Knowledge discovery with classification rules in a cardiovascular dataset.

PubMed

Podgorelec, Vili; Kokol, Peter; Stiglic, Milojka Molan; Hericko, Marjan; Rozman, Ivan

2005-12-01

In this paper we study an evolutionary machine learning approach to data mining and knowledge discovery based on the induction of classification rules. A method for automatic rules induction called AREX using evolutionary induction of decision trees and automatic programming is introduced. The proposed algorithm is applied to a cardiovascular dataset consisting of different groups of attributes which should possibly reveal the presence of some specific cardiovascular problems in young patients. A case study is presented that shows the use of AREX for the classification of patients and for discovering possible new medical knowledge from the dataset. The defined knowledge discovery loop comprises a medical expert's assessment of induced rules to drive the evolution of rule sets towards more appropriate solutions. The final result is the discovery of a possible new medical knowledge in the field of pediatric cardiology.

Learning temporal rules to forecast instability in continuously monitored patients.

PubMed

Guillame-Bert, Mathieu; Dubrawski, Artur; Wang, Donghan; Hravnak, Marilyn; Clermont, Gilles; Pinsky, Michael R

2017-01-01

Inductive machine learning, and in particular extraction of association rules from data, has been successfully used in multiple application domains, such as market basket analysis, disease prognosis, fraud detection, and protein sequencing. The appeal of rule extraction techniques stems from their ability to handle intricate problems yet produce models based on rules that can be comprehended by humans, and are therefore more transparent. Human comprehension is a factor that may improve adoption and use of data-driven decision support systems clinically via face validity. In this work, we explore whether we can reliably and informatively forecast cardiorespiratory instability (CRI) in step-down unit (SDU) patients utilizing data from continuous monitoring of physiologic vital sign (VS) measurements. We use a temporal association rule extraction technique in conjunction with a rule fusion protocol to learn how to forecast CRI in continuously monitored patients. We detail our approach and present and discuss encouraging empirical results obtained using continuous multivariate VS data from the bedside monitors of 297 SDU patients spanning 29 346 hours (3.35 patient-years) of observation. We present example rules that have been learned from data to illustrate potential benefits of comprehensibility of the extracted models, and we analyze the empirical utility of each VS as a potential leading indicator of an impending CRI event. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Applications of Machine Learning and Rule Induction,

DTIC Science & Technology

1995-02-15

An important area of application for machine learning is in automating the acquisition of knowledge bases required for expert systems. In this paper...we review the major paradigms for machine learning , including neural networks, instance-based methods, genetic learning, rule induction, and analytic

Airway emergencies presenting to the paediatric emergency department requiring advanced management techniques.

PubMed

Simma, Leopold; Cincotta, Domenic; Sabato, Stefan; Long, Elliot

2017-09-01

Airway emergencies presenting to the emergency department (ED) are usually managed with conventional equipment and techniques. The patient group managed urgently in the operating room (OR) has not been described. This study aims to describe a case series of children presenting to the ED with airway emergencies managed urgently in the OR, particularly the anaesthetic equipment and techniques used and airway findings. A retrospective cohort study undertaken at The Royal Children's Hospital, Melbourne, Australia. All patients presenting to the ED between 1 January 2012 and 30 July 2015 (42 months) with an airway emergency who were subsequently managed in the OR were included. Patient characteristics, anaesthetic equipment and technique and airway findings were recorded. Twenty-two airway emergencies in 21 patients were included over the study period, on average one every 2 months. Median age was 18 months and 43% were male. Inhalational induction was used in 77.3%, combined inhalational and intravenous induction in 9.1%, and intravenous induction alone in 13.6%. The most commonly used inhalational induction agent was sevoflurane, and the most commonly used intravenous induction agents were ketamine and propofol. Ten airway emergencies did not require intubation, seven for removal of inhaled foreign body, two with progressive tracheal stenosis requiring emergent dilatation and one examination under anaesthesia to rule out inhaled foreign body. Of the 12 airway emergencies that required immediate intubation, direct laryngoscopy was used in 9 and fibre-optic intubating bronchoscopy in 3. For intubations performed by direct laryngoscopy, one was difficult (Cormack and Lehane grade 3). First pass success was 83.3%. Adverse events occurred in 3/22 (13.6%) cases. Advanced airway techniques, including inhalational induction and intubation via fibre-optic intubating bronchoscope, are rarely but predictably required in the management of patients presenting to the ED. Institutions caring for children should prepare in advance where such patients should be managed, by whom, and provide equipment and training for their care. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Automated rule-base creation via CLIPS-Induce

NASA Technical Reports Server (NTRS)

Murphy, Patrick M.

1994-01-01

Many CLIPS rule-bases contain one or more rule groups that perform classification. In this paper we describe CLIPS-Induce, an automated system for the creation of a CLIPS classification rule-base from a set of test cases. CLIPS-Induce consists of two components, a decision tree induction component and a CLIPS production extraction component. ID3, a popular decision tree induction algorithm, is used to induce a decision tree from the test cases. CLIPS production extraction is accomplished through a top-down traversal of the decision tree. Nodes of the tree are used to construct query rules, and branches of the tree are used to construct classification rules. The learned CLIPS productions may easily be incorporated into a large CLIPS system that perform tasks such as accessing a database or displaying information.

Multistrategy learning: A case study

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

Domingos, P.

1996-12-31

Two of the most popular approaches to induction are instance-based learning (IBL) and rule generation. Their strengths and weaknesses are largely complementary. IBL methods are able to identify small details in the instance space, but have trouble with attributes that are relevant in some parts of the space but not others. Conversely, rule induction methods may overlook small exception regions, but are able to select different attributes in different parts of the instance space. The two methods have been unified in the RISE algorithm. RISE views instances as maximally specific rules, forms more general rules by gradually clustering instances ofmore » the same class, and classifies a test example by letting the nearest rule win. This approach potentially combines the advantages of rule induction and IBL, and has indeed been observed to be more accurate than each on a large number of bench-mark datasets. However, it is important to determine if this performance is indeed due to the hypothesized advantages, and to define the situations in which RISE`s bias will and will not be preferable to those of the individual approaches. This abstract reports experiments to this end in artificial domains.« less

Cross-Validation of Survival Bump Hunting by Recursive Peeling Methods.

PubMed

Dazard, Jean-Eudes; Choe, Michael; LeBlanc, Michael; Rao, J Sunil

2014-08-01

We introduce a survival/risk bump hunting framework to build a bump hunting model with a possibly censored time-to-event type of response and to validate model estimates. First, we describe the use of adequate survival peeling criteria to build a survival/risk bump hunting model based on recursive peeling methods. Our method called "Patient Recursive Survival Peeling" is a rule-induction method that makes use of specific peeling criteria such as hazard ratio or log-rank statistics. Second, to validate our model estimates and improve survival prediction accuracy, we describe a resampling-based validation technique specifically designed for the joint task of decision rule making by recursive peeling (i.e. decision-box) and survival estimation. This alternative technique, called "combined" cross-validation is done by combining test samples over the cross-validation loops, a design allowing for bump hunting by recursive peeling in a survival setting. We provide empirical results showing the importance of cross-validation and replication.

Cross-Validation of Survival Bump Hunting by Recursive Peeling Methods

PubMed Central

Dazard, Jean-Eudes; Choe, Michael; LeBlanc, Michael; Rao, J. Sunil

2015-01-01

We introduce a survival/risk bump hunting framework to build a bump hunting model with a possibly censored time-to-event type of response and to validate model estimates. First, we describe the use of adequate survival peeling criteria to build a survival/risk bump hunting model based on recursive peeling methods. Our method called “Patient Recursive Survival Peeling” is a rule-induction method that makes use of specific peeling criteria such as hazard ratio or log-rank statistics. Second, to validate our model estimates and improve survival prediction accuracy, we describe a resampling-based validation technique specifically designed for the joint task of decision rule making by recursive peeling (i.e. decision-box) and survival estimation. This alternative technique, called “combined” cross-validation is done by combining test samples over the cross-validation loops, a design allowing for bump hunting by recursive peeling in a survival setting. We provide empirical results showing the importance of cross-validation and replication. PMID:26997922

Empirical Analysis and Refinement of Expert System Knowledge Bases

DTIC Science & Technology

1990-03-31

the number of hidden units and the error rates is listed in Figure 6. 3.3. Cancer Data A data qet for eva!ukting th.- Frognosis of breast cancer ...Alternative Rule Induction Methods A data set for evaluating the prognosis of breast cancer recurrence was analyzed by Michalski’s AQI5 rule induction program...AQ15 7 2 32% PVM 2 1 23% Figure 6-3: Comparative Summa-y for AQI5 and PVM on Breast Cancer Data 6.2.2. Alternative Decision Tree Induction Methods

Automated identification of protein-ligand interaction features using Inductive Logic Programming: a hexose binding case study.

PubMed

A Santos, Jose C; Nassif, Houssam; Page, David; Muggleton, Stephen H; E Sternberg, Michael J

2012-07-11

There is a need for automated methods to learn general features of the interactions of a ligand class with its diverse set of protein receptors. An appropriate machine learning approach is Inductive Logic Programming (ILP), which automatically generates comprehensible rules in addition to prediction. The development of ILP systems which can learn rules of the complexity required for studies on protein structure remains a challenge. In this work we use a new ILP system, ProGolem, and demonstrate its performance on learning features of hexose-protein interactions. The rules induced by ProGolem detect interactions mediated by aromatics and by planar-polar residues, in addition to less common features such as the aromatic sandwich. The rules also reveal a previously unreported dependency for residues cys and leu. They also specify interactions involving aromatic and hydrogen bonding residues. This paper shows that Inductive Logic Programming implemented in ProGolem can derive rules giving structural features of protein/ligand interactions. Several of these rules are consistent with descriptions in the literature. In addition to confirming literature results, ProGolem's model has a 10-fold cross-validated predictive accuracy that is superior, at the 95% confidence level, to another ILP system previously used to study protein/hexose interactions and is comparable with state-of-the-art statistical learners.

Standard Practices for Usage of Inductive Magnetic Field Probes with Application to Electric Propulsion Testing

NASA Technical Reports Server (NTRS)

Polzin, Kurt A.; Hill, Carrie S.; Turchi, Peter J.; Burton, Rodney L.; Messer, Sarah; Lovberg, Ralph H.; Hallock, Ashley K.

2013-01-01

Inductive magnetic field probes (also known as B-dot probes and sometimes as B-probes or magnetic probes) are often employed to perform field measurements in electric propulsion applications where there are time-varying fields. Magnetic field probes provide the means to measure these magnetic fields and can even be used to measure the plasma current density indirectly through the application of Ampere's law. Measurements of this type can yield either global information related to a thruster and its performance or detailed, local data related to the specific physical processes occurring in the plasma. Results of the development of a standard for B-dot probe measurements are presented, condensing the available literature on the subject into an accessible set of rules, guidelines, and techniques to standardize the performance and presentation of future measurements.

Discovering rules for protein-ligand specificity using support vector inductive logic programming.

PubMed

Kelley, Lawrence A; Shrimpton, Paul J; Muggleton, Stephen H; Sternberg, Michael J E

2009-09-01

Structural genomics initiatives are rapidly generating vast numbers of protein structures. Comparative modelling is also capable of producing accurate structural models for many protein sequences. However, for many of the known structures, functions are not yet determined, and in many modelling tasks, an accurate structural model does not necessarily tell us about function. Thus, there is a pressing need for high-throughput methods for determining function from structure. The spatial arrangement of key amino acids in a folded protein, on the surface or buried in clefts, is often the determinants of its biological function. A central aim of molecular biology is to understand the relationship between such substructures or surfaces and biological function, leading both to function prediction and to function design. We present a new general method for discovering the features of binding pockets that confer specificity for particular ligands. Using a recently developed machine-learning technique which couples the rule-discovery approach of inductive logic programming with the statistical learning power of support vector machines, we are able to discriminate, with high precision (90%) and recall (86%) between pockets that bind FAD and those that bind NAD on a large benchmark set given only the geometry and composition of the backbone of the binding pocket without the use of docking. In addition, we learn rules governing this specificity which can feed into protein functional design protocols. An analysis of the rules found suggests that key features of the binding pocket may be tied to conformational freedom in the ligand. The representation is sufficiently general to be applicable to any discriminatory binding problem. All programs and data sets are freely available to non-commercial users at http://www.sbg.bio.ic.ac.uk/svilp_ligand/.

Common and dissociable neural correlates associated with component processes of inductive reasoning.

PubMed

Jia, Xiuqin; Liang, Peipeng; Lu, Jie; Yang, Yanhui; Zhong, Ning; Li, Kuncheng

2011-06-15

The ability to draw numerical inductive reasoning requires two key cognitive processes, identification and extrapolation. This study aimed to identify the neural correlates of both component processes of numerical inductive reasoning using event-related fMRI. Three kinds of tasks: rule induction (RI), rule induction and application (RIA), and perceptual judgment (Jud) were solved by twenty right-handed adults. Our results found that the left superior parietal lobule (SPL) extending into the precuneus and left dorsolateral prefrontal cortex (DLPFC) were commonly recruited in the two components. It was also observed that the fronto-parietal network was more specific to identification, whereas the striatal-thalamic network was more specific to extrapolation. The findings suggest that numerical inductive reasoning is mediated by the coordination of multiple brain areas including the prefrontal, parietal, and subcortical regions, of which some are more specific to demands on only one of these two component processes, whereas others are sensitive to both. Copyright © 2011 Elsevier Inc. All rights reserved.

Induction for Radiology Patients

NASA Astrophysics Data System (ADS)

Yıldırım, Pınar; Tolun, Mehmet R.

This paper represents the implementation of an inductive learning algorithm for patients of Radiology Department in Hacettepe University hospitals to discover the relationship between patient demographics information and time that patients spend during a specific radiology exam. ILA has been used for the implementation which generates rules and the results are evaluated by evaluation metrics. According to generated rules, some patients in different age groups or birthplaces may spend more time for the same radiology exam than the others.

Automated identification of protein-ligand interaction features using Inductive Logic Programming: a hexose binding case study

PubMed Central

2012-01-01

Background There is a need for automated methods to learn general features of the interactions of a ligand class with its diverse set of protein receptors. An appropriate machine learning approach is Inductive Logic Programming (ILP), which automatically generates comprehensible rules in addition to prediction. The development of ILP systems which can learn rules of the complexity required for studies on protein structure remains a challenge. In this work we use a new ILP system, ProGolem, and demonstrate its performance on learning features of hexose-protein interactions. Results The rules induced by ProGolem detect interactions mediated by aromatics and by planar-polar residues, in addition to less common features such as the aromatic sandwich. The rules also reveal a previously unreported dependency for residues cys and leu. They also specify interactions involving aromatic and hydrogen bonding residues. This paper shows that Inductive Logic Programming implemented in ProGolem can derive rules giving structural features of protein/ligand interactions. Several of these rules are consistent with descriptions in the literature. Conclusions In addition to confirming literature results, ProGolem’s model has a 10-fold cross-validated predictive accuracy that is superior, at the 95% confidence level, to another ILP system previously used to study protein/hexose interactions and is comparable with state-of-the-art statistical learners. PMID:22783946

Specific impairments of rule induction in different frontal lobe subgroups.

PubMed

Reverberi, Carlo; Lavaroni, Antonio; Gigli, Gian Luigi; Skrap, Miran; Shallice, Tim

2005-01-01

The neural correlates of inductive reasoning are still poorly understood. In order to explore them, we administered a revised version of the Brixton test, a rule attainment task, to a group of 40 patients with a focal frontal brain lesion of mixed aetiology and to 43 control subjects. To interpret an impairment on the test as suggesting an inductive reasoning deficit a number of alternative hypotheses need first to be considered, namely whether the Brixton impairment could be explained by: (i) a working memory deficit; (ii) a monitoring deficit; (iii) a difficulty in applying an already induced rule; (iv) greater impulsivity. The patients with left lateral (LL) frontal lesions were significantly impaired on the Brixton test; more importantly they were the only group in which none of the alternative hypotheses we explored proved able to explain the flawed performance. In sharp contrast, right lateral lesion patients did not make significantly more errors on the Brixton test than controls, but they produced three times more capture errors (a sign of impaired monitoring processes). The results were interpreted as suggesting functional dissociations between inductive reasoning, monitoring and working memory and a localisation of key processes for induction in left lateral frontal cortex and in right lateral cortex for monitoring and checking.

Comparison of rule induction, decision trees and formal concept analysis approaches for classification

NASA Astrophysics Data System (ADS)

Kotelnikov, E. V.; Milov, V. R.

2018-05-01

Rule-based learning algorithms have higher transparency and easiness to interpret in comparison with neural networks and deep learning algorithms. These properties make it possible to effectively use such algorithms to solve descriptive tasks of data mining. The choice of an algorithm depends also on its ability to solve predictive tasks. The article compares the quality of the solution of the problems with binary and multiclass classification based on the experiments with six datasets from the UCI Machine Learning Repository. The authors investigate three algorithms: Ripper (rule induction), C4.5 (decision trees), In-Close (formal concept analysis). The results of the experiments show that In-Close demonstrates the best quality of classification in comparison with Ripper and C4.5, however the latter two generate more compact rule sets.

Machine learning methods applied on dental fear and behavior management problems in children.

PubMed

Klingberg, G; Sillén, R; Norén, J G

1999-08-01

The etiologies of dental fear and dental behavior management problems in children were investigated in a database of information on 2,257 Swedish children 4-6 and 9-11 years old. The analyses were performed using computerized inductive techniques within the field of artificial intelligence. The database held information regarding dental fear levels and behavior management problems, which were defined as outcomes, i.e. dependent variables. The attributes, i.e. independent variables, included data on dental health and dental treatments, information about parental dental fear, general anxiety, socioeconomic variables, etc. The data contained both numerical and discrete variables. The analyses were performed using an inductive analysis program (XpertRule Analyser, Attar Software Ltd, Lancashire, UK) that presents the results in a hierarchic diagram called a knowledge tree. The importance of the different attributes is represented by their position in this diagram. The results show that inductive methods are well suited for analyzing multifactorial and complex relationships in large data sets, and are thus a useful complement to multivariate statistical techniques. The knowledge trees for the two outcomes, dental fear and behavior management problems, were very different from each other, suggesting that the two phenomena are not equivalent. Dental fear was found to be more related to non-dental variables, whereas dental behavior management problems seemed connected to dental variables.

The discovery of indicator variables for QSAR using inductive logic programming

NASA Astrophysics Data System (ADS)

King, Ross D.; Srinivasan, Ashwin

1997-11-01

A central problem in forming accurate regression equations in QSAR studies isthe selection of appropriate descriptors for the compounds under study. Wedescribe a novel procedure for using inductive logic programming (ILP) todiscover new indicator variables (attributes) for QSAR problems, and show thatthese improve the accuracy of the derived regression equations. ILP techniqueshave previously been shown to work well on drug design problems where thereis a large structural component or where clear comprehensible rules arerequired. However, ILP techniques have had the disadvantage of only being ableto make qualitative predictions (e.g. active, inactive) and not to predictreal numbers (regression). We unify ILP and linear regression techniques togive a QSAR method that has the strength of ILP at describing stericstructure, with the familiarity and power of linear regression. We evaluatedthe utility of this new QSAR technique by examining the prediction ofbiological activity with and without the addition of new structural indicatorvariables formed by ILP. In three out of five datasets examined the additionof ILP variables produced statistically better results (P < 0.01) over theoriginal description. The new ILP variables did not increase the overallcomplexity of the derived QSAR equations and added insight into possiblemechanisms of action. We conclude that ILP can aid in the process of drugdesign.

A neural model of rule generation in inductive reasoning.

PubMed

Rasmussen, Daniel; Eliasmith, Chris

2011-01-01

Inductive reasoning is a fundamental and complex aspect of human intelligence. In particular, how do subjects, given a set of particular examples, generate general descriptions of the rules governing that set? We present a biologically plausible method for accomplishing this task and implement it in a spiking neuron model. We demonstrate the success of this model by applying it to the problem domain of Raven's Progressive Matrices, a widely used tool in the field of intelligence testing. The model is able to generate the rules necessary to correctly solve Raven's items, as well as recreate many of the experimental effects observed in human subjects. Copyright © 2011 Cognitive Science Society, Inc.

Online Pedagogical Tutorial Tactics Optimization Using Genetic-Based Reinforcement Learning

PubMed Central

Lin, Hsuan-Ta; Lee, Po-Ming; Hsiao, Tzu-Chien

2015-01-01

Tutorial tactics are policies for an Intelligent Tutoring System (ITS) to decide the next action when there are multiple actions available. Recent research has demonstrated that when the learning contents were controlled so as to be the same, different tutorial tactics would make difference in students' learning gains. However, the Reinforcement Learning (RL) techniques that were used in previous studies to induce tutorial tactics are insufficient when encountering large problems and hence were used in offline manners. Therefore, we introduced a Genetic-Based Reinforcement Learning (GBML) approach to induce tutorial tactics in an online-learning manner without basing on any preexisting dataset. The introduced method can learn a set of rules from the environment in a manner similar to RL. It includes a genetic-based optimizer for rule discovery task by generating new rules from the old ones. This increases the scalability of a RL learner for larger problems. The results support our hypothesis about the capability of the GBML method to induce tutorial tactics. This suggests that the GBML method should be favorable in developing real-world ITS applications in the domain of tutorial tactics induction. PMID:26065018

Online Pedagogical Tutorial Tactics Optimization Using Genetic-Based Reinforcement Learning.

PubMed

Lin, Hsuan-Ta; Lee, Po-Ming; Hsiao, Tzu-Chien

2015-01-01

Tutorial tactics are policies for an Intelligent Tutoring System (ITS) to decide the next action when there are multiple actions available. Recent research has demonstrated that when the learning contents were controlled so as to be the same, different tutorial tactics would make difference in students' learning gains. However, the Reinforcement Learning (RL) techniques that were used in previous studies to induce tutorial tactics are insufficient when encountering large problems and hence were used in offline manners. Therefore, we introduced a Genetic-Based Reinforcement Learning (GBML) approach to induce tutorial tactics in an online-learning manner without basing on any preexisting dataset. The introduced method can learn a set of rules from the environment in a manner similar to RL. It includes a genetic-based optimizer for rule discovery task by generating new rules from the old ones. This increases the scalability of a RL learner for larger problems. The results support our hypothesis about the capability of the GBML method to induce tutorial tactics. This suggests that the GBML method should be favorable in developing real-world ITS applications in the domain of tutorial tactics induction.

Radiation and Electromagnetic Induction Data Fusion for Detection of Buried Radioactive Metal Waste - 12282

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

Long, Zhiling; Wei, Wei; Turlapaty, Anish

2012-07-01

At the United States Army's test sites, fired penetrators made of Depleted Uranium (DU) have been buried under ground and become hazardous waste. Previously, we developed techniques for detecting buried radioactive targets. We also developed approaches for locating buried paramagnetic metal objects by utilizing the electromagnetic induction (EMI) sensor data. In this paper, we apply data fusion techniques to combine results from both the radiation detection and the EMI detection, so that we can further distinguish among DU penetrators, DU oxide, and non- DU metal debris. We develop a two-step fusion approach for the task, and test it with surveymore » data collected on simulation targets. In this work, we explored radiation and EMI data fusion for detecting DU, oxides, and non-DU metals. We developed a two-step fusion approach based on majority voting and a set of decision rules. With this approach, we fuse results from radiation detection based on the RX algorithm and EMI detection based on a 3-step analysis. Our fusion approach has been tested successfully with data collected on simulation targets. In the future, we will need to further verify the effectiveness of this fusion approach with field data. (authors)« less

Incremental Learning of Context Free Grammars by Parsing-Based Rule Generation and Rule Set Search

NASA Astrophysics Data System (ADS)

Nakamura, Katsuhiko; Hoshina, Akemi

This paper discusses recent improvements and extensions in Synapse system for inductive inference of context free grammars (CFGs) from sample strings. Synapse uses incremental learning, rule generation based on bottom-up parsing, and the search for rule sets. The form of production rules in the previous system is extended from Revised Chomsky Normal Form A→βγ to Extended Chomsky Normal Form, which also includes A→B, where each of β and γ is either a terminal or nonterminal symbol. From the result of bottom-up parsing, a rule generation mechanism synthesizes minimum production rules required for parsing positive samples. Instead of inductive CYK algorithm in the previous version of Synapse, the improved version uses a novel rule generation method, called ``bridging,'' which bridges the lacked part of the derivation tree for the positive string. The improved version also employs a novel search strategy, called serial search in addition to minimum rule set search. The synthesis of grammars by the serial search is faster than the minimum set search in most cases. On the other hand, the size of the generated CFGs is generally larger than that by the minimum set search, and the system can find no appropriate grammar for some CFL by the serial search. The paper shows experimental results of incremental learning of several fundamental CFGs and compares the methods of rule generation and search strategies.

An integrated method for cancer classification and rule extraction from microarray data

PubMed Central

Huang, Liang-Tsung

2009-01-01

Different microarray techniques recently have been successfully used to investigate useful information for cancer diagnosis at the gene expression level due to their ability to measure thousands of gene expression levels in a massively parallel way. One important issue is to improve classification performance of microarray data. However, it would be ideal that influential genes and even interpretable rules can be explored at the same time to offer biological insight. Introducing the concepts of system design in software engineering, this paper has presented an integrated and effective method (named X-AI) for accurate cancer classification and the acquisition of knowledge from DNA microarray data. This method included a feature selector to systematically extract the relative important genes so as to reduce the dimension and retain as much as possible of the class discriminatory information. Next, diagonal quadratic discriminant analysis (DQDA) was combined to classify tumors, and generalized rule induction (GRI) was integrated to establish association rules which can give an understanding of the relationships between cancer classes and related genes. Two non-redundant datasets of acute leukemia were used to validate the proposed X-AI, showing significantly high accuracy for discriminating different classes. On the other hand, I have presented the abilities of X-AI to extract relevant genes, as well as to develop interpretable rules. Further, a web server has been established for cancer classification and it is freely available at . PMID:19272192

Evidence of a Transition from Perceptual to Category Induction in 3- to 9-Year-Old Children

ERIC Educational Resources Information Center

Badger, Julia R.; Shapiro, Laura R.

2012-01-01

We examined whether inductive reasoning development is better characterized by accounts assuming an early category bias versus an early perceptual bias. We trained 264 children aged 3 to 9 years to categorize novel insects using a rule that directly pitted category membership against appearance. This was followed by an induction task with…

The interaction of process and domain in prefrontal cortex during inductive reasoning

PubMed Central

Babcock, Laura; Vallesi, Antonino

2015-01-01

Inductive reasoning is an everyday process that allows us to make sense of the world by creating rules from a series of instances. Consistent with accounts of process-based fractionations of the prefrontal cortex (PFC) along the left–right axis, inductive reasoning has been reliably localized to left PFC. However, these results may be confounded by the task domain, which is typically verbal. Indeed, some studies show that right PFC activation is seen with spatial tasks. This study used fMRI to examine the effects of process and domain on the brain regions recruited during a novel pattern discovery task. Twenty healthy young adult participants were asked to discover the rule underlying the presentation of a series of letters in varied spatial locations. The rules were either verbal (pertaining to a single semantic category) or spatial (geometric figures). Bilateral ventrolateral PFC activations were seen for the spatial domain, while the verbal domain showed only left ventrolateral PFC. A conjunction analysis revealed that the two domains recruited a common region of left ventrolateral PFC. The data support a central role of left PFC in inductive reasoning. Importantly, they also suggest that both process and domain shape the localization of reasoning in the brain. PMID:25498406

The interaction of process and domain in prefrontal cortex during inductive reasoning.

PubMed

Babcock, Laura; Vallesi, Antonino

2015-01-01

Inductive reasoning is an everyday process that allows us to make sense of the world by creating rules from a series of instances. Consistent with accounts of process-based fractionations of the prefrontal cortex (PFC) along the left-right axis, inductive reasoning has been reliably localized to left PFC. However, these results may be confounded by the task domain, which is typically verbal. Indeed, some studies show that right PFC activation is seen with spatial tasks. This study used fMRI to examine the effects of process and domain on the brain regions recruited during a novel pattern discovery task. Twenty healthy young adult participants were asked to discover the rule underlying the presentation of a series of letters in varied spatial locations. The rules were either verbal (pertaining to a single semantic category) or spatial (geometric figures). Bilateral ventrolateral PFC activations were seen for the spatial domain, while the verbal domain showed only left ventrolateral PFC. A conjunction analysis revealed that the two domains recruited a common region of left ventrolateral PFC. The data support a central role of left PFC in inductive reasoning. Importantly, they also suggest that both process and domain shape the localization of reasoning in the brain. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

Effect of airway clearance techniques on the efficacy of the sputum induction procedure.

PubMed

Elkins, M R; Lane, T; Goldberg, H; Pagliuso, J; Garske, L A; Hector, E; Marchetto, L; Alison, J A; Bye, P T P

2005-11-01

Sputum induction is used in the early identification of tuberculosis (TB) and pneumocystis infections of the lung. Although manual physiotherapy techniques to clear the airways are often incorporated in the sputum induction procedure, their efficacy in this setting is unknown. This randomised, crossover trial enrolled adults referred for sputum induction for suspected TB and pneumocystis infections of the lung. All participants underwent two sputum induction procedures, inhaling 3% saline via ultrasonic nebuliser. During one randomly allocated procedure, airway clearance techniques (chest wall percussion, vibration, huffing) were incorporated. In total, 59 participants completed the trial. The airway clearance techniques had no significant effect on how the test was tolerated, the volume expectorated or the quality of the sample obtained (assessed by the presence of alveolar macrophages). The techniques did not significantly affect how often the test identified a suspected organism, nor the sensitivity or specificity of sputum induction. In conclusion, the study was unable to demonstrate any effect of airway clearance techniques on the sputum induction procedure. The results provide some justification for not including airway clearance techniques as part of the sputum induction procedure.

A general approach for developing system-specific functions to score protein-ligand docked complexes using support vector inductive logic programming.

PubMed

Amini, Ata; Shrimpton, Paul J; Muggleton, Stephen H; Sternberg, Michael J E

2007-12-01

Despite the increased recent use of protein-ligand and protein-protein docking in the drug discovery process due to the increases in computational power, the difficulty of accurately ranking the binding affinities of a series of ligands or a series of proteins docked to a protein receptor remains largely unsolved. This problem is of major concern in lead optimization procedures and has lead to the development of scoring functions tailored to rank the binding affinities of a series of ligands to a specific system. However, such methods can take a long time to develop and their transferability to other systems remains open to question. Here we demonstrate that given a suitable amount of background information a new approach using support vector inductive logic programming (SVILP) can be used to produce system-specific scoring functions. Inductive logic programming (ILP) learns logic-based rules for a given dataset that can be used to describe properties of each member of the set in a qualitative manner. By combining ILP with support vector machine regression, a quantitative set of rules can be obtained. SVILP has previously been used in a biological context to examine datasets containing a series of singular molecular structures and properties. Here we describe the use of SVILP to produce binding affinity predictions of a series of ligands to a particular protein. We also for the first time examine the applicability of SVILP techniques to datasets consisting of protein-ligand complexes. Our results show that SVILP performs comparably with other state-of-the-art methods on five protein-ligand systems as judged by similar cross-validated squares of their correlation coefficients. A McNemar test comparing SVILP to CoMFA and CoMSIA across the five systems indicates our method to be significantly better on one occasion. The ability to graphically display and understand the SVILP-produced rules is demonstrated and this feature of ILP can be used to derive hypothesis for future ligand design in lead optimization procedures. The approach can readily be extended to evaluate the binding affinities of a series of protein-protein complexes. (c) 2007 Wiley-Liss, Inc.

Children's Acquisition of Conditional Logic Structure: Teachable?

ERIC Educational Resources Information Center

Lee, Seong-Soo

1985-01-01

To assess the teachability of conditional logic structure, the commonly used syllogistic conditional reasoning task was divided into three main components: (1) inductive rule learning; (2) induction of conditional language; and (3) deductive interpretation. When trained on all components, fifth and seventh graders became very competent in dealing…

Discovering H-bonding rules in crystals with inductive logic programming.

PubMed

Ando, Howard Y; Dehaspe, Luc; Luyten, Walter; Van Craenenbroeck, Elke; Vandecasteele, Henk; Van Meervelt, Luc

2006-01-01

In the domain of crystal engineering, various schemes have been proposed for the classification of hydrogen bonding (H-bonding) patterns observed in 3D crystal structures. In this study, the aim is to complement these schemes with rules that predict H-bonding in crystals from 2D structural information only. Modern computational power and the advances in inductive logic programming (ILP) can now provide computational chemistry with the opportunity for extracting structure-specific rules from large databases that can be incorporated into expert systems. ILP technology is here applied to H-bonding in crystals to develop a self-extracting expert system utilizing data in the Cambridge Structural Database of small molecule crystal structures. A clear increase in performance was observed when the ILP system DMax was allowed to refer to the local structural environment of the possible H-bond donor/acceptor pairs. This ability distinguishes ILP from more traditional approaches that build rules on the basis of global molecular properties.

The Interplay of Externalizing Problems and Physical and Inductive Discipline during Childhood

ERIC Educational Resources Information Center

Choe, Daniel Ewon; Olson, Sheryl L.; Sameroff, Arnold J.

2013-01-01

Children who are physically disciplined are at elevated risk for externalizing problems. Conversely, maternal reasoning and reminding of rules, or inductive discipline, is associated with fewer child externalizing problems. Few studies have simultaneously examined bidirectional associations between these forms of discipline and child adjustment…

Expert system and process optimization techniques for real-time monitoring and control of plasma processes

NASA Astrophysics Data System (ADS)

Cheng, Jie; Qian, Zhaogang; Irani, Keki B.; Etemad, Hossein; Elta, Michael E.

1991-03-01

To meet the ever-increasing demand of the rapidly-growing semiconductor manufacturing industry it is critical to have a comprehensive methodology integrating techniques for process optimization real-time monitoring and adaptive process control. To this end we have accomplished an integrated knowledge-based approach combining latest expert system technology machine learning method and traditional statistical process control (SPC) techniques. This knowledge-based approach is advantageous in that it makes it possible for the task of process optimization and adaptive control to be performed consistently and predictably. Furthermore this approach can be used to construct high-level and qualitative description of processes and thus make the process behavior easy to monitor predict and control. Two software packages RIST (Rule Induction and Statistical Testing) and KARSM (Knowledge Acquisition from Response Surface Methodology) have been developed and incorporated with two commercially available packages G2 (real-time expert system) and ULTRAMAX (a tool for sequential process optimization).

Eye Movement Analysis of Information Processing under Different Testing Conditions.

ERIC Educational Resources Information Center

Dillon, Ronna F.

1985-01-01

Undergraduates were given complex figural analogies items, and eye movements were observed under three types of feedback: (1) elaborate feedback; (2) subjects verbalized their thinking and application of rules; and (3) no feedback. Both feedback conditions enhanced the rule-governed information processing during inductive reasoning. (Author/GDC)

On rules of induction and the raven paradox in Bayesian confirmation theory

NASA Astrophysics Data System (ADS)

Afshar, H. M.; Sunehag, P.

2014-12-01

Confirmation theory is studying how one can confirm a universal statement like "All ravens are black". Early authors discussed how one's degree of belief in such a statement should change with new evidence and suggested various rules of induction. Nicod's Condition (NC) says that the claim that all F are G is supported by observing a previously unseen object that is both F and G. Hempel pointed out that NC implies the paradoxical conclusion that observing a white sock supports that all ravens are black. In our time, confirmation is studied by using subjective conditional probability as degrees of belief with Kolmogorov's axioms as the main rules of induction. The old rules and problems of induction are, however, still studied within the probabilistic framework. We consider a setting where the number of individuals having a particular property is given and find that NC can contradict a simpler principle, namely projectability (PJ) which says that if we observe an object with property ψ then other objects are also more likely to have property ψ. We find that intuition can side with either one depending on the situation. We suggest that a more appropriate formalization of the intuition behind NC is the weaker principle of reasoning by analogy (RA). RA says that if we see an object that is F and G and we know that another object is F, then it is more likely to also be G. Projectability might still be considered valid for relatively uninformed a priori beliefs. If one decides that a principle like projectability is valid for confirmation in an uninformed situation, it provides a test that an a priori distribution must satisfy. Hence, decreasing the arbitrariness of the choice of measure. Further, by considering background knowledge saying only how many ravens there are in the world we conclude that if someone accepts the projectability principle, an agent will not increment the belief that all ravens are black when having observed a white sock. Most Bayesian approaches have so far derived a small increment in confirmation by relying on some particular a priori measure. A conclusion rejected by common sense. We here resolve the contradiction by formally identifying the natural background knowledge considered and the inductive rule that the a priori belief should comply with in the situation at hand. The original paradox is dispelled by rejecting NC.

Decoding rule search domain in the left inferior frontal gyrus

PubMed Central

Babcock, Laura; Vallesi, Antonino

2018-01-01

Traditionally, the left hemisphere has been thought to extract mainly verbal patterns of information, but recent evidence has shown that the left Inferior Frontal Gyrus (IFG) is active during inductive reasoning in both the verbal and spatial domains. We aimed to understand whether the left IFG supports inductive reasoning in a domain-specific or domain-general fashion. To do this we used Multi-Voxel Pattern Analysis to decode the representation of domain during a rule search task. Thirteen participants were asked to extract the rule underlying streams of letters presented in different spatial locations. Each rule was either verbal (letters forming words) or spatial (positions forming geometric figures). Our results show that domain was decodable in the left prefrontal cortex, suggesting that this region represents domain-specific information, rather than processes common to the two domains. A replication study with the same participants tested two years later confirmed these findings, though the individual representations changed, providing evidence for the flexible nature of representations. This study extends our knowledge on the neural basis of goal-directed behaviors and on how information relevant for rule extraction is flexibly mapped in the prefrontal cortex. PMID:29547623

On the determinants of the conjunction fallacy: probability versus inductive confirmation.

PubMed

Tentori, Katya; Crupi, Vincenzo; Russo, Selena

2013-02-01

Major recent interpretations of the conjunction fallacy postulate that people assess the probability of a conjunction according to (non-normative) averaging rules as applied to the constituents' probabilities or represent the conjunction fallacy as an effect of random error in the judgment process. In the present contribution, we contrast such accounts with a different reading of the phenomenon based on the notion of inductive confirmation as defined by contemporary Bayesian theorists. Averaging rule hypotheses along with the random error model and many other existing proposals are shown to all imply that conjunction fallacy rates would rise as the perceived probability of the added conjunct does. By contrast, our account predicts that the conjunction fallacy depends on the added conjunct being perceived as inductively confirmed. Four studies are reported in which the judged probability versus confirmation of the added conjunct have been systematically manipulated and dissociated. The results consistently favor a confirmation-theoretic account of the conjunction fallacy against competing views. Our proposal is also discussed in connection with related issues in the study of human inductive reasoning. 2013 APA, all rights reserved

Fault detection and diagnosis of induction motors using motor current signature analysis and a hybrid FMM-CART model.

PubMed

Seera, Manjeevan; Lim, Chee Peng; Ishak, Dahaman; Singh, Harapajan

2012-01-01

In this paper, a novel approach to detect and classify comprehensive fault conditions of induction motors using a hybrid fuzzy min-max (FMM) neural network and classification and regression tree (CART) is proposed. The hybrid model, known as FMM-CART, exploits the advantages of both FMM and CART for undertaking data classification and rule extraction problems. A series of real experiments is conducted, whereby the motor current signature analysis method is applied to form a database comprising stator current signatures under different motor conditions. The signal harmonics from the power spectral density are extracted as discriminative input features for fault detection and classification with FMM-CART. A comprehensive list of induction motor fault conditions, viz., broken rotor bars, unbalanced voltages, stator winding faults, and eccentricity problems, has been successfully classified using FMM-CART with good accuracy rates. The results are comparable, if not better, than those reported in the literature. Useful explanatory rules in the form of a decision tree are also elicited from FMM-CART to analyze and understand different fault conditions of induction motors.

An inductive method for automatic generation of referring physician prefetch rules for PACS.

PubMed

Okura, Yasuhiko; Matsumura, Yasushi; Harauchi, Hajime; Sukenobu, Yoshiharu; Kou, Hiroko; Kohyama, Syunsuke; Yasuda, Norihiro; Yamamoto, Yuichiro; Inamura, Kiyonari

2002-12-01

To prefetch images in a hospital-wide picture archiving and communication system (PACS), a rule must be devised to permit accurate selection of examinations in which a patient's images are stored. We developed an inductive method to compose prefetch rules from practical data which were obtained in a hospital using a decision tree algorithm. Our methods were evaluated on data acquired in Osaka University Hospital for one month. The data collected consisted of 58,617 cases of consultation reservations, 643,797 examination histories of patients, and 323,993 records of image requests in PACS. Four parameters indicating whether the images of the patient were requested or not for each consultation reservation were derived from the database. As a result, the successful selection sensitivity for consultations in which images were requested was approximately 0.8, and the specificity for excluding consultations accurately where images were not requested was approximately 0.7.

Induction Based on Circumscription

NASA Astrophysics Data System (ADS)

Saito, Haruka; Inoue, Katsumi

We investigate induction from the viewpoint of nonmonotonic reasoning. Induction we consider in this paper is descriptive induction. Hypotheses from descriptive induction have the weak property that they only describe rules with respect to the observations and do not realize an inductive leap. In this paper, we define a new form of descriptive induction with circumscription and the idea of explanation and show two procedures for computing it. The new descriptive induction is called circumscriptive induction. By deciding the roles of predicates in circumscription, we can intentionally minimize models of a given inductive problem. By adopting the idea of explanation, we can distinguish between background knowledge and observations. Additionally, we consider the relationship between the way of choosing the roles of predicates in computing circumscription and the property of hypotheses obtained by circumscriptive induction. It is shown that hypotheses from circumscriptive induction reflect a difference between background knowledge and observations and do not realize an inductive leap. We also investigate revision of hypotheses which is as important as generation of hypotheses. In a process of hypothesis revision, a difference between previous induction and circumscriptive induction is clearly characterised.

Bayesian Learning and the Psychology of Rule Induction

ERIC Educational Resources Information Center

Endress, Ansgar D.

2013-01-01

In recent years, Bayesian learning models have been applied to an increasing variety of domains. While such models have been criticized on theoretical grounds, the underlying assumptions and predictions are rarely made concrete and tested experimentally. Here, I use Frank and Tenenbaum's (2011) Bayesian model of rule-learning as a case study to…

Acquisition of Inductive Biconditional Reasoning Skills: Training of Simultaneous and Sequential Processing.

ERIC Educational Resources Information Center

Lee, Seong-Soo

1982-01-01

Tenth-grade students (n=144) received training on one of three processing methods: coding-mapping (simultaneous), coding only, or decision tree (sequential). The induced simultaneous processing strategy worked optimally under rule learning, while the sequential strategy was difficult to induce and/or not optimal for rule-learning operations.…

Different strategies in solving series completion inductive reasoning problems: an fMRI and computational study.

PubMed

Liang, Peipeng; Jia, Xiuqin; Taatgen, Niels A; Zhong, Ning; Li, Kuncheng

2014-08-01

Neural correlate of human inductive reasoning process is still unclear. Number series and letter series completion are two typical inductive reasoning tasks, and with a common core component of rule induction. Previous studies have demonstrated that different strategies are adopted in number series and letter series completion tasks; even the underlying rules are identical. In the present study, we examined cortical activation as a function of two different reasoning strategies for solving series completion tasks. The retrieval strategy, used in number series completion tasks, involves direct retrieving of arithmetic knowledge to get the relations between items. The procedural strategy, used in letter series completion tasks, requires counting a certain number of times to detect the relations linking two items. The two strategies require essentially the equivalent cognitive processes, but have different working memory demands (the procedural strategy incurs greater demands). The procedural strategy produced significant greater activity in areas involved in memory retrieval (dorsolateral prefrontal cortex, DLPFC) and mental representation/maintenance (posterior parietal cortex, PPC). An ACT-R model of the tasks successfully predicted behavioral performance and BOLD responses. The present findings support a general-purpose dual-process theory of inductive reasoning regarding the cognitive architecture. Copyright © 2014 Elsevier B.V. All rights reserved.

The use of decision tree induction and artificial neural networks for recognizing the geochemical distribution patterns of LREE in the Choghart deposit, Central Iran

NASA Astrophysics Data System (ADS)

Zaremotlagh, S.; Hezarkhani, A.

2017-04-01

Some evidences of rare earth elements (REE) concentrations are found in iron oxide-apatite (IOA) deposits which are located in Central Iranian microcontinent. There are many unsolved problems about the origin and metallogenesis of IOA deposits in this district. Although it is considered that felsic magmatism and mineralization were simultaneous in the district, interaction of multi-stage hydrothermal-magmatic processes within the Early Cambrian volcano-sedimentary sequence probably caused some epigenetic mineralizations. Secondary geological processes (e.g., multi-stage mineralization, alteration, and weathering) have affected on variations of major elements and possible redistribution of REE in IOA deposits. Hence, the geochemical behaviors and distribution patterns of REE are expected to be complicated in different zones of these deposits. The aim of this paper is recognizing LREE distribution patterns based on whole-rock chemical compositions and automatic discovery of their geochemical rules. For this purpose, the pattern recognition techniques including decision tree and neural network were applied on a high-dimensional geochemical dataset from Choghart IOA deposit. Because some data features were irrelevant or redundant in recognizing the distribution patterns of each LREE, a greedy attribute subset selection technique was employed to select the best subset of predictors used in classification tasks. The decision trees (CART algorithm) were pruned optimally to more accurately categorize independent test data than unpruned ones. The most effective classification rules were extracted from the pruned tree to describe the meaningful relationships between the predictors and different concentrations of LREE. A feed-forward artificial neural network was also applied to reliably predict the influence of various rock compositions on the spatial distribution patterns of LREE with a better performance than the decision tree induction. The findings of this study could be effectively used to visualize the LREE distribution patterns as geochemical maps.

Occupancy schedules learning process through a data mining framework

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

D'Oca, Simona; Hong, Tianzhen

Building occupancy is a paramount factor in building energy simulations. Specifically, lighting, plug loads, HVAC equipment utilization, fresh air requirements and internal heat gain or loss greatly depends on the level of occupancy within a building. Developing the appropriate methodologies to describe and reproduce the intricate network responsible for human-building interactions are needed. Extrapolation of patterns from big data streams is a powerful analysis technique which will allow for a better understanding of energy usage in buildings. A three-step data mining framework is applied to discover occupancy patterns in office spaces. First, a data set of 16 offices with 10more » minute interval occupancy data, over a two year period is mined through a decision tree model which predicts the occupancy presence. Then a rule induction algorithm is used to learn a pruned set of rules on the results from the decision tree model. Finally, a cluster analysis is employed in order to obtain consistent patterns of occupancy schedules. Furthermore, the identified occupancy rules and schedules are representative as four archetypal working profiles that can be used as input to current building energy modeling programs, such as EnergyPlus or IDA-ICE, to investigate impact of occupant presence on design, operation and energy use in office buildings.« less

Occupancy schedules learning process through a data mining framework

DOE PAGES

D'Oca, Simona; Hong, Tianzhen

2014-12-17

Building occupancy is a paramount factor in building energy simulations. Specifically, lighting, plug loads, HVAC equipment utilization, fresh air requirements and internal heat gain or loss greatly depends on the level of occupancy within a building. Developing the appropriate methodologies to describe and reproduce the intricate network responsible for human-building interactions are needed. Extrapolation of patterns from big data streams is a powerful analysis technique which will allow for a better understanding of energy usage in buildings. A three-step data mining framework is applied to discover occupancy patterns in office spaces. First, a data set of 16 offices with 10more » minute interval occupancy data, over a two year period is mined through a decision tree model which predicts the occupancy presence. Then a rule induction algorithm is used to learn a pruned set of rules on the results from the decision tree model. Finally, a cluster analysis is employed in order to obtain consistent patterns of occupancy schedules. Furthermore, the identified occupancy rules and schedules are representative as four archetypal working profiles that can be used as input to current building energy modeling programs, such as EnergyPlus or IDA-ICE, to investigate impact of occupant presence on design, operation and energy use in office buildings.« less

Controlling false-negative errors in microarray differential expression analysis: a PRIM approach.

PubMed

Cole, Steve W; Galic, Zoran; Zack, Jerome A

2003-09-22

Theoretical considerations suggest that current microarray screening algorithms may fail to detect many true differences in gene expression (Type II analytic errors). We assessed 'false negative' error rates in differential expression analyses by conventional linear statistical models (e.g. t-test), microarray-adapted variants (e.g. SAM, Cyber-T), and a novel strategy based on hold-out cross-validation. The latter approach employs the machine-learning algorithm Patient Rule Induction Method (PRIM) to infer minimum thresholds for reliable change in gene expression from Boolean conjunctions of fold-induction and raw fluorescence measurements. Monte Carlo analyses based on four empirical data sets show that conventional statistical models and their microarray-adapted variants overlook more than 50% of genes showing significant up-regulation. Conjoint PRIM prediction rules recover approximately twice as many differentially expressed transcripts while maintaining strong control over false-positive (Type I) errors. As a result, experimental replication rates increase and total analytic error rates decline. RT-PCR studies confirm that gene inductions detected by PRIM but overlooked by other methods represent true changes in mRNA levels. PRIM-based conjoint inference rules thus represent an improved strategy for high-sensitivity screening of DNA microarrays. Freestanding JAVA application at http://microarray.crump.ucla.edu/focus

The Case for Problem Solving in Second Language Learning. CLCS Occasional Paper No. 33.

ERIC Educational Resources Information Center

Bourke, James Mannes

A study undertaken in Ireland investigated the effectiveness of a second language teaching strategy that focused on grammatical problem-solving. In this approach, the problems are located within the target language system, and the problem-solving involves induction of grammatical rules and use of those rules. Learners are confronted with instances…

Multi-class Mode of Action Classification of Toxic Compounds Using Logic Based Kernel Methods.

PubMed

Lodhi, Huma; Muggleton, Stephen; Sternberg, Mike J E

2010-09-17

Toxicity prediction is essential for drug design and development of effective therapeutics. In this paper we present an in silico strategy, to identify the mode of action of toxic compounds, that is based on the use of a novel logic based kernel method. The technique uses support vector machines in conjunction with the kernels constructed from first order rules induced by an Inductive Logic Programming system. It constructs multi-class models by using a divide and conquer reduction strategy that splits multi-classes into binary groups and solves each individual problem recursively hence generating an underlying decision list structure. In order to evaluate the effectiveness of the approach for chemoinformatics problems like predictive toxicology, we apply it to toxicity classification in aquatic systems. The method is used to identify and classify 442 compounds with respect to the mode of action. The experimental results show that the technique successfully classifies toxic compounds and can be useful in assessing environmental risks. Experimental comparison of the performance of the proposed multi-class scheme with the standard multi-class Inductive Logic Programming algorithm and multi-class Support Vector Machine yields statistically significant results and demonstrates the potential power and benefits of the approach in identifying compounds of various toxic mechanisms. Copyright © 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

32 CFR 1630.47 - Class 4-W: Registrant who has completed alternative service in lieu of induction.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 32 National Defense 6 2010-07-01 2010-07-01 false Class 4-W: Registrant who has completed... to National Defense SELECTIVE SERVICE SYSTEM CLASSIFICATION RULES § 1630.47 Class 4-W: Registrant who has completed alternative service in lieu of induction. In Class 4-W shall be placed any registrant...

The Effectiveness of Guided Induction versus Deductive Instruction on the Development of Complex Spanish "Gustar" Structures: An Analysis of Learning Outcomes and Processes

ERIC Educational Resources Information Center

Cerezo, Luis; Caras, Allison; Leow, Ronald P.

2016-01-01

Meta-analytic research suggests an edge of explicit over implicit instruction for the development of complex L2 grammatical structures, but the jury is still out as to which type of explicit instruction--"deductive" or "inductive," where rules are respectively provided or elicited--proves more effective. Avoiding this…

Fuzzy – PI controller to control the velocity parameter of Induction Motor

NASA Astrophysics Data System (ADS)

Malathy, R.; Balaji, V.

2018-04-01

The major application of Induction motor includes the usage of the same in industries because of its high robustness, reliability, low cost, highefficiency and good self-starting capability. Even though it has the above mentioned advantages, it also have some limitations: (1) the standard motor is not a true constant-speed machine, itsfull-load slip varies less than 1 % (in high-horsepower motors).And (2) it is not inherently capable of providing variable-speedoperation. In order to solve the above mentioned problem smart motor controls and variable speed controllers are used. Motor applications involve non linearity features, which can be controlled by Fuzzy logic controller as it is capable of handling those features with high efficiency and it act similar to human operator. This paper presents individuality of the plant modelling. The fuzzy logic controller (FLC)trusts on a set of linguistic if-then rules, a rule-based Mamdani for closed loop Induction Motor model. Themotor model is designed and membership functions are chosenaccording to the parameters of the motor model. Simulation results contains non linearity in induction motor model. A conventional PI controller iscompared practically to fuzzy logic controller using Simulink.

49 CFR 236.552 - Insulation resistance; requirement.

Code of Federal Regulations, 2010 CFR

2010-10-01

... ADMINISTRATION, DEPARTMENT OF TRANSPORTATION RULES, STANDARDS, AND INSTRUCTIONS GOVERNING THE INSTALLATION... resistance between wiring and ground of continuous inductive automatic cab signal system, automatic train...

Brief Report: Impaired Flexible Item Selection Task (FIST) in School-Age Children with Autism Spectrum Disorders

ERIC Educational Resources Information Center

Yerys, Benjamin E.; Wolff, Brian C.; Moody, Eric; Pennington, Bruce F.; Hepburn, Susan L.

2012-01-01

Cognitive flexibility has been measured with inductive reasoning or explicit rule tasks in individuals with autism spectrum disorders (ASD). The "Flexible Item Selection Task" (FIST) differs from previous cognitive flexibility tasks in ASD research by giving children an abstract, ambiguous rule to switch. The ASD group (N = 22; Mean age = 8.28…

Generating Concise Rules for Human Motion Retrieval

NASA Astrophysics Data System (ADS)

Mukai, Tomohiko; Wakisaka, Ken-Ichi; Kuriyama, Shigeru

This paper proposes a method for retrieving human motion data with concise retrieval rules based on the spatio-temporal features of motion appearance. Our method first converts motion clip into a form of clausal language that represents geometrical relations between body parts and their temporal relationship. A retrieval rule is then learned from the set of manually classified examples using inductive logic programming (ILP). ILP automatically discovers the essential rule in the same clausal form with a user-defined hypothesis-testing procedure. All motions are indexed using this clausal language, and the desired clips are retrieved by subsequence matching using the rule. Such rule-based retrieval offers reasonable performance and the rule can be intuitively edited in the same language form. Consequently, our method enables efficient and flexible search from a large dataset with simple query language.

Intra-regional classification of grape seeds produced in Mendoza province (Argentina) by multi-elemental analysis and chemometrics tools.

PubMed

Canizo, Brenda V; Escudero, Leticia B; Pérez, María B; Pellerano, Roberto G; Wuilloud, Rodolfo G

2018-03-01

The feasibility of the application of chemometric techniques associated with multi-element analysis for the classification of grape seeds according to their provenance vineyard soil was investigated. Grape seed samples from different localities of Mendoza province (Argentina) were evaluated. Inductively coupled plasma mass spectrometry (ICP-MS) was used for the determination of twenty-nine elements (Ag, As, Ce, Co, Cs, Cu, Eu, Fe, Ga, Gd, La, Lu, Mn, Mo, Nb, Nd, Ni, Pr, Rb, Sm, Te, Ti, Tl, Tm, U, V, Y, Zn and Zr). Once the analytical data were collected, supervised pattern recognition techniques such as linear discriminant analysis (LDA), partial least square discriminant analysis (PLS-DA), k-nearest neighbors (k-NN), support vector machine (SVM) and Random Forest (RF) were applied to construct classification/discrimination rules. The results indicated that nonlinear methods, RF and SVM, perform best with up to 98% and 93% accuracy rate, respectively, and therefore are excellent tools for classification of grapes. Copyright © 2017 Elsevier Ltd. All rights reserved.

Using machine learning techniques to automate sky survey catalog generation

NASA Technical Reports Server (NTRS)

Fayyad, Usama M.; Roden, J. C.; Doyle, R. J.; Weir, Nicholas; Djorgovski, S. G.

1993-01-01

We describe the application of machine classification techniques to the development of an automated tool for the reduction of a large scientific data set. The 2nd Palomar Observatory Sky Survey provides comprehensive photographic coverage of the northern celestial hemisphere. The photographic plates are being digitized into images containing on the order of 10(exp 7) galaxies and 10(exp 8) stars. Since the size of this data set precludes manual analysis and classification of objects, our approach is to develop a software system which integrates independently developed techniques for image processing and data classification. Image processing routines are applied to identify and measure features of sky objects. Selected features are used to determine the classification of each object. GID3* and O-BTree, two inductive learning techniques, are used to automatically learn classification decision trees from examples. We describe the techniques used, the details of our specific application, and the initial encouraging results which indicate that our approach is well-suited to the problem. The benefits of the approach are increased data reduction throughput, consistency of classification, and the automated derivation of classification rules that will form an objective, examinable basis for classifying sky objects. Furthermore, astronomers will be freed from the tedium of an intensely visual task to pursue more challenging analysis and interpretation problems given automatically cataloged data.

Induction of lucid dreams: a systematic review of evidence.

PubMed

Stumbrys, Tadas; Erlacher, Daniel; Schädlich, Melanie; Schredl, Michael

2012-09-01

In lucid dreams the dreamer is aware of dreaming and often able to influence the ongoing dream content. Lucid dreaming is a learnable skill and a variety of techniques is suggested for lucid dreaming induction. This systematic review evaluated the evidence for the effectiveness of induction techniques. A comprehensive literature search was carried out in biomedical databases and specific resources. Thirty-five studies were included in the analysis (11 sleep laboratory and 24 field studies), of which 26 employed cognitive techniques, 11 external stimulation and one drug application. The methodological quality of the included studies was relatively low. None of the induction techniques were verified to induce lucid dreams reliably and consistently, although some of them look promising. On the basis of the reviewed studies, a taxonomy of lucid dream induction methods is presented. Several methodological issues are discussed and further directions for future studies are proposed. Copyright © 2012 Elsevier Inc. All rights reserved.

