Characterizing Rule-Based Category Learning Deficits in Patients with Parkinson's Disease

ERIC Educational Resources Information Center

Filoteo, J. Vincent; Maddox, W. Todd; Ing, A. David; Song, David D.

2007-01-01

Parkinson's disease (PD) patients and normal controls were tested in three category learning experiments to determine if previously observed rule-based category learning impairments in PD patients were due to deficits in selective attention or working memory. In Experiment 1, optimal categorization required participants to base their decision on a…

Strategy Selection for Cognitive Skill Acquisition Depends on Task Demands and Working Memory Capacity

ERIC Educational Resources Information Center

Hinze, Scott R.; Bunting, Michael F; Pellegrino, James W.

2009-01-01

The involvement of working memory capacity (WMC) in ruled-based cognitive skill acquisition is well-established, but the duration of its involvement and its role in learning strategy selection are less certain. Participants (N=610) learned four logic rules, their corresponding symbols, or logic gates, and the appropriate input-output combinations…

Communication: The H2@C60 inelastic neutron scattering selection rule: Expanded and explained

NASA Astrophysics Data System (ADS)

Poirier, Bill

2015-09-01

Recently [M. Xu et al., J. Chem. Phys. 139, 064309 (2013)], an unexpected selection rule was discovered for the title system, contradicting the previously held belief that inelastic neutron scattering (INS) is not subject to any selection rules. Moreover, the newly predicted forbidden transitions, which emerge only in the context of coupled H2 translation-rotation (TR) dynamics, have been confirmed experimentally. However, a simple physical understanding, e.g., based on group theory, has been heretofore lacking. This is provided in the present paper, in which we (1) derive the correct symmetry group for the H2@C60 TR Hamiltonian and eigenstates; (2) complete the INS selection rule, and show that the set of forbidden transitions is actually much larger than previously believed; and (3) evaluate previous theoretical and experimental results, in light of the new findings.

Communication: The H{sub 2}@C{sub 60} inelastic neutron scattering selection rule: Expanded and explained

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

Poirier, Bill, E-mail: Bill.Poirier@ttu.edu

Recently [M. Xu et al., J. Chem. Phys. 139, 064309 (2013)], an unexpected selection rule was discovered for the title system, contradicting the previously held belief that inelastic neutron scattering (INS) is not subject to any selection rules. Moreover, the newly predicted forbidden transitions, which emerge only in the context of coupled H{sub 2} translation-rotation (TR) dynamics, have been confirmed experimentally. However, a simple physical understanding, e.g., based on group theory, has been heretofore lacking. This is provided in the present paper, in which we (1) derive the correct symmetry group for the H{sub 2}@C{sub 60} TR Hamiltonian and eigenstates;more » (2) complete the INS selection rule, and show that the set of forbidden transitions is actually much larger than previously believed; and (3) evaluate previous theoretical and experimental results, in light of the new findings.« less

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.

A method and knowledge base for automated inference of patient problems from structured data in an electronic medical record.

PubMed

Wright, Adam; Pang, Justine; Feblowitz, Joshua C; Maloney, Francine L; Wilcox, Allison R; Ramelson, Harley Z; Schneider, Louise I; Bates, David W

2011-01-01

Accurate knowledge of a patient's medical problems is critical for clinical decision making, quality measurement, research, billing and clinical decision support. Common structured sources of problem information include the patient problem list and billing data; however, these sources are often inaccurate or incomplete. To develop and validate methods of automatically inferring patient problems from clinical and billing data, and to provide a knowledge base for inferring problems. We identified 17 target conditions and designed and validated a set of rules for identifying patient problems based on medications, laboratory results, billing codes, and vital signs. A panel of physicians provided input on a preliminary set of rules. Based on this input, we tested candidate rules on a sample of 100,000 patient records to assess their performance compared to gold standard manual chart review. The physician panel selected a final rule for each condition, which was validated on an independent sample of 100,000 records to assess its accuracy. Seventeen rules were developed for inferring patient problems. Analysis using a validation set of 100,000 randomly selected patients showed high sensitivity (range: 62.8-100.0%) and positive predictive value (range: 79.8-99.6%) for most rules. Overall, the inference rules performed better than using either the problem list or billing data alone. We developed and validated a set of rules for inferring patient problems. These rules have a variety of applications, including clinical decision support, care improvement, augmentation of the problem list, and identification of patients for research cohorts.

A generalization of Hamilton's rule--love others how much?

PubMed

Alger, Ingela; Weibull, Jörgen W

2012-04-21

According to Hamilton's (1964a, b) rule, a costly action will be undertaken if its fitness cost to the actor falls short of the discounted benefit to the recipient, where the discount factor is Wright's index of relatedness between the two. We propose a generalization of this rule, and show that if evolution operates at the level of behavior rules, rather than directly at the level of actions, evolution will select behavior rules that induce a degree of cooperation that may differ from that predicted by Hamilton's rule as applied to actions. In social dilemmas there will be less (more) cooperation than under Hamilton's rule if the actions are strategic substitutes (complements). Our approach is based on natural selection, defined in terms of personal (direct) fitness, and applies to a wide range of pairwise interactions. Copyright © 2011 Elsevier Ltd. All rights reserved.

A mobile asset sharing policy for hospitals with real time locating systems.

PubMed

Demircan-Yıldız, Ece Arzu; Fescioglu-Unver, Nilgun

2016-01-01

Each year, hospitals lose a considerable amount of time and money due to misplaced mobile assets. In addition the assets which remain in departments that frequently use them depreciate early, while other assets of the same type in different departments are rarely used. A real time locating system can prevent these losses when used with appropriate asset sharing policies. This research quantifies the amount of time a medium size hospital saves by using real time locating system and proposes an asset selection rule to eliminate the asset usage imbalance problem. The asset selection rule proposed is based on multi objective optimization techniques. The effectiveness of this rule on asset to patient time and asset utilization rate variance performance measures were tested using discrete event simulation method. Results show that the proposed asset selection rule improved the usage balance significantly. Sensitivity analysis showed that the proposed rule is robust to changes in demand rates and user preferences. Real time locating systems enable saving considerable amount of time in hospitals, and they can still be improved by integrating decision support mechanisms. Combining tracking technology and asset selection rules helps improve healthcare services.

Proceedings of the RADC Spectrum Estimation Workshop (2nd) held 3, 4, & 5 October 1979, Griffiss AFB, NY

DTIC Science & Technology

1979-10-01

However, this author’s ex- perience has shown that most order selection rules , including Akaike’s, are not enough to be effeutive against the line splitting...and reduced spectral peak frequency estimation biases. A set of sensitive stopping rules for order se- L lection has been found for the algorithm...7] as the rule for order selection, the minimum FPE of the 41-point sequence with tne Burg algorithm was found at order 23. The AR spectrum based on

Five rules for the evolution of cooperation.

PubMed

Nowak, Martin A

2006-12-08

Cooperation is needed for evolution to construct new levels of organization. Genomes, cells, multicellular organisms, social insects, and human society are all based on cooperation. Cooperation means that selfish replicators forgo some of their reproductive potential to help one another. But natural selection implies competition and therefore opposes cooperation unless a specific mechanism is at work. Here I discuss five mechanisms for the evolution of cooperation: kin selection, direct reciprocity, indirect reciprocity, network reciprocity, and group selection. For each mechanism, a simple rule is derived that specifies whether natural selection can lead to cooperation.

Five Rules for the Evolution of Cooperation

NASA Astrophysics Data System (ADS)

Nowak, Martin A.

2006-12-01

Cooperation is needed for evolution to construct new levels of organization. Genomes, cells, multicellular organisms, social insects, and human society are all based on cooperation. Cooperation means that selfish replicators forgo some of their reproductive potential to help one another. But natural selection implies competition and therefore opposes cooperation unless a specific mechanism is at work. Here I discuss five mechanisms for the evolution of cooperation: kin selection, direct reciprocity, indirect reciprocity, network reciprocity, and group selection. For each mechanism, a simple rule is derived that specifies whether natural selection can lead to cooperation.

A method and knowledge base for automated inference of patient problems from structured data in an electronic medical record

PubMed Central

Pang, Justine; Feblowitz, Joshua C; Maloney, Francine L; Wilcox, Allison R; Ramelson, Harley Z; Schneider, Louise I; Bates, David W

2011-01-01

Background Accurate knowledge of a patient's medical problems is critical for clinical decision making, quality measurement, research, billing and clinical decision support. Common structured sources of problem information include the patient problem list and billing data; however, these sources are often inaccurate or incomplete. Objective To develop and validate methods of automatically inferring patient problems from clinical and billing data, and to provide a knowledge base for inferring problems. Study design and methods We identified 17 target conditions and designed and validated a set of rules for identifying patient problems based on medications, laboratory results, billing codes, and vital signs. A panel of physicians provided input on a preliminary set of rules. Based on this input, we tested candidate rules on a sample of 100 000 patient records to assess their performance compared to gold standard manual chart review. The physician panel selected a final rule for each condition, which was validated on an independent sample of 100 000 records to assess its accuracy. Results Seventeen rules were developed for inferring patient problems. Analysis using a validation set of 100 000 randomly selected patients showed high sensitivity (range: 62.8–100.0%) and positive predictive value (range: 79.8–99.6%) for most rules. Overall, the inference rules performed better than using either the problem list or billing data alone. Conclusion We developed and validated a set of rules for inferring patient problems. These rules have a variety of applications, including clinical decision support, care improvement, augmentation of the problem list, and identification of patients for research cohorts. PMID:21613643

Cognitive changes in conjunctive rule-based category learning: An ERP approach.

PubMed

Rabi, Rahel; Joanisse, Marc F; Zhu, Tianshu; Minda, John Paul

2018-06-25

When learning rule-based categories, sufficient cognitive resources are needed to test hypotheses, maintain the currently active rule in working memory, update rules after feedback, and to select a new rule if necessary. Prior research has demonstrated that conjunctive rules are more complex than unidimensional rules and place greater demands on executive functions like working memory. In our study, event-related potentials (ERPs) were recorded while participants performed a conjunctive rule-based category learning task with trial-by-trial feedback. In line with prior research, correct categorization responses resulted in a larger stimulus-locked late positive complex compared to incorrect responses, possibly indexing the updating of rule information in memory. Incorrect trials elicited a pronounced feedback-locked P300 elicited which suggested a disconnect between perception, and the rule-based strategy. We also examined the differential processing of stimuli that were able to be correctly classified by the suboptimal single-dimensional rule ("easy" stimuli) versus those that could only be correctly classified by the optimal, conjunctive rule ("difficult" stimuli). Among strong learners, a larger, late positive slow wave emerged for difficult compared with easy stimuli, suggesting differential processing of category items even though strong learners performed well on the conjunctive category set. Overall, the findings suggest that ERP combined with computational modelling can be used to better understand the cognitive processes involved in rule-based category learning.

How to select combination operators for fuzzy expert systems using CRI

NASA Technical Reports Server (NTRS)

Turksen, I. B.; Tian, Y.

1992-01-01

A method to select combination operators for fuzzy expert systems using the Compositional Rule of Inference (CRI) is proposed. First, fuzzy inference processes based on CRI are classified into three categories in terms of their inference results: the Expansion Type Inference, the Reduction Type Inference, and Other Type Inferences. Further, implication operators under Sup-T composition are classified as the Expansion Type Operator, the Reduction Type Operator, and the Other Type Operators. Finally, the combination of rules or their consequences is investigated for inference processes based on CRI.

Best Communication Practices for Preparation of Exceptional Event Demonstrations

EPA Pesticide Factsheets

OAQPS developed this document of Best Practices based on input received from EPA regional offices and selected state/local air agencies who submitted Exceptional Event Demonstrations under the 2007 version of the Exceptional Events Rule (EE Rule).

Selecting Statistical Quality Control Procedures for Limiting the Impact of Increases in Analytical Random Error on Patient Safety.

PubMed

Yago, Martín

2017-05-01

QC planning based on risk management concepts can reduce the probability of harming patients due to an undetected out-of-control error condition. It does this by selecting appropriate QC procedures to decrease the number of erroneous results reported. The selection can be easily made by using published nomograms for simple QC rules when the out-of-control condition results in increased systematic error. However, increases in random error also occur frequently and are difficult to detect, which can result in erroneously reported patient results. A statistical model was used to construct charts for the 1 ks and X /χ 2 rules. The charts relate the increase in the number of unacceptable patient results reported due to an increase in random error with the capability of the measurement procedure. They thus allow for QC planning based on the risk of patient harm due to the reporting of erroneous results. 1 ks Rules are simple, all-around rules. Their ability to deal with increases in within-run imprecision is minimally affected by the possible presence of significant, stable, between-run imprecision. X /χ 2 rules perform better when the number of controls analyzed during each QC event is increased to improve QC performance. Using nomograms simplifies the selection of statistical QC procedures to limit the number of erroneous patient results reported due to an increase in analytical random error. The selection largely depends on the presence or absence of stable between-run imprecision. © 2017 American Association for Clinical Chemistry.

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.

Neurons with object-centered spatial selectivity in macaque SEF: do they represent locations or rules?

PubMed

Tremblay, Léon; Gettner, Sonya N; Olson, Carl R

2002-01-01

In macaque monkeys performing a task that requires eye movements to the leftmost or rightmost of two dots in a horizontal array, some neurons in the supplementary eye field (SEF) fire differentially according to which side of the array is the target regardless of the array's location on the screen. We refer to these neurons as exhibiting selectivity for object-centered location. This form of selectivity might arise from involvement of the neurons in either of two processes: representing the locations of targets or representing the rules by which targets are selected. To distinguish between these possibilities, we monitored neuronal activity in the SEF of two monkeys performing a task that required the selection of targets by either an object-centered spatial rule or a color rule. On each trial, a sample array consisting of two side-by-side dots appeared; then a cue flashed on one dot; then the display vanished and a delay ensued. Next a target array consisting of two side-by-side dots appeared at an unpredictable location and another delay ensued; finally the monkey had to make an eye movement to one of the target dots. On some trials, the monkey had to select the dot on the same side as the cue (right or left). On other trials, he had to select the target of the same color as the cue (red or green). Neuronal activity robustly encoded the object-centered locations first of the cue and then of the target regardless of the whether the monkey was following a rule based on object-centered location or color. Neuronal activity was at most weakly affected by the type of rule the monkey was following (object-centered-location or color) or by the color of the cue and target (red or green). On trials involving a color rule, neuronal activity was moderately enhanced when the cue and target appeared on opposite sides of their respective arrays. We conclude that the general function of SEF neurons selective for object-centered location is to represent where the cue and target are in their respective arrays rather than to represent the rule for target selection.

Five rules for the evolution of cooperation

PubMed Central

Nowak, Martin A.

2011-01-01

Cooperation is needed for evolution to construct new levels of organization. The emergence of genomes, cells, multi-cellular organisms, social insects and human society are all based on cooperation. Cooperation means that selfish replicators forgo some of their reproductive potential to help one another. But natural selection implies competition and therefore opposes cooperation unless a specific mechanism is at work. Here I discuss five mechanisms for the evolution of cooperation: kin selection, direct reciprocity, indirect reciprocity, network reciprocity and group selection. For each mechanism, a simple rule is derived which specifies whether natural selection can lead to cooperation. PMID:17158317

The neural basis for novel semantic categorization.

PubMed

Koenig, Phyllis; Smith, Edward E; Glosser, Guila; DeVita, Chris; Moore, Peachie; McMillan, Corey; Gee, Jim; Grossman, Murray

2005-01-15

We monitored regional cerebral activity with BOLD fMRI during acquisition of a novel semantic category and subsequent categorization of test stimuli by a rule-based strategy or a similarity-based strategy. We observed different patterns of activation in direct comparisons of rule- and similarity-based categorization. During rule-based category acquisition, subjects recruited anterior cingulate, thalamic, and parietal regions to support selective attention to perceptual features, and left inferior frontal cortex to helps maintain rules in working memory. Subsequent rule-based categorization revealed anterior cingulate and parietal activation while judging stimuli whose conformity with the rules was readily apparent, and left inferior frontal recruitment during judgments of stimuli whose conformity was less apparent. By comparison, similarity-based category acquisition showed recruitment of anterior prefrontal and posterior cingulate regions, presumably to support successful retrieval of previously encountered exemplars from long-term memory, and bilateral temporal-parietal activation for perceptual feature integration. Subsequent similarity-based categorization revealed temporal-parietal, posterior cingulate, and anterior prefrontal activation. These findings suggest that large-scale networks support relatively distinct categorization processes during the acquisition and judgment of semantic category knowledge.

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.

Evaluating Machine Learning Classifiers for Hybrid Network Intrusion Detection Systems

DTIC Science & Technology

2015-03-26

7 VRT Vulnerability Research Team...and the Talos (formerly the Vulnerability Research Team ( VRT )) [7] 7 ruleset libraries are the two leading rulesets in use. Both libraries offer paid...rule sets to load for the signature-based IDS. Snort is selected as the IDS engine using the “ VRT and ET No/GPL” rule set. The total rule count in the

A networked voting rule for democratic representation

NASA Astrophysics Data System (ADS)

Hernández, Alexis R.; Gracia-Lázaro, Carlos; Brigatti, Edgardo; Moreno, Yamir

2018-03-01

We introduce a general framework for exploring the problem of selecting a committee of representatives with the aim of studying a networked voting rule based on a decentralized large-scale platform, which can assure a strong accountability of the elected. The results of our simulations suggest that this algorithm-based approach is able to obtain a high representativeness for relatively small committees, performing even better than a classical voting rule based on a closed list of candidates. We show that a general relation between committee size and representatives exists in the form of an inverse square root law and that the normalized committee size approximately scales with the inverse of the community size, allowing the scalability to very large populations. These findings are not strongly influenced by the different networks used to describe the individuals' interactions, except for the presence of few individuals with very high connectivity which can have a marginal negative effect in the committee selection process.

STRATEGIES OF MARINE DINOFLAGELLATE SURVIVAL AND SOME RULES OF ASSEMBLY. (R829368)

EPA Science Inventory

Dinoflagellate ecology is based on multiple adaptive strategies and species having diverse habitat preferences. Nine types of mixing-irradiance-nutrient habitats selecting for specific marine dinoflagellate life-form types are recognised, with five rules of assembly proposed t...

R-charge conservation and more in factorizable and non-factorizable orbifolds

NASA Astrophysics Data System (ADS)

Bizet, Nana G. Cabo; Kobayashi, Tatsuo; Peña, Damián K. Mayorga; Parameswaran, Susha L.; Schmitz, Matthias; Zavala, Ivonne

2013-05-01

We consider the string theory origin of R-charge conservation laws in heterotic orbifold compactifications, deriving the corresponding string coupling selection rule for factorizable and non-factorizable orbifolds, with prime ordered and non-prime ordered point groups. R-charge conservation arises due to symmetries among the worldsheet instantons that can mediate the couplings. Among our results is a previously missed non-trivial contribution to the conserved R-charges from the γ-phases in non-prime orbifolds, which weakens the R-charge selection rule. Symmetries among the worldsheet instantons can also lead to additional selection rules for some couplings. We make a similar analysis for Rule 4 or the "torus lattice selection rule". Moreover, we identify a new string selection rule, that we call Rule 6 or the "coset vector selection rule".

Scattering property based contextual PolSAR speckle filter

NASA Astrophysics Data System (ADS)

Mullissa, Adugna G.; Tolpekin, Valentyn; Stein, Alfred

2017-12-01

Reliability of the scattering model based polarimetric SAR (PolSAR) speckle filter depends upon the accurate decomposition and classification of the scattering mechanisms. This paper presents an improved scattering property based contextual speckle filter based upon an iterative classification of the scattering mechanisms. It applies a Cloude-Pottier eigenvalue-eigenvector decomposition and a fuzzy H/α classification to determine the scattering mechanisms on a pre-estimate of the coherency matrix. The H/α classification identifies pixels with homogeneous scattering properties. A coarse pixel selection rule groups pixels that are either single bounce, double bounce or volume scatterers. A fine pixel selection rule is applied to pixels within each canonical scattering mechanism. We filter the PolSAR data and depending on the type of image scene (urban or rural) use either the coarse or fine pixel selection rule. Iterative refinement of the Wishart H/α classification reduces the speckle in the PolSAR data. Effectiveness of this new filter is demonstrated by using both simulated and real PolSAR data. It is compared with the refined Lee filter, the scattering model based filter and the non-local means filter. The study concludes that the proposed filter compares favorably with other polarimetric speckle filters in preserving polarimetric information, point scatterers and subtle features in PolSAR data.

Patterns Exploration on Patterns of Empirical Herbal Formula of Chinese Medicine by Association Rules

PubMed Central

Huang, Li; Yuan, Jiamin; Yang, Zhimin; Xu, Fuping; Huang, Chunhua

2015-01-01

Background. In this study, we use association rules to explore the latent rules and patterns of prescribing and adjusting the ingredients of herbal decoctions based on empirical herbal formula of Chinese Medicine (CM). Materials and Methods. The consideration and development of CM prescriptions based on the knowledge of CM doctors are analyzed. The study contained three stages. The first stage is to identify the chief symptoms to a specific empirical herbal formula, which can serve as the key indication for herb addition and cancellation. The second stage is to conduct a case study on the empirical CM herbal formula for insomnia. Doctors will add extra ingredients or cancel some of them by CM syndrome diagnosis. The last stage of the study is to divide the observed cases into the effective group and ineffective group based on the assessed clinical effect by doctors. The patterns during the diagnosis and treatment are selected by the applied algorithm and the relations between clinical symptoms or indications and herb choosing principles will be selected by the association rules algorithm. Results. Totally 40 patients were observed in this study: 28 patients were considered effective after treatment and the remaining 12 were ineffective. 206 patterns related to clinical indications of Chinese Medicine were checked and screened with each observed case. In the analysis of the effective group, we used the algorithm of association rules to select combinations between 28 herbal adjustment strategies of the empirical herbal formula and the 190 patterns of individual clinical manifestations. During this stage, 11 common patterns were eliminated and 5 major symptoms for insomnia remained. 12 association rules were identified which included 5 herbal adjustment strategies. Conclusion. The association rules method is an effective algorithm to explore the latent relations between clinical indications and herbal adjustment strategies for the study on empirical herbal formulas. PMID:26495415

System Complexity Reduction via Feature Selection

ERIC Educational Resources Information Center

Deng, Houtao

2011-01-01

This dissertation transforms a set of system complexity reduction problems to feature selection problems. Three systems are considered: classification based on association rules, network structure learning, and time series classification. Furthermore, two variable importance measures are proposed to reduce the feature selection bias in tree…

Civilian Health and Medical Program of the Uniformed Services (CHAMPUS); TRICARE Reserve Select; TRICARE Dental Program; Early Eligibility for TRICARE for Certain Reserve Component Members. Final rule.

PubMed

2015-09-15

TRICARE Reserve Select (TRS) is a premium-based TRICARE health plan available for purchase worldwide by qualified members of the Ready Reserve and by qualified survivors of TRS members. TRICARE Dental Program (TDP) is a premium-based TRICARE dental plan available for purchase worldwide by qualified Service members. This final rule revises requirements and procedures for the TRS program to specify the appropriate actuarial basis for calculating premiums in addition to making other minor clarifying administrative changes. For a member who is involuntarily separated from the Selected Reserve under other than adverse conditions this final rule provides a time-limited exception that allows TRS coverage in effect to continue for up to 180 days after the date on which the member is separated from the Selected Reserve and TDP coverage in effect to continue for no less than 180 days after the separation date. It also expands early TRICARE eligibility for certain Reserve Component members from a maximum of 90 days to a maximum of 180 days prior to activation in support of a contingency operation for more than 30 days.

Application of a rule-based knowledge system using CLIPS for the taxonomy of selected Opuntia species

NASA Technical Reports Server (NTRS)

Heymans, Bart C.; Onema, Joel P.; Kuti, Joseph O.

1991-01-01

A rule based knowledge system was developed in CLIPS (C Language Integrated Production System) for identifying Opuntia species in the family Cactaceae, which contains approx. 1500 different species. This botanist expert tool system is capable of identifying selected Opuntia plants from the family level down to the species level when given some basic characteristics of the plants. Many plants are becoming of increasing importance because of their nutrition and human health potential, especially in the treatment of diabetes mellitus. The expert tool system described can be extremely useful in an unequivocal identification of many useful Opuntia species.

A networked voting rule for democratic representation

PubMed Central

Brigatti, Edgardo; Moreno, Yamir

2018-01-01

We introduce a general framework for exploring the problem of selecting a committee of representatives with the aim of studying a networked voting rule based on a decentralized large-scale platform, which can assure a strong accountability of the elected. The results of our simulations suggest that this algorithm-based approach is able to obtain a high representativeness for relatively small committees, performing even better than a classical voting rule based on a closed list of candidates. We show that a general relation between committee size and representatives exists in the form of an inverse square root law and that the normalized committee size approximately scales with the inverse of the community size, allowing the scalability to very large populations. These findings are not strongly influenced by the different networks used to describe the individuals’ interactions, except for the presence of few individuals with very high connectivity which can have a marginal negative effect in the committee selection process. PMID:29657817

Deriving adaptive operating rules of hydropower reservoirs using time-varying parameters generated by the EnKF

NASA Astrophysics Data System (ADS)

Feng, Maoyuan; Liu, Pan; Guo, Shenglian; Shi, Liangsheng; Deng, Chao; Ming, Bo

2017-08-01

Operating rules have been used widely to decide reservoir operations because of their capacity for coping with uncertain inflow. However, stationary operating rules lack adaptability; thus, under changing environmental conditions, they cause inefficient reservoir operation. This paper derives adaptive operating rules based on time-varying parameters generated using the ensemble Kalman filter (EnKF). A deterministic optimization model is established to obtain optimal water releases, which are further taken as observations of the reservoir simulation model. The EnKF is formulated to update the operating rules sequentially, providing a series of time-varying parameters. To identify the index that dominates the variations of the operating rules, three hydrologic factors are selected: the reservoir inflow, ratio of future inflow to current available water, and available water. Finally, adaptive operating rules are derived by fitting the time-varying parameters with the identified dominant hydrologic factor. China's Three Gorges Reservoir was selected as a case study. Results show that (1) the EnKF has the capability of capturing the variations of the operating rules, (2) reservoir inflow is the factor that dominates the variations of the operating rules, and (3) the derived adaptive operating rules are effective in improving hydropower benefits compared with stationary operating rules. The insightful findings of this study could be used to help adapt reservoir operations to mitigate the effects of changing environmental conditions.

Index Fund Selections with GAs and Classifications Based on Turnover

NASA Astrophysics Data System (ADS)

Orito, Yukiko; Motoyama, Takaaki; Yamazaki, Genji

It is well known that index fund selections are important for the risk hedge of investment in a stock market. The`selection’means that for`stock index futures’, n companies of all ones in the market are selected. For index fund selections, Orito et al.(6) proposed a method consisting of the following two steps : Step 1 is to select N companies in the market with a heuristic rule based on the coefficient of determination between the return rate of each company in the market and the increasing rate of the stock price index. Step 2 is to construct a group of n companies by applying genetic algorithms to the set of N companies. We note that the rule of Step 1 is not unique. The accuracy of the results using their method depends on the length of time data (price data) in the experiments. The main purpose of this paper is to introduce a more`effective rule’for Step 1. The rule is based on turnover. The method consisting of Step 1 based on turnover and Step 2 is examined with numerical experiments for the 1st Section of Tokyo Stock Exchange. The results show that with our method, it is possible to construct the more effective index fund than the results of Orito et al.(6). The accuracy of the results using our method depends little on the length of time data (turnover data). The method especially works well when the increasing rate of the stock price index over a period can be viewed as a linear time series data.

77 FR 55888 - Self-Regulatory Organizations; NYSE Arca, Inc.; Order Approving a Proposed Rule Change Amending...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-09-11

... Rule 7.31(h) To Add a PL Select Order September 5, 2012. I. Introduction On May 22, 2012, NYSE Arca...,\\2\\ a proposed rule change to amend NYSE Arca Equities Rule 7.31(h) to add a PL Select Order. The... Rule Change Amending NYSE Arca Equities Rule 7.31(h) To Add a PL Select Order Type). II. Description of...

78 FR 65407 - Self-Regulatory Organizations; NYSE Arca, Inc.; Notice of Filing of Proposed Rule Change To List...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-10-31

... selling investments for the Portfolio. Investments are selected based on fundamental and quantitative... Equity Portfolio. Investments are selected based on fundamental and quantitative analysis. MFS uses... trust and is registered with the Commission as an open-end management investment company.\\5\\ SSgA Funds...

76 FR 51442 - Self-Regulatory Organizations; NYSE Arca, Inc.; Notice of Filing of Proposed Rule Change To List...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-08-18

...-Adviser has designed the following quantitative stock selection rules to make allocation decisions and to..., the Sub-Adviser's investment process is quantitative. Based on extensive historical research, the Sub... open-end fund's portfolio composition must be subject to procedures designed to prevent the use and...

Improving the Bandwidth Selection in Kernel Equating

ERIC Educational Resources Information Center

Andersson, Björn; von Davier, Alina A.

2014-01-01

We investigate the current bandwidth selection methods in kernel equating and propose a method based on Silverman's rule of thumb for selecting the bandwidth parameters. In kernel equating, the bandwidth parameters have previously been obtained by minimizing a penalty function. This minimization process has been criticized by practitioners…

Logical recoding of S-R rules can reverse the effects of spatial S-R correspondence.

PubMed

Wühr, Peter; Biebl, Rupert

2009-02-01

Two experiments investigated competing explanations for the reversal of spatial stimulus-response (S-R) correspondence effects (i.e., Simon effects) with an incompatible S-R mapping on the relevant, nonspatial dimension. Competing explanations were based on generalized S-R rules (logical-recoding account) or referred to display-control arrangement correspondence or to S-S congruity. In Experiment 1, compatible responses to finger-name stimuli presented at left/right locations produced normal Simon effects, whereas incompatible responses to finger-name stimuli produced an inverted Simon effect. This finding supports the logical-recoding account. In Experiment 2, spatial S-R correspondence and color S-R correspondence were varied independently, and main effects of these variables were observed. The lack of an interaction between these variables, however, disconfirms a prediction of the display-control arrangement correspondence account. Together, the results provide converging evidence for the logical-recoding account. This account claims that participants derive generalized response selection rules (e.g., the identity or reversal rule) from specific S-R rules and inadvertently apply the generalized rules to the irrelevant (spatial) S-R dimension when selecting their response.

Enhanced image fusion using directional contrast rules in fuzzy transform domain.

PubMed

Nandal, Amita; Rosales, Hamurabi Gamboa

2016-01-01

In this paper a novel image fusion algorithm based on directional contrast in fuzzy transform (FTR) domain is proposed. Input images to be fused are first divided into several non-overlapping blocks. The components of these sub-blocks are fused using directional contrast based fuzzy fusion rule in FTR domain. The fused sub-blocks are then transformed into original size blocks using inverse-FTR. Further, these inverse transformed blocks are fused according to select maximum based fusion rule for reconstructing the final fused image. The proposed fusion algorithm is both visually and quantitatively compared with other standard and recent fusion algorithms. Experimental results demonstrate that the proposed method generates better results than the other methods.

Rule Extraction Based on Extreme Learning Machine and an Improved Ant-Miner Algorithm for Transient Stability Assessment.

PubMed

Li, Yang; Li, Guoqing; Wang, Zhenhao

2015-01-01

In order to overcome the problems of poor understandability of the pattern recognition-based transient stability assessment (PRTSA) methods, a new rule extraction method based on extreme learning machine (ELM) and an improved Ant-miner (IAM) algorithm is presented in this paper. First, the basic principles of ELM and Ant-miner algorithm are respectively introduced. Then, based on the selected optimal feature subset, an example sample set is generated by the trained ELM-based PRTSA model. And finally, a set of classification rules are obtained by IAM algorithm to replace the original ELM network. The novelty of this proposal is that transient stability rules are extracted from an example sample set generated by the trained ELM-based transient stability assessment model by using IAM algorithm. The effectiveness of the proposed method is shown by the application results on the New England 39-bus power system and a practical power system--the southern power system of Hebei province.

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.

Fusion of classifiers for REIS-based detection of suspicious breast lesions

NASA Astrophysics Data System (ADS)

Lederman, Dror; Wang, Xingwei; Zheng, Bin; Sumkin, Jules H.; Tublin, Mitchell; Gur, David

2011-03-01

After developing a multi-probe resonance-frequency electrical impedance spectroscopy (REIS) system aimed at detecting women with breast abnormalities that may indicate a developing breast cancer, we have been conducting a prospective clinical study to explore the feasibility of applying this REIS system to classify younger women (< 50 years old) into two groups of "higher-than-average risk" and "average risk" of having or developing breast cancer. The system comprises one central probe placed in contact with the nipple, and six additional probes uniformly distributed along an outside circle to be placed in contact with six points on the outer breast skin surface. In this preliminary study, we selected an initial set of 174 examinations on participants that have completed REIS examinations and have clinical status verification. Among these, 66 examinations were recommended for biopsy due to findings of a highly suspicious breast lesion ("positives"), and 108 were determined as negative during imaging based procedures ("negatives"). A set of REIS-based features, extracted using a mirror-matched approach, was computed and fed into five machine learning classifiers. A genetic algorithm was used to select an optimal subset of features for each of the five classifiers. Three fusion rules, namely sum rule, weighted sum rule and weighted median rule, were used to combine the results of the classifiers. Performance evaluation was performed using a leave-one-case-out cross-validation method. The results indicated that REIS may provide a new technology to identify younger women with higher than average risk of having or developing breast cancer. Furthermore, it was shown that fusion rule, such as a weighted median fusion rule and a weighted sum fusion rule may improve performance as compared with the highest performing single classifier.

Surface stability and the selection rules of substrate orientation for optimal growth of epitaxial II-VI semiconductors

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

Yin, Wan-Jian; Department of Physics & Astronomy, and Wright Center for Photovoltaics Innovation and Commercialization, The University of Toledo, Toledo, Ohio 43606; Yang, Ji-Hui

2015-10-05

The surface structures of ionic zinc-blende CdTe (001), (110), (111), and (211) surfaces are systematically studied by first-principles density functional calculations. Based on the surface structures and surface energies, we identify the detrimental twinning appearing in molecular beam epitaxy (MBE) growth of II-VI compounds as the (111) lamellar twin boundaries. To avoid the appearance of twinning in MBE growth, we propose the following selection rules for choosing optimal substrate orientations: (1) the surface should be nonpolar so that there is no large surface reconstructions that could act as a nucleation center and promote the formation of twins; (2) the surfacemore » structure should have low symmetry so that there are no multiple equivalent directions for growth. These straightforward rules, in consistent with experimental observations, provide guidelines for selecting proper substrates for high-quality MBE growth of II-VI compounds.« less

Single-Sex Schools, Student Achievement, and Course Selection: Evidence from Rule-Based Student Assignments in Trinidad and Tobago. NBER Working Paper No. 16817

ERIC Educational Resources Information Center

Jackson, C. Kirabo

2011-01-01

Existing studies on single-sex schooling suffer from biases due to student selection to schools and single-sex schools being better in unmeasured ways. In Trinidad and Tobago students are assigned to secondary schools based on an algorithm allowing one to address self-selection bias and cleanly estimate an upper-bound single-sex school effect. The…

An automatic fuzzy-based multi-temporal brain digital subtraction angiography image fusion algorithm using curvelet transform and content selection strategy.

PubMed

Momeni, Saba; Pourghassem, Hossein

2014-08-01

Recently image fusion has prominent role in medical image processing and is useful to diagnose and treat many diseases. Digital subtraction angiography is one of the most applicable imaging to diagnose brain vascular diseases and radiosurgery of brain. This paper proposes an automatic fuzzy-based multi-temporal fusion algorithm for 2-D digital subtraction angiography images. In this algorithm, for blood vessel map extraction, the valuable frames of brain angiography video are automatically determined to form the digital subtraction angiography images based on a novel definition of vessel dispersion generated by injected contrast material. Our proposed fusion scheme contains different fusion methods for high and low frequency contents based on the coefficient characteristic of wrapping second generation of curvelet transform and a novel content selection strategy. Our proposed content selection strategy is defined based on sample correlation of the curvelet transform coefficients. In our proposed fuzzy-based fusion scheme, the selection of curvelet coefficients are optimized by applying weighted averaging and maximum selection rules for the high frequency coefficients. For low frequency coefficients, the maximum selection rule based on local energy criterion is applied to better visual perception. Our proposed fusion algorithm is evaluated on a perfect brain angiography image dataset consisting of one hundred 2-D internal carotid rotational angiography videos. The obtained results demonstrate the effectiveness and efficiency of our proposed fusion algorithm in comparison with common and basic fusion algorithms.

