PubMed

Li, Yiyang; Jin, Weiqi; Li, Shuo; Zhang, Xu; Zhu, Jin

2017-05-08

Cooled infrared detector arrays always suffer from undesired ripple residual nonuniformity (RNU) in sky scene observations. The ripple residual nonuniformity seriously affects the imaging quality, especially for small target detection. It is difficult to eliminate it using the calibration-based techniques and the current scene-based nonuniformity algorithms. In this paper, we present a modified temporal high-pass nonuniformity correction algorithm using fuzzy scene classification. The fuzzy scene classification is designed to control the correction threshold so that the algorithm can remove ripple RNU without degrading the scene details. We test the algorithm on a real infrared sequence by comparing it to several well-established methods. The result shows that the algorithm has obvious advantages compared with the tested methods in terms of detail conservation and convergence speed for ripple RNU correction. Furthermore, we display our architecture with a prototype built on a Xilinx Virtex-5 XC5VLX50T field-programmable gate array (FPGA), which has two advantages: (1) low resources consumption; and (2) small hardware delay (less than 10 image rows). It has been successfully applied in an actual system.

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

PubMed

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

2005-03-01

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

[Categorical and dimensional diagnosis in schizoid and narcissistic personality disorders: critical interpretation of literature cases].

PubMed

Coccanari De Fornari, Maria Antonietta; Piccione, Michele; Giampà, Alessio

2010-01-01

In the general reflection inherent categorical and dimensional diagnosis and the opportunity to put neurotic and psychotic personality in the various chapters of the discipline, a never-ending discussion on the similarities and differences between clinical pictures classified in separate entries (think of the comings and goings from one cluster to another between schizoid and avoidant personality disorder). Other cogent discussion focused on the nosographical criteria, targeted to a modified classification that takes into account dimensional rather than descriptive criteria. About personality disorders think of the debate on their degree of severity, as assessed by criteria such dissimilar from various authors, as to be very different in this sense a ranking according to the variables considered (eg, classifications by Kernberg and Millon). As an established tradition that a contribution to psychological studies derives also from the literary and artistic forms in general, we propose, through the interpretation of literary cases, the dimensional affinity between schizoid and narcissistic disorders. The dimensions taken into account are those of affectivity and intersubjectivity, impaired in both disorders.

Exception handling for sensor fusion

NASA Astrophysics Data System (ADS)

Chavez, G. T.; Murphy, Robin R.

1993-08-01

This paper presents a control scheme for handling sensing failures (sensor malfunctions, significant degradations in performance due to changes in the environment, and errant expectations) in sensor fusion for autonomous mobile robots. The advantages of the exception handling mechanism are that it emphasizes a fast response to sensing failures, is able to use only a partial causal model of sensing failure, and leads to a graceful degradation of sensing if the sensing failure cannot be compensated for. The exception handling mechanism consists of two modules: error classification and error recovery. The error classification module in the exception handler attempts to classify the type and source(s) of the error using a modified generate-and-test procedure. If the source of the error is isolated, the error recovery module examines its cache of recovery schemes, which either repair or replace the current sensing configuration. If the failure is due to an error in expectation or cannot be identified, the planner is alerted. Experiments using actual sensor data collected by the CSM Mobile Robotics/Machine Perception Laboratory's Denning mobile robot demonstrate the operation of the exception handling mechanism.

Continuous Change Detection of Urban Lakes in Wuhan, China Using Multi-Temporal Remote Sensing Images

NASA Astrophysics Data System (ADS)

Zhang, W.; Kong, X.; Tan, G.; Zheng, S.

2018-04-01

Urban lakes are important natural, scenic and pattern attractions of the city, and they are potential development resources as well. However, lots of urban lakes in China have been shrunk significantly or disappeared due to rapid urbanization. In this study, four Landsat images were used to perform a case study for lake change detection in downtown Wuhan, China, which were acquired on 1991, 2002, 2011 and 2017, respectively. Modified NDWI (MNDWI) was adopted to extract water bodies of urban areas from all these images, and OTSU was used to optimize the threshold selection. Furthermore, the variation of lake shrinkage was analysed in detail according to SVM classification and post-classification comparison, and the coverage of urban lakes in central area of Wuhan has decreased by 47.37 km2 between 1991 and 2017. The experimental results revealed that there were significant changes in the surface area of urban lakes over the 27 years, and it also indicated that rapid urbanization has a strong impact on the losses of urban water resources.