75 FR 38156 - Small Business Size Standards: Waiver of the Nonmanufacturer Rule

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-01

... Systems (CS-MS), High Performance Liquid Chromatography (HPLC) Systems, Gas Chromatography Mass... Chromatography (HPLC) Systems, Gas Chromatography Mass Spectrometry (GC-MS) Systems, and, Inductively Coupled...

Global electromagnetic induction in the moon and planets. [poloidal eddy current transient response

NASA Technical Reports Server (NTRS)

Dyal, P.; Parkin, C. W.

1973-01-01

Experiments and analyses concerning electromagnetic induction in the moon and other extraterrestrial bodies are summarized. The theory of classical electromagnetic induction in a sphere is first considered, and this treatment is extended to the case of the moon, where poloidal eddy-current response has been found experimentally to dominate other induction modes. Analysis of lunar poloidal induction yields lunar internal electrical conductivity and temperature profiles. Two poloidal-induction analytical techniques are discussed: a transient-response method applied to time-series magnetometer data, and a harmonic-analysis method applied to data numerically Fourier-transformed to the frequency domain, with emphasis on the former technique. Attention is given to complicating effects of the solar wind interaction with both induced poloidal fields and remanent steady fields. The static magnetization field induction mode is described, from which are calculated bulk magnetic permeability profiles. Magnetic field measurements obtained from the moon and from fly-bys of Venus and Mars are studied to determine the feasibility of extending theoretical and experimental induction techniques to other bodies in the solar system.

Traditional versus rule-based programming techniques - Application to the control of optional flight information

NASA Technical Reports Server (NTRS)

Ricks, Wendell R.; Abbott, Kathy H.

1987-01-01

A traditional programming technique for controlling the display of optional flight information in a civil transport cockpit is compared to a rule-based technique for the same function. This application required complex decision logic and a frequently modified rule base. The techniques are evaluated for execution efficiency and implementation ease; the criterion used to calculate the execution efficiency is the total number of steps required to isolate hypotheses that were true and the criteria used to evaluate the implementability are ease of modification and verification and explanation capability. It is observed that the traditional program is more efficient than the rule-based program; however, the rule-based programming technique is more applicable for improving programmer productivity.

Applying machine learning classification techniques to automate sky object cataloguing

NASA Astrophysics Data System (ADS)

Fayyad, Usama M.; Doyle, Richard J.; Weir, W. Nick; Djorgovski, Stanislav

1993-08-01

We describe the application of an Artificial Intelligence machine learning techniques to the development of an automated tool for the reduction of a large scientific data set. The 2nd Mt. Palomar Northern Sky Survey is nearly completed. This survey provides comprehensive coverage of the northern celestial hemisphere in the form of photographic plates. The plates are being transformed into digitized images whose quality will probably not be surpassed in the next ten to twenty years. The images are expected to contain on the order of 107 galaxies and 108 stars. Astronomers wish to determine which of these sky objects belong to various classes of galaxies and stars. Unfortunately, the size of this data set precludes analysis in an exclusively manual fashion. Our approach is to develop a software system which integrates the functions of independently developed techniques for image processing and data classification. Digitized sky images are passed through image processing routines to identify sky objects and to extract a set of features for each object. These routines are used to help select a useful set of attributes for classifying sky objects. Then GID3 (Generalized ID3) and O-B Tree, two inductive learning techniques, learns classification decision trees from examples. These classifiers will then be applied to new data. These developmnent process is highly interactive, with astronomer input playing a vital role. Astronomers refine the feature set used to construct sky object descriptions, and evaluate the performance of the automated classification technique on new data. This paper gives an overview of the machine learning techniques with an emphasis on their general applicability, describes the details of our specific application, and reports the initial encouraging results. The results indicate that our machine learning approach is well-suited to the problem. The primary benefit of the approach is increased data reduction throughput. Another benefit is consistency of classification. The classification rules which are the product of the inductive learning techniques will form an objective, examinable basis for classifying sky objects. A final, not to be underestimated benefit is that astronomers will be freed from the tedium of an intensely visual task to pursue more challenging analysis and interpretation problems based on automatically catalogued data.

Improving the Interpretability of Classification Rules Discovered by an Ant Colony Algorithm: Extended Results.

PubMed

Otero, Fernando E B; Freitas, Alex A

2016-01-01

Most ant colony optimization (ACO) algorithms for inducing classification rules use a ACO-based procedure to create a rule in a one-at-a-time fashion. An improved search strategy has been proposed in the cAnt-Miner[Formula: see text] algorithm, where an ACO-based procedure is used to create a complete list of rules (ordered rules), i.e., the ACO search is guided by the quality of a list of rules instead of an individual rule. In this paper we propose an extension of the cAnt-Miner[Formula: see text] algorithm to discover a set of rules (unordered rules). The main motivations for this work are to improve the interpretation of individual rules by discovering a set of rules and to evaluate the impact on the predictive accuracy of the algorithm. We also propose a new measure to evaluate the interpretability of the discovered rules to mitigate the fact that the commonly used model size measure ignores how the rules are used to make a class prediction. Comparisons with state-of-the-art rule induction algorithms, support vector machines, and the cAnt-Miner[Formula: see text] producing ordered rules are also presented.

Cocaine Promotes Coincidence Detection and Lowers Induction Threshold during Hebbian Associative Synaptic Potentiation in Prefrontal Cortex.

PubMed

Ruan, Hongyu; Yao, Wei-Dong

2017-01-25

Addictive drugs usurp neural plasticity mechanisms that normally serve reward-related learning and memory, primarily by evoking changes in glutamatergic synaptic strength in the mesocorticolimbic dopamine circuitry. Here, we show that repeated cocaine exposure in vivo does not alter synaptic strength in the mouse prefrontal cortex during an early period of withdrawal, but instead modifies a Hebbian quantitative synaptic learning rule by broadening the temporal window and lowers the induction threshold for spike-timing-dependent LTP (t-LTP). After repeated, but not single, daily cocaine injections, t-LTP in layer V pyramidal neurons is induced at +30 ms, a normally ineffective timing interval for t-LTP induction in saline-exposed mice. This cocaine-induced, extended-timing t-LTP lasts for ∼1 week after terminating cocaine and is accompanied by an increased susceptibility to potentiation by fewer pre-post spike pairs, indicating a reduced t-LTP induction threshold. Basal synaptic strength and the maximal attainable t-LTP magnitude remain unchanged after cocaine exposure. We further show that the cocaine facilitation of t-LTP induction is caused by sensitized D1-cAMP/protein kinase A dopamine signaling in pyramidal neurons, which then pathologically recruits voltage-gated l-type Ca 2+ channels that synergize with GluN2A-containing NMDA receptors to drive t-LTP at extended timing. Our results illustrate a mechanism by which cocaine, acting on a key neuromodulation pathway, modifies the coincidence detection window during Hebbian plasticity to facilitate associative synaptic potentiation in prefrontal excitatory circuits. By modifying rules that govern activity-dependent synaptic plasticity, addictive drugs can derail the experience-driven neural circuit remodeling process important for executive control of reward and addiction. It is believed that addictive drugs often render an addict's brain reward system hypersensitive, leaving the individual more susceptible to relapse. We found that repeated cocaine exposure alters a Hebbian associative synaptic learning rule that governs activity-dependent synaptic plasticity in the mouse prefrontal cortex, characterized by a broader temporal window and a lower threshold for spike-timing-dependent LTP (t-LTP), a cellular form of learning and memory. This rule change is caused by cocaine-exacerbated D1-cAMP/protein kinase A dopamine signaling in pyramidal neurons that in turn pathologically recruits l-type Ca 2+ channels to facilitate coincidence detection during t-LTP induction. Our study provides novel insights on how cocaine, even with only brief exposure, may prime neural circuits for subsequent experience-dependent remodeling that may underlie certain addictive behavior. Copyright © 2017 the authors 0270-6474/17/370986-12$15.00/0.

Inductional Effects in a Halbach Magnet Motion Above Distributed Inductance

NASA Astrophysics Data System (ADS)

Tchatchoua, Yves; Conrow, Ary; Kim, Dong; Morgan, Daniel; Majewski, Walerian; Zafar, Zaeema

2013-03-01

We experimented with attempts to levitate a linear (bar) Halbach array of five 1'' Nd magnets above a linear inductive track. Next, in order to achieve a control over the relative velocity, we designed a different experiment. In it a large wheel with circumferentially positioned along its rim inducting coils rotates, while the magnet is suspended directly above the rim of the wheel on a force sensor. Faraday's Law with the Lenz's Rule is responsible for the lifting and drag forces on the magnet; the horizontal drag force is measured by another force sensor. Approximating the magnet's linear relative motion over inductors with a motion along a large circle, we may use formulas derived earlier in the literature for linear inductive levitation. We measured lift and drag forces as functions of relative velocity of the Halbach magnet and the inductive ``track,'' in an approximate agreement with the existing theory. We then vary the inductance and shape of the inductive elements to find the most beneficial choice for the lift/drag ratio at the lowest relative speed.

General Purpose Data-Driven Online System Health Monitoring with Applications to Space Operations

NASA Technical Reports Server (NTRS)

Iverson, David L.; Spirkovska, Lilly; Schwabacher, Mark

2010-01-01

Modern space transportation and ground support system designs are becoming increasingly sophisticated and complex. Determining the health state of these systems using traditional parameter limit checking, or model-based or rule-based methods is becoming more difficult as the number of sensors and component interactions grows. Data-driven monitoring techniques have been developed to address these issues by analyzing system operations data to automatically characterize normal system behavior. System health can be monitored by comparing real-time operating data with these nominal characterizations, providing detection of anomalous data signatures indicative of system faults, failures, or precursors of significant failures. The Inductive Monitoring System (IMS) is a general purpose, data-driven system health monitoring software tool that has been successfully applied to several aerospace applications and is under evaluation for anomaly detection in vehicle and ground equipment for next generation launch systems. After an introduction to IMS application development, we discuss these NASA online monitoring applications, including the integration of IMS with complementary model-based and rule-based methods. Although the examples presented in this paper are from space operations applications, IMS is a general-purpose health-monitoring tool that is also applicable to power generation and transmission system monitoring.

Rapid sequence induction has no use in pediatric anesthesia.

PubMed

Engelhardt, Thomas

2015-01-01

(Classic) rapid sequence induction and intubation (RSII) has been considered fundamental to the provision of safe anesthesia. This technique consists of a combination of drugs and techniques and is intended to prevent pulmonary aspiration of gastric content with catastrophic outcomes to the patient. This review investigates aspects of this technique and highlights dangers and frauds if this technique is transferred directly into pediatric anesthesia practice. The author recommends a controlled anesthesia induction by trained pediatric anesthesiologist with suitable equipment for the children considered at risk of pulmonary aspiration. RSSI is a dangerous technique if adopted without modification into pediatric anesthesia and has in its 'classic' form no use. © 2014 John Wiley & Sons Ltd.

Learning and Tuning of Fuzzy Rules

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.

1997-01-01

In this chapter, we review some of the current techniques for learning and tuning fuzzy rules. For clarity, we refer to the process of generating rules from data as the learning problem and distinguish it from tuning an already existing set of fuzzy rules. For learning, we touch on unsupervised learning techniques such as fuzzy c-means, fuzzy decision tree systems, fuzzy genetic algorithms, and linear fuzzy rules generation methods. For tuning, we discuss Jang's ANFIS architecture, Berenji-Khedkar's GARIC architecture and its extensions in GARIC-Q. We show that the hybrid techniques capable of learning and tuning fuzzy rules, such as CART-ANFIS, RNN-FLCS, and GARIC-RB, are desirable in development of a number of future intelligent systems.

Performance of dual inverter fed open end winding induction motor drive using carrier shift PWM techniques

NASA Astrophysics Data System (ADS)

Priya Darshini, B.; Ranjit, M.; Babu, V. Ramesh

2018-04-01

In this paper different Multicarrier PWM (MCPWM) techniques are proposed for dual inverter fed open end induction motor (IM) drive to achieve multilevel operation. To generate the switching pulses for the dual inverter sinusoidal modulating signal is compared with multi carrier signals. A common mode voltage (CMV) has been analyzed in the proposed open end winding induction motor drive. All the proposed techniques mitigate the CMV along with the harmonic distortion in the phase voltage. To authenticate the proposed work several simulation techniques have been carried out using MATLAB/SIMULINK and the corresponding results are presented and compared.

Concurrent approach for evolving compact decision rule sets

NASA Astrophysics Data System (ADS)

Marmelstein, Robert E.; Hammack, Lonnie P.; Lamont, Gary B.

1999-02-01

The induction of decision rules from data is important to many disciplines, including artificial intelligence and pattern recognition. To improve the state of the art in this area, we introduced the genetic rule and classifier construction environment (GRaCCE). It was previously shown that GRaCCE consistently evolved decision rule sets from data, which were significantly more compact than those produced by other methods (such as decision tree algorithms). The primary disadvantage of GRaCCe, however, is its relatively poor run-time execution performance. In this paper, a concurrent version of the GRaCCE architecture is introduced, which improves the efficiency of the original algorithm. A prototype of the algorithm is tested on an in- house parallel processor configuration and the results are discussed.

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.

Diagnosis of the three-phase induction motor using thermal imaging

NASA Astrophysics Data System (ADS)

Glowacz, Adam; Glowacz, Zygfryd

2017-03-01

Three-phase induction motors are used in the industry commonly for example woodworking machines, blowers, pumps, conveyors, elevators, compressors, mining industry, automotive industry, chemical industry and railway applications. Diagnosis of faults is essential for proper maintenance. Faults may damage a motor and damaged motors generate economic losses caused by breakdowns in production lines. In this paper the authors develop fault diagnostic techniques of the three-phase induction motor. The described techniques are based on the analysis of thermal images of three-phase induction motor. The authors analyse thermal images of 3 states of the three-phase induction motor: healthy three-phase induction motor, three-phase induction motor with 2 broken bars, three-phase induction motor with faulty ring of squirrel-cage. In this paper the authors develop an original method of the feature extraction of thermal images MoASoID (Method of Areas Selection of Image Differences). This method compares many training sets together and it selects the areas with the biggest changes for the recognition process. Feature vectors are obtained with the use of mentioned MoASoID and image histogram. Next 3 methods of classification are used: NN (the Nearest Neighbour classifier), K-means, BNN (the back-propagation neural network). The described fault diagnostic techniques are useful for protection of three-phase induction motor and other types of rotating electrical motors such as: DC motors, generators, synchronous motors.

Numerical Integration

ERIC Educational Resources Information Center

Sozio, Gerry

2009-01-01

Senior secondary students cover numerical integration techniques in their mathematics courses. In particular, students would be familiar with the "midpoint rule," the elementary "trapezoidal rule" and "Simpson's rule." This article derives these techniques by methods which secondary students may not be familiar with and an approach that…

Learning rules for spike timing-dependent plasticity depend on dendritic synapse location.

PubMed

Letzkus, Johannes J; Kampa, Björn M; Stuart, Greg J

2006-10-11

Previous studies focusing on the temporal rules governing changes in synaptic strength during spike timing-dependent synaptic plasticity (STDP) have paid little attention to the fact that synaptic inputs are distributed across complex dendritic trees. During STDP, propagation of action potentials (APs) back to the site of synaptic input is thought to trigger plasticity. However, in pyramidal neurons, backpropagation of single APs is decremental, whereas high-frequency bursts lead to generation of distal dendritic calcium spikes. This raises the question whether STDP learning rules depend on synapse location and firing mode. Here, we investigate this issue at synapses between layer 2/3 and layer 5 pyramidal neurons in somatosensory cortex. We find that low-frequency pairing of single APs at positive times leads to a distance-dependent shift to long-term depression (LTD) at distal inputs. At proximal sites, this LTD could be converted to long-term potentiation (LTP) by dendritic depolarizations suprathreshold for BAC-firing or by high-frequency AP bursts. During AP bursts, we observed a progressive, distance-dependent shift in the timing requirements for induction of LTP and LTD, such that distal synapses display novel timing rules: they potentiate when inputs are activated after burst onset (negative timing) but depress when activated before burst onset (positive timing). These findings could be explained by distance-dependent differences in the underlying dendritic voltage waveforms driving NMDA receptor activation during STDP induction. Our results suggest that synapse location within the dendritic tree is a crucial determinant of STDP, and that synapses undergo plasticity according to local rather than global learning rules.

Integrating machine learning and physician knowledge to improve the accuracy of breast biopsy.

PubMed

Dutra, I; Nassif, H; Page, D; Shavlik, J; Strigel, R M; Wu, Y; Elezaby, M E; Burnside, E

2011-01-01

In this work we show that combining physician rules and machine learned rules may improve the performance of a classifier that predicts whether a breast cancer is missed on percutaneous, image-guided breast core needle biopsy (subsequently referred to as "breast core biopsy"). Specifically, we show how advice in the form of logical rules, derived by a sub-specialty, i.e. fellowship trained breast radiologists (subsequently referred to as "our physicians") can guide the search in an inductive logic programming system, and improve the performance of a learned classifier. Our dataset of 890 consecutive benign breast core biopsy results along with corresponding mammographic findings contains 94 cases that were deemed non-definitive by a multidisciplinary panel of physicians, from which 15 were upgraded to malignant disease at surgery. Our goal is to predict upgrade prospectively and avoid surgery in women who do not have breast cancer. Our results, some of which trended toward significance, show evidence that inductive logic programming may produce better results for this task than traditional propositional algorithms with default parameters. Moreover, we show that adding knowledge from our physicians into the learning process may improve the performance of the learned classifier trained only on data.

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.

Structural analysis of eyespots: dynamics of morphogenic signals that govern elemental positions in butterfly wings

PubMed Central

2012-01-01

Background To explain eyespot colour-pattern determination in butterfly wings, the induction model has been discussed based on colour-pattern analyses of various butterfly eyespots. However, a detailed structural analysis of eyespots that can serve as a foundation for future studies is still lacking. In this study, fundamental structural rules related to butterfly eyespots are proposed, and the induction model is elaborated in terms of the possible dynamics of morphogenic signals involved in the development of eyespots and parafocal elements (PFEs) based on colour-pattern analysis of the nymphalid butterfly Junonia almana. Results In a well-developed eyespot, the inner black core ring is much wider than the outer black ring; this is termed the inside-wide rule. It appears that signals are wider near the focus of the eyespot and become narrower as they expand. Although fundamental signal dynamics are likely to be based on a reaction-diffusion mechanism, they were described well mathematically as a type of simple uniformly decelerated motion in which signals associated with the outer and inner black rings of eyespots and PFEs are released at different time points, durations, intervals, and initial velocities into a two-dimensional field of fundamentally uniform or graded resistance; this produces eyespots and PFEs that are diverse in size and structure. The inside-wide rule, eyespot distortion, structural differences between small and large eyespots, and structural changes in eyespots and PFEs in response to physiological treatments were explained well using mathematical simulations. Natural colour patterns and previous experimental findings that are not easily explained by the conventional gradient model were also explained reasonably well by the formal mathematical simulations performed in this study. Conclusions In a mode free from speculative molecular interactions, the present study clarifies fundamental structural rules related to butterfly eyespots, delineates a theoretical basis for the induction model, and proposes a mathematically simple mode of long-range signalling that may reflect developmental mechanisms associated with butterfly eyespots. PMID:22409965

Structural analysis of eyespots: dynamics of morphogenic signals that govern elemental positions in butterfly wings.

PubMed

Otaki, Joji M

2012-03-13

To explain eyespot colour-pattern determination in butterfly wings, the induction model has been discussed based on colour-pattern analyses of various butterfly eyespots. However, a detailed structural analysis of eyespots that can serve as a foundation for future studies is still lacking. In this study, fundamental structural rules related to butterfly eyespots are proposed, and the induction model is elaborated in terms of the possible dynamics of morphogenic signals involved in the development of eyespots and parafocal elements (PFEs) based on colour-pattern analysis of the nymphalid butterfly Junonia almana. In a well-developed eyespot, the inner black core ring is much wider than the outer black ring; this is termed the inside-wide rule. It appears that signals are wider near the focus of the eyespot and become narrower as they expand. Although fundamental signal dynamics are likely to be based on a reaction-diffusion mechanism, they were described well mathematically as a type of simple uniformly decelerated motion in which signals associated with the outer and inner black rings of eyespots and PFEs are released at different time points, durations, intervals, and initial velocities into a two-dimensional field of fundamentally uniform or graded resistance; this produces eyespots and PFEs that are diverse in size and structure. The inside-wide rule, eyespot distortion, structural differences between small and large eyespots, and structural changes in eyespots and PFEs in response to physiological treatments were explained well using mathematical simulations. Natural colour patterns and previous experimental findings that are not easily explained by the conventional gradient model were also explained reasonably well by the formal mathematical simulations performed in this study. In a mode free from speculative molecular interactions, the present study clarifies fundamental structural rules related to butterfly eyespots, delineates a theoretical basis for the induction model, and proposes a mathematically simple mode of long-range signalling that may reflect developmental mechanisms associated with butterfly eyespots.

Investigation of induction motor temperature distribution in traction applications

NASA Astrophysics Data System (ADS)

Pugachev, A. A.; Kosmodamianskiy, A. S.

2017-10-01

The relevance of thermal behavior investigation of traction induction motors is shown. The brief survey of techniques to monitor the temperature of an induction motors is carried out. The detailed multi-node equivalent thermal circuit of an induction motor is designed for steady state. The calculation technique of some units’ thermal resistances by using of construction features and geometric sizes of an induction motor is shown. Results of thermal processes calculation for 14 kWAO-63-4 induction motor are shown. The adequacy of proposed thermal model is proved by means of good convergence of calculated results with the results obtained by the experimental investigation on the same induction motor. As a result of investigation, it is established that the slot winding of the stator located about on 2/3 of its length from the cooling air entrance has the highest value of temperature.

An expert system shell for inferring vegetation characteristics: Interface for the addition of techniques (Task H)

NASA Technical Reports Server (NTRS)

Harrison, P. Ann

1993-01-01

All the NASA VEGetation Workbench (VEG) goals except the Learning System provide the scientist with several different techniques. When VEG is run, rules assist the scientist in selecting the best of the available techniques to apply to the sample of cover type data being studied. The techniques are stored in the VEG knowledge base. The design and implementation of an interface that allows the scientist to add new techniques to VEG without assistance from the developer were completed. A new interface that enables the scientist to add techniques to VEG without assistance from the developer was designed and implemented. This interface does not require the scientist to have a thorough knowledge of Knowledge Engineering Environment (KEE) by Intellicorp or a detailed knowledge of the structure of VEG. The interface prompts the scientist to enter the required information about the new technique. It prompts the scientist to enter the required Common Lisp functions for executing the technique and the left hand side of the rule that causes the technique to be selected. A template for each function and rule and detailed instructions about the arguments of the functions, the values they should return, and the format of the rule are displayed. Checks are made to ensure that the required data were entered, the functions compiled correctly, and the rule parsed correctly before the new technique is stored. The additional techniques are stored separately from the VEG knowledge base. When the VEG knowledge base is loaded, the additional techniques are not normally loaded. The interface allows the scientist the option of adding all the previously defined new techniques before running VEG. When the techniques are added, the required units to store the additional techniques are created automatically in the correct places in the VEG knowledge base. The methods file containing the functions required by the additional techniques is loaded. New rule units are created to store the new rules. The interface that allow the scientist to select which techniques to use is updated automatically to include the new techniques. Task H was completed. The interface that allows the scientist to add techniques to VEG was implemented and comprehensively tested. The Common Lisp code for the Add Techniques system is listed in Appendix A.

Automatic inference of indexing rules for MEDLINE

PubMed Central

Névéol, Aurélie; Shooshan, Sonya E; Claveau, Vincent

2008-01-01

Background: Indexing is a crucial step in any information retrieval system. In MEDLINE, a widely used database of the biomedical literature, the indexing process involves the selection of Medical Subject Headings in order to describe the subject matter of articles. The need for automatic tools to assist MEDLINE indexers in this task is growing with the increasing number of publications being added to MEDLINE. Methods: In this paper, we describe the use and the customization of Inductive Logic Programming (ILP) to infer indexing rules that may be used to produce automatic indexing recommendations for MEDLINE indexers. Results: Our results show that this original ILP-based approach outperforms manual rules when they exist. In addition, the use of ILP rules also improves the overall performance of the Medical Text Indexer (MTI), a system producing automatic indexing recommendations for MEDLINE. Conclusion: We expect the sets of ILP rules obtained in this experiment to be integrated into MTI. PMID:19025687

Automatic inference of indexing rules for MEDLINE.

PubMed

Névéol, Aurélie; Shooshan, Sonya E; Claveau, Vincent

2008-11-19

Indexing is a crucial step in any information retrieval system. In MEDLINE, a widely used database of the biomedical literature, the indexing process involves the selection of Medical Subject Headings in order to describe the subject matter of articles. The need for automatic tools to assist MEDLINE indexers in this task is growing with the increasing number of publications being added to MEDLINE. In this paper, we describe the use and the customization of Inductive Logic Programming (ILP) to infer indexing rules that may be used to produce automatic indexing recommendations for MEDLINE indexers. Our results show that this original ILP-based approach outperforms manual rules when they exist. In addition, the use of ILP rules also improves the overall performance of the Medical Text Indexer (MTI), a system producing automatic indexing recommendations for MEDLINE. We expect the sets of ILP rules obtained in this experiment to be integrated into MTI.

Universal 'imaginary closed circuit method' and formula for determination of direction of induced emf/current

NASA Astrophysics Data System (ADS)

Balaram Atram, Dattatraya

2011-01-01

Fleming's right-hand rule and the right-flat-hand rule are generally applied for determining the direction of flow of induced emf/current in straight conductors. The right-hand-fingers rule is applied for coils only. The right-hand-thumb rule can be applied for either straight conductors or coils. Different rules have to be applied for different situations. Also, a formula for determining the direction of induced emf/current does not exist on the basis of these rules. In this article, based on Faraday's law of electromagnetic induction and Lenz's law, an 'imaginary closed circuit method' and a formula for determination of direction of induced emf/current has been proposed. The method is universal in the sense that it is applicable for conductors of any shape, for any kind of relative motion of the conductor with respect to the magnetic flux, and moreover it is applicable for the case of varying magnetic flux.

The interplay of externalizing problems and physical and inductive discipline during childhood.

PubMed

Choe, Daniel Ewon; Olson, Sheryl L; Sameroff, Arnold J

2013-11-01

Children who are physically disciplined are at elevated risk for externalizing problems. Conversely, maternal reasoning and reminding of rules, or inductive discipline, is associated with fewer child externalizing problems. Few studies have simultaneously examined bidirectional associations between these forms of discipline and child adjustment using cross-informant, multimethod data. We hypothesized that less inductive and more physical discipline would predict more externalizing problems, children would have evocative effects on parenting, and high levels of either form of discipline would predict low levels of the other. In a study of 241 children-spanning ages 3, 5.5, and 10-structural equation modeling indicated that 3-year-olds with higher teacher ratings of externalizing problems received higher mother ratings of physical discipline at age 5.5. Mothers endorsing more inductive discipline at child age 3 reported less physical discipline and had children with fewer externalizing problems at age 5.5. Negative bidirectional associations emerged between physical and inductive discipline from ages 5.5 to 10. Findings suggested children's externalizing problems elicited physical discipline, and maternal inductive discipline might help prevent externalizing problems and physical discipline.

Inductive electronegativity scale. Iterative calculation of inductive partial charges.

PubMed

Cherkasov, Artem

2003-01-01

A number of novel QSAR descriptors have been introduced on the basis of the previously elaborated models for steric and inductive effects. The developed "inductive" parameters include absolute and effective electronegativity, atomic partial charges, and local and global chemical hardness and softness. Being based on traditional inductive and steric substituent constants these 3D descriptors provide a valuable insight into intramolecular steric and electronic interactions and can find broad application in structure-activity studies. Possible interpretation of physical meaning of the inductive descriptors has been suggested by considering a neutral molecule as an electrical capacitor formed by charged atomic spheres. This approximation relates inductive chemical softness and hardness of bound atom(s) with the total area of the facings of electrical capacitor formed by the atom(s) and the rest of the molecule. The derived full electronegativity equalization scheme allows iterative calculation of inductive partial charges on the basis of atomic electronegativities, covalent radii, and intramolecular distances. A range of inductive descriptors has been computed for a variety of organic compounds. The calculated inductive charges in the studied molecules have been validated by experimental C-1s Electron Core Binding Energies and molecular dipole moments. Several semiempirical chemical rules, such as equalized electronegativity's arithmetic mean, principle of maximum hardness, and principle of hardness borrowing could be explicitly illustrated in the framework of the developed approach.

Uncertain decision tree inductive inference

NASA Astrophysics Data System (ADS)

Zarban, L.; Jafari, S.; Fakhrahmad, S. M.

2011-10-01

Induction is the process of reasoning in which general rules are formulated based on limited observations of recurring phenomenal patterns. Decision tree learning is one of the most widely used and practical inductive methods, which represents the results in a tree scheme. Various decision tree algorithms have already been proposed such as CLS, ID3, Assistant C4.5, REPTree and Random Tree. These algorithms suffer from some major shortcomings. In this article, after discussing the main limitations of the existing methods, we introduce a new decision tree induction algorithm, which overcomes all the problems existing in its counterparts. The new method uses bit strings and maintains important information on them. This use of bit strings and logical operation on them causes high speed during the induction process. Therefore, it has several important features: it deals with inconsistencies in data, avoids overfitting and handles uncertainty. We also illustrate more advantages and the new features of the proposed method. The experimental results show the effectiveness of the method in comparison with other methods existing in the literature.

Response to traumatic brain injury neurorehabilitation through an artificial intelligence and statistics hybrid knowledge discovery from databases methodology.

PubMed

Gibert, Karina; García-Rudolph, Alejandro; García-Molina, Alberto; Roig-Rovira, Teresa; Bernabeu, Montse; Tormos, José María

2008-01-01

Develop a classificatory tool to identify different populations of patients with Traumatic Brain Injury based on the characteristics of deficit and response to treatment. A KDD framework where first, descriptive statistics of every variable was done, data cleaning and selection of relevant variables. Then data was mined using a generalization of Clustering based on rules (CIBR), an hybrid AI and Statistics technique which combines inductive learning (AI) and clustering (Statistics). A prior Knowledge Base (KB) is considered to properly bias the clustering; semantic constraints implied by the KB hold in final clusters, guaranteeing interpretability of the resultis. A generalization (Exogenous Clustering based on rules, ECIBR) is presented, allowing to define the KB in terms of variables which will not be considered in the clustering process itself, to get more flexibility. Several tools as Class panel graph are introduced in the methodology to assist final interpretation. A set of 5 classes was recommended by the system and interpretation permitted profiles labeling. From the medical point of view, composition of classes is well corresponding with different patterns of increasing level of response to rehabilitation treatments. All the patients initially assessable conform a single group. Severe impaired patients are subdivided in four profiles which clearly distinct response patterns. Particularly interesting the partial response profile, where patients could not improve executive functions. Meaningful classes were obtained and, from a semantics point of view, the results were sensibly improved regarding classical clustering, according to our opinion that hybrid AI & Stats techniques are more powerful for KDD than pure ones.

Cross-validation and Peeling Strategies for Survival Bump Hunting using Recursive Peeling Methods

PubMed Central

Dazard, Jean-Eudes; Choe, Michael; LeBlanc, Michael; Rao, J. Sunil

2015-01-01

We introduce a framework to build a survival/risk bump hunting model with a censored time-to-event response. Our Survival Bump Hunting (SBH) method is based on a recursive peeling procedure that uses a specific survival peeling criterion derived from non/semi-parametric statistics such as the hazards-ratio, the log-rank test or the Nelson--Aalen estimator. To optimize the tuning parameter of the model and validate it, we introduce an objective function based on survival or prediction-error statistics, such as the log-rank test and the concordance error rate. We also describe two alternative cross-validation techniques adapted to the joint task of decision-rule making by recursive peeling and survival estimation. Numerical analyses show the importance of replicated cross-validation and the differences between criteria and techniques in both low and high-dimensional settings. Although several non-parametric survival models exist, none addresses the problem of directly identifying local extrema. We show how SBH efficiently estimates extreme survival/risk subgroups unlike other models. This provides an insight into the behavior of commonly used models and suggests alternatives to be adopted in practice. Finally, our SBH framework was applied to a clinical dataset. In it, we identified subsets of patients characterized by clinical and demographic covariates with a distinct extreme survival outcome, for which tailored medical interventions could be made. An R package PRIMsrc (Patient Rule Induction Method in Survival, Regression and Classification settings) is available on CRAN (Comprehensive R Archive Network) and GitHub. PMID:27034730

Evaluation Effect of Shiatsu Technique on Labor Induction in Post-Term Pregnancy

PubMed Central

Batool, Teimoori; Shahin-Dokht, Navvabi-Rigi; Shahnaz, Rajabi; Azizollah, Arbabisarjou

2015-01-01

Objective: Labor induction in post-term pregnancy is considered as a conventional process of mothers’ care. Shiatsu technique is one of the complementary methods which use for post-term pregnancy induction. Therefore, the researchers decided to examine the effect of Shiatsu technique on the induction of post-term pregnancy. Materials and Methods: This is a randomized control trials which conducted on 288 women with post-term pregnancy who referred to consulting clinic at Ali- Ibn- Abi -Talib Hospital, in Zahedan-Iran in 2010-2011. Participants were selected based on random table. The participants divided into two groups: the first was shiatsu technique and the second group was control group (routine procedure). Shiatsu technique was conducted on the participants of intervention group for 30s on three points by an experienced midwife. The gathered data analyzed by SPSS version 15.00 and comparing tests were t-students tests, chi-square. Results: Mothers ages range were between 16 to 42 yr (mean 26.5-5.7) in shiatsu and 17 to 43 yr (mean 24.5-5.1) in control group. Regarding spontaneous initiation of labor, 82 women (56.9%) in Shiatsu group had spontaneous initiation of labor, whereas the number of women was only 12 (8.3%) in control group. Women who have used Shiatsu technique were significantly more likely to have spontaneous labour than those women who did not. Conclusions: Results of the study showed that shiatsu technique can be used as one of safe complementary methods for post-term pregnancy induction. PMID:25948426

Steady-state, lumped-parameter model for capacitor-run, single-phase induction motors

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

Umans, S.D.

1996-01-01

This paper documents a technique for deriving a steady-state, lumped-parameter model for capacitor-run, single-phase induction motors. The objective of this model is to predict motor performance parameters such as torque, loss distribution, and efficiency as a function of applied voltage and motor speed as well as the temperatures of the stator windings and of the rotor. The model includes representations of both the main and auxiliary windings (including arbitrary external impedances) and also the effects of core and rotational losses. The technique can be easily implemented and the resultant model can be used in a wide variety of analyses tomore » investigate motor performance as a function of load, speed, and winding and rotor temperatures. The technique is based upon a coupled-circuit representation of the induction motor. A notable feature of the model is the technique used for representing core loss. In equivalent-circuit representations of transformers and induction motors, core loss is typically represented by a core-loss resistance in shunt with the magnetizing inductance. In order to maintain the coupled-circuit viewpoint adopted in this paper, this technique was modified slightly; core loss is represented by a set of core-loss resistances connected to the ``secondaries`` of a set of windings which perfectly couple to the air-gap flux of the motor. An example of the technique is presented based upon a 3.5 kW, single-phase, capacitor-run motor and the validity of the technique is demonstrated by comparing predicted and measured motor performance.« less

Passive acquisition of CLIPS rules

NASA Technical Reports Server (NTRS)

Kovarik, Vincent J., Jr.

1991-01-01

The automated acquisition of knowledge by machine has not lived up to expectations, and knowledge engineering remains a human intensive task. Part of the reason for the lack of success is the difference in the cognitive focus of the expert. The expert must shift his or her focus from the subject domain to that of the representation environment. In doing so this cognitive shift introduces opportunity for errors and omissions. Presented here is work that observes the expert interact with a simulation of the domain. The system logs changes in the simulation objects and the expert's actions in response to those changes. This is followed by the application of inductive reasoning to move the domain specific rules observed to general domain rules.

Stepfamily Communication Strengths: Understanding the Ties That Bind.

ERIC Educational Resources Information Center

Golish, Tamara D.

2003-01-01

Examines the communication strategies that differentiate "strong" stepfamilies from stepfamilies having more difficulty, inductively deriving a composite of stepfamily "communication strengths." Finds that in general, strong stepfamilies reported using everyday talk, more openness, spending time together as a family, communicating clear rules and…

Experiments and Demonstrations in Physics: Bar-Ilan Physics Laboratory (2nd Edition)

NASA Astrophysics Data System (ADS)

Kraftmakher, Yaakov

2014-08-01

The following sections are included: * Data-acquisition systems from PASCO * ScienceWorkshop 750 Interface and DataStudio software * 850 Universal Interface and Capstone software * Mass on spring * Torsional pendulum * Hooke's law * Characteristics of DC source * Digital storage oscilloscope * Charging and discharging a capacitor * Charge and energy stored in a capacitor * Speed of sound in air * Lissajous patterns * I-V characteristics * Light bulb * Short time intervals * Temperature measurements * Oersted's great discovery * Magnetic field measurements * Magnetic force * Magnetic braking * Curie's point I * Electric power in AC circuits * Faraday's law of induction I * Self-inductance and mutual inductance * Electromagnetic screening * LCR circuit I * Coupled LCR circuits * Probability functions * Photometric laws * Kirchhoff's rule for thermal radiation * Malus' law * Infrared radiation * Irradiance and illuminance

The diversity effect of inductive reasoning under segment manipulation of complex cognition.

PubMed

Chen, Antao; Li, Hong; Feng, Tingyong; Gao, Xuemei; Zhang, Zhongming; Li, Fuhong; Yang, Dong

2005-12-01

The present study proposed the idea of segment manipulation of complex cognition (SMCC), and technically made it possible the quantitative treatment and systematical manipulation on the premise diversity. The segment manipulation of complex cognition divides the previous inductive strengths judgment task into three distinct steps, attempting to particularly distinguish the psychological processes and their rules. The results in Experiment 1 showed that compared with the traditional method, the quantitative treatment and systematical manipulation of SMCC on the diversity did not change the task's nature, and remain rational and a good measurement of inductive strength judgment. The results in Experiment 2 showed that the participants' response rules in the triple-step task were expected from our proposal, and that in Step 2 the "feeling of surprise" (FOS), which seems implausible but predicted from the diversity premises, was measured, and its component might be the critical part that produced the diversity effect. The "feeling of surprise" may reflect the impact of emotion on cognition, representing a strong revision to premise probability principle of pure rational hypothesis proposed by Lo et al., and its roles in the diversity effect are worthy of further research. In this regards were discussed the mistakes that the premise probability principle makes when it takes posterity probability as prior probability.

Use of an expert system data analysis manager for space shuttle main engine test evaluation

NASA Technical Reports Server (NTRS)

Abernethy, Ken

1988-01-01

The ability to articulate, collect, and automate the application of the expertise needed for the analysis of space shuttle main engine (SSME) test data would be of great benefit to NASA liquid rocket engine experts. This paper describes a project whose goal is to build a rule-based expert system which incorporates such expertise. Experiential expertise, collected directly from the experts currently involved in SSME data analysis, is used to build a rule base to identify engine anomalies similar to those analyzed previously. Additionally, an alternate method of expertise capture is being explored. This method would generate rules inductively based on calculations made using a theoretical model of the SSME's operation. The latter rules would be capable of diagnosing anomalies which may not have appeared before, but whose effects can be predicted by the theoretical model.

Structural knowledge learning from maps for supervised land cover/use classification: Application to the monitoring of land cover/use maps in French Guiana

NASA Astrophysics Data System (ADS)

Bayoudh, Meriam; Roux, Emmanuel; Richard, Gilles; Nock, Richard

2015-03-01

The number of satellites and sensors devoted to Earth observation has become increasingly elevated, delivering extensive data, especially images. At the same time, the access to such data and the tools needed to process them has considerably improved. In the presence of such data flow, we need automatic image interpretation methods, especially when it comes to the monitoring and prediction of environmental and societal changes in highly dynamic socio-environmental contexts. This could be accomplished via artificial intelligence. The concept described here relies on the induction of classification rules that explicitly take into account structural knowledge, using Aleph, an Inductive Logic Programming (ILP) system, combined with a multi-class classification procedure. This methodology was used to monitor changes in land cover/use of the French Guiana coastline. One hundred and fifty-eight classification rules were induced from 3 diachronic land cover/use maps including 38 classes. These rules were expressed in first order logic language, which makes them easily understandable by non-experts. A 10-fold cross-validation gave significant average values of 84.62%, 99.57% and 77.22% for classification accuracy, specificity and sensitivity, respectively. Our methodology could be beneficial to automatically classify new objects and to facilitate object-based classification procedures.

Efficient Power Network Analysis with Modeling of Inductive Effects

NASA Astrophysics Data System (ADS)

Zeng, Shan; Yu, Wenjian; Hong, Xianlong; Cheng, Chung-Kuan

In this paper, an efficient method is proposed to accurately analyze large-scale power/ground (P/G) networks, where inductive parasitics are modeled with the partial reluctance. The method is based on frequency-domain circuit analysis and the technique of vector fitting [14], and obtains the time-domain voltage response at given P/G nodes. The frequency-domain circuit equation including partial reluctances is derived, and then solved with the GMRES algorithm with rescaling, preconditioning and recycling techniques. With the merit of sparsified reluctance matrix and iterative solving techniques for the frequency-domain circuit equations, the proposed method is able to handle large-scale P/G networks with complete inductive modeling. Numerical results show that the proposed method is orders of magnitude faster than HSPICE, several times faster than INDUCTWISE [4], and capable of handling the inductive P/G structures with more than 100, 000 wire segments.

A Modified Rule of Thumb for Evaluating Scale Reproducibilities Determined by Electronic Computers

ERIC Educational Resources Information Center

Hofmann, Richard J.

1978-01-01

The Goodenough technique for determining scale error is compared to the Guttman technique and demonstrated to be more conservative than the Guttman technique. Implications with regard to Guttman's evaluative rule of thumb for evaluating a reproducibility are noted. (Author)

Automated Induction Of Rule-Based Neural Networks

NASA Technical Reports Server (NTRS)

Smyth, Padhraic J.; Goodman, Rodney M.

1994-01-01

Prototype expert systems implemented in software and are functionally equivalent to neural networks set up automatically and placed into operation within minutes following information-theoretic approach to automated acquisition of knowledge from large example data bases. Approach based largely on use of ITRULE computer program.

Modifications to the Patient Rule-Induction Method that utilize non-additive combinations of genetic and environmental effects to define partitions that predict ischemic heart disease.

PubMed

Dyson, Greg; Frikke-Schmidt, Ruth; Nordestgaard, Børge G; Tybjaerg-Hansen, Anne; Sing, Charles F

2009-05-01

This article extends the Patient Rule-Induction Method (PRIM) for modeling cumulative incidence of disease developed by Dyson et al. (Genet Epidemiol 31:515-527) to include the simultaneous consideration of non-additive combinations of predictor variables, a significance test of each combination, an adjustment for multiple testing and a confidence interval for the estimate of the cumulative incidence of disease in each partition. We employ the partitioning algorithm component of the Combinatorial Partitioning Method to construct combinations of predictors, permutation testing to assess the significance of each combination, theoretical arguments for incorporating a multiple testing adjustment and bootstrap resampling to produce the confidence intervals. An illustration of this revised PRIM utilizing a sample of 2,258 European male participants from the Copenhagen City Heart Study is presented that assesses the utility of genetic variants in predicting the presence of ischemic heart disease beyond the established risk factors.

Modifications to the Patient Rule-Induction Method that utilize non-additive combinations of genetic and environmental effects to define partitions that predict ischemic heart disease

PubMed Central

Dyson, Greg; Frikke-Schmidt, Ruth; Nordestgaard, Børge G.; Tybjærg-Hansen, Anne; Sing, Charles F.

2009-01-01

This paper extends the Patient Rule-Induction Method (PRIM) for modeling cumulative incidence of disease developed by Dyson et al. (2007) to include the simultaneous consideration of non-additive combinations of predictor variables, a significance test of each combination, an adjustment for multiple testing and a confidence interval for the estimate of the cumulative incidence of disease in each partition. We employ the partitioning algorithm component of the Combinatorial Partitioning Method (CPM) to construct combinations of predictors, permutation testing to assess the significance of each combination, theoretical arguments for incorporating a multiple testing adjustment and bootstrap resampling to produce the confidence intervals. An illustration of this revised PRIM utilizing a sample of 2258 European male participants from the Copenhagen City Heart Study is presented that assesses the utility of genetic variants in predicting the presence of ischemic heart disease beyond the established risk factors. PMID:19025787

Knowledge Discovery in Variant Databases Using Inductive Logic Programming

PubMed Central

Nguyen, Hoan; Luu, Tien-Dao; Poch, Olivier; Thompson, Julie D.

2013-01-01

Understanding the effects of genetic variation on the phenotype of an individual is a major goal of biomedical research, especially for the development of diagnostics and effective therapeutic solutions. In this work, we describe the use of a recent knowledge discovery from database (KDD) approach using inductive logic programming (ILP) to automatically extract knowledge about human monogenic diseases. We extracted background knowledge from MSV3d, a database of all human missense variants mapped to 3D protein structure. In this study, we identified 8,117 mutations in 805 proteins with known three-dimensional structures that were known to be involved in human monogenic disease. Our results help to improve our understanding of the relationships between structural, functional or evolutionary features and deleterious mutations. Our inferred rules can also be applied to predict the impact of any single amino acid replacement on the function of a protein. The interpretable rules are available at http://decrypthon.igbmc.fr/kd4v/. PMID:23589683

Knowledge discovery in variant databases using inductive logic programming.

PubMed

Nguyen, Hoan; Luu, Tien-Dao; Poch, Olivier; Thompson, Julie D

2013-01-01

Understanding the effects of genetic variation on the phenotype of an individual is a major goal of biomedical research, especially for the development of diagnostics and effective therapeutic solutions. In this work, we describe the use of a recent knowledge discovery from database (KDD) approach using inductive logic programming (ILP) to automatically extract knowledge about human monogenic diseases. We extracted background knowledge from MSV3d, a database of all human missense variants mapped to 3D protein structure. In this study, we identified 8,117 mutations in 805 proteins with known three-dimensional structures that were known to be involved in human monogenic disease. Our results help to improve our understanding of the relationships between structural, functional or evolutionary features and deleterious mutations. Our inferred rules can also be applied to predict the impact of any single amino acid replacement on the function of a protein. The interpretable rules are available at http://decrypthon.igbmc.fr/kd4v/.

Decision Tree based Prediction and Rule Induction for Groundwater Trichloroethene (TCE) Pollution Vulnerability

NASA Astrophysics Data System (ADS)

Park, J.; Yoo, K.

2013-12-01

For groundwater resource conservation, it is important to accurately assess groundwater pollution sensitivity or vulnerability. In this work, we attempted to use data mining approach to assess groundwater pollution vulnerability in a TCE (trichloroethylene) contaminated Korean industrial site. The conventional DRASTIC method failed to describe TCE sensitivity data with a poor correlation with hydrogeological properties. Among the different data mining methods such as Artificial Neural Network (ANN), Multiple Logistic Regression (MLR), Case Base Reasoning (CBR), and Decision Tree (DT), the accuracy and consistency of Decision Tree (DT) was the best. According to the following tree analyses with the optimal DT model, the failure of the conventional DRASTIC method in fitting with TCE sensitivity data may be due to the use of inaccurate weight values of hydrogeological parameters for the study site. These findings provide a proof of concept that DT based data mining approach can be used in predicting and rule induction of groundwater TCE sensitivity without pre-existing information on weights of hydrogeological properties.

Tennis-Badminton-Squash Guide with Official Rules. June 1972 - June 1974.

ERIC Educational Resources Information Center

Knight, Martha, Ed.; And Others

Rules in tennis, badminton, and squash for girls and women from June 1972 - June 1974 are discussed. Standards in the sports are detailed along with the Division for Girls and Women's Sports (DGWS) statement of beliefs. Specific articles dealing with teaching techniques, officiating techniques, and rules for tennis and badminton are presented.…

Highly scalable and robust rule learner: performance evaluation and comparison.

PubMed

Kurgan, Lukasz A; Cios, Krzysztof J; Dick, Scott

2006-02-01

Business intelligence and bioinformatics applications increasingly require the mining of datasets consisting of millions of data points, or crafting real-time enterprise-level decision support systems for large corporations and drug companies. In all cases, there needs to be an underlying data mining system, and this mining system must be highly scalable. To this end, we describe a new rule learner called DataSqueezer. The learner belongs to the family of inductive supervised rule extraction algorithms. DataSqueezer is a simple, greedy, rule builder that generates a set of production rules from labeled input data. In spite of its relative simplicity, DataSqueezer is a very effective learner. The rules generated by the algorithm are compact, comprehensible, and have accuracy comparable to rules generated by other state-of-the-art rule extraction algorithms. The main advantages of DataSqueezer are very high efficiency, and missing data resistance. DataSqueezer exhibits log-linear asymptotic complexity with the number of training examples, and it is faster than other state-of-the-art rule learners. The learner is also robust to large quantities of missing data, as verified by extensive experimental comparison with the other learners. DataSqueezer is thus well suited to modern data mining and business intelligence tasks, which commonly involve huge datasets with a large fraction of missing data.

How to heat up from the cold: examining the preconditions for (unconscious) mood effects.

PubMed

Ruys, Kirsten I; Stapel, Diederik A

2008-05-01

What are the necessary preconditions to make people feel good or bad? In this research, the authors aimed to uncover the bare essentials of mood induction. Several induction techniques exist, and most of these techniques demand a relatively high amount of cognitive capacity. Moreover, to be effective, most techniques require conscious awareness. The authors proposed that the common and defining element in all effective mood induction techniques is the dominating salience of evaluative tone over descriptive meaning. This evaluative-tone hypothesis was tested in two paradigms in which the evaluative meaning of the "primed" concept was more salient than its descriptive meaning (i.e., when subliminal stimulus exposure was so short that mainly the evaluative meaning was activated [see D. A. Stapel, W. Koomen, & K. I. Ruys, 2002] and when the primed concepts were sufficiently extreme such that evaluative meaning always dominated descriptive meaning). Explicit and implicit mood measures showed that the activation of a dominating evaluative tone affected people's mood states. Implications of these findings for theories on unconscious mood induction are discussed. (c) 2008 APA, all rights reserved

Application of Electromagnetic Induction Technique to Measure the Void Fraction in Oil/Gas Two Phase Flow

NASA Astrophysics Data System (ADS)

Wahhab, H. A. Abdul; Aziz, A. R. A.; Al-Kayiem, H. H.; Nasif, M. S.; Reda, M. N.

2018-03-01

In this work, electromagnetic induction technique of measuring void fraction in liquid/gas fuel flow was utilized. In order to improve the electric properties of liquid fuel, an iron oxide Fe3O4 nanoparticles at 3% was blended to enhance the liquid fuel magnetization. Experiments have been conducted for a wide range of liquid and gas superficial velocities. From the experimental results, it was realized that there is an existing linear relationship between the void fraction and the measured electromotive force, when induction coils were connected in series for excitation coils, regardless of increase or decrease CNG bubbles distribution in liquid fuel flow. Therefore, it was revealed that the utilized method yielded quite reasonable account for measuring the void fraction, showing good agreement with the other available measurement techniques in the two-phase flow, and also with the published literature of the bubbly flow pattern. From the results of the present investigation, it has been proven that the electromagnetic induction is a feasible technique for the actual measurement of void fraction in a Diesel/CNG fuel flow.

The seats of reason? An imaging study of deductive and inductive reasoning.

PubMed

Goel, V; Gold, B; Kapur, S; Houle, S

1997-03-24

We carried out a neuroimaging study to test the neurophysiological predictions made by different cognitive models of reasoning. Ten normal volunteers performed deductive and inductive reasoning tasks while their regional cerebral blood flow pattern was recorded using [15O]H2O PET imaging. In the control condition subjects semantically comprehended sets of three sentences. In the deductive reasoning condition subjects determined whether the third sentence was entailed by the first two sentences. In the inductive reasoning condition subjects reported whether the third sentence was plausible given the first two sentences. The deduction condition resulted in activation of the left inferior frontal gyrus (Brodmann areas 45, 47). The induction condition resulted in activation of a large area comprised of the left medial frontal gyrus, the left cingulate gyrus, and the left superior frontal gyrus (Brodmann areas 8, 9, 24, 32). Induction was distinguished from deduction by the involvement of the medial aspect of the left superior frontal gyrus (Brodmann areas 8, 9). These results are consistent with cognitive models of reasoning that postulate different mechanisms for inductive and deductive reasoning and view deduction as a formal rule-based process.

The Interplay of Externalizing Problems and Physical and Inductive Discipline during Childhood

PubMed Central

Choe, Daniel Ewon; Olson, Sheryl L.; Sameroff, Arnold J.

2013-01-01

Children who are physically disciplined are at elevated risk for externalizing problems. Conversely, maternal reasoning and reminding of rules, or inductive discipline, is associated with fewer child externalizing problems. Few studies have simultaneously examined bidirectional associations between these forms of discipline and child adjustment using cross-informant, multi-method data. We hypothesized that less inductive and more physical discipline would predict more externalizing problems, children would have evocative effects on parenting, and high levels of either form of discipline would predict low levels of the other. In a study of 241 children–spanning ages 3, 5.5, and 10–structural equation modeling indicated that 3-year-olds with higher teacher ratings of externalizing problems received higher mother ratings of physical discipline at age 5.5. Mothers endorsing more inductive discipline at child age 3 reported less physical discipline and had children with fewer externalizing problems at age 5.5. Negative bidirectional associations emerged between physical and inductive discipline from ages 5.5 to 10. Findings suggested children’s externalizing problems elicited physical discipline, and maternal inductive discipline might help prevent externalizing problems and physical discipline. PMID:23458660

Identifying Kinds of Reasoning in Collective Argumentation

ERIC Educational Resources Information Center

Conner, AnnaMarie; Singletary, Laura M.; Smith, Ryan C.; Wagner, Patty Anne; Francisco, Richard T.

2014-01-01

We combine Peirce's rule, case, and result with Toulmin's data, claim, and warrant to differentiate between deductive, inductive, abductive, and analogical reasoning within collective argumentation. In this theoretical article, we illustrate these kinds of reasoning in episodes of collective argumentation using examples from one…

Toward a Unified Theory of Human Reasoning.

ERIC Educational Resources Information Center

Sternberg, Robert J.

1986-01-01

The goal of this unified theory of human reasoning is to specify what constitutes reasoning and to characterize the psychological distinction between inductive and deductive reasoning. The theory views reasoning as the controlled and mediated application of three processes (encoding, comparison and selective combination) to inferential rules. (JAZ)

49 CFR 236.562 - Minimum rail current required.

Code of Federal Regulations, 2011 CFR

2011-10-01

..., INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Rules and Instructions; Locomotives § 236.562 Minimum... continuous inductive automatic train stop or train control device to normal condition or to obtain a proceed...

49 CFR 236.562 - Minimum rail current required.

Code of Federal Regulations, 2010 CFR

2010-10-01

..., INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Rules and Instructions; Locomotives § 236.562 Minimum... continuous inductive automatic train stop or train control device to normal condition or to obtain a proceed...

Rational identification of aggregation hotspots based on secondary structure and amino acid hydrophobicity.

PubMed

Matsui, Daisuke; Nakano, Shogo; Dadashipour, Mohammad; Asano, Yasuhisa

2017-08-25

Insolubility of proteins expressed in the Escherichia coli expression system hinders the progress of both basic and applied research. Insoluble proteins contain residues that decrease their solubility (aggregation hotspots). Mutating these hotspots to optimal amino acids is expected to improve protein solubility. To date, however, the identification of these hotspots has proven difficult. In this study, using a combination of approaches involving directed evolution and primary sequence analysis, we found two rules to help inductively identify hotspots: the α-helix rule, which focuses on the hydrophobicity of amino acids in the α-helix structure, and the hydropathy contradiction rule, which focuses on the difference in hydrophobicity relative to the corresponding amino acid in the consensus protein. By properly applying these two rules, we succeeded in improving the probability that expressed proteins would be soluble. Our methods should facilitate research on various insoluble proteins that were previously difficult to study due to their low solubility.

Data mining and visualization techniques

DOEpatents

Wong, Pak Chung [Richland, WA; Whitney, Paul [Richland, WA; Thomas, Jim [Richland, WA

2004-03-23

Disclosed are association rule identification and visualization methods, systems, and apparatus. An association rule in data mining is an implication of the form X.fwdarw.Y where X is a set of antecedent items and Y is the consequent item. A unique visualization technique that provides multiple antecedent, consequent, confidence, and support information is disclosed to facilitate better presentation of large quantities of complex association rules.

Factors of Compliance of a Child with Rules in a Russian Cultural Context

ERIC Educational Resources Information Center

Bayanova, Larisa F.; Mustafin, Timur R.

2016-01-01

The article covers the analysis of the child's psychology compliance with culture rules--the cultural congruence. The description of the technique aimed to detect the cultural congruence of five- to six-year-old children is presented. The technique is made on the basis of the revealed range of rules of a child's and adult's interaction in a social…

Micro-size antenna structure with vertical nanowires for wireless power transmission and communication.