Strategies for adding adaptive learning mechanisms to rule-based diagnostic expert systems

NASA Technical Reports Server (NTRS)

Stclair, D. C.; Sabharwal, C. L.; Bond, W. E.; Hacke, Keith

1988-01-01

Rule-based diagnostic expert systems can be used to perform many of the diagnostic chores necessary in today's complex space systems. These expert systems typically take a set of symptoms as input and produce diagnostic advice as output. The primary objective of such expert systems is to provide accurate and comprehensive advice which can be used to help return the space system in question to nominal operation. The development and maintenance of diagnostic expert systems is time and labor intensive since the services of both knowledge engineer(s) and domain expert(s) are required. The use of adaptive learning mechanisms to increment evaluate and refine rules promises to reduce both time and labor costs associated with such systems. This paper describes the basic adaptive learning mechanisms of strengthening, weakening, generalization, discrimination, and discovery. Next basic strategies are discussed for adding these learning mechanisms to rule-based diagnostic expert systems. These strategies support the incremental evaluation and refinement of rules in the knowledge base by comparing the set of advice given by the expert system (A) with the correct diagnosis (C). Techniques are described for selecting those rules in the in the knowledge base which should participate in adaptive learning. The strategies presented may be used with a wide variety of learning algorithms. Further, these strategies are applicable to a large number of rule-based diagnostic expert systems. They may be used to provide either immediate or deferred updating of the knowledge base.

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.

It's Your Game-Tech: Toward Sexual Health in the Digital Age.

PubMed

Shegog, Ross; Peskin, Melissa F; Markham, Christine; Thiel, Melanie; Karny, Efrat; Addy, Robert C; Johnson, Kimberly A; Tortolero, Susan

2014-08-01

Adolescent sexually transmitted infection (STI) and birth rates indicate a need for effective middle school HIV/STI, and pregnancy prevention curricula to delay, or mitigate consequences of, early sexual activity. Individual and organizational barriers to adoption, implementation, and maintenance, however, can hamper dissemination of evidence-based sexual health curricula, adversely impacting fidelity and reach. Internet-based approaches may help mitigate these barriers. This paper describes the development and feasibility testing of It's Your Game ( IYG )-Tech, a stand-alone 13-lesson Internet-based sexual health life-skills curriculum adapted from an existing effective sexual health curriculum-It's Your Game… Keep it Real ( IYG ). IYG -Tech development adaptation steps were to: 1) Select a suitable effective program and gather the original program materials; 2) Develop "proof of concept" lessons and test usability and impact; 3) Develop the program design document describing the core content, scope, and methods and strategies; and 4) produce the new program. Lab- and school-based tests with middle school students demonstrated high ratings on usability parameters and immediate impact on selected psychosocial factors related to sexual behavior-perceptions of friends' beliefs, reasons for not having sex, condom use self-efficacy, abstinence intentions, negotiating with others to protect personal rules, and improved knowledge about what constitutes healthy relationships (all p < .05). Youth rated IYG -Tech is favorably compared to other learning channels (>76.2% agreement) and rated the lessons as helpful in making healthy choices, selecting personal rules, detecting challenges to those rules, and protecting personal rules through negotiation and refusal skills (89.5% - 100%). Further efficacy testing is indicated for IYG -Tech as a potential strategy to deliver effective HIV/STI, and pregnancy prevention to middle school youth.

Classifying the Indication for Colonoscopy Procedures: A Comparison of NLP Approaches in a Diverse National Healthcare System.

PubMed

Patterson, Olga V; Forbush, Tyler B; Saini, Sameer D; Moser, Stephanie E; DuVall, Scott L

2015-01-01

In order to measure the level of utilization of colonoscopy procedures, identifying the primary indication for the procedure is required. Colonoscopies may be utilized not only for screening, but also for diagnostic or therapeutic purposes. To determine whether a colonoscopy was performed for screening, we created a natural language processing system to identify colonoscopy reports in the electronic medical record system and extract indications for the procedure. A rule-based model and three machine-learning models were created using 2,000 manually annotated clinical notes of patients cared for in the Department of Veterans Affairs. Performance of the models was measured and compared. Analysis of the models on a test set of 1,000 documents indicates that the rule-based system performance stays fairly constant as evaluated on training and testing sets. However, the machine learning model without feature selection showed significant decrease in performance. Therefore, rule-based classification system appears to be more robust than a machine-learning system in cases when no feature selection is performed.

Frequency selection rule for high definition and high frame rate Lissajous scanning.

PubMed

Hwang, Kyungmin; Seo, Yeong-Hyeon; Ahn, Jinhyo; Kim, Pilhan; Jeong, Ki-Hun

2017-10-26

Lissajous microscanners are very attractive in compact laser scanning applications such as endomicroscopy or pro-projection display owing to high mechanical stability and low operating voltages. The scanning frequency serves as a critical factor for determining the scanning imaging quality. Here we report the selection rule of scanning frequencies that can realize high definition and high frame-rate (HDHF) full-repeated Lissajous scanning imaging. The fill factor (FF) monotonically increases with the total lobe number of a Lissajous curve, i.e., the sum of scanning frequencies divided by the great common divisor (GCD) of bi-axial scanning frequencies. The frames per second (FPS), called the pattern repeated rate or the frame rate, linearly increases with GCD. HDHF Lissajous scanning is achieved at the bi-axial scanning frequencies, where the GCD has the maximum value among various sets of the scanning frequencies satisfying the total lobe number for a target FF. Based on this selection rule, the experimental results clearly demonstrate that conventional Lissajous scanners substantially increase both FF and FPS by slightly modulating the scanning frequencies at near the resonance within the resonance bandwidth of a Lissajous scanner. This selection rule provides a new guideline for HDHF Lissajous scanning in compact laser scanning systems.

Structural and Functional Basis of the Fidelity of Nucleotide Selection by Flavivirus RNA-Dependent RNA Polymerases

PubMed Central

Canard, Bruno

2018-01-01

Viral RNA-dependent RNA polymerases (RdRps) play a central role not only in viral replication, but also in the genetic evolution of viral RNAs. After binding to an RNA template and selecting 5′-triphosphate ribonucleosides, viral RdRps synthesize an RNA copy according to Watson-Crick base-pairing rules. The copy process sometimes deviates from both the base-pairing rules specified by the template and the natural ribose selectivity and, thus, the process is error-prone due to the intrinsic (in)fidelity of viral RdRps. These enzymes share a number of conserved amino-acid sequence strings, called motifs A–G, which can be defined from a structural and functional point-of-view. A co-relation is gradually emerging between mutations in these motifs and viral genome evolution or observed mutation rates. Here, we review our current knowledge on these motifs and their role on the structural and mechanistic basis of the fidelity of nucleotide selection and RNA synthesis by Flavivirus RdRps. PMID:29385764

Nonlinear optical selection rule based on valley-exciton locking in monolayer ws 2

DOE PAGES

Xiao, Jun; Ye, Ziliang; Wang, Ying; ...

2015-12-18

Optical selection rules fundamentally determine the optical transitions between energy states in a variety of physical systems, from hydrogen atoms to bulk crystals such as gallium arsenide. These rules are important for optoelectronic applications such as lasers, energy-dispersive X-ray spectroscopy, and quantum computation. Recently, single-layer transition metal dichalcogenides have been found to exhibit valleys in momentum space with nontrivial Berry curvature and excitons with large binding energy. However, there has been little study of how the unique valley degree of freedom combined with the strong excitonic effect influences the nonlinear optical excitation. Here in this paper, we report the discoverymore » of nonlinear optical selection rules in monolayer WS 2, an important candidate for visible 2D optoelectronics because of its high quantum yield and large direct bandgap. We experimentally demonstrated this principle for second-harmonic generation and two-photon luminescence (TPL). Moreover, the circularly polarized TPL and the study of its dynamics evince a sub-ps interexciton relaxation (2p → 1s). The discovery of this new optical selection rule in a valleytronic 2D system not only considerably enhances knowledge in this area but also establishes a foundation for the control of optical transitions that will be crucial for valley optoelectronic device applications such as 2D valley-polarized THz sources with 2p-1s transitions, optical switches, and coherent control for quantum computing.« less

A tweaking principle for executive control: neuronal circuit mechanism for rule-based task switching and conflict resolution.

PubMed

Ardid, Salva; Wang, Xiao-Jing

2013-12-11

A hallmark of executive control is the brain's agility to shift between different tasks depending on the behavioral rule currently in play. In this work, we propose a "tweaking hypothesis" for task switching: a weak rule signal provides a small bias that is dramatically amplified by reverberating attractor dynamics in neural circuits for stimulus categorization and action selection, leading to an all-or-none reconfiguration of sensory-motor mapping. Based on this principle, we developed a biologically realistic model with multiple modules for task switching. We found that the model quantitatively accounts for complex task switching behavior: switch cost, congruency effect, and task-response interaction; as well as monkey's single-neuron activity associated with task switching. The model yields several testable predictions, in particular, that category-selective neurons play a key role in resolving sensory-motor conflict. This work represents a neural circuit model for task switching and sheds insights in the brain mechanism of a fundamental cognitive capability.

Microcomputer-based classification of environmental data in municipal areas

NASA Astrophysics Data System (ADS)

Thiergärtner, H.

1995-10-01

Multivariate data-processing methods used in mineral resource identification can be used to classify urban regions. Using elements of expert systems, geographical information systems, as well as known classification and prognosis systems, it is possible to outline a single model that consists of resistant and of temporary parts of a knowledge base including graphical input and output treatment and of resistant and temporary elements of a bank of methods and algorithms. Whereas decision rules created by experts will be stored in expert systems directly, powerful classification rules in form of resistant but latent (implicit) decision algorithms may be implemented in the suggested model. The latent functions will be transformed into temporary explicit decision rules by learning processes depending on the actual task(s), parameter set(s), pixels selection(s), and expert control(s). This takes place both at supervised and nonsupervised classification of multivariately described pixel sets representing municipal subareas. The model is outlined briefly and illustrated by results obtained in a target area covering a part of the city of Berlin (Germany).

Computer language for identifying chemicals with comprehensive two-dimensional gas chromatography and mass spectrometry.

PubMed

Reichenbach, Stephen E; Kottapalli, Visweswara; Ni, Mingtian; Visvanathan, Arvind

2005-04-15

This paper describes a language for expressing criteria for chemical identification with comprehensive two-dimensional gas chromatography paired with mass spectrometry (GC x GC-MS) and presents computer-based tools implementing the language. The Computer Language for Indentifying Chemicals (CLIC) allows expressions that describe rules (or constraints) for selecting chemical peaks or data points based on multi-dimensional chromatographic properties and mass spectral characteristics. CLIC offers chromatographic functions of retention times, functions of mass spectra, numbers for quantitative and relational evaluation, and logical and arithmetic operators. The language is demonstrated with the compound-class selection rules described by Welthagen et al. [W. Welthagen, J. Schnelle-Kreis, R. Zimmermann, J. Chromatogr. A 1019 (2003) 233-249]. A software implementation of CLIC provides a calculator-like graphical user-interface (GUI) for building and applying selection expressions. From the selection calculator, expressions can be used to select chromatographic peaks that meet the criteria or create selection chromatograms that mask data points inconsistent with the criteria. Selection expressions can be combined with graphical, geometric constraints in the retention-time plane as a powerful component for chemical identification with template matching or used to speed and improve mass spectrum library searches.

Improving Sector Hash Carving with Rule-Based and Entropy-Based Non-Probative Block Filters

DTIC Science & Technology

2015-03-01

0x20 exceeds the histogram rule’s threshold of 256 instances of a single 4-byte value. The 0x20 bytes are part of an Extensible Metadata Platform (XMP...block consists of data separated by NULL bytes of padding. The histogram rule is triggered for the block because the block contains more than 256 4...sdash can reduce the rate of false positive matches. After characteristic features have been selected, the features are hashed using SHA -1, which creates

Equations for Scoring Rules When Data Are Missing

NASA Technical Reports Server (NTRS)

James, Mark

2006-01-01

A document presents equations for scoring rules in a diagnostic and/or prognostic artificial-intelligence software system of the rule-based inference-engine type. The equations define a set of metrics that characterize the evaluation of a rule when data required for the antecedence clause(s) of the rule are missing. The metrics include a primary measure denoted the rule completeness metric (RCM) plus a number of subsidiary measures that contribute to the RCM. The RCM is derived from an analysis of a rule with respect to its truth and a measure of the completeness of its input data. The derivation is such that the truth value of an antecedent is independent of the measure of its completeness. The RCM can be used to compare the degree of completeness of two or more rules with respect to a given set of data. Hence, the RCM can be used as a guide to choosing among rules during the rule-selection phase of operation of the artificial-intelligence system..

Developing a modular architecture for creation of rule-based clinical diagnostic criteria.

PubMed

Hong, Na; Pathak, Jyotishman; Chute, Christopher G; Jiang, Guoqian

2016-01-01

With recent advances in computerized patient records system, there is an urgent need for producing computable and standards-based clinical diagnostic criteria. Notably, constructing rule-based clinical diagnosis criteria has become one of the goals in the International Classification of Diseases (ICD)-11 revision. However, few studies have been done in building a unified architecture to support the need for diagnostic criteria computerization. In this study, we present a modular architecture for enabling the creation of rule-based clinical diagnostic criteria leveraging Semantic Web technologies. The architecture consists of two modules: an authoring module that utilizes a standards-based information model and a translation module that leverages Semantic Web Rule Language (SWRL). In a prototype implementation, we created a diagnostic criteria upper ontology (DCUO) that integrates ICD-11 content model with the Quality Data Model (QDM). Using the DCUO, we developed a transformation tool that converts QDM-based diagnostic criteria into Semantic Web Rule Language (SWRL) representation. We evaluated the domain coverage of the upper ontology model using randomly selected diagnostic criteria from broad domains (n = 20). We also tested the transformation algorithms using 6 QDM templates for ontology population and 15 QDM-based criteria data for rule generation. As the results, the first draft of DCUO contains 14 root classes, 21 subclasses, 6 object properties and 1 data property. Investigation Findings, and Signs and Symptoms are the two most commonly used element types. All 6 HQMF templates are successfully parsed and populated into their corresponding domain specific ontologies and 14 rules (93.3 %) passed the rule validation. Our efforts in developing and prototyping a modular architecture provide useful insight into how to build a scalable solution to support diagnostic criteria representation and computerization.

78 FR 6385 - Self-Regulatory Organizations; NYSE Arca, Inc.; Order Approving a Proposed Rule Change Amending...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-01-30

... Rule 7.31(h)(7) To Permit PL Select Orders To Interact With Incoming Orders Larger Than the Size of the PL Select Order January 24, 2013. I. Introduction On November 27, 2012, NYSE Arca, Inc. (``Exchange... proposed rule change to amend NYSE Arca Equities Rule 7.31(h)(7) to permit PL Select Orders to interact...

Confirming a predicted selection rule in inelastic neutron scattering spectroscopy: the quantum translator-rotator H2 entrapped inside C60.

PubMed

Xu, Minzhong; Jiménez-Ruiz, Mónica; Johnson, Mark R; Rols, Stéphane; Ye, Shufeng; Carravetta, Marina; Denning, Mark S; Lei, Xuegong; Bačić, Zlatko; Horsewill, Anthony J

2014-09-19

We report an inelastic neutron scattering (INS) study of a H2 molecule encapsulated inside the fullerene C60 which confirms the recently predicted selection rule, the first to be established for the INS spectroscopy of aperiodic, discrete molecular compounds. Several transitions from the ground state of para-H2 to certain excited translation-rotation states, forbidden according to the selection rule, are systematically absent from the INS spectra, thus validating the selection rule with a high degree of confidence. Its confirmation sets a precedent, as it runs counter to the widely held view that the INS spectroscopy of molecular compounds is not subject to any selection rules.

Strategies of marine dinoflagellate survival and some rules of assembly

NASA Astrophysics Data System (ADS)

Smayda, Theodore J.; Reynolds, Colin S.

2003-03-01

Dinoflagellate ecology is based on multiple adaptive strategies and species having diverse habitat preferences. Nine types of mixing-irradiance-nutrient habitats selecting for specific marine dinoflagellate life-form types are recognised, with five rules of assembly proposed to govern bloom-species selection and community organisation within these habitats. Assembly is moulded around an abiotic template of light energy, nutrient supply and physical mixing in permutative combinations. Species selected will have one of three basic ( C-, S-, R-) strategies: colonist species ( C-) which predominate in chemically disturbed habitats; nutrient stress tolerant species ( S-), and species ( R-) tolerant of shear/stress forces in physically disturbed water masses. This organisational plan of three major habitat variables and three major adaptive strategies is termed the 3-3 plan. The bloom behaviour and habitat specialisation of dinoflagellates and diatoms are compared. Dinoflagellates behave as annual species, bloom soloists, are ecophysiologically diverse, and habitat specialists whose blooms tend to be monospecific. Diatoms behave as perennial species, guild members, are habitat cosmopolites, have a relatively uniform bloom strategy based on species-rich pools and exhibit limited habitat specialisation. Dinoflagellate bloom-species selection follows a taxonomic hierarchical pathway which progresses from phylogenetic to generic to species selection, and in that sequence. Each hierarchical taxonomic level has its own adaptive requirements subject to rules of assembly. Dinoflagellates would appear to be well suited to exploit marine habitats and to be competitive with other phylogenetic groups, yet fail to do so.

Constructing Compact Takagi-Sugeno Rule Systems: Identification of Complex Interactions in Epidemiological Data

PubMed Central

Zhou, Shang-Ming; Lyons, Ronan A.; Brophy, Sinead; Gravenor, Mike B.

2012-01-01

The Takagi-Sugeno (TS) fuzzy rule system is a widely used data mining technique, and is of particular use in the identification of non-linear interactions between variables. However the number of rules increases dramatically when applied to high dimensional data sets (the curse of dimensionality). Few robust methods are available to identify important rules while removing redundant ones, and this results in limited applicability in fields such as epidemiology or bioinformatics where the interaction of many variables must be considered. Here, we develop a new parsimonious TS rule system. We propose three statistics: R, L, and ω-values, to rank the importance of each TS rule, and a forward selection procedure to construct a final model. We use our method to predict how key components of childhood deprivation combine to influence educational achievement outcome. We show that a parsimonious TS model can be constructed, based on a small subset of rules, that provides an accurate description of the relationship between deprivation indices and educational outcomes. The selected rules shed light on the synergistic relationships between the variables, and reveal that the effect of targeting specific domains of deprivation is crucially dependent on the state of the other domains. Policy decisions need to incorporate these interactions, and deprivation indices should not be considered in isolation. The TS rule system provides a basis for such decision making, and has wide applicability for the identification of non-linear interactions in complex biomedical data. PMID:23272108

Constructing compact Takagi-Sugeno rule systems: identification of complex interactions in epidemiological data.

PubMed

Zhou, Shang-Ming; Lyons, Ronan A; Brophy, Sinead; Gravenor, Mike B

2012-01-01

The Takagi-Sugeno (TS) fuzzy rule system is a widely used data mining technique, and is of particular use in the identification of non-linear interactions between variables. However the number of rules increases dramatically when applied to high dimensional data sets (the curse of dimensionality). Few robust methods are available to identify important rules while removing redundant ones, and this results in limited applicability in fields such as epidemiology or bioinformatics where the interaction of many variables must be considered. Here, we develop a new parsimonious TS rule system. We propose three statistics: R, L, and ω-values, to rank the importance of each TS rule, and a forward selection procedure to construct a final model. We use our method to predict how key components of childhood deprivation combine to influence educational achievement outcome. We show that a parsimonious TS model can be constructed, based on a small subset of rules, that provides an accurate description of the relationship between deprivation indices and educational outcomes. The selected rules shed light on the synergistic relationships between the variables, and reveal that the effect of targeting specific domains of deprivation is crucially dependent on the state of the other domains. Policy decisions need to incorporate these interactions, and deprivation indices should not be considered in isolation. The TS rule system provides a basis for such decision making, and has wide applicability for the identification of non-linear interactions in complex biomedical data.

Evaluation of a multi-arm multi-stage Bayesian design for phase II drug selection trials - an example in hemato-oncology.

PubMed

Jacob, Louis; Uvarova, Maria; Boulet, Sandrine; Begaj, Inva; Chevret, Sylvie

2016-06-02

Multi-Arm Multi-Stage designs aim at comparing several new treatments to a common reference, in order to select or drop any treatment arm to move forward when such evidence already exists based on interim analyses. We redesigned a Bayesian adaptive design initially proposed for dose-finding, focusing our interest in the comparison of multiple experimental drugs to a control on a binary criterion measure. We redesigned a phase II clinical trial that randomly allocates patients across three (one control and two experimental) treatment arms to assess dropping decision rules. We were interested in dropping any arm due to futility, either based on historical control rate (first rule) or comparison across arms (second rule), and in stopping experimental arm due to its ability to reach a sufficient response rate (third rule), using the difference of response probabilities in Bayes binomial trials between the treated and control as a measure of treatment benefit. Simulations were then conducted to investigate the decision operating characteristics under a variety of plausible scenarios, as a function of the decision thresholds. Our findings suggest that one experimental treatment was less efficient than the control and could have been dropped from the trial based on a sample of approximately 20 instead of 40 patients. In the simulation study, stopping decisions were reached sooner for the first rule than for the second rule, with close mean estimates of response rates and small bias. According to the decision threshold, the mean sample size to detect the required 0.15 absolute benefit ranged from 63 to 70 (rule 3) with false negative rates of less than 2 % (rule 1) up to 6 % (rule 2). In contrast, detecting a 0.15 inferiority in response rates required a sample size ranging on average from 23 to 35 (rules 1 and 2, respectively) with a false positive rate ranging from 3.6 to 0.6 % (rule 3). Adaptive trial design is a good way to improve clinical trials. It allows removing ineffective drugs and reducing the trial sample size, while maintaining unbiased estimates. Decision thresholds can be set according to predefined fixed error decision rates. ClinicalTrials.gov Identifier: NCT01342692 .

Inference of combinatorial Boolean rules of synergistic gene sets from cancer microarray datasets.

PubMed

Park, Inho; Lee, Kwang H; Lee, Doheon

2010-06-15

Gene set analysis has become an important tool for the functional interpretation of high-throughput gene expression datasets. Moreover, pattern analyses based on inferred gene set activities of individual samples have shown the ability to identify more robust disease signatures than individual gene-based pattern analyses. Although a number of approaches have been proposed for gene set-based pattern analysis, the combinatorial influence of deregulated gene sets on disease phenotype classification has not been studied sufficiently. We propose a new approach for inferring combinatorial Boolean rules of gene sets for a better understanding of cancer transcriptome and cancer classification. To reduce the search space of the possible Boolean rules, we identify small groups of gene sets that synergistically contribute to the classification of samples into their corresponding phenotypic groups (such as normal and cancer). We then measure the significance of the candidate Boolean rules derived from each group of gene sets; the level of significance is based on the class entropy of the samples selected in accordance with the rules. By applying the present approach to publicly available prostate cancer datasets, we identified 72 significant Boolean rules. Finally, we discuss several identified Boolean rules, such as the rule of glutathione metabolism (down) and prostaglandin synthesis regulation (down), which are consistent with known prostate cancer biology. Scripts written in Python and R are available at http://biosoft.kaist.ac.kr/~ihpark/. The refined gene sets and the full list of the identified Boolean rules are provided in the Supplementary Material. Supplementary data are available at Bioinformatics online.

Modifying Rules of a Regular Girls Softball League to Facilitate the Inclusion of a Child with Severe Disabilities.

ERIC Educational Resources Information Center

Bernabe, Elaine A.; Block, Martin E.

1994-01-01

Coaches and players were assisted in modifying select rules of a girls' fast-pitch softball league so as to accommodate the skill limitations of a player with moderate to severe disabilities. The girl's batting average and on-base average indicated that modifications were effective. The player was well received by her teammates and other teams.…

Self-interested agents create, maintain, and modify group-functional culture.

PubMed

Singh, Manvir; Glowacki, Luke; Wrangham, Richard W

2016-01-01

We agree that institutions and rules are crucial for explaining human sociality, but we question the claim of there not being "alternatives to CGS [that] can easily account for the institutionalized cooperation that characterizes human societies" (target article, sect. 7). Hypothesizing that self-interested individuals coercively and collaboratively create rules, we propose that agent-based hypotheses offer viable alternatives to cultural group selection (CGS).

A Bayesian model averaging method for the derivation of reservoir operating rules

NASA Astrophysics Data System (ADS)

Zhang, Jingwen; Liu, Pan; Wang, Hao; Lei, Xiaohui; Zhou, Yanlai

2015-09-01

Because the intrinsic dynamics among optimal decision making, inflow processes and reservoir characteristics are complex, functional forms of reservoir operating rules are always determined subjectively. As a result, the uncertainty of selecting form and/or model involved in reservoir operating rules must be analyzed and evaluated. In this study, we analyze the uncertainty of reservoir operating rules using the Bayesian model averaging (BMA) model. Three popular operating rules, namely piecewise linear regression, surface fitting and a least-squares support vector machine, are established based on the optimal deterministic reservoir operation. These individual models provide three-member decisions for the BMA combination, enabling the 90% release interval to be estimated by the Markov Chain Monte Carlo simulation. A case study of China's the Baise reservoir shows that: (1) the optimal deterministic reservoir operation, superior to any reservoir operating rules, is used as the samples to derive the rules; (2) the least-squares support vector machine model is more effective than both piecewise linear regression and surface fitting; (3) BMA outperforms any individual model of operating rules based on the optimal trajectories. It is revealed that the proposed model can reduce the uncertainty of operating rules, which is of great potential benefit in evaluating the confidence interval of decisions.

Affect-Aware Adaptive Tutoring Based on Human-Automation Etiquette Strategies.

PubMed

Yang, Euijung; Dorneich, Michael C

2018-06-01

We investigated adapting the interaction style of intelligent tutoring system (ITS) feedback based on human-automation etiquette strategies. Most ITSs adapt the content difficulty level, adapt the feedback timing, or provide extra content when they detect cognitive or affective decrements. Our previous work demonstrated that changing the interaction style via different feedback etiquette strategies has differential effects on students' motivation, confidence, satisfaction, and performance. The best etiquette strategy was also determined by user frustration. Based on these findings, a rule set was developed that systemically selected the proper etiquette strategy to address one of four learning factors (motivation, confidence, satisfaction, and performance) under two different levels of user frustration. We explored whether etiquette strategy selection based on this rule set (systematic) or random changes in etiquette strategy for a given level of frustration affected the four learning factors. Participants solved mathematics problems under different frustration conditions with feedback that adapted dynamic changes in etiquette strategies either systematically or randomly. The results demonstrated that feedback with etiquette strategies chosen systematically via the rule set could selectively target and improve motivation, confidence, satisfaction, and performance more than changing etiquette strategies randomly. The systematic adaptation was effective no matter the level of frustration for the participant. If computer tutors can vary the interaction style to effectively mitigate negative emotions, then ITS designers would have one more mechanism in which to design affect-aware adaptations that provide the proper responses in situations where human emotions affect the ability to learn.

Complex Dynamics of Droplet Traffic in a Bifurcating Microfluidic Channel: Periodicity, Multistability, and Selection Rules

NASA Astrophysics Data System (ADS)

Sessoms, D. A.; Amon, A.; Courbin, L.; Panizza, P.

2010-10-01

The binary path selection of droplets reaching a T junction is regulated by time-delayed feedback and nonlinear couplings. Such mechanisms result in complex dynamics of droplet partitioning: numerous discrete bifurcations between periodic regimes are observed. We introduce a model based on an approximation that makes this problem tractable. This allows us to derive analytical formulae that predict the occurrence of the bifurcations between consecutive regimes, establish selection rules for the period of a regime, and describe the evolutions of the period and complexity of droplet pattern in a cycle with the key parameters of the system. We discuss the validity and limitations of our model which describes semiquantitatively both numerical simulations and microfluidic experiments.

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.

Is cooperation viable in mobile organisms? Simple Walk Away rule favors the evolution of cooperation in groups

PubMed Central

Aktipis, C. Athena

2011-01-01

The evolution of cooperation through partner choice mechanisms is often thought to involve relatively complex cognitive abilities. Using agent-based simulations I model a simple partner choice rule, the ‘Walk Away’ rule, where individuals stay in groups that provide higher returns (by virtue of having more cooperators), and ‘Walk Away’ from groups providing low returns. Implementing this conditional movement rule in a public goods game leads to a number of interesting findings: 1) cooperators have a selective advantage when thresholds are high, corresponding to low tolerance for defectors, 2) high thresholds lead to high initial rates of movement and low final rates of movement (after selection), and 3) as cooperation is selected, the population undergoes a spatial transition from high migration (and a many small and ephemeral groups) to low migration (and large and stable groups). These results suggest that the very simple ‘Walk Away’ rule of leaving uncooperative groups can favor the evolution of cooperation, and that cooperation can evolve in populations in which individuals are able to move in response to local social conditions. A diverse array of organisms are able to leave degraded physical or social environments. The ubiquitous nature of conditional movement suggests that ‘Walk Away’ dynamics may play an important role in the evolution of social behavior in both cognitively complex and cognitively simple organisms. PMID:21666771

77 FR 34115 - Self-Regulatory Organizations; NYSE Arca, Inc.; Notice of Filing of Proposed Rule Change Amending...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-06-08

... Equities Rule 7.31(h) To Add a PL Select Order Type June 4, 2012. Pursuant to Section 19(b)(1) of the... Change The Exchange proposes to amend NYSE Arca Equities Rule 7.31(h) to add a PL Select Order type. The... add a PL Select Order type. Pursuant to NYSE Arca Equities Rule 7.31(h)(4), a Passive Liquidity (``PL...

The impact of egocentric vs. allocentric agency attributions on the neural bases of reasoning about social rules.

PubMed

Canessa, Nicola; Pantaleo, Giuseppe; Crespi, Chiara; Gorini, Alessandra; Cappa, Stefano F

2014-09-18

We used the "standard" and "switched" social contract versions of the Wason Selection-task to investigate the neural bases of human reasoning about social rules. Both these versions typically elicit the deontically correct answer, i.e. the proper identification of the violations of a conditional obligation. Only in the standard version of the task, however, this response corresponds to the logically correct one. We took advantage of this differential adherence to logical vs. deontical accuracy to test the different predictions of logic rule-based vs. visuospatial accounts of inferential abilities in 14 participants who solved the standard and switched versions of the Selection-task during functional-Magnetic-Resonance-Imaging. Both versions activated the well known left fronto-parietal network of deductive reasoning. The standard version additionally recruited the medial parietal and right inferior parietal cortex, previously associated with mental imagery and with the adoption of egocentric vs. allocentric spatial reference frames. These results suggest that visuospatial processes encoding one's own subjective experience in social interactions may support and shape the interpretation of deductive arguments and/or the resulting inferences, thus contributing to elicit content effects in human reasoning. Copyright © 2014 Elsevier B.V. All rights reserved.

Selection of the distributional rule as an alternative tool to foster cooperation in a Public Good Game

NASA Astrophysics Data System (ADS)

Colasante, Annarita

2017-02-01

This paper presents an investigation about cooperation in a Public Good Game using an Agent Based Model calibrated on experimental data. Starting from the experiment proposed in Colasante and Russo (2016), we analyze the dynamic of cooperation in a Public Good Game where agents receive an heterogeneous income and choose both the level of contribution and the distribution rule. The starting point is the calibration and the output validation of the model using the experimental results. Once tested the goodness of fit of the Agent Based Model, we run some policy experiment in order to verify how each distribution rule, i.e. equidistribution, proportional to contribution and progressive, affects the level of contribution in the simulated model. We find out that the share of cooperators decreases over time if we exogenously set the equidistribution rule. On the contrary, the share of cooperators converges to 100 % if we impose the progressive rule. Finally, the most interesting result refers to the effect of the progressive rule. We observe that, in the case of high inequality, this rule is not able to reduce the heterogeneity of income.

Pillars of judgment: how memory abilities affect performance in rule-based and exemplar-based judgments.

PubMed

Hoffmann, Janina A; von Helversen, Bettina; Rieskamp, Jörg

2014-12-01

Making accurate judgments is an essential skill in everyday life. Although how different memory abilities relate to categorization and judgment processes has been hotly debated, the question is far from resolved. We contribute to the solution by investigating how individual differences in memory abilities affect judgment performance in 2 tasks that induced rule-based or exemplar-based judgment strategies. In a study with 279 participants, we investigated how working memory and episodic memory affect judgment accuracy and strategy use. As predicted, participants switched strategies between tasks. Furthermore, structural equation modeling showed that the ability to solve rule-based tasks was predicted by working memory, whereas episodic memory predicted judgment accuracy in the exemplar-based task. Last, the probability of choosing an exemplar-based strategy was related to better episodic memory, but strategy selection was unrelated to working memory capacity. In sum, our results suggest that different memory abilities are essential for successfully adopting different judgment strategies. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Development of a New Departure Aversion Standard for Light Aircraft

NASA Technical Reports Server (NTRS)

Borer, Nicholas K.

2017-01-01

The Federal Aviation Administration (FAA) and European Aviation Safety Agency (EASA) have recently established new light aircraft certification rules that introduce significant changes to the current regulations. The changes include moving from prescriptive design requirements to performance-based standards, transferring many of the acceptable means of compliance out of the rules and into consensus standards. In addition, the FAA/EASA rules change the performance requirements associated with some of the more salient safety issues regarding light aircraft. One significant change is the elimination of spin recovery demonstration. The new rules now call for enhanced stall warning and aircraft handling characteristics that demonstrate resistance to inadvertent departure from controlled flight. The means of compliance with these changes in a safe, cost-effective manner is a challenging problem. This paper discusses existing approaches to reducing the likelihood of departure from controlled flight and introduces a new approach, dubbed Departure Aversion, which allows applicants to tailor the amount of departure resistance, stall warning, and enhanced safety equipment to meet the new proposed rules. The Departure Aversion approach gives applicants the freedom to select the most cost-effective portfolio for their design, while meeting the safety intent of the new rules, by ensuring that any combination of the selected approaches will be at a higher equivalent level of safety than today's status quo.

The effect of multiple primary rules on population-based cancer survival

PubMed Central

Weir, Hannah K.; Johnson, Christopher J.; Thompson, Trevor D.

2015-01-01

Purpose Different rules for registering multiple primary (MP) cancers are used by cancer registries throughout the world, making international data comparisons difficult. This study evaluates the effect of Surveillance, Epidemiology, and End Results (SEER) and International Association of Cancer Registries (IACR) MP rules on population-based cancer survival estimates. Methods Data from five US states and six metropolitan area cancer registries participating in the SEER Program were used to estimate age-standardized relative survival (RS%) for first cancers-only and all first cancers matching the selection criteria according to SEER and IACR MP rules for all cancer sites combined and for the top 25 cancer site groups among men and women. Results During 1995–2008, the percentage of MP cancers (all sites, both sexes) increased 25.4 % by using SEER rules (from 14.6 to 18.4 %) and 20.1 % by using IACR rules (from 13.2 to 15.8 %). More MP cancers were registered among females than among males, and SEER rules registered more MP cancers than IACR rules (15.8 vs. 14.4 % among males; 17.2 vs. 14.5 % among females). The top 3 cancer sites with the largest differences were melanoma (5.8 %), urinary bladder (3.5 %), and kidney and renal pelvis (2.9 %) among males, and breast (5.9 %), melanoma (3.9 %), and urinary bladder (3.4 %) among females. Five-year survival estimates (all sites combined) restricted to first primary cancers-only were higher than estimates by using first site-specific primaries (SEER or IACR rules), and for 11 of 21 sites among males and 11 of 23 sites among females. SEER estimates are comparable to IACR estimates for all site-specific cancers and marginally higher for all sites combined among females (RS 62.28 vs. 61.96 %). Conclusion Survival after diagnosis has improved for many leading cancers. However, cancer patients remain at risk of subsequent cancers. Survival estimates based on first cancers-only exclude a large and increasing number of MP cancers. To produce clinically and epidemiologically relevant and less biased cancer survival estimates, data on all cancers should be included in the analysis. The multiple primary rules (SEER or IACR) used to identify primary cancers do not affect survival estimates if all first cancers matching the selection criteria are used to produce site-specific survival estimates. PMID:23558444

Simulation Of Combat With An Expert System

NASA Technical Reports Server (NTRS)

Provenzano, J. P.