Evaluation of SLAR and thematic mapper MSS data for forest cover mapping using computer-aided analysis techniques

NASA Technical Reports Server (NTRS)

Hoffer, R. M. (Principal Investigator)

1981-01-01

Training and test data sets for CAM1S from NS-001 MSS data for two dates (geometrically adjusted to 30 meter resolution) were used to evaluate wavelength band. Two sets of tapes containing digitized HH and HV polarization data were obtained. Because the SAR data on the 9 track tapes contained no meaningful data, the 7 track tapes were copied onto 9 track tapes at LARS. The LARSYS programs were modified and a program was written to reformat the digitized SAR data into a LARSYS format. The radar imagery is being qualitatively interpreted. Results are to be used to identify possible cover types, to produce a classification map to aid in the numerical evaluation classification of radar data, and to develop an interpretation key for radar imagery. The four spatial resolution data sets were analyzed. A program was developed to reduce the spatial distortions resulting from variable viewing distance, and geometrically adjusted data sets were generated. A flowchart of steps taken to geometrically adjust a data set from the NS-001 scanner is presented.

The scope and specific criteria of compensation for occupational diseases in Korea.

PubMed

Song, Jaechul; Kim, Inah; Choi, Byung-Soon

2014-06-01

The range of diseases covered by workers' compensation is constantly expanding. However, new regulations are required for the recognition of occupational diseases (ODs) because OD types evolve with changes in industrial structures and working conditions. OD criteria are usually based on medical relevance, but they vary depending on the social security system and laws of each country. In addition, the proposed range and extent of work-relatedness vary depending on the socio-economic conditions of each country. The Labor Standards Act (LSA) and the Industrial Accident Compensation Insurance Act (IACIA) of Korea employ lists based on their requirements without listing causes and diseases separately. Despite a considerable reshuffle in 2003, the basic framework has been maintained for 50 yr, and many cases do not fit into the international disease classification system. Since July 1, 2013, Korea has expanded the range of occupational accidents to include occupational cancers and has implemented revised LSA and IACIA enforcement decrees. There have been improvements to OD recognition standards with the inclusion of additional or modified criteria, a revised and improved classification scheme for risk factors and ODs, and so on.

Current Issues in the Diagnosis of Attention Deficit Hyperactivity Disorder, Oppositional Defiant Disorder, and Conduct Disorder

PubMed Central

Frick, Paul J.; Nigg, Joel T.

2015-01-01

This review evaluates the diagnostic criteria for three of the most common disorders for which children and adolescents are referred for mental health treatment: attention deficit hyperactivity disorder (ADHD), oppositional defiant disorder (ODD), and conduct disorder (CD). Although research supports the validity and clinical utility of these disorders, several issues are highlighted that could enhance the current diagnostic criteria. For ADHD, defining the core features of the disorder and its fit with other disorders, enhancing the validity of the criteria through the lifespan, considering alternative ways to form subtypes of the disorder, and modifying the age-of-onset criterion are discussed relative to the current diagnostic criteria. For ODD, eliminating the exclusionary criteria of CD, recognizing important symptom domains within the disorder, and using the cross-situational pervasiveness of the disorder as an index of severity are highlighted as important issues for improving classification. Finally, for CD, enhancing the current subtypes related to age of onset and integrating callous-unemotional traits into the diagnostic criteria are identified as key issues for improving classification. PMID:22035245

Maximum workplace concentration values and carcinogenicity classification for mixtures.

PubMed Central

Bartsch, R; Forderkunz, S; Reuter, U; Sterzl-Eckert, H; Greim, H

1998-01-01

In Germany, the Commission for the Investigation of Health Hazards of Chemical Compounds in the Work Area (MAK Commission) generally sets maximum workplace concentration values (i.e., a proposed occupational exposure level [OEL]) for single substances, not for mixtures. For mixtures containing substances with a genotoxic and carcinogenic potential, the commission considered it scientifically inappropriate to establish a safe threshold. This approach is currently under discussion. Carcinogenic mixtures are categorized according to either the carcinogenicity of the mixture or the classification of the carcinogenic substances included. In regulating exposure to mixtures, an approach similar to that used by the American Conference of Governmental Hygienists is proposed: For components with the same target organ and mode of action or interfering metabolism, synergistic effects must be expected and the respective OELs must be lowered. However, if there is proof that the components act independently, the OELs of the individual compounds are not considered to be modified. In the view of the commission, calculating OELs for solvent mixtures according to their liquid phase composition is not justified, and the setting of scientifically based OELs for complex mixtures is not possible. PMID:9860883

Determining decision thresholds and evaluating indicators when conservation status is measured as a continuum.