PubMed

Kang, Jong-Gu; Jeong, Yeri; Shin, Jeong Hee; Choi, Ji-Woong; Sohn, Jung Inn; Cha, Seung Nam; Jang, Jae Eun

2014-11-01

For biomedical implanted devices, a wireless power or a signal transmission is essential to protect an infection and to enhance durability. In this study, we present a magnetic induction technique for a power transmission without any wire connection between transmitter (Tx) and receiver (Rx) in a micro scale. Due to a micro size effect of a flat spiral coil, a magnetic inductance is not high. To enhance the magnetic inductance, a three dimensional magnetic core is added to an antenna structure, which is consisted of ZnO nano wires coated by a nickel (Ni) layer. ZnO nano wires easily supply a large effective surface area with a vertical structural effect to the magnetic core structure, which induces a higher magnetic inductance with a ferro-magnetic material Ni. The magnetic induction antenna with the magnetic core shows a high inductance value, a low reflection power and a strong power transmission. The power transmission efficiencies are tested under the air and the water medium are almost the same values, so that the magnetic induction technique is quite proper to body implanted systems.

Traditional versus rule-based programming techniques: Application to the control of optional flight information

NASA Technical Reports Server (NTRS)

Ricks, Wendell R.; Abbott, Kathy H.

1987-01-01

To the software design community, the concern over the costs associated with a program's execution time and implementation is great. It is always desirable, and sometimes imperative, that the proper programming technique is chosen which minimizes all costs for a given application or type of application. A study is described that compared cost-related factors associated with traditional programming techniques to rule-based programming techniques for a specific application. The results of this study favored the traditional approach regarding execution efficiency, but favored the rule-based approach regarding programmer productivity (implementation ease). Although this study examined a specific application, the results should be widely applicable.

Electrical termination techniques

NASA Technical Reports Server (NTRS)

Oakey, W. E.; Schleicher, R. R.

1976-01-01

A technical review of high reliability electrical terminations for electronic equipment was made. Seven techniques were selected from this review for further investigation, experimental work, and preliminary testing. From the preliminary test results, four techniques were selected for final testing and evaluation. These four were: (1) induction soldering, (2) wire wrap, (3) percussive arc welding, and (4) resistance welding. Of these four, induction soldering was selected as the best technique in terms of minimizing operator errors, controlling temperature and time, minimizing joint contamination, and ultimately producing a reliable, uniform, and reusable electrical termination.

Scaffold hopping in drug discovery using inductive logic programming.

PubMed

Tsunoyama, Kazuhisa; Amini, Ata; Sternberg, Michael J E; Muggleton, Stephen H

2008-05-01

In chemoinformatics, searching for compounds which are structurally diverse and share a biological activity is called scaffold hopping. Scaffold hopping is important since it can be used to obtain alternative structures when the compound under development has unexpected side-effects. Pharmaceutical companies use scaffold hopping when they wish to circumvent prior patents for targets of interest. We propose a new method for scaffold hopping using inductive logic programming (ILP). ILP uses the observed spatial relationships between pharmacophore types in pretested active and inactive compounds and learns human-readable rules describing the diverse structures of active compounds. The ILP-based scaffold hopping method is compared to two previous algorithms (chemically advanced template search, CATS, and CATS3D) on 10 data sets with diverse scaffolds. The comparison shows that the ILP-based method is significantly better than random selection while the other two algorithms are not. In addition, the ILP-based method retrieves new active scaffolds which were not found by CATS and CATS3D. The results show that the ILP-based method is at least as good as the other methods in this study. ILP produces human-readable rules, which makes it possible to identify the three-dimensional features that lead to scaffold hopping. A minor variant of a rule learnt by ILP for scaffold hopping was subsequently found to cover an inhibitor identified by an independent study. This provides a successful result in a blind trial of the effectiveness of ILP to generate rules for scaffold hopping. We conclude that ILP provides a valuable new approach for scaffold hopping.

Quantitative structure-activity relationships by neural networks and inductive logic programming. II. The inhibition of dihydrofolate reductase by triazines

NASA Astrophysics Data System (ADS)

Hirst, Jonathan D.; King, Ross D.; Sternberg, Michael J. E.

1994-08-01

One of the largest available data sets for developing a quantitative structure-activity relationship (QSAR) — the inhibition of dihydrofolate reductase (DHFR) by 2,4-diamino-6,6-dimethyl-5-phenyl-dihydrotriazine derivatives — has been used for a sixfold cross-validation trial of neural networks, inductive logic programming (ILP) and linear regression. No statistically significant difference was found between the predictive capabilities of the methods. However, the representation of molecules by attributes, which is integral to the ILP approach, provides understandable rules about drug-receptor interactions.

10 CFR 431.12 - Definitions.

Code of Federal Regulations, 2011 CFR

2011-01-01

...) Standard 112-1996, Test Procedure for Polyphase Induction Motors and Generators, and Test Method (1) of CSA... a system, that has its own rules of procedure and management, for giving written assurance that a... operated by an entity independent of both the party seeking the written assurance and the party providing...

10 CFR 431.12 - Definitions.

Code of Federal Regulations, 2012 CFR

2012-01-01

...) Standard 112-1996, Test Procedure for Polyphase Induction Motors and Generators, and Test Method (1) of CSA... a system, that has its own rules of procedure and management, for giving written assurance that a... operated by an entity independent of both the party seeking the written assurance and the party providing...

75 FR 31288 - Plant-Verified Drop Shipment (PVDS)-Nonpostal Documentation

Federal Register 2010, 2011, 2012, 2013, 2014

2010-06-03

... POSTAL SERVICE 39 CFR Part 111 Plant-Verified Drop Shipment (PVDS)--Nonpostal Documentation AGENCY... 8125, Plant-Verified Drop Shipment (PVDS) Verification and Clearance, is the sole source of evidence... induction points of plant-verified drop shipment mailings, the Postal Service is adopting this final rule to...

Data Mining in Health and Medical Information.

ERIC Educational Resources Information Center

Bath, Peter A.

2004-01-01

Presents a literature review that covers the following topics related to data mining (DM) in health and medical information: the potential of DM in health and medicine; statistical methods; evaluation of methods; DM tools for health and medicine; inductive learning of symbolic rules; application of DM tools in diagnosis and prognosis; and…

The Relevance of AI Research to CAI.

ERIC Educational Resources Information Center

Kearsley, Greg P.

This article provides a tutorial introduction to Artificial Intelligence (AI) research for those involved in Computer Assisted Instruction (CAI). The general theme is that much of the current work in AI, particularly in the areas of natural language understanding systems, rule induction, programming languages, and socratic systems, has important…

The ABCs of Writing a Technical Glossary.

ERIC Educational Resources Information Center

Gray, Evie; Ingram, William; Bodson, Dennis

1998-01-01

Explains format, style rules, and lexicographic conventions that improve clarity and precision in a technical glossary. Discusses general rules, rules of style, rules of grammar and syntax, and rules for figures. Describes the computer display techniques and file management system used to develop such a glossary. (SR)

Design of a Low-Energy FARAD Thruster

NASA Technical Reports Server (NTRS)

Polzin, K. A.; Rose, M. F.; Miller, R.; Best, S.; Owens, T.; Dankanich, J.

2007-01-01

The design of an electrodeless thruster that relies on a pulsed, rf-assisted discharge and electromagnetic acceleration using an inductive coil is presented. The thruster design is optimized using known performance,scaling parameters, and experimentally-determined design rules, with design targets for discharge energy, plasma exhaust velocity; and thrust efficiency of 100 J/pulse, 25 km/s, and 50%, respectively. Propellant is injected using a high-speed gas valve and preionized by a pulsed-RF signal supplied by a vector inversion generator, allowing for current sheet formation at lower discharge voltages and energies relative to pulsed inductive accelerators that do not employ preionization. The acceleration coil is designed to possess an inductance of at least 700 nH while the target stray (non-coil) inductance in the circuit is 70 nH. A Bernardes and Merryman pulsed power train or a pulse compression power train provide current to the acceleration coil and solid-state components are used to switch both powertrains.

CARIBIAM: constrained Association Rules using Interactive Biological IncrementAl Mining.

PubMed

Rahal, Imad; Rahhal, Riad; Wang, Baoying; Perrizo, William

2008-01-01

This paper analyses annotated genome data by applying a very central data-mining technique known as Association Rule Mining (ARM) with the aim of discovering rules and hypotheses capable of yielding deeper insights into this type of data. In the literature, ARM has been noted for producing an overwhelming number of rules. This work proposes a new technique capable of using domain knowledge in the form of queries in order to efficiently mine only the subset of the associations that are of interest to investigators in an incremental and interactive manner.

[Mood induction procedures: a critical review].

PubMed

Gilet, A-L

2008-06-01

For a long period in the history of psychological research, emotion and cognition have been studied independently, as if one were irrelevant to the other. The renewed interest of researchers for the study of the relations between cognition and emotion has led to the development of a range of laboratory methods for inducing temporary mood states. This paper aims to review the main mood induction procedures allowing the induction of a negative mood as well as a positive mood, developed since the pioneer study of Schachter and Singer [Psychol Rev 69 (1962) 379-399] and to account for the usefulness and problems related to the use of such techniques. The first part of this paper deals with the detailed presentation of some of the most popular mood induction procedures according to their type: simple (use of only one mood induction technique) or combined (association of two or more techniques at once). The earliest of the modern techniques is the Velten Mood Induction Procedure [Behav Res Ther 6 (1968) 473-482], which involves reading aloud sixty self-referent statements progressing from relative neutral mood to negative mood or dysphoria. Some researchers have varied the procedure slightly by changing the number of the statements [Behav Res Ther 21 (1983) 233-239, Br J Clin Psychol 21 (1982) 111-117, J Pers Soc Psychol 35 (1977) 625-636]. Various other mood induction procedures have been developed including music induction [Cogn Emotion 11 (1997) 403-432, Br J Med Psychol 55 (1982) 127-138], film clip induction [J Pers Soc Psychol 20 (1971) 37-43, Cogn Emotion 7 (1993) 171-193, Rottenberg J, Ray RR, Gross JJ. Emotion elicitation using films. In: Coan JA, Allen JJB, editors. The handbook of emotion elicitation and assessment. New York: Oxford University Press, 2007], autobiographical recall [J Clin Psychol 36 (1980) 215-226, Jallais C. Effets des humeurs positives et négatives sur les structures de connaissances de type script. Thèse de doctorat non publiée. Université de Nantes, Nantes] or combined inductions [Gilet AL. Etude des effets des humeurs positives et négatives sur l'organisation des connaissances en mémoire sémantique. Thèse de doctorat non publiée, Université de Nantes, Nantes, J Ment Imagery 19 (1995) 133-150]. In music or film clip inductions, subjects are asked to listen or view some mood-suggestive pieces of material determined by the experimenter according to standardized music or film sets [J Ment Imagery 19 (1995) 133-150, Cogn Emotion 7 (1993) 171-193] and selected to elicit target moods. According to many authors, these two mood induction procedures seem to be among the most effective manners to induce moods [Br J Psychol 85 (1994) 55-78, Eur J Soc Psychol 26 (1996) 557-580] in an individual or in a group setting [Jallais C. Effets des humeurs positives et négatives sur les structures de connaissances de type script. Thèse de doctorat non publiée. Université de Nantes, Nantes]. As it is believed that multiple inductions contribute additively to a mood [Am Psychol 36 (1981) 129-148], researchers proposed to combine two or more techniques at the same time. Thus, the Velten Mood Induction Procedure has been successively associated with the hypnosis mood induction procedure [J Pers Soc Psychol 42 (1982) 927-934], the music mood induction procedure [Behav Res Ther 21 (1983) 233-239, J Exp Soc Psychol 26 (1990) 465-480] or the imagination mood induction procedure [Br J Clin Psychol 21 (1982) 111-117]. Successful combinations of inductions usually use a first induction that occupies foreground attention and a second one that contributes to congruent background atmosphere. One of the most successful combined mood induction procedures has been developed by Mayer, Allen and Beauregard [J Ment Imagery 19 (1995) 133-150]. This technique associates guided imagery with music and is supposed to increase effectiveness of the induction. In the second part of this paper the aim is to present the usefulness of mood induction procedures in the study of cognitive processes in depression [Clin Psychol Rev 25 (2005) 487-510], borderline personality disorder [J Behav Ther Exp Psychiatry 36 (2005) 226-239] or associated with brain imaging [Am J Psychiatry 161 (2004) 2245-2256]. Then the inherent problems to the use of experimental mood induction procedures are reconsidered. Doubts have effectively arisen about the effectiveness and validity of the mood induction procedures usually used in research. Some authors questioned whether a sufficient intensity of mood is produced or the possibility that the effects observed are due mainly to demand effects [Br J Psychol 85 (1994) 55-78, Clin Psychol Rev 10 (1990) 669-697, Eur J Soc Psychol 26 (1996) 557-580]. In fact, the various mood induction procedures are not equal with regard to the demand effects observed. The question of demand characteristics with respect to mood induction procedures is still under debate, even if demand effects are supposed to be most likely to occur with self-statement techniques (especially with the Velten mood induction procedure) or when subjects are explicitly instructed to try to enter a specific mood state [Eur J Soc Psychol 26 (1996) 557-580]. Another interrogation relates to the effectiveness of these various procedures of induction and the duration of induced moods. Generally, the various techniques used produce true changes of moods in the majority if not the whole of the subjects. However, certain procedures seem more effective in inducing a mood in particular [Br J Psychol 85 (1994) 55-78, Clin Psychol Rev 10 (1990) 669-697, Eur J Soc Psychol 26 (1996) 557-580]. As for the duration of induced moods this depends at the same time on the procedure used and the mood induced. Nevertheless, mood induction remains fundamental in the study of the effects of mood on the cognitive activities, insofar as it makes it possible to study the effects of negative as well as positive moods.

The performance of non-invasive tests to rule-in and rule-out significant coronary artery stenosis in patients with stable angina: a meta-analysis focused on post-test disease probability.

PubMed

Knuuti, Juhani; Ballo, Haitham; Juarez-Orozco, Luis Eduardo; Saraste, Antti; Kolh, Philippe; Rutjes, Anne Wilhelmina Saskia; Jüni, Peter; Windecker, Stephan; Bax, Jeroen J; Wijns, William

2018-05-29

To determine the ranges of pre-test probability (PTP) of coronary artery disease (CAD) in which stress electrocardiogram (ECG), stress echocardiography, coronary computed tomography angiography (CCTA), single-photon emission computed tomography (SPECT), positron emission tomography (PET), and cardiac magnetic resonance (CMR) can reclassify patients into a post-test probability that defines (>85%) or excludes (<15%) anatomically (defined by visual evaluation of invasive coronary angiography [ICA]) and functionally (defined by a fractional flow reserve [FFR] ≤0.8) significant CAD. A broad search in electronic databases until August 2017 was performed. Studies on the aforementioned techniques in >100 patients with stable CAD that utilized either ICA or ICA with FFR measurement as reference, were included. Study-level data was pooled using a hierarchical bivariate random-effects model and likelihood ratios were obtained for each technique. The PTP ranges for each technique to rule-in or rule-out significant CAD were defined. A total of 28 664 patients from 132 studies that used ICA as reference and 4131 from 23 studies using FFR, were analysed. Stress ECG can rule-in and rule-out anatomically significant CAD only when PTP is ≥80% (76-83) and ≤19% (15-25), respectively. Coronary computed tomography angiography is able to rule-in anatomic CAD at a PTP ≥58% (45-70) and rule-out at a PTP ≤80% (65-94). The corresponding PTP values for functionally significant CAD were ≥75% (67-83) and ≤57% (40-72) for CCTA, and ≥71% (59-81) and ≤27 (24-31) for ICA, demonstrating poorer performance of anatomic imaging against FFR. In contrast, functional imaging techniques (PET, stress CMR, and SPECT) are able to rule-in functionally significant CAD when PTP is ≥46-59% and rule-out when PTP is ≤34-57%. The various diagnostic modalities have different optimal performance ranges for the detection of anatomically and functionally significant CAD. Stress ECG appears to have very limited diagnostic power. The selection of a diagnostic technique for any given patient to rule-in or rule-out CAD should be based on the optimal PTP range for each test and on the assumed reference standard.

Inductance Calculations of Variable Pitch Helical Inductors

DTIC Science & Technology

2015-08-01

8217 ’ Integral solution using Simpson’s Rule ’ Dim i As Integer Dim Pi As Double, uo As Double, kc As Double Dim a As Double, amax As Double, da As...Double Dim steps As Integer Dim func1a As Double, func1b As Double ’ On Error GoTo err_TorisV1 steps = 1000 Pi = 3.14159 uo = 4 * Pi * 0.0000001...As Double ’ ’ Integral solution using Simpson’s Rule ’ Dim i As Integer Dim Pi As Double, uo As Double, kc As Double Dim a As Double, amax As

A rough set-based association rule approach implemented on a brand trust evaluation model

NASA Astrophysics Data System (ADS)

Liao, Shu-Hsien; Chen, Yin-Ju

2017-09-01

In commerce, businesses use branding to differentiate their product and service offerings from those of their competitors. The brand incorporates a set of product or service features that are associated with that particular brand name and identifies the product/service segmentation in the market. This study proposes a new data mining approach, a rough set-based association rule induction, implemented on a brand trust evaluation model. In addition, it presents as one way to deal with data uncertainty to analyse ratio scale data, while creating predictive if-then rules that generalise data values to the retail region. As such, this study uses the analysis of algorithms to find alcoholic beverages brand trust recall. Finally, discussions and conclusion are presented for further managerial implications.

Evaluation and Selection of Best Priority Sequencing Rule in Job Shop Scheduling using Hybrid MCDM Technique

NASA Astrophysics Data System (ADS)

Kiran Kumar, Kalla; Nagaraju, Dega; Gayathri, S.; Narayanan, S.

2017-05-01

Priority Sequencing Rules provide the guidance for the order in which the jobs are to be processed at a workstation. The application of different priority rules in job shop scheduling gives different order of scheduling. More experimentation needs to be conducted before a final choice is made to know the best priority sequencing rule. Hence, a comprehensive method of selecting the right choice is essential in managerial decision making perspective. This paper considers seven different priority sequencing rules in job shop scheduling. For evaluation and selection of the best priority sequencing rule, a set of eight criteria are considered. The aim of this work is to demonstrate the methodology of evaluating and selecting the best priority sequencing rule by using hybrid multi criteria decision making technique (MCDM), i.e., analytical hierarchy process (AHP) with technique for order preference by similarity to ideal solution (TOPSIS). The criteria weights are calculated by using AHP whereas the relative closeness values of all priority sequencing rules are computed based on TOPSIS with the help of data acquired from the shop floor of a manufacturing firm. Finally, from the findings of this work, the priority sequencing rules are ranked from most important to least important. The comprehensive methodology presented in this paper is very much essential for the management of a workstation to choose the best priority sequencing rule among the available alternatives for processing the jobs with maximum benefit.

Improving visibility of rear surface cracks during inductive thermography of metal plates using Autoencoder

NASA Astrophysics Data System (ADS)

Xie, Jing; Xu, Changhang; Chen, Guoming; Huang, Weiping

2018-06-01

Inductive thermography is one kind of infrared thermography (IRT) technique, which is effective in detection of front surface cracks in metal plates. However, rear surface cracks are usually missed due to their weak indications during inductive thermography. Here we propose a novel approach (AET: AE Thermography) to improve the visibility of rear surface cracks during inductive thermography by employing the Autoencoder (AE) algorithm, which is an important block to construct deep learning architectures. We construct an integrated framework for processing the raw inspection data of inductive thermography using the AE algorithm. Through this framework, underlying features of rear surface cracks are efficiently extracted and new clearer images are constructed. Experiments of inductive thermography were conducted on steel specimens to verify the efficacy of the proposed approach. We visually compare the raw thermograms, the empirical orthogonal functions (EOFs) of the prominent component thermography (PCT) technique and the results of AET. We further quantitatively evaluated AET by calculating crack contrast and signal-to-noise ratio (SNR). The results demonstrate that the proposed AET approach can remarkably improve the visibility of rear surface cracks and then improve the capability of inductive thermography in detecting rear surface cracks in metal plates.

75 FR 3163 - Vocational Rehabilitation and Employment Program-Basic Entitlement; Effective Date of Induction...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-01-20

... implemented changes to services provided under 38 U.S.C. chapter 31, which resulted from a court decision and..., for vocational rehabilitation basic entitlement determinations resulting from the Veterans' Benefits... issuing any rule that may result in the expenditure by State, local, and Tribal governments, in the...

On the Determinants of the Conjunction Fallacy: Probability versus Inductive Confirmation

ERIC Educational Resources Information Center

Tentori, Katya; Crupi, Vincenzo; Russo, Selena

2013-01-01

Major recent interpretations of the conjunction fallacy postulate that people assess the probability of a conjunction according to (non-normative) averaging rules as applied to the constituents' probabilities or represent the conjunction fallacy as an effect of random error in the judgment process. In the present contribution, we contrast such…

An Application of the Patient Rule-Induction Method for Evaluating the Contribution of the Apolipoprotein E and Lipoprotein Lipase Genes to Predicting Ischemic Heart Disease

PubMed Central

Dyson, Greg; Frikke-Schmidt, Ruth; Nordestgaard, Børge G.; Tybjærg-Hansen, Anne; Sing, Charles F.

2007-01-01

Different combinations of genetic and environmental risk factors are known to contribute to the complex etiology of ischemic heart disease (IHD) in different subsets of individuals. We employed the Patient Rule-Induction Method (PRIM) to select the combination of risk factors and risk factor values that identified each of 16 mutually exclusive partitions of individuals having significantly different levels of risk of IHD. PRIM balances two competing objectives: (1) finding partitions where the risk of IHD is high and (2) maximizing the number of IHD cases explained by the partitions. A sequential PRIM analysis was applied to data on the incidence of IHD collected over 8 years for a sample of 5,455 unrelated individuals from the Copenhagen City Heart Study (CCHS) to assess the added value of variation in two candidate susceptibility genes beyond the traditional, lipid and body mass index risk factors for IHD. An independent sample of 362 unrelated individuals also from the city of Copenhagen was used to test the model obtained for each of the hypothesized partitions. PMID:17436307

Predicting who will drop out of nursing courses: a machine learning exercise.

PubMed

Moseley, Laurence G; Mead, Donna M

2008-05-01

The concepts of causation and prediction are different, and have different implications for practice. This distinction is applied here to studies of the problem of student attrition (although it is more widely applicable). Studies of attrition from nursing courses have tended to concentrate on causation, trying, largely unsuccessfully, to elicit what causes drop out. However, the problem may more fruitfully be cast in terms of predicting who is likely to drop out. One powerful method for attempting to make predictions is rule induction. This paper reports the use of the Answer Tree package from SPSS for that purpose. The main data set consisted of 3978 records on 528 nursing students, split into a training set and a test set. The source was standard university student records. The method obtained 84% sensitivity, 70% specificity, and 94% accuracy on previously unseen cases. The method requires large amounts of high quality data. When such data are available, rule induction offers a way to reduce attrition. It would be desirable to compare its results with those of predictions made by tutors using more informal conventional methods.

Representation of molecular structure using quantum topology with inductive logic programming in structure-activity relationships.

PubMed

Buttingsrud, Bård; Ryeng, Einar; King, Ross D; Alsberg, Bjørn K

2006-06-01

The requirement of aligning each individual molecule in a data set severely limits the type of molecules which can be analysed with traditional structure activity relationship (SAR) methods. A method which solves this problem by using relations between objects is inductive logic programming (ILP). Another advantage of this methodology is its ability to include background knowledge as 1st-order logic. However, previous molecular ILP representations have not been effective in describing the electronic structure of molecules. We present a more unified and comprehensive representation based on Richard Bader's quantum topological atoms in molecules (AIM) theory where critical points in the electron density are connected through a network. AIM theory provides a wealth of chemical information about individual atoms and their bond connections enabling a more flexible and chemically relevant representation. To obtain even more relevant rules with higher coverage, we apply manual postprocessing and interpretation of ILP rules. We have tested the usefulness of the new representation in SAR modelling on classifying compounds of low/high mutagenicity and on a set of factor Xa inhibitors of high and low affinity.

Assessment of Remaining Lubricant Life

DTIC Science & Technology

1986-11-01

tioxidant, inexpensive spectrophotometers are used. However, the greatest advantage of the Mitsubishi chemical stressing technique was the fact that it uses...samples, the method’s main advantage over the thermal stressing techniques is eliminated. The colorimetric method had the advantage over induction period...decrease of 18 torr. The main advantage of defining the induction period in this manner is that it eliminates any need for interpretation by the

Predicting higher selection in elite junior Australian Rules football: The influence of physical performance and anthropometric attributes.

PubMed

Robertson, Sam; Woods, Carl; Gastin, Paul

2015-09-01

To develop a physiological performance and anthropometric attribute model to predict Australian Football League draft selection. Cross-sectional observational. Data was obtained (n=4902) from three Under-18 Australian football competitions between 2010 and 2013. Players were allocated into one of the three groups, based on their highest level of selection in their final year of junior football (Australian Football League Drafted, n=292; National Championship, n=293; State-level club, n=4317). Physiological performance (vertical jumps, agility, speed and running endurance) and anthropometric (body mass and height) data were obtained. Hedge's effect sizes were calculated to assess the influence of selection-level and competition on these physical attributes, with logistic regression models constructed to discriminate Australian Football League Drafted and National Championship players. Rule induction analysis was undertaken to determine a set of rules for discriminating selection-level. Effect size comparisons revealed a range of small to moderate differences between State-level club players and both other groups for all attributes, with trivial to small differences between Australian Football League Drafted and National Championship players noted. Logistic regression models showed multistage fitness test, height and 20 m sprint time as the most important attributes in predicting Draft success. Rule induction analysis showed that players displaying multistage fitness test scores of >14.01 and/or 20 m sprint times of <2.99 s were most likely to be recruited. High levels of performance in aerobic and/or speed tests increase the likelihood of elite junior Australian football players being recruited to the highest level of the sport. Copyright © 2014 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

[Edouard Kufferath (1853-1909), eminent figure of past gynaecology and obstetrics at the ULB (Université libre de Bruxelles)].

PubMed

Leroy, F; Kufferath, P

2010-01-01

Edouard Kufferath (1853-1909) came from a German family of musicians. He was appointed as professor of obstetrics for 20 years and was Rector of the ULB (Université libre de Bruxelles) in 1905-1906. He was the first in Belgium to apply strict aseptic rules in obstetrics and to obtain hence a drastic reduction of maternal and newborn mortalities consecutive to puerperal fever. He improved the technique of symphyseotomy and invented a new method of labour induction. The type of obstetrical forceps that he conceived was known by his name and remained widely used by obstetricians in Brussels during at least six decades before the diffusion of the Swedish vacuum extractor. The exceptional quality of Kufferath's teaching was unanimously recognized. He became also active as communal Counsellor of the City of Brussels. Unanimously admired and respected, he prematurely passed away from a tongue cancer at the age of 55 years, covered with official honours.

Data Clustering and Evolving Fuzzy Decision Tree for Data Base Classification Problems

NASA Astrophysics Data System (ADS)

Chang, Pei-Chann; Fan, Chin-Yuan; Wang, Yen-Wen

Data base classification suffers from two well known difficulties, i.e., the high dimensionality and non-stationary variations within the large historic data. This paper presents a hybrid classification model by integrating a case based reasoning technique, a Fuzzy Decision Tree (FDT), and Genetic Algorithms (GA) to construct a decision-making system for data classification in various data base applications. The model is major based on the idea that the historic data base can be transformed into a smaller case-base together with a group of fuzzy decision rules. As a result, the model can be more accurately respond to the current data under classifying from the inductions by these smaller cases based fuzzy decision trees. Hit rate is applied as a performance measure and the effectiveness of our proposed model is demonstrated by experimentally compared with other approaches on different data base classification applications. The average hit rate of our proposed model is the highest among others.

Efficient Grammar Induction Algorithm with Parse Forests from Real Corpora

NASA Astrophysics Data System (ADS)

Kurihara, Kenichi; Kameya, Yoshitaka; Sato, Taisuke

The task of inducing grammar structures has received a great deal of attention. The reasons why researchers have studied are different; to use grammar induction as the first stage in building large treebanks or to make up better language models. However, grammar induction has inherent computational complexity. To overcome it, some grammar induction algorithms add new production rules incrementally. They refine the grammar while keeping their computational complexity low. In this paper, we propose a new efficient grammar induction algorithm. Although our algorithm is similar to algorithms which learn a grammar incrementally, our algorithm uses the graphical EM algorithm instead of the Inside-Outside algorithm. We report results of learning experiments in terms of learning speeds. The results show that our algorithm learns a grammar in constant time regardless of the size of the grammar. Since our algorithm decreases syntactic ambiguities in each step, our algorithm reduces required time for learning. This constant-time learning considerably affects learning time for larger grammars. We also reports results of evaluation of criteria to choose nonterminals. Our algorithm refines a grammar based on a nonterminal in each step. Since there can be several criteria to decide which nonterminal is the best, we evaluate them by learning experiments.

Integrative relational machine-learning for understanding drug side-effect profiles

PubMed Central

2013-01-01

Background Drug side effects represent a common reason for stopping drug development during clinical trials. Improving our ability to understand drug side effects is necessary to reduce attrition rates during drug development as well as the risk of discovering novel side effects in available drugs. Today, most investigations deal with isolated side effects and overlook possible redundancy and their frequent co-occurrence. Results In this work, drug annotations are collected from SIDER and DrugBank databases. Terms describing individual side effects reported in SIDER are clustered with a semantic similarity measure into term clusters (TCs). Maximal frequent itemsets are extracted from the resulting drug x TC binary table, leading to the identification of what we call side-effect profiles (SEPs). A SEP is defined as the longest combination of TCs which are shared by a significant number of drugs. Frequent SEPs are explored on the basis of integrated drug and target descriptors using two machine learning methods: decision-trees and inductive-logic programming. Although both methods yield explicit models, inductive-logic programming method performs relational learning and is able to exploit not only drug properties but also background knowledge. Learning efficiency is evaluated by cross-validation and direct testing with new molecules. Comparison of the two machine-learning methods shows that the inductive-logic-programming method displays a greater sensitivity than decision trees and successfully exploit background knowledge such as functional annotations and pathways of drug targets, thereby producing rich and expressive rules. All models and theories are available on a dedicated web site. Conclusions Side effect profiles covering significant number of drugs have been extracted from a drug ×side-effect association table. Integration of background knowledge concerning both chemical and biological spaces has been combined with a relational learning method for discovering rules which explicitly characterize drug-SEP associations. These rules are successfully used for predicting SEPs associated with new drugs. PMID:23802887

Integrative relational machine-learning for understanding drug side-effect profiles.

PubMed

Bresso, Emmanuel; Grisoni, Renaud; Marchetti, Gino; Karaboga, Arnaud Sinan; Souchet, Michel; Devignes, Marie-Dominique; Smaïl-Tabbone, Malika

2013-06-26

Drug side effects represent a common reason for stopping drug development during clinical trials. Improving our ability to understand drug side effects is necessary to reduce attrition rates during drug development as well as the risk of discovering novel side effects in available drugs. Today, most investigations deal with isolated side effects and overlook possible redundancy and their frequent co-occurrence. In this work, drug annotations are collected from SIDER and DrugBank databases. Terms describing individual side effects reported in SIDER are clustered with a semantic similarity measure into term clusters (TCs). Maximal frequent itemsets are extracted from the resulting drug x TC binary table, leading to the identification of what we call side-effect profiles (SEPs). A SEP is defined as the longest combination of TCs which are shared by a significant number of drugs. Frequent SEPs are explored on the basis of integrated drug and target descriptors using two machine learning methods: decision-trees and inductive-logic programming. Although both methods yield explicit models, inductive-logic programming method performs relational learning and is able to exploit not only drug properties but also background knowledge. Learning efficiency is evaluated by cross-validation and direct testing with new molecules. Comparison of the two machine-learning methods shows that the inductive-logic-programming method displays a greater sensitivity than decision trees and successfully exploit background knowledge such as functional annotations and pathways of drug targets, thereby producing rich and expressive rules. All models and theories are available on a dedicated web site. Side effect profiles covering significant number of drugs have been extracted from a drug ×side-effect association table. Integration of background knowledge concerning both chemical and biological spaces has been combined with a relational learning method for discovering rules which explicitly characterize drug-SEP associations. These rules are successfully used for predicting SEPs associated with new drugs.

A 25-Gbps high-sensitivity optical receiver with 10-Gbps photodiode using inductive input coupling for optical interconnects

NASA Astrophysics Data System (ADS)

Oku, Hideki; Narita, Kiyomi; Shiraishi, Takashi; Ide, Satoshi; Tanaka, Kazuhiro

2012-01-01

A 25-Gbps high-sensitivity optical receiver with a 10-Gbps photodiode (PD) using inductive input coupling has been demonstrated for optical interconnects. We introduced the inductive input coupling technique to achieve the 25-Gbps optical receiver using a 10-Gbps PD. We implemented an input inductor (Lin) between the PD and trans-impedance amplifier (TIA), and optimized inductance to enhance the bandwidth and reduce the input referred noise current through simulation with the RF PD-model. Near the resonance frequency of the tank circuit formed by PD capacitance, Lin, and TIA input capacitance, the PD photo-current through Lin into the TIA is enhanced. This resonance has the effects of enhancing the bandwidth at TIA input and reducing the input equivalent value of the noise current from TIA. We fabricated the 25-Gbps optical receiver with the 10-Gbps PD using an inductive input coupling technique. Due to the application of an inductor, the receiver bandwidth is enhanced from 10 GHz to 14.2 GHz. Thanks to this wide-band and low-noise performance, we were able to improve the sensitivity at an error rate of 1E-12 from non-error-free to -6.5 dBm. These results indicate that our technique is promising for cost-effective optical interconnects.

Implementation of a new fuzzy vector control of induction motor.

PubMed

Rafa, Souad; Larabi, Abdelkader; Barazane, Linda; Manceur, Malik; Essounbouli, Najib; Hamzaoui, Abdelaziz

2014-05-01

The aim of this paper is to present a new approach to control an induction motor using type-1 fuzzy logic. The induction motor has a nonlinear model, uncertain and strongly coupled. The vector control technique, which is based on the inverse model of the induction motors, solves the coupling problem. Unfortunately, in practice this is not checked because of model uncertainties. Indeed, the presence of the uncertainties led us to use human expertise such as the fuzzy logic techniques. In order to maintain the decoupling and to overcome the problem of the sensitivity to the parametric variations, the field-oriented control is replaced by a new block control. The simulation results show that the both control schemes provide in their basic configuration, comparable performances regarding the decoupling. However, the fuzzy vector control provides the insensitivity to the parametric variations compared to the classical one. The fuzzy vector control scheme is successfully implemented in real-time using a digital signal processor board dSPACE 1104. The efficiency of this technique is verified as well as experimentally at different dynamic operating conditions such as sudden loads change, parameter variations, speed changes, etc. The fuzzy vector control is found to be a best control for application in an induction motor. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

40 CFR Appendix C to Part 136 - Inductively Coupled Plasma-Atomic Emission Spectrometric Method for Trace Element Analysis of...

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 22 2010-07-01 2010-07-01 false Inductively Coupled Plasma-Atomic... to Part 136—Inductively Coupled Plasma—Atomic Emission Spectrometric Method for Trace Element... technique. Samples are nebulized and the aerosol that is produced is transported to the plasma torch where...

40 CFR Appendix C to Part 136 - Inductively Coupled Plasma-Atomic Emission Spectrometric Method for Trace Element Analysis of...

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 23 2011-07-01 2011-07-01 false Inductively Coupled Plasma-Atomic... to Part 136—Inductively Coupled Plasma—Atomic Emission Spectrometric Method for Trace Element... technique. Samples are nebulized and the aerosol that is produced is transported to the plasma torch where...

Efficiency optimization of class-D biomedical inductive wireless power transfer systems by means of frequency adjustment.

PubMed

Schormans, Matthew; Valente, Virgilio; Demosthenous, Andreas

2015-01-01

Inductive powering for implanted medical devices is a commonly employed technique, that allows for implants to avoid more dangerous methods such as the use of transcutaneous wires or implanted batteries. However, wireless powering in this way also comes with a number of difficulties and conflicting requirements, which are often met by using designs based on compromise. In particular, one aspect common to most inductive power links is that they are driven with a fixed frequency, which may not be optimal depending on factors such as coupling and load. In this paper, a method is proposed in which an inductive power link is driven by a frequency that is maintained at an optimum value f(opt), to ensure that the link is in resonance. In order to maintain this resonance, a phase tracking technique is employed at the primary side of the link; this allows for compensation of changes in coil separation and load. The technique is shown to provide significant improvements in maintained secondary voltage and efficiency for a range of loads when the link is overcoupled.

Qualitative Discovery in Medical Databases

NASA Technical Reports Server (NTRS)

Maluf, David A.

2000-01-01

Implication rules have been used in uncertainty reasoning systems to confirm and draw hypotheses or conclusions. However a major bottleneck in developing such systems lies in the elicitation of these rules. This paper empirically examines the performance of evidential inferencing with implication networks generated using a rule induction tool called KAT. KAT utilizes an algorithm for the statistical analysis of empirical case data, and hence reduces the knowledge engineering efforts and biases in subjective implication certainty assignment. The paper describes several experiments in which real-world diagnostic problems were investigated; namely, medical diagnostics. In particular, it attempts to show that: (1) with a limited number of case samples, KAT is capable of inducing implication networks useful for making evidential inferences based on partial observations, and (2) observation driven by a network entropy optimization mechanism is effective in reducing the uncertainty of predicted events.

A Synopsis of Yaw-Induction Techniques Used During Projectile Free-Flight Aerodynamics Experiments

DTIC Science & Technology

2013-03-01

the projectile exits the launch tube is often needed. Over the years, numerous yaw-induction techniques have been developed to deliberately...launch phase, and provide insight pertaining to their implementation and success based upon some quantitative results. 2. WORN TUBES AS YAW...disturbances are predominantly introduced while the projectile is still in bore or in transition (i.e., mechanically disengaged from the gun tube but not

Binary translation using peephole translation rules

DOEpatents

Bansal, Sorav; Aiken, Alex

2010-05-04

An efficient binary translator uses peephole translation rules to directly translate executable code from one instruction set to another. In a preferred embodiment, the translation rules are generated using superoptimization techniques that enable the translator to automatically learn translation rules for translating code from the source to target instruction set architecture.

Dynamic association rules for gene expression data analysis.

PubMed

Chen, Shu-Chuan; Tsai, Tsung-Hsien; Chung, Cheng-Han; Li, Wen-Hsiung

2015-10-14

The purpose of gene expression analysis is to look for the association between regulation of gene expression levels and phenotypic variations. This association based on gene expression profile has been used to determine whether the induction/repression of genes correspond to phenotypic variations including cell regulations, clinical diagnoses and drug development. Statistical analyses on microarray data have been developed to resolve gene selection issue. However, these methods do not inform us of causality between genes and phenotypes. In this paper, we propose the dynamic association rule algorithm (DAR algorithm) which helps ones to efficiently select a subset of significant genes for subsequent analysis. The DAR algorithm is based on association rules from market basket analysis in marketing. We first propose a statistical way, based on constructing a one-sided confidence interval and hypothesis testing, to determine if an association rule is meaningful. Based on the proposed statistical method, we then developed the DAR algorithm for gene expression data analysis. The method was applied to analyze four microarray datasets and one Next Generation Sequencing (NGS) dataset: the Mice Apo A1 dataset, the whole genome expression dataset of mouse embryonic stem cells, expression profiling of the bone marrow of Leukemia patients, Microarray Quality Control (MAQC) data set and the RNA-seq dataset of a mouse genomic imprinting study. A comparison of the proposed method with the t-test on the expression profiling of the bone marrow of Leukemia patients was conducted. We developed a statistical way, based on the concept of confidence interval, to determine the minimum support and minimum confidence for mining association relationships among items. With the minimum support and minimum confidence, one can find significant rules in one single step. The DAR algorithm was then developed for gene expression data analysis. Four gene expression datasets showed that the proposed DAR algorithm not only was able to identify a set of differentially expressed genes that largely agreed with that of other methods, but also provided an efficient and accurate way to find influential genes of a disease. In the paper, the well-established association rule mining technique from marketing has been successfully modified to determine the minimum support and minimum confidence based on the concept of confidence interval and hypothesis testing. It can be applied to gene expression data to mine significant association rules between gene regulation and phenotype. The proposed DAR algorithm provides an efficient way to find influential genes that underlie the phenotypic variance.

CFAVC scheme for high frequency series resonant inverter-fed domestic induction heating system

NASA Astrophysics Data System (ADS)

Nagarajan, Booma; Reddy Sathi, Rama

2016-01-01

This article presents the investigations on the constant frequency asymmetric voltage cancellation control in the AC-AC resonant converter-fed domestic induction heating system. Conventional fixed frequency control techniques used in the high frequency converters lead to non-zero voltage switching operation and reduced output power. The proposed control technique produces higher output power than the conventional fixed-frequency control strategies. In this control technique, zero-voltage-switching operation is maintained during different duty cycle operation for reduction in the switching losses. Complete analysis of the induction heating power supply system with asymmetric voltage cancellation control is discussed in this article. Simulation and experimental study on constant frequency asymmetric voltage cancellation (CFAVC)-controlled full bridge series resonant inverter is performed. Time domain simulation results for the open and closed loop of the system are obtained using MATLAB simulation tool. The simulation results prove the control of voltage and power in a wide range. PID controller-based closed loop control system achieves the voltage regulation of the proposed system for the step change in load. Hardware implementation of the system under CFAVC control is done using the embedded controller. The simulation and experimental results validate the performance of the CFAVC control technique for series resonant-based induction cooking system.

Cognitive flexibility in young children: General or task-specific capacity?

PubMed

Deák, Gedeon O; Wiseheart, Melody

2015-10-01

Cognitive flexibility is the ability to adapt to changing tasks or problems. To test whether cognitive flexibility is a coherent cognitive capacity in young children, we tested 3- to 5-year-olds' performance on two forms of task switching, rule-based (Three Dimension Changes Card Sorting, 3DCCS) and inductive (Flexible Induction of Meaning-Animates and Objects, FIM-Ob and FIM-An), as well as tests of response speed, verbal working memory, inhibition, and reasoning. Results suggest that cognitive flexibility is not a globally coherent trait; only the two inductive word-meaning (FIM) tests showed high inter-test coherence. Task- and knowledge-specific factors also determine children's flexibility in a given test. Response speed, vocabulary size, and causal reasoning skills further predicted individual and age differences in flexibility, although they did not have the same predictive relation with all three flexibility tests. Copyright © 2015 Elsevier Inc. All rights reserved.

Theoretical and Experimental Estimations of Volumetric Inductive Phase Shift in Breast Cancer Tissue

NASA Astrophysics Data System (ADS)

González, C. A.; Lozano, L. M.; Uscanga, M. C.; Silva, J. G.; Polo, S. M.

2013-04-01

Impedance measurements based on magnetic induction for breast cancer detection has been proposed in some studies. This study evaluates theoretical and experimentally the use of a non-invasive technique based on magnetic induction for detection of patho-physiological conditions in breast cancer tissue associated to its volumetric electrical conductivity changes through inductive phase shift measurements. An induction coils-breast 3D pixel model was designed and tested. The model involves two circular coils coaxially centered and a human breast volume centrally placed with respect to the coils. A time-harmonic numerical simulation study addressed the effects of frequency-dependent electrical properties of tumoral tissue on the volumetric inductive phase shift of the breast model measured with the circular coils as inductor and sensor elements. Experimentally; five female volunteer patients with infiltrating ductal carcinoma previously diagnosed by the radiology and oncology departments of the Specialty Clinic for Women of the Mexican Army were measured by an experimental inductive spectrometer and the use of an ergonomic inductor-sensor coil designed to estimate the volumetric inductive phase shift in human breast tissue. Theoretical and experimental inductive phase shift estimations were developed at four frequencies: 0.01, 0.1, 1 and 10 MHz. The theoretical estimations were qualitatively in agreement with the experimental findings. Important increments in volumetric inductive phase shift measurements were evident at 0.01MHz in theoretical and experimental observations. The results suggest that the tested technique has the potential to detect pathological conditions in breast tissue associated to cancer by non-invasive monitoring. Further complementary studies are warranted to confirm the observations.

Induction generators for Wind Energy Conversion Systems. Part I: review of induction generator with squirrel cage rotor. Part II: the Double Output Induction Generator (DOIG). Progress report, July-December 1975

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

Jayadev, T.S.

1976-02-01

The application of induction generators in Wind Energy Conversion Systems (WECS) is described. The conventional induction generator, which is an induction machine with a squirrel cage rotor, had been used in large wind power plants in Europe, but has not caught much attention until now by designers of large systems in this country. The induction generator with a squirrel cage rotor is described and useful design techniques to build induction generators for wind energy application are outlined. The Double Output Induction Generator (DOIG) - so called because power is fed into the grid from the stator, as well as themore » rotor is described. It is a wound rotor induction machine with power electronics to convert rotor slip frequency power to that of line frequency.« less

Analyzing Large Gene Expression and Methylation Data Profiles Using StatBicRM: Statistical Biclustering-Based Rule Mining

PubMed Central

Maulik, Ujjwal; Mallik, Saurav; Mukhopadhyay, Anirban; Bandyopadhyay, Sanghamitra

2015-01-01

Microarray and beadchip are two most efficient techniques for measuring gene expression and methylation data in bioinformatics. Biclustering deals with the simultaneous clustering of genes and samples. In this article, we propose a computational rule mining framework, StatBicRM (i.e., statistical biclustering-based rule mining) to identify special type of rules and potential biomarkers using integrated approaches of statistical and binary inclusion-maximal biclustering techniques from the biological datasets. At first, a novel statistical strategy has been utilized to eliminate the insignificant/low-significant/redundant genes in such way that significance level must satisfy the data distribution property (viz., either normal distribution or non-normal distribution). The data is then discretized and post-discretized, consecutively. Thereafter, the biclustering technique is applied to identify maximal frequent closed homogeneous itemsets. Corresponding special type of rules are then extracted from the selected itemsets. Our proposed rule mining method performs better than the other rule mining algorithms as it generates maximal frequent closed homogeneous itemsets instead of frequent itemsets. Thus, it saves elapsed time, and can work on big dataset. Pathway and Gene Ontology analyses are conducted on the genes of the evolved rules using David database. Frequency analysis of the genes appearing in the evolved rules is performed to determine potential biomarkers. Furthermore, we also classify the data to know how much the evolved rules are able to describe accurately the remaining test (unknown) data. Subsequently, we also compare the average classification accuracy, and other related factors with other rule-based classifiers. Statistical significance tests are also performed for verifying the statistical relevance of the comparative results. Here, each of the other rule mining methods or rule-based classifiers is also starting with the same post-discretized data-matrix. Finally, we have also included the integrated analysis of gene expression and methylation for determining epigenetic effect (viz., effect of methylation) on gene expression level. PMID:25830807

Analyzing large gene expression and methylation data profiles using StatBicRM: statistical biclustering-based rule mining.

PubMed

Maulik, Ujjwal; Mallik, Saurav; Mukhopadhyay, Anirban; Bandyopadhyay, Sanghamitra

2015-01-01

Microarray and beadchip are two most efficient techniques for measuring gene expression and methylation data in bioinformatics. Biclustering deals with the simultaneous clustering of genes and samples. In this article, we propose a computational rule mining framework, StatBicRM (i.e., statistical biclustering-based rule mining) to identify special type of rules and potential biomarkers using integrated approaches of statistical and binary inclusion-maximal biclustering techniques from the biological datasets. At first, a novel statistical strategy has been utilized to eliminate the insignificant/low-significant/redundant genes in such way that significance level must satisfy the data distribution property (viz., either normal distribution or non-normal distribution). The data is then discretized and post-discretized, consecutively. Thereafter, the biclustering technique is applied to identify maximal frequent closed homogeneous itemsets. Corresponding special type of rules are then extracted from the selected itemsets. Our proposed rule mining method performs better than the other rule mining algorithms as it generates maximal frequent closed homogeneous itemsets instead of frequent itemsets. Thus, it saves elapsed time, and can work on big dataset. Pathway and Gene Ontology analyses are conducted on the genes of the evolved rules using David database. Frequency analysis of the genes appearing in the evolved rules is performed to determine potential biomarkers. Furthermore, we also classify the data to know how much the evolved rules are able to describe accurately the remaining test (unknown) data. Subsequently, we also compare the average classification accuracy, and other related factors with other rule-based classifiers. Statistical significance tests are also performed for verifying the statistical relevance of the comparative results. Here, each of the other rule mining methods or rule-based classifiers is also starting with the same post-discretized data-matrix. Finally, we have also included the integrated analysis of gene expression and methylation for determining epigenetic effect (viz., effect of methylation) on gene expression level.

Donald J. Cram, Host-Guest Chemistry, Cram's Rule of Asymmetric Induction

Science.gov Websites

across organic chemistry, with applications in both basic research as well as specific fields, such as for life and science have forever changed "teaching in organic chemistry, and altered the shape organic chemistry; his research affects the many ways organic chemistry now appears in our daily lives

77 FR 17386 - Significant New Use Rule for Hexabromocyclododecane and 1,2,5,6,9,10-Hexabromocyclododecane

Federal Register 2010, 2011, 2012, 2013, 2014

2012-03-26

... metabolism, oxidative stress, reproductive activity) have also been observed in fish (Palace, et al., 2008.... November 2009. 72, pp. 985- 1993. 16. Zhang, et al. 2008. Induction of hepatic enzymes and oxidative stress..., freshwater and marine fish, aquatic invertebrates, birds and bird eggs, and one plant species (Covaci, et al...

When Global Structure "Explains Away" Local Grammar: A Bayesian Account of Rule-Induction in Tone Sequences

ERIC Educational Resources Information Center

Dawson, Colin; Gerken, LouAnn

2011-01-01

While many constraints on learning must be relatively experience-independent, past experience provides a rich source of guidance for subsequent learning. Discovering structure in some domain can inform a learner's future hypotheses about that domain. If a general property accounts for particular sub-patterns, a rational learner should not…

Relevance of microelectronic education to industrial needs

NASA Technical Reports Server (NTRS)

Prince, J. L.; Lathrop, J. W.

1977-01-01

The relevance of microelectronic education to industrial needs was evaluated, and four categories were surveyed: (1) facts and rules; (2) skills; (3) personality; and (4) deductive-inductive reasoning. Examples of specific items in each category are given to illustrate their meaning and it was indicated as to which items in each category are strongly impacted by microelectronics courses and laboratories.

Determinants and development of a web-based child mortality prediction model in resource-limited settings: A data mining approach.

PubMed

Tesfaye, Brook; Atique, Suleman; Elias, Noah; Dibaba, Legesse; Shabbir, Syed-Abdul; Kebede, Mihiretu

2017-03-01

Improving child health and reducing child mortality rate are key health priorities in developing countries. This study aimed to identify determinant sand develop, a web-based child mortality prediction model in Ethiopian local language using classification data mining algorithm. Decision tree (using J48 algorithm) and rule induction (using PART algorithm) techniques were applied on 11,654 records of Ethiopian demographic and health survey data. Waikato Environment for Knowledge Analysis (WEKA) for windows version 3.6.8 was used to develop optimal models. 8157 (70%) records were randomly allocated to training group for model building while; the remaining 3496 (30%) records were allocated as the test group for model validation. The validation of the model was assessed using accuracy, sensitivity, specificity and area under Receiver Operating Characteristics (ROC) curve. Using Statistical Package for Social Sciences (SPSS) version 20.0; logistic regressions and Odds Ratio (OR) with 95% Confidence Interval (CI) was used to identify determinants of child mortality. The child mortality rate was 72 deaths per 1000 live births. Breast-feeding (AOR= 1.46, (95% CI [1.22. 1.75]), maternal education (AOR= 1.40, 95% CI [1.11, 1.81]), family planning (AOR= 1.21, [1.08, 1.43]), preceding birth interval (AOR= 4.90, [2.94, 8.15]), presence of diarrhea (AOR= 1.54, 95% CI [1.32, 1.66]), father's education (AOR= 1.4, 95% CI [1.04, 1.78]), low birth weight (AOR= 1.2, 95% CI [0.98, 1.51]) and, age of the mother at first birth (AOR= 1.42, [1.01-1.89]) were found to be determinants for child mortality. The J48 model had better performance, accuracy (94.3%), sensitivity (93.8%), specificity (94.3%), Positive Predictive Value (PPV) (92.2%), Negative Predictive Value (NPV) (94.5%) and, the area under ROC (94.8%). Subsequent to developing an optimal prediction model, we relied on this model to develop a web-based application system for child mortality prediction. In this study, nearly accurate results were obtained by employing decision tree and rule induction techniques. Determinants are identified and a web-based child mortality prediction model in Ethiopian local language is developed. Thus, the result obtained could support child health intervention programs in Ethiopia where trained human resource for health is limited. Advanced classification algorithms need to be tested to come up with optimal models. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Rules in School. Strategies for Teachers Series.

ERIC Educational Resources Information Center

Brady, Kathryn; Forton, Mary Beth; Porter, Deborah; Wood, Chip

This book offers an approach for helping K-8 students become invested in creating and living by classroom rules. It provides techniques for: helping students articulate their hopes and dreams for school; involving students in generating classroom rules that grow out of their hopes and dreams; modeling, practicing, and role playing the rules; using…

Inductive discipline, parental expression of disappointed expectations, and moral identity in adolescence.

PubMed

Patrick, Renee B; Gibbs, John C

2012-08-01

Within the fields of socialization and moral development, the relationship of parenting to adolescents' sense of morality and self has been understudied. This study investigated the relationships between perceived parental disciplinary techniques and moral identity among early and middle adolescents. Participants included 93 (54% female) 5th, 8th and 10th graders, as well as their mothers. Students completed self-report measures concerning their mothers' disciplinary techniques and moral self-concept; mothers reported specifically on parental discipline frequency. The parental discipline measure was structured in terms of Hoffman's typology of induction, love withdrawal, and power assertion. Adolescents reported the frequency of their mothers' disciplinary techniques, as well as their perceptions (fairness or appropriateness evaluations, emotional reactions) concerning their mothers' most frequently used technique. Parental induction (orienting the transgressor to the plight of the victim) and expression of disappointed expectations were viewed as more appropriate and responded to with more positive emotion and guilt relative to other disciplinary techniques (e.g., power assertion). In addition, parental use of inductive discipline (including parental disappointment) during the adolescent years related to higher moral identity, defined in terms of the ascription of specifically moral (e.g., fair, kind) over non-moral (e.g., athletic, smart) qualities to the self. In contrast, love withdrawal and power assertion did not relate to moral identity. The findings suggest that parental expression of disappointed expectations, especially when perceived favorably, plays an important role in the formation of moral identity during the adolescent years.

Machine Learning Techniques in Optimal Design

NASA Technical Reports Server (NTRS)

Cerbone, Giuseppe

1992-01-01

Many important applications can be formalized as constrained optimization tasks. For example, we are studying the engineering domain of two-dimensional (2-D) structural design. In this task, the goal is to design a structure of minimum weight that bears a set of loads. A solution to a design problem in which there is a single load (L) and two stationary support points (S1 and S2) consists of four members, E1, E2, E3, and E4 that connect the load to the support points is discussed. In principle, optimal solutions to problems of this kind can be found by numerical optimization techniques. However, in practice [Vanderplaats, 1984] these methods are slow and they can produce different local solutions whose quality (ratio to the global optimum) varies with the choice of starting points. Hence, their applicability to real-world problems is severely restricted. To overcome these limitations, we propose to augment numerical optimization by first performing a symbolic compilation stage to produce: (a) objective functions that are faster to evaluate and that depend less on the choice of the starting point and (b) selection rules that associate problem instances to a set of recommended solutions. These goals are accomplished by successive specializations of the problem class and of the associated objective functions. In the end, this process reduces the problem to a collection of independent functions that are fast to evaluate, that can be differentiated symbolically, and that represent smaller regions of the overall search space. However, the specialization process can produce a large number of sub-problems. This is overcome by deriving inductively selection rules which associate problems to small sets of specialized independent sub-problems. Each set of candidate solutions is chosen to minimize a cost function which expresses the tradeoff between the quality of the solution that can be obtained from the sub-problem and the time it takes to produce it. The overall solution to the problem, is then obtained by solving in parallel each of the sub-problems in the set and computing the one with the minimum cost. In addition to speeding up the optimization process, our use of learning methods also relieves the expert from the burden of identifying rules that exactly pinpoint optimal candidate sub-problems. In real engineering tasks it is usually too costly to the engineers to derive such rules. Therefore, this paper also contributes to a further step towards the solution of the knowledge acquisition bottleneck [Feigenbaum, 1977] which has somewhat impaired the construction of rulebased expert systems.

Comparative evaluation of power factor impovement techniques for squirrel cage induction motors

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

Spee, R.; Wallace, A.K.

1992-04-01

This paper describes the results obtained from a series of tests of relatively simple methods of improving the power factor of squirrel-cage induction motors. The methods, which are evaluated under controlled laboratory conditions for a 10-hp, high-efficiency motor, include terminal voltage reduction; terminal static capacitors; and a floating'' winding with static capacitors. The test results are compared with equivalent circuit model predictions that are then used to identify optimum conditions for each of the power factor improvement techniques compared with the basic induction motor. Finally, the relative economic value, and the implications of component failures, of the three methods aremore » discussed.« less

[Induction on callus culture and regeneration of Orostachyis fimbriatae].

PubMed

Su, Rui-jun; Zou, Li-juan; Wu, Qing-gui; Luo, Ming-hua

2014-01-01

To explore the effects of different hormonal combinations on induction, proliferation and differentiation of Orostachyis fimbriatae callus culture. Aseptic seedling leaves were used as explants,the different concentrations of IAA,NAA, 6-BA and KT on induction proliferation of callus were optimized by orthogonal test to explore the optimum medium for differentiation of callus by tissue culture techniques. The best medium for induction was MS + IAA 1.0 mg/L + NAA 0.5 mg/L + KT 1.0 mg/L, and the best hormonal combination for proliferation was MS + IAA 0.5 mg/L + 6-BA 0.5 mg/I. + KT 1.0 mg/L. The best medium for differentiation was MS + IAA 0.1 mg/L + KT 2.0 mg/L, and 1/2MS + IAA 0.2 mg/L was the optimum medium for rooting culture. The system of regeneration of Orostachyis fimbriatae is establishd by tissue culture techniques in this study.