1989-01-01

Proposed expert system predicts outcomes of combat situations. Called "COBRA", combat outcome based on rules for attrition, system selects rules for mathematical modeling of losses and discrete events in combat according to previous experiences. Used with another software module known as the "Game". Game/COBRA software system, consisting of Game and COBRA modules, provides for both quantitative aspects and qualitative aspects in simulations of battles. COBRA intended for simulation of large-scale military exercises, concepts embodied in it have much broader applicability. In industrial research, knowledge-based system enables qualitative as well as quantitative simulations.

Teaching the Spin Selection Rule: An Inductive Approach

ERIC Educational Resources Information Center

Halstead, Judith A.

2013-01-01

In the group exercise described, students are guided through an inductive justification for the spin conservation selection rule ([delta]S = 0). Although the exercise only explicitly involves various states of helium, the conclusion is one of the most widely applicable selection rules for the interaction of light with matter, applying, in various…

The Effect of a History-Fitness Updating Rule on Evolutionary Games

NASA Astrophysics Data System (ADS)

Du, Wen-Bo; Cao, Xian-Bin; Liu, Run-Ran; Jia, Chun-Xiao

In this paper, we introduce a history-fitness-based updating rule into the evolutionary prisoner's dilemma game (PDG) on square lattices, and study how it works on the evolution of cooperation level. Under this updating rule, the player i will firstly select player j from its direct neighbors at random and then compare their fitness which is determined by the current payoff and history fitness. If player i's fitness is larger than that of j, player i will be more likely to keep its own strategy. Numerical results show that the cooperation level is remarkably promoted by the history-fitness-based updating rule. Moreover, there exists a moderate mixing proportion of current payoff and history fitness that can induce the optimal fitness, where the highest cooperation level is obtained. Our work may shed some new light on the ubiquitous cooperative behaviors in nature and society induced by the history factor.

Intraband magneto-optical absorption in InAs/GaAs quantum dots: Orbital Zeeman splitting and the Thomas-Reiche-Kuhn sum rule

NASA Astrophysics Data System (ADS)

Zhang, J.-Z.; Galbraith, I.

2008-05-01

Using perturbation theory, intraband magneto-optical absorption is calculated for InAs/GaAs truncated pyramidal quantum dots in a magnetic field applied parallel to the growth direction z . The effects of the magnetic field on the electronic states as well as the intraband transitions are systematically studied. Selection rules governing the intraband transitions are discussed based on the symmetry properties of the electronic states. While the broadband z -polarized absorption is almost insensitive to the magnetic field, the orbital Zeeman splitting is the dominant feature in the in-plane polarized spectrum. Strong in-plane polarized magneto-absorption features are located in the far-infrared region, while z -polarized absorption occurs at higher frequencies. This is due to the dot geometry (the base length is much larger than the height) yielding different quantum confinement in the vertical and lateral directions. The Thomas-Reiche-Kuhn sum rule, including the magnetic field effect, is applied together with the selection rules to the absorption spectra. The orbital Zeeman splitting depends on both the dot size and the confining potential—the splitting decreases as the dot size or the confining potential decreases. Our calculated Zeeman splittings are in agreement with experimental data.

Integrated modelling of stormwater treatment systems uptake.

PubMed

Castonguay, A C; Iftekhar, M S; Urich, C; Bach, P M; Deletic, A

2018-05-24

Nature-based solutions provide a variety of benefits in growing cities, ranging from stormwater treatment to amenity provision such as aesthetics. However, the decision-making process involved in the installation of such green infrastructure is not straightforward, as much uncertainty around the location, size, costs and benefits impedes systematic decision-making. We developed a model to simulate decision rules used by local municipalities to install nature-based stormwater treatment systems, namely constructed wetlands, ponds/basins and raingardens. The model was used to test twenty-four scenarios of policy-making, by combining four asset selection, two location selection and three budget constraint decision rules. Based on the case study of a local municipality in Metropolitan Melbourne, Australia, the modelled uptake of stormwater treatment systems was compared with attributes of real-world systems for the simulation period. Results show that the actual budgeted funding is not reliable to predict systems' uptake and that policy-makers are more likely to plan expenditures based on installation costs. The model was able to replicate the cumulative treatment capacity and the location of systems. As such, it offers a novel approach to investigate the impact of using different decision rules to provide environmental services considering biophysical and economic factors. Copyright © 2018 Elsevier Ltd. All rights reserved.

Genetic reinforcement learning through symbiotic evolution for fuzzy controller design.

PubMed

Juang, C F; Lin, J Y; Lin, C T

2000-01-01

An efficient genetic reinforcement learning algorithm for designing fuzzy controllers is proposed in this paper. The genetic algorithm (GA) adopted in this paper is based upon symbiotic evolution which, when applied to fuzzy controller design, complements the local mapping property of a fuzzy rule. Using this Symbiotic-Evolution-based Fuzzy Controller (SEFC) design method, the number of control trials, as well as consumed CPU time, are considerably reduced when compared to traditional GA-based fuzzy controller design methods and other types of genetic reinforcement learning schemes. Moreover, unlike traditional fuzzy controllers, which partition the input space into a grid, SEFC partitions the input space in a flexible way, thus creating fewer fuzzy rules. In SEFC, different types of fuzzy rules whose consequent parts are singletons, fuzzy sets, or linear equations (TSK-type fuzzy rules) are allowed. Further, the free parameters (e.g., centers and widths of membership functions) and fuzzy rules are all tuned automatically. For the TSK-type fuzzy rule especially, which put the proposed learning algorithm in use, only the significant input variables are selected to participate in the consequent of a rule. The proposed SEFC design method has been applied to different simulated control problems, including the cart-pole balancing system, a magnetic levitation system, and a water bath temperature control system. The proposed SEFC has been verified to be efficient and superior from these control problems, and from comparisons with some traditional GA-based fuzzy systems.

Ontology-Based Method for Fault Diagnosis of Loaders.

PubMed

Xu, Feixiang; Liu, Xinhui; Chen, Wei; Zhou, Chen; Cao, Bingwei

2018-02-28

This paper proposes an ontology-based fault diagnosis method which overcomes the difficulty of understanding complex fault diagnosis knowledge of loaders and offers a universal approach for fault diagnosis of all loaders. This method contains the following components: (1) An ontology-based fault diagnosis model is proposed to achieve the integrating, sharing and reusing of fault diagnosis knowledge for loaders; (2) combined with ontology, CBR (case-based reasoning) is introduced to realize effective and accurate fault diagnoses following four steps (feature selection, case-retrieval, case-matching and case-updating); and (3) in order to cover the shortages of the CBR method due to the lack of concerned cases, ontology based RBR (rule-based reasoning) is put forward through building SWRL (Semantic Web Rule Language) rules. An application program is also developed to implement the above methods to assist in finding the fault causes, fault locations and maintenance measures of loaders. In addition, the program is validated through analyzing a case study.

Ontology-Based Method for Fault Diagnosis of Loaders

PubMed Central

Liu, Xinhui; Chen, Wei; Zhou, Chen; Cao, Bingwei

2018-01-01

This paper proposes an ontology-based fault diagnosis method which overcomes the difficulty of understanding complex fault diagnosis knowledge of loaders and offers a universal approach for fault diagnosis of all loaders. This method contains the following components: (1) An ontology-based fault diagnosis model is proposed to achieve the integrating, sharing and reusing of fault diagnosis knowledge for loaders; (2) combined with ontology, CBR (case-based reasoning) is introduced to realize effective and accurate fault diagnoses following four steps (feature selection, case-retrieval, case-matching and case-updating); and (3) in order to cover the shortages of the CBR method due to the lack of concerned cases, ontology based RBR (rule-based reasoning) is put forward through building SWRL (Semantic Web Rule Language) rules. An application program is also developed to implement the above methods to assist in finding the fault causes, fault locations and maintenance measures of loaders. In addition, the program is validated through analyzing a case study. PMID:29495646

Application of Adaptive Design Methodology in Development of a Long-Acting Glucagon-Like Peptide-1 Analog (Dulaglutide): Statistical Design and Simulations

PubMed Central

Skrivanek, Zachary; Berry, Scott; Berry, Don; Chien, Jenny; Geiger, Mary Jane; Anderson, James H.; Gaydos, Brenda

2012-01-01

Background Dulaglutide (dula, LY2189265), a long-acting glucagon-like peptide-1 analog, is being developed to treat type 2 diabetes mellitus. Methods To foster the development of dula, we designed a two-stage adaptive, dose-finding, inferentially seamless phase 2/3 study. The Bayesian theoretical framework is used to adaptively randomize patients in stage 1 to 7 dula doses and, at the decision point, to either stop for futility or to select up to 2 dula doses for stage 2. After dose selection, patients continue to be randomized to the selected dula doses or comparator arms. Data from patients assigned the selected doses will be pooled across both stages and analyzed with an analysis of covariance model, using baseline hemoglobin A1c and country as covariates. The operating characteristics of the trial were assessed by extensive simulation studies. Results Simulations demonstrated that the adaptive design would identify the correct doses 88% of the time, compared to as low as 6% for a fixed-dose design (the latter value based on frequentist decision rules analogous to the Bayesian decision rules for adaptive design). Conclusions This article discusses the decision rules used to select the dula dose(s); the mathematical details of the adaptive algorithm—including a description of the clinical utility index used to mathematically quantify the desirability of a dose based on safety and efficacy measurements; and a description of the simulation process and results that quantify the operating characteristics of the design. PMID:23294775

76 FR 4144 - Self-Regulatory Organizations; Notice of Filing and Immediate Effectiveness of Proposed Rule...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-01-24

... PHLX LLC Relating to Rebates and Fees for Adding and Removing Liquidity in Select Symbols January 14... Terms of Substance of the Proposed Rule Change The Exchange proposes to amend the Select Symbols in... Select Symbols. The text of the proposed rule change is available on the Exchange's Web site at http...

ORTHO-PARA SELECTION RULES IN THE GAS-PHASE CHEMISTRY OF INTERSTELLAR AMMONIA

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

Faure, A.; Hily-Blant, P.; Le Gal, R.

The ortho-para chemistry of ammonia in the cold interstellar medium is investigated using a gas-phase chemical network. Branching ratios for the primary reaction chain involved in the formation and destruction of ortho- and para-NH{sub 3} were derived using angular momentum rules based on the conservation of the nuclear spin. We show that the 'anomalous' ortho-to-para ratio of ammonia ({approx}0.7) observed in various interstellar regions is in fact consistent with nuclear spin selection rules in a para-enriched H{sub 2} gas. This ratio is found to be independent of temperature in the range 5-30 K. We also predict an ortho-to-para ratio ofmore » {approx}2.3 for NH{sub 2}. We conclude that a low ortho-to-para ratio of H{sub 2} naturally drives the ortho-to-para ratios of nitrogen hydrides below the statistical values.« less

Age-Related Brain Activation Changes during Rule Repetition in Word-Matching.

PubMed

Methqal, Ikram; Pinsard, Basile; Amiri, Mahnoush; Wilson, Maximiliano A; Monchi, Oury; Provost, Jean-Sebastien; Joanette, Yves

2017-01-01

Objective: The purpose of this study was to explore the age-related brain activation changes during a word-matching semantic-category-based task, which required either repeating or changing a semantic rule to be applied. In order to do so, a word-semantic rule-based task was adapted from the Wisconsin Sorting Card Test, involving the repeated feedback-driven selection of given pairs of words based on semantic category-based criteria. Method: Forty healthy adults (20 younger and 20 older) performed a word-matching task while undergoing a fMRI scan in which they were required to pair a target word with another word from a group of three words. The required pairing is based on three word-pair semantic rules which correspond to different levels of semantic control demands: functional relatedness, moderately typical-relatedness (which were considered as low control demands), and atypical-relatedness (high control demands). The sorting period consisted of a continuous execution of the same sorting rule and an inferred trial-by-trial feedback was given. Results: Behavioral performance revealed increases in response times and decreases of correct responses according to the level of semantic control demands (functional vs. typical vs. atypical) for both age groups (younger and older) reflecting graded differences in the repetition of the application of a given semantic rule. Neuroimaging findings of significant brain activation showed two main results: (1) Greater task-related activation changes for the repetition of the application of atypical rules relative to typical and functional rules, and (2) Changes (older > younger) in the inferior prefrontal regions for functional rules and more extensive and bilateral activations for typical and atypical rules. Regarding the inter-semantic rules comparison, only task-related activation differences were observed for functional > typical (e.g., inferior parietal and temporal regions bilaterally) and atypical > typical (e.g., prefrontal, inferior parietal, posterior temporal, and subcortical regions). Conclusion: These results suggest that healthy cognitive aging relies on the adaptive changes of inferior prefrontal resources involved in the repetitive execution of semantic rules, thus reflecting graded differences in support of task demands.

A Flexible Mechanism of Rule Selection Enables Rapid Feature-Based Reinforcement Learning

PubMed Central

Balcarras, Matthew; Womelsdorf, Thilo

2016-01-01

Learning in a new environment is influenced by prior learning and experience. Correctly applying a rule that maps a context to stimuli, actions, and outcomes enables faster learning and better outcomes compared to relying on strategies for learning that are ignorant of task structure. However, it is often difficult to know when and how to apply learned rules in new contexts. In our study we explored how subjects employ different strategies for learning the relationship between stimulus features and positive outcomes in a probabilistic task context. We test the hypothesis that task naive subjects will show enhanced learning of feature specific reward associations by switching to the use of an abstract rule that associates stimuli by feature type and restricts selections to that dimension. To test this hypothesis we designed a decision making task where subjects receive probabilistic feedback following choices between pairs of stimuli. In the task, trials are grouped in two contexts by blocks, where in one type of block there is no unique relationship between a specific feature dimension (stimulus shape or color) and positive outcomes, and following an un-cued transition, alternating blocks have outcomes that are linked to either stimulus shape or color. Two-thirds of subjects (n = 22/32) exhibited behavior that was best fit by a hierarchical feature-rule model. Supporting the prediction of the model mechanism these subjects showed significantly enhanced performance in feature-reward blocks, and rapidly switched their choice strategy to using abstract feature rules when reward contingencies changed. Choice behavior of other subjects (n = 10/32) was fit by a range of alternative reinforcement learning models representing strategies that do not benefit from applying previously learned rules. In summary, these results show that untrained subjects are capable of flexibly shifting between behavioral rules by leveraging simple model-free reinforcement learning and context-specific selections to drive responses. PMID:27064794

Polarized excitons and optical activity in single-wall carbon nanotubes

NASA Astrophysics Data System (ADS)

Chang, Yao-Wen; Jin, Bih-Yaw

2018-05-01

The polarized excitons and optical activity of single-wall carbon nanotubes (SWNTs) are studied theoretically by π -electron Hamiltonian and helical-rotational symmetry. By taking advantage of the symmetrization, the single-particle energy and properties of a SWNT are characterized with the corresponding helical band structure. The dipole-moment matrix elements, magnetic-moment matrix elements, and the selection rules can also be derived. Based on different selection rules, the optical transitions can be assigned as the parallel-polarized, left-handed circularly-polarized, and right-handed circularly-polarized transitions, where the combination of the last two gives the cross-polarized transition. The absorption and circular dichroism (CD) spectra are simulated by exciton calculation. The calculated results are well comparable with the reported measurements. Built on the foundation, magnetic-field effects on the polarized excitons and optical activity of SWNTs are studied. Dark-bright exciton splitting and interband Faraday effect in the CD spectrum of SWNTs under an axial magnetic field are predicted. The Faraday rotation dispersion can be analyzed according to the selection rules of circular polarizations and the helical band structure.

75 FR 76065 - Self-Regulatory Organizations; Notice of Filing and Immediate Effectiveness of Proposed Rule...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-12-07

... PHLX, Inc. Relating to Rebates and Fees for Adding and Removing Liquidity in Select Symbols December 1... Select Symbols in Section I of the Fee Schedule. The text of the proposed rule change is available on the.... Purpose The purpose of the proposed rule change is to amend the list of Select Symbols in the Exchange's...

Appropriateness guidelines and predictive rules to select patients for upper endoscopy: a nationwide multicenter study.

PubMed

Buri, Luigi; Hassan, Cesare; Bersani, Gianluca; Anti, Marcello; Bianco, Maria Antonietta; Cipolletta, Livio; Di Giulio, Emilio; Di Matteo, Giovanni; Familiari, Luigi; Ficano, Leonardo; Loriga, Pietro; Morini, Sergio; Pietropaolo, Vincenzo; Zambelli, Alessandro; Grossi, Enzo; Intraligi, Marco; Buscema, Massimo

2010-06-01

Selecting patients appropriately for upper endoscopy (EGD) is crucial for efficient use of endoscopy. The objective of this study was to compare different clinical strategies and statistical methods to select patients for EGD, namely appropriateness guidelines, age and/or alarm features, and multivariate and artificial neural network (ANN) models. A nationwide, multicenter, prospective study was undertaken in which consecutive patients referred for EGD during a 1-month period were enrolled. Before EGD, the endoscopist assessed referral appropriateness according to the American Society for Gastrointestinal Endoscopy (ASGE) guidelines, also collecting clinical and demographic variables. Outcomes of the study were detection of relevant findings and new diagnosis of malignancy at EGD. The accuracy of the following clinical strategies and predictive rules was compared: (i) ASGE appropriateness guidelines (indicated vs. not indicated), (ii) simplified rule (>or=45 years or alarm features vs. <45 years without alarm features), (iii) logistic regression model, and (iv) ANN models. A total of 8,252 patients were enrolled in 57 centers. Overall, 3,803 (46%) relevant findings and 132 (1.6%) new malignancies were detected. Sensitivity, specificity, and area under the receiver-operating characteristic curve (AUC) of the simplified rule were similar to that of the ASGE guidelines for both relevant findings (82%/26%/0.55 vs. 88%/27%/0.52) and cancer (97%/22%/0.58 vs. 98%/20%/0.58). Both logistic regression and ANN models seemed to be substantially more accurate in predicting new cases of malignancy, with an AUC of 0.82 and 0.87, respectively. A simple predictive rule based on age and alarm features is similarly effective to the more complex ASGE guidelines in selecting patients for EGD. Regression and ANN models may be useful in identifying a relatively small subgroup of patients at higher risk of cancer.

A Compensatory Approach to Optimal Selection with Mastery Scores. Research Report 94-2.

ERIC Educational Resources Information Center

van der Linden, Wim J.; Vos, Hans J.

This paper presents some Bayesian theories of simultaneous optimization of decision rules for test-based decisions. Simultaneous decision making arises when an institution has to make a series of selection, placement, or mastery decisions with respect to subjects from a population. An obvious example is the use of individualized instruction in…

Lung Cancer Assistant: a hybrid clinical decision support application for lung cancer care.

PubMed

Sesen, M Berkan; Peake, Michael D; Banares-Alcantara, Rene; Tse, Donald; Kadir, Timor; Stanley, Roz; Gleeson, Fergus; Brady, Michael

2014-09-06

Multidisciplinary team (MDT) meetings are becoming the model of care for cancer patients worldwide. While MDTs have improved the quality of cancer care, the meetings impose substantial time pressure on the members, who generally attend several such MDTs. We describe Lung Cancer Assistant (LCA), a clinical decision support (CDS) prototype designed to assist the experts in the treatment selection decisions in the lung cancer MDTs. A novel feature of LCA is its ability to provide rule-based and probabilistic decision support within a single platform. The guideline-based CDS is based on clinical guideline rules, while the probabilistic CDS is based on a Bayesian network trained on the English Lung Cancer Audit Database (LUCADA). We assess rule-based and probabilistic recommendations based on their concordances with the treatments recorded in LUCADA. Our results reveal that the guideline rule-based recommendations perform well in simulating the recorded treatments with exact and partial concordance rates of 0.57 and 0.79, respectively. On the other hand, the exact and partial concordance rates achieved with probabilistic results are relatively poorer with 0.27 and 0.76. However, probabilistic decision support fulfils a complementary role in providing accurate survival estimations. Compared to recorded treatments, both CDS approaches promote higher resection rates and multimodality treatments.

Toward sensor-based context aware systems.

PubMed

Sakurai, Yoshitaka; Takada, Kouhei; Anisetti, Marco; Bellandi, Valerio; Ceravolo, Paolo; Damiani, Ernesto; Tsuruta, Setsuo

2012-01-01

This paper proposes a methodology for sensor data interpretation that can combine sensor outputs with contexts represented as sets of annotated business rules. Sensor readings are interpreted to generate events labeled with the appropriate type and level of uncertainty. Then, the appropriate context is selected. Reconciliation of different uncertainty types is achieved by a simple technique that moves uncertainty from events to business rules by generating combs of standard Boolean predicates. Finally, context rules are evaluated together with the events to take a decision. The feasibility of our idea is demonstrated via a case study where a context-reasoning engine has been connected to simulated heartbeat sensors using prerecorded experimental data. We use sensor outputs to identify the proper context of operation of a system and trigger decision-making based on context information.

A Pilot Study on Modeling of Diagnostic Criteria Using OWL and SWRL.

PubMed

Hong, Na; Jiang, Guoqian; Pathak, Jyotishiman; Chute, Christopher G

2015-01-01

The objective of this study is to describe our efforts in a pilot study on modeling diagnostic criteria using a Semantic Web-based approach. We reused the basic framework of the ICD-11 content model and refined it into an operational model in the Web Ontology Language (OWL). The refinement is based on a bottom-up analysis method, in which we analyzed data elements (including value sets) in a collection (n=20) of randomly selected diagnostic criteria. We also performed a case study to formalize rule logic in the diagnostic criteria of metabolic syndrome using the Semantic Web Rule Language (SWRL). The results demonstrated that it is feasible to use OWL and SWRL to formalize the diagnostic criteria knowledge, and to execute the rules through reasoning.

Alpha-beta coordination method for collective search

DOEpatents

Goldsmith, Steven Y.

2002-01-01

The present invention comprises a decentralized coordination strategy called alpha-beta coordination. The alpha-beta coordination strategy is a family of collective search methods that allow teams of communicating agents to implicitly coordinate their search activities through a division of labor based on self-selected roles and self-determined status. An agent can play one of two complementary roles. An agent in the alpha role is motivated to improve its status by exploring new regions of the search space. An agent in the beta role is also motivated to improve its status, but is conservative and tends to remain aggregated with other agents until alpha agents have clearly identified and communicated better regions of the search space. An agent can select its role dynamically based on its current status value relative to the status values of neighboring team members. Status can be determined by a function of the agent's sensor readings, and can generally be a measurement of source intensity at the agent's current location. An agent's decision cycle can comprise three sequential decision rules: (1) selection of a current role based on the evaluation of the current status data, (2) selection of a specific subset of the current data, and (3) determination of the next heading using the selected data. Variations of the decision rules produce different versions of alpha and beta behaviors that lead to different collective behavior properties.

Universal rule for the symmetric division of plant cells

PubMed Central

Besson, Sébastien; Dumais, Jacques

2011-01-01

The division of eukaryotic cells involves the assembly of complex cytoskeletal structures to exert the forces required for chromosome segregation and cytokinesis. In plants, empirical evidence suggests that tensional forces within the cytoskeleton cause cells to divide along the plane that minimizes the surface area of the cell plate (Errera’s rule) while creating daughter cells of equal size. However, exceptions to Errera’s rule cast doubt on whether a broadly applicable rule can be formulated for plant cell division. Here, we show that the selection of the plane of division involves a competition between alternative configurations whose geometries represent local area minima. We find that the probability of observing a particular division configuration increases inversely with its relative area according to an exponential probability distribution known as the Gibbs measure. Moreover, a comparison across land plants and their most recent algal ancestors confirms that the probability distribution is widely conserved and independent of cell shape and size. Using a maximum entropy formulation, we show that this empirical division rule is predicted by the dynamics of the tense cytoskeletal elements that lead to the positioning of the preprophase band. Based on the fact that the division plane is selected from the sole interaction of the cytoskeleton with cell shape, we posit that the new rule represents the default mechanism for plant cell division when internal or external cues are absent. PMID:21383128

Simulation of large-scale rule-based models

PubMed Central

Colvin, Joshua; Monine, Michael I.; Faeder, James R.; Hlavacek, William S.; Von Hoff, Daniel D.; Posner, Richard G.

2009-01-01

Motivation: Interactions of molecules, such as signaling proteins, with multiple binding sites and/or multiple sites of post-translational covalent modification can be modeled using reaction rules. Rules comprehensively, but implicitly, define the individual chemical species and reactions that molecular interactions can potentially generate. Although rules can be automatically processed to define a biochemical reaction network, the network implied by a set of rules is often too large to generate completely or to simulate using conventional procedures. To address this problem, we present DYNSTOC, a general-purpose tool for simulating rule-based models. Results: DYNSTOC implements a null-event algorithm for simulating chemical reactions in a homogenous reaction compartment. The simulation method does not require that a reaction network be specified explicitly in advance, but rather takes advantage of the availability of the reaction rules in a rule-based specification of a network to determine if a randomly selected set of molecular components participates in a reaction during a time step. DYNSTOC reads reaction rules written in the BioNetGen language which is useful for modeling protein–protein interactions involved in signal transduction. The method of DYNSTOC is closely related to that of StochSim. DYNSTOC differs from StochSim by allowing for model specification in terms of BNGL, which extends the range of protein complexes that can be considered in a model. DYNSTOC enables the simulation of rule-based models that cannot be simulated by conventional methods. We demonstrate the ability of DYNSTOC to simulate models accounting for multisite phosphorylation and multivalent binding processes that are characterized by large numbers of reactions. Availability: DYNSTOC is free for non-commercial use. The C source code, supporting documentation and example input files are available at http://public.tgen.org/dynstoc/. Contact: dynstoc@tgen.org Supplementary information: Supplementary data are available at Bioinformatics online. PMID:19213740

The Construct of Attention in Schizophrenia

PubMed Central

Luck, Steven J.; Gold, James M.

2008-01-01

Schizophrenia is widely thought to involve deficits of attention. However, the term attention can be defined so broadly that impaired performance on virtually any task could be construed as evidence for a deficit in attention, and this has slowed cumulative progress in understanding attention deficits in schizophrenia. To address this problem, we divide the general concept of attention into two distinct constructs: input selection, the selection of task-relevant inputs for further processing; and rule selection, the selective activation of task-appropriate rules. These constructs are closely tied to working memory, because input selection mechanisms are used to control the transfer of information into working memory and because working memory stores the rules used by rule selection mechanisms. These constructs are also closely tied to executive function, because executive systems are used to guide input selection and because rule selection is itself at key aspect of executive function. Within the domain of input selection, it is important to distinguish between the control of selection—the processes that guide attention to task-relevant inputs—and the implementation of selection—the processes that enhance the processing of the relevant inputs and suppress the irrelevant inputs. Current evidence suggests that schizophrenia involves a significant impairment in the control of selection but little or no impairment in the implementation of selection. Consequently, the CNTRICS participants agreed by consensus that attentional control should be a priority target for measurement and treatment research in schizophrenia. PMID:18374901

Context-Awareness Based Personalized Recommendation of Anti-Hypertension Drugs.

PubMed

Chen, Dexin; Jin, Dawei; Goh, Tiong-Thye; Li, Na; Wei, Leiru

2016-09-01

The World Health Organization estimates that almost one-third of the world's adult population are suffering from hypertension which has gradually become a "silent killer". Due to the varieties of anti-hypertensive drugs, patients are interested in how these drugs can be selected to match their respective conditions. This study provides a personalized recommendation service system of anti-hypertensive drugs based on context-awareness and designs a context ontology framework of the service. In addition, this paper introduces a Semantic Web Rule Language (SWRL)-based rule to provide high-level context reasoning and information recommendation and to overcome the limitation of ontology reasoning. To make the information recommendation of the drugs more personalized, this study also devises three categories of information recommendation rules that match different priority levels and uses a ranking algorithm to optimize the recommendation. The experiment conducted shows that combining the anti-hypertensive drugs personalized recommendation service context ontology (HyRCO) with the optimized rule reasoning can achieve a higher-quality personalized drug recommendation service. Accordingly this exploratory study of the personalized recommendation service for hypertensive drugs and its method can be easily adopted for other diseases.

75 FR 36698 - Draft Regulatory Guide: Issuance, Availability

Federal Register 2010, 2011, 2012, 2013, 2014

2010-06-28

... information based on the likelihood of pipe breaks of different sizes. The rule would divide all coolant... to and including a ``transition break size,'' and breaks larger than the transition size up to the largest pipe in the reactor coolant system. Selection of the transition size was based upon pipe break...

High-resolution, anthropomorphic, computational breast phantom: fusion of rule-based structures with patient-based anatomy

NASA Astrophysics Data System (ADS)

Chen, Xinyuan; Gong, Xiaolin; Graff, Christian G.; Santana, Maira; Sturgeon, Gregory M.; Sauer, Thomas J.; Zeng, Rongping; Glick, Stephen J.; Lo, Joseph Y.

2017-03-01

While patient-based breast phantoms are realistic, they are limited by low resolution due to the image acquisition and segmentation process. The purpose of this study is to restore the high frequency components for the patient-based phantoms by adding power law noise (PLN) and breast structures generated based on mathematical models. First, 3D radial symmetric PLN with β=3 was added at the boundary between adipose and glandular tissue to connect broken tissue and create a high frequency contour of the glandular tissue. Next, selected high-frequency features from the FDA rule-based computational phantom (Cooper's ligaments, ductal network, and blood vessels) were fused into the phantom. The effects of enhancement in this study were demonstrated by 2D mammography projections and digital breast tomosynthesis (DBT) reconstruction volumes. The addition of PLN and rule-based models leads to a continuous decrease in β. The new β is 2.76, which is similar to what typically found for reconstructed DBT volumes. The new combined breast phantoms retain the realism from segmentation and gain higher resolution after restoration.

Procrastinating Behavior in Computer-Based Learning Environments to Predict Performance: A Case Study in Moodle

PubMed Central

Cerezo, Rebeca; Esteban, María; Sánchez-Santillán, Miguel; Núñez, José C.

2017-01-01

Introduction: Research about student performance has traditionally considered academic procrastination as a behavior that has negative effects on academic achievement. Although there is much evidence for this in class-based environments, there is a lack of research on Computer-Based Learning Environments (CBLEs). Therefore, the purpose of this study is to evaluate student behavior in a blended learning program and specifically procrastination behavior in relation to performance through Data Mining techniques. Materials and Methods: A sample of 140 undergraduate students participated in a blended learning experience implemented in a Moodle (Modular Object Oriented Developmental Learning Environment) Management System. Relevant interaction variables were selected for the study, taking into account student achievement and analyzing data by means of association rules, a mining technique. The association rules were arrived at and filtered through two selection criteria: 1, rules must have an accuracy over 0.8 and 2, they must be present in both sub-samples. Results: The findings of our study highlight the influence of time management in online learning environments, particularly on academic achievement, as there is an association between procrastination variables and student performance. Conclusion: Negative impact of procrastination in learning outcomes has been observed again but in virtual learning environments where practical implications, prevention of, and intervention in, are different from class-based learning. These aspects are discussed to help resolve student difficulties at various ages. PMID:28883801

Procrastinating Behavior in Computer-Based Learning Environments to Predict Performance: A Case Study in Moodle.

PubMed

Cerezo, Rebeca; Esteban, María; Sánchez-Santillán, Miguel; Núñez, José C

2017-01-01

Introduction: Research about student performance has traditionally considered academic procrastination as a behavior that has negative effects on academic achievement. Although there is much evidence for this in class-based environments, there is a lack of research on Computer-Based Learning Environments (CBLEs) . Therefore, the purpose of this study is to evaluate student behavior in a blended learning program and specifically procrastination behavior in relation to performance through Data Mining techniques. Materials and Methods: A sample of 140 undergraduate students participated in a blended learning experience implemented in a Moodle (Modular Object Oriented Developmental Learning Environment) Management System. Relevant interaction variables were selected for the study, taking into account student achievement and analyzing data by means of association rules, a mining technique. The association rules were arrived at and filtered through two selection criteria: 1, rules must have an accuracy over 0.8 and 2, they must be present in both sub-samples. Results: The findings of our study highlight the influence of time management in online learning environments, particularly on academic achievement, as there is an association between procrastination variables and student performance. Conclusion: Negative impact of procrastination in learning outcomes has been observed again but in virtual learning environments where practical implications, prevention of, and intervention in, are different from class-based learning. These aspects are discussed to help resolve student difficulties at various ages.

Reasoning versus text processing in the Wason selection task: a nondeontic perspective on perspective effects.

PubMed

Almor, A; Sloman, S A

2000-09-01

We argue that perspective effects in the Wason four-card selection task are a product of the linguistic interpretation of the rule in the context of the problem text and not of the reasoning process underlying card selection. In three experiments, participants recalled the rule they used in either a selection or a plausibility rating task. The results showed that (1) participants tended to recall rules compatible with their card selection and not with the rule as stated in the problem and (2) recall was not affected by whether or not participants performed card selection. We conclude that perspective effects in the Wason selection task do not concern how card selection is reasoned about but instead reflect the inferential text processing involved in the comprehension of the problem text. Together with earlier research that showed selection performance in nondeontic contexts to be indistinguishable from selection performance in deontic contexts (Almor & Sloman, 1996; Sperber, Cara, & Girotto, 1995), the present results undermine the claim that reasoning in a deontic context elicits specialized cognitive processes.

Electrically-induced polarization selection rules of a graphene quantum dot

NASA Astrophysics Data System (ADS)

Dong, Qing-Rui; Li, Yan; Jia, Chen; Wang, Fu-Li; Zhang, Ya-Ting; Liu, Chun-Xiang

2018-05-01

We study theoretically the single-electron triangular zigzag graphene quantum dot in uniform in-plane electric fields. The absorption spectra of the dot are calculated by the tight-binding method. The energy spectra and the distribution of wave functions are also presented to analyse the absorption spectra. The orthogonal zero-energy eigenstates are arranged along to the direction of the external field. The remarkable result is that all intraband transitions and some interband transitions are forbidden when the absorbed light is polarized along the direction of the electric field. With x-direction electric field, all intraband absorption is y polarized due to the electric-field-direction-polarization selection rule. Moreover, with y-direction electric field, all absorption is either x or y polarized due to the parity selection rule as well as to the electric-field-direction-polarization selection rule. Our calculation shows that the formation of the absorption spectra is co-decided by the polarization selection rules and the overlap between the eigenstates of the transition.

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.

Rule Encoding in Orbitofrontal Cortex and Striatum Guides Selection

PubMed Central

Castagno, Meghan D.; Hayden, Benjamin Y.

2016-01-01

Active maintenance of rules, like other executive functions, is often thought to be the domain of a discrete executive system. An alternative view is that rule maintenance is a broadly distributed function relying on widespread cortical and subcortical circuits. Tentative evidence supporting this view comes from research showing some rule selectivity in the orbitofrontal cortex and dorsal striatum. We recorded in these regions and in the ventral striatum, which has not been associated previously with rule representation, as macaques performed a Wisconsin Card Sorting Task. We found robust encoding of rule category (color vs shape) and rule identity (six possible rules) in all three regions. Rule identity modulated responses to potential choice targets, suggesting that rule information guides behavior by highlighting choice targets. The effects that we observed were not explained by differences in behavioral performance across rules and thus cannot be attributed to reward expectation. Our results suggest that rule maintenance and rule-guided selection of options are distributed processes and provide new insight into orbital and striatal contributions to executive control. SIGNIFICANCE STATEMENT Rule maintenance, an important executive function, is generally thought to rely on dorsolateral brain regions. In this study, we examined activity of single neurons in orbitofrontal cortex and in ventral and dorsal striatum of macaques in a Wisconsin Card Sorting Task. Neurons in all three areas encoded rules and rule categories robustly. Rule identity also affected neural responses to potential choice options, suggesting that stored information is used to influence decisions. These results endorse the hypothesis that rule maintenance is a broadly distributed mental operation. PMID:27807165

77 FR 43879 - Self-Regulatory Organizations; NYSE Arca, Inc.; Notice of Designation of a Longer Period for...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-07-26

... Proposed Rule Change Amending NYSE Arca Equities Rule 7.31(h) To Add a PL Select Order Type July 20, 2012...(h) to add a PL Select Order type. The proposed rule change was published for comment in the Federal... security at a specified, undisplayed price. The PL Select Order would be a subset of the PL Order that...