PubMed

Connors, B M; Cooper, A B

2014-12-01

Categorization of the status of populations, species, and ecosystems underpins most conservation activities. Status is often based on how a system's current indicator value (e.g., change in abundance) relates to some threshold of conservation concern. Receiver operating characteristic (ROC) curves can be used to quantify the statistical reliability of indicators of conservation status and evaluate trade-offs between correct (true positive) and incorrect (false positive) classifications across a range of decision thresholds. However, ROC curves assume a discrete, binary relationship between an indicator and the conservation status it is meant to track, which is a simplification of the more realistic continuum of conservation status, and may limit the applicability of ROC curves in conservation science. We describe a modified ROC curve that treats conservation status as a continuum rather than a discrete state. We explored the influence of this continuum and typical sources of variation in abundance that can lead to classification errors (i.e., random variation and measurement error) on the true and false positive rates corresponding to varying decision thresholds and the reliability of change in abundance as an indicator of conservation status, respectively. We applied our modified ROC approach to an indicator of endangerment in Pacific salmon (Oncorhynchus nerka) (i.e., percent decline in geometric mean abundance) and an indicator of marine ecosystem structure and function (i.e., detritivore biomass). Failure to treat conservation status as a continuum when choosing thresholds for indicators resulted in the misidentification of trade-offs between true and false positive rates and the overestimation of an indicator's reliability. We argue for treating conservation status as a continuum when ROC curves are used to evaluate decision thresholds in indicators for the assessment of conservation status. © 2014 Society for Conservation Biology.

The T-plasty: a modified YV-plasty for highly recurrent bladder neck contracture after transurethral surgery for benign hyperplasia of the prostate: clinical outcome and patient satisfaction.

PubMed

Reiss, C P; Rosenbaum, C M; Becker, A; Schriefer, P; Ludwig, T A; Engel, O; Riechardt, S; Fisch, M; Dahlem, R

2016-10-01

To describe a modified surgical technique for treatment of highly recurrent bladder neck contracture (BNC) after transurethral surgery for benign hyperplasia and to evaluate success rate and patient satisfaction of this novel technique. Ten patients with highly recurrent BNC and multiple prior attempts of endoscopic treatment underwent the T-plasty. Perioperative complications were recorded and classified according to the Clavien classification. Patient reported functional outcomes were retrospectively analysed using a standardized questionnaire assessing recurrence of stenosis, incontinence, satisfaction and changes in quality of life (QoL). The questionnaires included validated IPSS and SF-8-health survey items. Mean age at the time of surgery was 69.2 years (range 61-79), and the mean follow-up was 26 months (range 3-46). No complications grade 3 or higher according to the Clavien classification occurred. Success rate was 100 %. No de novo stress incontinence occurred. Urinary stream was described as very strong to moderate by 80 % of the patients, mean post-operative IPSS-score was 11.3 (range 4-29), and mean post-operative IPSS-QoL was 2.4 (range 1-5). Patients satisfaction was very high or high in 90 %, and QoL improved in 90 %. The SF-8-health survey showed values comparable to the reference population. The T-plasty represents a safe and valuable option in treating highly recurrent BNC after surgery for benign hyperplasia. It offers multiple advantages compared to other techniques such as a single-staged approach and the opportunity for reconstruction of a reliable wide bladder neck by usage of two well-vascularized flaps. Success rate, low rate of complications and preservation of continence are highly encouraging.

Analysis of mandibular second molars with fused roots and shallow radicular grooves by using micro-computed tomography.

PubMed

Amoroso-Silva, Pablo; De Moraes, Ivaldo Gomes; Marceliano-Alves, Marilia; Bramante, Clovis Monteiro; Zapata, Ronald Ordinola; Hungaro Duarte, Marco Antonio

2018-01-01

This study aimed to describe the morphological and morphometric aspects of fused mandibular second molars with radicular shallow grooves using micro-computed tomography (CT). Eighty-eight mandibular second molars with fused roots were scanned in a micro-CT scanner at a voxel size of 19.6 μm. After reconstruction, only molars without C-shaped roots and presenting shallow radicular grooves were selected. 30 molars were chosen for further analysis. Canal cross-sections were classified according to Fan's modified classification (C1, C2, C3, and C4) and morphometric parameters at the apical region, examination of accessory foramina and tridimensional configuration were evaluated. Three-dimensional reconstructions indicated a higher prevalence of merging type ( n = 22). According to Fan's modified classification, the C4 configuration was predominant in the 3 apical mm. Roundness median values revealed a more round-shaped canals at 3 mm (0.72) than at 2 (0.63) and 1 (0.61) mm from the apex. High values of major and minor diameters were observed in the canals of these evaluated sections. In addition, few accessory apical foramina were observed at 1 and 2 mm from the apex. The average distance between last accessory foramina and the anatomic apex was 1.17 mm. A less complex internal anatomy is found when a mandibular second molar presents fused roots with shallow radicular grooves. The merging type canal was frequently observed. Moreover, the C4 configuration was predominant at a point 3 mm from the apex and presented rounded canals, large apical diameters, and few accessory foramina. The cervical and middle thirds presented C3 and C1 canal configurations most frequently. A minor morphological complexity is found when fused mandibular second molars present shallow radicular grooves.