Subranging technique using superconducting technology

DOEpatents

Gupta, Deepnarayan

2003-01-01

Subranging techniques using "digital SQUIDs" are used to design systems with large dynamic range, high resolution and large bandwidth. Analog-to-digital converters (ADCs) embodying the invention include a first SQUID based "coarse" resolution circuit and a second SQUID based "fine" resolution circuit to convert an analog input signal into "coarse" and "fine" digital signals for subsequent processing. In one embodiment, an ADC includes circuitry for supplying an analog input signal to an input coil having at least a first inductive section and a second inductive section. A first superconducting quantum interference device (SQUID) is coupled to the first inductive section and a second SQUID is coupled to the second inductive section. The first SQUID is designed to produce "coarse" (large amplitude, low resolution) output signals and the second SQUID is designed to produce "fine" (low amplitude, high resolution) output signals in response to the analog input signals.

Evaluation of Noncontact Power Collection Techniques

DOT National Transportation Integrated Search

1972-07-01

An evaluation is made of four basic noncontacting techniques of power collection which have possible applicability in future high speed ground transportation systems. The techniques considered include the electric arc, magnetic induction, electrostat...

Computer-assisted expert case definition in electronic health records.

PubMed

Walker, Alexander M; Zhou, Xiaofeng; Ananthakrishnan, Ashwin N; Weiss, Lisa S; Shen, Rongjun; Sobel, Rachel E; Bate, Andrew; Reynolds, Robert F

2016-02-01

To describe how computer-assisted presentation of case data can lead experts to infer machine-implementable rules for case definition in electronic health records. As an illustration the technique has been applied to obtain a definition of acute liver dysfunction (ALD) in persons with inflammatory bowel disease (IBD). The technique consists of repeatedly sampling new batches of case candidates from an enriched pool of persons meeting presumed minimal inclusion criteria, classifying the candidates by a machine-implementable candidate rule and by a human expert, and then updating the rule so that it captures new distinctions introduced by the expert. Iteration continues until an update results in an acceptably small number of changes to form a final case definition. The technique was applied to structured data and terms derived by natural language processing from text records in 29,336 adults with IBD. Over three rounds the technique led to rules with increasing predictive value, as the experts identified exceptions, and increasing sensitivity, as the experts identified missing inclusion criteria. In the final rule inclusion and exclusion terms were often keyed to an ALD onset date. When compared against clinical review in an independent test round, the derived final case definition had a sensitivity of 92% and a positive predictive value of 79%. An iterative technique of machine-supported expert review can yield a case definition that accommodates available data, incorporates pre-existing medical knowledge, is transparent and is open to continuous improvement. The expert updates to rules may be informative in themselves. In this limited setting, the final case definition for ALD performed better than previous, published attempts using expert definitions. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Challenging Aerospace Problems for Intelligent Systems

DTIC Science & Technology

2003-06-01

importance of each rule. Techniques such as logarithmic regression or Saaty’s AHP may be employed to apply the weights on to the fuzzy rules. 15-9 Given u...at which designs could be evaluated. This implies that modeling techniques such as neural networks, fuzzy systems and so on can play an important role...failure conditions [4-6]. These approaches apply techniques, such as neural networks, fuzzy logic, and parameter identification, to improve aircraft

Rules, Technique, and Practical Knowledge: A Wittgensteinian Exploration of Vocational Learning

ERIC Educational Resources Information Center

Winch, Christopher

2006-01-01

In this essay, Christopher Winch explores the relevance of Ludwig Wittgenstein's account of rule-following to vocational education with particular reference to the often-made claim that any account of an activity in terms of rule-following implies rigidity and inflexibility. He argues that most rule-following is only successful when it involves a…

Logical Differential Prediction Bayes Net, improving breast cancer diagnosis for older women.

PubMed

Nassif, Houssam; Wu, Yirong; Page, David; Burnside, Elizabeth

2012-01-01

Overdiagnosis is a phenomenon in which screening identities cancer which may not go on to cause symptoms or death. Women over 65 who develop breast cancer bear the heaviest burden of overdiagnosis. This work introduces novel machine learning algorithms to improve diagnostic accuracy of breast cancer in aging populations. At the same time, we aim at minimizing unnecessary invasive procedures (thus decreasing false positives) and concomitantly addressing overdiagnosis. We develop a novel algorithm. Logical Differential Prediction Bayes Net (LDP-BN), that calculates the risk of breast disease based on mammography findings. LDP-BN uses Inductive Logic Programming (ILP) to learn relational rules, selects older-specific differentially predictive rules, and incorporates them into a Bayes Net, significantly improving its performance. In addition, LDP-BN offers valuable insight into the classification process, revealing novel older-specific rules that link mass presence to invasive, and calcification presence and lack of detectable mass to DCIS.

Where There Are No Rules or Systems to Guide Us: Argument from Example in a Hermeneutic Rhetoric

ERIC Educational Resources Information Center

Arthos, John

2003-01-01

Many rhetoricians treat argument from example as a kind of induction, an illustration of a general principle. Although this is one function of example, consistent with Aristotle's statements about the paradeigma and "The New Rhetoric's" "argumentation by example," it camouflages the practice of exemplary proof that has contributed to our richest…

An application of the patient rule-induction method for evaluating the contribution of the Apolipoprotein E and Lipoprotein Lipase genes to predicting ischemic heart disease.

PubMed

Dyson, Greg; Frikke-Schmidt, Ruth; Nordestgaard, Børge G; Tybjaerg-Hansen, Anne; Sing, Charles F

2007-09-01

Different combinations of genetic and environmental risk factors are known to contribute to the complex etiology of ischemic heart disease (IHD) in different subsets of individuals. We employed the Patient Rule-Induction Method (PRIM) to select the combination of risk factors and risk factor values that identified each of 16 mutually exclusive partitions of individuals having significantly different levels of risk of IHD. PRIM balances two competing objectives: (1) finding partitions where the risk of IHD is high and (2) maximizing the number of IHD cases explained by the partitions. A sequential PRIM analysis was applied to data on the incidence of IHD collected over 8 years for a sample of 5,455 unrelated individuals from the Copenhagen City Heart Study (CCHS) to assess the added value of variation in two candidate susceptibility genes beyond the traditional, lipid and body mass index risk factors for IHD. An independent sample of 362 unrelated individuals also from the city of Copenhagen was used to test the model obtained for each of the hypothesized partitions. Copyright (c) 2007 Wiley-Liss, Inc.

Inductive learning of thyroid functional states using the ID3 algorithm. The effect of poor examples on the learning result.

PubMed

Forsström, J

1992-01-01

The ID3 algorithm for inductive learning was tested using preclassified material for patients suspected to have a thyroid illness. Classification followed a rule-based expert system for the diagnosis of thyroid function. Thus, the knowledge to be learned was limited to the rules existing in the knowledge base of that expert system. The learning capability of the ID3 algorithm was tested with an unselected learning material (with some inherent missing data) and with a selected learning material (no missing data). The selected learning material was a subgroup which formed a part of the unselected learning material. When the number of learning cases was increased, the accuracy of the program improved. When the learning material was large enough, an increase in the learning material did not improve the results further. A better learning result was achieved with the selected learning material not including missing data as compared to unselected learning material. With this material we demonstrate a weakness in the ID3 algorithm: it can not find available information from good example cases if we add poor examples to the data.

Application of decision rules for empowering of Indonesian telematics services SMEs

NASA Astrophysics Data System (ADS)

Tosida, E. T.; Hairlangga, O.; Amirudin, F.; Ridwanah, M.

2018-03-01

The independence of the field of telematics became one of Indonesia's vision in 2024. One effort to achieve it can be done by empowering SMEs in the field of telematics. Empowerment carried out need a practical mechanism by utilizing data centered, including through the National Economic Census database (Susenas). Based on the Susenas can be formulated the decision rules of determining the provision of assistance for SMEs in the field of telematics. The way it did by generating the rule base through the classification technique. The CART algorithm-based decision rule model performs better than C45 and ID3 models. The high level of performance model is also in line with the regulations applied by the government. This becomes one of the strengths of research, because the resulting model is consistent with the existing conditions in Indonesia. The rules base generated from the three classification techniques show different rules. The CART technique has pattern matching with the realization of activities in The Ministry of Cooperatives and SMEs. So far, the government has difficulty in referring data related to the empowerment of SMEs telematics services. Therefore, the findings resulting from this research can be used as an alternative decision support system related to the program of empowerment of SMEs in telematics.

Inferring Intra-Community Microbial Interaction Patterns from Metagenomic Datasets Using Associative Rule Mining Techniques

PubMed Central

Mande, Sharmila S.

2016-01-01

The nature of inter-microbial metabolic interactions defines the stability of microbial communities residing in any ecological niche. Deciphering these interaction patterns is crucial for understanding the mode/mechanism(s) through which an individual microbial community transitions from one state to another (e.g. from a healthy to a diseased state). Statistical correlation techniques have been traditionally employed for mining microbial interaction patterns from taxonomic abundance data corresponding to a given microbial community. In spite of their efficiency, these correlation techniques can capture only 'pair-wise interactions'. Moreover, their emphasis on statistical significance can potentially result in missing out on several interactions that are relevant from a biological standpoint. This study explores the applicability of one of the earliest association rule mining algorithm i.e. the 'Apriori algorithm' for deriving 'microbial association rules' from the taxonomic profile of given microbial community. The classical Apriori approach derives association rules by analysing patterns of co-occurrence/co-exclusion between various '(subsets of) features/items' across various samples. Using real-world microbiome data, the efficiency/utility of this rule mining approach in deciphering multiple (biologically meaningful) association patterns between 'subsets/subgroups' of microbes (constituting microbiome samples) is demonstrated. As an example, association rules derived from publicly available gut microbiome datasets indicate an association between a group of microbes (Faecalibacterium, Dorea, and Blautia) that are known to have mutualistic metabolic associations among themselves. Application of the rule mining approach on gut microbiomes (sourced from the Human Microbiome Project) further indicated similar microbial association patterns in gut microbiomes irrespective of the gender of the subjects. A Linux implementation of the Association Rule Mining (ARM) software (customised for deriving 'microbial association rules' from microbiome data) is freely available for download from the following link: http://metagenomics.atc.tcs.com/arm. PMID:27124399

Inferring Intra-Community Microbial Interaction Patterns from Metagenomic Datasets Using Associative Rule Mining Techniques.

PubMed

Tandon, Disha; Haque, Mohammed Monzoorul; Mande, Sharmila S

2016-01-01

The nature of inter-microbial metabolic interactions defines the stability of microbial communities residing in any ecological niche. Deciphering these interaction patterns is crucial for understanding the mode/mechanism(s) through which an individual microbial community transitions from one state to another (e.g. from a healthy to a diseased state). Statistical correlation techniques have been traditionally employed for mining microbial interaction patterns from taxonomic abundance data corresponding to a given microbial community. In spite of their efficiency, these correlation techniques can capture only 'pair-wise interactions'. Moreover, their emphasis on statistical significance can potentially result in missing out on several interactions that are relevant from a biological standpoint. This study explores the applicability of one of the earliest association rule mining algorithm i.e. the 'Apriori algorithm' for deriving 'microbial association rules' from the taxonomic profile of given microbial community. The classical Apriori approach derives association rules by analysing patterns of co-occurrence/co-exclusion between various '(subsets of) features/items' across various samples. Using real-world microbiome data, the efficiency/utility of this rule mining approach in deciphering multiple (biologically meaningful) association patterns between 'subsets/subgroups' of microbes (constituting microbiome samples) is demonstrated. As an example, association rules derived from publicly available gut microbiome datasets indicate an association between a group of microbes (Faecalibacterium, Dorea, and Blautia) that are known to have mutualistic metabolic associations among themselves. Application of the rule mining approach on gut microbiomes (sourced from the Human Microbiome Project) further indicated similar microbial association patterns in gut microbiomes irrespective of the gender of the subjects. A Linux implementation of the Association Rule Mining (ARM) software (customised for deriving 'microbial association rules' from microbiome data) is freely available for download from the following link: http://metagenomics.atc.tcs.com/arm.

Decision rules for unbiased inventory estimates

NASA Technical Reports Server (NTRS)

Argentiero, P. D.; Koch, D.

1979-01-01

An efficient and accurate procedure for estimating inventories from remote sensing scenes is presented. In place of the conventional and expensive full dimensional Bayes decision rule, a one-dimensional feature extraction and classification technique was employed. It is shown that this efficient decision rule can be used to develop unbiased inventory estimates and that for large sample sizes typical of satellite derived remote sensing scenes, resulting accuracies are comparable or superior to more expensive alternative procedures. Mathematical details of the procedure are provided in the body of the report and in the appendix. Results of a numerical simulation of the technique using statistics obtained from an observed LANDSAT scene are included. The simulation demonstrates the effectiveness of the technique in computing accurate inventory estimates.

A path planning method for robot end effector motion using the curvature theory of the ruled surfaces

NASA Astrophysics Data System (ADS)

Güler, Fatma; Kasap, Emin

Using the curvature theory for the ruled surfaces a technique for robot trajectory planning is presented. This technique ensures the calculation of robot’s next path. The positional variation of the Tool Center Point (TCP), linear velocity, angular velocity are required in the work area of the robot. In some circumstances, it may not be physically achievable and a re-computation of the robot trajectory might be necessary. This technique is suitable for re-computation of the robot trajectory. We obtain different robot trajectories which change depending on the darboux angle function and define trajectory ruled surface family with a common trajectory curve with the rotation trihedron. Also, the motion of robot end effector is illustrated with examples.

Induction motor speed control using varied duty cycle terminal voltage via PI controller

NASA Astrophysics Data System (ADS)

Azwin, A.; Ahmed, S.

2018-03-01

This paper deals with the PI speed controller for the three-phase induction motor using PWM technique. The PWM generated signal is utilized for voltage source inverter with an optimal duty cycle on a simplified induction motor model. A control algorithm for generating PWM control signal is developed. Obtained results shows that the steady state error and overshoot of the developed system is in the limit under different speed and load condition. The robustness of the control performance would be potential for induction motor performance improvement.

Anovulation and ovulation induction

PubMed Central

Katsikis, I; Kita, M; Karkanaki, A; Prapas, N; Panidis, D

2006-01-01

Conventional treatment of normogonadotropic anovulatory infertility is ovulation induction using the antiestrogen clomiphene citrate, followed by follicle-stimulating hormone. Multiple follicle development, associated with ovarian hyperstimulation, and multiple pregnancy remain the major complications. Cumulative singleton and multiple pregnancy rate data after different induction treatments are needed. Newer ovulation induction interventions, such as insulin-sensitizing drugs, aromatase inhibitors and laparoscopic ovarian electrocoagulation, should be compared with conventional treatments. Ovulation induction efficiency might improve if patient subgroups with altered chances for success or complications with new or conventional techniques could be identified, using multivariate prediction models based on initial screening characteristics. This would make ovulation induction more cost-effective, safe and convenient, enabling doctors to advise patients on the most effective and patient-tailored treatment strategy. PMID:20351807

Various Indices for Diagnosis of Air-gap Eccentricity Fault in Induction Motor-A Review

NASA Astrophysics Data System (ADS)

Nikhil; Mathew, Lini, Dr.; Sharma, Amandeep

2018-03-01

From the past few years, research has gained an ardent pace in the field of fault detection and diagnosis in induction motors. In the current scenario, software is being introduced with diagnostic features to improve stability and reliability in fault diagnostic techniques. Human involvement in decision making for fault detection is slowly being replaced by Artificial Intelligence techniques. In this paper, a brief introduction of eccentricity fault is presented along with their causes and effects on the health of induction motors. Various indices used to detect eccentricity are being introduced along with their boundary conditions and their future scope of research. At last, merits and demerits of all indices are discussed and a comparison is made between them.

Machine Learning

NASA Astrophysics Data System (ADS)

Hoffmann, Achim; Mahidadia, Ashesh

The purpose of this chapter is to present fundamental ideas and techniques of machine learning suitable for the field of this book, i.e., for automated scientific discovery. The chapter focuses on those symbolic machine learning methods, which produce results that are suitable to be interpreted and understood by humans. This is particularly important in the context of automated scientific discovery as the scientific theories to be produced by machines are usually meant to be interpreted by humans. This chapter contains some of the most influential ideas and concepts in machine learning research to give the reader a basic insight into the field. After the introduction in Sect. 1, general ideas of how learning problems can be framed are given in Sect. 2. The section provides useful perspectives to better understand what learning algorithms actually do. Section 3 presents the Version space model which is an early learning algorithm as well as a conceptual framework, that provides important insight into the general mechanisms behind most learning algorithms. In section 4, a family of learning algorithms, the AQ family for learning classification rules is presented. The AQ family belongs to the early approaches in machine learning. The next, Sect. 5 presents the basic principles of decision tree learners. Decision tree learners belong to the most influential class of inductive learning algorithms today. Finally, a more recent group of learning systems are presented in Sect. 6, which learn relational concepts within the framework of logic programming. This is a particularly interesting group of learning systems since the framework allows also to incorporate background knowledge which may assist in generalisation. Section 7 discusses Association Rules - a technique that comes from the related field of Data mining. Section 8 presents the basic idea of the Naive Bayesian Classifier. While this is a very popular learning technique, the learning result is not well suited for human comprehension as it is essentially a large collection of probability values. In Sect. 9, we present a generic method for improving accuracy of a given learner by generatingmultiple classifiers using variations of the training data. While this works well in most cases, the resulting classifiers have significantly increased complexity and, hence, tend to destroy the human readability of the learning result that a single learner may produce. Section 10 contains a summary, mentions briefly other techniques not discussed in this chapter and presents outlook on the potential of machine learning in the future.

Neural network explanation using inversion.

PubMed

Saad, Emad W; Wunsch, Donald C

2007-01-01

An important drawback of many artificial neural networks (ANN) is their lack of explanation capability [Andrews, R., Diederich, J., & Tickle, A. B. (1996). A survey and critique of techniques for extracting rules from trained artificial neural networks. Knowledge-Based Systems, 8, 373-389]. This paper starts with a survey of algorithms which attempt to explain the ANN output. We then present HYPINV, a new explanation algorithm which relies on network inversion; i.e. calculating the ANN input which produces a desired output. HYPINV is a pedagogical algorithm, that extracts rules, in the form of hyperplanes. It is able to generate rules with arbitrarily desired fidelity, maintaining a fidelity-complexity tradeoff. To our knowledge, HYPINV is the only pedagogical rule extraction method, which extracts hyperplane rules from continuous or binary attribute neural networks. Different network inversion techniques, involving gradient descent as well as an evolutionary algorithm, are presented. An information theoretic treatment of rule extraction is presented. HYPINV is applied to example synthetic problems, to a real aerospace problem, and compared with similar algorithms using benchmark problems.

Real time automatic detection of bearing fault in induction machine using kurtogram analysis.

PubMed

Tafinine, Farid; Mokrani, Karim

2012-11-01

A proposed signal processing technique for incipient real time bearing fault detection based on kurtogram analysis is presented in this paper. The kurtogram is a fourth-order spectral analysis tool introduced for detecting and characterizing non-stationarities in a signal. This technique starts from investigating the resonance signatures over selected frequency bands to extract the representative features. The traditional spectral analysis is not appropriate for non-stationary vibration signal and for real time diagnosis. The performance of the proposed technique is examined by a series of experimental tests corresponding to different bearing conditions. Test results show that this signal processing technique is an effective bearing fault automatic detection method and gives a good basis for an integrated induction machine condition monitor.

A Bayesian Scoring Technique for Mining Predictive and Non-Spurious Rules

PubMed Central

Batal, Iyad; Cooper, Gregory; Hauskrecht, Milos

2015-01-01

Rule mining is an important class of data mining methods for discovering interesting patterns in data. The success of a rule mining method heavily depends on the evaluation function that is used to assess the quality of the rules. In this work, we propose a new rule evaluation score - the Predictive and Non-Spurious Rules (PNSR) score. This score relies on Bayesian inference to evaluate the quality of the rules and considers the structure of the rules to filter out spurious rules. We present an efficient algorithm for finding rules with high PNSR scores. The experiments demonstrate that our method is able to cover and explain the data with a much smaller rule set than existing methods. PMID:25938136

A Bayesian Scoring Technique for Mining Predictive and Non-Spurious Rules.

PubMed

Batal, Iyad; Cooper, Gregory; Hauskrecht, Milos

Rule mining is an important class of data mining methods for discovering interesting patterns in data. The success of a rule mining method heavily depends on the evaluation function that is used to assess the quality of the rules. In this work, we propose a new rule evaluation score - the Predictive and Non-Spurious Rules (PNSR) score. This score relies on Bayesian inference to evaluate the quality of the rules and considers the structure of the rules to filter out spurious rules. We present an efficient algorithm for finding rules with high PNSR scores. The experiments demonstrate that our method is able to cover and explain the data with a much smaller rule set than existing methods.

Extract useful knowledge from agro-hydrological simulations data for decision making

NASA Astrophysics Data System (ADS)

Gascuel-odoux, C.; Bouadi, T.; Cordier, M.; Quiniou, R.

2013-12-01

In recent years, models have been developed and used to test the effect of scenarios and help stakeholders in decision making. Agro-hydrological models have guided agricultural water management by testing the effect of landscape structure and farming system changes on water quantity and quality. Such models generate a large amount of data but few are stored and are often not customized for stakeholders, so that a great amount of information is lost from the simulation process or not transformed in a usable format. A first approach, already published (Trepos et al., 2012), has been developed to identify object oriented tree patterns, that represent surface flow and pollutant pathways from plot to plot, involved in water pollution by herbicides. A simulation model (Gascuel-odoux et al., 2009) predicted herbicide transfer rate, defined as the proportion of applied herbicide that reaches water courses. The predictions were used as a set of learning examples for symbolic learning techniques to induce rules based on qualitative and quantitative attributes and explain two extreme classes in transfer rate. Two automatic symbolic learning techniques were used: the inductive logic programming approach to induce spatial tree patterns, and an attribute-value method to induce aggregated attributes of the trees. A visualization interface allows the users to identify rules explaining contamination and mitigation measures improving the current situation. A second approach has been recently developed to analyse directly the simulated data (Bouadi et al, submitted). A data warehouse called N-catch has been built to store and manage simulation data from the agro-hydrological model TNT2 (Beaujouan et al., 2002). 44 output key simulated variables are stored per plot and at a daily time step on a 50 squared km area, i.e, 8 GB of storage size. After identifying the set of multileveled dimensions integrating hierarchical structures and relationships among related dimension levels, N-Catch has been designed using the open source Business Intelligence Platform Pentaho. We show how to use online analytical processing (OLAP) to access and exploit, intuitively and quickly, the multidimensional and aggregated data from the N-Catch data warehouse. We illustrate how the data warehouse can be used to explore spatio-temporal dimensions efficiently and to discover new knowledge at multiple levels of simulation. OLAP tool can be used to synthesize environmental information and understand nitrogen emissions in water bodies by generating comparative and personalized views of historical data. This DWH is currently extended with data mining or information retrieval methods as Skyline queries to perform advanced analyses (Bouadi et al., 2012). Bouadi et al. N-Catch: A Data Warehouse for Multilevel Analysis of Simulated Nitrogen Data from an Agro-hydrological Model. Submitted. Bouadi et al., 2012) Bouadi, T., Cordier, M., and Quiniou, R. (2012). Incremental computation of skyline queries with dynamic preferences. In DEXA (1), pages 219-233. Trepos et al. 2012. Mining simulation data by rule induction to determine critical source areas of stream water pollution by herbicides. Computers and Electronics in Agriculture 86, 75-88.

Natural language processing and inference rules as strategies for updating problem list in an electronic health record.

PubMed

Plazzotta, Fernando; Otero, Carlos; Luna, Daniel; de Quiros, Fernan Gonzalez Bernaldo

2013-01-01

Physicians do not always keep the problem list accurate, complete and updated. To analyze natural language processing (NLP) techniques and inference rules as strategies to maintain completeness and accuracy of the problem list in EHRs. Non systematic literature review in PubMed, in the last 10 years. Strategies to maintain the EHRs problem list were analyzed in two ways: inputting and removing problems from the problem list. NLP and inference rules have acceptable performance for inputting problems into the problem list. No studies using these techniques for removing problems were published Conclusion: Both tools, NLP and inference rules have had acceptable results as tools for maintain the completeness and accuracy of the problem list.

Rule Mining Techniques to Predict Prokaryotic Metabolic Pathways.

PubMed

Saidi, Rabie; Boudellioua, Imane; Martin, Maria J; Solovyev, Victor

2017-01-01

It is becoming more evident that computational methods are needed for the identification and the mapping of pathways in new genomes. We introduce an automatic annotation system (ARBA4Path Association Rule-Based Annotator for Pathways) that utilizes rule mining techniques to predict metabolic pathways across wide range of prokaryotes. It was demonstrated that specific combinations of protein domains (recorded in our rules) strongly determine pathways in which proteins are involved and thus provide information that let us very accurately assign pathway membership (with precision of 0.999 and recall of 0.966) to proteins of a given prokaryotic taxon. Our system can be used to enhance the quality of automatically generated annotations as well as annotating proteins with unknown function. The prediction models are represented in the form of human-readable rules, and they can be used effectively to add absent pathway information to many proteins in UniProtKB/TrEMBL database.

76 FR 54821 - Proposed Collection; Comment Request

Federal Register 2010, 2011, 2012, 2013, 2014

2011-09-02

... with purchase or sale transactions effected in reliance on the rule. The rule requires the fund's board... affiliated transactions effected during the preceding quarter in reliance on the rule were made in compliance... through the use of automated collection techniques or other forms of information technology. Consideration...

Analysis of Occupational Accidents in Underground and Surface Mining in Spain Using Data-Mining Techniques

PubMed Central

Sanmiquel, Lluís; Bascompta, Marc; Rossell, Josep M.; Anticoi, Hernán Francisco; Guash, Eduard

2018-01-01

An analysis of occupational accidents in the mining sector was conducted using the data from the Spanish Ministry of Employment and Social Safety between 2005 and 2015, and data-mining techniques were applied. Data was processed with the software Weka. Two scenarios were chosen from the accidents database: surface and underground mining. The most important variables involved in occupational accidents and their association rules were determined. These rules are composed of several predictor variables that cause accidents, defining its characteristics and context. This study exposes the 20 most important association rules in the sector—either surface or underground mining—based on the statistical confidence levels of each rule as obtained by Weka. The outcomes display the most typical immediate causes, along with the percentage of accidents with a basis in each association rule. The most important immediate cause is body movement with physical effort or overexertion, and the type of accident is physical effort or overexertion. On the other hand, the second most important immediate cause and type of accident are different between the two scenarios. Data-mining techniques were chosen as a useful tool to find out the root cause of the accidents. PMID:29518921

Analysis of Occupational Accidents in Underground and Surface Mining in Spain Using Data-Mining Techniques.

PubMed

Sanmiquel, Lluís; Bascompta, Marc; Rossell, Josep M; Anticoi, Hernán Francisco; Guash, Eduard

2018-03-07

An analysis of occupational accidents in the mining sector was conducted using the data from the Spanish Ministry of Employment and Social Safety between 2005 and 2015, and data-mining techniques were applied. Data was processed with the software Weka. Two scenarios were chosen from the accidents database: surface and underground mining. The most important variables involved in occupational accidents and their association rules were determined. These rules are composed of several predictor variables that cause accidents, defining its characteristics and context. This study exposes the 20 most important association rules in the sector-either surface or underground mining-based on the statistical confidence levels of each rule as obtained by Weka. The outcomes display the most typical immediate causes, along with the percentage of accidents with a basis in each association rule. The most important immediate cause is body movement with physical effort or overexertion, and the type of accident is physical effort or overexertion. On the other hand, the second most important immediate cause and type of accident are different between the two scenarios. Data-mining techniques were chosen as a useful tool to find out the root cause of the accidents.

The Evolvement of Automobile Steering System Based on TRIZ

NASA Astrophysics Data System (ADS)

Zhao, Xinjun; Zhang, Shuang

Products and techniques pass through a process of birth, growth, maturity, death and quit the stage like biological evolution process. The developments of products and techniques conform to some evolvement rules. If people know and hold these rules, they can design new kind of products and forecast the develop trends of the products. Thereby, enterprises can grasp the future technique directions of products, and make product and technique innovation. Below, based on TRIZ theory, the mechanism evolvement, the function evolvement and the appearance evolvement of automobile steering system had been analyzed and put forward some new ideas about future automobile steering system.

The Value of Data Mining in Music Education Research and Some Findings from Its Application to a Study of Instrumental Learning during Childhood

ERIC Educational Resources Information Center

Faulkner, Robert; Davidson, Jane W.; McPherson, Gary E.

2010-01-01

The use of data mining for the analysis of data collected in natural settings is increasingly recognized as a legitimate mode of enquiry. This rule-inductive paradigm is an effective means of discovering relationships within large datasets--especially in research that has limited experimental design--and for the subsequent formulation of…

The application of magnetic gradiometry and electromagnetic induction at a former radioactive waste disposal site.

PubMed

Rucker, Dale Franklin

2010-04-01

A former radioactive waste disposal site is surveyed with two non-intrusive geophysical techniques, including magnetic gradiometry and electromagnetic induction. Data were gathered over the site by towing the geophysical equipment mounted to a non-electrically conductive and non-magnetic fibre-glass cart. Magnetic gradiometry, which detects the location of ferromagnetic material, including iron and steel, was used to map the existence of a previously unknown buried pipeline formerly used in the delivery of liquid waste to a number of surface disposal trenches and concrete vaults. The existence of a possible pipeline is reinforced by historical engineering drawing and photographs. The electromagnetic induction (EMI) technique was used to map areas of high and low electrical conductivity, which coincide with the magnetic gradiometry data. The EMI also provided information on areas of high electrical conductivity unrelated to a pipeline network. Both data sets demonstrate the usefulness of surface geophysical surveillance techniques to minimize the risk of exposure in the event of future remediation efforts.

Three-year-olds obey the sample size principle of induction: the influence of evidence presentation and sample size disparity on young children's generalizations.

PubMed

Lawson, Chris A

2014-07-01

Three experiments with 81 3-year-olds (M=3.62years) examined the conditions that enable young children to use the sample size principle (SSP) of induction-the inductive rule that facilitates generalizations from large rather than small samples of evidence. In Experiment 1, children exhibited the SSP when exemplars were presented sequentially but not when exemplars were presented simultaneously. Results from Experiment 3 suggest that the advantage of sequential presentation is not due to the additional time to process the available input from the two samples but instead may be linked to better memory for specific individuals in the large sample. In addition, findings from Experiments 1 and 2 suggest that adherence to the SSP is mediated by the disparity between presented samples. Overall, these results reveal that the SSP appears early in development and is guided by basic cognitive processes triggered during the acquisition of input. Copyright © 2013 Elsevier Inc. All rights reserved.

Medical therapeutics: from induction to scientific evolution.

PubMed

Nunes, José Pedro Lopes

2013-01-01

The field of medical therapeutics may be characterized as having suffered major scientific evolution in the last decades. The publication of landmark studies has been important enough to produce shifts in patient care. However, the scientific evolution in this field does not necessarily imply a progressively greater degree of certitude. In fact, it is not uncommon for new knowledge, when reflected in clinical practice, to weaken previous knowledge. In medical therapeutics, strict inductive reasoning implies the existence of empirical intervention data, typically clinical trial data. In many instances, however, such data does not exist-leaving room for a mixture of inductive and "pseudo-deductive" reasoning. It is often necessary to establish treatment on the basis of incomplete and inconclusive information, more so when the clinical situation is grave, but when no valid information exists, no treatment may be an option. In many instances, the rule "I wish not to impose on others" has superseded the concept "Do not impose on others what you yourself do not desire."

The turbulent recirculating flow field in a coreless induction furnace. A comparison of theoretical predictions with measurements

NASA Technical Reports Server (NTRS)

El-Kaddah, N.; Szekely, J.

1982-01-01

A mathematical representation for the electromagnetic force field and the fluid flow field in a coreless induction furnace is presented. The fluid flow field was represented by writing the axisymmetric turbulent Navier-Stokes equation, containing the electromagnetic body force term. The electromagnetic body force field was calculated by using a technique of mutual inductances. The kappa-epsilon model was employed for evaluating the turbulent viscosity and the resultant differential equations were solved numerically. Theoretically predicted velocity fields are in reasonably good agreement with the experimental measurements reported by Hunt and Moore; furthermore, the agreement regarding the turbulent intensities are essentially quantitative. These results indicate that the kappa-epsilon model provides a good engineering representation of the turbulent recirculating flows occurring in induction furnaces. At this stage it is not clear whether the discrepancies between measurements and the predictions, which were not very great in any case, are attributable either to the model or to the measurement techniques employed.

Automatic rule generation for high-level vision

NASA Technical Reports Server (NTRS)

Rhee, Frank Chung-Hoon; Krishnapuram, Raghu

1992-01-01

A new fuzzy set based technique that was developed for decision making is discussed. It is a method to generate fuzzy decision rules automatically for image analysis. This paper proposes a method to generate rule-based approaches to solve problems such as autonomous navigation and image understanding automatically from training data. The proposed method is also capable of filtering out irrelevant features and criteria from the rules.

NONDESTRUCTIVE TESTING (NDT) TECHNIQUES TO DETECT CONTAINED SUBSURFACE HAZARDOUS WASTE

EPA Science Inventory

The project involves the detection of buried containers with NDT (remote-sensing) techniques. Seventeen techniques were considered and four were ultimately decided upon. They were: electromagnetic induction (EMI); metal detection (MD); magnetometer (MAG); and ground penetrating r...

The natural lifespan of a safety policy: violations and system migration in anaesthesia.

PubMed

de Saint Maurice, Guillaume; Auroy, Yves; Vincent, Charles; Amalberti, René

2010-08-01

Safety rules continue growing rapidly, as if constraining human behaviour was the unique avenue for reaching ultimate safety. Safety rules are essential for a safe system, but their multiplication can have counterproductive effects. To monitor, in an anaesthesia ward, compliance with a process-oriented safety rule, and understand barriers and facilitators which help and hinder physicians from following guidelines. The rule stipulated that the day before surgery anaesthetists had to record in the patient's file the drugs to be used for the anaesthesia (induction, maintenance, airway control). Compliance was assessed before introduction of the rule, immediately after, at 6 months and at 12 months. All medical staff were blinded to the protocol. 717 patient records were included. The results showed an initial compliance with policy, reaching 86% for some items (never 100%). Reduction began within 6 months and returned almost to initial levels within a year. One individual showed poor compliance throughout the study but even initially compliant doctors experienced a reduction. Compliance was higher for complex surgery but lower for unscheduled surgery and when job pressure was greater. Compliance eroded over time. A major trigger of erosion seemed to be lack of continued compliance by a senior member of staff. Rules and procedures constitute fragile safety barriers, and it may be better to forego introducing a new safety rule if it is not considered as a priority by staff and is therefore vulnerable to sacrifice in case of conflict with competitive demands.

Learning the Rules: The Anatomy of Children's Relationships.

ERIC Educational Resources Information Center

Bigelow, Brian J.; Tesson, Geoffrey; Lewko, John H.

This book explores the process and characteristics of children's personal and social relationships. To determine what relationships mean to children and how children manage those relationships, a recursive interviewing technique was used with nearly a thousand children to detail children's social rules. Those rules cover a range of social issues,…

Australian and New Zealand Indigenous mothers' report respect for smoking bans in homes.

PubMed

Glover, Marewa; Kira, Anette; Johnston, Vanessa; Walker, Natalie; Brown, Ngiare; Thomas, David

2015-03-01

There is limited data about the reasons behind residential rules to reduce environmental tobacco smoke (ETS) exposure or the establishment or enforcement of such rules in Indigenous populations. We aimed to gain an understanding of smokefree rules around Australian and New Zealand (NZ) Indigenous infants. This was a qualitative study nested within a randomised controlled trial that aimed to test the efficacy of a family-centred tobacco control programme about environmental tobacco smoke (ETS) to improve the respiratory health of Indigenous infants in Australia and New Zealand. Qualitative semi-structured interviews were conducted with 26 Indigenous mothers of infants in Australia (n=7) and NZ (n=19). We asked about the presence of smokefree rules, who set the rules, how the rules were set and enforced, and presence of smokefree rules in participants' wider social circle. Interviews were audiotaped, transcribed, and inductively analysed to identify key themes. Sixty-nine percent of mothers had partners, 77% smoked and all reported some presence of smokefree rules for house and car. Three main themes were identified: strategies to minimise exposure to ETS, establishing smokefree rules in homes and cars, and, adherence and enforcement of smokefree rules. Several strategies were identified to limit children's exposure to ETS, including rules to limit exposure to third-hand smoke. Mothers extended their smokefree rules to apply to other people's houses or cars, and reported that their family and social circles also had smokefree rules. The main reason for having smokefree rules was for the health of their children. Rules were most commonly set by the mother, often jointly with their partner. Few mothers reported challenges or problems with other people adhering to the smokefree rules. Women tried very hard to, and believed that they were effective in, protecting their children from the harmful effects of ETS exposure. In this context, health professionals need to emphasise smoking cessation in parents, so that children are maximally protected from ETS exposure. Copyright © 2014 Australian College of Midwives. Published by Elsevier Ltd. All rights reserved.

Evolving rule-based systems in two medical domains using genetic programming.

PubMed

Tsakonas, Athanasios; Dounias, Georgios; Jantzen, Jan; Axer, Hubertus; Bjerregaard, Beth; von Keyserlingk, Diedrich Graf

2004-11-01

To demonstrate and compare the application of different genetic programming (GP) based intelligent methodologies for the construction of rule-based systems in two medical domains: the diagnosis of aphasia's subtypes and the classification of pap-smear examinations. Past data representing (a) successful diagnosis of aphasia's subtypes from collaborating medical experts through a free interview per patient, and (b) correctly classified smears (images of cells) by cyto-technologists, previously stained using the Papanicolaou method. Initially a hybrid approach is proposed, which combines standard genetic programming and heuristic hierarchical crisp rule-base construction. Then, genetic programming for the production of crisp rule based systems is attempted. Finally, another hybrid intelligent model is composed by a grammar driven genetic programming system for the generation of fuzzy rule-based systems. Results denote the effectiveness of the proposed systems, while they are also compared for their efficiency, accuracy and comprehensibility, to those of an inductive machine learning approach as well as to those of a standard genetic programming symbolic expression approach. The proposed GP-based intelligent methodologies are able to produce accurate and comprehensible results for medical experts performing competitive to other intelligent approaches. The aim of the authors was the production of accurate but also sensible decision rules that could potentially help medical doctors to extract conclusions, even at the expense of a higher classification score achievement.

Metal Solidification Imaging Process by Magnetic Induction Tomography.

PubMed

Ma, Lu; Spagnul, Stefano; Soleimani, Manuchehr

2017-11-06

There are growing number of important applications that require a contactless method for monitoring an object surrounded inside a metallic enclosure. Imaging metal solidification is a great example for which there is no real time monitoring technique at present. This paper introduces a technique - magnetic induction tomography - for the real time in-situ imaging of the metal solidification process. Rigorous experimental verifications are presented. Firstly, a single inductive coil is placed on the top of a melting wood alloy to examine the changes of its inductance during solidification process. Secondly, an array of magnetic induction coils are designed to investigate the feasibility of a tomographic approach, i.e., when one coil is driven by an alternating current as a transmitter and a vector of phase changes are measured from the remaining of the coils as receivers. Phase changes are observed when the wood alloy state changes from liquid to solid. Thirdly, a series of static cold phantoms are created to represent various liquid/solid interfaces to verify the system performance. Finally, a powerful temporal reconstruction method is applied to realise real time in-situ visualisation of the solidification and the measurement of solidified shell thickness, a first report of its kind.

Induction motor control

NASA Technical Reports Server (NTRS)

Hansen, Irving G.

1990-01-01

Electromechanical actuators developed to date have commonly utilized permanent magnet (PM) synchronous motors. More recently switched reluctance (SR) motors have been advocated due to their robust characteristics. Implications of work which utilizes induction motors and advanced control techniques are discussed. When induction motors are operated from an energy source capable of controlling voltages and frequencies independently, drive characteristics are obtained which are superior to either PM or SR motors. By synthesizing the machine frequency from a high frequency carrier (nominally 20 kHz), high efficiencies, low distortion, and rapid torque response are available. At this time multiple horsepower machine drives were demonstrated, and work is on-going to develop a 20 hp average, 40 hp peak class of aerospace actuators. This effort is based upon high frequency power distribution and management techniques developed by NASA for Space Station Freedom.

Induction motor control

NASA Technical Reports Server (NTRS)

Hansen, Irving G.

1990-01-01

Electromechanical actuators developed to date have commonly ultilized permanent magnet (PM) synchronous motors. More recently switched reluctance (SR) motors have been advocated due to their robust characteristics. Implications of work which utilized induction motors and advanced control techniques are discussed. When induction motors are operated from an energy source capable of controlling voltages and frequencies independently, drive characteristics are obtained which are superior to either PM or SR motors. By synthesizing the machine frequency from a high-frequency carrier (nominally 20 kHz), high efficiencies, low distortion, and rapid torque response are available. At this time multiple horsepower machine drives were demonstrated, and work is on-going to develop a 20 hp average, 40 hp peak class of aerospace actuators. This effort is based upon high-frequency power distribution and management techniques developed by NASA for Space Station Freedom.

Locating and Quantifying Broadband Fan Sources Using In-Duct Microphones

NASA Technical Reports Server (NTRS)

Dougherty, Robert P.; Walker, Bruce E.; Sutliff, Daniel L.

2010-01-01

In-duct beamforming techniques have been developed for locating broadband noise sources on a low-speed fan and quantifying the acoustic power in the inlet and aft fan ducts. The NASA Glenn Research Center's Advanced Noise Control Fan was used as a test bed. Several of the blades were modified to provide a broadband source to evaluate the efficacy of the in-duct beamforming technique. Phased arrays consisting of rings and line arrays of microphones were employed. For the imaging, the data were mathematically resampled in the frame of reference of the rotating fan. For both the imaging and power measurement steps, array steering vectors were computed using annular duct modal expansions, selected subsets of the cross spectral matrix elements were used, and the DAMAS and CLEAN-SC deconvolution algorithms were applied.

Aerospace induction motor actuators driven from a 20-kHz power link

NASA Technical Reports Server (NTRS)

Hansen, Irving G.

1990-01-01

Aerospace electromechanical actuators utilizing induction motors are under development in sizes up to 40 kW. While these actuators have immediate application to the Advanced Launch System (ALS) program, several potential applications are currently under study including the Advanced Aircraft Program. Several recent advances developed for the Space Station Freedom have allowed induction motors to be selected as a first choice for such applications. Among these technologies are bi-directional electronics and high frequency power distribution techniques. Each of these technologies are discussed with emphasis on their impact upon induction motor operation.

Inductively Coupled Plasma Mass Spectrometry (ICP-MS) and its Application in Life Sciences

NASA Astrophysics Data System (ADS)

Xu, Gu-feng; Wang, Hong-mei

2001-08-01

Inductively-coupled plasma mass spectrometry (ICP-MS) has made much progress since its birth in the late 1990s. This paper will give a rather systematic overview on the use of this technique in new devices and technologies related to plasma source, sample-introducing device and detecting spectrometer etc. In this overview, an emphasis will be put on the evaluation of the ICP-MS technique in combination with a series of physical, chemical and biological techniques, such as laser ablation (LA), capillary electrophoresis (CE) and high performance liquid chromatograph (HPLC), along with their representative high accuracy and high sensitivity. Finally, comprehensive and fruitful applications of the ICP-MS and its combinative techniques in the detection of trace metallic elements and isotopes in complex biological and environmental samples will be revealed.

Kidney Versus Islet Allograft Survival After Induction of Mixed Chimerism With Combined Donor Bone Marrow Transplantation.

PubMed

Oura, Tetsu; Ko, Dicken S C; Boskovic, Svjetlan; O'Neil, John J; Chipashvili, Vaja; Koulmanda, Maria; Hotta, Kiyohiko; Kawai, Kento; Nadazdin, Ognjenka; Smith, R Neal; Cosimi, A B; Kawai, Tatsuo

2016-01-01

We have previously reported successful induction of transient mixed chimerism and long-term acceptance of renal allografts in MHC mismatched nonhuman primates. In this study, we attempted to extend this tolerance induction approach to islet allografts. A total of eight recipients underwent MHC mismatched combined islet and bone marrow (BM) transplantation after induction of diabetes by streptozotocin. Three recipients were treated after a nonmyeloablative conditioning regimen that included low-dose total body and thymic irradiation, horse Atgam (ATG), six doses of anti-CD154 monoclonal antibody (mAb), and a 1-month course of cyclosporine (CyA) (Islet A). In Islet B, anti-CD8 mAb was administered in place of CyA. In Islet C, two recipients were treated with Islet B, but without ATG. The results were compared with previously reported results of eight cynomolgus monkeys that received combined kidney and BM transplantation (Kidney A) following the same conditioning regimen used in Islet A. The majority of kidney/BM recipients achieved long-term renal allograft survival after induction of transient chimerism. However, prolonged islet survival was not achieved in similarly conditioned islet/BM recipients (Islet A), despite induction of comparable levels of chimerism. In order to rule out islet allograft loss due to CyA toxicity, three recipients were treated with anti-CD8 mAb in place of CyA. Although these recipients developed significantly superior mixed chimerism and more prolonged islet allograft survival (61, 103, and 113 days), islet function was lost soon after the disappearance of chimerism. In Islet C recipients, neither prolonged chimerism nor islet survival was observed (30 and 40 days). Significant improvement of mixed chimerism induction and islet allograft survival were achieved with a CyA-free regimen that included anti-CD8 mAb. However, unlike the kidney allograft, islet allograft tolerance was not induced with transient chimerism. Induction of more durable mixed chimerism may be necessary for induction of islet allograft tolerance.

Supervised Learning in CINets

DTIC Science & Technology

2011-07-01

supervised learning process is compared to that of Artificial Neural Network ( ANNs ), fuzzy logic rule set, and Bayesian network approaches...of both fuzzy logic systems and Artificial Neural Networks ( ANNs ). Like fuzzy logic systems, the CINet technique allows the use of human- intuitive...fuzzy rule systems [3] CINets also maintain features common to both fuzzy systems and ANNs . The technique can be be shown to possess the property

Analysis, Simulation, and Verification of Knowledge-Based, Rule-Based, and Expert Systems

NASA Technical Reports Server (NTRS)

Hinchey, Mike; Rash, James; Erickson, John; Gracanin, Denis; Rouff, Chris

2010-01-01

Mathematically sound techniques are used to view a knowledge-based system (KBS) as a set of processes executing in parallel and being enabled in response to specific rules being fired. The set of processes can be manipulated, examined, analyzed, and used in a simulation. The tool that embodies this technology may warn developers of errors in their rules, but may also highlight rules (or sets of rules) in the system that are underspecified (or overspecified) and need to be corrected for the KBS to operate as intended. The rules embodied in a KBS specify the allowed situations, events, and/or results of the system they describe. In that sense, they provide a very abstract specification of a system. The system is implemented through the combination of the system specification together with an appropriate inference engine, independent of the algorithm used in that inference engine. Viewing the rule base as a major component of the specification, and choosing an appropriate specification notation to represent it, reveals how additional power can be derived from an approach to the knowledge-base system that involves analysis, simulation, and verification. This innovative approach requires no special knowledge of the rules, and allows a general approach where standardized analysis, verification, simulation, and model checking techniques can be applied to the KBS.

Iterative categorization (IC): a systematic technique for analysing qualitative data

PubMed Central

2016-01-01

Abstract The processes of analysing qualitative data, particularly the stage between coding and publication, are often vague and/or poorly explained within addiction science and research more broadly. A simple but rigorous and transparent technique for analysing qualitative textual data, developed within the field of addiction, is described. The technique, iterative categorization (IC), is suitable for use with inductive and deductive codes and can support a range of common analytical approaches, e.g. thematic analysis, Framework, constant comparison, analytical induction, content analysis, conversational analysis, discourse analysis, interpretative phenomenological analysis and narrative analysis. Once the data have been coded, the only software required is a standard word processing package. Worked examples are provided. PMID:26806155

Effect of inter-tissue inductive coupling on multi-frequency imaging of intracranial hemorrhage by magnetic induction tomography

NASA Astrophysics Data System (ADS)

Xiao, Zhili; Tan, Chao; Dong, Feng

2017-08-01

Magnetic induction tomography (MIT) is a promising technique for continuous monitoring of intracranial hemorrhage due to its contactless nature, low cost and capacity to penetrate the high-resistivity skull. The inter-tissue inductive coupling increases with frequency, which may lead to errors in multi-frequency imaging at high frequency. The effect of inter-tissue inductive coupling was investigated to improve the multi-frequency imaging of hemorrhage. An analytical model of inter-tissue inductive coupling based on the equivalent circuit was established. A set of new multi-frequency decomposition equations separating the phase shift of hemorrhage from other brain tissues was derived by employing the coupling information to improve the multi-frequency imaging of intracranial hemorrhage. The decomposition error and imaging error are both decreased after considering the inter-tissue inductive coupling information. The study reveals that the introduction of inter-tissue inductive coupling can reduce the errors of multi-frequency imaging, promoting the development of intracranial hemorrhage monitoring by multi-frequency MIT.

Induction motor broken rotor bar fault location detection through envelope analysis of start-up current using Hilbert transform

NASA Astrophysics Data System (ADS)

Abd-el-Malek, Mina; Abdelsalam, Ahmed K.; Hassan, Ola E.

2017-09-01

Robustness, low running cost and reduced maintenance lead Induction Motors (IMs) to pioneerly penetrate the industrial drive system fields. Broken rotor bars (BRBs) can be considered as an important fault that needs to be early assessed to minimize the maintenance cost and labor time. The majority of recent BRBs' fault diagnostic techniques focus on differentiating between healthy and faulty rotor cage. In this paper, a new technique is proposed for detecting the location of the broken bar in the rotor. The proposed technique relies on monitoring certain statistical parameters estimated from the analysis of the start-up stator current envelope. The envelope of the signal is obtained using Hilbert Transformation (HT). The proposed technique offers non-invasive, fast computational and accurate location diagnostic process. Various simulation scenarios are presented that validate the effectiveness of the proposed technique.

Symptom Induction and De-escalation in the Treatment of Panic Attacks.

ERIC Educational Resources Information Center

Dattilio, Frank M.

1990-01-01

Describes technique known as symptom induction and de-escalation for panic attacks in which goal is to reproduce the type of situation that may precipitate an attack and then to show the client how the attacks can be "turned on" as well as "turned off." (ABL)

Low-inductance bus lines

NASA Technical Reports Server (NTRS)

Kernick, A.

1977-01-01

Laminated bus strips and bifilar litz cable connectors for high-power rectifiers, thrisistors, and transistors provide low inductance and eliminate electromagnetic interference in high-power circuits. These techniques offer significant cost advantages because of ease of assembly and consistent high quality of product. Effectiveness makes general usage in static power conversion likely.

A neural network simulation package in CLIPS

NASA Technical Reports Server (NTRS)

Bhatnagar, Himanshu; Krolak, Patrick D.; Mcgee, Brenda J.; Coleman, John

1990-01-01

The intrinsic similarity between the firing of a rule and the firing of a neuron has been captured in this research to provide a neural network development system within an existing production system (CLIPS). A very important by-product of this research has been the emergence of an integrated technique of using rule based systems in conjunction with the neural networks to solve complex problems. The systems provides a tool kit for an integrated use of the two techniques and is also extendible to accommodate other AI techniques like the semantic networks, connectionist networks, and even the petri nets. This integrated technique can be very useful in solving complex AI problems.

Strong induction effects during the substorm on 27 August 2001

NASA Astrophysics Data System (ADS)

Mishin, V. V.; Mishin, V. M.; Lunyushkin, S. B.; Pu, Z.; Wang, C.

2015-10-01

We report on strong induction effects notably contributing to the cross polar cap potential drop and the energy balance during the growth and active phases of the substorm on 27 August 2001. The inductance of the magnetosphere is found to be crucial for the energy balance and electrical features of the magnetosphere in the course of the substorm. The inductive response to the switching on and off of the solar wind-magnetosphere generator exceeds the effect of the interplanetary magnetic field (IMF) variation. The induction effects are most apparent during the substorm expansion onset when the rapid growth of the ionospheric conductivity is accompanied by the fast release of the magnetic energy stored in the magnetotail during the growth phase. Using the magnetogram inversion technique, we estimated the magnetospheric inductance and effective ionospheric conductivity during the loading and unloading phases.

Fundamentals of electric power conversion. Volume 2, Energy-efficient polyphase AC induction motors, final report

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

Umans, S.D.

1992-12-01

Its rugged nature and straightforward design make the induction motor the most commonly used type of electric motor. This motor ranges in size fro the fractional-horsepower, single-phase motors found in household appliances to polyphase motors rated at thousands of horsepower for industrial applications. Volume 1 of this report describes the function of induction motors, their characteristics, and induction motor testing. Volume 2 describes the characteristics of high-efficiency induction motors, with emphasis on the techniques used to obtain high efficiency. This two-volume report is written in nontechnical language and is intended for readers who require background from applications, marketing, motor planning,more » or managerial perspective.« less

Fundamentals of electric power conversion. Volume 1, Operating characteristics and testing of AC induction motors, final report

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

Umans, S.D.

1992-12-01

Its rugged nature and straightforward design make the induction motor the most commonly used type of electric motor. This motor ranges in size from the fractional-horsepower, single-phase motors found in household appliances to polyphase motors rated at thousands of horsepower for industrial applications. Volume 1 of this report describes the function of induction motors, their characteristics, and induction motor testing. Volume 2 describes the characteristics of high-efficiency induction motors, with emphasis on the techniques used to obtain high efficiency. This two-volume report is written in nontechnical language and is intended for readers who require background from an applications, marketing, motormore » planning, or managerial perspective.« less

Simple methods of exploiting the underlying structure of rule-based systems

NASA Technical Reports Server (NTRS)

Hendler, James

1986-01-01

Much recent work in the field of expert systems research has aimed at exploiting the underlying structures of the rule base for reasons of analysis. Such techniques as Petri-nets and GAGs have been proposed as representational structures that will allow complete analysis. Much has been made of proving isomorphisms between the rule bases and the mechanisms, and in examining the theoretical power of this analysis. In this paper we describe some early work in a new system which has much simpler (and thus, one hopes, more easily achieved) aims and less formality. The technique being examined is a very simple one: OPS5 programs are analyzed in a purely syntactic way and a FSA description is generated. In this paper we describe the technique and some user interface tools which exploit this structure.

Quasi-chemical theory of F-(aq): The "no split occupancies rule" revisited

NASA Astrophysics Data System (ADS)

Chaudhari, Mangesh I.; Rempe, Susan B.; Pratt, Lawrence R.

2017-10-01

We use ab initio molecular dynamics (AIMD) calculations and quasi-chemical theory (QCT) to study the inner-shell structure of F-(aq) and to evaluate that single-ion free energy under standard conditions. Following the "no split occupancies" rule, QCT calculations yield a free energy value of -101 kcal/mol under these conditions, in encouraging agreement with tabulated values (-111 kcal/mol). The AIMD calculations served only to guide the definition of an effective inner-shell constraint. QCT naturally includes quantum mechanical effects that can be concerning in more primitive calculations, including electronic polarizability and induction, electron density transfer, electron correlation, molecular/atomic cooperative interactions generally, molecular flexibility, and zero-point motion. No direct assessment of the contribution of dispersion contributions to the internal energies has been attempted here, however. We anticipate that other aqueous halide ions might be treated successfully with QCT, provided that the structure of the underlying statistical mechanical theory is absorbed, i.e., that the "no split occupancies" rule is recognized.

Comparison of Acid Titration, Conductivity, Flame Photometry, ICP-MS, and Accelerated Lamellae Formation Techniques in Determining Glass Vial Quality.

PubMed

Fujimori, Kiyoshi; Lee, Hans; Sloey, Christopher; Ricci, Margaret S; Wen, Zai-Qing; Phillips, Joseph; Nashed-Samuel, Yasser

2016-01-01

Certain types of glass vials used as primary containers for liquid formulations of biopharmaceutical drug products have been observed with delamination that produced small glass like flakes termed lamellae under certain conditions during storage. The cause of this delamination is in part related to the glass surface defects, which renders the vials susceptible to flaking, and lamellae are formed during the high-temperature melting and annealing used for vial fabrication and shaping. The current European Pharmacopoeia method to assess glass vial quality utilizes acid titration of vial extract pools to determine hydrolytic resistance or alkalinity. Four alternative techniques with improved throughput, convenience, and/or comprehension were examined by subjecting seven lots of vials to analysis by all techniques. The first three new techniques of conductivity, flame photometry, and inductively coupled plasma mass spectrometry measured the same sample pools as acid titration. All three showed good correlation with alkalinity: conductivity (R(2) = 0.9951), flame photometry sodium (R(2) = 0.9895), and several elements by inductively coupled plasma mass spectrometry [(sodium (R(2) = 0.9869), boron (R(2) = 0.9796), silicon (R(2) = 0.9426), total (R(2) = 0.9639)]. The fourth technique processed the vials under conditions that promote delamination, termed accelerated lamellae formation, and then inspected those vials visually for lamellae. The visual inspection results without the lot with different processing condition correlated well with alkalinity (R(2) = 0.9474). Due to vial processing differences affecting alkalinity measurements and delamination propensity differently, the ratio of silicon and sodium measurements from inductively coupled plasma mass spectrometry was the most informative technique to assess overall vial quality and vial propensity for lamellae formation. The other techniques of conductivity, flame photometry, and accelerated lamellae formation condition may still be suitable for routine screening of vial lots produced under consistent processes. Recently, delamination that produced small glass like flakes termed lamellae has been observed in glass vials that are commonly used as primary containers for pharmaceutical drug products under certain conditions during storage. The main cause of these lamellae was the quality of the glass itself related to the manufacturing process. Current European Pharmacopoeia method to assess glass vial quality utilizes acid titration of vial extract pools to determine hydrolytic resistance or alkalinity. As alternative to the European Pharmacopoeia method, four other techniques were assessed. Three new techniques of conductivity, flame photometry, and inductively coupled plasma mass spectrometry measured the vial extract pool as acid titration to quantify quality, and they demonstrated good correlation with original alkalinity. The fourth technique processed the vials under conditions that promote delamination, termed accelerated lamellae formation, and the vials were then inspected visually for lamellae. The accelerated lamellae formation technique also showed good correlation with alkalinity. Of the new four techniques, inductively coupled plasma mass spectrometry was the most informative technique to assess overall vial quality even with differences in processing between vial lots. Other three techniques were still suitable for routine screening of vial lots produced under consistent processes. © PDA, Inc. 2016.