Fuzzy support vector machine: an efficient rule-based classification technique for microarrays.

PubMed

Hajiloo, Mohsen; Rabiee, Hamid R; Anooshahpour, Mahdi

2013-01-01

The abundance of gene expression microarray data has led to the development of machine learning algorithms applicable for tackling disease diagnosis, disease prognosis, and treatment selection problems. However, these algorithms often produce classifiers with weaknesses in terms of accuracy, robustness, and interpretability. This paper introduces fuzzy support vector machine which is a learning algorithm based on combination of fuzzy classifiers and kernel machines for microarray classification. Experimental results on public leukemia, prostate, and colon cancer datasets show that fuzzy support vector machine applied in combination with filter or wrapper feature selection methods develops a robust model with higher accuracy than the conventional microarray classification models such as support vector machine, artificial neural network, decision trees, k nearest neighbors, and diagonal linear discriminant analysis. Furthermore, the interpretable rule-base inferred from fuzzy support vector machine helps extracting biological knowledge from microarray data. Fuzzy support vector machine as a new classification model with high generalization power, robustness, and good interpretability seems to be a promising tool for gene expression microarray classification.

Mode Selection Rules for a Two-Delay System with Positive and Negative Feedback Loops

NASA Astrophysics Data System (ADS)

Takahashi, Kin'ya; Kobayashi, Taizo

2018-04-01

The mode selection rules for a two-delay system, which has negative feedback with a short delay time t1 and positive feedback with a long delay time t2, are studied numerically and theoretically. We find two types of mode selection rules depending on the strength of the negative feedback. When the strength of the negative feedback |α1| (α1 < 0) is sufficiently small compared with that of the positive feedback α2 (> 0), 2m + 1-th harmonic oscillation is well sustained in a neighborhood of t1/t2 = even/odd, i.e., relevant condition. In a neighborhood of the irrelevant condition given by t1/t2 = odd/even or t1/t2 = odd/odd, higher harmonic oscillations are observed. However, if |α1| is slightly less than α2, a different mode selection rule works, where the condition t1/t2 = odd/even is relevant and the conditions t1/t2 = odd/odd and t1/t2 = even/odd are irrelevant. These mode selection rules are different from the mode selection rule of the normal two-delay system with two positive feedback loops, where t1/t2 = odd/odd is relevant and the others are irrelevant. The two types of mode selection rules are induced by individually different mechanisms controlling the Hopf bifurcation, i.e., the Hopf bifurcation controlled by the "boosted bifurcation process" and by the "anomalous bifurcation process", which occur for |α1| below and above the threshold value αth, respectively.

Evolving optimised decision rules for intrusion detection using particle swarm paradigm

NASA Astrophysics Data System (ADS)

Sivatha Sindhu, Siva S.; Geetha, S.; Kannan, A.

2012-12-01

The aim of this article is to construct a practical intrusion detection system (IDS) that properly analyses the statistics of network traffic pattern and classify them as normal or anomalous class. The objective of this article is to prove that the choice of effective network traffic features and a proficient machine-learning paradigm enhances the detection accuracy of IDS. In this article, a rule-based approach with a family of six decision tree classifiers, namely Decision Stump, C4.5, Naive Baye's Tree, Random Forest, Random Tree and Representative Tree model to perform the detection of anomalous network pattern is introduced. In particular, the proposed swarm optimisation-based approach selects instances that compose training set and optimised decision tree operate over this trained set producing classification rules with improved coverage, classification capability and generalisation ability. Experiment with the Knowledge Discovery and Data mining (KDD) data set which have information on traffic pattern, during normal and intrusive behaviour shows that the proposed algorithm produces optimised decision rules and outperforms other machine-learning algorithm.

An Algorithm of Association Rule Mining for Microbial Energy Prospection

PubMed Central

Shaheen, Muhammad; Shahbaz, Muhammad

2017-01-01

The presence of hydrocarbons beneath earth’s surface produces some microbiological anomalies in soils and sediments. The detection of such microbial populations involves pure bio chemical processes which are specialized, expensive and time consuming. This paper proposes a new algorithm of context based association rule mining on non spatial data. The algorithm is a modified form of already developed algorithm which was for spatial database only. The algorithm is applied to mine context based association rules on microbial database to extract interesting and useful associations of microbial attributes with existence of hydrocarbon reserve. The surface and soil manifestations caused by the presence of hydrocarbon oxidizing microbes are selected from existing literature and stored in a shared database. The algorithm is applied on the said database to generate direct and indirect associations among the stored microbial indicators. These associations are then correlated with the probability of hydrocarbon’s existence. The numerical evaluation shows better accuracy for non-spatial data as compared to conventional algorithms at generating reliable and robust rules. PMID:28393846

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.

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.

Hierarchical fuzzy control of low-energy building systems

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

Yu, Zhen; Dexter, Arthur

2010-04-15

A hierarchical fuzzy supervisory controller is described that is capable of optimizing the operation of a low-energy building, which uses solar energy to heat and cool its interior spaces. The highest level fuzzy rules choose the most appropriate set of lower level rules according to the weather and occupancy information; the second level fuzzy rules determine an optimal energy profile and the overall modes of operation of the heating, ventilating and air-conditioning system (HVAC); the third level fuzzy rules select the mode of operation of specific equipment, and assign schedules to the local controllers so that the optimal energy profilemore » can be achieved in the most efficient way. Computer simulation is used to compare the hierarchical fuzzy control scheme with a supervisory control scheme based on expert rules. The performance is evaluated by comparing the energy consumption and thermal comfort. (author)« less

Automatic Learning of Fine Operating Rules for Online Power System Security Control.

PubMed

Sun, Hongbin; Zhao, Feng; Wang, Hao; Wang, Kang; Jiang, Weiyong; Guo, Qinglai; Zhang, Boming; Wehenkel, Louis

2016-08-01

Fine operating rules for security control and an automatic system for their online discovery were developed to adapt to the development of smart grids. The automatic system uses the real-time system state to determine critical flowgates, and then a continuation power flow-based security analysis is used to compute the initial transfer capability of critical flowgates. Next, the system applies the Monte Carlo simulations to expected short-term operating condition changes, feature selection, and a linear least squares fitting of the fine operating rules. The proposed system was validated both on an academic test system and on a provincial power system in China. The results indicated that the derived rules provide accuracy and good interpretability and are suitable for real-time power system security control. The use of high-performance computing systems enables these fine operating rules to be refreshed online every 15 min.

Civilian Health and Medical Program of the Uniformed Services (CHAMPUS); TRICARE Reserve Select for certain members of the selected reserve; Transitional Assistance Management Program; early eligibility for TRICARE for certain reserve component members. Interim final rule with comment period.

PubMed

2005-03-16

This interim final rule establishes requirements and procedures for implementation of TRICARE Reserve Select. It also revises requirements and procedures for the Transitional Assistance Management Program. In addition, it establishes requirements and procedures for implementation of the earlier TRICARE eligibility for certain reserve component members. The rule is being published as an interim final rule with comment period in order to comply with statutory effective dates.

Evaluation of empirical rule of linearly correlated peptide selection (ERLPS) for proteotypic peptide-based quantitative proteomics.

PubMed

Liu, Kehui; Zhang, Jiyang; Fu, Bin; Xie, Hongwei; Wang, Yingchun; Qian, Xiaohong

2014-07-01

Precise protein quantification is essential in comparative proteomics. Currently, quantification bias is inevitable when using proteotypic peptide-based quantitative proteomics strategy for the differences in peptides measurability. To improve quantification accuracy, we proposed an "empirical rule for linearly correlated peptide selection (ERLPS)" in quantitative proteomics in our previous work. However, a systematic evaluation on general application of ERLPS in quantitative proteomics under diverse experimental conditions needs to be conducted. In this study, the practice workflow of ERLPS was explicitly illustrated; different experimental variables, such as, different MS systems, sample complexities, sample preparations, elution gradients, matrix effects, loading amounts, and other factors were comprehensively investigated to evaluate the applicability, reproducibility, and transferability of ERPLS. The results demonstrated that ERLPS was highly reproducible and transferable within appropriate loading amounts and linearly correlated response peptides should be selected for each specific experiment. ERLPS was used to proteome samples from yeast to mouse and human, and in quantitative methods from label-free to O18/O16-labeled and SILAC analysis, and enabled accurate measurements for all proteotypic peptide-based quantitative proteomics over a large dynamic range. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

75 FR 6769 - Self-Regulatory Organizations; Financial Industry Regulatory Authority, Inc.; Order Approving...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-02-10

... To Amend the Hearing Location Rules of the Codes of Arbitration Procedure for Customer and Industry... expand the criteria for selecting a hearing location for an arbitration proceeding. The proposed rule..., 2010. II. Description of the Proposed Rule Change Hearing Location Selection Under the Customer Code...

A New Approach for Resolving Conflicts in Actionable Behavioral Rules

PubMed Central

Zhu, Dan; Zeng, Daniel

2014-01-01

Knowledge is considered actionable if users can take direct actions based on such knowledge to their advantage. Among the most important and distinctive actionable knowledge are actionable behavioral rules that can directly and explicitly suggest specific actions to take to influence (restrain or encourage) the behavior in the users' best interest. However, in mining such rules, it often occurs that different rules may suggest the same actions with different expected utilities, which we call conflicting rules. To resolve the conflicts, a previous valid method was proposed. However, inconsistency of the measure for rule evaluating may hinder its performance. To overcome this problem, we develop a new method that utilizes rule ranking procedure as the basis for selecting the rule with the highest utility prediction accuracy. More specifically, we propose an integrative measure, which combines the measures of the support and antecedent length, to evaluate the utility prediction accuracies of conflicting rules. We also introduce a tunable weight parameter to allow the flexibility of integration. We conduct several experiments to test our proposed approach and evaluate the sensitivity of the weight parameter. Empirical results indicate that our approach outperforms those from previous research. PMID:25162054

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.

78 FR 62017 - Regulatory Capital Rules: Regulatory Capital, Implementation of Basel III, Capital Adequacy...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-10-11

...The Office of the Comptroller of the Currency (OCC) and Board of Governors of the Federal Reserve System (Board), are adopting a final rule that revises their risk-based and leverage capital requirements for banking organizations. The final rule consolidates three separate notices of proposed rulemaking that the OCC, Board, and FDIC published in the Federal Register on August 30, 2012, with selected changes. The final rule implements a revised definition of regulatory capital, a new common equity tier 1 minimum capital requirement, a higher minimum tier 1 capital requirement, and, for banking organizations subject to the advanced approaches risk-based capital rules, a supplementary leverage ratio that incorporates a broader set of exposures in the denominator. The final rule incorporates these new requirements into the agencies' prompt corrective action (PCA) framework. In addition, the final rule establishes limits on a banking organization's capital distributions and certain discretionary bonus payments if the banking organization does not hold a specified amount of common equity tier 1 capital in addition to the amount necessary to meet its minimum risk-based capital requirements. Further, the final rule amends the methodologies for determining risk-weighted assets for all banking organizations, and introduces disclosure requirements that would apply to top-tier banking organizations domiciled in the United States with $50 billion or more in total assets. The final rule also adopts changes to the agencies' regulatory capital requirements that meet the requirements of section 171 and section 939A of the Dodd-Frank Wall Street Reform and Consumer Protection Act. The final rule also codifies the agencies' regulatory capital rules, which have previously resided in various appendices to their respective regulations, into a harmonized integrated regulatory framework. In addition, the OCC is amending the market risk capital rule (market risk rule) to apply to Federal savings associations, and the Board is amending the advanced approaches and market risk rules to apply to top-tier savings and loan holding companies domiciled in the United States, except for certain savings and loan holding companies that are substantially engaged in insurance underwriting or commercial activities, as described in this preamble.

The Adverse Drug Reactions from Patient Reports in Social Media Project: Five Major Challenges to Overcome to Operationalize Analysis and Efficiently Support Pharmacovigilance Process

PubMed Central

Dahamna, Badisse; Guillemin-Lanne, Sylvie; Darmoni, Stefan J; Faviez, Carole; Huot, Charles; Katsahian, Sandrine; Leroux, Vincent; Pereira, Suzanne; Richard, Christophe; Schück, Stéphane; Souvignet, Julien; Lillo-Le Louët, Agnès; Texier, Nathalie

2017-01-01

Background Adverse drug reactions (ADRs) are an important cause of morbidity and mortality. Classical Pharmacovigilance process is limited by underreporting which justifies the current interest in new knowledge sources such as social media. The Adverse Drug Reactions from Patient Reports in Social Media (ADR-PRISM) project aims to extract ADRs reported by patients in these media. We identified 5 major challenges to overcome to operationalize the analysis of patient posts: (1) variable quality of information on social media, (2) guarantee of data privacy, (3) response to pharmacovigilance expert expectations, (4) identification of relevant information within Web pages, and (5) robust and evolutive architecture. Objective This article aims to describe the current state of advancement of the ADR-PRISM project by focusing on the solutions we have chosen to address these 5 major challenges. Methods In this article, we propose methods and describe the advancement of this project on several aspects: (1) a quality driven approach for selecting relevant social media for the extraction of knowledge on potential ADRs, (2) an assessment of ethical issues and French regulation for the analysis of data on social media, (3) an analysis of pharmacovigilance expert requirements when reviewing patient posts on the Internet, (4) an extraction method based on natural language processing, pattern based matching, and selection of relevant medical concepts in reference terminologies, and (5) specifications of a component-based architecture for the monitoring system. Results Considering the 5 major challenges, we (1) selected a set of 21 validated criteria for selecting social media to support the extraction of potential ADRs, (2) proposed solutions to guarantee data privacy of patients posting on Internet, (3) took into account pharmacovigilance expert requirements with use case diagrams and scenarios, (4) built domain-specific knowledge resources embeding a lexicon, morphological rules, context rules, semantic rules, syntactic rules, and post-analysis processing, and (5) proposed a component-based architecture that allows storage of big data and accessibility to third-party applications through Web services. Conclusions We demonstrated the feasibility of implementing a component-based architecture that allows collection of patient posts on the Internet, near real-time processing of those posts including annotation, and storage in big data structures. In the next steps, we will evaluate the posts identified by the system in social media to clarify the interest and relevance of such approach to improve conventional pharmacovigilance processes based on spontaneous reporting. PMID:28935617

Data Mining for Financial Applications

NASA Astrophysics Data System (ADS)

Kovalerchuk, Boris; Vityaev, Evgenii

This chapter describes Data Mining in finance by discussing financial tasks, specifics of methodologies and techniques in this Data Mining area. It includes time dependence, data selection, forecast horizon, measures of success, quality of patterns, hypothesis evaluation, problem ID, method profile, attribute-based and relational methodologies. The second part of the chapter discusses Data Mining models and practice in finance. It covers use of neural networks in portfolio management, design of interpretable trading rules and discovering money laundering schemes using decision rules and relational Data Mining methodology.

Comparing the Performance of Five Multidimensional CAT Selection Procedures with Different Stopping Rules

ERIC Educational Resources Information Center

Yao, Lihua

2013-01-01

Through simulated data, five multidimensional computerized adaptive testing (MCAT) selection procedures with varying test lengths are examined and compared using different stopping rules. Fixed item exposure rates are used for all the items, and the Priority Index (PI) method is used for the content constraints. Two stopping rules, standard error…

7 CFR 29.6104 - Rule 18.

Code of Federal Regulations, 2014 CFR

2014-01-01

... INSPECTION Standards Rules § 29.6104 Rule 18. Burn shall be determined as the average burning time of leaves selected at random from the sample. A minimum of 10 leaves shall be selected as representative regardless... on the same side of the leaf. The leaf shall be punctured to permit quick ignition when placed over a...

7 CFR 29.6104 - Rule 18.

Code of Federal Regulations, 2010 CFR

2010-01-01

... INSPECTION Standards Rules § 29.6104 Rule 18. Burn shall be determined as the average burning time of leaves selected at random from the sample. A minimum of 10 leaves shall be selected as representative regardless... on the same side of the leaf. The leaf shall be punctured to permit quick ignition when placed over a...

7 CFR 29.6104 - Rule 18.

Code of Federal Regulations, 2013 CFR

2013-01-01

... INSPECTION Standards Rules § 29.6104 Rule 18. Burn shall be determined as the average burning time of leaves selected at random from the sample. A minimum of 10 leaves shall be selected as representative regardless... on the same side of the leaf. The leaf shall be punctured to permit quick ignition when placed over a...

7 CFR 29.6104 - Rule 18.

Code of Federal Regulations, 2011 CFR

2011-01-01

... INSPECTION Standards Rules § 29.6104 Rule 18. Burn shall be determined as the average burning time of leaves selected at random from the sample. A minimum of 10 leaves shall be selected as representative regardless... on the same side of the leaf. The leaf shall be punctured to permit quick ignition when placed over a...

7 CFR 29.6104 - Rule 18.

Code of Federal Regulations, 2012 CFR

2012-01-01

... INSPECTION Standards Rules § 29.6104 Rule 18. Burn shall be determined as the average burning time of leaves selected at random from the sample. A minimum of 10 leaves shall be selected as representative regardless... on the same side of the leaf. The leaf shall be punctured to permit quick ignition when placed over a...

Fuzzy architecture assessment for critical infrastructure resilience

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

Muller, George

2012-12-01

This paper presents an approach for the selection of alternative architectures in a connected infrastructure system to increase resilience of the overall infrastructure system. The paper begins with a description of resilience and critical infrastructure, then summarizes existing approaches to resilience, and presents a fuzzy-rule based method of selecting among alternative infrastructure architectures. This methodology includes considerations which are most important when deciding on an approach to resilience. The paper concludes with a proposed approach which builds on existing resilience architecting methods by integrating key system aspects using fuzzy memberships and fuzzy rule sets. This novel approach aids the systemsmore » architect in considering resilience for the evaluation of architectures for adoption into the final system architecture.« less

Surface-Enhanced Raman Scattering Surface Selection Rules for the Proteomic Liquid Biopsy in Real Samples: Efficient Detection of the Oncoprotein c-MYC.

PubMed

Pazos, Elena; Garcia-Algar, Manuel; Penas, Cristina; Nazarenus, Moritz; Torruella, Arnau; Pazos-Perez, Nicolas; Guerrini, Luca; Vázquez, M Eugenio; Garcia-Rico, Eduardo; Mascareñas, José L; Alvarez-Puebla, Ramon A

2016-11-02

Blood-based biomarkers (liquid biopsy) offer extremely valuable tools for the noninvasive diagnosis and monitoring of tumors. The protein c-MYC, a transcription factor that has been shown to be deregulated in up to 70% of human cancers, can be used as a robust proteomic signature for cancer. Herein, we developed a rapid, highly specific, and sensitive surface-enhanced Raman scattering (SERS) assay for the quantification of c-MYC in real blood samples. The sensing scheme relies on the use of specifically designed hybrid plasmonic materials and their bioderivatization with a selective peptidic receptor modified with a SERS transducer. Peptide/c-MYC recognition events translate into measurable alterations of the SERS spectra associated with a molecular reorientation of the transducer, in agreement with the surface selection rules. The efficiency of the sensor is demonstrated in cellular lines, healthy donors and a cancer patient.

SKOLAR MD: A Model for Self-Directed, In-Context Continuing Medical Education

PubMed Central

Strasberg, Howard R.; Rindfleisch, Thomas C.; Hardy, Steven

2003-01-01

INTRODUCTION SKOLAR has implemented a web-based CME program with which physicians can earn AMA Category 1 credit for self-directed learning. METHODS Physicians researched their questions in SKOLAR and applied for CME. Physician auditors reviewed all requests across two phases of the project. A selection rule set was derived from phase one and used in phase two to flag a subset of requests for detailed review. The selection rule set is described. RESULTS In phase one, SKOLAR received 1039 CME applications. Applicants frequently found their answer (94%) and would apply it clinically (93%). A linear regression analysis comparing time awarded to time requested (capped at actual time spent) had R2=0.79. DISCUSSION We believe that hat this self-directed approach to CME is effective and an important complement to traditional CME programs. However, selective audit of self-directed CME requests is necessary to ensure validity of credits awarded. PMID:14728250

Robust Strategy for Rocket Engine Health Monitoring

NASA Technical Reports Server (NTRS)

Santi, L. Michael

2001-01-01

Monitoring the health of rocket engine systems is essentially a two-phase process. The acquisition phase involves sensing physical conditions at selected locations, converting physical inputs to electrical signals, conditioning the signals as appropriate to establish scale or filter interference, and recording results in a form that is easy to interpret. The inference phase involves analysis of results from the acquisition phase, comparison of analysis results to established health measures, and assessment of health indications. A variety of analytical tools may be employed in the inference phase of health monitoring. These tools can be separated into three broad categories: statistical, rule based, and model based. Statistical methods can provide excellent comparative measures of engine operating health. They require well-characterized data from an ensemble of "typical" engines, or "golden" data from a specific test assumed to define the operating norm in order to establish reliable comparative measures. Statistical methods are generally suitable for real-time health monitoring because they do not deal with the physical complexities of engine operation. The utility of statistical methods in rocket engine health monitoring is hindered by practical limits on the quantity and quality of available data. This is due to the difficulty and high cost of data acquisition, the limited number of available test engines, and the problem of simulating flight conditions in ground test facilities. In addition, statistical methods incur a penalty for disregarding flow complexity and are therefore limited in their ability to define performance shift causality. Rule based methods infer the health state of the engine system based on comparison of individual measurements or combinations of measurements with defined health norms or rules. This does not mean that rule based methods are necessarily simple. Although binary yes-no health assessment can sometimes be established by relatively simple rules, the causality assignment needed for refined health monitoring often requires an exceptionally complex rule base involving complicated logical maps. Structuring the rule system to be clear and unambiguous can be difficult, and the expert input required to maintain a large logic network and associated rule base can be prohibitive.

Cooperation and charity in spatial public goods game under different strategy update rules

NASA Astrophysics Data System (ADS)

Li, Yixiao; Jin, Xiaogang; Su, Xianchuang; Kong, Fansheng; Peng, Chengbin

2010-03-01

Human cooperation can be influenced by other human behaviors and recent years have witnessed the flourishing of studying the coevolution of cooperation and punishment, yet the common behavior of charity is seldom considered in game-theoretical models. In this article, we investigate the coevolution of altruistic cooperation and egalitarian charity in spatial public goods game, by considering charity as the behavior of reducing inter-individual payoff differences. Our model is that, in each generation of the evolution, individuals play games first and accumulate payoff benefits, and then each egalitarian makes a charity donation by payoff transfer in its neighborhood. To study the individual-level evolutionary dynamics, we adopt different strategy update rules and investigate their effects on charity and cooperation. These rules can be classified into two global rules: random selection rule in which individuals randomly update strategies, and threshold selection rule where only those with payoffs below a threshold update strategies. Simulation results show that random selection enhances the cooperation level, while threshold selection lowers the threshold of the multiplication factor to maintain cooperation. When charity is considered, it is incapable in promoting cooperation under random selection, whereas it promotes cooperation under threshold selection. Interestingly, the evolution of charity strongly depends on the dispersion of payoff acquisitions of the population, which agrees with previous results. Our work may shed light on understanding human egalitarianism.

Levels of integration in cognitive control and sequence processing in the prefrontal cortex.

PubMed

Bahlmann, Jörg; Korb, Franziska M; Gratton, Caterina; Friederici, Angela D

2012-01-01

Cognitive control is necessary to flexibly act in changing environments. Sequence processing is needed in language comprehension to build the syntactic structure in sentences. Functional imaging studies suggest that sequence processing engages the left ventrolateral prefrontal cortex (PFC). In contrast, cognitive control processes additionally recruit bilateral rostral lateral PFC regions. The present study aimed to investigate these two types of processes in one experimental paradigm. Sequence processing was manipulated using two different sequencing rules varying in complexity. Cognitive control was varied with different cue-sets that determined the choice of a sequencing rule. Univariate analyses revealed distinct PFC regions for the two types of processing (i.e. sequence processing: left ventrolateral PFC and cognitive control processing: bilateral dorsolateral and rostral PFC). Moreover, in a common brain network (including left lateral PFC and intraparietal sulcus) no interaction between sequence and cognitive control processing was observed. In contrast, a multivariate pattern analysis revealed an interaction of sequence and cognitive control processing, such that voxels in left lateral PFC and parietal cortex showed different tuning functions for tasks involving different sequencing and cognitive control demands. These results suggest that the difference between the process of rule selection (i.e. cognitive control) and the process of rule-based sequencing (i.e. sequence processing) find their neuronal underpinnings in distinct activation patterns in lateral PFC. Moreover, the combination of rule selection and rule sequencing can shape the response of neurons in lateral PFC and parietal cortex.

Levels of Integration in Cognitive Control and Sequence Processing in the Prefrontal Cortex

PubMed Central

Bahlmann, Jörg; Korb, Franziska M.; Gratton, Caterina; Friederici, Angela D.

2012-01-01

Cognitive control is necessary to flexibly act in changing environments. Sequence processing is needed in language comprehension to build the syntactic structure in sentences. Functional imaging studies suggest that sequence processing engages the left ventrolateral prefrontal cortex (PFC). In contrast, cognitive control processes additionally recruit bilateral rostral lateral PFC regions. The present study aimed to investigate these two types of processes in one experimental paradigm. Sequence processing was manipulated using two different sequencing rules varying in complexity. Cognitive control was varied with different cue-sets that determined the choice of a sequencing rule. Univariate analyses revealed distinct PFC regions for the two types of processing (i.e. sequence processing: left ventrolateral PFC and cognitive control processing: bilateral dorsolateral and rostral PFC). Moreover, in a common brain network (including left lateral PFC and intraparietal sulcus) no interaction between sequence and cognitive control processing was observed. In contrast, a multivariate pattern analysis revealed an interaction of sequence and cognitive control processing, such that voxels in left lateral PFC and parietal cortex showed different tuning functions for tasks involving different sequencing and cognitive control demands. These results suggest that the difference between the process of rule selection (i.e. cognitive control) and the process of rule-based sequencing (i.e. sequence processing) find their neuronal underpinnings in distinct activation patterns in lateral PFC. Moreover, the combination of rule selection and rule sequencing can shape the response of neurons in lateral PFC and parietal cortex. PMID:22952762

Bridging the gap between formal and experience-based knowledge for context-aware laparoscopy.

PubMed

Katić, Darko; Schuck, Jürgen; Wekerle, Anna-Laura; Kenngott, Hannes; Müller-Stich, Beat Peter; Dillmann, Rüdiger; Speidel, Stefanie

2016-06-01

Computer assistance is increasingly common in surgery. However, the amount of information is bound to overload processing abilities of surgeons. We propose methods to recognize the current phase of a surgery for context-aware information filtering. The purpose is to select the most suitable subset of information for surgical situations which require special assistance. We combine formal knowledge, represented by an ontology, and experience-based knowledge, represented by training samples, to recognize phases. For this purpose, we have developed two different methods. Firstly, we use formal knowledge about possible phase transitions to create a composition of random forests. Secondly, we propose a method based on cultural optimization to infer formal rules from experience to recognize phases. The proposed methods are compared with a purely formal knowledge-based approach using rules and a purely experience-based one using regular random forests. The comparative evaluation on laparoscopic pancreas resections and adrenalectomies employs a consistent set of quality criteria on clean and noisy input. The rule-based approaches proved best with noisefree data. The random forest-based ones were more robust in the presence of noise. Formal and experience-based knowledge can be successfully combined for robust phase recognition.

Complexity of line-seru conversion for different scheduling rules and two improved exact algorithms for the multi-objective optimization.

PubMed

Yu, Yang; Wang, Sihan; Tang, Jiafu; Kaku, Ikou; Sun, Wei

2016-01-01

Productivity can be greatly improved by converting the traditional assembly line to a seru system, especially in the business environment with short product life cycles, uncertain product types and fluctuating production volumes. Line-seru conversion includes two decision processes, i.e., seru formation and seru load. For simplicity, however, previous studies focus on the seru formation with a given scheduling rule in seru load. We select ten scheduling rules usually used in seru load to investigate the influence of different scheduling rules on the performance of line-seru conversion. Moreover, we clarify the complexities of line-seru conversion for ten different scheduling rules from the theoretical perspective. In addition, multi-objective decisions are often used in line-seru conversion. To obtain Pareto-optimal solutions of multi-objective line-seru conversion, we develop two improved exact algorithms based on reducing time complexity and space complexity respectively. Compared with the enumeration based on non-dominated sorting to solve multi-objective problem, the two improved exact algorithms saves computation time greatly. Several numerical simulation experiments are performed to show the performance improvement brought by the two proposed exact algorithms.

The Decision to Engage Cognitive Control Is Driven by Expected Reward-Value: Neural and Behavioral Evidence

PubMed Central

Dixon, Matthew L.; Christoff, Kalina

2012-01-01

Cognitive control is a fundamental skill reflecting the active use of task-rules to guide behavior and suppress inappropriate automatic responses. Prior work has traditionally used paradigms in which subjects are told when to engage cognitive control. Thus, surprisingly little is known about the factors that influence individuals' initial decision of whether or not to act in a reflective, rule-based manner. To examine this, we took three classic cognitive control tasks (Stroop, Wisconsin Card Sorting Task, Go/No-Go task) and created novel ‘free-choice’ versions in which human subjects were free to select an automatic, pre-potent action, or an action requiring rule-based cognitive control, and earned varying amounts of money based on their choices. Our findings demonstrated that subjects' decision to engage cognitive control was driven by an explicit representation of monetary rewards expected to be obtained from rule-use. Subjects rarely engaged cognitive control when the expected outcome was of equal or lesser value as compared to the value of the automatic response, but frequently engaged cognitive control when it was expected to yield a larger monetary outcome. Additionally, we exploited fMRI-adaptation to show that the lateral prefrontal cortex (LPFC) represents associations between rules and expected reward outcomes. Together, these findings suggest that individuals are more likely to act in a reflective, rule-based manner when they expect that it will result in a desired outcome. Thus, choosing to exert cognitive control is not simply a matter of reason and willpower, but rather, conforms to standard mechanisms of value-based decision making. Finally, in contrast to current models of LPFC function, our results suggest that the LPFC plays a direct role in representing motivational incentives. PMID:23284730

75 FR 20651 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-04-20

... Proposed Rule Change To Amend the Global Select Market Initial Listing Requirements April 14, 2010... the Global Select initial listing requirements and to make a technical conforming correction to a rule...'s market capitalization at the time of listing. (f)-(h) No change. (i) A Company whose business plan...

Internal quality control: best practice.

PubMed

Kinns, Helen; Pitkin, Sarah; Housley, David; Freedman, Danielle B

2013-12-01

There is a wide variation in laboratory practice with regard to implementation and review of internal quality control (IQC). A poor approach can lead to a spectrum of scenarios from validation of incorrect patient results to over investigation of falsely rejected analytical runs. This article will provide a practical approach for the routine clinical biochemistry laboratory to introduce an efficient quality control system that will optimise error detection and reduce the rate of false rejection. Each stage of the IQC system is considered, from selection of IQC material to selection of IQC rules, and finally the appropriate action to follow when a rejection signal has been obtained. The main objective of IQC is to ensure day-to-day consistency of an analytical process and thus help to determine whether patient results are reliable enough to be released. The required quality and assay performance varies between analytes as does the definition of a clinically significant error. Unfortunately many laboratories currently decide what is clinically significant at the troubleshooting stage. Assay-specific IQC systems will reduce the number of inappropriate sample-run rejections compared with the blanket use of one IQC rule. In practice, only three or four different IQC rules are required for the whole of the routine biochemistry repertoire as assays are assigned into groups based on performance. The tools to categorise performance and assign IQC rules based on that performance are presented. Although significant investment of time and education is required prior to implementation, laboratories have shown that such systems achieve considerable reductions in cost and labour.

Rules of co-occurring mutations characterize the antigenic evolution of human influenza A/H3N2, A/H1N1 and B viruses.

PubMed

Chen, Haifen; Zhou, Xinrui; Zheng, Jie; Kwoh, Chee-Keong

2016-12-05

The human influenza viruses undergo rapid evolution (especially in hemagglutinin (HA), a glycoprotein on the surface of the virus), which enables the virus population to constantly evade the human immune system. Therefore, the vaccine has to be updated every year to stay effective. There is a need to characterize the evolution of influenza viruses for better selection of vaccine candidates and the prediction of pandemic strains. Studies have shown that the influenza hemagglutinin evolution is driven by the simultaneous mutations at antigenic sites. Here, we analyze simultaneous or co-occurring mutations in the HA protein of human influenza A/H3N2, A/H1N1 and B viruses to predict potential mutations, characterizing the antigenic evolution. We obtain the rules of mutation co-occurrence using association rule mining after extracting HA1 sequences and detect co-mutation sites under strong selective pressure. Then we predict the potential drifts with specific mutations of the viruses based on the rules and compare the results with the "observed" mutations in different years. The sites under frequent mutations are in antigenic regions (epitopes) or receptor binding sites. Our study demonstrates the co-occurring site mutations obtained by rule mining can capture the evolution of influenza viruses, and confirms that cooperative interactions among sites of HA1 protein drive the influenza antigenic evolution.

Scale characters analysis for gully structure in the watersheds of loess landforms based on digital elevation models

NASA Astrophysics Data System (ADS)

Zhu, Hongchun; Zhao, Yipeng; Liu, Haiying

2018-04-01

Scale is the basic attribute for expressing and describing spatial entity and phenomena. It offers theoretical significance in the study of gully structure information, variable characteristics of watershed morphology, and development evolution at different scales. This research selected five different areas in China's Loess Plateau as the experimental region and used DEM data at different scales as the experimental data. First, the change rule of the characteristic parameters of the data at different scales was analyzed. The watershed structure information did not change along with a change in the data scale. This condition was proven by selecting indices of gully bifurcation ratio and fractal dimension as characteristic parameters of watershed structure information. Then, the change rule of the characteristic parameters of gully structure with different analysis scales was analyzed by setting the scale sequence of analysis at the extraction gully. The gully structure of the watershed changed with variations in the analysis scale, and the change rule was obvious when the gully level changed. Finally, the change rule of the characteristic parameters of the gully structure at different areas was analyzed. The gully fractal dimension showed a significant numerical difference in different areas, whereas the variation of the gully branch ratio was small. The change rule indicated that the development degree of the gully obviously varied in different regions, but the morphological structure was basically similar.

Scale characters analysis for gully structure in the watersheds of loess landforms based on digital elevation models

NASA Astrophysics Data System (ADS)

Zhu, Hongchun; Zhao, Yipeng; Liu, Haiying

2018-06-01

Scale is the basic attribute for expressing and describing spatial entity and phenomena. It offers theoretical significance in the study of gully structure information, variable characteristics of watershed morphology, and development evolution at different scales. This research selected five different areas in China's Loess Plateau as the experimental region and used DEM data at different scales as the experimental data. First, the change rule of the characteristic parameters of the data at different scales was analyzed. The watershed structure information did not change along with a change in the data scale. This condition was proven by selecting indices of gully bifurcation ratio and fractal dimension as characteristic parameters of watershed structure information. Then, the change rule of the characteristic parameters of gully structure with different analysis scales was analyzed by setting the scale sequence of analysis at the extraction gully. The gully structure of the watershed changed with variations in the analysis scale, and the change rule was obvious when the gully level changed. Finally, the change rule of the characteristic parameters of the gully structure at different areas was analyzed. The gully fractal dimension showed a significant numerical difference in different areas, whereas the variation of the gully branch ratio was small. The change rule indicated that the development degree of the gully obviously varied in different regions, but the morphological structure was basically similar.