Determination of the health of Lunyangwa wetland using Wetland Classification and Risk Assessment Index

NASA Astrophysics Data System (ADS)

Wanda, Elijah M. M.; Mamba, Bhekie B.; Msagati, Titus A. M.; Msilimba, Golden

2016-04-01

Wetlands are major sources of various ecological goods and services including storage and distribution of water in space and time which help in ensuring the availability of surface and groundwater throughout the year. However, there still remains a poor understanding of the range of values of water quality parameters that occur in wetlands either in its impacted state or under natural conditions. It was thus imperative to determine the health of Lunyangwa wetland in Mzuzu City in Malawi in order to classify and determine its state. This study used the Escom's Wetland Classification and Risk Assessment Index Field Guide to determine the overall characteristics of Lunyangwa wetland and to calculate its combined Wetland Index Score. Data on site information, field measurements (i.e. EC, pH, temperature and DO) and physical characteristics of Lunyangwa wetland were collected from March, 2013 to February, 2014. Results indicate that Lunyangwa wetland is a largely open water zone which is dominated by free-floating plants on the water surface, beneath surface and emergent in substrate. Furthermore, the wetland can be classified as of a C ecological category (score = 60-80%), which has been moderately modified with moderate risks of the losses and changes occurring in the natural habitat and biota in the wetland. It was observed that the moderate modification and risk were largely because of industrial, agricultural, urban/social catchment stressors on the wetland. This study recommends an integrated and sustainable management approach coupled with continuous monitoring and evaluation of the health of the wetland for all stakeholders in Mzuzu City. This would help to maintain the health of Lunyangwa wetland which is currently at risk of being further modified due to the identified catchment stressors.

The efficacy of the modified classification system of soft tissue injury in extension injury of the lower cervical spine.

PubMed

Song, Kyung-Jin; Kim, Gyu-Hyung; Lee, Kwang-Bok

2008-07-01

To classify comprehensively the severity of soft tissue injury for extension injuries of the lower cervical spine by magnetic resonance imaging (MRI). To investigate severity of extension injuries using a modified classification system for soft tissue injury by MRI, and to determine the possibility of predicting cord injury by determining the severity of soft tissue injury. It is difficult to diagnose extension injuries by plain radiography and computed tomography. MRI is considered to be the best method of diagnosing soft tissue injuries. The authors examined whether an MRI based diagnostic standard could be devised for extension injuries of the cervical spine. MRI was performed before surgery in 81 patients that had experienced a distractive-extension injury during the past 5 years. Severities of soft tissue injury were subdivided into 5 stages. The retropharyngeal space and the retrotracheal space were measured, and their correlations with the severity of soft tissue injury were examined, as was the relation between canal stenosis and cord injury. Cord injury developed in injuries greater than Grade III (according to our devised system) accompanied by posterior longitudinal ligament rupture (P < 0.01). As the severity of soft tissue injury increased, the cord signal change increased (P < 0.01), the retropharyngeal space and the retrotracheal space increased, and swelling severity in each stage were statistically significant (P < 0.01). In canal stenosis patients, soft tissue damage and cord injury were not found to be associated (P = 0.45). In cases of distractive-extension injury, levels of soft tissue injury were determined accurately by MRI. Moreover, the severity of soft tissue injury was found to be closely associated with the development of cord injury.

Evaluation of the dermal carcinogenicity of lubricant base oils by the mouse skin painting bioassay and other proposed methods.