Numerical and experimental study of curved and planar frequency selective surfaces with arbitrary illumination. M.S. Thesis - Maryland Univ., 1989

NASA Technical Reports Server (NTRS)

Caroglanian, Armen

1991-01-01

A frequency selective surface (FSS) composed of apertures in a metallic sheet is known as the inductive FSS. The infinite inductive FSS theory is derived and the aperture fields are solved by a spectral domain formulation with method of moments solution. Both full domain and subsectional basis functions are studied. A locally planar technique (LPT) is used to determine the forward scattered field from a generally shaped inductive FSS with arbitrary illumination.

77 FR 47050 - Commission Information Collection Activities; Comment Request

Federal Register 2010, 2011, 2012, 2013, 2014

2012-08-07

... for violations of the Anti-Manipulation rule or other rules, regulations, or orders to which the price... automated collection techniques or other forms of information technology. Dated: August 1, 2012. Kimberly D...

Exploration of association rule mining for coding consistency and completeness assessment in inpatient administrative health data.

PubMed

Peng, Mingkai; Sundararajan, Vijaya; Williamson, Tyler; Minty, Evan P; Smith, Tony C; Doktorchik, Chelsea T A; Quan, Hude

2018-03-01

Data quality assessment is a challenging facet for research using coded administrative health data. Current assessment approaches are time and resource intensive. We explored whether association rule mining (ARM) can be used to develop rules for assessing data quality. We extracted 2013 and 2014 records from the hospital discharge abstract database (DAD) for patients between the ages of 55 and 65 from five acute care hospitals in Alberta, Canada. The ARM was conducted using the 2013 DAD to extract rules with support ≥0.0019 and confidence ≥0.5 using the bootstrap technique, and tested in the 2014 DAD. The rules were compared against the method of coding frequency and assessed for their ability to detect error introduced by two kinds of data manipulation: random permutation and random deletion. The association rules generally had clear clinical meanings. Comparing 2014 data to 2013 data (both original), there were 3 rules with a confidence difference >0.1, while coding frequency difference of codes in the right hand of rules was less than 0.004. After random permutation of 50% of codes in the 2014 data, average rule confidence dropped from 0.72 to 0.27 while coding frequency remained unchanged. Rule confidence decreased with the increase of coding deletion, as expected. Rule confidence was more sensitive to code deletion compared to coding frequency, with slope of change ranging from 1.7 to 184.9 with a median of 9.1. The ARM is a promising technique to assess data quality. It offers a systematic way to derive coding association rules hidden in data, and potentially provides a sensitive and efficient method of assessing data quality compared to standard methods. Copyright © 2018 Elsevier Inc. All rights reserved.

Fundamentals of electric power conversion

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

Umans, S.D.

1992-12-01

Its rugged nature and straightforward design make the induction motor the most commonly used type of electric motor. This motor ranges in size from the fractional-horsepower, single-phase motors found in household appliances to polyphase motors rated at thousands of horsepower for industrial applications. Volume 1 of this report describes the function of induction motors, their characteristics, and induction motor testing. Volume 2 describes the characteristics of high-efficiency induction motors, with emphasis on the techniques used to obtain high efficiency. This two-volume report is written in nontechnical language and is intended for readers who require background from an applications, marketing, motormore » planning, or managerial perspective.« less

Fundamentals of electric power conversion

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

Umans, S.D.

1992-12-01

Its rugged nature and straightforward design make the induction motor the most commonly used type of electric motor. This motor ranges in size fro the fractional-horsepower, single-phase motors found in household appliances to polyphase motors rated at thousands of horsepower for industrial applications. Volume 1 of this report describes the function of induction motors, their characteristics, and induction motor testing. Volume 2 describes the characteristics of high-efficiency induction motors, with emphasis on the techniques used to obtain high efficiency. This two-volume report is written in nontechnical language and is intended for readers who require background from applications, marketing, motor planning,more » or managerial perspective.« less

An Intelligent Harmonic Synthesis Technique for Air-Gap Eccentricity Fault Diagnosis in Induction Motors

NASA Astrophysics Data System (ADS)

Li, De Z.; Wang, Wilson; Ismail, Fathy

2017-11-01

Induction motors (IMs) are commonly used in various industrial applications. To improve energy consumption efficiency, a reliable IM health condition monitoring system is very useful to detect IM fault at its earliest stage to prevent operation degradation, and malfunction of IMs. An intelligent harmonic synthesis technique is proposed in this work to conduct incipient air-gap eccentricity fault detection in IMs. The fault harmonic series are synthesized to enhance fault features. Fault related local spectra are processed to derive fault indicators for IM air-gap eccentricity diagnosis. The effectiveness of the proposed harmonic synthesis technique is examined experimentally by IMs with static air-gap eccentricity and dynamic air-gap eccentricity states under different load conditions. Test results show that the developed harmonic synthesis technique can extract fault features effectively for initial IM air-gap eccentricity fault detection.

Exploration of SWRL Rule Bases through Visualization, Paraphrasing, and Categorization of Rules

NASA Astrophysics Data System (ADS)

Hassanpour, Saeed; O'Connor, Martin J.; Das, Amar K.

Rule bases are increasingly being used as repositories of knowledge content on the Semantic Web. As the size and complexity of these rule bases increases, developers and end users need methods of rule abstraction to facilitate rule management. In this paper, we describe a rule abstraction method for Semantic Web Rule Language (SWRL) rules that is based on lexical analysis and a set of heuristics. Our method results in a tree data structure that we exploit in creating techniques to visualize, paraphrase, and categorize SWRL rules. We evaluate our approach by applying it to several biomedical ontologies that contain SWRL rules, and show how the results reveal rule patterns within the rule base. We have implemented our method as a plug-in tool for Protégé-OWL, the most widely used ontology modeling software for the Semantic Web. Our tool can allow users to rapidly explore content and patterns in SWRL rule bases, enabling their acquisition and management.

On recursion.

PubMed

Watumull, Jeffrey; Hauser, Marc D; Roberts, Ian G; Hornstein, Norbert

2014-01-08

It is a truism that conceptual understanding of a hypothesis is required for its empirical investigation. However, the concept of recursion as articulated in the context of linguistic analysis has been perennially confused. Nowhere has this been more evident than in attempts to critique and extend Hauseretal's. (2002) articulation. These authors put forward the hypothesis that what is uniquely human and unique to the faculty of language-the faculty of language in the narrow sense (FLN)-is a recursive system that generates and maps syntactic objects to conceptual-intentional and sensory-motor systems. This thesis was based on the standard mathematical definition of recursion as understood by Gödel and Turing, and yet has commonly been interpreted in other ways, most notably and incorrectly as a thesis about the capacity for syntactic embedding. As we explain, the recursiveness of a function is defined independent of such output, whether infinite or finite, embedded or unembedded-existent or non-existent. And to the extent that embedding is a sufficient, though not necessary, diagnostic of recursion, it has not been established that the apparent restriction on embedding in some languages is of any theoretical import. Misunderstanding of these facts has generated research that is often irrelevant to the FLN thesis as well as to other theories of language competence that focus on its generative power of expression. This essay is an attempt to bring conceptual clarity to such discussions as well as to future empirical investigations by explaining three criterial properties of recursion: computability (i.e., rules in intension rather than lists in extension); definition by induction (i.e., rules strongly generative of structure); and mathematical induction (i.e., rules for the principled-and potentially unbounded-expansion of strongly generated structure). By these necessary and sufficient criteria, the grammars of all natural languages are recursive.

A novel logic-based approach for quantitative toxicology prediction.

PubMed

Amini, Ata; Muggleton, Stephen H; Lodhi, Huma; Sternberg, Michael J E

2007-01-01

There is a pressing need for accurate in silico methods to predict the toxicity of molecules that are being introduced into the environment or are being developed into new pharmaceuticals. Predictive toxicology is in the realm of structure activity relationships (SAR), and many approaches have been used to derive such SAR. Previous work has shown that inductive logic programming (ILP) is a powerful approach that circumvents several major difficulties, such as molecular superposition, faced by some other SAR methods. The ILP approach reasons with chemical substructures within a relational framework and yields chemically understandable rules. Here, we report a general new approach, support vector inductive logic programming (SVILP), which extends the essentially qualitative ILP-based SAR to quantitative modeling. First, ILP is used to learn rules, the predictions of which are then used within a novel kernel to derive a support-vector generalization model. For a highly heterogeneous dataset of 576 molecules with known fathead minnow fish toxicity, the cross-validated correlation coefficients (R2CV) from a chemical descriptor method (CHEM) and SVILP are 0.52 and 0.66, respectively. The ILP, CHEM, and SVILP approaches correctly predict 55, 58, and 73%, respectively, of toxic molecules. In a set of 165 unseen molecules, the R2 values from the commercial software TOPKAT and SVILP are 0.26 and 0.57, respectively. In all calculations, SVILP showed significant improvements in comparison with the other methods. The SVILP approach has a major advantage in that it uses ILP automatically and consistently to derive rules, mostly novel, describing fragments that are toxicity alerts. The SVILP is a general machine-learning approach and has the potential of tackling many problems relevant to chemoinformatics including in silico drug design.

On recursion

PubMed Central

Watumull, Jeffrey; Hauser, Marc D.; Roberts, Ian G.; Hornstein, Norbert

2014-01-01

It is a truism that conceptual understanding of a hypothesis is required for its empirical investigation. However, the concept of recursion as articulated in the context of linguistic analysis has been perennially confused. Nowhere has this been more evident than in attempts to critique and extend Hauseretal's. (2002) articulation. These authors put forward the hypothesis that what is uniquely human and unique to the faculty of language—the faculty of language in the narrow sense (FLN)—is a recursive system that generates and maps syntactic objects to conceptual-intentional and sensory-motor systems. This thesis was based on the standard mathematical definition of recursion as understood by Gödel and Turing, and yet has commonly been interpreted in other ways, most notably and incorrectly as a thesis about the capacity for syntactic embedding. As we explain, the recursiveness of a function is defined independent of such output, whether infinite or finite, embedded or unembedded—existent or non-existent. And to the extent that embedding is a sufficient, though not necessary, diagnostic of recursion, it has not been established that the apparent restriction on embedding in some languages is of any theoretical import. Misunderstanding of these facts has generated research that is often irrelevant to the FLN thesis as well as to other theories of language competence that focus on its generative power of expression. This essay is an attempt to bring conceptual clarity to such discussions as well as to future empirical investigations by explaining three criterial properties of recursion: computability (i.e., rules in intension rather than lists in extension); definition by induction (i.e., rules strongly generative of structure); and mathematical induction (i.e., rules for the principled—and potentially unbounded—expansion of strongly generated structure). By these necessary and sufficient criteria, the grammars of all natural languages are recursive. PMID:24409164

Rules and Laws against Light Pollution in Italy

NASA Astrophysics Data System (ADS)

di Sora, Mario

1999-08-01

Campo Catino astronomical observatory is engaged in fighting light pollution for many years. In Italy, after many years of unjustified inactivity by astronomers and amateurs, a movement of opinion is born intending to resolve this problem definitely. All that through this themes spread at cultural and technical level and, above all, obtaining municipal and regional rules approval and national law. In this field the Campo Catino astronomical observatory distinguishes itself particularly because it has contributed to edit the Bill (No. 751) proposed to the Italian parliament by Senator Lino Diana, (in 1992 and subsequently in 1994 and 1996), it is entitled: "Urgent measures about the fight against light pollution and the induction of power consumption by using external lighting." and, because, Campo Catino observatory has elaborated a rule already approved by several municipalities in Frosinone province (but utilized as example by other Italian municipalities as Florence, Civitavecchia and Piacenza). It proposes to reduce, by five years after its approval, the artificial lights spread high-up and energy consumptions by using appropriate criteria and products. In this presentation the author explains juridical and technical aspects concerning the rules and laws created to fight light pollution in Italy.

Automated diagnosis of coronary artery disease based on data mining and fuzzy modeling.

PubMed

Tsipouras, Markos G; Exarchos, Themis P; Fotiadis, Dimitrios I; Kotsia, Anna P; Vakalis, Konstantinos V; Naka, Katerina K; Michalis, Lampros K

2008-07-01

A fuzzy rule-based decision support system (DSS) is presented for the diagnosis of coronary artery disease (CAD). The system is automatically generated from an initial annotated dataset, using a four stage methodology: 1) induction of a decision tree from the data; 2) extraction of a set of rules from the decision tree, in disjunctive normal form and formulation of a crisp model; 3) transformation of the crisp set of rules into a fuzzy model; and 4) optimization of the parameters of the fuzzy model. The dataset used for the DSS generation and evaluation consists of 199 subjects, each one characterized by 19 features, including demographic and history data, as well as laboratory examinations. Tenfold cross validation is employed, and the average sensitivity and specificity obtained is 62% and 54%, respectively, using the set of rules extracted from the decision tree (first and second stages), while the average sensitivity and specificity increase to 80% and 65%, respectively, when the fuzzification and optimization stages are used. The system offers several advantages since it is automatically generated, it provides CAD diagnosis based on easily and noninvasively acquired features, and is able to provide interpretation for the decisions made.

Refractory metal shielding /insulation/ increases operating range of induction furnace

NASA Technical Reports Server (NTRS)

Ebihara, B. T.

1965-01-01

Thermal radiation shield contains escaping heat from an induction furnace. The shield consists of a sheet of refractory metal foil and a loosely packed mat of refractory metal fibers in a concentric pattern. This shielding technique can be used for high temperature ovens, high temperature fluid lines, and chemical reaction vessels.

A qualitative review for wireless health monitoring system

NASA Astrophysics Data System (ADS)

Arshad, Atika; Fadzil Ismail, Ahmad; Khan, Sheroz; Zahirul Alam, A. H. M.; Tasnim, Rumana; Samnan Haider, Syed; Shobaki, Mohammed M.; Shahid, Zeeshan

2013-12-01

A proliferating interest has been being observed over the past years in accurate wireless system development in order to monitor incessant human activities in health care centres. Furthermore because of the swelling number of elderly population and the inadequate number of competent staffs for nursing homes there is a big market petition for health care monitoring system. In order to detect human researchers developed different methods namely which include Field Identification technique, Visual Sensor Network, radar detection, e-mobile techniques and so on. An all-encompassing overview of the non-wired human detection application advancement is presented in this paper. Inductive links are used for human detection application while wiring an electronic system has become impractical in recent times. Keeping in mind the shortcomings, an Inductive Intelligent Sensor (IIS) has been proposed as a novel human monitoring system for future implementation. The proposed sensor works towards exploring the signature signals of human body movement and size. This proposed sensor is fundamentally based on inductive loop that senses the presence and a passing human resulting an inductive change.

Development of in situ two-coil mutual inductance technique in a multifunctional scanning tunneling microscope.

PubMed

Duan, Ming-Chao; Liu, Zhi-Long; Ge, Jian-Feng; Tang, Zhi-Jun; Wang, Guan-Yong; Wang, Zi-Xin; Guan, Dandan; Li, Yao-Yi; Qian, Dong; Liu, Canhua; Jia, Jin-Feng

2017-07-01

Superconducting thin films have been a focal point for intensive research efforts since their reduced dimension allows for a wide variety of quantum phenomena. Many of these films, fabricated in UHV chambers, are highly vulnerable to air exposure, making it difficult to measure intrinsic superconducting properties such as zero resistance and perfect diamagnetism with ex situ experimental techniques. Previously, we developed a multifunctional scanning tunneling microscope (MSTM) containing in situ four-point probe (4PP) electrical transport measurement capability in addition to the usual STM capabilities [Ge et al., Rev. Sci. Instrum. 86, 053903 (2015)]. Here we improve this MSTM via development of both transmission and reflection two-coil mutual inductance techniques for in situ measurement of the diamagnetic response of a superconductor. This addition does not alter the original STM and 4PP functions of the MSTM. We demonstrate the performance of the two-coil mutual inductance setup on a 10-nm-thick NbN thin film grown on a Nb-doped SrTiO 3 (111) substrate.

Optimising Sterilisation Techniques and Callus Induction of Nodes Durio Zibethinus Murr in Vitro Method with Various Media

NASA Astrophysics Data System (ADS)

Hermayani, N.; Retnoningsih, A.; Rahayu, E. S.

2017-04-01

The application of in vitro propagation method needs an aseptic or sterile condition. The objective of the study was to get an optimal sterilisation techniques and medium of callus induction of Durio zibethinus. Sterilisation treatments studied were NaClO and Ca(ClO)2. The three kind of callus induction medium studied were Gamborg (B5), Woody Plant Medium (WPM), and Murashige and Skoog (MS) with the addition of auxin and cytokinin. The experiment unit was three bottles with nodes as explant. Cultures were kept in the culture room for 16 hours daily by LED light intensity of 1000 lux. Parameters investigated of sterilisation technique development was the percentage of contamination, the percentage of explant browning, and the percentage of life explants; whereas the callus induction measured were the rate of callus formation, percentage of callus covered, callus texture, colour and diameter of callus. The results showed that the code of C3 is soaking in calcium hypochlorite (Ca(ClO)2) 50% for 3 minutes, calcium hypochlorite 40% for 2 minutes, and 70% alcohol for 30 seconds separately were suitable for sterilisation of nodes explant. The development of callus on B5 medium with the addition of auxin (2,4-D) 2 ppm and cytokinin (Thidiazuron) 1 ppm was best compared to the other.

Study of the production of unique new glasses

NASA Technical Reports Server (NTRS)

Happe, R. A.

1972-01-01

A number of high new oxide glasses have been prepared by a laser-spin melting technique where droplets are ejected from a molten mass. Techniques have been developed for measuring the optical properties of most of the new glasses so produced. A preliminary study of processing equipment for producing new glasses in a zero gravity environment onboard manned space laboratory is reported. Induction and laser melting emerge as preferred techniques for melting spheroids of new glass compositions in space. Sample calculations for power required to induction melt new glass compositions are presented. Cooling rate calculations show that radiation cooling of the high melting materials results in very short cooling times for 1/2 inch diameters to temperatures where the spheroids can be handled.

Plasminogen activator: analysis of enzyme induction by ultraviolet irradiation mapping

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

Miskin, R.; Reich, E.; Dixon, K.

1981-10-01

Ultraviolet irradiation mapping techniques have previously been used to study the organization of eucaryotic gene classes and transcription units. We used the same method to probe some regulatory phenomena observed in the induction of plasminogen activator (PA) biosynthesis: PA synthesis in chicken embryo fibroblasts is induced by tumor-promoting phorbol esters and by retinoic acid; furthermore, PA induction by phorbol esters is synergistic with transformation, being 10- to 20-fold greater in virus-transformed cells than in normal cells. We found that the ultraviolet irradiation inactivation cross sections for PA induction by phorbol esters and by retinoate differed significantly, suggesting that these agentsmore » induce PA biosynthesis by different mechanisms. On the other hand, the ultraviolet irradiation sensitivity of phorbol ester induction in normal chicken embryo fibroblasts was the same as in transformed cells, indicating that the synergism of transformation and phorbol esters is probably not due to different pathways of PA induction.« less

[Unconscious induction of emotions and unintended change in behavior].

PubMed

Sokolowski, K

1992-01-01

The problem of most mood induction procedures in psychological laboratories is located in their demand characteristics. The subjects either have to help change their mood actively, or are at best only passively aware of the induction process. To overcome the necessity of consciousness of the mood induction procedure we developed a technique based on the involuntary tendency to imitate the expression of perceived faces ("emotional infection"). Three different mood induction conditions--operationalized by means of happy, neutral, or sad pairs of faces, which had to be compared in spite of their age--were imbedded in an experiment disguised as, research in perception'. The results show mood influences only in the behavioral measures: Happy induced subjects wrote significantly faster than neutral and sad ones. In contrast, the self description data--measured via mood adjectives--showed no typical changes due to the induction condition. The subjects seemed to be unaware of the cause and the effect of their changed mood.

Improving Predictions of Multiple Binary Models in ILP

PubMed Central

2014-01-01

Despite the success of ILP systems in learning first-order rules from small number of examples and complexly structured data in various domains, they struggle in dealing with multiclass problems. In most cases they boil down a multiclass problem into multiple black-box binary problems following the one-versus-one or one-versus-rest binarisation techniques and learn a theory for each one. When evaluating the learned theories of multiple class problems in one-versus-rest paradigm particularly, there is a bias caused by the default rule toward the negative classes leading to an unrealistic high performance beside the lack of prediction integrity between the theories. Here we discuss the problem of using one-versus-rest binarisation technique when it comes to evaluating multiclass data and propose several methods to remedy this problem. We also illustrate the methods and highlight their link to binary tree and Formal Concept Analysis (FCA). Our methods allow learning of a simple, consistent, and reliable multiclass theory by combining the rules of the multiple one-versus-rest theories into one rule list or rule set theory. Empirical evaluation over a number of data sets shows that our proposed methods produce coherent and accurate rule models from the rules learned by the ILP system of Aleph. PMID:24696657

Mitochondrial replacement techniques and Mexico's rule of law: on the legality of the first maternal spindle transfer case

PubMed Central

Medina-Arellano, María de Jesús

2017-01-01

Abstract News about the first baby born after a mitochondrial replacement technique (MRT; specifically maternal spindle transfer) broke on September 27, 2016 and, in a matter of hours, went global. Of special interest was the fact that the mitochondrial replacement procedure happened in Mexico. One of the scientists behind this world first was quoted as having said that he and his team went to Mexico to carry out the procedure because, in Mexico, there are no rules. In this paper, we explore Mexico's rule of law in relation to mitochondrial replacement techniques and show that, in fact, certain instances of MRTs are prohibited at the federal level and others are prohibited at the state level. According to our interpretation of the law, the scientists behind this first successful MRT procedure broke federal regulations regarding assisted fertilization research. PMID:28852557

A Simple and Accurate Analysis of Conductivity Loss in Millimeter-Wave Helical Slow-Wave Structures

NASA Astrophysics Data System (ADS)

Datta, S. K.; Kumar, Lalit; Basu, B. N.

2009-04-01

Electromagnetic field analysis of a helix slow-wave structure was carried out and a closed form expression was derived for the inductance per unit length of the transmission-line equivalent circuit of the structure, taking into account the actual helix tape dimensions and surface current on the helix over the actual metallic area of the tape. The expression of the inductance per unit length, thus obtained, was used for estimating the increment in the inductance per unit length caused due to penetration of the magnetic flux into the conducting surfaces following Wheeler’s incremental inductance rule, which was subsequently interpreted for the attenuation constant of the propagating structure. The analysis was computationally simple and accurate, and accrues the accuracy of 3D electromagnetic analysis by allowing the use of dispersion characteristics obtainable from any standard electromagnetic modeling. The approach was benchmarked against measurement for two practical structures, and excellent agreement was observed. The analysis was subsequently applied to demonstrate the effects of conductivity on the attenuation constant of a typical broadband millimeter-wave helical slow-wave structure with respect to helix materials and copper plating on the helix, surface finish of the helix, dielectric loading effect and effect of high temperature operation - a comparative study of various such aspects are covered.

Accurate Induction Energies for Small Organic Molecules. 2. Development and Testing of Distributed Polarizability Models against SAPT(DFT) Energies.

PubMed

Misquitta, Alston J; Stone, Anthony J; Price, Sarah L

2008-01-01

In part 1 of this two-part investigation we set out the theoretical basis for constructing accurate models of the induction energy of clusters of moderately sized organic molecules. In this paper we use these techniques to develop a variety of accurate distributed polarizability models for a set of representative molecules that include formamide, N-methyl propanamide, benzene, and 3-azabicyclo[3.3.1]nonane-2,4-dione. We have also explored damping, penetration, and basis set effects. In particular, we have provided a way to treat the damping of the induction expansion. Different approximations to the induction energy are evaluated against accurate SAPT(DFT) energies, and we demonstrate the accuracy of our induction models on the formamide-water dimer.

Definition of Time Induction of Self-Ignition of the Substance on the Prognostic Extrapolation Depending on the Basis of Indicators Fire and Explosion Hazard

NASA Astrophysics Data System (ADS)

Sechin, A.; Kyrmakova, O.; Osipenko, S.

2016-01-01

In this article the research directed on development of a technique of definition of time of induction of the self-ignition of substances and materials which is an indicator of the beginning of development of an emergency is conducted. The experiment consisting in supervision over process of self-ignition of coal and oil deposits was the basis for research. On the basis of experimental data the curve expressing analytic - expected dependence of size of temperature of ignition on induction time was constructed. Proceeding from graphical representation of process, functional dependence of time of induction on a temperature indicator was received: y = 16920 • x0 537. By means of known indicators of such substances as bitumen oil oxidized (the combustible solid substance received by oxidation of residual product of oil refining) and tar oil (the combustible solid substance which is residual product of oil refining) and the received algorithm, verification of reliability of the received dependence and a technique of definition of time of induction of spontaneous ignition of deposits of oil in general was carried out. The practical importance of the conducted research is that having data on time of induction of process of self-ignition, by means of preventive measures becomes possible to avoid and prevent accidents in oil and oil processing branches, at the same time loss of property and loss of human life.

Biometric image enhancement using decision rule based image fusion techniques

NASA Astrophysics Data System (ADS)

Sagayee, G. Mary Amirtha; Arumugam, S.

2010-02-01

Introducing biometrics into information systems may result in considerable benefits. Most of the researchers confirmed that the finger print is widely used than the iris or face and more over it is the primary choice for most privacy concerned applications. For finger prints applications, choosing proper sensor is at risk. The proposed work deals about, how the image quality can be improved by introducing image fusion technique at sensor levels. The results of the images after introducing the decision rule based image fusion technique are evaluated and analyzed with its entropy levels and root mean square error.

Mindlessly Polite: A Conceptual Replication of the Emotional Seesaw Effect on Compliance and Information Processing

PubMed Central

Kaczmarek, Magdalena C.; Steffens, Melanie C.

2017-01-01

Recent studies demonstrated that the sequential induction of contrasting negative and positive emotions can be used as a social influence technique. The original field experiments found that whenever a sudden change in the emotional dynamic occurs – from negative to positive or vice versa – an increase in compliant behavior and an impairment in cognitive functioning can be observed. The goal of the present experiments was a conceptual replication and extension of the results in a more controlled and counterbalanced fashion. To this aim a novel emotion induction technique was created using an outcome related expectancy violation to induce and change emotions. In a first experiment, the influence of contrasting emotions (vs. only one emotion) on compliance, message processing and information recall was assessed among 80 undergraduate students. We were able to show that a positive, then negative experience, and vice versa, led to losses in processing efficacy, not only leaving individuals momentarily vulnerable to social influence attempts, but also impairing information recall. We replicated this pattern of findings in a second experiment (N = 41). The implications of this innovative induction technique and its findings for theory and future research on the emerging field on contrasting emotions as social-influence techniques are discussed. PMID:28270788

Mindlessly Polite: A Conceptual Replication of the Emotional Seesaw Effect on Compliance and Information Processing.

PubMed

Kaczmarek, Magdalena C; Steffens, Melanie C

2017-01-01

Recent studies demonstrated that the sequential induction of contrasting negative and positive emotions can be used as a social influence technique. The original field experiments found that whenever a sudden change in the emotional dynamic occurs - from negative to positive or vice versa - an increase in compliant behavior and an impairment in cognitive functioning can be observed. The goal of the present experiments was a conceptual replication and extension of the results in a more controlled and counterbalanced fashion. To this aim a novel emotion induction technique was created using an outcome related expectancy violation to induce and change emotions. In a first experiment, the influence of contrasting emotions (vs. only one emotion) on compliance, message processing and information recall was assessed among 80 undergraduate students. We were able to show that a positive, then negative experience, and vice versa, led to losses in processing efficacy, not only leaving individuals momentarily vulnerable to social influence attempts, but also impairing information recall. We replicated this pattern of findings in a second experiment ( N = 41). The implications of this innovative induction technique and its findings for theory and future research on the emerging field on contrasting emotions as social-influence techniques are discussed.

77 FR 14225 - Prevention of Significant Deterioration and Title V Greenhouse Gas Tailoring Rule Step 3, GHG...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-03-08

... thresholds. \\2\\ 75 FR 31559. As we committed to do in the Tailoring Rule, we have been exploring a variety of... Corporate Average Fuel Economy Standards; Final Rule,'' 75 FR 25,324 (May 7, 2010) (the Light-duty Vehicle... announced a plan to explore streamlining techniques that could make the permitting programs more efficient...

Assessing Performance of Multipurpose Reservoir System Using Two-Point Linear Hedging Rule

NASA Astrophysics Data System (ADS)

Sasireka, K.; Neelakantan, T. R.

2017-07-01

Reservoir operation is the one of the important filed of water resource management. Innovative techniques in water resource management are focussed at optimizing the available water and in decreasing the environmental impact of water utilization on the natural environment. In the operation of multi reservoir system, efficient regulation of the release to satisfy the demand for various purpose like domestic, irrigation and hydropower can lead to increase the benefit from the reservoir as well as significantly reduces the damage due to floods. Hedging rule is one of the emerging techniques in reservoir operation, which reduce the severity of drought by accepting number of smaller shortages. The key objective of this paper is to maximize the minimum power production and improve the reliability of water supply for municipal and irrigation purpose by using hedging rule. In this paper, Type II two-point linear hedging rule is attempted to improve the operation of Bargi reservoir in the Narmada basin in India. The results obtained from simulation of hedging rule is compared with results from Standard Operating Policy, the result shows that the application of hedging rule significantly improved the reliability of water supply and reliability of irrigation release and firm power production.

31 CFR 205.13 - How do you determine when State or Federal interest liability accrues?

Code of Federal Regulations, 2010 CFR

2010-07-01

... SERVICE RULES AND PROCEDURES FOR EFFICIENT FEDERAL-STATE FUNDS TRANSFERS Rules Applicable to Federal... mutually agreed to funding techniques are applied, depending on the terms of the Treasury-State agreement...

Scalability of a Methodology for Generating Technical Trading Rules with GAPs Based on Risk-Return Adjustment and Incremental Training

NASA Astrophysics Data System (ADS)

de La Cal, E. A.; Fernández, E. M.; Quiroga, R.; Villar, J. R.; Sedano, J.

In previous works a methodology was defined, based on the design of a genetic algorithm GAP and an incremental training technique adapted to the learning of series of stock market values. The GAP technique consists in a fusion of GP and GA. The GAP algorithm implements the automatic search for crisp trading rules taking as objectives of the training both the optimization of the return obtained and the minimization of the assumed risk. Applying the proposed methodology, rules have been obtained for a period of eight years of the S&P500 index. The achieved adjustment of the relation return-risk has generated rules with returns very superior in the testing period to those obtained applying habitual methodologies and even clearly superior to Buy&Hold. This work probes that the proposed methodology is valid for different assets in a different market than previous work.

The association rules search of Indonesian university graduate’s data using FP-growth algorithm

NASA Astrophysics Data System (ADS)

Faza, S.; Rahmat, R. F.; Nababan, E. B.; Arisandi, D.; Effendi, S.

2018-02-01

The attribute varieties in university graduates data have caused frustrations to the institution in finding the combinations of attributes that often emerge and have high integration between attributes. Association rules mining is a data mining technique to determine the integration of the data or the way of a data set affects another set of data. By way of explanation, there are possibilities in finding the integration of data on a large scale. Frequent Pattern-Growth (FP-Growth) algorithm is one of the association rules mining technique to determine a frequent itemset in an FP-Tree data set. From the research on the search of university graduate’s association rules, it can be concluded that the most common attributes that have high integration between them are in the combination of State-owned High School outside Medan, regular university entrance exam, GPA of 3.00 to 3.49 and over 4-year-long study duration.

Biased Feedback in Spatial Recall Yields a Violation of Delta Rule Learning

PubMed Central

Lipinski, John; Spencer, John P.; Samuelson, Larissa K.

2010-01-01

This study investigates whether inductive processes influencing spatial memory performance generalize to supervised learning scenarios with differential feedback. After providing a location memory response in a spatial recall task, participants received visual feedback showing the target location. In critical blocks, feedback was systematically biased either 4° towards the vertical axis (Towards condition) or 4° further away from the vertical axis (Away condition). Results showed that the weaker teaching signal (i.e., a smaller difference between the remembered location and the feedback location) in the Away condition produced a stronger experience-dependent change over blocks than in the Towards condition. This violates delta rule learning. Subsequent simulations of the Dynamic Field Theory of spatial cognition provide a theoretically unified account of these results. PMID:20702881

Biased feedback in spatial recall yields a violation of delta rule learning.

PubMed

Lipinski, John; Spencer, John P; Samuelson, Larissa K

2010-08-01

This study investigates whether inductive processes influencing spatial memory performance generalize to supervised learning scenarios with differential feedback. After providing a location memory response in a spatial recall task, participants received visual feedback showing the target location. In critical blocks, feedback was systematically biased either 4 degrees toward the vertical axis (toward condition) or 4 degrees farther away from the vertical axis (away condition). Results showed that the weaker teaching signal (i.e., a smaller difference between the remembered location and the feedback location) produced a stronger experience-dependent change over blocks in the away condition than in the toward condition. This violates delta rule learning. Subsequent simulations of the dynamic field theory of spatial cognition provide a theoretically unified account of these results.

Further Improvement in Outcomes of Nasopharyngeal Carcinoma With Optimized Radiotherapy and Induction Plus Concomitant Chemotherapy: An Update of the Milan Experience

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

Palazzi, Mauro; Orlandi, Ester; Bossi, Paolo

2009-07-01

Purpose: To report the outcome of a consecutive series of patients with nonmetastatic nasopharyngeal carcinoma (NPC), focusing on the impact of treatment-related factors. Methods and Materials: Between 2000 and 2006, 87 patients with NPC were treated with either conventional (two- or three-dimensional) radiotherapy (RT) or with intensity-modulated RT (IMRT). Of these patients, 81 (93%) received either concomitant CHT (24%) or both induction and concomitant chemotherapy (CHT) (69%). Stage was III in 36% and IV in 39% of patients. Outcomes in this study population were compared with those in the previous series of 171 patients treated during 1990 to 1999. Results:more » With a median follow-up of 46 months, actuarial rates at 3 years were the following: local control, 96%; local-regional control, 93%; distant control (DC), 90%; disease-free survival (DFS), 82%; overall survival, 90%. In Stage III to IV patients, distant control at 3 years was 56% in patients treated with concomitant CHT only and 92% in patients treated with both induction and concomitant CHT (p = 0.014). At multivariate analysis, histology, N-stage, RT technique, and total RT dose had the strongest independent impact on DFS (p < 0.05). Induction CHT had a borderline effect on DC (p = 0.07). Most dosimetric statistics were improved in the group of patients treated with IMRT compared with conventional 3D technique. All outcome endpoints were substantially better in the study population compared with those in the previous series. Conclusions: Outcome of NPC has further improved in the study period compared with the previous decade, with a significant effect of RT technique optimization. The impact of induction CHT remains to be demonstrated in controlled trials.« less

An investigation of fluid flow during induction stroke of a water analog model of an IC engine using an innovative optical velocimetry concept: LIPA

NASA Technical Reports Server (NTRS)

Stier, Bernd; Falco, R. E.

1994-01-01

Optical measurements on an axisymmetrical quartz component engine research model were made to evaluate the flow field encountered during induction. The measurement technique is LIPA (Laser Induced Photochemical Anemometry), a non-intrusive velocimetry concept that provides an investigator of fluid flow with a tool to attain planar information about three-dimensional velocity and vorticity vectors in a single measurement step. The goal of this investigation is to further develop this measurement technique and apply it to study the induction stroke of a water analog model of a four-stroke internal combustion engine. The research conducted in the water analog model is a fundamental scientific inquiry into the flow fields that develop in the induction stroke of an engine at idling engine speeds. As this is the first investigation of its kind using LIPA technique, our goal has been to quantify, in a preliminary manner, the flow field features that develop during the intake stroke. In the process a more comprehensive understanding of the flow field features was developed, and tied to the quantification. The study evaluated the flow field of the intake stroke by estimating fields of velocity and vorticity. On the basis of these data, information about fluid dynamics during induction at engine speeds of 10, 20, and 30 RPM (corresponding to 170, 340, and 510 RPM respectively, when air is the flowing medium) for three different valve lifts was obtained. The overall development of the flow field, its energy content (kinetic, fluctuation) for the different settings of the engine parameters, vorticity information, and cyclic variations have been quantified. These have been discussed in terms of mixing performance.

Improved model reduction and tuning of fractional-order PI(λ)D(μ) controllers for analytical rule extraction with genetic programming.

PubMed

Das, Saptarshi; Pan, Indranil; Das, Shantanu; Gupta, Amitava

2012-03-01

Genetic algorithm (GA) has been used in this study for a new approach of suboptimal model reduction in the Nyquist plane and optimal time domain tuning of proportional-integral-derivative (PID) and fractional-order (FO) PI(λ)D(μ) controllers. Simulation studies show that the new Nyquist-based model reduction technique outperforms the conventional H(2)-norm-based reduced parameter modeling technique. With the tuned controller parameters and reduced-order model parameter dataset, optimum tuning rules have been developed with a test-bench of higher-order processes via genetic programming (GP). The GP performs a symbolic regression on the reduced process parameters to evolve a tuning rule which provides the best analytical expression to map the data. The tuning rules are developed for a minimum time domain integral performance index described by a weighted sum of error index and controller effort. From the reported Pareto optimal front of the GP-based optimal rule extraction technique, a trade-off can be made between the complexity of the tuning formulae and the control performance. The efficacy of the single-gene and multi-gene GP-based tuning rules has been compared with the original GA-based control performance for the PID and PI(λ)D(μ) controllers, handling four different classes of representative higher-order processes. These rules are very useful for process control engineers, as they inherit the power of the GA-based tuning methodology, but can be easily calculated without the requirement for running the computationally intensive GA every time. Three-dimensional plots of the required variation in PID/fractional-order PID (FOPID) controller parameters with reduced process parameters have been shown as a guideline for the operator. Parametric robustness of the reported GP-based tuning rules has also been shown with credible simulation examples. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

Bayesian learning and the psychology of rule induction

PubMed Central

Endress, Ansgar D.

2014-01-01

In recent years, Bayesian learning models have been applied to an increasing variety of domains. While such models have been criticized on theoretical grounds, the underlying assumptions and predictions are rarely made concrete and tested experimentally. Here, I use Frank and Tenenbaum's (2011) Bayesian model of rule-learning as a case study to spell out the underlying assumptions, and to confront them with the empirical results Frank and Tenenbaum (2011) propose to simulate, as well as with novel experiments. While rule-learning is arguably well suited to rational Bayesian approaches, I show that their models are neither psychologically plausible nor ideal observer models. Further, I show that their central assumption is unfounded: humans do not always preferentially learn more specific rules, but, at least in some situations, those rules that happen to be more salient. Even when granting the unsupported assumptions, I show that all of the experiments modeled by Frank and Tenenbaum (2011) either contradict their models, or have a large number of more plausible interpretations. I provide an alternative account of the experimental data based on simple psychological mechanisms, and show that this account both describes the data better, and is easier to falsify. I conclude that, despite the recent surge in Bayesian models of cognitive phenomena, psychological phenomena are best understood by developing and testing psychological theories rather than models that can be fit to virtually any data. PMID:23454791

Phonological Concept Learning.

PubMed

Moreton, Elliott; Pater, Joe; Pertsova, Katya

2017-01-01

Linguistic and non-linguistic pattern learning have been studied separately, but we argue for a comparative approach. Analogous inductive problems arise in phonological and visual pattern learning. Evidence from three experiments shows that human learners can solve them in analogous ways, and that human performance in both cases can be captured by the same models. We test GMECCS (Gradual Maximum Entropy with a Conjunctive Constraint Schema), an implementation of the Configural Cue Model (Gluck & Bower, ) in a Maximum Entropy phonotactic-learning framework (Goldwater & Johnson, ; Hayes & Wilson, ) with a single free parameter, against the alternative hypothesis that learners seek featurally simple algebraic rules ("rule-seeking"). We study the full typology of patterns introduced by Shepard, Hovland, and Jenkins () ("SHJ"), instantiated as both phonotactic patterns and visual analogs, using unsupervised training. Unlike SHJ, Experiments 1 and 2 found that both phonotactic and visual patterns that depended on fewer features could be more difficult than those that depended on more features, as predicted by GMECCS but not by rule-seeking. GMECCS also correctly predicted performance differences between stimulus subclasses within each pattern. A third experiment tried supervised training (which can facilitate rule-seeking in visual learning) to elicit simple rule-seeking phonotactic learning, but cue-based behavior persisted. We conclude that similar cue-based cognitive processes are available for phonological and visual concept learning, and hence that studying either kind of learning can lead to significant insights about the other. Copyright © 2015 Cognitive Science Society, Inc.

Repetitive Reaction and Restitution (R3) induction of drought hardiness in conifer container seedlings

Treesearch

Jol Hodgson

2011-01-01

Planting failures are often attributed to unexpectedly harsh conditions after planting. Characterization of soil water at the planting site, along with associated influences of site preparation and soil texture, is recommended. Additionally, tree planting technique and seedling biology should be targeted to site conditions. A nursery regime for induction of drought...

Induction of soybean resistance to the Mexican bean beetle (Coleoptera: Coccinellidae)

Treesearch

A.L. Iverson; R.B. Hammond; L.R. Iverson

2001-01-01

We tested chemical and insect feeding-induced insect resistance on soybean plants.The chemical induction effects of jasmonic acid (JA) and salicylic acid (SA) were investigated. We also evaluated the effects of plants stressed with previous insect herbivory. A larval antibiosis screening technique (LAST) and a preference test were performed in petri dishes using...

Ovulation induction in women with polycystic ovary syndrome.

PubMed

Perales-Puchalt, Alfredo; Legro, Richard S

2013-08-01

Polycystic ovary syndrome (PCOS) is the most common cause of anovulatory infertility. There are multiple ways to induce ovulation in PCOS patients, which will eventually provide a successful live birth. Each of these treatments varies in aggressiveness and effectiveness. Ranging from lifestyle modifications, through insulin-sensitizing agents, selective estrogen receptor modulators, aromatase inhibitors, gonadotropins, to laparoscopic ovarian drilling and assisted reproductive techniques, each method achieves ovulation induction through different mechanisms of action. This review provides a description and specific characteristics of the different methods used for ovulation induction which can help to design a personalized approach to each PCOS patient, and a general stepwise approach to ovulation induction in these patients. Copyright © 2013 Elsevier Inc. All rights reserved.

Negative coupled inductors for polyphase choppers

NASA Technical Reports Server (NTRS)

Jamieson, Robert S. (Inventor)

1984-01-01

A technique for negatively coupling the outputs of polyphase choppers is disclosed, wherein the output inductance of each phase is divided into two windings, and each winding is negatively coupled to a corresponding winding of a neighboring phase. In a preferred embodiment for a three-phase chopper circuit, the output inductance of phase A is divided into windings 100 and 102, the output inductance of phase B is divided into windings 110 and 112, and the output inductance of phase C is divided into windings 120 and 122. Pairs of windings 100 and 110, 112 and 120, and 102 and 122 are respectively disposed in transformers arranged for negatively coupling the windings of each pair.

Progress in mental workload measurement

NASA Technical Reports Server (NTRS)

Moray, Neville; Turksen, Burhan; Aidie, Paul; Drascic, David; Eisen, Paul

1986-01-01

Two new techniques are described, one using subjective, the other physiological data for the measurement of workload in complex tasks. The subjective approach uses fuzzy measurement to analyze and predict the difficulty of combinations of skill based and rule based behavior from the difficulty of skill based behavior and rule based behavior measured separately. The physiological technique offers an on-line real-time filter for measuring the Mulder signal at 0.1 Hz in the heart rate variability spectrum.

Training Fires on Indian Reservations in Idaho, Oregon, and Washington

EPA Pesticide Factsheets

The Federal Air Rules for Reservations (FARR) Open Burning Rule allows Fire Protection Services to request permission from EPA to conduct an outdoor burn by qualified personnel to train firefighters on fire suppression and fire fighting techniques.

Fuzzy CMAC With incremental Bayesian Ying-Yang learning and dynamic rule construction.

PubMed

Nguyen, M N

2010-04-01

Inspired by the philosophy of ancient Chinese Taoism, Xu's Bayesian ying-yang (BYY) learning technique performs clustering by harmonizing the training data (yang) with the solution (ying). In our previous work, the BYY learning technique was applied to a fuzzy cerebellar model articulation controller (FCMAC) to find the optimal fuzzy sets; however, this is not suitable for time series data analysis. To address this problem, we propose an incremental BYY learning technique in this paper, with the idea of sliding window and rule structure dynamic algorithms. Three contributions are made as a result of this research. First, an online expectation-maximization algorithm incorporated with the sliding window is proposed for the fuzzification phase. Second, the memory requirement is greatly reduced since the entire data set no longer needs to be obtained during the prediction process. Third, the rule structure dynamic algorithm with dynamically initializing, recruiting, and pruning rules relieves the "curse of dimensionality" problem that is inherent in the FCMAC. Because of these features, the experimental results of the benchmark data sets of currency exchange rates and Mackey-Glass show that the proposed model is more suitable for real-time streaming data analysis.

Recent Developments in the Speciation and Determination of Mercury Using Various Analytical Techniques

PubMed Central

Suvarapu, Lakshmi Narayana; Baek, Sung-Ok

2015-01-01

This paper reviews the speciation and determination of mercury by various analytical techniques such as atomic absorption spectrometry, voltammetry, inductively coupled plasma techniques, spectrophotometry, spectrofluorometry, high performance liquid chromatography, and gas chromatography. Approximately 126 research papers on the speciation and determination of mercury by various analytical techniques published in international journals since 2013 are reviewed. PMID:26236539

Prediction of cancer class with majority voting genetic programming classifier using gene expression data.

PubMed

Paul, Topon Kumar; Iba, Hitoshi

2009-01-01

In order to get a better understanding of different types of cancers and to find the possible biomarkers for diseases, recently, many researchers are analyzing the gene expression data using various machine learning techniques. However, due to a very small number of training samples compared to the huge number of genes and class imbalance, most of these methods suffer from overfitting. In this paper, we present a majority voting genetic programming classifier (MVGPC) for the classification of microarray data. Instead of a single rule or a single set of rules, we evolve multiple rules with genetic programming (GP) and then apply those rules to test samples to determine their labels with majority voting technique. By performing experiments on four different public cancer data sets, including multiclass data sets, we have found that the test accuracies of MVGPC are better than those of other methods, including AdaBoost with GP. Moreover, some of the more frequently occurring genes in the classification rules are known to be associated with the types of cancers being studied in this paper.

Iterative categorization (IC): a systematic technique for analysing qualitative data.

PubMed

Neale, Joanne

2016-06-01

The processes of analysing qualitative data, particularly the stage between coding and publication, are often vague and/or poorly explained within addiction science and research more broadly. A simple but rigorous and transparent technique for analysing qualitative textual data, developed within the field of addiction, is described. The technique, iterative categorization (IC), is suitable for use with inductive and deductive codes and can support a range of common analytical approaches, e.g. thematic analysis, Framework, constant comparison, analytical induction, content analysis, conversational analysis, discourse analysis, interpretative phenomenological analysis and narrative analysis. Once the data have been coded, the only software required is a standard word processing package. Worked examples are provided. © 2016 The Authors. Addiction published by John Wiley & Sons Ltd on behalf of Society for the Study of Addiction.

Rule-Based Runtime Verification

NASA Technical Reports Server (NTRS)

Barringer, Howard; Goldberg, Allen; Havelund, Klaus; Sen, Koushik

2003-01-01

We present a rule-based framework for defining and implementing finite trace monitoring logics, including future and past time temporal logic, extended regular expressions, real-time logics, interval logics, forms of quantified temporal logics, and so on. Our logic, EAGLE, is implemented as a Java library and involves novel techniques for rule definition, manipulation and execution. Monitoring is done on a state-by-state basis, without storing the execution trace.

A Hybrid Genetic Programming Algorithm for Automated Design of Dispatching Rules.

PubMed

Nguyen, Su; Mei, Yi; Xue, Bing; Zhang, Mengjie

2018-06-04

Designing effective dispatching rules for production systems is a difficult and timeconsuming task if it is done manually. In the last decade, the growth of computing power, advanced machine learning, and optimisation techniques has made the automated design of dispatching rules possible and automatically discovered rules are competitive or outperform existing rules developed by researchers. Genetic programming is one of the most popular approaches to discovering dispatching rules in the literature, especially for complex production systems. However, the large heuristic search space may restrict genetic programming from finding near optimal dispatching rules. This paper develops a new hybrid genetic programming algorithm for dynamic job shop scheduling based on a new representation, a new local search heuristic, and efficient fitness evaluators. Experiments show that the new method is effective regarding the quality of evolved rules. Moreover, evolved rules are also significantly smaller and contain more relevant attributes.

Kidney versus Islet Allograft Survival after Induction of Mixed Chimerism with Combined Donor Bone Marrow Transplantation

PubMed Central

Oura, Tetsu; Ko, Dicken S.C.; Boskovic, Svjetlan; O'Neil, John J.; Chipashvili, Vaja; Koulmanda, Maria; Hotta, Kiyohiko; Kawai, Kento; Nadazdin, Ognjenka; Smith, R. Neal; Cosimi, A. B.; Kawai, Tatsuo

2016-01-01

Background We have previously reported successful induction of transient mixed chimerism and long-term acceptance of renal allografts in MHC-mismatched nonhuman primates. In this study, we attempted to extend this tolerance induction approach to islet allografts. Methods A total of eight recipients underwent MHC mismatched combined islet and bone marrow (BM) transplantation after induction of diabetes by streptozotocin. Three recipients were treated after a nonmyeloablative conditioning regimen that includes low dose total body and thymic irradiation, horse ATG (Atgam), six doses of anti-CD154 monoclonal antibody (mAb) and a one month course of cyclosporine (CyA) (Islet-A). In Islet-B, anti-CD8 mAb was administered in place of CyA. In Islet-C, two recipients were treated with Islet-B but without Atgam. The results were compared with previously reported results of eight cynomolgus monkeys that received combined kidney and bone marrow transplantation (Kidney-A) following the same conditioning regimen used in Islet-A. Results The majority of Kidney/BM recipients achieved long-term renal allograft survival after induction of transient chimerism. However, prolonged islet survival was not achieved in similarly conditioned Islet/BM recipients (Islet-A), despite induction of comparable levels of chimerism. In order to rule out islet allograft loss due to calcineurin inhibitor (CNI) toxicity, three recipients were treated with anti-CD8 mAb in place of CNI. Although these recipients developed significantly superior mixed chimerism and more prolonged islet allograft survival (61, 103, and 113 days), islet function was lost soon after the disappearance of chimerism. In Islet-C recipients, neither prolonged chimerism nor islet survival was observed (30 and 40 days). Conclusion Significant improvement of mixed chimerism induction and islet allograft survival were achieved with a CNI-free regimen that includes anti-CD8 mAb. However, unlike the kidney allograft, islet allograft tolerance was not induced with transient chimerism. Induction of more durable mixed chimerism may be necessary for induction of islet allograft tolerance. PMID:26337731

Comparison of Effectiveness in Differentiating Benign from Malignant Ovarian Masses between IOTA Simple Rules and Subjective Sonographic Assessment.

PubMed

Tongsong, Theera; Tinnangwattana, Dangcheewan; Vichak-Ururote, Linlada; Tontivuthikul, Paponrad; Charoenratana, Cholaros; Lerthiranwong, Thitikarn

2016-01-01

To compare diagnostic performance in differentiating benign from malignant ovarian masses between IOTA (the International Ovarian Tumor Analysis) simple rules and subjective sonographic assessment. Women scheduled for elective surgery because of ovarian masses were recruited into the study and underwent ultrasound examination within 24 hours of surgery to apply the IOTA simple rules by general gynecologists and to record video clips for subjective assessment by an experienced sonographer. The diagnostic performance of the IOTA rules and subjective assessment for differentiation between benign and malignant masses was compared. The gold standard diagnosis was pathological or operative findings. A total of 150 ovarian masses were covered, comprising 105 (70%) benign and 45 (30%) malignant. Of them, the IOTA simple rules could be applied in 119 (79.3%) and were inconclusive in 31 (20.7%) whereas subjective assessment could be applied in all cases (100%). The sensitivity and the specificity of the IOTA simple rules and subjective assessment were not significantly different, 82.9% vs 86.7% and 94.0% vs 94.3% respectively. The agreement of the two methods in prediction was high with a Kappa index of 0.835. Both techniques had a high diagnostic performance in differentiation between benign and malignant ovarian masses but the IOTA rules had a relatively high rate of inconclusive results. The IOTA rules can be used as an effective screening technique by general gynecologists but when the results are inconclusive they should consult experienced sonographers.

Efficiency measurement of health care organizations: What models are used?

PubMed Central

Jaafaripooyan, Ebrahim; Emamgholipour, Sara; Raei, Behzad

2017-01-01

Background: Literature abounds with various techniques for efficiency measurement of health care organizations (HCOs), which should be used cautiously and appropriately. The present study aimed at discovering the rules regulating the interplay among the number of inputs, outputs, and decision- making units (DMUs) and identifying all methods used for the measurement of Iranian HCOs and critically appraising all DEA studies on Iranian HCOs in their application of such rules. Methods: The present study employed a systematic search of all studies related to efficiency measurement of Iranian HCOs. A search was conducted in different databases such as PubMed and Scopus between 2001 and 2015 to identify the studies related to the measurement in health care. The retrieved studies passed through a multi-stage (title, abstract, body) filtering process. Data extraction table for each study was completed and included method, number of inputs and outputs, DMUs, and their efficiency score. Results: Various methods were found for efficiency measurement. Overall, 122 studies were retrieved, of which 73 had exclusively employed DEA technique for measuring the efficiency of HCOs in Iran, and 23 with hybrid models (including DEA). Only 6 studies had explicitly used the rules of thumb. Conclusion: The number of inputs, outputs, and DMUs should be cautiously selected in DEA like techniques, as their proportionality can directly affect the discriminatory power of the technique. The given literature seemed to be, to a large extent, unsuccessful in attending to such proportionality. This study collected a list of key rules (of thumb) on the interplay of inputs, outputs, and DMUs, which could be considered by most researchers keen to apply DEA technique.

New Teaching Techniques to Improve Critical Thinking. The Diaprove Methodology

ERIC Educational Resources Information Center

Saiz, Carlos; Rivas, Silvia F.

2016-01-01

The objective of this research is to ascertain whether new instructional techniques can improve critical thinking. To achieve this goal, two different instruction techniques (ARDESOS--group 1--and DIAPROVE--group 2--) were studied and a pre-post assessment of critical thinking in various dimensions such as argumentation, inductive reasoning,…

When global structure "Explains Away" local grammar: a Bayesian account of rule-induction in tone sequences.

PubMed

Dawson, Colin; Gerken, Louann

2011-09-01

While many constraints on learning must be relatively experience-independent, past experience provides a rich source of guidance for subsequent learning. Discovering structure in some domain can inform a learner's future hypotheses about that domain. If a general property accounts for particular sub-patterns, a rational learner should not stipulate separate explanations for each detail without additional evidence, as the general structure has "explained away" the original evidence. In a grammar-learning experiment using tone sequences, manipulating learners' prior exposure to a tone environment affects their sensitivity to the grammar-defining feature, in this case consecutive repeated tones. Grammar-learning performance is worse if context melodies are "smooth" -- when small intervals occur more than large ones -- as Smoothness is a general property accounting for a high rate of repetition. We present an idealized Bayesian model as a "best case" benchmark for learning repetition grammars. When context melodies are Smooth, the model places greater weight on the small-interval constraint, and does not learn the repetition rule as well as when context melodies are not Smooth, paralleling the human learners. These findings support an account of abstract grammar-induction in which learners rationally assess the statistical evidence for underlying structure based on a generative model of the environment. Copyright © 2010 Elsevier B.V. All rights reserved.

Measuring uncertainty by extracting fuzzy rules using rough sets and extracting fuzzy rules under uncertainty and measuring definability using rough sets

NASA Technical Reports Server (NTRS)

Worm, Jeffrey A.; Culas, Donald E.

1991-01-01

Computers are not designed to handle terms where uncertainty is present. To deal with uncertainty, techniques other than classical logic must be developed. This paper examines the concepts of statistical analysis, the Dempster-Shafer theory, rough set theory, and fuzzy set theory to solve this problem. The fundamentals of these theories are combined to provide the possible optimal solution. By incorporating principles from these theories, a decision-making process may be simulated by extracting two sets of fuzzy rules: certain rules and possible rules. From these rules a corresponding measure of how much we believe these rules is constructed. From this, the idea of how much a fuzzy diagnosis is definable in terms of its fuzzy attributes is studied.

Extending radiative transfer models by use of Bayes rule. [in atmospheric science

NASA Technical Reports Server (NTRS)

Whitney, C.

1977-01-01

This paper presents a procedure that extends some existing radiative transfer modeling techniques to problems in atmospheric science where curvature and layering of the medium and dynamic range and angular resolution of the signal are important. Example problems include twilight and limb scan simulations. Techniques that are extended include successive orders of scattering, matrix operator, doubling, Gauss-Seidel iteration, discrete ordinates and spherical harmonics. The procedure for extending them is based on Bayes' rule from probability theory.

Blackout cloth for dormancy induction

Treesearch

Tom Jopson

2007-01-01

The use of blackout cloth to create long night photoperiods for the induction of dormancy in certain conifer species has been an established practice for a long time. Its use was suggested by Tinus and McDonald (1979) as an effective technique, and the practice has been commonly used in Canadian forest nurseries for a number of years. Cal-Forest Nursery installed its...