Computer-Aided Clinical Trial Recruitment Based on Domain-Specific Language Translation: A Case Study of Retinopathy of Prematurity

PubMed Central

2017-01-01

Reusing the data from healthcare information systems can effectively facilitate clinical trials (CTs). How to select candidate patients eligible for CT recruitment criteria is a central task. Related work either depends on DBA (database administrator) to convert the recruitment criteria to native SQL queries or involves the data mapping between a standard ontology/information model and individual data source schema. This paper proposes an alternative computer-aided CT recruitment paradigm, based on syntax translation between different DSLs (domain-specific languages). In this paradigm, the CT recruitment criteria are first formally represented as production rules. The referenced rule variables are all from the underlying database schema. Then the production rule is translated to an intermediate query-oriented DSL (e.g., LINQ). Finally, the intermediate DSL is directly mapped to native database queries (e.g., SQL) automated by ORM (object-relational mapping). PMID:29065644

Computer-Aided Clinical Trial Recruitment Based on Domain-Specific Language Translation: A Case Study of Retinopathy of Prematurity.

PubMed

Zhang, Yinsheng; Zhang, Guoming; Shang, Qian

2017-01-01

Reusing the data from healthcare information systems can effectively facilitate clinical trials (CTs). How to select candidate patients eligible for CT recruitment criteria is a central task. Related work either depends on DBA (database administrator) to convert the recruitment criteria to native SQL queries or involves the data mapping between a standard ontology/information model and individual data source schema. This paper proposes an alternative computer-aided CT recruitment paradigm, based on syntax translation between different DSLs (domain-specific languages). In this paradigm, the CT recruitment criteria are first formally represented as production rules. The referenced rule variables are all from the underlying database schema. Then the production rule is translated to an intermediate query-oriented DSL (e.g., LINQ). Finally, the intermediate DSL is directly mapped to native database queries (e.g., SQL) automated by ORM (object-relational mapping).

Use of Six Sigma Worksheets for assessment of internal and external failure costs associated with candidate quality control rules for an ADVIA 120 hematology analyzer.

PubMed

Cian, Francesco; Villiers, Elisabeth; Archer, Joy; Pitorri, Francesca; Freeman, Kathleen

2014-06-01

Quality control (QC) validation is an essential tool in total quality management of a veterinary clinical pathology laboratory. Cost-analysis can be a valuable technique to help identify an appropriate QC procedure for the laboratory, although this has never been reported in veterinary medicine. The aim of this study was to determine the applicability of the Six Sigma Quality Cost Worksheets in the evaluation of possible candidate QC rules identified by QC validation. Three months of internal QC records were analyzed. EZ Rules 3 software was used to evaluate candidate QC procedures, and the costs associated with the application of different QC rules were calculated using the Six Sigma Quality Cost Worksheets. The costs associated with the current and the candidate QC rules were compared, and the amount of cost savings was calculated. There was a significant saving when the candidate 1-2.5s, n = 3 rule was applied instead of the currently utilized 1-2s, n = 3 rule. The savings were 75% per year (£ 8232.5) based on re-evaluating all of the patient samples in addition to the controls, and 72% per year (£ 822.4) based on re-analyzing only the control materials. The savings were also shown to change accordingly with the number of samples analyzed and with the number of daily QC procedures performed. These calculations demonstrated the importance of the selection of an appropriate QC procedure, and the usefulness of the Six Sigma Costs Worksheet in determining the most cost-effective rule(s) when several candidate rules are identified by QC validation. © 2014 American Society for Veterinary Clinical Pathology and European Society for Veterinary Clinical Pathology.

Summation rules for a fully nonlocal energy-based quasicontinuum method

NASA Astrophysics Data System (ADS)

Amelang, J. S.; Venturini, G. N.; Kochmann, D. M.

2015-09-01

The quasicontinuum (QC) method coarse-grains crystalline atomic ensembles in order to bridge the scales from individual atoms to the micro- and mesoscales. A crucial cornerstone of all QC techniques, summation or quadrature rules efficiently approximate the thermodynamic quantities of interest. Here, we investigate summation rules for a fully nonlocal, energy-based QC method to approximate the total Hamiltonian of a crystalline atomic ensemble by a weighted sum over a small subset of all atoms in the crystal lattice. Our formulation does not conceptually differentiate between atomistic and coarse-grained regions and thus allows for seamless bridging without domain-coupling interfaces. We review traditional summation rules and discuss their strengths and weaknesses with a focus on energy approximation errors and spurious force artifacts. Moreover, we introduce summation rules which produce no residual or spurious force artifacts in centrosymmetric crystals in the large-element limit under arbitrary affine deformations in two dimensions (and marginal force artifacts in three dimensions), while allowing us to seamlessly bridge to full atomistics. Through a comprehensive suite of examples with spatially non-uniform QC discretizations in two and three dimensions, we compare the accuracy of the new scheme to various previous ones. Our results confirm that the new summation rules exhibit significantly smaller force artifacts and energy approximation errors. Our numerical benchmark examples include the calculation of elastic constants from completely random QC meshes and the inhomogeneous deformation of aggressively coarse-grained crystals containing nano-voids. In the elastic regime, we directly compare QC results to those of full atomistics to assess global and local errors in complex QC simulations. Going beyond elasticity, we illustrate the performance of the energy-based QC method with the new second-order summation rule by the help of nanoindentation examples with automatic mesh adaptation. Overall, our findings provide guidelines for the selection of summation rules for the fully nonlocal energy-based QC method.

78 FR 3952 - Self-Regulatory Organizations; International Securities Exchange, LLC; Notice of Filing and...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-01-17

.... For Select Symbols (excluding SPY), the Exchange currently provides a base rebate of $0.34 per... SPY), the Exchange currently provides a base rebate of $0.34 per contract, per leg, for Priority... Securities Exchange Act of 1934 (the ``Act''),\\1\\ and Rule 19b-4 thereunder,\\2\\ notice is hereby given that...

R symmetries and a heterotic MSSM

NASA Astrophysics Data System (ADS)

Kappl, Rolf; Nilles, Hans Peter; Schmitz, Matthias

2015-02-01

We employ powerful techniques based on Hilbert and Gröbner bases to analyze particle physics models derived from string theory. Individual models are shown to have a huge landscape of vacua that differ in their phenomenological properties. We explore the (discrete) symmetries of these vacua, the new R symmetry selection rules and their consequences for moduli stabilization.

75 FR 66404 - Self-Regulatory Organizations; C2 Options Exchange, Incorporated; Notice of Filing and Immediate...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-10-28

... Change The Exchange proposes to modify the wording of Rule 6.12 relating to the C2 matching algorithm... matching algorithm and subsequently overlay certain priorities over the selected base algorithm. There are currently two base algorithms: price-time (often referred to as first in, first out or FIFO) in which...

10 CFR 600.13 - Merit review.

Code of Federal Regulations, 2012 CFR

2012-01-01

... ENERGY (CONTINUED) ASSISTANCE REGULATIONS FINANCIAL ASSISTANCE RULES General § 600.13 Merit review. (a) It is the policy of DOE that discretionary financial assistance be awarded through a merit-based selection process. A merit review means a thorough, consistent, and objective examination of applications...

10 CFR 600.13 - Merit review.

Code of Federal Regulations, 2011 CFR

2011-01-01

... ENERGY (CONTINUED) ASSISTANCE REGULATIONS FINANCIAL ASSISTANCE RULES General § 600.13 Merit review. (a) It is the policy of DOE that discretionary financial assistance be awarded through a merit-based selection process. A merit review means a thorough, consistent, and objective examination of applications...

10 CFR 600.13 - Merit review.

Code of Federal Regulations, 2010 CFR

2010-01-01

... ENERGY (CONTINUED) ASSISTANCE REGULATIONS FINANCIAL ASSISTANCE RULES General § 600.13 Merit review. (a) It is the policy of DOE that discretionary financial assistance be awarded through a merit-based selection process. A merit review means a thorough, consistent, and objective examination of applications...

10 CFR 600.13 - Merit review.

Code of Federal Regulations, 2013 CFR

2013-01-01

... ENERGY (CONTINUED) ASSISTANCE REGULATIONS FINANCIAL ASSISTANCE RULES General § 600.13 Merit review. (a) It is the policy of DOE that discretionary financial assistance be awarded through a merit-based selection process. A merit review means a thorough, consistent, and objective examination of applications...

10 CFR 600.13 - Merit review.

Code of Federal Regulations, 2014 CFR

2014-01-01

... ENERGY (CONTINUED) ASSISTANCE REGULATIONS FINANCIAL ASSISTANCE RULES General § 600.13 Merit review. (a) It is the policy of DOE that discretionary financial assistance be awarded through a merit-based selection process. A merit review means a thorough, consistent, and objective examination of applications...

Neural substrates of similarity and rule-based strategies in judgment

PubMed Central

von Helversen, Bettina; Karlsson, Linnea; Rasch, Björn; Rieskamp, Jörg

2014-01-01

Making accurate judgments is a core human competence and a prerequisite for success in many areas of life. Plenty of evidence exists that people can employ different judgment strategies to solve identical judgment problems. In categorization, it has been demonstrated that similarity-based and rule-based strategies are associated with activity in different brain regions. Building on this research, the present work tests whether solving two identical judgment problems recruits different neural substrates depending on people's judgment strategies. Combining cognitive modeling of judgment strategies at the behavioral level with functional magnetic resonance imaging (fMRI), we compare brain activity when using two archetypal judgment strategies: a similarity-based exemplar strategy and a rule-based heuristic strategy. Using an exemplar-based strategy should recruit areas involved in long-term memory processes to a larger extent than a heuristic strategy. In contrast, using a heuristic strategy should recruit areas involved in the application of rules to a larger extent than an exemplar-based strategy. Largely consistent with our hypotheses, we found that using an exemplar-based strategy led to relatively higher BOLD activity in the anterior prefrontal and inferior parietal cortex, presumably related to retrieval and selective attention processes. In contrast, using a heuristic strategy led to relatively higher activity in areas in the dorsolateral prefrontal and the temporal-parietal cortex associated with cognitive control and information integration. Thus, even when people solve identical judgment problems, different neural substrates can be recruited depending on the judgment strategy involved. PMID:25360099

Reconstruction of DNA sequences using genetic algorithms and cellular automata: towards mutation prediction?

PubMed

Mizas, Ch; Sirakoulis, G Ch; Mardiris, V; Karafyllidis, I; Glykos, N; Sandaltzopoulos, R

2008-04-01

Change of DNA sequence that fuels evolution is, to a certain extent, a deterministic process because mutagenesis does not occur in an absolutely random manner. So far, it has not been possible to decipher the rules that govern DNA sequence evolution due to the extreme complexity of the entire process. In our attempt to approach this issue we focus solely on the mechanisms of mutagenesis and deliberately disregard the role of natural selection. Hence, in this analysis, evolution refers to the accumulation of genetic alterations that originate from mutations and are transmitted through generations without being subjected to natural selection. We have developed a software tool that allows modelling of a DNA sequence as a one-dimensional cellular automaton (CA) with four states per cell which correspond to the four DNA bases, i.e. A, C, T and G. The four states are represented by numbers of the quaternary number system. Moreover, we have developed genetic algorithms (GAs) in order to determine the rules of CA evolution that simulate the DNA evolution process. Linear evolution rules were considered and square matrices were used to represent them. If DNA sequences of different evolution steps are available, our approach allows the determination of the underlying evolution rule(s). Conversely, once the evolution rules are deciphered, our tool may reconstruct the DNA sequence in any previous evolution step for which the exact sequence information was unknown. The developed tool may be used to test various parameters that could influence evolution. We describe a paradigm relying on the assumption that mutagenesis is governed by a near-neighbour-dependent mechanism. Based on the satisfactory performance of our system in the deliberately simplified example, we propose that our approach could offer a starting point for future attempts to understand the mechanisms that govern evolution. The developed software is open-source and has a user-friendly graphical input interface.

Optimum use of air tankers in initial attack: selection, basing, and transfer rules

Treesearch

Francis E. Greulich; William G. O' Regan

1982-01-01

Fire managers face two interrelated problems in deciding the most efficient use of air tankers: where best to base them, and how best to reallocate them each day in anticipation of fire occurrence. A computerized model based on a mixed integer linear program can help in assigning air tankers throughout the fire season. The model was tested using information from...

Urban Rain Gauge Siting Selection Based on Gis-Multicriteria Analysis

NASA Astrophysics Data System (ADS)

Fu, Yanli; Jing, Changfeng; Du, Mingyi

2016-06-01

With the increasingly rapid growth of urbanization and climate change, urban rainfall monitoring as well as urban waterlogging has widely been paid attention. In the light of conventional siting selection methods do not take into consideration of geographic surroundings and spatial-temporal scale for the urban rain gauge site selection, this paper primarily aims at finding the appropriate siting selection rules and methods for rain gauge in urban area. Additionally, for optimization gauge location, a spatial decision support system (DSS) aided by geographical information system (GIS) has been developed. In terms of a series of criteria, the rain gauge optimal site-search problem can be addressed by a multicriteria decision analysis (MCDA). A series of spatial analytical techniques are required for MCDA to identify the prospective sites. With the platform of GIS, using spatial kernel density analysis can reflect the population density; GIS buffer analysis is used to optimize the location with the rain gauge signal transmission character. Experiment results show that the rules and the proposed method are proper for the rain gauge site selection in urban areas, which is significant for the siting selection of urban hydrological facilities and infrastructure, such as water gauge.

10 CFR 2.311 - Interlocutory review of rulings on requests for hearings/petitions to intervene, selection of...

Code of Federal Regulations, 2010 CFR

2010-01-01

... 10 Energy 1 2010-01-01 2010-01-01 false Interlocutory review of rulings on requests for hearings/petitions to intervene, selection of hearing procedures, and requests by potential parties for access to sensitive unclassified non-safeguards information and safeguards information. 2.311 Section 2.311 Energy NUCLEAR REGULATORY COMMISSION RULES OF...

Evaluation for the Allocation of University Research Project Funding: Can Rules Improve the Peer Review?

ERIC Educational Resources Information Center

Reale, Emanuela; Zinilli, Antonio

2017-01-01

Evaluation for the allocation of project-funding schemes devoted to sustain academic research often undergoes changes of the rules for the ex-ante selection, which are supposed to improve the capability of peer review to select the best proposals. How modifications of the rules realize a more accountable evaluation result? Do the changes suggest…

A Method for the Comparison of Item Selection Rules in Computerized Adaptive Testing

ERIC Educational Resources Information Center

Barrada, Juan Ramon; Olea, Julio; Ponsoda, Vicente; Abad, Francisco Jose

2010-01-01

In a typical study comparing the relative efficiency of two item selection rules in computerized adaptive testing, the common result is that they simultaneously differ in accuracy and security, making it difficult to reach a conclusion on which is the more appropriate rule. This study proposes a strategy to conduct a global comparison of two or…

Advertisement scheduling on commercial radio station using genetics algorithm

NASA Astrophysics Data System (ADS)

Purnamawati, S.; Nababan, E. B.; Tsani, B.; Taqyuddin, R.; Rahmat, R. F.

2018-03-01

On the commercial radio station, the advertising schedule is done manually, which resulted in ineffectiveness of ads schedule. Playback time consists of two types such as prime time and regular time. Radio Ads scheduling will be discussed in this research is based on ad playback schedule between 5am until 12am which rules every 15 minutes. It provides 3 slots ads with playback duration per ads maximum is 1 minute. If the radio broadcast time per day is 12 hours, then the maximum number of ads per day which can be aired is 76 ads. The other is the enactment of rules of prime time, namely the hours where the common people (listeners) have the greatest opportunity to listen to the radio, namely between the hours and hours of 4 am - 8 am, 6 pm - 10 pm. The number of screenings of the same ads on one day are limited to prime time ie 5 times, while for regular time is 8 times. Radio scheduling process is done using genetic algorithms which are composed of processes initialization chromosomes, selection, crossover and mutation. Study on chromosome 3 genes, each chromosome will be evaluated based on the value of fitness calculated based on the number of infractions that occurred on each individual chromosome. Where rule 1 is the number of screenings per ads must not be more than 5 times per day and rule 2 is there should never be two or more scheduling ads delivered on the same day and time. After fitness value of each chromosome is acquired, then the do the selection, crossover and mutation. From this research result, the optimal advertising schedule with schedule a whole day and ads data playback time ads with this level of accuracy: the average percentage was 83.79%.

Nonequivalence of updating rules in evolutionary games under high mutation rates.

PubMed

Kaiping, G A; Jacobs, G S; Cox, S J; Sluckin, T J

2014-10-01

Moran processes are often used to model selection in evolutionary simulations. The updating rule in Moran processes is a birth-death process, i. e., selection according to fitness of an individual to give birth, followed by the death of a random individual. For well-mixed populations with only two strategies this updating rule is known to be equivalent to selecting unfit individuals for death and then selecting randomly for procreation (biased death-birth process). It is, however, known that this equivalence does not hold when considering structured populations. Here we study whether changing the updating rule can also have an effect in well-mixed populations in the presence of more than two strategies and high mutation rates. We find, using three models from different areas of evolutionary simulation, that the choice of updating rule can change model results. We show, e. g., that going from the birth-death process to the death-birth process can change a public goods game with punishment from containing mostly defectors to having a majority of cooperative strategies. From the examples given we derive guidelines indicating when the choice of the updating rule can be expected to have an impact on the results of the model.

Nonequivalence of updating rules in evolutionary games under high mutation rates

NASA Astrophysics Data System (ADS)

Kaiping, G. A.; Jacobs, G. S.; Cox, S. J.; Sluckin, T. J.

2014-10-01

Moran processes are often used to model selection in evolutionary simulations. The updating rule in Moran processes is a birth-death process, i. e., selection according to fitness of an individual to give birth, followed by the death of a random individual. For well-mixed populations with only two strategies this updating rule is known to be equivalent to selecting unfit individuals for death and then selecting randomly for procreation (biased death-birth process). It is, however, known that this equivalence does not hold when considering structured populations. Here we study whether changing the updating rule can also have an effect in well-mixed populations in the presence of more than two strategies and high mutation rates. We find, using three models from different areas of evolutionary simulation, that the choice of updating rule can change model results. We show, e. g., that going from the birth-death process to the death-birth process can change a public goods game with punishment from containing mostly defectors to having a majority of cooperative strategies. From the examples given we derive guidelines indicating when the choice of the updating rule can be expected to have an impact on the results of the model.

CARSVM: a class association rule-based classification framework and its application to gene expression data.

PubMed

Kianmehr, Keivan; Alhajj, Reda

2008-09-01

In this study, we aim at building a classification framework, namely the CARSVM model, which integrates association rule mining and support vector machine (SVM). The goal is to benefit from advantages of both, the discriminative knowledge represented by class association rules and the classification power of the SVM algorithm, to construct an efficient and accurate classifier model that improves the interpretability problem of SVM as a traditional machine learning technique and overcomes the efficiency issues of associative classification algorithms. In our proposed framework: instead of using the original training set, a set of rule-based feature vectors, which are generated based on the discriminative ability of class association rules over the training samples, are presented to the learning component of the SVM algorithm. We show that rule-based feature vectors present a high-qualified source of discrimination knowledge that can impact substantially the prediction power of SVM and associative classification techniques. They provide users with more conveniences in terms of understandability and interpretability as well. We have used four datasets from UCI ML repository to evaluate the performance of the developed system in comparison with five well-known existing classification methods. Because of the importance and popularity of gene expression analysis as real world application of the classification model, we present an extension of CARSVM combined with feature selection to be applied to gene expression data. Then, we describe how this combination will provide biologists with an efficient and understandable classifier model. The reported test results and their biological interpretation demonstrate the applicability, efficiency and effectiveness of the proposed model. From the results, it can be concluded that a considerable increase in classification accuracy can be obtained when the rule-based feature vectors are integrated in the learning process of the SVM algorithm. In the context of applicability, according to the results obtained from gene expression analysis, we can conclude that the CARSVM system can be utilized in a variety of real world applications with some adjustments.

Human Cognition and Information Display in C3I System Tasks.

DTIC Science & Technology

1988-12-01

goes without saying that rule-based tasks are the easiest to automate, but for reasons discussed earlier, they still merit our attention . Moreover...selective attention task. Since selective attention must operate after memory retrieval, it is only when different responses are elicited that the...stimuli that is processed by impairing the memory traces of signals that originally attract less attention . Although the research reviewed above gives

Derivation of optimal joint operating rules for multi-purpose multi-reservoir water-supply system

NASA Astrophysics Data System (ADS)

Tan, Qiao-feng; Wang, Xu; Wang, Hao; Wang, Chao; Lei, Xiao-hui; Xiong, Yi-song; Zhang, Wei

2017-08-01

The derivation of joint operating policy is a challenging task for a multi-purpose multi-reservoir system. This study proposed an aggregation-decomposition model to guide the joint operation of multi-purpose multi-reservoir system, including: (1) an aggregated model based on the improved hedging rule to ensure the long-term water-supply operating benefit; (2) a decomposed model to allocate the limited release to individual reservoirs for the purpose of maximizing the total profit of the facing period; and (3) a double-layer simulation-based optimization model to obtain the optimal time-varying hedging rules using the non-dominated sorting genetic algorithm II, whose objectives were to minimize maximum water deficit and maximize water supply reliability. The water-supply system of Li River in Guangxi Province, China, was selected for the case study. The results show that the operating policy proposed in this study is better than conventional operating rules and aggregated standard operating policy for both water supply and hydropower generation due to the use of hedging mechanism and effective coordination among multiple objectives.

R package PRIMsrc: Bump Hunting by Patient Rule Induction Method for Survival, Regression and Classification

PubMed Central

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

2015-01-01

PRIMsrc is a novel implementation of a non-parametric bump hunting procedure, based on the Patient Rule Induction Method (PRIM), offering a unified treatment of outcome variables, including censored time-to-event (Survival), continuous (Regression) and discrete (Classification) responses. To fit the model, it uses a recursive peeling procedure with specific peeling criteria and stopping rules depending on the response. To validate the model, it provides an objective function based on prediction-error or other specific statistic, as well as two alternative cross-validation techniques, adapted to the task of decision-rule making and estimation in the three types of settings. PRIMsrc comes as an open source R package, including at this point: (i) a main function for fitting a Survival Bump Hunting model with various options allowing cross-validated model selection to control model size (#covariates) and model complexity (#peeling steps) and generation of cross-validated end-point estimates; (ii) parallel computing; (iii) various S3-generic and specific plotting functions for data visualization, diagnostic, prediction, summary and display of results. It is available on CRAN and GitHub. PMID:26798326

Effects of Differential Reinforcement and Rules With Feedback on Preference for Choice and Verbal Reports

PubMed Central

Karsina, Allen; Thompson, Rachel H; Rodriguez, Nicole M; Vanselow, Nicholas R

2012-01-01

We evaluated the effects of differential reinforcement and accurate verbal rules with feedback on the preference for choice and the verbal reports of 6 adults. Participants earned points on a probabilistic schedule by completing the terminal links of a concurrent-chains arrangement in a computer-based game of chance. In free-choice terminal links, participants selected 3 numbers from an 8-number array; in restricted-choice terminal links participants selected the order of 3 numbers preselected by a computer program. A pop-up box then informed the participants if the numbers they selected or ordered matched or did not match numbers generated by the computer but not displayed; matching in a trial resulted in one point earned. In baseline sessions, schedules of reinforcement were equal across free- and restricted-choice arrangements and a running tally of points earned was shown each trial. The effects of differentially reinforcing restricted-choice selections were evaluated using a reversal design. For 4 participants, the effects of providing a running tally of points won by arrangement and verbal rules regarding the schedule of reinforcement were also evaluated using a nonconcurrent multiple-baseline-across-participants design. Results varied across participants but generally demonstrated that (a) preference for choice corresponded more closely to verbal reports of the odds of winning than to reinforcement schedules, (b) rules and feedback were correlated with more accurate verbal reports, and (c) preference for choice corresponded more highly to the relative number of reinforcements obtained across free- and restricted-choice arrangements in a session than to the obtained probability of reinforcement or to verbal reports of the odds of winning. PMID:22754103

Effects of differential reinforcement and rules with feedback on preference for choice and verbal reports.

PubMed

Karsina, Allen; Thompson, Rachel H; Rodriguez, Nicole M; Vanselow, Nicholas R

2012-01-01

We evaluated the effects of differential reinforcement and accurate verbal rules with feedback on the preference for choice and the verbal reports of 6 adults. Participants earned points on a probabilistic schedule by completing the terminal links of a concurrent-chains arrangement in a computer-based game of chance. In free-choice terminal links, participants selected 3 numbers from an 8-number array; in restricted-choice terminal links participants selected the order of 3 numbers preselected by a computer program. A pop-up box then informed the participants if the numbers they selected or ordered matched or did not match numbers generated by the computer but not displayed; matching in a trial resulted in one point earned. In baseline sessions, schedules of reinforcement were equal across free- and restricted-choice arrangements and a running tally of points earned was shown each trial. The effects of differentially reinforcing restricted-choice selections were evaluated using a reversal design. For 4 participants, the effects of providing a running tally of points won by arrangement and verbal rules regarding the schedule of reinforcement were also evaluated using a nonconcurrent multiple-baseline-across-participants design. Results varied across participants but generally demonstrated that (a) preference for choice corresponded more closely to verbal reports of the odds of winning than to reinforcement schedules, (b) rules and feedback were correlated with more accurate verbal reports, and (c) preference for choice corresponded more highly to the relative number of reinforcements obtained across free- and restricted-choice arrangements in a session than to the obtained probability of reinforcement or to verbal reports of the odds of winning.

Self-accommodation of B19' martensite in Ti-Ni shape memory alloys - Part I. Morphological and crystallographic studies of the variant selection rule

NASA Astrophysics Data System (ADS)

Nishida, M.; Nishiura, T.; Kawano, H.; Inamura, T.

2012-06-01

The self-accommodation morphologies of B19‧ martensite in Ti-Ni alloys have been investigated by optical microscopy, scanning electron microscopy (SEM) and transmission electron microscopy (TEM). Twelve pairs of minimum units consisting of two habit plane variants (HPVs) with V-shaped morphology connected to a ? B19‧ type I variant accommodation twin were observed. Three types of self-accommodation morphologies, based on the V-shaped minimum unit, developed around one of the {111}B2 traces, which were triangular, rhombic and hexangular and consisted of three, four and six HPVs, respectively. In addition, the variant selection rule and the number of possible HPV combinations in each of these self-accommodation morphologies are discussed.

Basic mathematical rules are encoded by primate prefrontal cortex neurons

PubMed Central

Bongard, Sylvia; Nieder, Andreas

2010-01-01

Mathematics is based on highly abstract principles, or rules, of how to structure, process, and evaluate numerical information. If and how mathematical rules can be represented by single neurons, however, has remained elusive. We therefore recorded the activity of individual prefrontal cortex (PFC) neurons in rhesus monkeys required to switch flexibly between “greater than” and “less than” rules. The monkeys performed this task with different numerical quantities and generalized to set sizes that had not been presented previously, indicating that they had learned an abstract mathematical principle. The most prevalent activity recorded from randomly selected PFC neurons reflected the mathematical rules; purely sensory- and memory-related activity was almost absent. These data show that single PFC neurons have the capacity to represent flexible operations on most abstract numerical quantities. Our findings support PFC network models implementing specific “rule-coding” units that control the flow of information between segregated input, memory, and output layers. We speculate that these neuronal circuits in the monkey lateral PFC could readily have been adopted in the course of primate evolution for syntactic processing of numbers in formalized mathematical systems. PMID:20133872

Systematic methods for knowledge acquisition and expert system development

NASA Technical Reports Server (NTRS)

Belkin, Brenda L.; Stengel, Robert F.

1991-01-01

Nine cooperating rule-based systems, collectively called AUTOCREW which were designed to automate functions and decisions associated with a combat aircraft's subsystems, are discussed. The organization of tasks within each system is described; performance metrics were developed to evaluate the workload of each rule base and to assess the cooperation between the rule bases. Simulation and comparative workload results for two mission scenarios are given. The scenarios are inbound surface-to-air-missile attack on the aircraft and pilot incapacitation. The methodology used to develop the AUTOCREW knowledge bases is summarized. Issues involved in designing the navigation sensor selection expert in AUTOCREW's NAVIGATOR knowledge base are discussed in detail. The performance of seven navigation systems aiding a medium-accuracy INS was investigated using Kalman filter covariance analyses. A navigation sensor management (NSM) expert system was formulated from covariance simulation data using the analysis of variance (ANOVA) method and the ID3 algorithm. ANOVA results show that statistically different position accuracies are obtained when different navaids are used, the number of navaids aiding the INS is varied, the aircraft's trajectory is varied, and the performance history is varied. The ID3 algorithm determines the NSM expert's classification rules in the form of decision trees. The performance of these decision trees was assessed on two arbitrary trajectories, and the results demonstrate that the NSM expert adapts to new situations and provides reasonable estimates of the expected hybrid performance.

Systematic reconstruction of TRANSPATH data into Cell System Markup Language

PubMed Central

Nagasaki, Masao; Saito, Ayumu; Li, Chen; Jeong, Euna; Miyano, Satoru

2008-01-01

Background Many biological repositories store information based on experimental study of the biological processes within a cell, such as protein-protein interactions, metabolic pathways, signal transduction pathways, or regulations of transcription factors and miRNA. Unfortunately, it is difficult to directly use such information when generating simulation-based models. Thus, modeling rules for encoding biological knowledge into system-dynamics-oriented standardized formats would be very useful for fully understanding cellular dynamics at the system level. Results We selected the TRANSPATH database, a manually curated high-quality pathway database, which provides a plentiful source of cellular events in humans, mice, and rats, collected from over 31,500 publications. In this work, we have developed 16 modeling rules based on hybrid functional Petri net with extension (HFPNe), which is suitable for graphical representing and simulating biological processes. In the modeling rules, each Petri net element is incorporated with Cell System Ontology to enable semantic interoperability of models. As a formal ontology for biological pathway modeling with dynamics, CSO also defines biological terminology and corresponding icons. By combining HFPNe with the CSO features, it is possible to make TRANSPATH data to simulation-based and semantically valid models. The results are encoded into a biological pathway format, Cell System Markup Language (CSML), which eases the exchange and integration of biological data and models. Conclusion By using the 16 modeling rules, 97% of the reactions in TRANSPATH are converted into simulation-based models represented in CSML. This reconstruction demonstrates that it is possible to use our rules to generate quantitative models from static pathway descriptions. PMID:18570683

Systematic reconstruction of TRANSPATH data into cell system markup language.

PubMed

Nagasaki, Masao; Saito, Ayumu; Li, Chen; Jeong, Euna; Miyano, Satoru

2008-06-23

Many biological repositories store information based on experimental study of the biological processes within a cell, such as protein-protein interactions, metabolic pathways, signal transduction pathways, or regulations of transcription factors and miRNA. Unfortunately, it is difficult to directly use such information when generating simulation-based models. Thus, modeling rules for encoding biological knowledge into system-dynamics-oriented standardized formats would be very useful for fully understanding cellular dynamics at the system level. We selected the TRANSPATH database, a manually curated high-quality pathway database, which provides a plentiful source of cellular events in humans, mice, and rats, collected from over 31,500 publications. In this work, we have developed 16 modeling rules based on hybrid functional Petri net with extension (HFPNe), which is suitable for graphical representing and simulating biological processes. In the modeling rules, each Petri net element is incorporated with Cell System Ontology to enable semantic interoperability of models. As a formal ontology for biological pathway modeling with dynamics, CSO also defines biological terminology and corresponding icons. By combining HFPNe with the CSO features, it is possible to make TRANSPATH data to simulation-based and semantically valid models. The results are encoded into a biological pathway format, Cell System Markup Language (CSML), which eases the exchange and integration of biological data and models. By using the 16 modeling rules, 97% of the reactions in TRANSPATH are converted into simulation-based models represented in CSML. This reconstruction demonstrates that it is possible to use our rules to generate quantitative models from static pathway descriptions.

Acute knee injuries: use of decision rules for selective radiograph ordering.

PubMed

Tandeter, H B; Shvartzman, P; Stevens, Max A

1999-12-01

Family physicians often encounter patients with acute knee trauma. Radiographs of injured knees are commonly ordered, even though fractures are found in only 6 percent of such patients and emergency department physicians can usually discriminate clinically between fracture and nonfracture. Decision rules have been developed to reduce the unnecessary use of radiologic studies in patients with acute knee injury. The Ottawa knee rules and the Pittsburgh decision rules are the latest guidelines for the selective use of radiographs in knee trauma. Application of these rules may lead to a more efficient evaluation of knee injuries and a reduction in health costs without an increase in adverse outcomes.

Medicare and Medicaid Programs; CY 2016 Home Health Prospective Payment System Rate Update; Home Health Value-Based Purchasing Model; and Home Health Quality Reporting Requirements. Final rule.

PubMed

2015-11-05

This final rule will update Home Health Prospective Payment System (HH PPS) rates, including the national, standardized 60-day episode payment rates, the national per-visit rates, and the non-routine medical supply (NRS) conversion factor under the Medicare prospective payment system for home health agencies (HHAs), effective for episodes ending on or after January 1, 2016. As required by the Affordable Care Act, this rule implements the 3rd year of the 4-year phase-in of the rebasing adjustments to the HH PPS payment rates. This rule updates the HH PPS case-mix weights using the most current, complete data available at the time of rulemaking and provides a clarification regarding the use of the "initial encounter'' seventh character applicable to certain ICD-10-CM code categories. This final rule will also finalize reductions to the national, standardized 60-day episode payment rate in CY 2016, CY 2017, and CY 2018 of 0.97 percent in each year to account for estimated case-mix growth unrelated to increases in patient acuity (nominal case-mix growth) between CY 2012 and CY 2014. In addition, this rule implements a HH value-based purchasing (HHVBP) model, beginning January 1, 2016, in which all Medicare-certified HHAs in selected states will be required to participate. Finally, this rule finalizes minor changes to the home health quality reporting program and minor technical regulations text changes.

Vortex Advisory System : Volume 1. Effectiveness for Selected Airports.

DOT National Transportation Integrated Search

1980-05-01

The Vortex Advisory System (VAS) is based on wind criterion--when the wind near the runway end is outside of the criterion, all interarrival Instrument Flight Rules (IFR) aircraft separations can be set at 3 nautical miles. Five years of wind data ha...

Modified Dempster-Shafer approach using an expected utility interval decision rule

NASA Astrophysics Data System (ADS)

Cheaito, Ali; Lecours, Michael; Bosse, Eloi

1999-03-01

The combination operation of the conventional Dempster- Shafer algorithm has a tendency to increase exponentially the number of propositions involved in bodies of evidence by creating new ones. The aim of this paper is to explore a 'modified Dempster-Shafer' approach of fusing identity declarations emanating form different sources which include a number of radars, IFF and ESM systems in order to limit the explosion of the number of propositions. We use a non-ad hoc decision rule based on the expected utility interval to select the most probable object in a comprehensive Platform Data Base containing all the possible identity values that a potential target may take. We study the effect of the redistribution of the confidence levels of the eliminated propositions which otherwise overload the real-time data fusion system; these eliminated confidence levels can in particular be assigned to ignorance, or uniformly added to the remaining propositions and to ignorance. A scenario has been selected to demonstrate the performance of our modified Dempster-Shafer method of evidential reasoning.

Using electronic data to predict the probability of true bacteremia from positive blood cultures.

PubMed

Wang, S J; Kuperman, G J; Ohno-Machado, L; Onderdonk, A; Sandige, H; Bates, D W

2000-01-01

As part of a project to help physicians make more appropriate treatment decisions, we implemented a clinical prediction rule that computes the probability of true bacteremia for positive blood cultures and displays this information when culture results are viewed online. Prior to implementing the rule, we performed a revalidation study to verify the accuracy of the previously published logistic regression model. We randomly selected 114 cases of positive blood cultures from a recent one-year period and performed a paper chart review with the help of infectious disease experts to determine whether the cultures were true positives or contaminants. Based on the results of this revalidation study, we updated the probabilities reported by the model and made additional enhancements to improve the accuracy of the rule. Next, we implemented the rule into our hospital's laboratory computer system so that the probability information was displayed with all positive blood culture results. We displayed the prediction rule information on approximately half of the 2184 positive blood cultures at our hospital that were randomly selected during a 6-month period. During the study, we surveyed 54 housestaff to obtain their opinions about the usefulness of this intervention. Fifty percent (27/54) indicated that the information had influenced their belief of the probability of bacteremia in their patients, and in 28% (15/54) of cases it changed their treatment decision. Almost all (98% (53/54)) indicated that they wanted to continue receiving this information. We conclude that the probability information provided by this clinical prediction rule is considered useful to physicians when making treatment decisions.