PubMed

Chasey, K L; McKee, R H

1993-01-01

Lubricant base oils are petroleum products that are predominantly derived from the vacuum distillation of crude oil. Various types of refinement can be employed during the manufacturing process, and evidence suggests that certain of the associated process streams produce skin cancer. Polycyclic aromatic compounds (PACs), some of which are considered as the causative agents, are removed, concentrated or chemically converted during the refinement process. In order to understand the effects of various types of refinement processes on carcinogenic potential, 94 oils were evaluated in the mouse epidermal cancer bioassay. This Exxon database is unique, because of the wide range of crude oils and processing histories represented. Seven processing history classifications are described, and conclusions concerning the impacts of each refinement process on dermal carcinogenicity are discussed. This research also included an evaluation of selected biological and chemical test methods for predicting carcinogenic potential. These included a modified version of the Ames test for mutagenicity, as well as analytical characterizations of the polycyclic aromatic structures in the oils. For classification purposes, a sample was considered to be carcinogenic if it resulted in the production of two or more tumor-bearing animals (in test groups of either 40 or 50 animals). The modified Ames test was considered to be positive if the mutagenicity index was > or = 2.0, and PAC analyses were similarly designated as positive or negative according to proposed guidelines. All of the alternative test methods showed similar agreement with dermal carcinogenicity bioassay data; concordance values were > or = 80%. However, each test was incorrect in ca. 10%-20% of the cases evaluated.(ABSTRACT TRUNCATED AT 250 WORDS)

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.

Measuring healthy behaviours using the stages of change model: an investigation into the physical activity and nutrition behaviours of Australian miners.

PubMed

Lacey, Sarah J; Street, Tamara D

2017-01-01

Obesity is one of the fastest growing modern day epidemics affecting preventable disease and premature deaths. Healthy lifestyle behaviours, such as physical activity and nutritional consumption, have been shown to reduce the likelihood of obesity and obesity related health risks. Originally designed for measurement of unhealthy behaviours, the Stages of Change model, describes 'precontemplators' as individuals who engage in the unhealthy behaviour, are unaware that their behaviour is problematic, and are resistant to change. The aim of this study was to refine and assess the measures of the Stages of Change model in order to achieve a concise and reliable classification of precontemplators, in the context of healthy behaviours. Eight hundred and ninety-seven employees participated in a health survey measuring current health behaviours and stage of change. This study compared a traditional precontemplation measure to a modified version in the assessment of two healthy behaviours: physical activity and fruit and vegetable consumption. The modified measure was more accurate and captured fewer individuals currently meeting the guideline for both physical activity and nutrition, compared to the traditional measure of stages of change. However, across all stages of change, the measure incorrectly classified some employees with regards to meeting health guidelines. When applied to healthy behaviours, the stages of change measure for precontemplation should be further refined to reflect knowledge that the behaviour is unhealthy, and apathy to change. Additionally, measures should define health guidelines to increase reliable classification across all stages of change. The findings can be applied to inform the design and implementation of health promotion strategies targeting obesity related lifestyle behaviours in the general population.

Magnetic resonance imaging-based measures predictive of short-term surgical outcome in patients with Chiari malformation Type I: a pilot study.

PubMed

Alperin, Noam; Loftus, James Ryan; Bagci, Ahmet M; Lee, Sang H; Oliu, Carlos J; Shah, Ashish H; Green, Barth A

2017-01-01

OBJECTIVE This study identifies quantitative imaging-based measures in patients with Chiari malformation Type I (CM-I) that are associated with positive outcomes after suboccipital decompression with duraplasty. METHODS Fifteen patients in whom CM-I was newly diagnosed underwent MRI preoperatively and 3 months postoperatively. More than 20 previously described morphological and physiological parameters were derived to assess quantitatively the impact of surgery. Postsurgical clinical outcomes were assessed in 2 ways, based on resolution of the patient's chief complaint and using a modified Chicago Chiari Outcome Scale (CCOS). Statistical analyses were performed to identify measures that were different between the unfavorable- and favorable-outcome cohorts. Multivariate analysis was used to identify the strongest predictors of outcome. RESULTS The strongest physiological parameter predictive of outcome was the preoperative maximal cord displacement in the upper cervical region during the cardiac cycle, which was significantly larger in the favorable-outcome subcohorts for both outcome types (p < 0.05). Several hydrodynamic measures revealed significantly larger preoperative-to-postoperative changes in the favorable-outcome subcohort. Predictor sets for the chief-complaint classification included the cord displacement, percent venous drainage through the jugular veins, and normalized cerebral blood flow with 93.3% accuracy. Maximal cord displacement combined with intracranial volume change predicted outcome based on the modified CCOS classification with similar accuracy. CONCLUSIONS Tested physiological measures were stronger predictors of outcome than the morphological measures in patients with CM-I. Maximal cord displacement and intracranial volume change during the cardiac cycle together with a measure that reflects the cerebral venous drainage pathway emerged as likely predictors of decompression outcome in patients with CM-I.

Discovering the Unknown: Improving Detection of Novel Species and Genera from Short Reads

DOE PAGES

Rosen, Gail L.; Polikar, Robi; Caseiro, Diamantino A.; ...