Magnetic induction system for two-stage gun projectile velocity measurements

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

Moody, R L; Konrad, C H

1984-05-01

A magnetic induction technique for measuring projectile velocities has been implemented on Sandia's two-stage light gas gun. The system has been designed to allow for projectile velocity measurements to an accuracy of approx. 0.2 percent. The velocity system has been successfully tested in a velocity range of 3.5 km/s to 6.5 km/s.

Speed control of an induction motor by 6-switched 3-level inverter

NASA Astrophysics Data System (ADS)

Saygin, Ali; Kerem, Alper

2017-12-01

This paper presents speed control analysis of an induction motor by a 6-switched 3-level inverter. In the analysis of topology, the study used the field oriented control technique which is widely used in the literature, easy and stable for operating systems. The field weaking technique was used for speeds exceeding nominal speed to reduce magnetic saturation and thermal losses. At the end of the process, it was observed to increase motor torque and inverter efficiency. Instead of using 12 switches in conventional 3-level inverters, 6 switches are used in this topology. Reduced number of switches is the greatest contribution of this study.

A concise guide for the determination of less-studied technology-critical elements (Nb, Ta, Ga, In, Ge, Te) by inductively coupled plasma mass spectrometry in environmental samples

NASA Astrophysics Data System (ADS)

Filella, Montserrat; Rodushkin, Ilia

2018-03-01

There is an increasing demand for analytical techniques able to measure so-called 'technology-critical elements', a set of chemical elements increasingly used in technological applications, in environmental matrices. Nowadays, inductively coupled plasma-mass spectrometry (ICP-MS) has become the technique of choice for measuring trace element concentrations. However, its application is often less straightforward than often assumed. The hints and drawbacks of ICP-MS application to the measurement of a set of less-studied technology-critical elements (Nb, Ta, Ga, In, Ge and Te) is discussed here and concise guidelines given.

Full-order observer for direct torque control of induction motor based on constant V/F control technique.

PubMed

Pimkumwong, Narongrit; Wang, Ming-Shyan

2018-02-01

This paper presents another control method for the three-phase induction motor that is direct torque control based on constant voltage per frequency control technique. This method uses the magnitude of stator flux and torque errors to generate the stator voltage and phase angle references for controlling the induction motor by using constant voltage per frequency control method. Instead of hysteresis comparators and optimum switching table, the PI controllers and space vector modulation technique are used to reduce torque and stator-flux ripples and achieve constant switching frequency. Moreover, the coordinate transformations are not required. To implement this control method, a full-order observer is used to estimate stator flux and overcome the problems from drift and saturation in using pure integrator. The feedback gains are designed by simple manner to improve the convergence of stator flux estimation, especially in low speed range. Furthermore, the necessary conditions to maintain the stability for feedback gain design are introduced. The simulation and experimental results show accurate and stable operation of the introduced estimator and good dynamic response of the proposed control method. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Techniques of Punishment and the Development of Self-Criticism

ERIC Educational Resources Information Center

Grusec, Joan E.; Ezrin, Sharyn A.

1972-01-01

The results of this study indicate that induction combined with withdrawal of love is no more effective as a punishment technique for the development of at least one aspect of conscience--self-criticism--than withdrawal of material reward. (Authors)

Fault ride-through enhancement using an enhanced field oriented control technique for converters of grid connected DFIG and STATCOM for different types of faults.

PubMed

Ananth, D V N; Nagesh Kumar, G V

2016-05-01

With increase in electric power demand, transmission lines were forced to operate close to its full load and due to the drastic change in weather conditions, thermal limit is increasing and the system is operating with less security margin. To meet the increased power demand, a doubly fed induction generator (DFIG) based wind generation system is a better alternative. For improving power flow capability and increasing security STATCOM can be adopted. As per modern grid rules, DFIG needs to operate without losing synchronism called low voltage ride through (LVRT) during severe grid faults. Hence, an enhanced field oriented control technique (EFOC) was adopted in Rotor Side Converter of DFIG converter to improve power flow transfer and to improve dynamic and transient stability. A STATCOM is coordinated to the system for obtaining much better stability and enhanced operation during grid fault. For the EFOC technique, rotor flux reference changes its value from synchronous speed to zero during fault for injecting current at the rotor slip frequency. In this process DC-Offset component of flux is controlled, decomposition during symmetric and asymmetric faults. The offset decomposition of flux will be oscillatory in a conventional field oriented control, whereas in EFOC it was aimed to damp quickly. This paper mitigates voltage and limits surge currents to enhance the operation of DFIG during symmetrical and asymmetrical faults. The system performance with different types of faults like single line to ground, double line to ground and triple line to ground was applied and compared without and with a STATCOM occurring at the point of common coupling with fault resistance of a very small value at 0.001Ω. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Civil liability: characterization of the demand for lawsuits against dentists.

PubMed

Zanin, Alice Aquino; Herrera, Lara Maria; Melani, Rodolfo Francisco Haltenhoff

2016-08-18

In light of the fact that dentists may be held civilly liable for their practice, it is important to understand the current situation of lawsuits filed against these professionals by studying current legal decisions and the literature. The objective of this study was to analyze the case law of the Court of Justice of São Paulo, Brazil, relative to the profile of patients and professionals, the most commonly involved specialties, the amounts litigated and the court decisions pertaining to civil liability lawsuits against dentists. In an inductive approach, a single researcher screened and collected civil liability rulings by accessing the Court's website, and following a statistical-descriptive procedure and an indirect observation technique. The most frequently involved specialty was prosthodontics. However, oral and maxillofacial surgery was related to a higher incidence of damages awarded to settle claims and to higher damage amounts. The dentist was found guilty in 44.32% of the cases researched. Pecuniary damages ranged between R$ 485.50 and R$ 12,530.00, and non-pecuniary damages ranged between R$ 2,500.00 and R$ 70,000.00. Most lawsuits were filed by women against male dentists. An increase in the relative number of lawsuits against companies versus individuals was observed.

Biometrics: Multi-Service Tactics, Techniques, and Procedures for Tactical Employment of Biometrics in Support of Operations

DTIC Science & Technology

2016-05-01

Biometrics in Support of Operations Biometrics -at-Sea: Business Rules for South Florida United States...Intelligence Activities Biometrics -Enabled Intelligence USCG Biometrics -at-Sea: Business Rules for...Defense Biometrics United States Intelligence Activities Active Army,

Rapid induction bonding of composites, plastics, and metals

NASA Technical Reports Server (NTRS)

Buckley, John D.; Fox, Robert L.

1991-01-01

The Toroid Bonding Gun is and induction heating device. It is a self contained, portable, low powered induction welding system developed for bonding or joining plastic, ceramic, or metallic parts. Structures can be bonded in a factory or in a the field. This type of equipment allows for applying heat directly to the bond lines and/or to the adhesives without heating the entire structure, supports, and fixtures of a bonding assembly. The induction heating gun originally developed for use in the fabrication of space Gangs of bonders are now used to rapidly join composite sheet and structural components. Other NASA-developed applications of this bonding technique include the joining of thermoplastic composites, thermosetting composites, metals, and combinations of these materials.

Expert networks in CLIPS

NASA Technical Reports Server (NTRS)

Hruska, S. I.; Dalke, A.; Ferguson, J. J.; Lacher, R. C.

1991-01-01

Rule-based expert systems may be structurally and functionally mapped onto a special class of neural networks called expert networks. This mapping lends itself to adaptation of connectionist learning strategies for the expert networks. A parsing algorithm to translate C Language Integrated Production System (CLIPS) rules into a network of interconnected assertion and operation nodes has been developed. The translation of CLIPS rules to an expert network and back again is illustrated. Measures of uncertainty similar to those rules in MYCIN-like systems are introduced into the CLIPS system and techniques for combining and hiring nodes in the network based on rule-firing with these certainty factors in the expert system are presented. Several learning algorithms are under study which automate the process of attaching certainty factors to rules.

Intelligent System Development Using a Rough Sets Methodology

NASA Technical Reports Server (NTRS)

Anderson, Gray T.; Shelton, Robert O.

1997-01-01

The purpose of this research was to examine the potential of the rough sets technique for developing intelligent models of complex systems from limited information. Rough sets a simple but promising technology to extract easily understood rules from data. The rough set methodology has been shown to perform well when used with a large set of exemplars, but its performance with sparse data sets is less certain. The difficulty is that rules will be developed based on just a few examples, each of which might have a large amount of noise associated with them. The question then becomes, what is the probability of a useful rule being developed from such limited information? One nice feature of rough sets is that in unusual situations, the technique can give an answer of 'I don't know'. That is, if a case arises that is different from the cases the rough set rules were developed on, the methodology can recognize this and alert human operators of it. It can also be trained to do this when the desired action is unknown because conflicting examples apply to the same set of inputs. This summer's project was to look at combining rough set theory with statistical theory to develop confidence limits in rules developed by rough sets. Often it is important not to make a certain type of mistake (e.g., false positives or false negatives), so the rules must be biased toward preventing a catastrophic error, rather than giving the most likely course of action. A method to determine the best course of action in the light of such constraints was examined. The resulting technique was tested with files containing electrical power line 'signatures' from the space shuttle and with decompression sickness data.

Implementing a Commercial Rule Base as a Medication Order Safety Net

PubMed Central

Reichley, Richard M.; Seaton, Terry L.; Resetar, Ervina; Micek, Scott T.; Scott, Karen L.; Fraser, Victoria J.; Dunagan, W. Claiborne; Bailey, Thomas C.

2005-01-01

A commercial rule base (Cerner Multum) was used to identify medication orders exceeding recommended dosage limits at five hospitals within BJC HealthCare, an integrated health care system. During initial testing, clinical pharmacists determined that there was an excessive number of nuisance and clinically insignificant alerts, with an overall alert rate of 9.2%. A method for customizing the commercial rule base was implemented to increase rule specificity for problematic rules. The system was subsequently deployed at two facilities and achieved alert rates of less than 1%. Pharmacists screened these alerts and contacted ordering physicians in 21% of cases. Physicians made therapeutic changes in response to 38% of alerts presented to them. By applying simple techniques to customize rules, commercial rule bases can be used to rapidly deploy a safety net to screen drug orders for excessive dosages, while preserving the rule architecture for later implementations of more finely tuned clinical decision support. PMID:15802481

Statistical Methods in Ai: Rare Event Learning Using Associative Rules and Higher-Order Statistics

NASA Astrophysics Data System (ADS)

Iyer, V.; Shetty, S.; Iyengar, S. S.

2015-07-01

Rare event learning has not been actively researched since lately due to the unavailability of algorithms which deal with big samples. The research addresses spatio-temporal streams from multi-resolution sensors to find actionable items from a perspective of real-time algorithms. This computing framework is independent of the number of input samples, application domain, labelled or label-less streams. A sampling overlap algorithm such as Brooks-Iyengar is used for dealing with noisy sensor streams. We extend the existing noise pre-processing algorithms using Data-Cleaning trees. Pre-processing using ensemble of trees using bagging and multi-target regression showed robustness to random noise and missing data. As spatio-temporal streams are highly statistically correlated, we prove that a temporal window based sampling from sensor data streams converges after n samples using Hoeffding bounds. Which can be used for fast prediction of new samples in real-time. The Data-cleaning tree model uses a nonparametric node splitting technique, which can be learned in an iterative way which scales linearly in memory consumption for any size input stream. The improved task based ensemble extraction is compared with non-linear computation models using various SVM kernels for speed and accuracy. We show using empirical datasets the explicit rule learning computation is linear in time and is only dependent on the number of leafs present in the tree ensemble. The use of unpruned trees (t) in our proposed ensemble always yields minimum number (m) of leafs keeping pre-processing computation to n × t log m compared to N2 for Gram Matrix. We also show that the task based feature induction yields higher Qualify of Data (QoD) in the feature space compared to kernel methods using Gram Matrix.

Inductive dielectric analyzer

NASA Astrophysics Data System (ADS)

Agranovich, Daniel; Polygalov, Eugene; Popov, Ivan; Ben Ishai, Paul; Feldman, Yuri

2017-03-01

One of the approaches to bypass the problem of electrode polarization in dielectric measurements is the free electrode method. The advantage of this technique is that, the probing electric field in the material is not supplied by contact electrodes, but rather by electromagnetic induction. We have designed an inductive dielectric analyzer based on a sensor comprising two concentric toroidal coils. In this work, we present an analytic derivation of the relationship between the impedance measured by the sensor and the complex dielectric permittivity of the sample. The obtained relationship was successfully employed to measure the dielectric permittivity and conductivity of various alcohols and aqueous salt solutions.

Study of Variable Frequency Induction Heating in Steel Making Process

NASA Astrophysics Data System (ADS)

Fukutani, Kazuhiko; Umetsu, Kenji; Itou, Takeo; Isobe, Takanori; Kitahara, Tadayuki; Shimada, Ryuichi

Induction heating technologies have been the standard technologies employed in steel making processes because they are clean, they have a high energy density, they are highly the controllable, etc. However, there is a problem in using them; in general, frequencies of the electric circuits have to be kept fixed to improve their power factors, and this constraint makes the processes inflexible. In order to overcome this problem, we have developed a new heating technique-variable frequency power supply with magnetic energy recovery switching. This technique helps us in improving the quality of steel products as well as the productivity. We have also performed numerical calculations and experiments to evaluate its effect on temperature distributions on heated steel plates. The obtained results indicate that the application of the technique in steel making processes would be advantageous.

75 FR 39710 - Proposed Collection; Comment Request

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-12

... information on respondents, including through the use of automated collection techniques or other forms of... Commission, Office of Investor Education and Advocacy, Washington, DC 20549-0213. Extension: Rule 303, SEC... (``Commission'') is soliciting comments on the existing collection of information provided for in Rule 303 (17...

Confidence of compliance: a Bayesian approach for percentile standards.

PubMed

McBride, G B; Ellis, J C

2001-04-01

Rules for assessing compliance with percentile standards commonly limit the number of exceedances permitted in a batch of samples taken over a defined assessment period. Such rules are commonly developed using classical statistical methods. Results from alternative Bayesian methods are presented (using beta-distributed prior information and a binomial likelihood), resulting in "confidence of compliance" graphs. These allow simple reading of the consumer's risk and the supplier's risks for any proposed rule. The influence of the prior assumptions required by the Bayesian technique on the confidence results is demonstrated, using two reference priors (uniform and Jeffreys') and also using optimistic and pessimistic user-defined priors. All four give less pessimistic results than does the classical technique, because interpreting classical results as "confidence of compliance" actually invokes a Bayesian approach with an extreme prior distribution. Jeffreys' prior is shown to be the most generally appropriate choice of prior distribution. Cost savings can be expected using rules based on this approach.

Analysis of four dental alloys following torch/centrifugal and induction/ vacuum-pressure casting procedures.

PubMed

Thompson, Geoffrey A; Luo, Qing; Hefti, Arthur

2013-12-01

Previous studies have shown casting methodology to influence the as-cast properties of dental casting alloys. It is important to consider clinically important mechanical properties so that the influence of casting can be clarified. The purpose of this study was to evaluate how torch/centrifugal and inductively cast and vacuum-pressure casting machines may affect the castability, microhardness, chemical composition, and microstructure of 2 high noble, 1 noble, and 1 base metal dental casting alloys. Two commonly used methods for casting were selected for comparison: torch/centrifugal casting and inductively heated/ vacuum-pressure casting. One hundred and twenty castability patterns were fabricated and divided into 8 groups. Four groups were torch/centrifugally cast in Olympia (O), Jelenko O (JO), Genesis II (G), and Liberty (L) alloys. Similarly, 4 groups were cast in O, JO, G, and L by an inductively induction/vacuum-pressure casting machine. Each specimen was evaluated for casting completeness to determine a castability value, while porosity was determined by standard x-ray techniques. Each group was metallographically prepared for further evaluation that included chemical composition, Vickers microhardness, and grain analysis of microstructure. Two-way ANOVA was used to determine significant differences among the main effects. Statistically significant effects were examined further with the Tukey HSD procedure for multiple comparisons. Data obtained from the castability experiments were non-normal and the variances were unequal. They were analyzed statistically with the Kruskal-Wallis rank sum test. Significant results were further investigated statistically with the Steel-Dwass method for multiple comparisons (α=.05). The alloy type had a significant effect on surface microhardness (P<.001). In contrast, the technique used for casting did not affect the microhardness of the test specimen (P=.465). Similarly, the interaction between the alloy and casting technique was not significant (P=.119). A high level of castability (98.5% on average) was achieved overall. The frequency of casting failures as a function of alloy type and casting method was determined. Failure was defined as a castability index score of <100%. Three of 28 possible comparisons between alloy and casting combinations were statistically significant. The results suggested that casting technique affects the castability index of alloys. Radiographic analysis detected large porosities in regions near the edge of the castability pattern and infrequently adjacent to noncast segments. All castings acquired traces of elements found in the casting crucibles. The grain size for each dental casting alloy was generally finer for specimens produced by the induction/vacuum-pressure method. The difference was substantial for JO and L. This study demonstrated a relation between casting techniques and some physical properties of metal ceramic casting alloys. Copyright © 2013 Editorial Council for the Journal of Prosthetic Dentistry. Published by Mosby, Inc. All rights reserved.

In situ calibration of inductively coupled plasma-atomic emission and mass spectroscopy

DOEpatents

Braymen, Steven D.

1996-06-11

A method and apparatus for in situ addition calibration of an inductively coupled plasma atomic emission spectrometer or mass spectrometer using a precision gas metering valve to introduce a volatile calibration gas of an element of interest directly into an aerosol particle stream. The present situ calibration technique is suitable for various remote, on-site sampling systems such as laser ablation or nebulization.

Monitoring by Control Technique - Cyclone

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Stationary source emissions monitoring is required to demonstrate that a source is meeting the requirements in Federal or state rules. This page is about cyclone control techniques used to reduce pollutant emissions.

Monitoring by Control Technique - Condensers

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Stationary source emissions monitoring is required to demonstrate that a source is meeting the requirements in Federal or state rules. This page is about condenser control techniques used to reduce pollutant emissions.

Deductive Glue Code Synthesis for Embedded Software Systems Based on Code Patterns

NASA Technical Reports Server (NTRS)

Liu, Jian; Fu, Jicheng; Zhang, Yansheng; Bastani, Farokh; Yen, I-Ling; Tai, Ann; Chau, Savio N.

2006-01-01

Automated code synthesis is a constructive process that can be used to generate programs from specifications. It can, thus, greatly reduce the software development cost and time. The use of formal code synthesis approach for software generation further increases the dependability of the system. Though code synthesis has many potential benefits, the synthesis techniques are still limited. Meanwhile, components are widely used in embedded system development. Applying code synthesis to component based software development (CBSD) process can greatly enhance the capability of code synthesis while reducing the component composition efforts. In this paper, we discuss the issues and techniques for applying deductive code synthesis techniques to CBSD. For deductive synthesis in CBSD, a rule base is the key for inferring appropriate component composition. We use the code patterns to guide the development of rules. Code patterns have been proposed to capture the typical usages of the components. Several general composition operations have been identified to facilitate systematic composition. We present the technique for rule development and automated generation of new patterns from existing code patterns. A case study of using this method in building a real-time control system is also presented.

Rule groupings: An approach towards verification of expert systems

NASA Technical Reports Server (NTRS)

Mehrotra, Mala

1991-01-01

Knowledge-based expert systems are playing an increasingly important role in NASA space and aircraft systems. However, many of NASA's software applications are life- or mission-critical and knowledge-based systems do not lend themselves to the traditional verification and validation techniques for highly reliable software. Rule-based systems lack the control abstractions found in procedural languages. Hence, it is difficult to verify or maintain such systems. Our goal is to automatically structure a rule-based system into a set of rule-groups having a well-defined interface to other rule-groups. Once a rule base is decomposed into such 'firewalled' units, studying the interactions between rules would become more tractable. Verification-aid tools can then be developed to test the behavior of each such rule-group. Furthermore, the interactions between rule-groups can be studied in a manner similar to integration testing. Such efforts will go a long way towards increasing our confidence in the expert-system software. Our research efforts address the feasibility of automating the identification of rule groups, in order to decompose the rule base into a number of meaningful units.

Advancements in Transmitters and Sensors for Biological Tissue Imaging in Magnetic Induction Tomography

PubMed Central

Zakaria, Zulkarnay; Rahim, Ruzairi Abdul; Mansor, Muhammad Saiful Badri; Yaacob, Sazali; Ayub, Nor Muzakkir Nor; Muji, Siti Zarina Mohd.; Rahiman, Mohd Hafiz Fazalul; Aman, Syed Mustafa Kamal Syed

2012-01-01

Magnetic Induction Tomography (MIT), which is also known as Electromagnetic Tomography (EMT) or Mutual Inductance Tomography, is among the imaging modalities of interest to many researchers around the world. This noninvasive modality applies an electromagnetic field and is sensitive to all three passive electromagnetic properties of a material that are conductivity, permittivity and permeability. MIT is categorized under the passive imaging family with an electrodeless technique through the use of excitation coils to induce an electromagnetic field in the material, which is then measured at the receiving side by sensors. The aim of this review is to discuss the challenges of the MIT technique and summarize the recent advancements in the transmitters and sensors, with a focus on applications in biological tissue imaging. It is hoped that this review will provide some valuable information on the MIT for those who have interest in this modality. The need of this knowledge may speed up the process of adopted of MIT as a medical imaging technology. PMID:22969341

SQUIDs vs. Induction Coils for Ultra-Low Field Nuclear Magnetic Resonance: Experimental and Simulation Comparison

PubMed Central

Matlashov, Andrei N.; Schultz, Larry J.; Espy, Michelle A.; Kraus, Robert H.; Savukov, Igor M.; Volegov, Petr L.; Wurden, Caroline J.

2011-01-01

Nuclear magnetic resonance (NMR) is widely used in medicine, chemistry and industry. One application area is magnetic resonance imaging (MRI). Recently it has become possible to perform NMR and MRI in the ultra-low field (ULF) regime requiring measurement field strengths of the order of only 1 Gauss. This technique exploits the advantages offered by superconducting quantum interference devices or SQUIDs. Our group has built SQUID based MRI systems for brain imaging and for liquid explosives detection at airport security checkpoints. The requirement for liquid helium cooling limits potential applications of ULF MRI for liquid identification and security purposes. Our experimental comparative investigation shows that room temperature inductive magnetometers may provide enough sensitivity in the 3–10 kHz range and can be used for fast liquid explosives detection based on ULF NMR technique. We describe experimental and computer-simulation results comparing multichannel SQUID based and induction coils based instruments that are capable of performing ULF MRI for liquid identification. PMID:21747638

Inductive sensor performance in partial discharges and noise separation by means of spectral power ratios.

PubMed

Ardila-Rey, Jorge Alfredo; Rojas-Moreno, Mónica Victoria; Martínez-Tarifa, Juan Manuel; Robles, Guillermo

2014-02-19

Partial discharge (PD) detection is a standardized technique to qualify electrical insulation in machines and power cables. Several techniques that analyze the waveform of the pulses have been proposed to discriminate noise from PD activity. Among them, spectral power ratio representation shows great flexibility in the separation of the sources of PD. Mapping spectral power ratios in two-dimensional plots leads to clusters of points which group pulses with similar characteristics. The position in the map depends on the nature of the partial discharge, the setup and the frequency response of the sensors. If these clusters are clearly separated, the subsequent task of identifying the source of the discharge is straightforward so the distance between clusters can be a figure of merit to suggest the best option for PD recognition. In this paper, two inductive sensors with different frequency responses to pulsed signals, a high frequency current transformer and an inductive loop sensor, are analyzed to test their performance in detecting and separating the sources of partial discharges.

An Inductive Logic Programming Approach to Validate Hexose Binding Biochemical Knowledge.

PubMed

Nassif, Houssam; Al-Ali, Hassan; Khuri, Sawsan; Keirouz, Walid; Page, David

2010-01-01

Hexoses are simple sugars that play a key role in many cellular pathways, and in the regulation of development and disease mechanisms. Current protein-sugar computational models are based, at least partially, on prior biochemical findings and knowledge. They incorporate different parts of these findings in predictive black-box models. We investigate the empirical support for biochemical findings by comparing Inductive Logic Programming (ILP) induced rules to actual biochemical results. We mine the Protein Data Bank for a representative data set of hexose binding sites, non-hexose binding sites and surface grooves. We build an ILP model of hexose-binding sites and evaluate our results against several baseline machine learning classifiers. Our method achieves an accuracy similar to that of other black-box classifiers while providing insight into the discriminating process. In addition, it confirms wet-lab findings and reveals a previously unreported Trp-Glu amino acids dependency.

T-cell receptor revision: friend or foe?

PubMed

Hale, J Scott; Fink, Pamela J

2010-04-01

T-cell receptor (TCR) revision is a process of tolerance induction by which peripheral T cells lose surface expression of an autoreactive TCR, reinduce expression of the recombinase machinery, rearrange genes encoding extrathymically generated TCRs for antigen, and express these new receptors on the cell surface. We discuss the evidence for this controversial tolerance mechanism below. Despite the apparent heresy of post-thymic gene rearrangement, we argue here that TCR revision follows the rules obeyed by maturing thymocytes undergoing gene recombination. Expression of the recombinase is carefully controlled both spatially and temporally, and may be initiated by loss of signals through surface TCRs. The resulting TCR repertoire is characterized by its diversity, self major histocompatibility complex restriction, self tolerance, and ability to mount productive immune responses specific for foreign antigens. Hence, TCR revision is a carefully regulated process of tolerance induction that can contribute to the protection of the individual against invading pathogens while preserving the integrity of self tissue.

Temporal data mining for the quality assessment of hemodialysis services.

PubMed

Bellazzi, Riccardo; Larizza, Cristiana; Magni, Paolo; Bellazzi, Roberto

2005-05-01

This paper describes the temporal data mining aspects of a research project that deals with the definition of methods and tools for the assessment of the clinical performance of hemodialysis (HD) services, on the basis of the time series automatically collected during hemodialysis sessions. Intelligent data analysis and temporal data mining techniques are applied to gain insight and to discover knowledge on the causes of unsatisfactory clinical results. In particular, two new methods for association rule discovery and temporal rule discovery are applied to the time series. Such methods exploit several pre-processing techniques, comprising data reduction, multi-scale filtering and temporal abstractions. We have analyzed the data of more than 5800 dialysis sessions coming from 43 different patients monitored for 19 months. The qualitative rules associating the outcome parameters and the measured variables were examined by the domain experts, which were able to distinguish between rules confirming available background knowledge and unexpected but plausible rules. The new methods proposed in the paper are suitable tools for knowledge discovery in clinical time series. Their use in the context of an auditing system for dialysis management helped clinicians to improve their understanding of the patients' behavior.

The first success of glass eel production in the world: basic biology on fish reproduction advances new applied technology in aquaculture.

PubMed

Kagawa, Hirohiko; Tanaka, Hideki; Ohta, Hiromi; Unuma, Tatsuya; Nomura, Kazuharu

2005-04-01

The eel has long been esteemed as an important food fish in the world, especially in Japan, and has been used as an experimental fish for many fields of fish physiology. However, the decreases in eel resources have been a serious concern in recent years. The catches of glass eels as seedlings for aquaculture have shown a long-term decrease in both Europe and East Asia. To increase eel resources, the development of techniques for artificial induction of maturation and spawning and rearing their larvae have been eagerly desired. Recent progress of reproductive physiology of fish, especially mechanisms of oocyte maturation and ovulation in female and of spermatozoa maturation in male, facilitate to establish techniques for hormonal induction of maturation and spawning in sexually immature eels. With persistent effort to development of rearing techniques of larvae, we have first succeeded to produce glass eel. These applied techniques are may contribute to understand the basic reproductive physiology of the eel.

Irreversible electroporation of locally advanced pancreatic neck/body adenocarcinoma

PubMed Central

2015-01-01

Objective Irreversible electroporation (IRE) of locally advanced pancreatic adenocarcinoma of the neck has been used to palliate appropriate stage 3 pancreatic cancers without evidence of metastasis and who have undergone appropriate induction therapy. Currently there has not been a standardized reported technique for pancreatic mid-body tumors for patient selection and intra-operative technique. Patients Subjects are patients with locally advanced pancreatic adenocarcinoma of the body/neck who have undergone appropriate induction chemotherapy for a reasonable duration. Main outcome measures Technique of open IRE of locally advanced pancreatic adenocarcinoma of the neck/body is described, with the emphasis on intra-operative ultrasound and intra-operative electroporation management. Results The technique of open IRE of the pancreatic neck/body with bracketing of the celiac axis and superior mesenteric artery with continuous intraoperative ultrasound imaging and consideration of intraoperative navigational system is described. Conclusions IRE of locally advanced pancreatic adenocarcinoma of the body/neck is feasible for appropriate patients with locally advanced unresectable pancreatic cancer. PMID:26029461

Timely Diagnostic Feedback for Database Concept Learning

ERIC Educational Resources Information Center

Lin, Jian-Wei; Lai, Yuan-Cheng; Chuang, Yuh-Shy

2013-01-01

To efficiently learn database concepts, this work adopts association rules to provide diagnostic feedback for drawing an Entity-Relationship Diagram (ERD). Using association rules and Asynchronous JavaScript and XML (AJAX) techniques, this work implements a novel Web-based Timely Diagnosis System (WTDS), which provides timely diagnostic feedback…

Comparison of Bispectral Index™ values during the flotation restricted environmental stimulation technique and results for stage I sleep: a prospective pilot investigation.

PubMed

Dunham, C Michael; McClain, Jesse V; Burger, Amanda

2017-11-29

To determine whether Bispectral Index™ values obtained during flotation-restricted environment stimulation technique have a similar profile in a single observation compared to literature-derived results found during sleep and other relaxation-induction interventions. Bispectral Index™ values were as follows: awake-state, 96.6; float session-1, 84.3; float session-2, 82.3; relaxation-induction, 82.8; stage I sleep, 86.0; stage II sleep, 66.2; and stages III-IV sleep, 45.1. Awake-state values differed from float session-1 (%difference 12.7%; Cohen's d = 3.6) and float session-2 (%difference 14.8%; Cohen's d = 4.6). Relaxation-induction values were similar to float session-1 (%difference 1.8%; Cohen's d = 0.3) and float session-2 (%difference 0.5%; Cohen's d = 0.1). Stage I sleep values were similar to float session-1 (%difference 1.9%; Cohen's d = 0.4) and float session-2 (%difference 4.3%; Cohen's d = 1.0). Stage II sleep values differed from float session-1 (%difference 21.5%; Cohen's d = 4.3) and float session-2 (%difference 19.6%; Cohen's d = 4.0). Stages III-IV sleep values differed from float session-1 (%difference 46.5%; Cohen's d = 5.6) and float session-2 (%difference 45.2%; Cohen's d = 5.4). Bispectral Index™ values during flotation were comparable to those found in stage I sleep and nadir values described with other relaxation-induction techniques.

Magnetic induction of hyperthermia by a modified self-learning fuzzy temperature controller

NASA Astrophysics Data System (ADS)

Wang, Wei-Cheng; Tai, Cheng-Chi

2017-07-01

The aim of this study involved developing a temperature controller for magnetic induction hyperthermia (MIH). A closed-loop controller was applied to track a reference model to guarantee a desired temperature response. The MIH system generated an alternating magnetic field to heat a high magnetic permeability material. This wireless induction heating had few side effects when it was extensively applied to cancer treatment. The effects of hyperthermia strongly depend on the precise control of temperature. However, during the treatment process, the control performance is degraded due to severe perturbations and parameter variations. In this study, a modified self-learning fuzzy logic controller (SLFLC) with a gain tuning mechanism was implemented to obtain high control performance in a wide range of treatment situations. This implementation was performed by appropriately altering the output scaling factor of a fuzzy inverse model to adjust the control rules. In this study, the proposed SLFLC was compared to the classical self-tuning fuzzy logic controller and fuzzy model reference learning control. Additionally, the proposed SLFLC was verified by conducting in vitro experiments with porcine liver. The experimental results indicated that the proposed controller showed greater robustness and excellent adaptability with respect to the temperature control of the MIH system.

Prediction in Health Domain Using Bayesian Networks Optimization Based on Induction Learning Techniques

NASA Astrophysics Data System (ADS)

Felgaer, Pablo; Britos, Paola; García-Martínez, Ramón

A Bayesian network is a directed acyclic graph in which each node represents a variable and each arc a probabilistic dependency; they are used to provide: a compact form to represent the knowledge and flexible methods of reasoning. Obtaining it from data is a learning process that is divided in two steps: structural learning and parametric learning. In this paper we define an automatic learning method that optimizes the Bayesian networks applied to classification, using a hybrid method of learning that combines the advantages of the induction techniques of the decision trees (TDIDT-C4.5) with those of the Bayesian networks. The resulting method is applied to prediction in health domain.

Determination of induction period and crystal growth mechanism of dexamethasone sodium phosphate in methanol-acetone system

NASA Astrophysics Data System (ADS)

Hao, Hongxun; Wang, Jingkang; Wang, Yongli

2005-02-01

The induction period of dexamethasone sodium phosphate at different supersaturation was experimentally determined in a methanol-acetone system. The laser monitoring observation technique was used to determine the appearance of the first nucleus in solution. The effect of solution composition on induction period was discussed. Based on classical homogeneous nucleation theory, the solid-liquid interfacial tension and surface entropy factor were calculated from the induction period data. The experimentally determined values of interfacial tension are in agreement with the theoretical values predicted by the Mersmann equation. It was found that the nucleus of dexamethasone sodium phosphate grows continuously in pure methanol and turns from continuous growth to birth and spread growth with increasing acetone content in a methanol-acetone mixture.

Solid fossil-fuel recovery by electrical induction heating in situ - A proposal

NASA Astrophysics Data System (ADS)

Fisher, S.

1980-04-01

A technique, termed electrical induction heating, is proposed for in situ processes of energy production from solid fossil fuels, such as bitumen production from underground distillation of oil sand; oil by underground distillation of oil shale; petroleum from heavy oil by underground mobilization of heavy oil, from either residues of conventional liquid petroleum deposits or new deposits of viscous oil; methane and coal tar from lignite and coal deposits by underground distillation of coal; and generation of electricity by surface combustion of low calorific-value gas from underground coke gasification by combustion of the organic residue left from the underground distillation of coal by induction heating. A method of surface distillation of mined coking coal by induction heating to produce coke, methane, and coal tar is also proposed.

Signal-chip microcomputer control system for a diffraction grating ruling engine

NASA Astrophysics Data System (ADS)

Wang, Xiaolin; Zhang, Yuhua; Yang, Houmin; Guo, Du

1998-08-01

A control system with a chip of 8031 single-chip microcomputer as its nucleus for a diffraction grating ruling engine has been developed, its hardware and software are presented in this paper. A series of techniques such as program-controlled amplifier and interference fringes subdivision as well as motor velocity step governing are adopted to improve the control accuracy. With this control system, 8 kinds of gratings of different spacings can be ruled, the positioning precision of the diffraction grating ruling engine (sigma) equals 3.6 nm, and the maximum positioning error is less than 14.6 nm.

Monitoring by Control Technique - Catalytic Oxidizer

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Stationary source emissions monitoring is required to demonstrate that a source is meeting the requirements in Federal or state rules. This page is about catalytic oxidizer control techniques used to reduce pollutant emissions.

Monitoring by Control Technique - Thermal Oxidizer

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Stationary source emissions monitoring is required to demonstrate that a source is meeting the requirements in Federal or state rules. This page is about thermal oxidizer control techniques used to reduce pollutant emissions.

Monitoring by Control Technique - Electrostatic Precipitators

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Stationary source emissions monitoring is required to demonstrate that a source is meeting the requirements in Federal or state rules. This page is about electrostatic precipitator control techniques used to reduce pollutant emissions.

Monitoring by Control Technique - Fabric Filters

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Stationary source emissions monitoring is required to demonstrate that a source is meeting the requirements in Federal or state rules. This page is about fabric filter control techniques used to reduce pollutant emissions.

Monitoring by Control Technique - Capture Systems

EPA Pesticide Factsheets

Stationary source emissions monitoring is required to demonstrate that a source is meeting the requirements in Federal or state rules. This page is about capture system control techniques used to reduce pollutant emissions.

Genetic analysis of tissue interactions required for otic placode induction in the zebrafish.

PubMed

Mendonsa, E S; Riley, B B

1999-02-01

Development of the vertebrate inner ear begins during gastrulation with induction of the otic placode. Several embryonic tissues, including cephalic mesendoderm, notochord, and hindbrain, have been implicated as potential sources of otic-inducing signals. However, the relative contributions of these tissues have not been determined, nor have any genes affecting placode induction been identified. To address these issues, we analyzed otic placode induction in zebrafish mutants that are deficient in prospective otic-inducing tissues. Otic development was monitored by examining mutant embryos for morphological changes and, in some cases, by visualizing expression patterns of dlx-3 or pax-2.1 in preotic cells several hours before otic placode formation. In cyclops (cyc-) mutants, which develop with a partial deficiency of prechordal mesendoderm, otic induction is delayed by up to 1 h. In one-eyed pinhead (oep-) mutants, which are more completely deficient in prechordal mesendoderm, otic induction is delayed by 1.5 h, and morphology of the otic vesicles is abnormal. Expression of marker genes in other regions of the neural plate is normal, suggesting that ablation of prechordal mesendoderm selectively inhibits otic induction. In contrast, the timing and morphology of otic development is not affected by mutations in no tail (ntl) or floating head (flh), which prevent notochord differentiation. Similarly, a mutation in valentino (val), which blocks early differentiation of rhombomeres 5 and 6 in the hindbrain, does not delay otic induction, although subsequent patterning of the otic vesicle is impaired. To test whether inductive signals from one tissue can compensate for loss of another, we generated double or triple mutants with various combinations of the above mutations. In none of the multiple mutants do the flh or val mutations exacerbate delays in placode induction, although val does contribute additively to defects in subsequent patterning of the otic vesicle. In contrast, mutants homozygous for both oep and ntl, which interact synergistically to disrupt differentiation of cephalic and axial mesendoderm, show a delay in otic development of about 3 h. These data suggest that cephalic mesendoderm, including prechordal mesendoderm and anterior paraxial mesendoderm, provides the first otic-inducing signals during gastrulation, whereas chordamesoderm plays no discernible role in this process. Because val- mutants are deficient for only a portion of the hindbrain, we cannot rule out a role for that tissue in otic placode induction. However, if the hindbrain does provide otic-inducing signals, they apparently differ quantitatively or qualitatively from the signals required for vesicle patterning, as val disrupts only the latter. Copyright 1999 Academic Press.

Rule-governed Approaches to Physics--Newton's Third Law.

ERIC Educational Resources Information Center

Maloney, David P.

1984-01-01

Describes an approach to assessing the use of rules in solving problems related to Newton's third law of motion. Discusses the problems used, method of questioning, scoring of problem sets, and a general overview of the use of the technique in aiding the teacher in dealing with student's conceptual levels. (JM)

75 FR 52472 - Spectrum Requirements for Advanced Medical Technologies

Federal Register 2010, 2011, 2012, 2013, 2014

2010-08-26

... requires a ``Commission- approved human body simulator and test technique,'' fails to provide sufficient... therapeutic purposes in humans. In the MedRadio Order, the Commission also adopted service and technical rules... devices--the more flexible MedRadio rules accommodate body-worn as well as implanted medical devices...

Managerial Innovation: Rules for Successful Implementation.

ERIC Educational Resources Information Center

Baldridge, J. Victor

1980-01-01

The Higher Education Research Institute studied the impact of Exxon Foundation grants from the Resource Allocation and Management Program (RAMP) at 49 private colleges to determine if and how college planning and financial stability were affected by changes in management techniques. Rules for supporting innovations at various phases of a project's…

RANWAR: rank-based weighted association rule mining from gene expression and methylation data.

PubMed

Mallik, Saurav; Mukhopadhyay, Anirban; Maulik, Ujjwal

2015-01-01

Ranking of association rules is currently an interesting topic in data mining and bioinformatics. The huge number of evolved rules of items (or, genes) by association rule mining (ARM) algorithms makes confusion to the decision maker. In this article, we propose a weighted rule-mining technique (say, RANWAR or rank-based weighted association rule-mining) to rank the rules using two novel rule-interestingness measures, viz., rank-based weighted condensed support (wcs) and weighted condensed confidence (wcc) measures to bypass the problem. These measures are basically depended on the rank of items (genes). Using the rank, we assign weight to each item. RANWAR generates much less number of frequent itemsets than the state-of-the-art association rule mining algorithms. Thus, it saves time of execution of the algorithm. We run RANWAR on gene expression and methylation datasets. The genes of the top rules are biologically validated by Gene Ontologies (GOs) and KEGG pathway analyses. Many top ranked rules extracted from RANWAR that hold poor ranks in traditional Apriori, are highly biologically significant to the related diseases. Finally, the top rules evolved from RANWAR, that are not in Apriori, are reported.

Analysis of laser-induction hybrid cladding processing conditions

NASA Astrophysics Data System (ADS)

Huang, Yongjun; Zeng, Xiaoyan; Hu, Qianwu

2007-12-01

A new cladding approach based on laser-induction hybrid technique on flat sheets is presented in this paper. Coating is produced by means of 5kw cw CO II laser equipped with 100kw high frequent inductor, and the experiments set-up, involving a special machining-head, which can provide laser-induction hybrid heat resources simultaneously. The formation of thick NiCrSiB coating on a steel substrate by off-axial powder feeding is studied from an experimental point of view. A substrate melting energy model is developed to describe the energy relationship between laser-induction hybrid cladding and laser cladding alone quantitatively. By comparing the experimental results with the calculational ones, it is shown that the tendency of fusion zone height of theoretical calculation is in agreement with that of tests in laser-induction hybrid cladding. Via analyses and tests, the conclusions can be lead to that the fusion zone height can be increased easily and the good bond of cladding track can be achieved within wide cladding processing window in laser-induction hybrid processing. It shows that the induction heating has an obvious effect on substrate melting and metallurgical bond.

Mood state dependency of dysfunctional attitudes in bipolar affective disorder.

PubMed

Babakhani, Anet; Startup, Mike

2012-01-01

Studies of cognitive styles among euthymic people with bipolar affective disorder (BAD) without use of mood induction techniques to access those cognitive styles give misleading impressions of normality of those cognitions. The aim of this study was to assess dysfunctional attitudes of participants with BAD, and control participants with no previous psychiatric histories, after mood inductions. Sad and happy moods were induced within 49 BAD and 37 controls. Dysfunctional attitudes were measured following mood inductions using the Dysfunctional Attitude Scale-short form (DAS-24), which has three subscales of achievement, interpersonal, and goal attainment. It was hypothesised that within BAD the sad mood induction would help in accessing dysfunctional attitudes in all three domains relative to the happy mood induction. This was supported. It was also hypothesised that the mood inductions would not affect dysfunctional attitudes within controls. This was supported. When diagnosis was entered as a between group variable, achievement dysfunctional attitudes were significantly higher in BAD compared to controls after a happy induction. Both sad and happy moods provoked higher levels of dysfunctional attitudes within BAD. Euphoria may be related to elevated achievement dysfunctional attitudes, raising risk for mania.

Hyperventilation and photic stimulation are useful additions to a placebo-based suggestive seizure induction protocol in patients with psychogenic nonepileptic seizures.

PubMed

Popkirov, Stoyan; Grönheit, Wenke; Wellmer, Jörg

2015-05-01

The early and definitive diagnosis of psychogenic nonepileptic seizures is a common challenge in epileptology practice. Suggestive seizure induction is a valuable tool to aid the differentiation between epileptic and psychogenic nonepileptic seizures, especially when long-term video-EEG monitoring is inconclusive or unavailable. In this retrospective analysis, we compared the diagnostic yield of a classical, placebo-based induction protocol with that of an extended protocol that includes hyperventilation and photic stimulation as means of suggestion while also implementing more open, standardized patient information. We investigated whether the diversification of suggestive seizure induction has an effect on diagnostic yield and whether it preempts the administration of placebo. Data from 52 patients with confirmed psychogenic nonepileptic seizures were analyzed. While suggestive seizure induction using only placebo-based suggestion provoked a typical event in 13 of 20 patients (65%), the extended protocol was positive in 27 of 34 cases (84%); this improvement was not significant (p=0.11). Noninvasive suggestion techniques accounted for 78% of inductions, avoiding placebo administration in a majority of patients. Still, placebo remains an important part of suggestive seizure induction, responsible for 22% (6 out of 27) of successful inductions using our extended protocol. Our study demonstrates that the diversification of suggestive seizure induction is feasible and beneficial for both patients and diagnosticians. Copyright © 2015 Elsevier Inc. All rights reserved.

Preventing the Catch and Release of Teachers in South Carolina: A Look into the Induction Program Components That Influence Induction Teacher Retention

ERIC Educational Resources Information Center

Counts, Christina Lind

2012-01-01

Catch and release is a practice within recreational fishing intended as a technique of conservation. After capture, the fish are unhooked and returned to the water before experiencing serious exhaustion or injury. This prevents a shortage in the supply and sustains a supply of fish. However, in field of education there is a strong need to…

Monitoring by Control Technique - Activated Carbon Adsorber

EPA Pesticide Factsheets

Stationary source emissions monitoring is required to demonstrate that a source is meeting the requirements in Federal or state rules. This page is about Activated Carbon Adsorber control techniques used to reduce pollutant emissions.

Monitoring by Control Technique - Electrified Filter Bed

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Stationary source emissions monitoring is required to demonstrate that a source is meeting the requirements in Federal or state rules. This page is about electrified filter bed control techniques used to reduce pollutant emissions.

Scoring Tools for the Analysis of Infant Respiratory Inductive Plethysmography Signals.

PubMed

Robles-Rubio, Carlos Alejandro; Bertolizio, Gianluca; Brown, Karen A; Kearney, Robert E

2015-01-01

Infants recovering from anesthesia are at risk of life threatening Postoperative Apnea (POA). POA events are rare, and so the study of POA requires the analysis of long cardiorespiratory records. Manual scoring is the preferred method of analysis for these data, but it is limited by low intra- and inter-scorer repeatability. Furthermore, recommended scoring rules do not provide a comprehensive description of the respiratory patterns. This work describes a set of manual scoring tools that address these limitations. These tools include: (i) a set of definitions and scoring rules for 6 mutually exclusive, unique patterns that fully characterize infant respiratory inductive plethysmography (RIP) signals; (ii) RIPScore, a graphical, manual scoring software to apply these rules to infant data; (iii) a library of data segments representing each of the 6 patterns; (iv) a fully automated, interactive formal training protocol to standardize the analysis and establish intra- and inter-scorer repeatability; and (v) a quality control method to monitor scorer ongoing performance over time. To evaluate these tools, three scorers from varied backgrounds were recruited and trained to reach a performance level similar to that of an expert. These scorers used RIPScore to analyze data from infants at risk of POA in two separate, independent instances. Scorers performed with high accuracy and consistency, analyzed data efficiently, had very good intra- and inter-scorer repeatability, and exhibited only minor confusion between patterns. These results indicate that our tools represent an excellent method for the analysis of respiratory patterns in long data records. Although the tools were developed for the study of POA, their use extends to any study of respiratory patterns using RIP (e.g., sleep apnea, extubation readiness). Moreover, by establishing and monitoring scorer repeatability, our tools enable the analysis of large data sets by multiple scorers, which is essential for longitudinal and multicenter studies.

A Comparison of Inductive Sensors in the Characterization of Partial Discharges and Electrical Noise Using the Chromatic Technique.

PubMed

Ardila-Rey, Jorge Alfredo; Montaña, Johny; de Castro, Bruno Albuquerque; Schurch, Roger; Covolan Ulson, José Alfredo; Muhammad-Sukki, Firdaus; Bani, Nurul Aini

2018-03-29

Partial discharges (PDs) are one of the most important classes of ageing processes that occur within electrical insulation. PD detection is a standardized technique to qualify the state of the insulation in electric assets such as machines and power cables. Generally, the classical phase-resolved partial discharge (PRPD) patterns are used to perform the identification of the type of PD source when they are related to a specific degradation process and when the electrical noise level is low compared to the magnitudes of the PD signals. However, in practical applications such as measurements carried out in the field or in industrial environments, several PD sources and large noise signals are usually present simultaneously. In this study, three different inductive sensors have been used to evaluate and compare their performance in the detection and separation of multiple PD sources by applying the chromatic technique to each of the measured signals.

Feasibility study of a swept frequency electromagnetic probe (SWEEP) using inductive coupling for the determination of subsurface conductivity of the earth and water prospecting in arid regions

NASA Technical Reports Server (NTRS)

Latorraca, G. A.; Bannister, L. H.

1974-01-01

Techniques developed for electromagnetic probing of the lunar interior, and techniques developed for the generation of high power audio frequencies were combined to make practical a magnetic inductive coupling system for the rapid measurement of ground conductivity profiles which are helpful when prospecting for the presence and quality of subsurface water. A system which involves the measurement of the direction, intensity, and time phase of the magnetic field observed near the surface of the earth at a distance from a horizontal coil energized so as to create a field that penetrates the earth was designed and studied to deduce the conductivity and stratification of the subsurface. Theoretical studies and a rudimentary experiment in an arid region showed that the approach is conceptually valid and that this geophysical prospecting technique can be developed for the economical exploration of subterranean water resources.

Fabrication of lithographically defined optical coupling facets for silicon-on-insulator waveguides by inductively coupled plasma etching

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

Yap, K.P.; Lamontagne, B.; Delage, A.

2006-05-15

We present a technique to lithographically define and fabricate all required optical facets on a silicon-on-insulator photonic integrated circuit by an inductively coupled plasma etch process. This technique offers 1 {mu}m positioning accuracy of the facets at any location within the chip and eliminates the need of polishing. Facet fabrication consists of two separate steps to ensure sidewall verticality and minimize attack on the end surfaces of the waveguides. Protection of the waveguides by a thermally evaporated aluminum layer before the 40-70 {mu}m deep optical facet etching has been proven essential in assuring the facet smoothness and integrity. Both scanningmore » electron microscopy analysis and optical measurement results show that the quality of the facets prepared by this technique is comparable to the conventional facets prepared by polishing.« less

Magnetic induction tomography of objects for security applications

NASA Astrophysics Data System (ADS)

Ward, Rob; Joseph, Max; Langley, Abbi; Taylor, Stuart; Watson, Joe C.

2017-10-01

A coil array imaging system has been further developed from previous investigations, focusing on designing its application for fast screening of small bags or parcels, with a view to the production of a compact instrument for security applications. In addition to reducing image acquisition times, work was directed toward exploring potential cost effective manufacturing routes. Based on magnetic induction tomography and eddy-current principles, the instrument captured images of conductive targets using a lock-in amplifier, individually multiplexing signals between a primary driver coil and a 20 by 21 imaging array of secondary passive coils constructed using a reproducible multiple tile design. The design was based on additive manufacturing techniques and provided 2 orthogonal imaging planes with an ability to reconstruct images in less than 10 seconds. An assessment of one of the imaging planes is presented. This technique potentially provides a cost effective threat evaluation technique that may compliment conventional radiographic approaches.

Identification of Malicious Web Pages by Inductive Learning

NASA Astrophysics Data System (ADS)

Liu, Peishun; Wang, Xuefang

Malicious web pages are an increasing threat to current computer systems in recent years. Traditional anti-virus techniques focus typically on detection of the static signatures of Malware and are ineffective against these new threats because they cannot deal with zero-day attacks. In this paper, a novel classification method for detecting malicious web pages is presented. This method is generalization and specialization of attack pattern based on inductive learning, which can be used for updating and expanding knowledge database. The attack pattern is established from an example and generalized by inductive learning, which can be used to detect unknown attacks whose behavior is similar to the example.

Introducing the Big Knowledge to Use (BK2U) challenge.

PubMed

Perl, Yehoshua; Geller, James; Halper, Michael; Ochs, Christopher; Zheng, Ling; Kapusnik-Uner, Joan

2017-01-01

The purpose of the Big Data to Knowledge initiative is to develop methods for discovering new knowledge from large amounts of data. However, if the resulting knowledge is so large that it resists comprehension, referred to here as Big Knowledge (BK), how can it be used properly and creatively? We call this secondary challenge, Big Knowledge to Use. Without a high-level mental representation of the kinds of knowledge in a BK knowledgebase, effective or innovative use of the knowledge may be limited. We describe summarization and visualization techniques that capture the big picture of a BK knowledgebase, possibly created from Big Data. In this research, we distinguish between assertion BK and rule-based BK (rule BK) and demonstrate the usefulness of summarization and visualization techniques of assertion BK for clinical phenotyping. As an example, we illustrate how a summary of many intracranial bleeding concepts can improve phenotyping, compared to the traditional approach. We also demonstrate the usefulness of summarization and visualization techniques of rule BK for drug-drug interaction discovery. © 2016 New York Academy of Sciences.

Association-rule-based tuberculosis disease diagnosis

NASA Astrophysics Data System (ADS)

Asha, T.; Natarajan, S.; Murthy, K. N. B.

2010-02-01

Tuberculosis (TB) is a disease caused by bacteria called Mycobacterium tuberculosis. It usually spreads through the air and attacks low immune bodies such as patients with Human Immunodeficiency Virus (HIV). This work focuses on finding close association rules, a promising technique in Data Mining, within TB data. The proposed method first normalizes of raw data from medical records which includes categorical, nominal and continuous attributes and then determines Association Rules from the normalized data with different support and confidence. Association rules are applied on a real data set containing medical records of patients with TB obtained from a state hospital. The rules determined describes close association between one symptom to another; as an example, likelihood that an occurrence of sputum is closely associated with blood cough and HIV.

Measuring uncertainty by extracting fuzzy rules using rough sets

NASA Technical Reports Server (NTRS)

Worm, Jeffrey A.

1991-01-01

Despite the advancements in the computer industry in the past 30 years, there is still one major deficiency. Computers are not designed to handle terms where uncertainty is present. To deal with uncertainty, techniques other than classical logic must be developed. The methods are examined of statistical analysis, the Dempster-Shafer theory, rough set theory, and fuzzy set theory to solve this problem. The fundamentals of these theories are combined to possibly provide the optimal solution. By incorporating principles from these theories, a decision making process may be simulated by extracting two sets of fuzzy rules: certain rules and possible rules. From these rules a corresponding measure of how much these rules is believed is constructed. From this, the idea of how much a fuzzy diagnosis is definable in terms of a set of fuzzy attributes is studied.

Discovering Sentinel Rules for Business Intelligence

NASA Astrophysics Data System (ADS)

Middelfart, Morten; Pedersen, Torben Bach

This paper proposes the concept of sentinel rules for multi-dimensional data that warns users when measure data concerning the external environment changes. For instance, a surge in negative blogging about a company could trigger a sentinel rule warning that revenue will decrease within two months, so a new course of action can be taken. Hereby, we expand the window of opportunity for organizations and facilitate successful navigation even though the world behaves chaotically. Since sentinel rules are at the schema level as opposed to the data level, and operate on data changes as opposed to absolute data values, we are able to discover strong and useful sentinel rules that would otherwise be hidden when using sequential pattern mining or correlation techniques. We present a method for sentinel rule discovery and an implementation of this method that scales linearly on large data volumes.

From Ringmaster to Conductor: 10 Simple Techniques Can Turn an Unruly Class into a Productive One

ERIC Educational Resources Information Center

Kraft, Matthew A.

2010-01-01

Challenging classrooms can overwhelm a teacher. However, by using effective classroom management and behavior modification techniques, teachers can change challenging classrooms into productive ones. Classroom management techniques include using a relevant curriculum, establishing nonnegotiable rules, ensuring that students know what behavior is…

31 CFR 205.10 - How do you document funding techniques?

Code of Federal Regulations, 2010 CFR

2010-07-01

... techniques? 205.10 Section 205.10 Money and Finance: Treasury Regulations Relating to Money and Finance... EFFICIENT FEDERAL-STATE FUNDS TRANSFERS Rules Applicable to Federal Assistance Programs Included in a Treasury-State Agreement § 205.10 How do you document funding techniques? The Treasury-State agreement must...

31 CFR 205.11 - What requirements apply to funding techniques?

Code of Federal Regulations, 2010 CFR

2010-07-01

... techniques? 205.11 Section 205.11 Money and Finance: Treasury Regulations Relating to Money and Finance... EFFICIENT FEDERAL-STATE FUNDS TRANSFERS Rules Applicable to Federal Assistance Programs Included in a Treasury-State Agreement § 205.11 What requirements apply to funding techniques? (a) A State and a Federal...

Automatic design of decision-tree induction algorithms tailored to flexible-receptor docking data.

PubMed

Barros, Rodrigo C; Winck, Ana T; Machado, Karina S; Basgalupp, Márcio P; de Carvalho, André C P L F; Ruiz, Duncan D; de Souza, Osmar Norberto

2012-11-21

This paper addresses the prediction of the free energy of binding of a drug candidate with enzyme InhA associated with Mycobacterium tuberculosis. This problem is found within rational drug design, where interactions between drug candidates and target proteins are verified through molecular docking simulations. In this application, it is important not only to correctly predict the free energy of binding, but also to provide a comprehensible model that could be validated by a domain specialist. Decision-tree induction algorithms have been successfully used in drug-design related applications, specially considering that decision trees are simple to understand, interpret, and validate. There are several decision-tree induction algorithms available for general-use, but each one has a bias that makes it more suitable for a particular data distribution. In this article, we propose and investigate the automatic design of decision-tree induction algorithms tailored to particular drug-enzyme binding data sets. We investigate the performance of our new method for evaluating binding conformations of different drug candidates to InhA, and we analyze our findings with respect to decision tree accuracy, comprehensibility, and biological relevance. The empirical analysis indicates that our method is capable of automatically generating decision-tree induction algorithms that significantly outperform the traditional C4.5 algorithm with respect to both accuracy and comprehensibility. In addition, we provide the biological interpretation of the rules generated by our approach, reinforcing the importance of comprehensible predictive models in this particular bioinformatics application. We conclude that automatically designing a decision-tree algorithm tailored to molecular docking data is a promising alternative for the prediction of the free energy from the binding of a drug candidate with a flexible-receptor.