77 FR 74528 - Self-Regulatory Organizations; NYSE Arca, Inc.; Notice of Filing of Proposed Rule Change Amending...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-12-14

... Equities Rule 7.31(h)(7) To Permit PL Select Orders To Interact With Incoming Orders Larger Than the Size of the PL Select Order December 7, 2012. Pursuant to Section 19(b)(1) \\1\\ of the Securities Exchange... permit PL Select Orders to interact with incoming orders larger than the size of the PL Select Order. The...

The law concerning the conduct of lineups in England and Wales: how well does it satisfy the recommendations of the American Psychology-Law Society?

PubMed

Kebbell, M R

2000-06-01

Four rules minimize the likelihood of a false conviction resulting from the misidentification of a suspect from a lineup: (1) The person conducting the lineup should not know which member of the lineup is the suspect. (2) The eyewitness should be warned that the criminal might not be present. (3) Foils should be selected based on the eyewitness's verbal description of the criminal. (4) Confidence should be recorded at the time of identification. In this paper the relevant law relating to lineups in England and Wales is outlined and the extent to which they satisfy the four rules is reviewed. It is concluded that the way in which lineups are conducted in England and Wales would, with minor modifications, satisfy the four rules, and this demonstrates that the rules can be applied practically.

Angular dependence of Raman scattering selection rules for long-wavelength optical phonons in short-period GaAs/AlAs superlattices

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

Volodin, V. A., E-mail: volodin@isp.nsc.ru; Sachkov, V. A.; Sinyukov, M. P.

2016-07-15

The angular dependence of Raman scattering selection rules for optical phonons in short-period (001) GaAs/AlAs superlattices is calculated and experimentally studied. Experiments are performed using a micro-Raman setup, in the scattering geometry with the wavevectors of the incident and scattered light lying in the plane of superlattices (so-called in-plane geometry). Phonon frequencies are calculated using the Born model taking the Coulomb interaction into account in the rigid-ion approximation. Raman scattering spectra are calculated in the framework of the deformation potential and electro-optical mechanisms. Calculations show an angular dependence of the selection rules for optical phonons with different directions of themore » wavevectors. Drastic differences in the selection rules are found for experimental and calculated spectra. Presumably, these differences are due to the Fröhlich mechanism in Raman scattering for short-period superlattices.« less

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.

Analysis of habitat-selection rules using an individual-based model

Treesearch

Steven F. Railsback; Bret C. Harvey

2002-01-01

Abstract - Despite their promise for simulating natural complexity,individual-based models (IBMs) are rarely used for ecological research or resource management. Few IBMs have been shown to reproduce realistic patterns of behavior by individual organisms.To test our IBM of stream salmonids and draw conclusions about foraging theory,we analyzed the IBM ’s ability to...

The Adverse Drug Reactions from Patient Reports in Social Media Project: Five Major Challenges to Overcome to Operationalize Analysis and Efficiently Support Pharmacovigilance Process.

PubMed

Bousquet, Cedric; Dahamna, Badisse; Guillemin-Lanne, Sylvie; Darmoni, Stefan J; Faviez, Carole; Huot, Charles; Katsahian, Sandrine; Leroux, Vincent; Pereira, Suzanne; Richard, Christophe; Schück, Stéphane; Souvignet, Julien; Lillo-Le Louët, Agnès; Texier, Nathalie

2017-09-21

Adverse drug reactions (ADRs) are an important cause of morbidity and mortality. Classical Pharmacovigilance process is limited by underreporting which justifies the current interest in new knowledge sources such as social media. The Adverse Drug Reactions from Patient Reports in Social Media (ADR-PRISM) project aims to extract ADRs reported by patients in these media. We identified 5 major challenges to overcome to operationalize the analysis of patient posts: (1) variable quality of information on social media, (2) guarantee of data privacy, (3) response to pharmacovigilance expert expectations, (4) identification of relevant information within Web pages, and (5) robust and evolutive architecture. This article aims to describe the current state of advancement of the ADR-PRISM project by focusing on the solutions we have chosen to address these 5 major challenges. In this article, we propose methods and describe the advancement of this project on several aspects: (1) a quality driven approach for selecting relevant social media for the extraction of knowledge on potential ADRs, (2) an assessment of ethical issues and French regulation for the analysis of data on social media, (3) an analysis of pharmacovigilance expert requirements when reviewing patient posts on the Internet, (4) an extraction method based on natural language processing, pattern based matching, and selection of relevant medical concepts in reference terminologies, and (5) specifications of a component-based architecture for the monitoring system. Considering the 5 major challenges, we (1) selected a set of 21 validated criteria for selecting social media to support the extraction of potential ADRs, (2) proposed solutions to guarantee data privacy of patients posting on Internet, (3) took into account pharmacovigilance expert requirements with use case diagrams and scenarios, (4) built domain-specific knowledge resources embeding a lexicon, morphological rules, context rules, semantic rules, syntactic rules, and post-analysis processing, and (5) proposed a component-based architecture that allows storage of big data and accessibility to third-party applications through Web services. We demonstrated the feasibility of implementing a component-based architecture that allows collection of patient posts on the Internet, near real-time processing of those posts including annotation, and storage in big data structures. In the next steps, we will evaluate the posts identified by the system in social media to clarify the interest and relevance of such approach to improve conventional pharmacovigilance processes based on spontaneous reporting. ©Cedric Bousquet, Badisse Dahamna, Sylvie Guillemin-Lanne, Stefan J Darmoni, Carole Faviez, Charles Huot, Sandrine Katsahian, Vincent Leroux, Suzanne Pereira, Christophe Richard, Stéphane Schück, Julien Souvignet, Agnès Lillo-Le Louët, Nathalie Texier. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 21.09.2017.

High Dimensional Classification Using Features Annealed Independence Rules.

PubMed

Fan, Jianqing; Fan, Yingying

2008-01-01

Classification using high-dimensional features arises frequently in many contemporary statistical studies such as tumor classification using microarray or other high-throughput data. The impact of dimensionality on classifications is largely poorly understood. In a seminal paper, Bickel and Levina (2004) show that the Fisher discriminant performs poorly due to diverging spectra and they propose to use the independence rule to overcome the problem. We first demonstrate that even for the independence classification rule, classification using all the features can be as bad as the random guessing due to noise accumulation in estimating population centroids in high-dimensional feature space. In fact, we demonstrate further that almost all linear discriminants can perform as bad as the random guessing. Thus, it is paramountly important to select a subset of important features for high-dimensional classification, resulting in Features Annealed Independence Rules (FAIR). The conditions under which all the important features can be selected by the two-sample t-statistic are established. The choice of the optimal number of features, or equivalently, the threshold value of the test statistics are proposed based on an upper bound of the classification error. Simulation studies and real data analysis support our theoretical results and demonstrate convincingly the advantage of our new classification procedure.

Agent-based model of angiogenesis simulates capillary sprout initiation in multicellular networks

PubMed Central

Walpole, J.; Chappell, J.C.; Cluceru, J.G.; Mac Gabhann, F.; Bautch, V.L.; Peirce, S. M.

2015-01-01

Many biological processes are controlled by both deterministic and stochastic influences. However, efforts to model these systems often rely on either purely stochastic or purely rule-based methods. To better understand the balance between stochasticity and determinism in biological processes a computational approach that incorporates both influences may afford additional insight into underlying biological mechanisms that give rise to emergent system properties. We apply a combined approach to the simulation and study of angiogenesis, the growth of new blood vessels from existing networks. This complex multicellular process begins with selection of an initiating endothelial cell, or tip cell, which sprouts from the parent vessels in response to stimulation by exogenous cues. We have constructed an agent-based model of sprouting angiogenesis to evaluate endothelial cell sprout initiation frequency and location, and we have experimentally validated it using high-resolution time-lapse confocal microscopy. ABM simulations were then compared to a Monte Carlo model, revealing that purely stochastic simulations could not generate sprout locations as accurately as the rule-informed agent-based model. These findings support the use of rule-based approaches for modeling the complex mechanisms underlying sprouting angiogenesis over purely stochastic methods. PMID:26158406

Agent-based model of angiogenesis simulates capillary sprout initiation in multicellular networks.

PubMed

Walpole, J; Chappell, J C; Cluceru, J G; Mac Gabhann, F; Bautch, V L; Peirce, S M

2015-09-01

Many biological processes are controlled by both deterministic and stochastic influences. However, efforts to model these systems often rely on either purely stochastic or purely rule-based methods. To better understand the balance between stochasticity and determinism in biological processes a computational approach that incorporates both influences may afford additional insight into underlying biological mechanisms that give rise to emergent system properties. We apply a combined approach to the simulation and study of angiogenesis, the growth of new blood vessels from existing networks. This complex multicellular process begins with selection of an initiating endothelial cell, or tip cell, which sprouts from the parent vessels in response to stimulation by exogenous cues. We have constructed an agent-based model of sprouting angiogenesis to evaluate endothelial cell sprout initiation frequency and location, and we have experimentally validated it using high-resolution time-lapse confocal microscopy. ABM simulations were then compared to a Monte Carlo model, revealing that purely stochastic simulations could not generate sprout locations as accurately as the rule-informed agent-based model. These findings support the use of rule-based approaches for modeling the complex mechanisms underlying sprouting angiogenesis over purely stochastic methods.

Electrophysiological responses to feedback during the application of abstract rules.

PubMed

Walsh, Matthew M; Anderson, John R

2013-11-01

Much research focuses on how people acquire concrete stimulus-response associations from experience; however, few neuroscientific studies have examined how people learn about and select among abstract rules. To address this issue, we recorded ERPs as participants performed an abstract rule-learning task. In each trial, they viewed a sample number and two test numbers. Participants then chose a test number using one of three abstract mathematical rules they freely selected from: greater than the sample number, less than the sample number, or equal to the sample number. No one rule was always rewarded, but some rules were rewarded more frequently than others. To maximize their earnings, participants needed to learn which rules were rewarded most frequently. All participants learned to select the best rules for repeating and novel stimulus sets that obeyed the overall reward probabilities. Participants differed, however, in the extent to which they overgeneralized those rules to repeating stimulus sets that deviated from the overall reward probabilities. The feedback-related negativity (FRN), an ERP component thought to reflect reward prediction error, paralleled behavior. The FRN was sensitive to item-specific reward probabilities in participants who detected the deviant stimulus set, and the FRN was sensitive to overall reward probabilities in participants who did not. These results show that the FRN is sensitive to the utility of abstract rules and that the individual's representation of a task's states and actions shapes behavior as well as the FRN.

Electrophysiological Responses to Feedback during the Application of Abstract Rules

PubMed Central

Walsh, Matthew M.; Anderson, John R.

2017-01-01

Much research focuses on how people acquire concrete stimulus–response associations from experience; however, few neuroscientific studies have examined how people learn about and select among abstract rules. To address this issue, we recorded ERPs as participants performed an abstract rule-learning task. In each trial, they viewed a sample number and two test numbers. Participants then chose a test number using one of three abstract mathematical rules they freely selected from: greater than the sample number, less than the sample number, or equal to the sample number. No one rule was always rewarded, but some rules were rewarded more frequently than others. To maximize their earnings, participants needed to learn which rules were rewarded most frequently. All participants learned to select the best rules for repeating and novel stimulus sets that obeyed the overall reward probabilities. Participants differed, however, in the extent to which they overgeneralized those rules to repeating stimulus sets that deviated from the overall reward probabilities. The feedback-related negativity (FRN), an ERP component thought to reflect reward prediction error, paralleled behavior. The FRN was sensitive to item-specific reward probabilities in participants who detected the deviant stimulus set, and the FRN was sensitive to overall reward probabilities in participants who did not. These results show that the FRN is sensitive to the utility of abstract rules and that the individualʼs representation of a taskʼs states and actions shapes behavior as well as the FRN. PMID:23915052

Evaluation of a rule-based method for epidemiological document classification towards the automation of systematic reviews.

PubMed

Karystianis, George; Thayer, Kristina; Wolfe, Mary; Tsafnat, Guy

2017-06-01

Most data extraction efforts in epidemiology are focused on obtaining targeted information from clinical trials. In contrast, limited research has been conducted on the identification of information from observational studies, a major source for human evidence in many fields, including environmental health. The recognition of key epidemiological information (e.g., exposures) through text mining techniques can assist in the automation of systematic reviews and other evidence summaries. We designed and applied a knowledge-driven, rule-based approach to identify targeted information (study design, participant population, exposure, outcome, confounding factors, and the country where the study was conducted) from abstracts of epidemiological studies included in several systematic reviews of environmental health exposures. The rules were based on common syntactical patterns observed in text and are thus not specific to any systematic review. To validate the general applicability of our approach, we compared the data extracted using our approach versus hand curation for 35 epidemiological study abstracts manually selected for inclusion in two systematic reviews. The returned F-score, precision, and recall ranged from 70% to 98%, 81% to 100%, and 54% to 97%, respectively. The highest precision was observed for exposure, outcome and population (100%) while recall was best for exposure and study design with 97% and 89%, respectively. The lowest recall was observed for the population (54%), which also had the lowest F-score (70%). The generated performance of our text-mining approach demonstrated encouraging results for the identification of targeted information from observational epidemiological study abstracts related to environmental exposures. We have demonstrated that rules based on generic syntactic patterns in one corpus can be applied to other observational study design by simple interchanging the dictionaries aiming to identify certain characteristics (i.e., outcomes, exposures). At the document level, the recognised information can assist in the selection and categorization of studies included in a systematic review. Copyright © 2017 Elsevier Inc. All rights reserved.

20 CFR 667.825 - What special rules apply to reviews of NFJP and WIA INA grant selections?

Code of Federal Regulations, 2011 CFR

2011-04-01

... 20 Employees' Benefits 3 2011-04-01 2011-04-01 false What special rules apply to reviews of NFJP and WIA INA grant selections? 667.825 Section 667.825 Employees' Benefits EMPLOYMENT AND TRAINING... competition and for the area and will select a grantee through the normal competitive process. ...

Development of expert system for biobased polymer material selection: food packaging application.

PubMed

Sanyang, M L; Sapuan, S M

2015-10-01

Biobased food packaging materials are gaining more attention owing to their intrinsic biodegradable nature and renewability. Selection of suitable biobased polymers for food packaging applications could be a tedious task with potential mistakes in choosing the best materials. In this paper, an expert system was developed using Exsys Corvid software to select suitable biobased polymer materials for packaging fruits, dry food and dairy products. If - Then rule based system was utilized to accomplish the material selection process whereas a score system was formulated to facilitate the ranking of selected materials. The expert system selected materials that satisfied all constraints and selection results were presented in suitability sequence depending on their scores. The expert system selected polylactic acid (PLA) as the most suitable material.

Missing-value estimation using linear and non-linear regression with Bayesian gene selection.

PubMed

Zhou, Xiaobo; Wang, Xiaodong; Dougherty, Edward R

2003-11-22

Data from microarray experiments are usually in the form of large matrices of expression levels of genes under different experimental conditions. Owing to various reasons, there are frequently missing values. Estimating these missing values is important because they affect downstream analysis, such as clustering, classification and network design. Several methods of missing-value estimation are in use. The problem has two parts: (1) selection of genes for estimation and (2) design of an estimation rule. We propose Bayesian variable selection to obtain genes to be used for estimation, and employ both linear and nonlinear regression for the estimation rule itself. Fast implementation issues for these methods are discussed, including the use of QR decomposition for parameter estimation. The proposed methods are tested on data sets arising from hereditary breast cancer and small round blue-cell tumors. The results compare very favorably with currently used methods based on the normalized root-mean-square error. The appendix is available from http://gspsnap.tamu.edu/gspweb/zxb/missing_zxb/ (user: gspweb; passwd: gsplab).

78 FR 55339 - Regulatory Capital Rules: Regulatory Capital, Implementation of Basel III, Capital Adequacy...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-09-10

...The Federal Deposit Insurance Corporation (FDIC) is adopting an interim final rule that revises its risk-based and leverage capital requirements for FDIC-supervised institutions. This interim final rule is substantially identical to a joint final rule issued by the Office of the Comptroller of the Currency (OCC) and the Board of Governors of the Federal Reserve System (Federal Reserve) (together, with the FDIC, the agencies). The interim final rule consolidates three separate notices of proposed rulemaking that the agencies jointly published in the Federal Register on August 30, 2012, with selected changes. The interim final rule implements a revised definition of regulatory capital, a new common equity tier 1 minimum capital requirement, a higher minimum tier 1 capital requirement, and, for FDIC-supervised institutions subject to the advanced approaches risk-based capital rules, a supplementary leverage ratio that incorporates a broader set of exposures in the denominator. The interim final rule incorporates these new requirements into the FDIC's prompt corrective action (PCA) framework. In addition, the interim final rule establishes limits on FDIC-supervised institutions' capital distributions and certain discretionary bonus payments if the FDIC-supervised institution does not hold a specified amount of common equity tier 1 capital in addition to the amount necessary to meet its minimum risk-based capital requirements. The interim final rule amends the methodologies for determining risk-weighted assets for all FDIC-supervised institutions. The interim final rule also adopts changes to the FDIC's regulatory capital requirements that meet the requirements of section 171 and section 939A of the Dodd-Frank Wall Street Reform and Consumer Protection Act. The interim final rule also codifies the FDIC's regulatory capital rules, which have previously resided in various appendices to their respective regulations, into a harmonized integrated regulatory framework. In addition, the FDIC is amending the market risk capital rule (market risk rule) to apply to state savings associations. The FDIC is issuing these revisions to its capital regulations as an interim final rule. The FDIC invites comments on the interaction of this rule with other proposed leverage ratio requirements applicable to large, systemically important banking organizations. This interim final rule otherwise contains regulatory text that is identical to the common rule text adopted as a final rule by the Federal Reserve and the OCC. This interim final rule enables the FDIC to proceed on a unified, expedited basis with the other federal banking agencies pending consideration of other issues. Specifically, the FDIC intends to evaluate this interim final rule in the context of the proposed well- capitalized and buffer levels of the supplementary leverage ratio applicable to large, systemically important banking organizations, as described in a separate Notice of Proposed Rulemaking (NPR) published in the Federal Register August 20, 2013. The FDIC is seeking commenters' views on the interaction of this interim final rule with the proposed rule regarding the supplementary leverage ratio for large, systemically important banking organizations.

Molnets: An Artificial Chemistry Based on Neural Networks

NASA Technical Reports Server (NTRS)

Colombano, Silvano; Luk, Johnny; Segovia-Juarez, Jose L.; Lohn, Jason; Clancy, Daniel (Technical Monitor)

2002-01-01

The fundamental problem in the evolution of matter is to understand how structure-function relationships are formed and increase in complexity from the molecular level all the way to a genetic system. We have created a system where structure-function relationships arise naturally and without the need of ad hoc function assignments to given structures. The idea was inspired by neural networks, where the structure of the net embodies specific computational properties. In this system networks interact with other networks to create connections between the inputs of one net and the outputs of another. The newly created net then recomputes its own synaptic weights, based on anti-hebbian rules. As a result some connections may be cut, and multiple nets can emerge as products of a 'reaction'. The idea is to study emergent reaction behaviors, based on simple rules that constitute a pseudophysics of the system. These simple rules are parameterized to produce behaviors that emulate chemical reactions. We find that these simple rules show a gradual increase in the size and complexity of molecules. We have been building a virtual artificial chemistry laboratory for discovering interesting reactions and for testing further ideas on the evolution of primitive molecules. Some of these ideas include the potential effect of membranes and selective diffusion according to molecular size.

Learning a New Selection Rule in Visual and Frontal Cortex.

PubMed

van der Togt, Chris; Stănişor, Liviu; Pooresmaeili, Arezoo; Albantakis, Larissa; Deco, Gustavo; Roelfsema, Pieter R

2016-08-01

How do you make a decision if you do not know the rules of the game? Models of sensory decision-making suggest that choices are slow if evidence is weak, but they may only apply if the subject knows the task rules. Here, we asked how the learning of a new rule influences neuronal activity in the visual (area V1) and frontal cortex (area FEF) of monkeys. We devised a new icon-selection task. On each day, the monkeys saw 2 new icons (small pictures) and learned which one was relevant. We rewarded eye movements to a saccade target connected to the relevant icon with a curve. Neurons in visual and frontal cortex coded the monkey's choice, because the representation of the selected curve was enhanced. Learning delayed the neuronal selection signals and we uncovered the cause of this delay in V1, where learning to select the relevant icon caused an early suppression of surrounding image elements. These results demonstrate that the learning of a new rule causes a transition from fast and random decisions to a more considerate strategy that takes additional time and they reveal the contribution of visual and frontal cortex to the learning process. © The Author 2016. Published by Oxford University Press.

In-silico evidences for binding of Glucokinase activators to EGFR C797S to overcome EGFR resistance obstacle with mutant-selective allosteric inhibition.

PubMed

Patel, Harun; Pawara, Rahul; Surana, Sanjay

2018-03-29

The tyrosine kinase inhibitors (TKI) against epidermal growth factor receptor (EGFR) are generally utilized as a part of patients with non-small cell lung carcinoma (NSCLC). However, EGFR T790M mutation results in resistance to most clinically available EGFR TKIs. Third-generation EGFR TKIs against the T790M mutation has been in active clinical development to triumph the resistance problem; they covalently bind with conserved Cys797 inside the EGFR active site, offering both potency and kinase-selectivity. Third generation drugs target C797, which makes the C797S resistance mutation more subtle. EGFR C797S mutation was accounted to be a main mechanism of resistance to the third-generation inhibitors. The C797S mutation gives off an impression of being an ideal target for conquering the acquired resistance to the third generation inhibitors. We have performed structure based-virtual screening strategies for binding of glucokinase activator to EGFR C797S, which can overcome EGFR resistance impediment with mutant-selective allosteric inhibition towards all kinds of mutant EGFR (T790M, L858R, TMLR) and WT EGFR. The final filter of Lipinski's Rule of Five, Jargan's Rule of Three and in silico ADME predictions gave 23 hits, which conform to Lipinski's rule and Jorgensen's rule and all their pharmacokinetic parameters are inside the appropriate range characterized for human use, in this manner demonstrating their potential as a drug-like molecule. Copyright © 2018 Elsevier Ltd. All rights reserved.

Hamilton's missing link.

PubMed

van Veelen, Matthijs

2007-06-07

Hamilton's famous rule was presented in 1964 in a paper called "The genetical theory of social behaviour (I and II)", Journal of Theoretical Biology 7, 1-16, 17-32. The paper contains a mathematical genetical model from which the rule supposedly follows, but it does not provide a link between the paper's central result, which states that selection dynamics take the population to a state where mean inclusive fitness is maximized, and the rule, which states that selection will lead to maximization of individual inclusive fitness. This note provides a condition under which Hamilton's rule does follow from his central result.

EXADS - EXPERT SYSTEM FOR AUTOMATED DESIGN SYNTHESIS

NASA Technical Reports Server (NTRS)

Rogers, J. L.

1994-01-01

The expert system called EXADS was developed to aid users of the Automated Design Synthesis (ADS) general purpose optimization program. Because of the general purpose nature of ADS, it is difficult for a nonexpert to select the best choice of strategy, optimizer, and one-dimensional search options from the one hundred or so combinations that are available. EXADS aids engineers in determining the best combination based on their knowledge of the problem and the expert knowledge previously stored by experts who developed ADS. EXADS is a customized application of the AESOP artificial intelligence program (the general version of AESOP is available separately from COSMIC. The ADS program is also available from COSMIC.) The expert system consists of two main components. The knowledge base contains about 200 rules and is divided into three categories: constrained, unconstrained, and constrained treated as unconstrained. The EXADS inference engine is rule-based and makes decisions about a particular situation using hypotheses (potential solutions), rules, and answers to questions drawn from the rule base. EXADS is backward-chaining, that is, it works from hypothesis to facts. The rule base was compiled from sources such as literature searches, ADS documentation, and engineer surveys. EXADS will accept answers such as yes, no, maybe, likely, and don't know, or a certainty factor ranging from 0 to 10. When any hypothesis reaches a confidence level of 90% or more, it is deemed as the best choice and displayed to the user. If no hypothesis is confirmed, the user can examine explanations of why the hypotheses failed to reach the 90% level. The IBM PC version of EXADS is written in IQ-LISP for execution under DOS 2.0 or higher with a central memory requirement of approximately 512K of 8 bit bytes. This program was developed in 1986.

Application of artificial intelligence (AI) concepts to the development of space flight parts approval model

NASA Technical Reports Server (NTRS)

Krishnan, G. S.

1997-01-01

A cost effective model which uses the artificial intelligence techniques in the selection and approval of parts is presented. The knowledge which is acquired from the specialists for different part types are represented in a knowledge base in the form of rules and objects. The parts information is stored separately in a data base and is isolated from the knowledge base. Validation, verification and performance issues are highlighted.

Logistic-based patient grouping for multi-disciplinary treatment.

PubMed

Maruşter, Laura; Weijters, Ton; de Vries, Geerhard; van den Bosch, Antal; Daelemans, Walter

2002-01-01

Present-day healthcare witnesses a growing demand for coordination of patient care. Coordination is needed especially in those cases in which hospitals have structured healthcare into specialty-oriented units, while a substantial portion of patient care is not limited to single units. From a logistic point of view, this multi-disciplinary patient care creates a tension between controlling the hospital's units, and the need for a control of the patient flow between units. A possible solution is the creation of new units in which different specialties work together for specific groups of patients. A first step in this solution is to identify the salient patient groups in need of multi-disciplinary care. Grouping techniques seem to offer a solution. However, most grouping approaches in medicine are driven by a search for pathophysiological homogeneity. In this paper, we present an alternative logistic-driven grouping approach. The starting point of our approach is a database with medical cases for 3,603 patients with peripheral arterial vascular (PAV) diseases. For these medical cases, six basic logistic variables (such as the number of visits to different specialist) are selected. Using these logistic variables, clustering techniques are used to group the medical cases in logistically homogeneous groups. In our approach, the quality of the resulting grouping is not measured by statistical significance, but by (i) the usefulness of the grouping for the creation of new multi-disciplinary units; (ii) how well patients can be selected for treatment in the new units. Given a priori knowledge of a patient (e.g. age, diagnosis), machine learning techniques are employed to induce rules that can be used for the selection of the patients eligible for treatment in the new units. In the paper, we describe the results of the above-proposed methodology for patients with PAV diseases. Two groupings and the accompanied classification rule sets are presented. One grouping is based on all the logistic variables, and another grouping is based on two latent factors found by applying factor analysis. On the basis of the experimental results, we can conclude that it is possible to search for medical logistic homogenous groups (i) that can be characterized by rules based on the aggregated logistic variables; (ii) for which we can formulate rules to predict to which cluster new patients belong.

Research on cutting path optimization of sheet metal parts based on ant colony algorithm

NASA Astrophysics Data System (ADS)

Wu, Z. Y.; Ling, H.; Li, L.; Wu, L. H.; Liu, N. B.

2017-09-01

In view of the disadvantages of the current cutting path optimization methods of sheet metal parts, a new method based on ant colony algorithm was proposed in this paper. The cutting path optimization problem of sheet metal parts was taken as the research object. The essence and optimization goal of the optimization problem were presented. The traditional serial cutting constraint rule was improved. The cutting constraint rule with cross cutting was proposed. The contour lines of parts were discretized and the mathematical model of cutting path optimization was established. Thus the problem was converted into the selection problem of contour lines of parts. Ant colony algorithm was used to solve the problem. The principle and steps of the algorithm were analyzed.

Performance of Thirteen Clinical Rules to Distinguish Bacterial and Presumed Viral Meningitis in Vietnamese Children

PubMed Central

Huy, Nguyen Tien; Thao, Nguyen Thanh Hong; Tuan, Nguyen Anh; Khiem, Nguyen Tuan; Moore, Christopher C.; Thi Ngoc Diep, Doan; Hirayama, Kenji

2012-01-01

Background and Purpose Successful outcomes from bacterial meningitis require rapid antibiotic treatment; however, unnecessary treatment of viral meningitis may lead to increased toxicities and expense. Thus, improved diagnostics are required to maximize treatment and minimize side effects and cost. Thirteen clinical decision rules have been reported to identify bacterial from viral meningitis. However, few rules have been tested and compared in a single study, while several rules are yet to be tested by independent researchers or in pediatric populations. Thus, simultaneous test and comparison of these rules are required to enable clinicians to select an optimal diagnostic rule for bacterial meningitis in settings and populations similar to ours. Methods A retrospective cross-sectional study was conducted at the Infectious Department of Pediatric Hospital Number 1, Ho Chi Minh City, Vietnam. The performance of the clinical rules was evaluated by area under a receiver operating characteristic curve (ROC-AUC) using the method of DeLong and McNemar test for specificity comparison. Results Our study included 129 patients, of whom 80 had bacterial meningitis and 49 had presumed viral meningitis. Spanos's rule had the highest AUC at 0.938 but was not significantly greater than other rules. No rule provided 100% sensitivity with a specificity higher than 50%. Based on our calculation of theoretical sensitivity and specificity, we suggest that a perfect rule requires at least four independent variables that posses both sensitivity and specificity higher than 85–90%. Conclusions No clinical decision rules provided an acceptable specificity (>50%) with 100% sensitivity when applying our data set in children. More studies in Vietnam and developing countries are required to develop and/or validate clinical rules and more very good biomarkers are required to develop such a perfect rule. PMID:23209715

Performance of thirteen clinical rules to distinguish bacterial and presumed viral meningitis in Vietnamese children.

PubMed

Huy, Nguyen Tien; Thao, Nguyen Thanh Hong; Tuan, Nguyen Anh; Khiem, Nguyen Tuan; Moore, Christopher C; Thi Ngoc Diep, Doan; Hirayama, Kenji

2012-01-01

Successful outcomes from bacterial meningitis require rapid antibiotic treatment; however, unnecessary treatment of viral meningitis may lead to increased toxicities and expense. Thus, improved diagnostics are required to maximize treatment and minimize side effects and cost. Thirteen clinical decision rules have been reported to identify bacterial from viral meningitis. However, few rules have been tested and compared in a single study, while several rules are yet to be tested by independent researchers or in pediatric populations. Thus, simultaneous test and comparison of these rules are required to enable clinicians to select an optimal diagnostic rule for bacterial meningitis in settings and populations similar to ours. A retrospective cross-sectional study was conducted at the Infectious Department of Pediatric Hospital Number 1, Ho Chi Minh City, Vietnam. The performance of the clinical rules was evaluated by area under a receiver operating characteristic curve (ROC-AUC) using the method of DeLong and McNemar test for specificity comparison. Our study included 129 patients, of whom 80 had bacterial meningitis and 49 had presumed viral meningitis. Spanos's rule had the highest AUC at 0.938 but was not significantly greater than other rules. No rule provided 100% sensitivity with a specificity higher than 50%. Based on our calculation of theoretical sensitivity and specificity, we suggest that a perfect rule requires at least four independent variables that posses both sensitivity and specificity higher than 85-90%. No clinical decision rules provided an acceptable specificity (>50%) with 100% sensitivity when applying our data set in children. More studies in Vietnam and developing countries are required to develop and/or validate clinical rules and more very good biomarkers are required to develop such a perfect rule.

Multiple systems of category learning.

PubMed

Smith, Edward E; Grossman, Murray

2008-01-01

We review neuropsychological and neuroimaging evidence for the existence of three qualitatively different categorization systems. These categorization systems are themselves based on three distinct memory systems: working memory (WM), explicit long-term memory (explicit LTM), and implicit long-term memory (implicit LTM). We first contrast categorization based on WM with that based on explicit LTM, where the former typically involves applying rules to a test item and the latter involves determining the similarity between stored exemplars or prototypes and a test item. Neuroimaging studies show differences between brain activity in normal participants as a function of whether they are instructed to categorize novel test items by rule or by similarity to known category members. Rule instructions typically lead to more activation in frontal or parietal areas, associated with WM and selective attention, whereas similarity instructions may activate parietal areas associated with the integration of perceptual features. Studies with neurological patients in the same paradigms provide converging evidence, e.g., patients with Alzheimer's disease, who have damage in prefrontal regions, are more impaired with rule than similarity instructions. Our second contrast is between categorization based on explicit LTM with that based on implicit LTM. Neuropsychological studies with patients with medial-temporal lobe damage show that patients are impaired on tasks requiring explicit LTM, but perform relatively normally on an implicit categorization task. Neuroimaging studies provide converging evidence: whereas explicit categorization is mediated by activation in numerous frontal and parietal areas, implicit categorization is mediated by a deactivation in posterior cortex.

Beyond Molecular Codes: Simple Rules to Wire Complex Brains

PubMed Central

Hassan, Bassem A.; Hiesinger, P. Robin

2015-01-01

Summary Molecular codes, like postal zip codes, are generally considered a robust way to ensure the specificity of neuronal target selection. However, a code capable of unambiguously generating complex neural circuits is difficult to conceive. Here, we re-examine the notion of molecular codes in the light of developmental algorithms. We explore how molecules and mechanisms that have been considered part of a code may alternatively implement simple pattern formation rules sufficient to ensure wiring specificity in neural circuits. This analysis delineates a pattern-based framework for circuit construction that may contribute to our understanding of brain wiring. PMID:26451480

Circular analysis in complex stochastic systems

PubMed Central

Valleriani, Angelo

2015-01-01

Ruling out observations can lead to wrong models. This danger occurs unwillingly when one selects observations, experiments, simulations or time-series based on their outcome. In stochastic processes, conditioning on the future outcome biases all local transition probabilities and makes them consistent with the selected outcome. This circular self-consistency leads to models that are inconsistent with physical reality. It is also the reason why models built solely on macroscopic observations are prone to this fallacy. PMID:26656656

An Intelligent computer-aided tutoring system for diagnosing anomalies of spacecraft in operation

NASA Technical Reports Server (NTRS)

Rolincik, Mark; Lauriente, Michael; Koons, Harry C.; Gorney, David

1993-01-01

A new rule-based, expert system for diagnosing spacecraft anomalies is under development. The knowledge base consists of over two-hundred (200) rules and provides links to historical and environmental databases. Environmental causes considered are bulk charging, single event upsets (SEU), surface charging, and total radiation dose. The system's driver translates forward chaining rules into a backward chaining sequence, prompting the user for information pertinent to the causes considered. When the user selects the novice mode, the system automatically gives detailed explanations and descriptions of terms and reasoning as the session progresses, in a sense teaching the user. As such it is an effective tutoring tool. The use of heuristics frees the user from searching through large amounts of irrelevant information and allows the user to input partial information (varying degrees of confidence in an answer) or 'unknown' to any question. The system is available on-line and uses C Language Integrated Production System (CLIPS), an expert shell developed by the NASA Johnson Space Center AI Laboratory in Houston.

Evaluation of Anomaly Detection Capability for Ground-Based Pre-Launch Shuttle Operations. Chapter 8

NASA Technical Reports Server (NTRS)

Martin, Rodney Alexander

2010-01-01

This chapter will provide a thorough end-to-end description of the process for evaluation of three different data-driven algorithms for anomaly detection to select the best candidate for deployment as part of a suite of IVHM (Integrated Vehicle Health Management) technologies. These algorithms were deemed to be sufficiently mature enough to be considered viable candidates for deployment in support of the maiden launch of Ares I-X, the successor to the Space Shuttle for NASA's Constellation program. Data-driven algorithms are just one of three different types being deployed. The other two types of algorithms being deployed include a "nile-based" expert system, and a "model-based" system. Within these two categories, the deployable candidates have already been selected based upon qualitative factors such as flight heritage. For the rule-based system, SHINE (Spacecraft High-speed Inference Engine) has been selected for deployment, which is a component of BEAM (Beacon-based Exception Analysis for Multimissions), a patented technology developed at NASA's JPL (Jet Propulsion Laboratory) and serves to aid in the management and identification of operational modes. For the "model-based" system, a commercially available package developed by QSI (Qualtech Systems, Inc.), TEAMS (Testability Engineering and Maintenance System) has been selected for deployment to aid in diagnosis. In the context of this particular deployment, distinctions among the use of the terms "data-driven," "rule-based," and "model-based," can be found in. Although there are three different categories of algorithms that have been selected for deployment, our main focus in this chapter will be on the evaluation of three candidates for data-driven anomaly detection. These algorithms will be evaluated upon their capability for robustly detecting incipient faults or failures in the ground-based phase of pre-launch space shuttle operations, rather than based oil heritage as performed in previous studies. Robust detection will allow for the achievement of pre-specified minimum false alarm and/or missed detection rates in the selection of alert thresholds. All algorithms will also be optimized with respect to an aggregation of these same criteria. Our study relies upon the use of Shuttle data to act as was a proxy for and in preparation for application to Ares I-X data, which uses a very similar hardware platform for the subsystems that are being targeted (TVC - Thrust Vector Control subsystem for the SRB (Solid Rocket Booster)).