2011-01-01

High-throughput sequencing technologies enable metagenome profiling, simultaneous sequencing of multiple microbial species present within an environmental sample. Since metagenomic data includes sequence fragments (“reads”) from organisms that are absent from any database, new algorithms must be developed for the identification and annotation of novel sequence fragments. Homology-based techniques have been modified to detect novel species and genera, but, composition-based methods, have not been adapted. We develop a detection technique that can discriminate between “known” and “unknown” taxa, which can be used with composition-based methods, as well as a hybrid method. Unlike previous studies, we rigorously evaluate all algorithms for theirmore » ability to detect novel taxa. First, we show that the integration of a detector with a composition-based method performs significantly better than homology-based methods for the detection of novel species and genera, with best performance at finer taxonomic resolutions. Most importantly, we evaluate all the algorithms by introducing an “unknown” class and show that the modified version of PhymmBL has similar or better overall classification performance than the other modified algorithms, especially for the species-level and ultrashort reads. Finally, we evaluate theperformance of several algorithms on a real acid mine drainage dataset.« less

Impact of improved soil climatology and intialization on WRF-chem dust simulations over West Asia

NASA Astrophysics Data System (ADS)

Omid Nabavi, Seyed; Haimberger, Leopold; Samimi, Cyrus

2016-04-01

Meteorological forecast models such as WRF-chem are designed to forecast not only standard atmospheric parameters but also aerosol, particularly mineral dust concentrations. It has therefore become an important tool for the prediction of dust storms in West Asia where dust storms have the considerable impact on living conditions. However, verification of forecasts against satellite data indicates only moderate skill in prediction of such events. Earlier studies have already indicated that the erosion factor, land use classification, soil moisture, and temperature initializations play a critical role in the accuracy of WRF-chem dust simulations. In the standard setting the erosion factor and land use classification are based on topographic variations and post-processed images of the advanced very high-resolution radiometer (AVHRR) during the period April 1992-March 1993. Furthermore, WRF-chem is normally initialized by the soil moisture and temperature of Final Analysis (FNL) model on 1.0x1.0 degree grids. In this study, we have changed boundary initial conditions so that they better represent current changing environmental conditions. To do so, land use (only bare soil class) and the erosion factor were both modified using information from MODIS deep blue AOD (Aerosol Optical Depth). In this method, bare soils are where the relative frequency of dust occurrence (deep blue AOD > 0.5) is more than one-third of a given month. Subsequently, the erosion factor, limited within the bare soil class, is determined by the monthly frequency of dust occurrence ranging from 0.3 to 1. It is worth to mention, that 50 percent of calculated erosion factor is afterward assigned to sand class while silt and clay classes each gain 25 percent of it. Soil moisture and temperature from the Global Land Data Assimilation System (GLDAS) were utilized to provide these initializations in higher resolution of 0.25 degree than in the standard setting. Modified and control simulations were conducted for the summertime of 2008-2012 and verified by satellite data (MODIS deep blue AOD, TOMs Aerosol Index and MISR AOD 550nm) and two well-known modeling systems of atmospheric composition (MACC and DREAM). All comparisons show a significant improvement in WRF-chem dust simulations after implementing the modifications. In comparison to the control run, the modified run bears an average increase of spearman correlation of 17-20 percent points when it is compared with satellite data. Our runs with modified WRF-chem even outperform MACC and DREAM dust simulations for the region.

A comparison of chemoembolization endpoints using angiographic versus transcatheter intraarterial perfusion/MR imaging monitoring.

PubMed

Lewandowski, Robert J; Wang, Dingxin; Gehl, James; Atassi, Bassel; Ryu, Robert K; Sato, Kent; Nemcek, Albert A; Miller, Frank H; Mulcahy, Mary F; Kulik, Laura; Larson, Andrew C; Salem, Riad; Omary, Reed A