Automatic design of decision-tree induction algorithms tailored to flexible-receptor docking data

PubMed Central

2012-01-01

Background This paper addresses the prediction of the free energy of binding of a drug candidate with enzyme InhA associated with Mycobacterium tuberculosis. This problem is found within rational drug design, where interactions between drug candidates and target proteins are verified through molecular docking simulations. In this application, it is important not only to correctly predict the free energy of binding, but also to provide a comprehensible model that could be validated by a domain specialist. Decision-tree induction algorithms have been successfully used in drug-design related applications, specially considering that decision trees are simple to understand, interpret, and validate. There are several decision-tree induction algorithms available for general-use, but each one has a bias that makes it more suitable for a particular data distribution. In this article, we propose and investigate the automatic design of decision-tree induction algorithms tailored to particular drug-enzyme binding data sets. We investigate the performance of our new method for evaluating binding conformations of different drug candidates to InhA, and we analyze our findings with respect to decision tree accuracy, comprehensibility, and biological relevance. Results The empirical analysis indicates that our method is capable of automatically generating decision-tree induction algorithms that significantly outperform the traditional C4.5 algorithm with respect to both accuracy and comprehensibility. In addition, we provide the biological interpretation of the rules generated by our approach, reinforcing the importance of comprehensible predictive models in this particular bioinformatics application. Conclusions We conclude that automatically designing a decision-tree algorithm tailored to molecular docking data is a promising alternative for the prediction of the free energy from the binding of a drug candidate with a flexible-receptor. PMID:23171000

Analyses of known and new types of polyhalogenated aromatic substances in oven ash from recycled aluminium production.

PubMed

Sinkkonen, Seija; Lahtiperä, Mirja; Vattulainen, Antero; Takhistov, Viatcheslav V; Viktorovskii, Igor V; Utsal, Viktor A; Paasivirta, Jaakko

2003-07-01

Persistent aromatic bromine, chlorine and mixed chlorine-bromine compounds were analysed from recycled aluminium smelter (ALS) ashes to explore the impact of brominated flame retardants (BFR) on their formation. Polybrominated diphenyl ethers (PBDE) were the most abundant original BFRs found. Induction furnace ash contained tetra- to octa-BDEs about 2000ng g(-1) in similar congener ratios as the original scrap, but contents of nona- and deca-BDEs were only 25 and 5ng g(-1) indicating their significant degradation in ALS process. In the most non-polar fraction, PCB levels and profiles were similar as earlier ALS ash samples in 1990s. The highest PCB level measured was that of deca-CB (450ng g(-1)) in the induction furnace ash. In this fraction, bromo compounds were non-detectable (<5ng g(-1)). Fraction of the most polar compounds (from reversed toluene elution of carbon column ("dioxin fraction") contained PCDDs, PCDFs and polychlorinated dibenzothiophenes (PCDTs) in similar amounts and congener profiles as earlier investigated ALS ash samples. Bromine-containing dioxin and furan congeners were not detected. From individual PCDDs and PCDFs, octaCDF was the most abundant (205ng g(-1)) in induction furnace ash. In this fraction, the original BFR, tetrabromo-bisphenol-A, was identified. Its level in the induction furnace ash was approximated to be 388ng g(-1). In addition, 12 novel brominated and chlorinated compounds were found as abundant (8-441ng g(-1) in the induction furnace ash) contaminants from the fraction. Four of them were bisphenol derivatives, five biphenylols, then octachlorofluorenone (OCFL) and octachlorobiphenylene (OCBP). Their structures or structure types were deduced from total low-resolution EI mass spectra by theoretical isotope cluster simulation (ICLU) and through known fragmentation rules.

Rumination relates to reduced autobiographical memory specificity in formerly depressed patients following a self-discrepancy challenge: the case of autobiographical memory specificity reactivity.

PubMed

Raes, Filip; Schoofs, Hanne; Griffith, James W; Hermans, Dirk

2012-12-01

Reduced Autobiographical Memory Specificity (rAMS) is a hypothesized vulnerability factor for depression. Rumination is thought to be one of the processes underlying rAMS, but research has failed to show an association between trait rumination and rAMS in individuals who are not currently depressed (e.g., community samples, college samples, and formerly depressed samples). The present study tested whether a challenge procedure that induces a self-discrepancy focus can elicit an association between trait rumination and rAMS in formerly depressed participants. Trait rumination was assessed via self-report. Measures of psychopathology and cognitive function, including depression, were assessed via self-report and interview. Autobiographical Memory Specificity (AMS) was evaluated before and after the induction of a self-discrepancy focus in formerly depressed participants. Results showed that trait rumination was indeed negatively correlated with AMS after, but not before the induction. Moreover, high trait ruminating participants showed a decrease in AMS following the induction. In other words, memory specificity was reactive to the induction, but no such decrease was observed in low trait ruminating individuals. This study is mostly of women. These results may not generalize well to men. Our experimental control was within-subjects, which, although powerful and economical, cannot rule out certain confounding processes including natural changes in self-discrepancy, or non-specific or unintended effects of the induction. In order to detect rAMS in formerly depressed individuals or to observe associations between rAMS and trait measures of rumination, state ruminative processing needs to be activated. Results are discussed by framing rAMS as an example of cognitive reactivity, a general type of processing that is associated with depression. Copyright © 2012 Elsevier Ltd. All rights reserved.

Geometry at the aliphatic tertiary carbon atom: computational and experimental test of the Walsh rule.

PubMed

Böhm, Stanislav; Exner, Otto

2004-02-01

The geometrical parameters of molecules of 2-substituted 2-methylpropanes and 1-substituted bicyclo[2.2.2]octanes were calculated at the B3LYP/6-311+G(d,p) level. They agreed reasonably well with the mean crystallographic values retrieved from the Cambridge Structural Database for a set of diverse non-cyclic structures with a tertiary C atom. The angle deformations at this C atom produced by the immediately bonded substituent are also closely related to those observed previously in benzene mono derivatives (either as calculated or as derived from crystallographic data). The calculated geometrical parameters were used to test the classical Walsh rule: It is evidently true that an electron-attracting substituent increases the proportion of C-atom p-electrons in the bond to the substituent and leaves more s-electrons to the remaining bonds; as a consequence the C-C-C angles at a tertiary carbon are widened and the C-C bonds shortened. However, this rule describes only part of the reality since the bond angles and lengths are controlled by other factors as well, for instance by steric crowding. Another imperfection of the Walsh rule is that the sequence of substituents does not correspond to their electronegativities, as measured by any known scale; more probably it is connected with the inductive effect, but then only very roughly.

Rules of meridians and acupoints selection in treatment of Parkinson's disease based on data mining techniques.

PubMed

Li, Zhe; Hu, Ying-Yu; Zheng, Chun-Ye; Su, Qiao-Zhen; An, Chang; Luo, Xiao-Dong; Liu, Mao-Cai

2018-01-15

To help selecting appropriate meridians and acupoints in clinical practice and experimental study for Parkinson's disease (PD), the rules of meridians and acupoints selection of acupuncture and moxibustion were analyzed in domestic and foreign clinical treatment for PD based on data mining techniques. Literature about PD treated by acupuncture and moxibustion in China and abroad was searched and selected from China National Knowledge Infrastructure and MEDLINE. Then the data from all eligible articles were extracted to establish the database of acupuncture-moxibustion for PD. The association rules of data mining techniques were used to analyze the rules of meridians and acupoints selection. Totally, 168 eligible articles were included and 184 acupoints were applied. The total frequency of acupoints application was 1,090 times. Those acupoints were mainly distributed in head and neck and extremities. Among all, Taichong (LR 3), Baihui (DU 20), Fengchi (GB 20), Hegu (LI 4) and Chorea-tremor Controlled Zone were the top five acupoints that had been used. Superior-inferior acupoints matching was utilized the most. As to involved meridians, Du Meridian, Dan (Gallbladder) Meridian, Dachang (Large Intestine) Meridian, and Gan (Liver) Meridian were the most popular meridians. The application of meridians and acupoints for PD treatment lay emphasis on the acupoints on the head, attach importance to extinguishing Gan wind, tonifying qi and blood, and nourishing sinews, and make good use of superior-inferior acupoints matching.

Incorporating Employee Heterogeneity into Default Rules for Retirement Plan Selection

ERIC Educational Resources Information Center

Goda, Gopi Shah; Manchester, Colleen Flaherty

2013-01-01

We study the effect of incorporating heterogeneity into default rules by examining the choice between retirement plans at a firm that transitioned from a defined benefit (DB) to a defined contribution (DC) plan. The default plan for existing employees varied discontinuously depending on their age. Employing regression discontinuity techniques,…

Matrix effects break the LC behavior rule for analytes in LC-MS/MS analysis of biological samples

USDA-ARS?s Scientific Manuscript database

High-performance liquid chromatography (HPLC) and liquid chromatography-tandem mass spectrometry (LC-MS/MS) are generally accepted as the preferred techniques for detecting and quantitating analytes of interest in biological matrices on the basis of the rule that one chemical compound yields one LC-...

Thin-plate spline quadrature of geodetic integrals

NASA Technical Reports Server (NTRS)

Vangysen, Herman

1989-01-01

Thin-plate spline functions (known for their flexibility and fidelity in representing experimental data) are especially well-suited for the numerical integration of geodetic integrals in the area where the integration is most sensitive to the data, i.e., in the immediate vicinity of the evaluation point. Spline quadrature rules are derived for the contribution of a circular innermost zone to Stoke's formula, to the formulae of Vening Meinesz, and to the recursively evaluated operator L(n) in the analytical continuation solution of Molodensky's problem. These rules are exact for interpolating thin-plate splines. In cases where the integration data are distributed irregularly, a system of linear equations needs to be solved for the quadrature coefficients. Formulae are given for the terms appearing in these equations. In case the data are regularly distributed, the coefficients may be determined once-and-for-all. Examples are given of some fixed-point rules. With such rules successive evaluation, within a circular disk, of the terms in Molodensky's series becomes relatively easy. The spline quadrature technique presented complements other techniques such as ring integration for intermediate integration zones.

In situ calibration of inductively coupled plasma-atomic emission and mass spectroscopy

DOEpatents

Braymen, S.D.

1996-06-11

A method and apparatus are disclosed for in situ addition calibration of an inductively coupled plasma atomic emission spectrometer or mass spectrometer using a precision gas metering valve to introduce a volatile calibration gas of an element of interest directly into an aerosol particle stream. The present in situ calibration technique is suitable for various remote, on-site sampling systems such as laser ablation or nebulization. 5 figs.

NDT of railway components using induction thermography

NASA Astrophysics Data System (ADS)

Netzelmann, U.; Walle, G.; Ehlen, A.; Lugin, S.; Finckbohner, M.; Bessert, S.

2016-02-01

Induction or eddy current thermography is used to detect surface cracks in ferritic steel. The technique is applied to detect surface cracks in rails from a moving test car. Cracks were detected at a train speed between 2 and 15 km/h. An automated demonstrator system for testing railway wheels after production is described. While the wheel is rotated, a robot guides the detection unit consisting of inductor and infrared camera over the surface.

Application of Advanced Concepts and Techniques in Electromagnetic Topology Based Simulations: CRIPTE and Related Codes

DTIC Science & Technology

2008-12-01

multiconductor transmission line theory. The per-unit capacitance, inductance , and characteristic impedance matrices generated from the companion LAPLACE...code based on the Method of Moments application, by meshing different sections of the multiconductor cable for capacitance and inductance matrices [21...conductors held together in four pairs and resided in the cable jacket. Each of eight conductors was also designed with the per unit length resistance

For beginners in anaesthesia, self-training with an audiovisual checklist improves safety during anaesthesia induction: A prospective, randomised, controlled two-centre study.

PubMed

Beck, Stefanie; Reich, Christian; Krause, Dorothea; Ruhnke, Bjarne; Daubmann, Anne; Weimann, Jörg; Zöllner, Christian; Kubitz, Jens

2018-01-31

Beginners in residency programmes in anaesthesia are challenged because working environment is complex, and they cannot rely on experience to meet challenges. During this early stage, residents need rules and structures to guide their actions and ensure patient safety. We investigated whether self-training with an electronic audiovisual checklist app on a mobile phone would produce a long-term improvement in the safety-relevant actions during induction of general anaesthesia. During the first month of their anaesthesia residency, we randomised 26 residents to the intervention and control groups. The study was performed between August 2013 and December 2014 in two university hospitals in Germany. In addition to normal training, the residents of the intervention group trained themselves on well tolerated induction using the electronic checklist for at least 60 consecutive general anaesthesia inductions. After an initial learning phase, all residents were observed during one induction of general anaesthesia. The primary outcome was the number of safety items completed during this anaesthesia induction. Secondary outcomes were similar observations 4 and 8 weeks later. Immediately, and 4 weeks after the first learning phase, residents in the intervention group completed a significantly greater number of safety checks than residents in the control group 2.8 [95% confidence interval (CI) 0.4 to 5.1, P = 0.021, Cohen's d = 0.47] and 3.7 (95% CI 1.3 to 6.1, P = 0.003, Cohen's d = 0.61), respectively. The difference between the groups had disappeared by 8 weeks: mean difference in the number of safety checks at 8 weeks was 0.4, 95% CI -2.0 to 2.8, P = 0.736, Cohen's d = 0.07). The use of an audiovisual self-training checklists improves safety-relevant behaviour in the early stages of a residency training programme in anaesthesia.

Optimum operation of restoration techniques for eutrophic water bodies

NASA Astrophysics Data System (ADS)

Hagen, N. M.; Kleeberg, H.-B.

1994-05-01

Operating rules have been applied in water resources management for a long time in order to control and supply a required quantity (volume) of water. The operating rules have to guarantee the optimum management of the reservoir(s). The quality of the stored water has been satisfactory for the desired utilization up to the sixties. Due to the deterioration of reservoir water quality through human impacts, however, increased attention had to be paid since. Eutrophication of stagnant waters is still an unsolved problem. Through means of various restoration techniques, i.e., dilution/flushing or hypolimnetic withdrawal, the quality of the stored water can be improved. Continuous operation or appropriate time or depth variant operating rules are required to achieve this goal. The paper presents such rules for long-term operation. They have been established for the first time and can he represented in two or three-dimensional graphs depending on the number of included components (e.g., actual water storage and quality). The ‘quality operating rules’ take into account the dynamics of the processes in aquatic ecosystems. Simplifications with regard to application and acceptance (e.g., clarity) are developed and tested. The general validity and efficiency of the operating rules have been proved in a case study (a multi-purpose reservoir) and a fictitious lake.

Complex-energy approach to sum rules within nuclear density functional theory

DOE PAGES

Hinohara, Nobuo; Kortelainen, Markus; Nazarewicz, Witold; ...

2015-04-27

The linear response of the nucleus to an external field contains unique information about the effective interaction, correlations governing the behavior of the many-body system, and properties of its excited states. To characterize the response, it is useful to use its energy-weighted moments, or sum rules. By comparing computed sum rules with experimental values, the information content of the response can be utilized in the optimization process of the nuclear Hamiltonian or nuclear energy density functional (EDF). But the additional information comes at a price: compared to the ground state, computation of excited states is more demanding. To establish anmore » efficient framework to compute energy-weighted sum rules of the response that is adaptable to the optimization of the nuclear EDF and large-scale surveys of collective strength, we have developed a new technique within the complex-energy finite-amplitude method (FAM) based on the quasiparticle random- phase approximation. The proposed sum-rule technique based on the complex-energy FAM is a tool of choice when optimizing effective interactions or energy functionals. The method is very efficient and well-adaptable to parallel computing. As a result, the FAM formulation is especially useful when standard theorems based on commutation relations involving the nuclear Hamiltonian and external field cannot be used.« less

TiN Coating of Accelerator Beamline Chambers

NASA Astrophysics Data System (ADS)

Leung, K. N.; Gough, R. A.; Mashaw, A.; Lee, Y.; Wutte, D.

1997-05-01

One of the problems encountered in many high-power rf systems is multipactoring inside vacuum cavities. The potential for multipactoring occurs whenever the secondary electron emission (SEM) coefficient of the surface exceeds unity. The secondary electtron emission coefficient of titanium-nitride is always less than unity. Therefore, a TiN coating can reduce multipactoring and also reduce photoemission electron from beam-pipe surfaces. The TiN film is very stable. A new technique is being explored at LBNL that will allow an efficient way to coat differently shaped surfaces. In this technique, rf-induction discharge with an exposed Ti induction antenna is used. Tests are being performed using argon, nitrogen, and a mixture of argon/nitrogen gases. Results of this testing will be presented.

Heuristics structure and pervade formal risk assessment.

PubMed

MacGillivray, Brian H

2014-04-01

Lay perceptions of risk appear rooted more in heuristics than in reason. A major concern of the risk regulation literature is that such "error-strewn" perceptions may be replicated in policy, as governments respond to the (mis)fears of the citizenry. This has led many to advocate a relatively technocratic approach to regulating risk, characterized by high reliance on formal risk and cost-benefit analysis. However, through two studies of chemicals regulation, we show that the formal assessment of risk is pervaded by its own set of heuristics. These include rules to categorize potential threats, define what constitutes valid data, guide causal inference, and to select and apply formal models. Some of these heuristics lay claim to theoretical or empirical justifications, others are more back-of-the-envelope calculations, while still more purport not to reflect some truth but simply to constrain discretion or perform a desk-clearing function. These heuristics can be understood as a way of authenticating or formalizing risk assessment as a scientific practice, representing a series of rules for bounding problems, collecting data, and interpreting evidence (a methodology). Heuristics are indispensable elements of induction. And so they are not problematic per se, but they can become so when treated as laws rather than as contingent and provisional rules. Pitfalls include the potential for systematic error, masking uncertainties, strategic manipulation, and entrenchment. Our central claim is that by studying the rules of risk assessment qua rules, we develop a novel representation of the methods, conventions, and biases of the prior art. © 2013 Society for Risk Analysis.

Electromagnetic induction imaging of concealed metallic objects by means of resonating circuits

NASA Astrophysics Data System (ADS)

Guilizzoni, R.; Watson, J. C.; Bartlett, P. A.; Renzoni, F.

2016-05-01

An electromagnetic induction system, suitable for 2D imaging of metallic samples of different electrical conductivities, has been developed. The system is based on a parallel LCR circuit comprising a ferrite-cored coil (7.8 mm x 9.5 mm, L=680 μH at 1 KHz), a variable resistor and capacitor. The working principle of the system is based on eddy current induction inside a metallic sample when this is introduced into the AC magnetic field created by the coil. The inductance of the LCR circuit is modified due to the presence of the sample, to an extent that depends on its conductivity. Such modification is known to increase when the system is operated at its resonant frequency. Characterizing different metals based on their values of conductivity is therefore possible by utilizing a suitable system operated at resonance. Both imaging and material characterization were demonstrated by means of the proposed electromagnetic induction technique. Furthermore, the choice of using a system with an adjustable resonant frequency made it possible to select resonances that allow magnetic-field penetration through conductive screens. Investigations on the possibility of imaging concealed metals by penetrating such shields have been carried out. A penetration depth of δ~3 mm through aluminium (Al) was achieved. This allowed concealed metallic samples- having conductivities ranging from 0.54 to 59.77 MSm-1 and hidden behind 1.5-mm-thick Al shields- to be imaged. Our results demonstrate that the presence of the concealed metallic objects can be revealed. The technique was thus shown to be a promising detection tool for security applications.

Surface Tension Guided Hanging-Drop: Producing Controllable 3D Spheroid of High-Passaged Human Dermal Papilla Cells and Forming Inductive Microtissues for Hair-Follicle Regeneration.

PubMed

Lin, Bojie; Miao, Yong; Wang, Jin; Fan, Zhexiang; Du, Lijuan; Su, Yongsheng; Liu, Bingcheng; Hu, Zhiqi; Xing, Malcolm

2016-03-09

Human dermal papilla (DP) cells have been studied extensively when grown in the conventional monolayer. However, because of great deviation from the real in vivo three-dimensional (3D) environment, these two-dimensional (2D) grown cells tend to lose the hair-inducible capability during passaging. Hence, these 2D caused concerns have motivated the development of novel 3D culture techniques to produce cellular microtissues with suitable mimics. The hanging-drop approach is based on surface tension-based technique and the interaction between surface tension and gravity field that makes a convergence of liquid drops. This study used this technique in a converged drop to form cellular spheroids of dermal papilla cells. It leads to a controllable 3Dspheroid model for scalable fabrication of inductive DP microtissues. The optimal conditions for culturing high-passaged (P8) DP spheroids were determined first. Then, the morphological, histological and functional studies were performed. In addition, expressions of hair-inductive markers including alkaline phosphatase, α-smooth muscle actin and neural cell adhesion molecule were also analyzed by quantitative RT-PCR, immunostaining and immunoblotting. Finally, P8-DP microtissues were coimplanted with newborn mouse epidermal cells (EPCs) into nude mice. Our results indicated that the formation of 3D microtissues not only endowed P8-DP microtissues many similarities to primary DP, but also confer these microtissues an enhanced ability to induce hair-follicle (HF) neogenesis in vivo. This model provides a potential to elucidate the native biology of human DP, and also shows the promising for the controllable and scalable production of inductive DP cells applied in future follicle regeneration.

Providing QoS through machine-learning-driven adaptive multimedia applications.

PubMed

Ruiz, Pedro M; Botía, Juan A; Gómez-Skarmeta, Antonio

2004-06-01

We investigate the optimization of the quality of service (QoS) offered by real-time multimedia adaptive applications through machine learning algorithms. These applications are able to adapt in real time their internal settings (i.e., video sizes, audio and video codecs, among others) to the unpredictably changing capacity of the network. Traditional adaptive applications just select a set of settings to consume less than the available bandwidth. We propose a novel approach in which the selected set of settings is the one which offers a better user-perceived QoS among all those combinations which satisfy the bandwidth restrictions. We use a genetic algorithm to decide when to trigger the adaptation process depending on the network conditions (i.e., loss-rate, jitter, etc.). Additionally, the selection of the new set of settings is done according to a set of rules which model the user-perceived QoS. These rules are learned using the SLIPPER rule induction algorithm over a set of examples extracted from scores provided by real users. We will demonstrate that the proposed approach guarantees a good user-perceived QoS even when the network conditions are constantly changing.

Two heads are better than one, but how much? Evidence that people's use of causal integration rules does not always conform to normative standards.

PubMed

Vadillo, Miguel A; Ortega-Castro, Nerea; Barberia, Itxaso; Baker, A G

2014-01-01

Many theories of causal learning and causal induction differ in their assumptions about how people combine the causal impact of several causes presented in compound. Some theories propose that when several causes are present, their joint causal impact is equal to the linear sum of the individual impact of each cause. However, some recent theories propose that the causal impact of several causes needs to be combined by means of a noisy-OR integration rule. In other words, the probability of the effect given several causes would be equal to the sum of the probability of the effect given each cause in isolation minus the overlap between those probabilities. In the present series of experiments, participants were given information about the causal impact of several causes and then they were asked what compounds of those causes they would prefer to use if they wanted to produce the effect. The results of these experiments suggest that participants actually use a variety of strategies, including not only the linear and the noisy-OR integration rules, but also averaging the impact of several causes.

Improving patient safety and optimizing nursing teamwork using crew resource management techniques.

PubMed

West, Priscilla; Sculli, Gary; Fore, Amanda; Okam, Nwoha; Dunlap, Cleveland; Neily, Julia; Mills, Peter

2012-01-01

This project describes the application of the "sterile cockpit rule," a crew resource management (CRM) technique, targeted to improve efficacy and safety for nursing assistants in the performance of patient care duties. Crew resource management techniques have been successfully implemented in the aviation industry to improve flight safety. Application of these techniques can improve patient safety in medical settings. The Veterans Affairs (VA) National Center for Patient Safety conducted a CRM training program in select VA nursing units. One unit developed a novel application of the sterile cockpit rule to create protected time for certified nursing assistants (CNAs) while they collected vital signs and blood glucose data at the beginning of each shift. The typical nursing authority structure was reversed, with senior nurses protecting CNAs from distractions. This process led to improvements in efficiency and communication among nurses, with the added benefit of increased staff morale. Crew resource management techniques can be used to improve efficiency, morale, and patient safety in the healthcare setting.

Inference in fuzzy rule bases with conflicting evidence

NASA Technical Reports Server (NTRS)

Koczy, Laszlo T.

1992-01-01

Inference based on fuzzy 'If ... then' rules has played a very important role since when Zadeh proposed the Compositional Rule of Inference and, especially, since the first successful application presented by Mamdani. From the mid-1980's when the 'fuzzy boom' started in Japan, numerous industrial applications appeared, all using simplified techniques because of the high levels of computational complexity. Another feature is that antecedents in the rules are distributed densely in the input space, so the conclusion can be calculated by some weighted combination of the consequents of the matching (fired) rules. The CRI works in the following way: If R is a rule and A* is an observation, the conclusion is computed by B* = R o A* (o stands for the max-min composition). Algorithms implementing this idea directly have an exponential time complexity (maybe the problem is NP-hard) as the rules are relations in X x Y, a k1 x k2 dimensional space, if X is k1, Y is k2 dimensional. The simplified techniques usually decompose the relation into k1 projections in X(sub i) and measure in some way the degree of similarity between observation and antecedent by some parameter of the overlapping. These parameters are aggregated to a single value in (0,1) which is applied as a resulting weight for the given rule. The projections of rules in dimensions Y(sub i) are weighted by these aggregated values and then they are combined in order to obtain a resulting conclusion separately in every dimension. This method is unapplicable with sparse bases as there is no guarantee that an arbitrary observation matches with any of the antecedents. Then, the degree of similarity is 0 and all consequents are weighted by 0. Some considerations for such a situation are summarized in the next sections.

Accurate and precise determination of isotopic ratios by MC-ICP-MS: a review.

PubMed

Yang, Lu

2009-01-01

For many decades the accurate and precise determination of isotope ratios has remained a very strong interest to many researchers due to its important applications in earth, environmental, biological, archeological, and medical sciences. Traditionally, thermal ionization mass spectrometry (TIMS) has been the technique of choice for achieving the highest accuracy and precision. However, recent developments in multi-collector inductively coupled plasma mass spectrometry (MC-ICP-MS) have brought a new dimension to this field. In addition to its simple and robust sample introduction, high sample throughput, and high mass resolution, the flat-topped peaks generated by this technique provide for accurate and precise determination of isotope ratios with precision reaching 0.001%, comparable to that achieved with TIMS. These features, in combination with the ability of the ICP source to ionize nearly all elements in the periodic table, have resulted in an increased use of MC-ICP-MS for such measurements in various sample matrices. To determine accurate and precise isotope ratios with MC-ICP-MS, utmost care must be exercised during sample preparation, optimization of the instrument, and mass bias corrections. Unfortunately, there are inconsistencies and errors evident in many MC-ICP-MS publications, including errors in mass bias correction models. This review examines "state-of-the-art" methodologies presented in the literature for achievement of precise and accurate determinations of isotope ratios by MC-ICP-MS. Some general rules for such accurate and precise measurements are suggested, and calculations of combined uncertainty of the data using a few common mass bias correction models are outlined.

Induction motor inter turn fault detection using infrared thermographic analysis

NASA Astrophysics Data System (ADS)

Singh, Gurmeet; Anil Kumar, T. Ch.; Naikan, V. N. A.

2016-07-01

Induction motors are the most commonly used prime movers in industries. These are subjected to various environmental, thermal and load stresses that ultimately reduces the motor efficiency and later leads to failure. Inter turn fault is the second most commonly observed faults in the motors and is considered the most severe. It can lead to the failure of complete phase and can even cause accidents, if left undetected or untreated. This paper proposes an online and non invasive technique that uses infrared thermography, in order to detect the presence of inter turn fault in induction motor drive. Two methods have been proposed that detect the fault and estimate its severity. One method uses transient thermal monitoring during the start of motor and other applies pseudo coloring technique on infrared image of the motor, after it reaches a thermal steady state. The designed template for pseudo-coloring is in acquiescence with the InterNational Electrical Testing Association (NETA) thermographic standard. An index is proposed to assess the severity of the fault present in the motor.

Inductive Sensor Performance in Partial Discharges and Noise Separation by Means of Spectral Power Ratios

PubMed Central

Ardila-Rey, Jorge Alfredo; Rojas-Moreno, Mónica Victoria; Martínez-Tarifa, Juan Manuel; Robles, Guillermo

2014-01-01

Partial discharge (PD) detection is a standardized technique to qualify electrical insulation in machines and power cables. Several techniques that analyze the waveform of the pulses have been proposed to discriminate noise from PD activity. Among them, spectral power ratio representation shows great flexibility in the separation of the sources of PD. Mapping spectral power ratios in two-dimensional plots leads to clusters of points which group pulses with similar characteristics. The position in the map depends on the nature of the partial discharge, the setup and the frequency response of the sensors. If these clusters are clearly separated, the subsequent task of identifying the source of the discharge is straightforward so the distance between clusters can be a figure of merit to suggest the best option for PD recognition. In this paper, two inductive sensors with different frequency responses to pulsed signals, a high frequency current transformer and an inductive loop sensor, are analyzed to test their performance in detecting and separating the sources of partial discharges. PMID:24556674

Granular Flow Graph, Adaptive Rule Generation and Tracking.

PubMed

Pal, Sankar Kumar; Chakraborty, Debarati Bhunia

2017-12-01

A new method of adaptive rule generation in granular computing framework is described based on rough rule base and granular flow graph, and applied for video tracking. In the process, several new concepts and operations are introduced, and methodologies formulated with superior performance. The flow graph enables in defining an intelligent technique for rule base adaptation where its characteristics in mapping the relevance of attributes and rules in decision-making system are exploited. Two new features, namely, expected flow graph and mutual dependency between flow graphs are defined to make the flow graph applicable in the tasks of both training and validation. All these techniques are performed in neighborhood granular level. A way of forming spatio-temporal 3-D granules of arbitrary shape and size is introduced. The rough flow graph-based adaptive granular rule-based system, thus produced for unsupervised video tracking, is capable of handling the uncertainties and incompleteness in frames, able to overcome the incompleteness in information that arises without initial manual interactions and in providing superior performance and gaining in computation time. The cases of partial overlapping and detecting the unpredictable changes are handled efficiently. It is shown that the neighborhood granulation provides a balanced tradeoff between speed and accuracy as compared to pixel level computation. The quantitative indices used for evaluating the performance of tracking do not require any information on ground truth as in the other methods. Superiority of the algorithm to nonadaptive and other recent ones is demonstrated extensively.

A symbolic/subsymbolic interface protocol for cognitive modeling

PubMed Central

Simen, Patrick; Polk, Thad

2009-01-01

Researchers studying complex cognition have grown increasingly interested in mapping symbolic cognitive architectures onto subsymbolic brain models. Such a mapping seems essential for understanding cognition under all but the most extreme viewpoints (namely, that cognition consists exclusively of digitally implemented rules; or instead, involves no rules whatsoever). Making this mapping reduces to specifying an interface between symbolic and subsymbolic descriptions of brain activity. To that end, we propose parameterization techniques for building cognitive models as programmable, structured, recurrent neural networks. Feedback strength in these models determines whether their components implement classically subsymbolic neural network functions (e.g., pattern recognition), or instead, logical rules and digital memory. These techniques support the implementation of limited production systems. Though inherently sequential and symbolic, these neural production systems can exploit principles of parallel, analog processing from decision-making models in psychology and neuroscience to explain the effects of brain damage on problem solving behavior. PMID:20711520

Entropic Inference

NASA Astrophysics Data System (ADS)

Caticha, Ariel

2011-03-01

In this tutorial we review the essential arguments behing entropic inference. We focus on the epistemological notion of information and its relation to the Bayesian beliefs of rational agents. The problem of updating from a prior to a posterior probability distribution is tackled through an eliminative induction process that singles out the logarithmic relative entropy as the unique tool for inference. The resulting method of Maximum relative Entropy (ME), includes as special cases both MaxEnt and Bayes' rule, and therefore unifies the two themes of these workshops—the Maximum Entropy and the Bayesian methods—into a single general inference scheme.

The Use of Role Play in the Training of Hypnotherapy.

ERIC Educational Resources Information Center

Sanders, Shirley

A model has been developed for using role play in the supervision and training of hypnotherapy. Specific techniques can be role played by trainee and supervisor which can enable the trainee to develop skill and confidence in the use of hypnotic techniques. Hypnotic induction, listening, observing and providing feedback, relaxation,…

Online Student Induction: A Case Study of the Use of Mass Customization Techniques

ERIC Educational Resources Information Center

Phillips, Marion; Hawkins, Rachel; Lunsford, Jane; Sinclair-Pearson, Andrew

2004-01-01

New technology within Open and Distance learning (ODL) provides new opportunities for the delivery of learner support resources. Mass customization techniques offer the advantages of efficient production combined with the development of a learning experience precisely tailored for the individual's study requirements. In this article, we discuss…

The Use of Clinical Hypnosis in a College Counseling Center.

ERIC Educational Resources Information Center

Cohen, Herbert A.

This report describes the use of hypnosis at the Hiram College Counseling Center, a counseling technique that has been especially helpful in academic, athletic, and personal improvement areas. The induction techniques of hypnosis are described as well as the use of hyperempiria. The use of hypnosis in improving study habits and alleviating test…

Parental Discipline in Anglo, Greek, Lebanese, and Vietnamese Cultures.

ERIC Educational Resources Information Center

Papps, Fiona; And Others

1995-01-01

Examined child discipline practices in four ethnic groups in Australia. Twenty mothers from each group responded to 12 situations involving children aged 8 and 4. Greek, Lebanese, Vietnamese, and Anglo mothers showed power assertion was the most frequently used disciplinary technique. Inductive techniques were used more often with the four-year…

A fuzzy hill-climbing algorithm for the development of a compact associative classifier

NASA Astrophysics Data System (ADS)

Mitra, Soumyaroop; Lam, Sarah S.

2012-02-01

Classification, a data mining technique, has widespread applications including medical diagnosis, targeted marketing, and others. Knowledge discovery from databases in the form of association rules is one of the important data mining tasks. An integrated approach, classification based on association rules, has drawn the attention of the data mining community over the last decade. While attention has been mainly focused on increasing classifier accuracies, not much efforts have been devoted towards building interpretable and less complex models. This paper discusses the development of a compact associative classification model using a hill-climbing approach and fuzzy sets. The proposed methodology builds the rule-base by selecting rules which contribute towards increasing training accuracy, thus balancing classification accuracy with the number of classification association rules. The results indicated that the proposed associative classification model can achieve competitive accuracies on benchmark datasets with continuous attributes and lend better interpretability, when compared with other rule-based systems.

40 CFR 141.404 - Treatment technique violations for ground water systems.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 23 2014-07-01 2014-07-01 false Treatment technique violations for ground water systems. 141.404 Section 141.404 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER REGULATIONS Ground Water Rule § 141.404 Treatment technique violations for...

Hypnotic induction in dentistry--coping with the fear of losing control (autonomy): a brief communication.

PubMed

Kleinhauz, M; Eli, I

1991-07-01

A common cause of stress among dental patients is the patient's fear of losing control in face of the "helplessness provoking" dental situation. Although hypno-relaxation and hypnosis serve as efficient tools to aid in the administration of dental treatment to such patients, some of them may view hypnosis as a further relinquishing of control to the hypnotist and thus resist hypnotic induction, despite their willingness to try to use hypnosis for therapeutic reasons. To avoid this resistance, a "self-control" induction method is suggested that enables the patient to remain in control throughout the process. This technique minimizes the threat of losing one's autonomy and thus enables treatment of these patients.

Variable speed induction motor operation from a 20-kHz power bus

NASA Technical Reports Server (NTRS)

Hansen, Irving G.

1989-01-01

Induction motors are recognized for their simple rugged construction. To date, however, their application to variable speed or servo drives was hampered by limitations on their control. Induction motor drives tend to be complex and to display troublesome low speed characteristics due in part to nonsinusoidal driving voltages. A technique was developed which involves direct synthesis of sinusoidal driving voltages from a high frequency power bus and independent control of frequency and voltages. Separation of frequency and voltage allows independent control of rotor and stator flux, full four quadrant operation, and instantaneous torque control. Recent test results, current status of the technology, and proposed aerospace applications will be discussed.

Variable speed induction motor operation from a 20-kHz power bus

NASA Technical Reports Server (NTRS)

Hansen, Irving G.

1989-01-01

Induction motors are recognized for their simple rugged construction to date, however, their application to variable speed or servo drives has been hampered by limitations on their control. Induction motor drives tend to be complex and to display troublesome low speed characteristics due in part to nonsinusoidal driving voltages. A technique was developed which involves direct synthesis of sinusoidal driving voltages from a high frequency power bus and independent control of frequency and voltages. Separation offrequency and voltage allows independent control of rotor and stator flux, full four-quadrant operation, and instantaneous torque control. Recent test results, current status of the technology, and proposed aerospace applications will be discussed.

High density growth of T7 expression strains with auto-induction option

DOEpatents

Studier, F. William

2010-07-20

A bacterial growth medium for promoting auto-induction of transcription of cloned DNA in cultures of bacterial cells grown batchwise is disclosed. The transcription is under the control of a lac repressor. Also disclosed is a bacterial growth medium for improving the production of a selenomethionine-containing protein or polypeptide in a bacterial cell, the protein or polypeptide being produced by recombinant DNA techniques from a lac or T7lac promoter, the bacterial cell encoding a vitamin B12-dependent homocysteine methylase. Finally, disclosed is a bacterial growth medium for suppressing auto-induction of expression in cultures of bacterial cells grown batchwise, said transcription being under the control of lac repressor.

Analysis of axial-induction-based wind plant control using an engineering and a high-order wind plant model

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

Annoni, Jennifer; Gebraad, Pieter M. O.; Scholbrock, Andrew K.

2015-08-14

Wind turbines are typically operated to maximize their performance without considering the impact of wake effects on nearby turbines. Wind plant control concepts aim to increase overall wind plant performance by coordinating the operation of the turbines. This paper focuses on axial-induction-based wind plant control techniques, in which the generator torque or blade pitch degrees of freedom of the wind turbines are adjusted. The paper addresses discrepancies between a high-order wind plant model and an engineering wind plant model. Changes in the engineering model are proposed to better capture the effects of axial-induction-based control shown in the high-order model.

Total Hip Joint Replacement Biotelemetry System

NASA Technical Reports Server (NTRS)

Boreham, J. F.; Postal, R. B.; Luntz, R. A.

1981-01-01

The development of a biotelemetry system that is hermetically sealed within a total hip replacement implant is reported. The telemetry system transmits six channels of stress data to reconstruct the major forces acting on the neck of the prosthesis and uses an induction power coupling technique to eliminate the need for internal batteries. The activities associated with the telemetry microminiaturization, data recovery console, hardware fabrications, power induction systems, electrical and mechanical testing and hermetic sealing test results are discussed.

Comparative Evaluation of Marginal Accuracy of a Cast Fixed Partial Denture Compared to Soldered Fixed Partial Denture Made of Two Different Base Metal Alloys and Casting Techniques: An In vitro Study.

PubMed

Jei, J Brintha; Mohan, Jayashree

2014-03-01

The periodontal health of abutment teeth and the durability of fixed partial denture depends on the marginal adaptation of the prosthesis. Any discrepancy in the marginal area leads to dissolution of luting agent and plaque accumulation. This study was done with the aim of evaluating the accuracy of marginal fit of four unit crown and bridge made up of Ni-Cr and Cr-Co alloys under induction and centrifugal casting. They were compared to cast fixed partial denture (FPD) and soldered FPD. For the purpose of this study a metal model was fabricated. A total of 40 samples (4-unit crown and bridge) were prepared in which 20 Cr-Co samples and 20 Ni-Cr samples were fabricated. Within these 20 samples of each group 10 samples were prepared by induction casting technique and other 10 samples with centrifugal casting technique. The cast FPD samples obtained were seated on the model and the samples were then measured with travelling microscope having precision of 0.001 cm. Sectioning of samples was done between the two pontics and measurements were made, then the soldering was made with torch soldering unit. The marginal discrepancy of soldered samples was measured and all findings were statistically analysed. The results revealed minimal marginal discrepancy with Cr-Co samples when compared to Ni-Cr samples done under induction casting technique. When compared to cast FPD samples, the soldered group showed reduced marginal discrepancy.

Solenoid-free plasma startup in NSTX using transient CHI

NASA Astrophysics Data System (ADS)

Raman, R.; Jarboe, T. R.; Mueller, D.; Nelson, B. A.; Bell, M. G.; Bell, R.; Gates, D.; Gerhardt, S.; Hosea, J.; Kaita, R.; Kugel, H.; LeBlanc, B.; Maingi, R.; Maqueda, R.; Menard, J.; Nagata, M.; Ono, M.; Paul, S.; Roquemore, L.; Sabbagh, S.; Soukhanovskii, V.; Taylor, G.

2009-06-01

Experiments in NSTX have now demonstrated the coupling of toroidal plasmas produced by the technique of coaxial helicity injection (CHI) to inductive sustainment and ramp-up of the toroidal plasma current. In these discharges, the central Ohmic transformer was used to apply an inductive loop voltage to discharges with a toroidal current of about 100 kA created by CHI. The coupled discharges have ramped up to >700 kA and transitioned into an H-mode demonstrating compatibility of this startup method with conventional operation. The electron temperature in the coupled discharges reached over 800 eV and the resulting plasma had low inductance, which is preferred for long-pulse high-performance discharges. These results from NSTX in combination with the previously obtained record 160 kA non-inductively generated startup currents in an ST or tokamak in NSTX demonstrate that CHI is a viable solenoid-free plasma startup method for future STs and tokamaks.

Chemical Waste Management and Disposal.

ERIC Educational Resources Information Center

Armour, Margaret-Ann

1988-01-01

Describes simple, efficient techniques for treating hazardous chemicals so that nontoxic and nonhazardous residues are formed. Discusses general rules for management of waste chemicals from school laboratories and general techniques for the disposal of waste or surplus chemicals. Lists specific disposal reactions. (CW)

Recent trends in high spin sensitivity magnetic resonance

NASA Astrophysics Data System (ADS)

Blank, Aharon; Twig, Ygal; Ishay, Yakir

2017-07-01

Magnetic resonance is a very powerful methodology that has been employed successfully in many applications for about 70 years now, resulting in a wealth of scientific, technological, and diagnostic data. Despite its many advantages, one major drawback of magnetic resonance is its relatively poor sensitivity and, as a consequence, its bad spatial resolution when examining heterogeneous samples. Contemporary science and technology often make use of very small amounts of material and examine heterogeneity on a very small length scale, both of which are well beyond the current capabilities of conventional magnetic resonance. It is therefore very important to significantly improve both the sensitivity and the spatial resolution of magnetic resonance techniques. The quest for higher sensitivity led in recent years to the development of many alternative detection techniques that seem to rival and challenge the conventional ;old-fashioned; induction-detection approach. The aim of this manuscript is to briefly review recent advances in the field, and to provide a quantitative as well as qualitative comparison between various detection methods with an eye to future potential advances and developments. We first offer a common definition of sensitivity in magnetic resonance to enable proper quantitative comparisons between various detection methods. Following that, up-to-date information about the sensitivity capabilities of the leading recently-developed detection approaches in magnetic resonance is provided, accompanied by a critical comparison between them and induction detection. Our conclusion from this comparison is that induction detection is still indispensable, and as such, it is very important to look for ways to significantly improve it. To do so, we provide expressions for the sensitivity of induction-detection, derived from both classical and quantum mechanics, that identify its main limiting factors. Examples from current literature, as well as a description of new ideas, show how these limiting factors can be mitigated to significantly improve the sensitivity of induction detection. Finally, we outline some directions for the possible applications of high-sensitivity induction detection in the field of electron spin resonance.

Comparative investigation of diagnosis media for induction machine mechanical unbalance fault.

PubMed

Salah, Mohamed; Bacha, Khmais; Chaari, Abdelkader

2013-11-01

For an induction machine, we suggest a theoretical development of the mechanical unbalance effect on the analytical expressions of radial vibration and stator current. Related spectra are described and characteristic defect frequencies are determined. Moreover, the stray flux expressions are developed for both axial and radial sensor coil positions and a substitute diagnosis technique is proposed. In addition, the load torque effect on the detection efficiency of these diagnosis media is discussed and a comparative investigation is performed. The decisive factor of comparison is the fault sensitivity. Experimental results show that spectral analysis of the axial stray flux can be an alternative solution to cover effectiveness limitation of the traditional stator current technique and to substitute the classical vibration practice. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

Inductive System Health Monitoring

NASA Technical Reports Server (NTRS)

Iverson, David L.

2004-01-01

The Inductive Monitoring System (IMS) software was developed to provide a technique to automatically produce health monitoring knowledge bases for systems that are either difficult to model (simulate) with a computer or which require computer models that are too complex to use for real time monitoring. IMS uses nominal data sets collected either directly from the system or from simulations to build a knowledge base that can be used to detect anomalous behavior in the system. Machine learning and data mining techniques are used to characterize typical system behavior by extracting general classes of nominal data from archived data sets. IMS is able to monitor the system by comparing real time operational data with these classes. We present a description of learning and monitoring method used by IMS and summarize some recent IMS results.

Universal Parameter Measurement and Sensorless Vector Control of Induction and Permanent Magnet Synchronous Motors

NASA Astrophysics Data System (ADS)

Yamamoto, Shu; Ara, Takahiro

Recently, induction motors (IMs) and permanent-magnet synchronous motors (PMSMs) have been used in various industrial drive systems. The features of the hardware device used for controlling the adjustable-speed drive in these motors are almost identical. Despite this, different techniques are generally used for parameter measurement and speed-sensorless control of these motors. If the same technique can be used for parameter measurement and sensorless control, a highly versatile adjustable-speed-drive system can be realized. In this paper, the authors describe a new universal sensorless control technique for both IMs and PMSMs (including salient pole and nonsalient pole machines). A mathematical model applicable for IMs and PMSMs is discussed. Using this model, the authors derive the proposed universal sensorless vector control algorithm on the basis of estimation of the stator flux linkage vector. All the electrical motor parameters are determined by a unified test procedure. The proposed method is implemented on three test machines. The actual driving test results demonstrate the validity of the proposed method.

A Comparison of Inductive Sensors in the Characterization of Partial Discharges and Electrical Noise Using the Chromatic Technique

PubMed Central

Ardila-Rey, Jorge Alfredo; Montaña, Johny; Schurch, Roger; Covolan Ulson, José Alfredo; Bani, Nurul Aini

2018-01-01

Partial discharges (PDs) are one of the most important classes of ageing processes that occur within electrical insulation. PD detection is a standardized technique to qualify the state of the insulation in electric assets such as machines and power cables. Generally, the classical phase-resolved partial discharge (PRPD) patterns are used to perform the identification of the type of PD source when they are related to a specific degradation process and when the electrical noise level is low compared to the magnitudes of the PD signals. However, in practical applications such as measurements carried out in the field or in industrial environments, several PD sources and large noise signals are usually present simultaneously. In this study, three different inductive sensors have been used to evaluate and compare their performance in the detection and separation of multiple PD sources by applying the chromatic technique to each of the measured signals. PMID:29596337

A Kalman Filter Based Technique for Stator Turn-Fault Detection of the Induction Motors

NASA Astrophysics Data System (ADS)

Ghanbari, Teymoor; Samet, Haidar

2017-11-01

Monitoring of the Induction Motors (IMs) through stator current for different faults diagnosis has considerable economic and technical advantages in comparison with the other techniques in this content. Among different faults of an IM, stator and bearing faults are more probable types, which can be detected by analyzing signatures of the stator currents. One of the most reliable indicators for fault detection of IMs is lower sidebands of power frequency in the stator currents. This paper deals with a novel simple technique for detecting stator turn-fault of the IMs. Frequencies of the lower sidebands are determined using the motor specifications and their amplitudes are estimated by a Kalman Filter (KF). Instantaneous Total Harmonic Distortion (ITHD) of these harmonics is calculated. Since variation of the ITHD for the three-phase currents is considerable in case of stator turn-fault, the fault can be detected using this criterion, confidently. Different simulation results verify high performance of the proposed method. The performance of the method is also confirmed using some experiments.

Quantitative structure-activity relationships by neural networks and inductive logic programming. I. The inhibition of dihydrofolate reductase by pyrimidines

NASA Astrophysics Data System (ADS)

Hirst, Jonathan D.; King, Ross D.; Sternberg, Michael J. E.

1994-08-01

Neural networks and inductive logic programming (ILP) have been compared to linear regression for modelling the QSAR of the inhibition of E. coli dihydrofolate reductase (DHFR) by 2,4-diamino-5-(substitured benzyl)pyrimidines, and, in the subsequent paper [Hirst, J.D., King, R.D. and Sternberg, M.J.E., J. Comput.-Aided Mol. Design, 8 (1994) 421], the inhibition of rodent DHFR by 2,4-diamino-6,6-dimethyl-5-phenyl-dihydrotriazines. Cross-validation trials provide a statistically rigorous assessment of the predictive capabilities of the methods, with training and testing data selected randomly and all the methods developed using identical training data. For the ILP analysis, molecules are represented by attributes other than Hansch parameters. Neural networks and ILP perform better than linear regression using the attribute representation, but the difference is not statistically significant. The major benefit from the ILP analysis is the formulation of understandable rules relating the activity of the inhibitors to their chemical structure.

T-cell receptor revision: friend or foe?

PubMed Central

Hale, J Scott; Fink, Pamela J

2010-01-01

T-cell receptor (TCR) revision is a process of tolerance induction by which peripheral T cells lose surface expression of an autoreactive TCR, reinduce expression of the recombinase machinery, rearrange genes encoding extrathymically generated TCRs for antigen, and express these new receptors on the cell surface. We discuss the evidence for this controversial tolerance mechanism below. Despite the apparent heresy of post-thymic gene rearrangement, we argue here that TCR revision follows the rules obeyed by maturing thymocytes undergoing gene recombination. Expression of the recombinase is carefully controlled both spatially and temporally, and may be initiated by loss of signals through surface TCRs. The resulting TCR repertoire is characterized by its diversity, self major histocompatibility complex restriction, self tolerance, and ability to mount productive immune responses specific for foreign antigens. Hence, TCR revision is a carefully regulated process of tolerance induction that can contribute to the protection of the individual against invading pathogens while preserving the integrity of self tissue. PMID:20201984

THRICE: A Technique for Improving the American English Language Delivery of Non-Native Speakers

ERIC Educational Resources Information Center

Coates, Thomas J.; Regdon, Patricia M.

1974-01-01

THRICE is an acronym for a set of rules and exercises for foreigners learning correct English pronunciation. The THRICE technique was developed for non-native speakers who have a good knowledge of English but whose pronunciation is poor; the student is taught appropriate speech delivery through self-conditioning techniques. (CK)

Welds in thermoplastic composite materials

NASA Astrophysics Data System (ADS)

Taylor, N. S.

Welding methods are reviewed that can be effectively used for joining of thermoplastic composites and continuous-fiber thermoplastics. Attention is given to the use of ultrasonic, vibration, hot-plate, resistance, and induction welding techniques. The welding techniques are shown to provide complementary weld qualities for the range of thermoplastic materials that are of interest to industrial and technological applications.

Improvements in the production of doubled haploids in durum wheat (Triticum turgidum L.) through isolated microspore culture.

PubMed

Cistué, Luis; Romagosa, I; Batlle, F; Echávarri, B

2009-05-01

The objective of this study was to produce durum wheat doubled haploid (DH) plants through the induction of microspore embryogenesis. The microspore culture technique was improved to maximize production of green plants per spike using three commercial cultivars. Studies on factors such as induction media composition, induction media support and the stage and growth of donor plants were carried out in order to develop an efficient protocol to regenerate green and fertile DH plants. Microspores were plated on a C(17) induction culture medium with ovary co-culture and a supplement of glutathione plus glutamine; 300 g/l Ficoll Type-400 was incorporated to the induction medium support. Donor plants were fertilized with a combination of macro and microelements. With the cultivars 'Ciccio' and 'Claudio' an average of 36.5 and 148.5 fertile plants were produced, respectively, from 1,000 anthers inoculated. This technique was then used to produce fertile DH plants of potential agronomic interest from a collection of ten F(1) crosses involving cultivars of high breeding value. From these crosses 849 green plants were obtained and seed was harvested from 702 plants indicating that 83% of green plants were fertile and therefore were spontaneously DHs. No aneuploid plant was obtained. The 702 plants yielded enough seeds to be field tested. One of the DH lines obtained by microspore embryogenesis, named 'Lanuza', has been sent to the Spanish Plant Variety Office for Registration by the Batlle Seed Company. This protocol can be used instead of the labor-intensive inter-generic crossing with maize as an economically feasible method to obtain DHs for most crosses involving the durum wheat cultivars grown in Spain.

Modular Approaches to Earth Science Scientific Computing: 3D Electromagnetic Induction Modeling as an Example

NASA Astrophysics Data System (ADS)

Tandon, K.; Egbert, G.; Siripunvaraporn, W.

2003-12-01

We are developing a modular system for three-dimensional inversion of electromagnetic (EM) induction data, using an object oriented programming approach. This approach allows us to modify the individual components of the inversion scheme proposed, and also reuse the components for variety of problems in earth science computing howsoever diverse they might be. In particular, the modularity allows us to (a) change modeling codes independently of inversion algorithm details; (b) experiment with new inversion algorithms; and (c) modify the way prior information is imposed in the inversion to test competing hypothesis and techniques required to solve an earth science problem. Our initial code development is for EM induction equations on a staggered grid, using iterative solution techniques in 3D. An example illustrated here is an experiment with the sensitivity of 3D magnetotelluric inversion to uncertainties in the boundary conditions required for regional induction problems. These boundary conditions should reflect the large-scale geoelectric structure of the study area, which is usually poorly constrained. In general for inversion of MT data, one fixes boundary conditions at the edge of the model domain, and adjusts the earth?s conductivity structure within the modeling domain. Allowing for errors in specification of the open boundary values is simple in principle, but no existing inversion codes that we are aware of have this feature. Adding a feature such as this is straightforward within the context of the modular approach. More generally, a modular approach provides an efficient methodology for setting up earth science computing problems to test various ideas. As a concrete illustration relevant to EM induction problems, we investigate the sensitivity of MT data near San Andreas Fault at Parkfield (California) to uncertainties in the regional geoelectric structure.

Geomagnetic field models for satellite angular motion studies

NASA Astrophysics Data System (ADS)

Ovchinnikov, M. Yu.; Penkov, V. I.; Roldugin, D. S.; Pichuzhkina, A. V.

2018-03-01

Four geomagnetic field models are discussed: IGRF, inclined, direct and simplified dipoles. Geomagnetic induction vector expressions are provided in different reference frames. Induction vector behavior is compared for different models. Models applicability for the analysis of satellite motion is studied from theoretical and engineering perspectives. Relevant satellite dynamics analysis cases using analytical and numerical techniques are provided. These cases demonstrate the benefit of a certain model for a specific dynamics study. Recommendations for models usage are summarized in the end.

Ultra-modified rapid sequence induction with transnasal humidified rapid insufflation ventilatory exchange: Challenging convention.

PubMed

Kulkarni, Ketan Sakharam; Dave, Nandini; Saran, Shriyam; Garasia, Madhu; Parelkar, Sandesh

2018-04-01

During positive pressure ventilation, gastric inflation and subsequent pulmonary aspiration can occur. Rapid sequence induction (RSI) technique is an age-old formula to prevent this. We adopted a novel approach of RSI for patients with high risk of aspiration and evaluated it further in patients undergoing laparoscopic surgeries. We believe that, in patients with risk of gastric insufflation and pulmonary aspiration, transnasal humidified rapid-insufflation ventilatory exchange can be useful in facilitating pre- and apnoeic oxygenation till tracheal isolation is achieved.

Four quadrant control of induction motors

NASA Technical Reports Server (NTRS)

Hansen, Irving G.

1991-01-01

Induction motors are the nation's workhorse, being the motor of choice in most applications due to their simple rugged construction. It has been estimated that 14 to 27 percent of the country's total electricity use could be saved with adjustable speed drives. Until now, induction motors have not been suited well for variable speed or servo-drives, due to the inherent complexity, size, and inefficiency of their variable speed controls. Work at NASA Lewis Research Center on field oriented control of induction motors using pulse population modulation method holds the promise for the desired drive electronics. The system allows for a variable voltage to frequency ratio which enables the user to operate the motor at maximum efficiency, while having independent control of both the speed and torque of an induction motor in all four quadrants of the speed torque map. Multiple horsepower machine drives were demonstrated, and work is on-going to develop a 20 hp average, 40 hp peak class of machine. The pulse population technique, results to date, and projections for implementation of this existing new motor control technology are discussed.

Fuzzy Logic Controlled Solar Module for Driving Three- Phase Induction Motor

NASA Astrophysics Data System (ADS)

Afiqah Zainal, Nurul; Sooi Tat, Chan; Ajisman

2016-02-01

Renewable energy produced by solar module gives advantages for generated three- phase induction motor in remote area. But, solar module's ou tput is uncertain and complex. Fuzzy logic controller is one of controllers that can handle non-linear system and maximum power of solar module. Fuzzy logic controller used for Maximum Power Point Tracking (MPPT) technique to control Pulse-Width Modulation (PWM) for switching power electronics circuit. DC-DC boost converter used to boost up photovoltaic voltage to desired output and supply voltage source inverter which controlled by three-phase PWM generated by microcontroller. IGBT switched Voltage source inverter (VSI) produced alternating current (AC) voltage from direct current (DC) source to control speed of three-phase induction motor from boost converter output. Results showed that, the output power of solar module is optimized and controlled by using fuzzy logic controller. Besides that, the three-phase induction motor can be drive and control using VSI switching by the PWM signal generated by the fuzzy logic controller. This concluded that the non-linear system can be controlled and used in driving three-phase induction motor.

A Comparison Study of Rule Space Method and Neural Network Model for Classifying Individuals and an Application.