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

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.

Synthesis of Polysyllabic Sequences of Thai Tones Using a Generative Model of Fundamental Frequency Contours

NASA Astrophysics Data System (ADS)

Seresangtakul, Pusadee; Takara, Tomio

In this paper, the distinctive tones of Thai in running speech are studied. We present rules to synthesize F0 contours of Thai tones in running speech by using the generative model of F0 contours. Along with our method, the pitch contours of Thai polysyllabic words, both disyllabic and trisyllabic words, were analyzed. The coarticulation effect of Thai tones in running speech were found. Based on the analysis of the polysyllabic words using this model, rules are derived and applied to synthesize Thai polysyllabic tone sequences. We performed listening tests to evaluate intelligibility of the rules for Thai tones generation. The average intelligibility scores became 98.8%, and 96.6% for disyllabic and trisyllabic words, respectively. From these result, the rule of the tones' generation was shown to be effective. Furthermore, we constructed the connecting rules to synthesize suprasegmental F0 contours using the trisyllable training rules' parameters. The parameters of the first, the third, and the second syllables were selected and assigned to the initial, the ending, and the remaining syllables in a sentence, respectively. Even such a simple rule, the synthesized phrases/senetences were completely identified in listening tests. The MOSs (Mean Opinion Score) was 3.50 while the original and analysis/synthesis samples were 4.82 and 3.59, respectively.

Revisiting negative selection algorithms.

PubMed

Ji, Zhou; Dasgupta, Dipankar

2007-01-01

This paper reviews the progress of negative selection algorithms, an anomaly/change detection approach in Artificial Immune Systems (AIS). Following its initial model, we try to identify the fundamental characteristics of this family of algorithms and summarize their diversities. There exist various elements in this method, including data representation, coverage estimate, affinity measure, and matching rules, which are discussed for different variations. The various negative selection algorithms are categorized by different criteria as well. The relationship and possible combinations with other AIS or other machine learning methods are discussed. Prospective development and applicability of negative selection algorithms and their influence on related areas are then speculated based on the discussion.

Self-Interest and the Design of Rules.

PubMed

Singh, Manvir; Wrangham, Richard; Glowacki, Luke

2017-12-01

Rules regulating social behavior raise challenging questions about cultural evolution in part because they frequently confer group-level benefits. Current multilevel selection theories contend that between-group processes interact with within-group processes to produce norms and institutions, but within-group processes have remained underspecified, leading to a recent emphasis on cultural group selection as the primary driver of cultural design. Here we present the self-interested enforcement (SIE) hypothesis, which proposes that the design of rules importantly reflects the relative enforcement capacities of competing parties. We show that, in addition to explaining patterns in cultural change and stability, SIE can account for the emergence of much group-functional culture. We outline how this process can stifle or accelerate cultural group selection, depending on various social conditions. Self-interested enforcement has important bearings on the emergence, stability, and change of rules.

Primer on clinical acid-base problem solving.

PubMed

Whittier, William L; Rutecki, Gregory W

2004-03-01

Acid-base problem solving has been an integral part of medical practice in recent generations. Diseases discovered in the last 30-plus years, for example, Bartter syndrome and Gitelman syndrome, D-lactic acidosis, and bulimia nervosa, can be diagnosed according to characteristic acid-base findings. Accuracy in acid-base problem solving is a direct result of a reproducible, systematic approach to arterial pH, partial pressure of carbon dioxide, bicarbonate concentration, and electrolytes. The 'Rules of Five' is one tool that enables clinicians to determine the cause of simple and complex disorders, even triple acid-base disturbances, with consistency. In addition, other electrolyte abnormalities that accompany acid-base disorders, such as hypokalemia, can be incorporated into algorithms that complement the Rules and contribute to efficient problem solving in a wide variety of diseases. Recently urine electrolytes have also assisted clinicians in further characterizing select disturbances. Acid-base patterns, in many ways, can serve as a 'common diagnostic pathway' shared by all subspecialties in medicine. From infectious disease (eg, lactic acidemia with highly active antiviral therapy therapy) through endocrinology (eg, Conn's syndrome, high urine chloride alkalemia) to the interface between primary care and psychiatry (eg, bulimia nervosa with multiple potential acid-base disturbances), acid-base problem solving is the key to unlocking otherwise unrelated diagnoses. Inasmuch as the Rules are clinical tools, they are applied throughout this monograph to diverse pathologic conditions typical in contemporary practice.

Cholinergic Overstimulation Attenuates Rule Selectivity in Macaque Prefrontal Cortex.

PubMed

Major, Alex J; Vijayraghavan, Susheel; Everling, Stefan

2018-01-31

Acetylcholine is released in the prefrontal cortex (PFC) and is a key modulator of cognitive performance in primates. Cholinergic stimulation has been shown to have beneficial effects on performance of cognitive tasks, and cholinergic receptors are being actively explored as promising targets for ameliorating cognitive deficits in Alzheimer's disease. We hypothesized that cholinergic stimulation of PFC during performance of a cognitive task would augment neuronal activity and neuronal coding of task attributes. We iontophoretically applied the general cholinergic receptor agonist carbachol onto neurons in dorsolateral PFC (DLPFC) of male rhesus macaques performing rule-guided prosaccades and antisaccades, a well established oculomotor task for testing cognitive control. Carbachol application had heterogeneous effects on neuronal excitability, with both excitation and suppression observed in significant proportions. Contrary to our prediction, neurons with rule-selective activity exhibited a reduction in selectivity during carbachol application. Cholinergic stimulation disrupted rule selectivity regardless of whether it had suppressive or excitatory effects on these neurons. In addition, cholinergic stimulation excited putative pyramidal neurons, whereas the activity of putative interneurons remained unchanged. Moreover, cholinergic stimulation attenuated saccade direction selectivity in putative pyramidal neurons due to nonspecific increases in activity. Our results suggest excessive cholinergic stimulation has detrimental effects on DLPFC representations of task attributes. These findings delineate the complexity and heterogeneity of neuromodulation of cerebral cortex by cholinergic stimulation, an area of active exploration with respect to the development of cognitive enhancers. SIGNIFICANCE STATEMENT The neurotransmitter acetylcholine is known to be important for cognitive processes in the prefrontal cortex. Removal of acetylcholine from prefrontal cortex can disrupt short-term memory performance and is reminiscent of Alzheimer's disease, which is characterized by degeneration of acetylcholine-producing neurons. Stimulation of cholinergic receptors is being explored to create cognitive enhancers for the treatment of Alzheimer's disease and other psychiatric diseases. Here, we stimulated cholinergic receptors in prefrontal cortex and examined its effects on neurons that are engaged in cognitive behavior. Surprisingly, cholinergic stimulation decreased neurons' ability to discriminate between rules. This work suggests that overstimulation of acetylcholine receptors could disrupt neuronal processing during cognition and is relevant to the design of cognitive enhancers based on stimulating the cholinergic system. Copyright © 2018 the authors 0270-6474/18/381137-14$15.00/0.

77 FR 73500 - Self-Regulatory Organizations; NYSE Arca, Inc.; Notice of Filing of Proposed Rule Change Relating...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-12-10

... Trading of Shares of the Horizons S&P 500 Covered Call ETF, Horizons S&P Financial Select Sector Covered Call ETF, and Horizons S&P Energy Select Sector Covered Call ETF Under NYSE Arca Equities Rule 5.2(j)(3... and trade shares (``Shares'') of the Horizons S&P 500 Covered Call ETF, Horizons S&P Financial Select...

Moral empiricism and the bias for act-based rules.

PubMed

Ayars, Alisabeth; Nichols, Shaun

2017-10-01

Previous studies on rule learning show a bias in favor of act-based rules, which prohibit intentionally producing an outcome but not merely allowing the outcome. Nichols, Kumar, Lopez, Ayars, and Chan (2016) found that exposure to a single sample violation in which an agent intentionally causes the outcome was sufficient for participants to infer that the rule was act-based. One explanation is that people have an innate bias to think rules are act-based. We suggest an alternative empiricist account: since most rules that people learn are act-based, people form an overhypothesis (Goodman, 1955) that rules are typically act-based. We report three studies that indicate that people can use information about violations to form overhypotheses about rules. In study 1, participants learned either three "consequence-based" rules that prohibited allowing an outcome or three "act-based" rules that prohibiting producing the outcome; in a subsequent learning task, we found that participants who had learned three consequence-based rules were more likely to think that the new rule prohibited allowing an outcome. In study 2, we presented participants with either 1 consequence-based rule or 3 consequence-based rules, and we found that those exposed to 3 such rules were more likely to think that a new rule was also consequence based. Thus, in both studies, it seems that learning 3 consequence-based rules generates an overhypothesis to expect new rules to be consequence-based. In a final study, we used a more subtle manipulation. We exposed participants to examples act-based or accident-based (strict liability) laws and then had them learn a novel rule. We found that participants who were exposed to the accident-based laws were more likely to think a new rule was accident-based. The fact that participants' bias for act-based rules can be shaped by evidence from other rules supports the idea that the bias for act-based rules might be acquired as an overhypothesis from the preponderance of act-based rules. Copyright © 2017 Elsevier B.V. All rights reserved.

Stratification of the severity of critically ill patients with classification trees

PubMed Central

2009-01-01

Background Development of three classification trees (CT) based on the CART (Classification and Regression Trees), CHAID (Chi-Square Automatic Interaction Detection) and C4.5 methodologies for the calculation of probability of hospital mortality; the comparison of the results with the APACHE II, SAPS II and MPM II-24 scores, and with a model based on multiple logistic regression (LR). Methods Retrospective study of 2864 patients. Random partition (70:30) into a Development Set (DS) n = 1808 and Validation Set (VS) n = 808. Their properties of discrimination are compared with the ROC curve (AUC CI 95%), Percent of correct classification (PCC CI 95%); and the calibration with the Calibration Curve and the Standardized Mortality Ratio (SMR CI 95%). Results CTs are produced with a different selection of variables and decision rules: CART (5 variables and 8 decision rules), CHAID (7 variables and 15 rules) and C4.5 (6 variables and 10 rules). The common variables were: inotropic therapy, Glasgow, age, (A-a)O2 gradient and antecedent of chronic illness. In VS: all the models achieved acceptable discrimination with AUC above 0.7. CT: CART (0.75(0.71-0.81)), CHAID (0.76(0.72-0.79)) and C4.5 (0.76(0.73-0.80)). PCC: CART (72(69-75)), CHAID (72(69-75)) and C4.5 (76(73-79)). Calibration (SMR) better in the CT: CART (1.04(0.95-1.31)), CHAID (1.06(0.97-1.15) and C4.5 (1.08(0.98-1.16)). Conclusion With different methodologies of CTs, trees are generated with different selection of variables and decision rules. The CTs are easy to interpret, and they stratify the risk of hospital mortality. The CTs should be taken into account for the classification of the prognosis of critically ill patients. PMID:20003229

Pollution Police: How to Determine Spectroscopic Selection Rules

ERIC Educational Resources Information Center

Selco, Jodye I.; Beery, Janet

2004-01-01

Students employ mathematics and physical chemistry in a project called Pollution Police to establish spectroscopic selection rules, and apply them to detect environmental contaminants from infrared spectra. This interdisciplinary project enables students to gain multiple information on molecular symmetry, and its role in the development of…

Bergmann's Rule, Adaptation, and Thermoregulation in Arctic Animals: Conflicting Perspectives from Physiology, Evolutionary Biology, and Physical Anthropology After World War II.

PubMed

Hagen, Joel B

2017-05-01

Bergmann's rule and Allen's rule played important roles in mid-twentieth century discussions of adaptation, variation, and geographical distribution. Although inherited from the nineteenth-century natural history tradition these rules gained significance during the consolidation of the modern synthesis as evolutionary theorists focused attention on populations as units of evolution. For systematists, the rules provided a compelling rationale for identifying geographical races or subspecies, a function that was also picked up by some physical anthropologists. More generally, the rules provided strong evidence for adaptation by natural selection. Supporters of the rules tacitly, or often explicitly, assumed that the clines described by the rules reflected adaptations for thermoregulation. This assumption was challenged by the physiologists Laurence Irving and Per Scholander based on their arctic research conducted after World War II. Their critique spurred a controversy played out in a series of articles in Evolution, in Ernst Mayr's Animal Species and Evolution, and in the writings of other prominent evolutionary biologists and physical anthropologists. Considering this episode highlights the complexity and ambiguity of important biological concepts such as adaptation, homeostasis, and self-regulation. It also demonstrates how different disciplinary orientations and styles of scientific research influenced evolutionary explanations, and the consequent difficulties of constructing a truly synthetic evolutionary biology in the decades immediately following World War II.

Correlated pay-offs are key to cooperation

PubMed Central

Frommen, Joachim G.; Riehl, Christina

2016-01-01

The general belief that cooperation and altruism in social groups result primarily from kin selection has recently been challenged, not least because results from cooperatively breeding insects and vertebrates have shown that groups may be composed mainly of non-relatives. This allows testing predictions of reciprocity theory without the confounding effect of relatedness. Here, we review complementary and alternative evolutionary mechanisms to kin selection theory and provide empirical examples of cooperative behaviour among unrelated individuals in a wide range of taxa. In particular, we focus on the different forms of reciprocity and on their underlying decision rules, asking about evolutionary stability, the conditions selecting for reciprocity and the factors constraining reciprocal cooperation. We find that neither the cognitive requirements of reciprocal cooperation nor the often sequential nature of interactions are insuperable stumbling blocks for the evolution of reciprocity. We argue that simple decision rules such as ‘help anyone if helped by someone’ should get more attention in future research, because empirical studies show that animals apply such rules, and theoretical models find that they can create stable levels of cooperation under a wide range of conditions. Owing to its simplicity, behaviour based on such a heuristic may in fact be ubiquitous. Finally, we argue that the evolution of exchange and trading of service and commodities among social partners needs greater scientific focus. PMID:26729924

Where neuroscience and dynamic system theory meet autonomous robotics: a contracting basal ganglia model for action selection.

PubMed

Girard, B; Tabareau, N; Pham, Q C; Berthoz, A; Slotine, J-J

2008-05-01

Action selection, the problem of choosing what to do next, is central to any autonomous agent architecture. We use here a multi-disciplinary approach at the convergence of neuroscience, dynamical system theory and autonomous robotics, in order to propose an efficient action selection mechanism based on a new model of the basal ganglia. We first describe new developments of contraction theory regarding locally projected dynamical systems. We exploit these results to design a stable computational model of the cortico-baso-thalamo-cortical loops. Based on recent anatomical data, we include usually neglected neural projections, which participate in performing accurate selection. Finally, the efficiency of this model as an autonomous robot action selection mechanism is assessed in a standard survival task. The model exhibits valuable dithering avoidance and energy-saving properties, when compared with a simple if-then-else decision rule.

The motor locus of no-go backward crosstalk.

PubMed

Durst, Moritz; Janczyk, Markus

2018-04-23

A frequent observation in dual-task studies is the backward crosstalk effect (BCE), meaning that aspects of a secondary Task 2 influence Task 1 performance. Up to this point, 2 major types of the BCE were investigated: a BCE based on dimensional overlap between both stimuli and/or responses (the compatibility-based BCE), and a BCE based on whether Task 2 is a go or no-go task (the no-go BCE). Recent evidence suggests that the compatibility-based BCE has its locus inside the response selection stage. The available evidence for the locus of the no-go BCE is still mixed, however. To this end, the 3 experiments reported in the present study used an extended psychological refractory period (PRP) paradigm with 3 subsequent tasks. Applying the locus of slack logic in Experiment 1, the no-go BCE was not absorbed into the cognitive slack and, thus, a locus before response selection could be ruled out. Subsequently applying the effect propagation logic in Experiment 2 and 3, the no-go BCE arising in Task 1 was even inverted in Task 3. Because no propagation of the no-go BCE was observed, a locus before or in response selection could be ruled out. Thus, we conclude that the no-go BCE has its locus during motor execution. Because the no-go BCE and the compatibility-based BCE are located in different stages, we suggest that both types of the BCE do not share a common underlying mechanism. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Rule-Based Categorization Deficits in Focal Basal Ganglia Lesion and Parkinson’s Disease Patients

PubMed Central

Ell, Shawn W.; Weinstein, Andrea; Ivry, Richard B.

2010-01-01

Patients with basal ganglia (BG) pathology are consistently found to be impaired on rule-based category learning tasks in which learning is thought to depend upon the use of an explicit, hypothesis-guided strategy. The factors that influence this impairment remain unclear. Moreover, it remains unknown if the impairments observed in patients with degenerative disorders such as Parkinson's disease (PD) are also observed in those with focal BG lesions. In the present study, we tested patients with either focal BG lesions or PD on two categorization tasks that varied in terms of their demands on selective attention and working memory. Individuals with focal BG lesions were impaired on the task in which working-memory demand was high and performed similarly to healthy controls on the task in which selective-attention demand was high. In contrast, individuals with PD were impaired on both tasks, and accuracy rates did not differ between on- and off-medication states for a subset of patients who were also tested after abstaining from dopaminergic medication. Quantitative, model-based analyses attributed the performance deficit for both groups in the task with high working-memory demand to the utilization of suboptimal strategies, whereas the PD-specific impairment on the task with high selective-attention demand was driven by the inconsistent use of an optimal strategy. These data suggest that the demands on selective attention and working memory affect the presence of impairment in patients with focal BG lesions and the nature of the impairment in patients with PD. PMID:20600196

Designing P-Optimal Item Pools in Computerized Adaptive Tests with Polytomous Items

ERIC Educational Resources Information Center

Zhou, Xuechun

2012-01-01

Current CAT applications consist of predominantly dichotomous items, and CATs with polytomously scored items are limited. To ascertain the best approach to polytomous CAT, a significant amount of research has been conducted on item selection, ability estimation, and impact of termination rules based on polytomous IRT models. Few studies…

Expert Systems: An Overview for Teacher-Librarians.

ERIC Educational Resources Information Center

Orwig, Gary; Barron, Ann

1992-01-01

Provides an overview of expert systems for teacher librarians. Highlights include artificial intelligence and expert systems; the development of the MYCIN medical expert system; rule-based expert systems; the use of expert system shells to develop a specific system; and how to select an appropriate application for an expert system. (11 references)…

76 FR 37351 - Information Collection Being Reviewed by the Federal Communications Commission Under Delegated...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-06-27

... required to obtain written permission from the Coast Guard in the area where radio-navigation/radio-location devices are located. This rule insures that no hazard to marine navigation will result from the grant of applications for non-selectable transponders and shore based radio- navigation aids. The Coast...

Sauerbraten, Rotkappchen und Goethe: The Quiz Show as an Introduction to German Studies.

ERIC Educational Resources Information Center

White, Diane

1980-01-01

Proposes an adaptation of the quiz-show format for classroom use, discussing a set of rules and sample questions designed for beginning and intermediate German students. Presents questions based on German life and culture which are especially selected to encourage participation from students majoring in subjects other than German. (MES)

78 FR 64566 - Self-Regulatory Organizations; Financial Industry Regulatory Authority, Inc.; Notice of Filing...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-10-29

... Effectiveness of a Proposed Rule Change To Revise the Series 6 Examination Program October 23, 2013. Pursuant to... selection specifications for the Investment Company and Variable Contracts Products Representative (Series 6... corresponding revisions to the Series 6 question bank. Based on instruction from SEC staff, FINRA is submitting...

Definition and application of a five-parameter characterization of one-dimensional cellular automata rule space.

PubMed

Oliveira, G M; de Oliveira, P P; Omar, N

2001-01-01

Cellular automata (CA) are important as prototypical, spatially extended, discrete dynamical systems. Because the problem of forecasting dynamic behavior of CA is undecidable, various parameter-based approximations have been developed to address the problem. Out of the analysis of the most important parameters available to this end we proposed some guidelines that should be followed when defining a parameter of that kind. Based upon the guidelines, new parameters were proposed and a set of five parameters was selected; two of them were drawn from the literature and three are new ones, defined here. This article presents all of them and makes their qualities evident. Then, two results are described, related to the use of the parameter set in the Elementary Rule Space: a phase transition diagram, and some general heuristics for forecasting the dynamics of one-dimensional CA. Finally, as an example of the application of the selected parameters in high cardinality spaces, results are presented from experiments involving the evolution of radius-3 CA in the Density Classification Task, and radius-2 CA in the Synchronization Task.

Rule of five in 2015 and beyond: Target and ligand structural limitations, ligand chemistry structure and drug discovery project decisions.

PubMed

Lipinski, Christopher A

2016-06-01

The rule of five (Ro5), based on physicochemical profiles of phase II drugs, is consistent with structural limitations in protein targets and the drug target ligands. Three of four parameters in Ro5 are fundamental to the structure of both target and drug binding sites. The chemical structure of the drug ligand depends on the ligand chemistry and design philosophy. Two extremes of chemical structure and design philosophy exist; ligands constructed in the medicinal chemistry synthesis laboratory without input from natural selection and natural product (NP) metabolites biosynthesized based on evolutionary selection. Exceptions to Ro5 are found mostly among NPs. Chemistry chameleon-like behavior of some NPs due to intra-molecular hydrogen bonding as exemplified by cyclosporine A is a strong contributor to NP Ro5 outliers. The fragment derived, drug Navitoclax is an example of the extensive expertise, resources, time and key decisions required for the rare discovery of a non-NP Ro5 outlier. Copyright © 2016 Elsevier B.V. All rights reserved.

Autonomous power expert system advanced development

NASA Technical Reports Server (NTRS)

Quinn, Todd M.; Walters, Jerry L.

1991-01-01

The autonomous power expert (APEX) system is being developed at Lewis Research Center to function as a fault diagnosis advisor for a space power distribution test bed. APEX is a rule-based system capable of detecting faults and isolating the probable causes. APEX also has a justification facility to provide natural language explanations about conclusions reached during fault isolation. To help maintain the health of the power distribution system, additional capabilities were added to APEX. These capabilities allow detection and isolation of incipient faults and enable the expert system to recommend actions/procedure to correct the suspected fault conditions. New capabilities for incipient fault detection consist of storage and analysis of historical data and new user interface displays. After the cause of a fault is determined, appropriate recommended actions are selected by rule-based inferencing which provides corrective/extended test procedures. Color graphics displays and improved mouse-selectable menus were also added to provide a friendlier user interface. A discussion of APEX in general and a more detailed description of the incipient detection, recommended actions, and user interface developments during the last year are presented.

Switch Hitting in Baseball: Apparent Rule-following, not Matching

PubMed Central

Poling, Alan; Weeden, Marc A; Redner, Ryan; Foster, T. Mary

2011-01-01

Many studies, including some dealing with shot selection in basketball and play selection in football, demonstrate that the generalized matching equation provides a good description of the allocation of time and effort to alternative responses as a function of the consequences of those alternatives. We examined whether it did so with respect to left- and right-handed at bats (alternative responses) and left- and right-handed total bases earned, runs batted in, and home runs (three consequences) for the outstanding baseball switch-hitters Mickey Mantle, Eddie Murray, and Pete Rose. With all hitters, undermatching, suggesting insensitivity to the consequences of behavior (reinforcement), was evident and there was substantial bias towards left-handed at bats. These players apparently chose handedness based on the rule “bat opposite the pitcher,” not on differential consequences obtained in major league games. The present findings are significant in representing a counter-instance of demonstrations of a matching relationship in sports in particular and in human behavior in general and in calling attention to the need for further study of the variables that affect choice. PMID:21909169

Inference from habitat-selection analysis depends on foraging strategies.

PubMed

Bastille-Rousseau, Guillaume; Fortin, Daniel; Dussault, Christian

2010-11-01

1. Several methods have been developed to assess habitat selection, most of which are based on a comparison between habitat attributes in used vs. unused or random locations, such as the popular resource selection functions (RSFs). Spatial evaluation of residency time has been recently proposed as a promising avenue for studying habitat selection. Residency-time analyses assume a positive relationship between residency time within habitat patches and selection. We demonstrate that RSF and residency-time analyses provide different information about the process of habitat selection. Further, we show how the consideration of switching rate between habitat patches (interpatch movements) together with residency-time analysis can reveal habitat-selection strategies. 2. Spatially explicit, individual-based modelling was used to simulate foragers displaying one of six foraging strategies in a heterogeneous environment. The strategies combined one of three patch-departure rules (fixed-quitting-harvest-rate, fixed-time and fixed-amount strategy), together with one of two interpatch-movement rules (random or biased). Habitat selection of simulated foragers was then assessed using RSF, residency-time and interpatch-movement analyses. 3. Our simulations showed that RSFs and residency times are not always equivalent. When foragers move in a non-random manner and do not increase residency time in richer patches, residency-time analysis can provide misleading assessments of habitat selection. This is because the overall time spent in the various patch types not only depends on residency times, but also on interpatch-movement decisions. 4. We suggest that RSFs provide the outcome of the entire selection process, whereas residency-time and interpatch-movement analyses can be used in combination to reveal the mechanisms behind the selection process. 5. We showed that there is a risk in using residency-time analysis alone to infer habitat selection. Residency-time analyses, however, may enlighten the mechanisms of habitat selection by revealing central components of resource-use strategies. Given that management decisions are often based on resource-selection analyses, the evaluation of resource-use strategies can be key information for the development of efficient habitat-management strategies. Combining RSF, residency-time and interpatch-movement analyses is a simple and efficient way to gain a more comprehensive understanding of habitat selection. © 2010 The Authors. Journal compilation © 2010 British Ecological Society.

Selecting Pesticides and Nonchemical Alternatives: Green Thumbs' Rules of Thumb Decision Tools.

ERIC Educational Resources Information Center

Grieshop, James I.; And Others

1992-01-01

A sample of 78 (of 320) home gardeners use rules of thumb (heuristics) to choose between chemical pesticides and nonchemical alternatives. Pesticides rank low in 24 choice attributes where alternatives rank high, and vice versa. Gender, age, and years of pesticide use correlate with pesticide selection. (SK)

Stabilizing Entanglement via Symmetry-Selective Bath Engineering in Superconducting Qubits.

PubMed

Kimchi-Schwartz, M E; Martin, L; Flurin, E; Aron, C; Kulkarni, M; Tureci, H E; Siddiqi, I

2016-06-17

Bath engineering, which utilizes coupling to lossy modes in a quantum system to generate nontrivial steady states, is a tantalizing alternative to gate- and measurement-based quantum science. Here, we demonstrate dissipative stabilization of entanglement between two superconducting transmon qubits in a symmetry-selective manner. We utilize the engineered symmetries of the dissipative environment to stabilize a target Bell state; we further demonstrate suppression of the Bell state of opposite symmetry due to parity selection rules. This implementation is resource efficient, achieves a steady-state fidelity F=0.70, and is scalable to multiple qubits.

Nighttime image dehazing using local atmospheric selection rule and weighted entropy for visible-light systems

NASA Astrophysics Data System (ADS)

Park, Dubok; Han, David K.; Ko, Hanseok

2017-05-01

Optical imaging systems are often degraded by scattering due to atmospheric particles, such as haze, fog, and mist. Imaging under nighttime haze conditions may suffer especially from the glows near active light sources as well as scattering. We present a methodology for nighttime image dehazing based on an optical imaging model which accounts for varying light sources and their glow. First, glow effects are decomposed using relative smoothness. Atmospheric light is then estimated by assessing global and local atmospheric light using a local atmospheric selection rule. The transmission of light is then estimated by maximizing an objective function designed on the basis of weighted entropy. Finally, haze is removed using two estimated parameters, namely, atmospheric light and transmission. The visual and quantitative comparison of the experimental results with the results of existing state-of-the-art methods demonstrates the significance of the proposed approach.

Extending (Q)SARs to incorporate proprietary knowledge for regulatory purposes: A case study using aromatic amine mutagenicity.

PubMed

Ahlberg, Ernst; Amberg, Alexander; Beilke, Lisa D; Bower, David; Cross, Kevin P; Custer, Laura; Ford, Kevin A; Van Gompel, Jacky; Harvey, James; Honma, Masamitsu; Jolly, Robert; Joossens, Elisabeth; Kemper, Raymond A; Kenyon, Michelle; Kruhlak, Naomi; Kuhnke, Lara; Leavitt, Penny; Naven, Russell; Neilan, Claire; Quigley, Donald P; Shuey, Dana; Spirkl, Hans-Peter; Stavitskaya, Lidiya; Teasdale, Andrew; White, Angela; Wichard, Joerg; Zwickl, Craig; Myatt, Glenn J

2016-06-01

Statistical-based and expert rule-based models built using public domain mutagenicity knowledge and data are routinely used for computational (Q)SAR assessments of pharmaceutical impurities in line with the approach recommended in the ICH M7 guideline. Knowledge from proprietary corporate mutagenicity databases could be used to increase the predictive performance for selected chemical classes as well as expand the applicability domain of these (Q)SAR models. This paper outlines a mechanism for sharing knowledge without the release of proprietary data. Primary aromatic amine mutagenicity was selected as a case study because this chemical class is often encountered in pharmaceutical impurity analysis and mutagenicity of aromatic amines is currently difficult to predict. As part of this analysis, a series of aromatic amine substructures were defined and the number of mutagenic and non-mutagenic examples for each chemical substructure calculated across a series of public and proprietary mutagenicity databases. This information was pooled across all sources to identify structural classes that activate or deactivate aromatic amine mutagenicity. This structure activity knowledge, in combination with newly released primary aromatic amine data, was incorporated into Leadscope's expert rule-based and statistical-based (Q)SAR models where increased predictive performance was demonstrated. Copyright © 2016 Elsevier Inc. All rights reserved.

Incorporating Virtual Reactions into a Logic-based Ligand-based Virtual Screening Method to Discover New Leads

PubMed Central

Reynolds, Christopher R; Muggleton, Stephen H; Sternberg, Michael J E

2015-01-01

The use of virtual screening has become increasingly central to the drug development pipeline, with ligand-based virtual screening used to screen databases of compounds to predict their bioactivity against a target. These databases can only represent a small fraction of chemical space, and this paper describes a method of exploring synthetic space by applying virtual reactions to promising compounds within a database, and generating focussed libraries of predicted derivatives. A ligand-based virtual screening tool Investigational Novel Drug Discovery by Example (INDDEx) is used as the basis for a system of virtual reactions. The use of virtual reactions is estimated to open up a potential space of 1.21×1012 potential molecules. A de novo design algorithm known as Partial Logical-Rule Reactant Selection (PLoRRS) is introduced and incorporated into the INDDEx methodology. PLoRRS uses logical rules from the INDDEx model to select reactants for the de novo generation of potentially active products. The PLoRRS method is found to increase significantly the likelihood of retrieving molecules similar to known actives with a p-value of 0.016. Case studies demonstrate that the virtual reactions produce molecules highly similar to known actives, including known blockbuster drugs. PMID:26583052

Building a Relationship between Robot Characteristics and Teleoperation User Interfaces.

PubMed

Mortimer, Michael; Horan, Ben; Seyedmahmoudian, Mehdi

2017-03-14

The Robot Operating System (ROS) provides roboticists with a standardized and distributed framework for real-time communication between robotic systems using a microkernel environment. This paper looks at how ROS metadata, Unified Robot Description Format (URDF), Semantic Robot Description Format (SRDF), and its message description language, can be used to identify key robot characteristics to inform User Interface (UI) design for the teleoperation of heterogeneous robot teams. Logical relationships between UI components and robot characteristics are defined by a set of relationship rules created using relevant and available information including developer expertise and ROS metadata. This provides a significant opportunity to move towards a rule-driven approach for generating the designs of teleoperation UIs; in particular the reduction of the number of different UI configurations required to teleoperate each individual robot within a heterogeneous robot team. This approach is based on using an underlying rule set identifying robots that can be teleoperated using the same UI configuration due to having the same or similar robot characteristics. Aside from reducing the number of different UI configurations an operator needs to be familiar with, this approach also supports consistency in UI configurations when a teleoperator is periodically switching between different robots. To achieve this aim, a Matlab toolbox is developed providing users with the ability to define rules specifying the relationship between robot characteristics and UI components. Once rules are defined, selections that best describe the characteristics of the robot type within a particular heterogeneous robot team can be made. A main advantage of this approach is that rather than specifying discrete robots comprising the team, the user can specify characteristics of the team more generally allowing the system to deal with slight variations that may occur in the future. In fact, by using the defined relationship rules and characteristic selections, the toolbox can automatically identify a reduced set of UI configurations required to control possible robot team configurations, as opposed to the traditional ad-hoc approach to teleoperation UI design. In the results section, three test cases are presented to demonstrate how the selection of different robot characteristics builds a number of robot characteristic combinations, and how the relationship rules are used to determine a reduced set of required UI configurations needed to control each individual robot in the robot team.

Building a Relationship between Robot Characteristics and Teleoperation User Interfaces

PubMed Central

Mortimer, Michael; Horan, Ben; Seyedmahmoudian, Mehdi

2017-01-01

The Robot Operating System (ROS) provides roboticists with a standardized and distributed framework for real-time communication between robotic systems using a microkernel environment. This paper looks at how ROS metadata, Unified Robot Description Format (URDF), Semantic Robot Description Format (SRDF), and its message description language, can be used to identify key robot characteristics to inform User Interface (UI) design for the teleoperation of heterogeneous robot teams. Logical relationships between UI components and robot characteristics are defined by a set of relationship rules created using relevant and available information including developer expertise and ROS metadata. This provides a significant opportunity to move towards a rule-driven approach for generating the designs of teleoperation UIs; in particular the reduction of the number of different UI configurations required to teleoperate each individual robot within a heterogeneous robot team. This approach is based on using an underlying rule set identifying robots that can be teleoperated using the same UI configuration due to having the same or similar robot characteristics. Aside from reducing the number of different UI configurations an operator needs to be familiar with, this approach also supports consistency in UI configurations when a teleoperator is periodically switching between different robots. To achieve this aim, a Matlab toolbox is developed providing users with the ability to define rules specifying the relationship between robot characteristics and UI components. Once rules are defined, selections that best describe the characteristics of the robot type within a particular heterogeneous robot team can be made. A main advantage of this approach is that rather than specifying discrete robots comprising the team, the user can specify characteristics of the team more generally allowing the system to deal with slight variations that may occur in the future. In fact, by using the defined relationship rules and characteristic selections, the toolbox can automatically identify a reduced set of UI configurations required to control possible robot team configurations, as opposed to the traditional ad-hoc approach to teleoperation UI design. In the results section, three test cases are presented to demonstrate how the selection of different robot characteristics builds a number of robot characteristic combinations, and how the relationship rules are used to determine a reduced set of required UI configurations needed to control each individual robot in the robot team. PMID:28335431

Pilot program to assess proposed basic quality assurance requirements in the medical use of byproduct materials

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

Kaplan, E.; Nelson, K.; Meinhold, C.B.

1991-10-01

In January 1990, the Nuclear Regulatory Commission (NRC) proposed amendments to 10 CFR Part 35 that would require medical licensees using byproduct material to establish and implement a basic quality assurance program. A 60-day real-world trial of the proposed rules was initiated to obtain information beyond that generally found through standard public comment procedures. Volunteers from randomly selected institutions had opportunities to review the details of the proposed regulations and to implement these rules on a daily basis during the trial. The participating institutions were then asked to evaluate the proposed regulations based on their personal experiences. The pilot projectmore » sought to determine whether medical institutions could develop written quality assurance programs that would meet the eight performance-based objectives of proposed Section 35.35. In addition, the NRC wanted to learn from these volunteers if they had any recommendations on how the rule could be revised to minimized its cost and to clarify its objectives without decreasing its effectiveness. It was found that licensees could develop acceptable QA programs under a performance-based approach, that most licensee programs did meet the proposed objectives, and that most written QA plans would require consultations with NRC or Agreement State personnel before they would fully meet all objectives of proposed Section 35.35. This report describes the overall pilot program. The methodology used to select and assemble the group of participating licensees is presented. The various workshops and evaluation questionnaires are discussed, and detailed findings are presented. 7 refs.« less

A novel variable selection approach that iteratively optimizes variable space using weighted binary matrix sampling.