2007-10-01

Transcatheter arterial chemoembolization (TACE) is an established treatment for unresectable liver cancer. This study was conducted to test the hypothesis that angiographic endpoints during TACE are measurable and reproducible by comparing subjective angiographic versus objective magnetic resonance (MR) endpoints of TACE. The study included 12 consecutive patients who presented for TACE for surgically unresectable HCC or progressive hepatic metastases despite chemotherapy. All procedures were performed with a dedicated imaging system. Angiographic series before and after TACE were reviewed independently by three board-certified interventional radiologists. A subjective angiographic chemoembolization endpoint (SACE) classification scheme, modified from an established angiographic grading system in the cardiology literature, was designed to assist in reproducibly classifying angiographic endpoints. Reproducibility in SACE classification level was compared among operators, and MR imaging perfusion reduction was compared with SACE levels for each observer. Twelve patients successfully underwent 15 separate TACE sessions. SACE levels ranged from I through IV. There was moderate agreement in SACE classification (kappa = 0.46 +/- 0.12). There was no correlation between SACE level and MR perfusion reduction (r = 0.16 for one operator and 0.02 for the other two). Angiographic endpoints during TACE vary widely, have moderate reproducibility among operators, and do not correlate with functional MR imaging perfusion endpoints. Future research should aim to determine ideal angiographic and functional MR imaging endpoints for TACE according to outcome measures such as imaging response, pathologic response, and survival.

Multivariate analysis of volatile compounds detected by headspace solid-phase microextraction/gas chromatography: A tool for sensory classification of cork stoppers.

PubMed

Prat, Chantal; Besalú, Emili; Bañeras, Lluís; Anticó, Enriqueta

2011-06-15

The volatile fraction of aqueous cork macerates of tainted and non-tainted agglomerate cork stoppers was analysed by headspace solid-phase microextraction (HS-SPME)/gas chromatography. Twenty compounds containing terpenoids, aliphatic alcohols, lignin-related compounds and others were selected and analysed in individual corks. Cork stoppers were previously classified in six different classes according to sensory descriptions including, 2,4,6-trichloroanisole taint and other frequent, non-characteristic odours found in cork. A multivariate analysis of the chromatographic data of 20 selected chemical compounds using linear discriminant analysis models helped in the differentiation of the a priori made groups. The discriminant model selected five compounds as the best combination. Selected compounds appear in the model in the following order; 2,4,6 TCA, fenchyl alcohol, 1-octen-3-ol, benzyl alcohol and benzothiazole. Unfortunately, not all six a priori differentiated sensory classes were clearly discriminated in the model, probably indicating that no measurable differences exist in the chromatographic data for some categories. The predictive analyses of a refined model in which two sensory classes were fused together resulted in a good classification. Prediction rates of control (non-tainted), TCA, musty-earthy-vegetative, vegetative and chemical descriptions were 100%, 100%, 85%, 67.3% and 100%, respectively, when the modified model was used. The multivariate analysis of chromatographic data will help in the classification of stoppers and provide a perfect complement to sensory analyses. Copyright © 2010 Elsevier Ltd. All rights reserved.

Gait dynamics to optimize fall risk assessment in geriatric patients admitted to an outpatient diagnostic clinic

PubMed Central

de Groot, Maartje H.; van Campen, Jos P.; Beijnen, Jos H.; Hortobágyi, Tibor; Vuillerme, Nicolas; Lamoth, Claudine C. J.

2017-01-01

Fall prediction in geriatric patients remains challenging because the increased fall risk involves multiple, interrelated factors caused by natural aging and/or pathology. Therefore, we used a multi-factorial statistical approach to model categories of modifiable fall risk factors among geriatric patients to identify fallers with highest sensitivity and specificity with a focus on gait performance. Patients (n = 61, age = 79; 41% fallers) underwent extensive screening in three categories: (1) patient characteristics (e.g., handgrip strength, medication use, osteoporosis-related factors) (2) cognitive function (global cognition, memory, executive function), and (3) gait performance (speed-related and dynamic outcomes assessed by tri-axial trunk accelerometry). Falls were registered prospectively (mean follow-up 8.6 months) and one year retrospectively. Principal Component Analysis (PCA) on 11 gait variables was performed to determine underlying gait properties. Three fall-classification models were then built using Partial Least Squares–Discriminant Analysis (PLS-DA), with separate and combined analyses of the fall risk factors. PCA identified ‘pace’, ‘variability’, and ‘coordination’ as key properties of gait. The best PLS-DA model produced a fall classification accuracy of AUC = 0.93. The specificity of the model using patient characteristics was 60% but reached 80% when cognitive and gait outcomes were added. The inclusion of cognition and gait dynamics in fall classification models reduced misclassification. We therefore recommend assessing geriatric patients’ fall risk using a multi-factorial approach that incorporates patient characteristics, cognition, and gait dynamics. PMID:28575126

Gait dynamics to optimize fall risk assessment in geriatric patients admitted to an outpatient diagnostic clinic.