ERIC Educational Resources Information Center

Hayashi, Atsuhiro

Both the Rule Space Method (RSM) and the Neural Network Model (NNM) are techniques of statistical pattern recognition and classification approaches developed for applications from different fields. RSM was developed in the domain of educational statistics. It started from the use of an incidence matrix Q that characterizes the underlying cognitive…

Monitoring by Control Technique - Compliant (Low/No VOC/HAP) Inks and Coatings

EPA Pesticide Factsheets

Stationary source emissions monitoring is required to demonstrate that a source is meeting the requirements in Federal or state rules. This page is about Compliant (Low/No VOC/HAP) Inks and Coatings control techniques used to reduce pollutant emissions.

Spatiotemporal analysis of brightness induction

PubMed Central

McCourt, Mark E.

2011-01-01

Brightness induction refers to a class of visual illusions in which the perceived intensity of a region of space is influenced by the luminance of surrounding regions. These illusions are significant because they provide insight into the neural organization of the visual system. A novel quadrature-phase motion cancelation technique was developed to measure the magnitude of the grating induction brightness illusion across a wide range of spatial frequencies, temporal frequencies and test field heights. Canceling contrast is greatest at low frequencies and declines with increasing frequency in both dimensions, and with increasing test field height. Canceling contrast scales as the product of inducing grating spatial frequency and test field height (the number of inducing grating cycles per test field height). When plotted using a spatial axis which indexes this product, the spatiotemporal induction surfaces for four test field heights can be described as four partially overlapping sections of a single larger surface. These properties of brightness induction are explained in the context of multiscale spatial filtering. The present study is the first to measure the magnitude of grating induction as a function of temporal frequency. Taken in conjunction with several other studies (Blakeslee & McCourt, 2008; Robinson & de Sa, 2008; Magnussen & Glad, 1975) the results of this study illustrate that at least one form of brightness induction is very much faster than that reported by DeValois et al. (1986) and Rossi and Paradiso (1996), and are inconsistent with the proposition that brightness induction results from a slow “filling in” process. PMID:21763339

Exploring perceptions and experiences of patients who have chronic pain as state prescription opioid policies change: a qualitative study in Indiana

PubMed Central

Al Achkar, Morhaf; Revere, Debra; Dennis, Barbara; MacKie, Palmer; Gupta, Sumedha; Grannis, Shaun

2017-01-01

Objectives The misuse and abuse of prescription opioids (POs) is an epidemic in the USA today. Many states have implemented legislation to curb the use of POs resulting from inappropriate prescribing. Indiana legislated opioid prescribing rules that went into effect in December 2013. The rules changed how chronic pain is managed by healthcare providers. This qualitative study aims to evaluate the impact of Indiana’s opioid prescription legislation on the patient experiences around pain management. Setting This is a qualitative study using interviews of patient and primary care providers to obtain triangulated data sources. The patients were recruited from an integrated pain clinic to which chronic pain patients were referred from federally qualified health clinics (FQHCs). The primacy care providers were recruited from the same FQHCs. The study used inductive, emergent thematic analysis. Participants Nine patient participants and five primary care providers were included in the study. Results Living with chronic pain is disruptive to patients’ lives on multiple dimensions. The established pain management practices were disrupted by the change in prescription rules. Patient–provider relationships, which involve power dynamics and decision making, shifted significantly in parallel to the rule change. Conclusions As a result of the changes in pain management practice, some patients experienced significant challenges. Further studies into the magnitude of this change are necessary. In addition, exploring methods for regulating prescribing while assuring adequate access to pain management is crucial. PMID:29133312

Autorefraction, Retinoscopy, Javal's Rule, and Grosvenor's Modified Javal's Rule: The Best Predictor of Refractive Astigmatism

PubMed Central

Asiedu, Kofi; Ampiah, Emmanuel Ekow

2016-01-01

The aim of the study was to determine the level of agreement between Javal's rule, autorefraction, retinoscopy, and refractive astigmatism and to determine which technique is the most suitable substitute when subjective refraction is not applicable using a clinical sample. A total of 36 subjects, 14 males and 22 females, were involved in this study. The intraclass correlation coefficients between subjective refraction, autorefraction, and retinoscopy were 0.895 and 0.989, respectively, for the spherical equivalent. The Bland-Altman 95% limits of agreement between subjective refraction and autorefraction; subjective refraction and retinoscopy; and autorefraction and retinoscopy were −2.84 to 3.58, −0.88 to 1.12, and −3.01 to 3.53, respectively, for the spherical equivalent. The intraclass correlation coefficients between spectacle total astigmatism and the following techniques were as follows: retinoscopy (0.85); autorefraction (0.92); Javal's rule (0.82); and Grosvenor et al. version (0.85). The Bland-Altman 95% limits of agreement between subjective refraction and autorefraction; subjective refraction and retinoscopy; subjective refraction and Javal's rule; and subjective refraction and Grosvenor et al. version were −0.87 to 1.25, −1.49 to 1.99, −0.73 to 1.93, and −0.89 to 1.7, respectively, for the total astigmatism. The study showed that autorefraction and Javal's rule may provide a starting point for subjective refraction cylinder power determination but only retinoscopy may satisfactorily replace subjective refraction total astigmatism when subjective refraction is not applicable. PMID:27803811

Development of a simplified optical technique for the simultaneous measurement of particle size distribution and velocity

NASA Technical Reports Server (NTRS)

Smith, J. L.

1983-01-01

Existing techniques were surveyed, an experimental procedure was developed, a laboratory test model was fabricated, limited data were recovered for proof of principle, and the relationship between particle size distribution and amplitude measurements was illustrated in an effort to develop a low cost, simplified optical technique for measuring particle size distributions and velocities in fluidized bed combustors and gasifiers. A He-Ne laser illuminated Rochi Rulings (range 10 to 500 lines per inch). Various samples of known particle size distributions were passed through the fringe pattern produced by the rulings. A photomultiplier tube converted light from the fringe volume to an electrical signal which was recorded using an oscilloscope and camera. The signal amplitudes were correlated against the known particle size distributions. The correlation holds true for various samples.

Direct repeat sequences in the Streptomyces chitinase-63 promoter direct both glucose repression and chitin induction

PubMed Central

Ni, Xiangyang; Westpheling, Janet

1997-01-01

The chi63 promoter directs glucose-sensitive, chitin-dependent transcription of a gene involved in the utilization of chitin as carbon source. Analysis of 5′ and 3′ deletions of the promoter region revealed that a 350-bp segment is sufficient for wild-type levels of expression and regulation. The analysis of single base changes throughout the promoter region, introduced by random and site-directed mutagenesis, identified several sequences to be important for activity and regulation. Single base changes at −10, −12, −32, −33, −35, and −37 upstream of the transcription start site resulted in loss of activity from the promoter, suggesting that bases in these positions are important for RNA polymerase interaction. The sequences centered around −10 (TATTCT) and −35 (TTGACC) in this promoter are, in fact, prototypical of eubacterial promoters. Overlapping the RNA polymerase binding site is a perfect 12-bp direct repeat sequence. Some base changes within this direct repeat resulted in constitutive expression, suggesting that this sequence is an operator for negative regulation. Other base changes resulted in loss of glucose repression while retaining the requirement for chitin induction, suggesting that this sequence is also involved in glucose repression. The fact that cis-acting mutations resulted in glucose resistance but not inducer independence rules out the possibility that glucose repression acts exclusively by inducer exclusion. The fact that mutations that affect glucose repression and chitin induction fall within the same direct repeat sequence module suggests that the direct repeat sequence facilitates both chitin induction and glucose repression. PMID:9371809

Enhanced waterlogging tolerance in barley by manipulation of expression of the N-end rule pathway E3 ligase PROTEOLYSIS6.

PubMed

Mendiondo, Guillermina M; Gibbs, Daniel J; Szurman-Zubrzycka, Miriam; Korn, Arnd; Marquez, Julietta; Szarejko, Iwona; Maluszynski, Miroslaw; King, John; Axcell, Barry; Smart, Katherine; Corbineau, Francoise; Holdsworth, Michael J

2016-01-01

Increased tolerance of crops to low oxygen (hypoxia) during flooding is a key target for food security. In Arabidopsis thaliana (L.) Heynh., the N-end rule pathway of targeted proteolysis controls plant responses to hypoxia by regulating the stability of group VII ethylene response factor (ERFVII) transcription factors, controlled by the oxidation status of amino terminal (Nt)-cysteine (Cys). Here, we show that the barley (Hordeum vulgare L.) ERFVII BERF1 is a substrate of the N-end rule pathway in vitro. Furthermore, we show that Nt-Cys acts as a sensor for hypoxia in vivo, as the stability of the oxygen-sensor reporter protein MCGGAIL-GUS increased in waterlogged transgenic plants. Transgenic RNAi barley plants, with reduced expression of the N-end rule pathway N-recognin E3 ligase PROTEOLYSIS6 (HvPRT6), showed increased expression of hypoxia-associated genes and altered seed germination phenotypes. In addition, in response to waterlogging, transgenic plants showed sustained biomass, enhanced yield, retention of chlorophyll, and enhanced induction of hypoxia-related genes. HvPRT6 RNAi plants also showed reduced chlorophyll degradation in response to continued darkness, often associated with waterlogged conditions. Barley Targeting Induced Local Lesions IN Genomes (TILLING) lines, containing mutant alleles of HvPRT6, also showed increased expression of hypoxia-related genes and phenotypes similar to RNAi lines. We conclude that the N-end rule pathway represents an important target for plant breeding to enhance tolerance to waterlogging in barley and other cereals. © 2015 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

Constraint-based Data Mining

NASA Astrophysics Data System (ADS)

Boulicaut, Jean-Francois; Jeudy, Baptiste

Knowledge Discovery in Databases (KDD) is a complex interactive process. The promising theoretical framework of inductive databases considers this is essentially a querying process. It is enabled by a query language which can deal either with raw data or patterns which hold in the data. Mining patterns turns to be the so-called inductive query evaluation process for which constraint-based Data Mining techniques have to be designed. An inductive query specifies declaratively the desired constraints and algorithms are used to compute the patterns satisfying the constraints in the data. We survey important results of this active research domain. This chapter emphasizes a real breakthrough for hard problems concerning local pattern mining under various constraints and it points out the current directions of research as well.

Advanced high-temperature electromagnetic pump

NASA Technical Reports Server (NTRS)

Gahan, J. W.; Powell, A. H.

1972-01-01

Three phase helical, electromagnetic induction pump for use as boiler feed pump in potassium Rankine-cycle power system is described. Techniques for fabricating components of pump are discussed. Specifications of pump are analyzed.

International Standardization of Library and Documentation Techniques.

ERIC Educational Resources Information Center

International Federation for Documentation, The Hague (Netherlands).

This comparative study of the national and international standards, rules and regulations on library and documentation techniques adopted in various countries was conducted as a preliminary step in determining the minimal bases for facilitating national and international cooperation between documentalists and librarians. The study compares and…

78 FR 34306 - Approval and Promulgation of Air Quality Implementation Plans: North Carolina; Control Techniques...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-06-07

... Promulgation of Air Quality Implementation Plans: North Carolina; Control Techniques Guidelines and Reasonably Available Control Technology AGENCY: Environmental Protection Agency (EPA). ACTION: Proposed rule. SUMMARY... Carolina's commitment associated with the conditional approval of its reasonably available control...

Experience with 100 consecutive simultaneous kidney-pancreas transplants with bladder drainage.

PubMed Central

Sollinger, H W; Knechtle, S J; Reed, A; D'Alessandro, A M; Kalayoglu, M; Belzer, F O; Pirsch, J

1991-01-01

From December 1985 to December 1989, 100 consecutive simultaneous pancreas-kidney (SPK) transplants were performed at the University of Wisconsin Hospital and Clinics. Bladder drainage technique was used for all grafts. One- and three-year patient survival was 93% and 90%; kidney survival, 90% and 85%; and pancreas survival, 86% and 84%. Quadruple immunosuppressive therapy was used in all patients and consisted of either MALG or OKT3 induction, and cyclosporine, prednisone, and azathioprine maintenance therapy. OKT3 induction therapy was used in 42 patients and Minnesota antilymphocyte globule in 58 patients, with equivalent results except for more opportunistic infection with OKT3. The duodenal button technique was used in the first 17 patients with systemic anticoagulation and was associated with significantly more postoperative bleeding and infection compared with the duodenal segment technique. The most common surgical complication of the duodenal segment technique was urine leak (13%), which usually occurred from the distal duodenal segment. The most common urologic complication of bladder drainage was hematuria (13%), which was usually self-limited. Within 6 months of transplantation, 84% of patients developed urinary tract infections, and 25% of patients had opportunistic infections. The surgical techniques and immunosuppressive methods used in this series are reviewed, and strategies for preventing medical and surgical complications are outlined. PMID:1741650

The Use of Electromagnetic Induction Techniques for Soil Mapping

NASA Astrophysics Data System (ADS)

Brevik, Eric C.; Doolittle, Jim

2015-04-01

Soils have high natural spatial variability. This has been recognized for a long time, and many methods of mapping that spatial variability have been investigated. One technique that has received considerable attention over the last ~30 years is electromagnetic induction (EMI). Particularly when coupled with modern GPS and GIS systems, EMI techniques have allowed the rapid and relatively inexpensive collection of large spatially-related data sets that can be correlated to soil properties that either directly or indirectly influence electrical conductance in the soil. Soil electrical conductivity is directly controlled by soil water content, soluble salt content, clay content and mineralogy, and temperature. A wide range of indirect controls have been identified, such as soil organic matter content and bulk density; both influence water relationships in the soil. EMI techniques work best in areas where there are large changes in one soil property that influences soil electrical conductance, and don't work as well when soil properties that influence electrical conductance are largely homogenous. This presentation will present examples of situations where EMI techniques were successful as well as a couple of examples of situations where EMI was not so useful in mapping the spatial variability of soil properties. Reasons for both the successes and failures will be discussed.

Using Optimisation Techniques to Granulise Rough Set Partitions

NASA Astrophysics Data System (ADS)

Crossingham, Bodie; Marwala, Tshilidzi

2007-11-01

This paper presents an approach to optimise rough set partition sizes using various optimisation techniques. Three optimisation techniques are implemented to perform the granularisation process, namely, genetic algorithm (GA), hill climbing (HC) and simulated annealing (SA). These optimisation methods maximise the classification accuracy of the rough sets. The proposed rough set partition method is tested on a set of demographic properties of individuals obtained from the South African antenatal survey. The three techniques are compared in terms of their computational time, accuracy and number of rules produced when applied to the Human Immunodeficiency Virus (HIV) data set. The optimised methods results are compared to a well known non-optimised discretisation method, equal-width-bin partitioning (EWB). The accuracies achieved after optimising the partitions using GA, HC and SA are 66.89%, 65.84% and 65.48% respectively, compared to the accuracy of EWB of 59.86%. In addition to rough sets providing the plausabilities of the estimated HIV status, they also provide the linguistic rules describing how the demographic parameters drive the risk of HIV.

Dynamic spectrum management: an impact on EW systems

NASA Astrophysics Data System (ADS)

Gajewski, P.; Łopatka, J.; Suchanski, M.

2017-04-01

Rapid evolution of wireless systems caused an enormous growth of data streams transmitted through the networks and, as a consequence, an accompanying demand concerning spectrum resources (SR). An avoidance of advisable disturbances is one of the main demands in military communications. To solve the interference problems, dynamic spectrum management (DSM) techniques can be used. Two main techniques are possible: centralized Coordinated Dynamic Spectrum Access (CDSA) and distributed Opportunistic Spectrum Access (OSA). CDSA enables the wireless networks planning automation, and systems dynamic reaction to random changes of Radio Environment (RE). For OSA, cognitive radio (CR) is the most promising technology that enables avoidance of interference with the other spectrum users due to CR's transmission parameters adaptation to the current radio situation, according to predefined Radio Policies rules. If DSM techniques are used, the inherent changes in EW systems are also needed. On one hand, new techniques of jamming should be elaborated, on the other hand, the rules and protocols of cooperation between communication network and EW systems should be developed.

Automated classification of MMPI profiles into psychotic, neurotic or personality disorder types.

PubMed

Hatcher, W E

1978-03-01

A Fortran program has been developed which can objectively classify Minnesota Multiphasic Inventory (MMPI) profiles as being psychotic, neurotic, personality disorder, or indeterminate types. The method used is a set of configural rules, 'Henrichs' rules for males'. The only input data required are K-corrected T scores, which are the end product of standard scoring techniques. To automate these rules it was necessary to rewrite them so that all decisions were the result of arithmetic comparisons or logical tests using only and, or and not. In particular, examination of the Welsh code, which many rules required, had to be stimulated by the use of several sorted arrays. The program has been carefully tested and is in the use in our computer lab.

A hierarchical structure for representing and learning fuzzy rules

NASA Technical Reports Server (NTRS)

Yager, Ronald R.

1993-01-01

Yager provides an example in which the flat representation of fuzzy if-then rules leads to unsatisfactory results. Consider a rule base consisting to two rules: if U is 12 the V is 29; if U is (10-15) the V is (25-30). If U = 12 we would get V is G where G = (25-30). The application of the defuzzification process leads to a selection of V = 27.5. Thus we see that the very specific instruction was not followed. The problem with the technique used is that the most specific information was swamped by the less specific information. In this paper we shall provide for a new structure for the representation of fuzzy if-then rules. The representational form introduced here is called a Hierarchical Prioritized Structure (HPS) representation. Most importantly in addition to overcoming the problem illustrated in the previous example this HPS representation has an inherent capability to emulate the learning of general rules and provides a reasonable accurate cognitive mapping of how human beings store information.

A multilayer perceptron solution to the match phase problem in rule-based artificial intelligence systems

NASA Technical Reports Server (NTRS)

Sartori, Michael A.; Passino, Kevin M.; Antsaklis, Panos J.

1992-01-01

In rule-based AI planning, expert, and learning systems, it is often the case that the left-hand-sides of the rules must be repeatedly compared to the contents of some 'working memory'. The traditional approach to solve such a 'match phase problem' for production systems is to use the Rete Match Algorithm. Here, a new technique using a multilayer perceptron, a particular artificial neural network model, is presented to solve the match phase problem for rule-based AI systems. A syntax for premise formulas (i.e., the left-hand-sides of the rules) is defined, and working memory is specified. From this, it is shown how to construct a multilayer perceptron that finds all of the rules which can be executed for the current situation in working memory. The complexity of the constructed multilayer perceptron is derived in terms of the maximum number of nodes and the required number of layers. A method for reducing the number of layers to at most three is also presented.

Étude comparative des techniques d'analyse par fluorescence X à dispersion d'énergie (ED-XRF) et à dispersion de longueur d'onde (WD-XRF), et par spectrométrie d'émission atomique à source plasma couplée par induction (ICP-AES)

NASA Astrophysics Data System (ADS)

Rahmani, A.; Benyaïch, F.; Bounakhla, M.; Bilal, E.; Moutte, J.; Gruffat, J. J.; Zahry, F.

2004-11-01

Dans ce travail, nous présentons une étude comparative des techniques d'analyse par fluorescence X à dispersion d'énergie (ED-XRF) et à dispersion de longueur d'onde (WD-XRF), et par spectrométrie d'émission atomique à source plasma couplée par induction (ICP-AES). Les résultats de la calibration des spectromètres à dispersion d'énergie, à excitation par sources radioactives (55Fe, 109Cd et 241Am) et à excitation secondaire (cible secondaire Mo et Cu) du Centre National pour l'Energie, les Sciences et les Techniques Nucléaires (CNESTEN, Rabat, Maroc) sur des échantillons étalons de références de l'Agence International de l'Energie Atomique (AIEA) et du Community Bureau of Référence (BCR) ont été comparés aux résultats d'analyse des mêmes échantillons étalons par la spectrométrie X à dispersion de longueur d'onde (WD-XRF) et par spectrométrie d'émission atomique à source plasma couplé par induction (ICP-AES) au département GENERIC du centre SPIN à l'Ecole des Mines de Saint-Etienne (France). Les trois techniques d'analyse utilisées donnent des résultats comparables pour le dosage des éléments majeurs, alors que pour les traces on note des déviations importantes à cause des effets de matrice qui sont difficiles à corriger dans le cas de la fluorescence X.

Automatic and controlled components of judgment and decision making.

PubMed

Ferreira, Mario B; Garcia-Marques, Leonel; Sherman, Steven J; Sherman, Jeffrey W

2006-11-01

The categorization of inductive reasoning into largely automatic processes (heuristic reasoning) and controlled analytical processes (rule-based reasoning) put forward by dual-process approaches of judgment under uncertainty (e.g., K. E. Stanovich & R. F. West, 2000) has been primarily a matter of assumption with a scarcity of direct empirical findings supporting it. The present authors use the process dissociation procedure (L. L. Jacoby, 1991) to provide convergent evidence validating a dual-process perspective to judgment under uncertainty based on the independent contributions of heuristic and rule-based reasoning. Process dissociations based on experimental manipulation of variables were derived from the most relevant theoretical properties typically used to contrast the two forms of reasoning. These include processing goals (Experiment 1), cognitive resources (Experiment 2), priming (Experiment 3), and formal training (Experiment 4); the results consistently support the author's perspective. They conclude that judgment under uncertainty is neither an automatic nor a controlled process but that it reflects both processes, with each making independent contributions.

The scaling behavior of hand motions reveals self-organization during an executive function task

NASA Astrophysics Data System (ADS)

Anastas, Jason R.; Stephen, Damian G.; Dixon, James A.

2011-05-01

Recent approaches to cognition explain cognitive phenomena in terms of interaction-dominant dynamics. In the current experiment, we extend this approach to executive function, a construct used to describe flexible, goal-oriented behavior. Participants were asked to perform a widely used executive function task, card sorting, under two conditions. In one condition, participants were given a rule with which to sort the cards. In the other condition, participants had to induce the rule from experimenter feedback. The motion of each participant’s hand was tracked during the sorting task. Detrended fluctuation analysis was performed on the inter-point time series using a windowing strategy to capture changes over each trial. For participants in the induction condition, the Hurst exponent sharply increased and then decreased. The Hurst exponents for the explicit condition did not show this pattern. Our results suggest that executive function may be understood in terms of changes in stability that arise from interaction-dominant dynamics.

Raft cultivation area extraction from high resolution remote sensing imagery by fusing multi-scale region-line primitive association features

NASA Astrophysics Data System (ADS)

Wang, Min; Cui, Qi; Wang, Jie; Ming, Dongping; Lv, Guonian

2017-01-01

In this paper, we first propose several novel concepts for object-based image analysis, which include line-based shape regularity, line density, and scale-based best feature value (SBV), based on the region-line primitive association framework (RLPAF). We then propose a raft cultivation area (RCA) extraction method for high spatial resolution (HSR) remote sensing imagery based on multi-scale feature fusion and spatial rule induction. The proposed method includes the following steps: (1) Multi-scale region primitives (segments) are obtained by image segmentation method HBC-SEG, and line primitives (straight lines) are obtained by phase-based line detection method. (2) Association relationships between regions and lines are built based on RLPAF, and then multi-scale RLPAF features are extracted and SBVs are selected. (3) Several spatial rules are designed to extract RCAs within sea waters after land and water separation. Experiments show that the proposed method can successfully extract different-shaped RCAs from HR images with good performance.

Identification of first-stage labor arrest by electromyography in term nulliparous women after induction of labor.

PubMed

Vasak, Blanka; Graatsma, Elisabeth M; Hekman-Drost, Elske; Eijkemans, Marinus J; Schagen van Leeuwen, Jules H; Visser, Gerard H A; Jacod, Benoit C

2017-07-01

Worldwide induction and cesarean delivery rates have increased rapidly, with consequences for subsequent pregnancies. The majority of intrapartum cesarean deliveries are performed for failure to progress, typically in nulliparous women at term. Current uterine registration techniques fail to identify inefficient contractions leading to first-stage labor arrest. An alternative technique, uterine electromyography has been shown to identify inefficient contractions leading to first-stage arrest of labor in nulliparous women with spontaneous onset of labor at term. The objective of this study was to determine whether this finding can be reproduced in induction of labor. Uterine activity was measured in 141 nulliparous women with singleton term pregnancies and a fetus in cephalic position during induced labor. Electrical activity of the myometrium during contractions was characterized by its power density spectrum. No significant differences were found in contraction characteristics between women with induced labor delivering vaginally with or without oxytocin and women with arrested labor with subsequent cesarean delivery. Uterine electromyography shows no correlation with progression of labor in induced labor, which is in contrast to spontaneous labor. © 2017 Nordic Federation of Societies of Obstetrics and Gynecology.

New Technique of AC drive in Tokamak using Permanent Magnets

NASA Astrophysics Data System (ADS)

Matteucci, Jackson; Zolfaghari, Ali

2013-10-01

This study investigates a new technique of capturing the rotational energy of alternating permanent magnets in order to inductively drive an alternating current in tokamak devices. The use of rotational motion bypasses many of the pitfalls seen in typical inductive and non-inductive current drives. Three specific designs are presented and assessed in the following criteria: the profile of the current generated, the RMS loop voltage generated as compared to the RMS power required to maintain it, the system's feasibility from an engineering perspective. All of the analysis has been done under ideal E&M conditions using the Maxwell 3D program. Preliminary results indicate that it is possible to produce an over 99% purely toroidal current with a RMS d Φ/dt of over 150 Tm2/s, driven by 20 MW or less of rotational power. The proposed mechanism demonstrates several key advantages including an efficient mechanical drive system, the generation of pure toroidal currents, and the potential for a quasi-steady state fusion reactor. The following quantities are presented for various driving frequencies and magnet strengths: plasma current generated, loop voltage, torque and power required. This project has been supported by DOE Funding under the SULI program.

Plasma Source Development for LAPD

NASA Astrophysics Data System (ADS)

Pribyl, P.; Gekelman, W.; Drandell, M.; Grunspen, S.; Nakamoto, M.; McBarron, A.

2003-10-01

The Large Plasma Device (LAPD) relies on an indirectly heated Barium Oxide (BaO) cathode to generate an extremely repeatable low-noise plasma. However there are two defects of this system: one is that the cathode is subject to oxygen poisoning in the event of accidental air leaks, requiring a lengthy recoating and regeneration process. Second, the indirect radiative heating is only about 50 % efficient, leading to a series of reliability issues. Alternate plasma sources are being investigated, including two types of directly heated BaO cathode and several configurations of inductively coupled RF plasmas. Direct heating for a cathode can be achieved either by embedding heaters within the nickel substrate, or by using inductive heating techniques to drive currents within the nickel itself. In both cases, the BaO coating still serves to emit the electrons and thus generate the plasma arc. An improved system would generate the plasma without the use of a "cathode" e.g. by inductively coupling energy directly into the plasma discharge. This technique is being investigated from the point of view of whether a) the bulk of the plasma column can be made sufficiently low-noise to be of experimental value and b) sufficiently dense plasmas can be formed.

Green and Fast Laser Fusion Technique for Bulk Silicate Rock Analysis by Laser Ablation-Inductively Coupled Plasma Mass Spectrometry.

PubMed

Zhang, Chenxi; Hu, Zhaochu; Zhang, Wen; Liu, Yongsheng; Zong, Keqing; Li, Ming; Chen, Haihong; Hu, Shenghong

2016-10-18

Sample preparation of whole-rock powders is the major limitation for their accurate and precise elemental analysis by laser ablation inductively-coupled plasma mass spectrometry (ICPMS). In this study, a green, efficient, and simplified fusion technique using a high energy infrared laser was developed for major and trace elemental analysis. Fusion takes only tens of milliseconds for each sample. Compared to the pressed pellet sample preparation, the analytical precision of the developed laser fusion technique is higher by an order of magnitude for most elements in granodiorite GSP-2. Analytical results obtained for five USGS reference materials (ranging from mafic to intermediate to felsic) using the laser fusion technique generally agree with recommended values with discrepancies of less than 10% for most elements. However, high losses (20-70%) of highly volatile elements (Zn and Pb) and the transition metal Cu are observed. The achieved precision is within 5% for major elements and within 15% for most trace elements. Direct laser fusion of rock powders is a green and notably simple method to obtain homogeneous samples, which will significantly accelerate the application of laser ablation ICPMS for whole-rock sample analysis.

Evidence flow graph methods for validation and verification of expert systems

NASA Technical Reports Server (NTRS)

Becker, Lee A.; Green, Peter G.; Bhatnagar, Jayant

1989-01-01

The results of an investigation into the use of evidence flow graph techniques for performing validation and verification of expert systems are given. A translator to convert horn-clause rule bases into evidence flow graphs, a simulation program, and methods of analysis were developed. These tools were then applied to a simple rule base which contained errors. It was found that the method was capable of identifying a variety of problems, for example that the order of presentation of input data or small changes in critical parameters could affect the output from a set of rules.

The Comparison of Fourth Grade Students' Essays Based on Free and Guided Writing Technique in Terms of the Quality of Written Expression

ERIC Educational Resources Information Center

Calp, Mehrali

2015-01-01

Writing exercises are more effective than grammar rules in terms of making children acquire language skills. Knowing the characteristics of text genres and the rules of writing are not enough to improve writing skills of teacher candidates and to acquire necessary strategies for teaching how to write. Teachers would be uncertain about assessment…

Design issues for a reinforcement-based self-learning fuzzy controller

NASA Technical Reports Server (NTRS)

Yen, John; Wang, Haojin; Dauherity, Walter

1993-01-01

Fuzzy logic controllers have some often cited advantages over conventional techniques such as PID control: easy implementation, its accommodation to natural language, the ability to cover wider range of operating conditions and others. One major obstacle that hinders its broader application is the lack of a systematic way to develop and modify its rules and as result the creation and modification of fuzzy rules often depends on try-error or pure experimentation. One of the proposed approaches to address this issue is self-learning fuzzy logic controllers (SFLC) that use reinforcement learning techniques to learn the desirability of states and to adjust the consequent part of fuzzy control rules accordingly. Due to the different dynamics of the controlled processes, the performance of self-learning fuzzy controller is highly contingent on the design. The design issue has not received sufficient attention. The issues related to the design of a SFLC for the application to chemical process are discussed and its performance is compared with that of PID and self-tuning fuzzy logic controller.

Towards a Framework for Change Detection in Data Sets

NASA Astrophysics Data System (ADS)

Böttcher, Mirko; Nauck, Detlef; Ruta, Dymitr; Spott, Martin

Since the world with its markets, innovations and customers is changing faster than ever before, the key to survival for businesses is the ability to detect, assess and respond to changing conditions rapidly and intelligently. Discovering changes and reacting to or acting upon them before others do has therefore become a strategical issue for many companies. However, existing data analysis techniques are insufflent for this task since they typically assume that the domain under consideration is stable over time. This paper presents a framework that detects changes within a data set at virtually any level of granularity. The underlying idea is to derive a rule-based description of the data set at different points in time and to subsequently analyse how these rules change. Nevertheless, further techniques are required to assist the data analyst in interpreting and assessing their changes. Therefore the framework also contains methods to discard rules that are non-drivers for change and to assess the interestingness of detected changes.

A hybrid learning method for constructing compact rule-based fuzzy models.

PubMed

Zhao, Wanqing; Niu, Qun; Li, Kang; Irwin, George W

2013-12-01

The Takagi–Sugeno–Kang-type rule-based fuzzy model has found many applications in different fields; a major challenge is, however, to build a compact model with optimized model parameters which leads to satisfactory model performance. To produce a compact model, most existing approaches mainly focus on selecting an appropriate number of fuzzy rules. In contrast, this paper considers not only the selection of fuzzy rules but also the structure of each rule premise and consequent, leading to the development of a novel compact rule-based fuzzy model. Here, each fuzzy rule is associated with two sets of input attributes, in which the first is used for constructing the rule premise and the other is employed in the rule consequent. A new hybrid learning method combining the modified harmony search method with a fast recursive algorithm is hereby proposed to determine the structure and the parameters for the rule premises and consequents. This is a hard mixed-integer nonlinear optimization problem, and the proposed hybrid method solves the problem by employing an embedded framework, leading to a significantly reduced number of model parameters and a small number of fuzzy rules with each being as simple as possible. Results from three examples are presented to demonstrate the compactness (in terms of the number of model parameters and the number of rules) and the performance of the fuzzy models obtained by the proposed hybrid learning method, in comparison with other techniques from the literature.

Herbert Hoover and William Shakespeare: Two Writers on Ethics.

ERIC Educational Resources Information Center

Somers, Margaret L.

1979-01-01

Outlines the ways in which Herbert Hoover and William Shakespeare wrote about professional ethics (for engineers and kings, respectively) using the writing techniques of concreteness, audience awareness, and development by induction. (TJ)

Promoter Sequences Prediction Using Relational Association Rule Mining

PubMed Central

Czibula, Gabriela; Bocicor, Maria-Iuliana; Czibula, Istvan Gergely

2012-01-01

In this paper we are approaching, from a computational perspective, the problem of promoter sequences prediction, an important problem within the field of bioinformatics. As the conditions for a DNA sequence to function as a promoter are not known, machine learning based classification models are still developed to approach the problem of promoter identification in the DNA. We are proposing a classification model based on relational association rules mining. Relational association rules are a particular type of association rules and describe numerical orderings between attributes that commonly occur over a data set. Our classifier is based on the discovery of relational association rules for predicting if a DNA sequence contains or not a promoter region. An experimental evaluation of the proposed model and comparison with similar existing approaches is provided. The obtained results show that our classifier overperforms the existing techniques for identifying promoter sequences, confirming the potential of our proposal. PMID:22563233

Determining anisotropic conductivity using diffusion tensor imaging data in magneto-acoustic tomography with magnetic induction

NASA Astrophysics Data System (ADS)

Ammari, Habib; Qiu, Lingyun; Santosa, Fadil; Zhang, Wenlong

2017-12-01

In this paper we present a mathematical and numerical framework for a procedure of imaging anisotropic electrical conductivity tensor by integrating magneto-acoutic tomography with data acquired from diffusion tensor imaging. Magneto-acoustic tomography with magnetic induction (MAT-MI) is a hybrid, non-invasive medical imaging technique to produce conductivity images with improved spatial resolution and accuracy. Diffusion tensor imaging (DTI) is also a non-invasive technique for characterizing the diffusion properties of water molecules in tissues. We propose a model for anisotropic conductivity in which the conductivity is proportional to the diffusion tensor. Under this assumption, we propose an optimal control approach for reconstructing the anisotropic electrical conductivity tensor. We prove convergence and Lipschitz type stability of the algorithm and present numerical examples to illustrate its accuracy and feasibility.

Adaptive Control for Buck Power Converter Using Fixed Point Inducting Control and Zero Average Dynamics Strategies

NASA Astrophysics Data System (ADS)

Hoyos Velasco, Fredy Edimer; García, Nicolás Toro; Garcés Gómez, Yeison Alberto

In this paper, the output voltage of a buck power converter is controlled by means of a quasi-sliding scheme. The Fixed Point Inducting Control (FPIC) technique is used for the control design, based on the Zero Average Dynamics (ZAD) strategy, including load estimation by means of the Least Mean Squares (LMS) method. The control scheme is tested in a Rapid Control Prototyping (RCP) system based on Digital Signal Processing (DSP) for dSPACE platform. The closed loop system shows adequate performance. The experimental and simulation results match. The main contribution of this paper is to introduce the load estimator by means of LMS, to make ZAD and FPIC control feasible in load variation conditions. In addition, comparison results for controlled buck converter with SMC, PID and ZAD-FPIC control techniques are shown.

A technique for solving constraint satisfaction problems using Prolog's definite clause grammars

NASA Technical Reports Server (NTRS)

Nachtsheim, Philip R.

1988-01-01

A new technique for solving constraint satisfaction problems using Prolog's definite clause grammars is presented. It exploits the fact that the grammar rule notation can be viewed as a state exchange notation. The novel feature of the technique is that it can perform informed as well as blind search. It provides the Prolog programmer with a new technique for application to a wide range of design, scheduling, and planning problems.

76 FR 52917 - Approval and Promulgation of Air Quality Implementation Plans; Pennsylvania; Adoption of Control...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-08-24

... Large Appliance and Metal Furniture Coatings AGENCY: Environmental Protection Agency (EPA). ACTION... Techniques Guidelines (CTG) standards for large appliance and metal furniture coatings. In the Final Rules...; Pennsylvania; Adoption of Control Techniques Guidelines for Large Appliance and Metal Furniture Coatings...

75 FR 59179 - Approval and Promulgation of Air Quality Implementation Plans; Maryland; Adoption of Control...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-09-27

... (RACT) for sources covered by EPA's Control Techniques Guidelines (CTG) for flexible packaging printing... Promulgation of Air Quality Implementation Plans; Maryland; Adoption of Control Techniques Guidelines for Flexible Packaging Printing AGENCY: Environmental Protection Agency (EPA). ACTION: Proposed rule. SUMMARY...

Use of labour induction and risk of cesarean delivery: a systematic review and meta-analysis

PubMed Central

Mishanina, Ekaterina; Rogozinska, Ewelina; Thatthi, Tej; Uddin-Khan, Rehan; Khan, Khalid S.; Meads, Catherine

2014-01-01

Background: Induction of labour is common, and cesarean delivery is regarded as its major complication. We conducted a systematic review and meta-analysis to investigate whether the risk of cesarean delivery is higher or lower following labour induction compared with expectant management. Methods: We searched 6 electronic databases for relevant articles published through April 2012 to identify randomized controlled trials (RCTs) in which labour induction was compared with placebo or expectant management among women with a viable singleton pregnancy. We assessed risk of bias and obtained data on rates of cesarean delivery. We used regression analysis techniques to explore the effect of patient characteristics, induction methods and study quality on risk of cesarean delivery. Results: We identified 157 eligible RCTs (n = 31 085). Overall, the risk of cesarean delivery was 12% lower with labour induction than with expectant management (pooled relative risk [RR] 0.88, 95% confidence interval [CI] 0.84–0.93; I2 = 0%). The effect was significant in term and post-term gestations but not in preterm gestations. Meta-regression analysis showed that initial cervical score, indication for induction and method of induction did not alter the main result. There was a reduced risk of fetal death (RR 0.50, 95% CI 0.25–0.99; I2 = 0%) and admission to a neonatal intensive care unit (RR 0.86, 95% CI 0.79–0.94), and no impact on maternal death (RR 1.00, 95% CI 0.10–9.57; I2 = 0%) with labour induction. Interpretation: The risk of cesarean delivery was lower among women whose labour was induced than among those managed expectantly in term and post-term gestations. There were benefits for the fetus and no increased risk of maternal death. PMID:24778358

Effect of casting atmosphere on the marginal deficiency and misfit of Ni-Cr alloys with and without beryllium.

PubMed

da Silva, Leandro J; Leal, Monica B; Valente, Mariana L C; de Castro, Denise T; Pagnano, Valéria O; Dos Reis, Andréa C; Bezzon, Osvaldo L

2017-07-01

The marginal adaptation of prosthetic crowns is still a significant clinical problem. The purpose of this in vitro study was to evaluate the marginal deficiency and misfit of Ni-Cr alloys with and without beryllium under different casting conditions. Four casting conditions were selected: flame-torch, induction/argon, induction/vacuum, and induction/air; and 2 alloys were used, Ni-Cr-Be and Ni-Cr. For each group, 10 metal specimens were prepared. Silicone indirect impressions and analysis of the degree of rounding were used to evaluate the marginal deficiencies of metal copings, and a standardized device for the setting pressure associated with optical microscopy was used to analyze the marginal misfit. Results were evaluated with 2-way ANOVA (α=.05), followed by the Tukey honest significant difference post hoc test, and the Pearson correlation test (α=.05). Alloy (P<.001) and casting technique (P<.001) were shown to affect marginal deficiencies. The Ni-Cr cast using the torch technique showed the highest marginal deficiency, and the Ni-Cr-Be cast in a controlled argon atmosphere showed the lowest (P<.001). Alloy (P=.472) and casting techniques (P=.206) did not affect the marginal misfit, but significant differences were found in the interaction (P=.001); the lowest misfit was achieved using the Ni-Cr-Be, and the highest misfit occurred with the molten Ni-Cr, using the cast torch technique. No correlation was found between deficiency and marginal misfit (r=.04, P=.69). The interactions demonstrated that the alloy containing beryllium that was cast in an argon atmosphere led to reduced marginal deficiency. Improved marginal adaptation can be achieved for the same alloy by using the torch technique. Copyright © 2016 Editorial Council for the Journal of Prosthetic Dentistry. Published by Elsevier Inc. All rights reserved.

Streamed video clips to reduce anxiety in children during inhaled induction of anesthesia.

PubMed

Mifflin, Katherine A; Hackmann, Thomas; Chorney, Jill Maclaren

2012-11-01

Anesthesia induction in children is frequently achieved by inhalation of nitrous oxide and sevoflurane. Pediatric anesthesiologists commonly use distraction techniques such as humor or nonprocedural talk to reduce anxiety and facilitate a smooth transition at this critical phase. There is a large body of successful distraction research that explores the use of video and television distraction methods for minor medical and dental procedures, but little research on the use of this method for ambulatory surgery. In this randomized control trial study we examined whether video distraction is effective in reducing the anxiety of children undergoing inhaled induction before ambulatory surgery. Children (control = 47, video = 42) between 2 and 10 years old undergoing ambulatory surgery were randomly assigned to a video distraction or control group. In the video distraction group a video clip of the child's preference was played during induction, and the control group received traditional distraction methods during induction. The modified Yale Preoperative Anxiety Scale was used to assess the children's anxiety before and during the process of receiving inhalation anesthetics. All subjects were similar in their age and anxiety scores before entering the operating rooms. Children in the video distraction group were significantly less anxious at induction and showed a significantly smaller change in anxiety from holding to induction than did children in the control group. Playing video clips during the inhaled induction of children undergoing ambulatory surgery is an effective method of reducing anxiety. Therefore, pediatric anesthesiologists may consider using video distraction as a useful, valid, alternative strategy for achieving a smooth transition to the anesthetized state.

Classified one-step high-radix signed-digit arithmetic units

NASA Astrophysics Data System (ADS)

Cherri, Abdallah K.

1998-08-01

High-radix number systems enable higher information storage density, less complexity, fewer system components, and fewer cascaded gates and operations. A simple one-step fully parallel high-radix signed-digit arithmetic is proposed for parallel optical computing based on new joint spatial encodings. This reduces hardware requirements and improves throughput by reducing the space-bandwidth produce needed. The high-radix signed-digit arithmetic operations are based on classifying the neighboring input digit pairs into various groups to reduce the computation rules. A new joint spatial encoding technique is developed to present both the operands and the computation rules. This technique increases the spatial bandwidth product of the spatial light modulators of the system. An optical implementation of the proposed high-radix signed-digit arithmetic operations is also presented. It is shown that our one-step trinary signed-digit and quaternary signed-digit arithmetic units are much simpler and better than all previously reported high-radix signed-digit techniques.

Effect of electric arc, gas oxygen torch and induction melting techniques on the marginal accuracy of cast base-metal and noble metal-ceramic crowns.

PubMed

Gómez-Cogolludo, Pablo; Castillo-Oyagüe, Raquel; Lynch, Christopher D; Suárez-García, María-Jesús

2013-09-01

The aim of this study was to identify the most appropriate alloy composition and melting technique by evaluating the marginal accuracy of cast metal-ceramic crowns. Seventy standardised stainless-steel abutments were prepared to receive metal-ceramic crowns and were randomly divided into four alloy groups: Group 1: palladium-gold (Pd-Au), Group 2: nickel-chromium-titanium (Ni-Cr-Ti), Group 3: nickel-chromium (Ni-Cr) and Group 4: titanium (Ti). Groups 1, 2 and 3 were in turn subdivided to be melted and cast using: (a) gas oxygen torch and centrifugal casting machine (TC) or (b) induction and centrifugal casting machine (IC). Group 4 was melted and cast using electric arc and vacuum/pressure machine (EV). All of the metal-ceramic crowns were luted with glass-ionomer cement. The marginal fit was measured under an optical microscope before and after cementation using image analysis software. All data was subjected to two-way analysis of variance (ANOVA). Duncan's multiple range test was run for post-hoc comparisons. The Student's t-test was used to investigate the influence of cementation (α=0.05). Uncemented Pd-Au/TC samples achieved the best marginal adaptation, while the worst fit corresponded to the luted Ti/EV crowns. Pd-Au/TC, Ni-Cr and Ti restorations demonstrated significantly increased misfit after cementation. The Ni-Cr-Ti alloy was the most predictable in terms of differences in misfit when either torch or induction was applied before or after cementation. Cemented titanium crowns exceeded the clinically acceptable limit of 120μm. The combination of alloy composition, melting technique, casting method and luting process influences the vertical seal of cast metal-ceramic crowns. An accurate use of the gas oxygen torch may overcome the results attained with the induction system concerning the marginal adaptation of fixed dental prostheses. Copyright © 2013 Elsevier Ltd. All rights reserved.

Integrating surface and borehole geophysics in ground water studies - an example using electromagnetic soundings in south Florida

USGS Publications Warehouse

Paillet, Frederick; Hite, Laura; Carlson, Matthew

1999-01-01

Time domain surface electromagnetic soundings, borehole induction logs, and other borehole logging techniques are used to construct a realistic model for the shallow subsurface hydraulic properties of unconsolidated sediments in south Florida. Induction logs are used to calibrate surface induction soundings in units of pore water salinity by correlating water sample specific electrical conductivity with the electrical conductivity of the formation over the sampled interval for a two‐layered aquifer model. Geophysical logs are also used to show that a constant conductivity layer model is appropriate for the south Florida study. Several physically independent log measurements are used to quantify the dependence of formation electrical conductivity on such parameters as salinity, permeability, and clay mineral fraction. The combined interpretation of electromagnetic soundings and induction logs was verified by logging three validation boreholes, confirming quantitative estimates of formation conductivity and thickness in the upper model layer, and qualitative estimates of conductivity in the lower model layer.

The role of accessory cells in polyclonal T cell activation. I. Both induction of interleukin 2 production and of interleukin 2 responsiveness by concanavalin A are accessory cell dependent.

PubMed

Hünig, T; Loos, M; Schimpl, A

1983-01-01

Recent studies from other laboratories have shown that concanavalin A (Con A) acts at two separate steps in polyclonal T cell activation: interleukin 2 (IL2) production, and induction of responsiveness to IL2. Using a combination of techniques for the depletion of accessory cells from lymph node T cells, we have investigated which of these steps, if not both, is responsible for the known requirement for accessory cells in the Con A response. It was found that with increasing T cell purification, first the ability is lost to produce sufficient levels of endogenous IL2, whereas induction of IL2 responsiveness can still take place. Further removal of accessory cells however yields a population of resting T cells that cannot be induced by Con A to become IL2-reactive. It was concluded that both IL2 production and induction of reactivity to IL2 are accessory cell-dependent events.

Design and test of a simple fast electromagnetic inductive gas valve for planar pulsed inductive plasma thruster

NASA Astrophysics Data System (ADS)

Guo, Dawei; Cheng, Mousen; Li, Xiaokang

2017-10-01

In support of our planar pulsed inductive plasma thruster research, a fast electromagnetic inductive valve for a gas propellant injection system has been built and tested. A new and important design feature is the use of a conical diaphragm as the action part, which greatly contributes to the virtue of simplicity for adopting the resultant force of the diaphragm deformation as the closing force. An optical transmission technique is adopted to measure the opening and closing characters of the valve while the gas throughput is determined by measuring the pressure change per pulse in a test chamber with a capacitance manometer. The experimental results revealed that the delay time before the valve reaction is less than 40 μs, and the valve pulse width is no longer than 160 μs full width at half maximum. The valve delivers 0-2.5 mg of argon gas per pulse varied by adjusting the drive voltage and gas pressure.

Design and test of a simple fast electromagnetic inductive gas valve for planar pulsed inductive plasma thruster.

PubMed

Guo, Dawei; Cheng, Mousen; Li, Xiaokang

2017-10-01

In support of our planar pulsed inductive plasma thruster research, a fast electromagnetic inductive valve for a gas propellant injection system has been built and tested. A new and important design feature is the use of a conical diaphragm as the action part, which greatly contributes to the virtue of simplicity for adopting the resultant force of the diaphragm deformation as the closing force. An optical transmission technique is adopted to measure the opening and closing characters of the valve while the gas throughput is determined by measuring the pressure change per pulse in a test chamber with a capacitance manometer. The experimental results revealed that the delay time before the valve reaction is less than 40 μs, and the valve pulse width is no longer than 160 μs full width at half maximum. The valve delivers 0-2.5 mg of argon gas per pulse varied by adjusting the drive voltage and gas pressure.

Frequency domain electromagnetic induction survey in the intertidal zone: Limitations of low-induction-number and depth of exploration

NASA Astrophysics Data System (ADS)

Delefortrie, Samuël; Saey, Timothy; Van De Vijver, Ellen; De Smedt, Philippe; Missiaen, Tine; Demerre, Ine; Van Meirvenne, Marc

2014-01-01

Subsurface investigation in the Belgian intertidal zone is severely complicated due to high heterogeneity and tides. Near-surface geophysical techniques can offer assistance since they allow fast surveying and collection of high spatial density data and frequency domain electromagnetic induction (EMI) was chosen for archaeological prospection on the Belgian shore. However, in the intertidal zone the effects of extreme salinity compromise validity of low-induction-number (LIN) approximated EMI data. In this paper, the effects of incursion of seawater on multi-receiver EMI data are investigated by means of survey results, field observations, cone penetration tests and in-situ electrical conductivity measurements. The consequences of LIN approximation breakdown were researched. Reduced depth of investigation of the quadrature-phase (Qu) response and a complex interpretation of the in-phase response were confirmed. Nonetheless, a high signal-to-noise ratio of the Qu response and viable data with regard to shallow subsurface investigation were also evidenced, allowing subsurface investigation in the intertidal zone.

Comparison of three rf plasma impedance monitors on a high phase angle planar inductively coupled plasma source

NASA Astrophysics Data System (ADS)

Uchiyama, H.; Watanabe, M.; Shaw, D. M.; Bahia, J. E.; Collins, G. J.

1999-10-01

Accurate measurement of plasma source impedance is important for verification of plasma circuit models, as well as for plasma process characterization and endpoint detection. Most impedance measurement techniques depend in some manner on the cosine of the phase angle to determine the impedance of the plasma load. Inductively coupled plasmas are generally highly inductive, with the phase angle between the applied rf voltage and the rf current in the range of 88 to near 90 degrees. A small measurement error in this phase angle range results in a large error in the calculated cosine of the angle, introducing large impedance measurement variations. In this work, we have compared the measured impedance of a planar inductively coupled plasma using three commercial plasma impedance monitors (ENI V/I probe, Advanced Energy RFZ60 and Advanced Energy Z-Scan). The plasma impedance is independently verified using a specially designed match network and a calibrated load, representing the plasma, to provide a measurement standard.

Gimme that old time religion: the influence of the healthcare belief system of chiropractic's early leaders on the development of x-ray imaging in the profession.

PubMed

Young, Kenneth John

2014-01-01

Chiropractic technique systems have been historically documented to advocate overutilization of radiography. Various rationales for this have been explored in the literature. However, little consideration has been given to the possibility that the healthcare belief system of prominent early chiropractors may have influenced the use of the diagnostic modality through the years. The original rationale was the visualisation of chiropractic subluxations, defined as bones slightly out of place, pressing on nerves, and ultimately causing disease. This paradigm of radiography has survived in parts of the chiropractic profession, despite lacking evidence of clinical validity. The purpose of this paper is to compare the characteristics of the chiropractic technique systems that have utilised radiography for subluxation detection with the characteristics of religion, and to discover potential historical links that may have facilitated the development of those characteristics. Twenty-three currently or previously existing technique systems requiring radiography for subluxation analysis were found using a search of the internet, books and consultation with experts. Evidence of religiosity from the early founders' writings was compared with textbooks, published papers, and websites of subsequently developed systems. Six criteria denoting religious thinking were developed using definitions from various sources. They are: supernatural concepts, claims of supremacy, rules and rituals, sacred artefacts, sacred stories, and special language. All of these were found to a greater or lesser degree in the publicly available documents of all the subluxation-based chiropractic x-ray systems. The founders and early pioneers of chiropractic did not benefit from the current understanding of science and research, and therefore substituted deductive and inductive reasoning to arrive at conclusions about health and disease in the human body. Some of this thinking and rationalisation demonstrably followed a religion-like pattern, including BJ Palmer's use of radiography. Although access to scientific methods and research education became much advanced and more accessible during the past few decades, the publicly available documents of technique systems that used radiography for chiropractic subluxation detection examined in this paper employed a historically derived paradigm for radiography that displayed characteristics in common with religion.

Aspects of rf-heating and gas-phase doping of large scale silicon crystals grown by the Float Zone technique

NASA Astrophysics Data System (ADS)

Zobel, F.; Mosel, F.; Sørensen, J.; Dold, P.

2018-05-01

Float Zone growth of silicon crystals is known as the method for providing excellent material properties. Basic principle of this technique is the radiofrequency induction heating, main aspects of this method will be discussed in this article. In contrast to other methods, one of the advantages of the Float Zone technique is the possibility for in-situ doping via gas phase. Experimental results on this topic will be shown and discussed.

Developments in ICP-MS: electrochemically modulated liquid chromatography for the clean-up of ICP-MS blanks and reduction of matrix effects by flow injection ICP-MS

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

Gross, Cory Thomas

2008-01-01

The focus of this dissertation is the development of techniques with which to enhance the existing abilities of inductively coupled plasma mass spectrometry (ICP-MS). ICP-MS is a powerful technique for trace metal analysis in samples of many types, but like any technique it has certain strengths and weaknesses. Attempts are made to improve upon those strengths and to overcome certain weaknesses.

Elastography methods for the non-invasive assessment of portal hypertension.

PubMed

Roccarina, Davide; Rosselli, Matteo; Genesca, Joan; Tsochatzis, Emmanuel A

2018-02-01

The gold standard to assess the presence and severity of portal hypertension remains the hepatic vein pressure gradient, however the recent development of non-invasive assessment using elastography techniques offers valuable alternatives. In this review, we discuss the diagnostic accuracy and utility of such techniques in patients with portal hypertension due to cirrhosis. Areas covered: A literature search focused on liver and spleen stiffness measurement with different elastographic techniques for the assessment of the presence and severity of portal hypertension and oesophageal varices in people with chronic liver disease. The combination of elastography with parameters such as platelet count and spleen size is also discussed. Expert commentary: Non-invasive assessment of liver fibrosis and portal hypertension is a validated tool for the diagnosis and follow-up of patients. Baveno VI recommended the combination of transient elastography and platelet count for ruling out varices needing treatment in patients with compensated advanced chronic liver disease. Assessment of aetiology specific cut-offs for ruling in and ruling out clinically significant portal hypertension is an unmet clinical need. The incorporation of spleen stiffness measurements in non-invasive algorithms using validated software and improved measuring scales might enhance the non-invasive diagnosis of portal hypertension in the next 5 years.

Robert's Rules for Optimal Learning: Model Development, Field Testing, Implications!

ERIC Educational Resources Information Center

McGinty, Robert L.

The value of accelerated learning techniques developed by the national organization for Suggestive Accelerated Learning Techniques (SALT) was tested in a study using Administrative Policy students taking the capstone course in the Eastern Washington University School of Business. Educators have linked the brain and how it functions to various…

39 CFR 3050.1 - Definitions applicable to this part.

Code of Federal Regulations, 2012 CFR

2012-07-01

... was applied by the Commission in its most recent Annual Compliance Determination unless a different analytical principle subsequently was accepted by the Commission in a final rule. (b) Accepted quantification technique refers to a quantification technique that was applied in the most recent iteration of the periodic...

39 CFR 3050.1 - Definitions applicable to this part.

Code of Federal Regulations, 2014 CFR

2014-07-01

... was applied by the Commission in its most recent Annual Compliance Determination unless a different analytical principle subsequently was accepted by the Commission in a final rule. (b) Accepted quantification technique refers to a quantification technique that was applied in the most recent iteration of the periodic...

A multiple kernel support vector machine scheme for feature selection and rule extraction from gene expression data of cancer tissue.

PubMed

Chen, Zhenyu; Li, Jianping; Wei, Liwei

2007-10-01

Recently, gene expression profiling using microarray techniques has been shown as a promising tool to improve the diagnosis and treatment of cancer. Gene expression data contain high level of noise and the overwhelming number of genes relative to the number of available samples. It brings out a great challenge for machine learning and statistic techniques. Support vector machine (SVM) has been successfully used to classify gene expression data of cancer tissue. In the medical field, it is crucial to deliver the user a transparent decision process. How to explain the computed solutions and present the extracted knowledge becomes a main obstacle for SVM. A multiple kernel support vector machine (MK-SVM) scheme, consisting of feature selection, rule extraction and prediction modeling is proposed to improve the explanation capacity of SVM. In this scheme, we show that the feature selection problem can be translated into an ordinary multiple parameters learning problem. And a shrinkage approach: 1-norm based linear programming is proposed to obtain the sparse parameters and the corresponding selected features. We propose a novel rule extraction approach using the information provided by the separating hyperplane and support vectors to improve the generalization capacity and comprehensibility of rules and reduce the computational complexity. Two public gene expression datasets: leukemia dataset and colon tumor dataset are used to demonstrate the performance of this approach. Using the small number of selected genes, MK-SVM achieves encouraging classification accuracy: more than 90% for both two datasets. Moreover, very simple rules with linguist labels are extracted. The rule sets have high diagnostic power because of their good classification performance.

Knowledge discovery from structured mammography reports using inductive logic programming.

PubMed

Burnside, Elizabeth S; Davis, Jesse; Costa, Victor Santos; Dutra, Inês de Castro; Kahn, Charles E; Fine, Jason; Page, David

2005-01-01

The development of large mammography databases provides an opportunity for knowledge discovery and data mining techniques to recognize patterns not previously appreciated. Using a database from a breast imaging practice containing patient risk factors, imaging findings, and biopsy results, we tested whether inductive logic programming (ILP) could discover interesting hypotheses that could subsequently be tested and validated. The ILP algorithm discovered two hypotheses from the data that were 1) judged as interesting by a subspecialty trained mammographer and 2) validated by analysis of the data itself.