PubMed

Kikkert, Lisette H J; de Groot, Maartje H; van Campen, Jos P; Beijnen, Jos H; Hortobágyi, Tibor; Vuillerme, Nicolas; Lamoth, Claudine C J

2017-01-01

Fall prediction in geriatric patients remains challenging because the increased fall risk involves multiple, interrelated factors caused by natural aging and/or pathology. Therefore, we used a multi-factorial statistical approach to model categories of modifiable fall risk factors among geriatric patients to identify fallers with highest sensitivity and specificity with a focus on gait performance. Patients (n = 61, age = 79; 41% fallers) underwent extensive screening in three categories: (1) patient characteristics (e.g., handgrip strength, medication use, osteoporosis-related factors) (2) cognitive function (global cognition, memory, executive function), and (3) gait performance (speed-related and dynamic outcomes assessed by tri-axial trunk accelerometry). Falls were registered prospectively (mean follow-up 8.6 months) and one year retrospectively. Principal Component Analysis (PCA) on 11 gait variables was performed to determine underlying gait properties. Three fall-classification models were then built using Partial Least Squares-Discriminant Analysis (PLS-DA), with separate and combined analyses of the fall risk factors. PCA identified 'pace', 'variability', and 'coordination' as key properties of gait. The best PLS-DA model produced a fall classification accuracy of AUC = 0.93. The specificity of the model using patient characteristics was 60% but reached 80% when cognitive and gait outcomes were added. The inclusion of cognition and gait dynamics in fall classification models reduced misclassification. We therefore recommend assessing geriatric patients' fall risk using a multi-factorial approach that incorporates patient characteristics, cognition, and gait dynamics.

Effect of nutritional status on Tuberculin skin testing.

PubMed

Piñeiro, Roi; Cilleruelo, María José; García-Hortelano, Milagros; García-Ascaso, Marta; Medina-Claros, Antonio; Mellado, María José

2013-04-01

To evaluate Tuberculin skin test (TST) results in a population of immigrants and internationally adopted children from several geographical areas; to analyze whether nutritional status can modify TST results. This cross-sectional observational study included adopted children and immigrants evaluated in the authors' unit between January 2003 and December 2008. Children diagnosed with tuberculosis, or vaccinated with live attenuated virus 2 mo earlier, HIV-infected, chronically ill or under treatment with immunosuppressive agents were excluded. TST was considered as dependent variable. Independent variables were gender, age, geographical origin, BCG scar, nutritional status, immune status and intestinal parasitism. One thousand seventy four children were included; 69.6 % were girls. There was a BCG scar in 79 % of children. Mantoux = 0 mm was found in 84.4 %, <10 mm in 4.1 %, and ≥10 mm in 11.4 % of children. Nutrition (McLaren's classification) was normal (≥90 %) in 26.7 % of the subjects, with mild malnutrition (80-89 %) in 36 %, moderate (70-79 %) in 23.2 % and severe (≤69 %) in 14.1 %. There was no difference in TST results among different nutritional status children. The nutritional status, measured by McLaren's classification, does not changes the results of TST. McLaren's classification only grades protein-caloric malnutrition, so in authors' experience this type of malnutrition does not interfere with TST results. Implementing other nutritional parameters could help to determine whether nutritional status should be taken into account when interpreting TST results.

Predicting clinical diagnosis in Huntington's disease: An imaging polymarker

PubMed Central

Daws, Richard E.; Soreq, Eyal; Johnson, Eileanoir B.; Scahill, Rachael I.; Tabrizi, Sarah J.; Barker, Roger A.; Hampshire, Adam

2018-01-01

Objective Huntington's disease (HD) gene carriers can be identified before clinical diagnosis; however, statistical models for predicting when overt motor symptoms will manifest are too imprecise to be useful at the level of the individual. Perfecting this prediction is integral to the search for disease modifying therapies. This study aimed to identify an imaging marker capable of reliably predicting real‐life clinical diagnosis in HD. Method A multivariate machine learning approach was applied to resting‐state and structural magnetic resonance imaging scans from 19 premanifest HD gene carriers (preHD, 8 of whom developed clinical disease in the 5 years postscanning) and 21 healthy controls. A classification model was developed using cross‐group comparisons between preHD and controls, and within the preHD group in relation to “estimated” and “actual” proximity to disease onset. Imaging measures were modeled individually, and combined, and permutation modeling robustly tested classification accuracy. Results Classification performance for preHDs versus controls was greatest when all measures were combined. The resulting polymarker predicted converters with high accuracy, including those who were not expected to manifest in that time scale based on the currently adopted statistical models. Interpretation We propose that a holistic multivariate machine learning treatment of brain abnormalities in the premanifest phase can be used to accurately identify those patients within 5 years of developing motor features of HD, with implications for prognostication and preclinical trials. Ann Neurol 2018;83:532–543 PMID:29405351