PubMed

Deng, Bai-chuan; Yun, Yong-huan; Liang, Yi-zeng; Yi, Lun-zhao

2014-10-07

In this study, a new optimization algorithm called the Variable Iterative Space Shrinkage Approach (VISSA) that is based on the idea of model population analysis (MPA) is proposed for variable selection. Unlike most of the existing optimization methods for variable selection, VISSA statistically evaluates the performance of variable space in each step of optimization. Weighted binary matrix sampling (WBMS) is proposed to generate sub-models that span the variable subspace. Two rules are highlighted during the optimization procedure. First, the variable space shrinks in each step. Second, the new variable space outperforms the previous one. The second rule, which is rarely satisfied in most of the existing methods, is the core of the VISSA strategy. Compared with some promising variable selection methods such as competitive adaptive reweighted sampling (CARS), Monte Carlo uninformative variable elimination (MCUVE) and iteratively retaining informative variables (IRIV), VISSA showed better prediction ability for the calibration of NIR data. In addition, VISSA is user-friendly; only a few insensitive parameters are needed, and the program terminates automatically without any additional conditions. The Matlab codes for implementing VISSA are freely available on the website: https://sourceforge.net/projects/multivariateanalysis/files/VISSA/.

A fuzzy neural network for intelligent data processing

NASA Astrophysics Data System (ADS)

Xie, Wei; Chu, Feng; Wang, Lipo; Lim, Eng Thiam

2005-03-01

In this paper, we describe an incrementally generated fuzzy neural network (FNN) for intelligent data processing. This FNN combines the features of initial fuzzy model self-generation, fast input selection, partition validation, parameter optimization and rule-base simplification. A small FNN is created from scratch -- there is no need to specify the initial network architecture, initial membership functions, or initial weights. Fuzzy IF-THEN rules are constantly combined and pruned to minimize the size of the network while maintaining accuracy; irrelevant inputs are detected and deleted, and membership functions and network weights are trained with a gradient descent algorithm, i.e., error backpropagation. Experimental studies on synthesized data sets demonstrate that the proposed Fuzzy Neural Network is able to achieve accuracy comparable to or higher than both a feedforward crisp neural network, i.e., NeuroRule, and a decision tree, i.e., C4.5, with more compact rule bases for most of the data sets used in our experiments. The FNN has achieved outstanding results for cancer classification based on microarray data. The excellent classification result for Small Round Blue Cell Tumors (SRBCTs) data set is shown. Compared with other published methods, we have used a much fewer number of genes for perfect classification, which will help researchers directly focus their attention on some specific genes and may lead to discovery of deep reasons of the development of cancers and discovery of drugs.

An optimal sample data usage strategy to minimize overfitting and underfitting effects in regression tree models based on remotely-sensed data

USGS Publications Warehouse

Gu, Yingxin; Wylie, Bruce K.; Boyte, Stephen; Picotte, Joshua J.; Howard, Danny; Smith, Kelcy; Nelson, Kurtis

2016-01-01

Regression tree models have been widely used for remote sensing-based ecosystem mapping. Improper use of the sample data (model training and testing data) may cause overfitting and underfitting effects in the model. The goal of this study is to develop an optimal sampling data usage strategy for any dataset and identify an appropriate number of rules in the regression tree model that will improve its accuracy and robustness. Landsat 8 data and Moderate-Resolution Imaging Spectroradiometer-scaled Normalized Difference Vegetation Index (NDVI) were used to develop regression tree models. A Python procedure was designed to generate random replications of model parameter options across a range of model development data sizes and rule number constraints. The mean absolute difference (MAD) between the predicted and actual NDVI (scaled NDVI, value from 0–200) and its variability across the different randomized replications were calculated to assess the accuracy and stability of the models. In our case study, a six-rule regression tree model developed from 80% of the sample data had the lowest MAD (MADtraining = 2.5 and MADtesting = 2.4), which was suggested as the optimal model. This study demonstrates how the training data and rule number selections impact model accuracy and provides important guidance for future remote-sensing-based ecosystem modeling.

A rule-based expert system for generating control displays at the Advanced Photon Source

NASA Astrophysics Data System (ADS)

Coulter, Karen J.

1994-12-01

The integration of a rule-based expert system for generating screen displays for controlling and monitoring instrumentation under the Experimental Physics and Industrial Control System (EPICS) is presented. The expert system is implemented using CLIPS, an expert system shell from the Software Technology Branch at Lyndon B. Johnson Space Center. The user selects the hardware input and output to be displayed and the expert system constructs a graphical control screen appropriate for the data. Such a system provides a method for implementing a common look and feel for displays created by several different users and reduces the amount of time required to create displays for new hardware configurations. Users are able to modify the displays as needed using the EPICS display editor tool.

Decision-Making in Agent-Based Models of Migration: State of the Art and Challenges.

PubMed

Klabunde, Anna; Willekens, Frans

We review agent-based models (ABM) of human migration with respect to their decision-making rules. The most prominent behavioural theories used as decision rules are the random utility theory, as implemented in the discrete choice model, and the theory of planned behaviour. We identify the critical choices that must be made in developing an ABM, namely the modelling of decision processes and social networks. We also discuss two challenges that hamper the widespread use of ABM in the study of migration and, more broadly, demography and the social sciences: (a) the choice and the operationalisation of a behavioural theory (decision-making and social interaction) and (b) the selection of empirical evidence to validate the model. We offer advice on how these challenges might be overcome.

Rule-based exposure assessment versus case-by-case expert assessment using the same information in a community-based study.

PubMed

Peters, Susan; Glass, Deborah C; Milne, Elizabeth; Fritschi, Lin

2014-03-01

Retrospective exposure assessment in community-based studies is largely reliant on questionnaire information. Expert assessment is often used to assess lifetime occupational exposures, but these assessments generally lack transparency and are very time-consuming. We explored the agreement between a rule-based assessment approach and case-by-case expert assessment of occupational exposures in a community-based study. We used data from a case-control study of childhood acute lymphoblastic leukaemia in which parental occupational exposures were originally assigned by expert assessment. Key questions were identified from the completed parent questionnaires and, on the basis of these, rules were written to assign exposure levels to diesel exhaust, pesticides and solvents. We estimated exposure prevalence separately for fathers and mothers, and used κ statistics to assess the agreement between the two exposure assessment methods. Exposures were assigned to 5829 jobs among 1079 men and 6189 jobs among 1234 women. For both sexes, agreement was good for the two assessment methods of exposure to diesel exhaust at a job level (κ=0.70 for men and κ=0.71 for women) and at a person level (κ=0.74 and κ=0.75). The agreement was good to excellent for pesticide exposure among men (κ=0.74 for jobs and κ=0.84 at a person level) and women (κ=0.68 and κ=0.71 at a job and person level, respectively). Moderate to good agreement was observed for assessment of solvent exposure, which was better for women than men. The rule-based assessment approach appeared to be an efficient alternative for assigning occupational exposures in a community-based study for a selection of occupational exposures.

New rules for visual selection: Isolating procedural attention.

PubMed

Ramamurthy, Mahalakshmi; Blaser, Erik

2017-02-01

High performance in well-practiced, everyday tasks-driving, sports, gaming-suggests a kind of procedural attention that can allocate processing resources to behaviorally relevant information in an unsupervised manner. Here we show that training can lead to a new, automatic attentional selection rule that operates in the absence of bottom-up, salience-driven triggers and willful top-down selection. Taking advantage of the fact that attention modulates motion aftereffects, observers were presented with a bivectorial display with overlapping, iso-salient red and green dot fields moving to the right and left, respectively, while distracted by a demanding auditory two-back memory task. Before training, since the motion vectors canceled each other out, no net motion aftereffect (MAE) was found. However, after 3 days (0.5 hr/day) of training, during which observers practiced selectively attending to the red, rightward field, a significant net MAE was observed-even when top-down selection was again distracted. Further experiments showed that these results were not due to perceptual learning, and that the new rule targeted the motion, and not the color of the target dot field, and global, not local, motion signals; thus, the new rule was: "select the rightward field." This study builds on recent work on selection history-driven and reward-driven biases, but uses a novel paradigm where the allocation of visual processing resources are measured passively, offline, and when the observer's ability to execute top-down selection is defeated.

Therapeutic considerations in special patients.

PubMed

Little, J W; Falace, D A

1984-07-01

Careful attention to patients' histories and their medical problems and consultation with their physicians should provide sound bases for selection of drugs. Antibiotic prophylaxis for patients with cardiovascular disorders is described for American Heart Association standards, but for other indications sound judgment based on the principles of antibiotic prophylaxis must be the rule. Patients with end-stage renal disease and severe liver impairment may be at risk with certain drugs. The most critical time for consideration of use of drugs during pregnancy is the first trimester. However, careful selection of drugs for use during the balance of the term can reduce the risk of harm to the mother and fetus.

77 FR 28797 - Redundancy of Communications Systems: Backup Power Private Land Mobile Radio Services: Selection...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-05-16

... Systems: Backup Power Private Land Mobile Radio Services: Selection and Assignment of Frequencies, and... certain rule provisions that are without current legal effect and obsolete. These nonsubstantive revisions... current legal effect and is deleted as obsolete. 2. This Order also deletes a rule providing that UHF...

A Survey of Social-Regulatory Practices in Selected Michigan Community Colleges.

ERIC Educational Resources Information Center

Hollander, Martin Elliot

This study surveyed social-regulatory practices of selected community colleges in Michigan to find out: origin and extent of written social-regulatory policies and the provisions for change; types of rules of conduct; and communication and enforcement of social-regulatory practices and rules. The study was limited to commuter-type publicly…

76 FR 79262 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Order Granting Approval of Proposed...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-12-21

...-Regulatory Organizations; The NASDAQ Stock Market LLC; Order Granting Approval of Proposed Rule Change To... Select Markets December 15, 2011. I. Introduction On August 30, 2011, The NASDAQ Stock Market LLC... Global and Global Select Markets. The proposed rule change was published in the Federal Register on...

Controllable phase transitions and novel selection rules in Josephson junctions with inherent orthogonality

NASA Astrophysics Data System (ADS)

Cheng, Qiang; Zhang, Kunhua; Ma, Hongyang

2018-03-01

We propose a new type of Josephson junction consisting of topologically nontrivial superconductors with inherent orthogonality and a ferromagnetic interface. It is found this type of junction can host rich ground states: 0 phase, π phase, 0 + π phase, φ0 phase and φ0 ± φ phase. Phase transitions can be controlled by changing the direction of the interfacial magnetization. Phase diagrams are presented in the orientation space. Novel selection rules for the lowest order current, sin ⁡ ϕ or cos ⁡ ϕ, of this kind of junction are derived. General conditions for the formation of various ground states are established, which possess guiding significance to the experimental design of required ground states for practical applications. We construct the succinct form of a Ginzburg-Landau type of free energy from the viewpoint of the interplay between topological superconductivity and ferromagnetism, which can immediately lead to the selection rules. The constructed terms are universally available to the topological Josephson junctions with or without inherent orthogonality reported recently. The spin supercurrent, its selection rules and their relations to the constructed energy are also investigated.

Allocating application to group of consecutive processors in fault-tolerant deadlock-free routing path defined by routers obeying same rules for path selection

DOEpatents

Leung, Vitus J [Albuquerque, NM; Phillips, Cynthia A [Albuquerque, NM; Bender, Michael A [East Northport, NY; Bunde, David P [Urbana, IL

2009-07-21

In a multiple processor computing apparatus, directional routing restrictions and a logical channel construct permit fault tolerant, deadlock-free routing. Processor allocation can be performed by creating a linear ordering of the processors based on routing rules used for routing communications between the processors. The linear ordering can assume a loop configuration, and bin-packing is applied to this loop configuration. The interconnection of the processors can be conceptualized as a generally rectangular 3-dimensional grid, and the MC allocation algorithm is applied with respect to the 3-dimensional grid.

A random rule model of surface growth

NASA Astrophysics Data System (ADS)

Mello, Bernardo A.

2015-02-01

Stochastic models of surface growth are usually based on randomly choosing a substrate site to perform iterative steps, as in the etching model, Mello et al. (2001) [5]. In this paper I modify the etching model to perform sequential, instead of random, substrate scan. The randomicity is introduced not in the site selection but in the choice of the rule to be followed in each site. The change positively affects the study of dynamic and asymptotic properties, by reducing the finite size effect and the short-time anomaly and by increasing the saturation time. It also has computational benefits: better use of the cache memory and the possibility of parallel implementation.

Constructing Agent Model for Virtual Training Systems

NASA Astrophysics Data System (ADS)

Murakami, Yohei; Sugimoto, Yuki; Ishida, Toru

Constructing highly realistic agents is essential if agents are to be employed in virtual training systems. In training for collaboration based on face-to-face interaction, the generation of emotional expressions is one key. In training for guidance based on one-to-many interaction such as direction giving for evacuations, emotional expressions must be supplemented by diverse agent behaviors to make the training realistic. To reproduce diverse behavior, we characterize agents by using a various combinations of operation rules instantiated by the user operating the agent. To accomplish this goal, we introduce a user modeling method based on participatory simulations. These simulations enable us to acquire information observed by each user in the simulation and the operating history. Using these data and the domain knowledge including known operation rules, we can generate an explanation for each behavior. Moreover, the application of hypothetical reasoning, which offers consistent selection of hypotheses, to the generation of explanations allows us to use otherwise incompatible operation rules as domain knowledge. In order to validate the proposed modeling method, we apply it to the acquisition of an evacuee's model in a fire-drill experiment. We successfully acquire a subject's model corresponding to the results of an interview with the subject.

Efficient Variable Selection Method for Exposure Variables on Binary Data

NASA Astrophysics Data System (ADS)

Ohno, Manabu; Tarumi, Tomoyuki

In this paper, we propose a new variable selection method for "robust" exposure variables. We define "robust" as property that the same variable can select among original data and perturbed data. There are few studies of effective for the selection method. The problem that selects exposure variables is almost the same as a problem that extracts correlation rules without robustness. [Brin 97] is suggested that correlation rules are possible to extract efficiently using chi-squared statistic of contingency table having monotone property on binary data. But the chi-squared value does not have monotone property, so it's is easy to judge the method to be not independent with an increase in the dimension though the variable set is completely independent, and the method is not usable in variable selection for robust exposure variables. We assume anti-monotone property for independent variables to select robust independent variables and use the apriori algorithm for it. The apriori algorithm is one of the algorithms which find association rules from the market basket data. The algorithm use anti-monotone property on the support which is defined by association rules. But independent property does not completely have anti-monotone property on the AIC of independent probability model, but the tendency to have anti-monotone property is strong. Therefore, selected variables with anti-monotone property on the AIC have robustness. Our method judges whether a certain variable is exposure variable for the independent variable using previous comparison of the AIC. Our numerical experiments show that our method can select robust exposure variables efficiently and precisely.

True Dopers or Negligent Athletes? An Analysis of Anti-Doping Rule Violations Reported to the World Anti-Doping Agency 2010-2012.

PubMed

de Hon, Olivier; van Bottenburg, Maarten

2017-12-06

The sanction that an athlete receives when an anti-doping rule violation has been committed depends on the specific circumstances of the case. Anti-doping tribunals decide on the final sanction, following the rules of the World Anti-Doping Code. To assess the athletes' degree of fault based on the length of sanctions imposed on them to feed policy-related discussions. Analysing data from the results management database of the World Anti-Doping Agency for anonymous information of anti-doping rule violations in eight selected sports covering the years 2010-2012. Four out of ten athletes who committed an anti-doping rule violation received a suspension that was lower than the standard. This is an indication that tribunals in many instances are not convinced that the athletes concerned were completely at fault, that mitigating circumstances were applicable, or that full responsibility of the suspected violation should not be held against them. Anabolic agents, peptide hormones, and hormone modulators lead to higher sanctions, as do combinations of several anti-doping rule violations. This first analysis of information from the World Anti-Doping Agency's results management database indicates that a large proportion of the athletes who commit anti-doping rule violations may have done this unintentionally. Anti-doping professionals should strive to improve this situation in various ways.

Systematic methods for knowledge acquisition and expert system development

NASA Technical Reports Server (NTRS)

Belkin, Brenda L.; Stengel, Robert F.

1991-01-01

Nine cooperating rule-based systems, collectively called AUTOCREW, were designed to automate functions and decisions associated with a combat aircraft's subsystem. The organization of tasks within each system is described; performance metrics were developed to evaluate the workload of each rule base, and to assess the cooperation between the rule-bases. Each AUTOCREW subsystem is composed of several expert systems that perform specific tasks. AUTOCREW's NAVIGATOR was analyzed in detail to understand the difficulties involved in designing the system and to identify tools and methodologies that ease development. The NAVIGATOR determines optimal navigation strategies from a set of available sensors. A Navigation Sensor Management (NSM) expert system was systematically designed from Kalman filter covariance data; four ground-based, a satellite-based, and two on-board INS-aiding sensors were modeled and simulated to aid an INS. The NSM Expert was developed using the Analysis of Variance (ANOVA) and the ID3 algorithm. Navigation strategy selection is based on an RSS position error decision metric, which is computed from the covariance data. Results show that the NSM Expert predicts position error correctly between 45 and 100 percent of the time for a specified navaid configuration and aircraft trajectory. The NSM Expert adapts to new situations, and provides reasonable estimates of hybrid performance. The systematic nature of the ANOVA/ID3 method makes it broadly applicable to expert system design when experimental or simulation data is available.

Structure coefficients and strategy selection in multiplayer games.

PubMed

McAvoy, Alex; Hauert, Christoph

2016-01-01

Evolutionary processes based on two-player games such as the Prisoner's Dilemma or Snowdrift Game are abundant in evolutionary game theory. These processes, including those based on games with more than two strategies, have been studied extensively under the assumption that selection is weak. However, games involving more than two players have not received the same level of attention. To address this issue, and to relate two-player games to multiplayer games, we introduce a notion of reducibility for multiplayer games that captures what it means to break down a multiplayer game into a sequence of interactions with fewer players. We discuss the role of reducibility in structured populations, and we give examples of games that are irreducible in any population structure. Since the known conditions for strategy selection, otherwise known as [Formula: see text]-rules, have been established only for two-player games with multiple strategies and for multiplayer games with two strategies, we extend these rules to multiplayer games with many strategies to account for irreducible games that cannot be reduced to those simpler types of games. In particular, we show that the number of structure coefficients required for a symmetric game with [Formula: see text]-player interactions and [Formula: see text] strategies grows in [Formula: see text] like [Formula: see text]. Our results also cover a type of ecologically asymmetric game based on payoff values that are derived not only from the strategies of the players, but also from their spatial positions within the population.

Clothing Professors with Immunity: Points of Law on Academic Freedom.

ERIC Educational Resources Information Center

Kellerman, Ed; Cornelius, Luke

Over the years the Supreme Court has given academic freedom a special First Amendment status. This study reviewed a selected group of recent cases at public universities, focusing particularly on several where rulings were based either on a professor's public comments or in-class verbiage, in an attempt to assess the current status of academic…

EXSPRT: An Expert Systems Approach to Computer-Based Adaptive Testing.

ERIC Educational Resources Information Center

Frick, Theodore W.; And Others

Expert systems can be used to aid decision making. A computerized adaptive test (CAT) is one kind of expert system, although it is not commonly recognized as such. A new approach, termed EXSPRT, was devised that combines expert systems reasoning and sequential probability ratio test stopping rules. EXSPRT-R uses random selection of test items,…

Selecting Senior Acquisition Officials: Assessing the Current Processes and Practices for Recruiting, Confirming, and Retaining Senior Officials in the Acquisition Workforce

DTIC Science & Technology

2016-04-21

Selecting Senior Acquisition Officials Assessing the Current Processes and Practices for Recruiting, Confirming, and Retaining Senior Officials...Task Group 2 Terms of Reference (TOR)  Selection of Senior Officials in the Acquisition Workforce – Consider ethics rules, congressional committee... Senior Acquisition positions – Re-validate the conflicts of interest and risk mitigation rules “[T]he committee directs the Chair of the Defense Business

Quantitative knowledge acquisition for expert systems

NASA Technical Reports Server (NTRS)

Belkin, Brenda L.; Stengel, Robert F.

1991-01-01

A common problem in the design of expert systems is the definition of rules from data obtained in system operation or simulation. While it is relatively easy to collect data and to log the comments of human operators engaged in experiments, generalizing such information to a set of rules has not previously been a direct task. A statistical method is presented for generating rule bases from numerical data, motivated by an example based on aircraft navigation with multiple sensors. The specific objective is to design an expert system that selects a satisfactory suite of measurements from a dissimilar, redundant set, given an arbitrary navigation geometry and possible sensor failures. The systematic development is described of a Navigation Sensor Management (NSM) Expert System from Kalman Filter convariance data. The method invokes two statistical techniques: Analysis of Variance (ANOVA) and the ID3 Algorithm. The ANOVA technique indicates whether variations of problem parameters give statistically different covariance results, and the ID3 algorithms identifies the relationships between the problem parameters using probabilistic knowledge extracted from a simulation example set. Both are detailed.

Bourdieu's Distinction between Rules and Strategies and Secondary Principal Practice: A Review of Selected Literature

ERIC Educational Resources Information Center

Anderson, Karen

2016-01-01

This paper reviews a selection of literature on secondary principal practice from which to propose an approach for further research. The review demonstrates that applications of Bourdieu's theory of practice have contributed to understandings about secondary principal practice, and that the distinction he made between rules and strategies has the…

76 FR 57781 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing of Proposed Rule...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-09-16

... Global Select Markets (``Eligible Switches''). \\4\\ A company transferring from the OTCBB or Pink Sheets...-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing of Proposed Rule Change To Describe Complimentary Services That Are Offered to Certain New Listings on NASDAQ's Global and Global Select Markets...

77 FR 38701 - Self-Regulatory Organizations; NYSE Arca, Inc.; Notice of Filing of Proposed Rule Change Amending...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-06-28

... process for the nomination and selection of fair representation directors for the NYSE Arca Board of Directors (``NYSE Arca Board''), and NYSE Arca Equities Rule 3.2 sets forth a similar process for the nomination and selection of fair representation directors for the NYSE Arca Equities Board of Directors...

77 FR 52977 - Regulatory Capital Rules: Advanced Approaches Risk-Based Capital Rule; Market Risk Capital Rule

Federal Register 2010, 2011, 2012, 2013, 2014

2012-08-30

... Corporation 12 CFR Parts 324, 325 Regulatory Capital Rules: Advanced Approaches Risk-Based Capital Rule... 325 RIN 3064-AD97 Regulatory Capital Rules: Advanced Approaches Risk-Based Capital Rule; Market Risk... the agencies' current capital rules. In this NPR (Advanced Approaches and Market Risk NPR) the...

Feature Selection for Classification of Polar Regions Using a Fuzzy Expert System

NASA Technical Reports Server (NTRS)

Penaloza, Mauel A.; Welch, Ronald M.

1996-01-01

Labeling, feature selection, and the choice of classifier are critical elements for classification of scenes and for image understanding. This study examines several methods for feature selection in polar regions, including the list, of a fuzzy logic-based expert system for further refinement of a set of selected features. Six Advanced Very High Resolution Radiometer (AVHRR) Local Area Coverage (LAC) arctic scenes are classified into nine classes: water, snow / ice, ice cloud, land, thin stratus, stratus over water, cumulus over water, textured snow over water, and snow-covered mountains. Sixty-seven spectral and textural features are computed and analyzed by the feature selection algorithms. The divergence, histogram analysis, and discriminant analysis approaches are intercompared for their effectiveness in feature selection. The fuzzy expert system method is used not only to determine the effectiveness of each approach in classifying polar scenes, but also to further reduce the features into a more optimal set. For each selection method,features are ranked from best to worst, and the best half of the features are selected. Then, rules using these selected features are defined. The results of running the fuzzy expert system with these rules show that the divergence method produces the best set features, not only does it produce the highest classification accuracy, but also it has the lowest computation requirements. A reduction of the set of features produced by the divergence method using the fuzzy expert system results in an overall classification accuracy of over 95 %. However, this increase of accuracy has a high computation cost.

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.

The dilemma of female mate selection in the brown bear, a species with sexually selected infanticide

PubMed Central

Bellemain, Eva; Zedrosser, Andreas; Manel, Stéphanie; Waits, Lisette P; Taberlet, Pierre; Swenson, Jon E

2005-01-01

Because of differential investment in gametes between sexes, females tend to be the more selective sex. Based on this concept, we investigate mate selection in a large carnivore: the brown bear (Ursus arctos). We hypothesize that, in this species with sexually selected infanticide (SSI), females may be faced with a dilemma: either select a high-quality partner based on phenotypic criteria, as suggested by theories of mate choice, or rather mate with future potentially infanticidal males as a counter-strategy to SSI. We evaluated which male characteristics were important in paternity assignment. Among males available in the vicinity of the females, the largest, most heterozygous and less inbred and also the geographically closest males were more often the fathers of the female's next litter. We suggest that female brown bears may select the closest males as a counter-strategy to infanticide and exercise a post-copulatory cryptic choice, based on physical attributes, such as a large body size, reflecting male genetic quality. However, male–male competition either in the form of fighting before copulation or during the post-copulatory phase, in the form of sperm competition, cannot entirely be ruled out. PMID:16543170

Research on regularized mean-variance portfolio selection strategy with modified Roy safety-first principle.

PubMed

Atta Mills, Ebenezer Fiifi Emire; Yan, Dawen; Yu, Bo; Wei, Xinyuan

2016-01-01

We propose a consolidated risk measure based on variance and the safety-first principle in a mean-risk portfolio optimization framework. The safety-first principle to financial portfolio selection strategy is modified and improved. Our proposed models are subjected to norm regularization to seek near-optimal stable and sparse portfolios. We compare the cumulative wealth of our preferred proposed model to a benchmark, S&P 500 index for the same period. Our proposed portfolio strategies have better out-of-sample performance than the selected alternative portfolio rules in literature and control the downside risk of the portfolio returns.

Self-organization in a distributed coordination game through heuristic rules

NASA Astrophysics Data System (ADS)

Agarwal, Shubham; Ghosh, Diptesh; Chakrabarti, Anindya S.

2016-12-01

In this paper, we consider a distributed coordination game played by a large number of agents with finite information sets, which characterizes emergence of a single dominant attribute out of a large number of competitors. Formally, N agents play a coordination game repeatedly, which has exactly N pure strategy Nash equilibria, and all of the equilibria are equally preferred by the agents. The problem is to select one equilibrium out of N possible equilibria in the least number of attempts. We propose a number of heuristic rules based on reinforcement learning to solve the coordination problem. We see that the agents self-organize into clusters with varying intensities depending on the heuristic rule applied, although all clusters but one are transitory in most cases. Finally, we characterize a trade-off in terms of the time requirement to achieve a degree of stability in strategies versus the efficiency of such a solution.

Use HypE to Hide Association Rules by Adding Items

PubMed Central

Cheng, Peng; Lin, Chun-Wei; Pan, Jeng-Shyang

2015-01-01

During business collaboration, partners may benefit through sharing data. People may use data mining tools to discover useful relationships from shared data. However, some relationships are sensitive to the data owners and they hope to conceal them before sharing. In this paper, we address this problem in forms of association rule hiding. A hiding method based on evolutionary multi-objective optimization (EMO) is proposed, which performs the hiding task by selectively inserting items into the database to decrease the confidence of sensitive rules below specified thresholds. The side effects generated during the hiding process are taken as optimization goals to be minimized. HypE, a recently proposed EMO algorithm, is utilized to identify promising transactions for modification to minimize side effects. Results on real datasets demonstrate that the proposed method can effectively perform sanitization with fewer damages to the non-sensitive knowledge in most cases. PMID:26070130

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.

Comparison of Natural Language Processing Rules-based and Machine-learning Systems to Identify Lumbar Spine Imaging Findings Related to Low Back Pain.

PubMed

Tan, W Katherine; Hassanpour, Saeed; Heagerty, Patrick J; Rundell, Sean D; Suri, Pradeep; Huhdanpaa, Hannu T; James, Kathryn; Carrell, David S; Langlotz, Curtis P; Organ, Nancy L; Meier, Eric N; Sherman, Karen J; Kallmes, David F; Luetmer, Patrick H; Griffith, Brent; Nerenz, David R; Jarvik, Jeffrey G

2018-03-28

To evaluate a natural language processing (NLP) system built with open-source tools for identification of lumbar spine imaging findings related to low back pain on magnetic resonance and x-ray radiology reports from four health systems. We used a limited data set (de-identified except for dates) sampled from lumbar spine imaging reports of a prospectively assembled cohort of adults. From N = 178,333 reports, we randomly selected N = 871 to form a reference-standard dataset, consisting of N = 413 x-ray reports and N = 458 MR reports. Using standardized criteria, four spine experts annotated the presence of 26 findings, where 71 reports were annotated by all four experts and 800 were each annotated by two experts. We calculated inter-rater agreement and finding prevalence from annotated data. We randomly split the annotated data into development (80%) and testing (20%) sets. We developed an NLP system from both rule-based and machine-learned models. We validated the system using accuracy metrics such as sensitivity, specificity, and area under the receiver operating characteristic curve (AUC). The multirater annotated dataset achieved inter-rater agreement of Cohen's kappa > 0.60 (substantial agreement) for 25 of 26 findings, with finding prevalence ranging from 3% to 89%. In the testing sample, rule-based and machine-learned predictions both had comparable average specificity (0.97 and 0.95, respectively). The machine-learned approach had a higher average sensitivity (0.94, compared to 0.83 for rules-based), and a higher overall AUC (0.98, compared to 0.90 for rules-based). Our NLP system performed well in identifying the 26 lumbar spine findings, as benchmarked by reference-standard annotation by medical experts. Machine-learned models provided substantial gains in model sensitivity with slight loss of specificity, and overall higher AUC. Copyright © 2018 The Association of University Radiologists. All rights reserved.

26 CFR 31.6302-0 - Table of Contents.

Code of Federal Regulations, 2010 CFR

2010-04-01

... Provisions of Special Application to Employment Taxes (Selected Provisions of Subtitle F, Internal Revenue.... (a) Introduction. (b) Determination of status. (1) In general. (2) Monthly depositor. (i) In General... rules. (1) Monthly rule. (2) Semi-Weekly rule. (i) In general. (ii) Semi-weekly period spanning two...

A films based approach to intensity imbalance correction for 65nm node c:PSM

NASA Astrophysics Data System (ADS)

Cottle, Rand; Sixt, Pierre; Lassiter, Matt; Cangemi, Marc; Martin, Patrick; Progler, Chris

2005-11-01

Intensity imbalance between the 0 and π phase features of c:PSM cause gate CD control and edge placement problems. Strategies such as undercut, selective biasing, and combinations of undercut and bias are currently used in production to mitigate these problems. However, there are drawbacks to these strategies such as space CD delta through pitch, gate CD control through defocus, design rule restrictions, and reticle manufacturability. This paper investigates the application of an innovative films-based approach to intensity balancing known as the Transparent Etch Stop Layer (TESL). TESL, in addition to providing a host of reticle quality and manufacturability benefits, also can be tuned to significantly reduce imbalance. Rigorous 3D vector simulations and experimental data compare through pitch and defocus performance of TESL and conventional c:PSM for 65nm design rules.

Kotai Antibody Builder: automated high-resolution structural modeling of antibodies.

PubMed

Yamashita, Kazuo; Ikeda, Kazuyoshi; Amada, Karlou; Liang, Shide; Tsuchiya, Yuko; Nakamura, Haruki; Shirai, Hiroki; Standley, Daron M

2014-11-15

Kotai Antibody Builder is a Web service for tertiary structural modeling of antibody variable regions. It consists of three main steps: hybrid template selection by sequence alignment and canonical rules, 3D rendering of alignments and CDR-H3 loop modeling. For the last step, in addition to rule-based heuristics used to build the initial model, a refinement option is available that uses fragment assembly followed by knowledge-based scoring. Using targets from the Second Antibody Modeling Assessment, we demonstrate that Kotai Antibody Builder generates models with an overall accuracy equal to that of the best-performing semi-automated predictors using expert knowledge. Kotai Antibody Builder is available at http://kotaiab.org standley@ifrec.osaka-u.ac.jp. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

A Probability Based Approach for the Allocation of Player Draft Selections in Australian Rules Football

PubMed Central

Anthony, Bedford; Schembri, Adrian J.

2006-01-01

Australian Rules Football, governed by the Australian Football League (AFL) is the most popular winter sport played in Australia. Like North American team based leagues such as the NFL, NBA and NHL, the AFL uses a draft system for rookie players to join a team’s list. The existing method of allocating draft selections in the AFL is simply based on the reverse order of each team’s finishing position for that season, with teams winning less than or equal to 5 regular season matches obtaining an additional early round priority draft pick. Much criticism has been levelled at the existing system since it rewards losing teams and does not encourage poorly performing teams to win matches once their season is effectively over. We propose a probability-based system that allocates a score based on teams that win ‘unimportant’ matches (akin to Carl Morris’ definition of importance). We base the calculation of ‘unimportance’ on the likelihood of a team making the final eight following each round of the season. We then investigate a variety of approaches based on the ‘unimportance’ measure to derive a score for ‘unimportant’ and unlikely wins. We explore derivatives of this system, compare past draft picks with those obtained under our system, and discuss the attractiveness of teams knowing the draft reward for winning each match in a season. Key Points Draft choices are allocated using a probabilistic approach that rewards teams for winning unimportant matches. The method is based upon Carl Morris’ Importance and probabilistic calculations of making the finals. The importance of a match is calculated probabilistically to arrive at a DScore. Higher DScores are weighted towards teams winning unimportant matches which in turn lead to higher draft selections. Provides an alternative to current draft systems that are based on ‘losing to win’. PMID:24357945

Network intrusion detection by the coevolutionary immune algorithm of artificial immune systems with clonal selection

NASA Astrophysics Data System (ADS)

Salamatova, T.; Zhukov, V.

2017-02-01

The paper presents the application of the artificial immune systems apparatus as a heuristic method of network intrusion detection for algorithmic provision of intrusion detection systems. The coevolutionary immune algorithm of artificial immune systems with clonal selection was elaborated. In testing different datasets the empirical results of evaluation of the algorithm effectiveness were achieved. To identify the degree of efficiency the algorithm was compared with analogs. The fundamental rules based of solutions generated by this algorithm are described in the article.

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.

[The method and application to construct experience recommendation platform of acupuncture ancient books based on data mining technology].

PubMed

Chen, Chuyun; Hong, Jiaming; Zhou, Weilin; Lin, Guohua; Wang, Zhengfei; Zhang, Qufei; Lu, Cuina; Lu, Lihong

2017-07-12

To construct a knowledge platform of acupuncture ancient books based on data mining technology, and to provide retrieval service for users. The Oracle 10 g database was applied and JAVA was selected as development language; based on the standard library and ancient books database established by manual entry, a variety of data mining technologies, including word segmentation, speech tagging, dependency analysis, rule extraction, similarity calculation, ambiguity analysis, supervised classification technology were applied to achieve text automatic extraction of ancient books; in the last, through association mining and decision analysis, the comprehensive and intelligent analysis of disease and symptom, meridians, acupoints, rules of acupuncture and moxibustion in acupuncture ancient books were realized, and retrieval service was provided for users through structure of browser/server (B/S). The platform realized full-text retrieval, word frequency analysis and association analysis; when diseases or acupoints were searched, the frequencies of meridian, acupoints (diseases) and techniques were presented from high to low, meanwhile the support degree and confidence coefficient between disease and acupoints (special acupoint), acupoints and acupoints in prescription, disease or acupoints and technique were presented. The experience platform of acupuncture ancient books based on data mining technology could be used as a reference for selection of disease, meridian and acupoint in clinical treatment and education of acupuncture and moxibustion.

Women with Intellectual Disabilities Talk about Their Perceptions of Sex

ERIC Educational Resources Information Center

Bernert, D. J.; Ogletree, R. J.

2013-01-01

Background: Sexuality is learned through sexual socialisation that women with intellectual disabilities (IDs) understand and express. Rules of sexual engagement for these women can include barriers for their socialisation, intimate partner selection, and sexual expression. These rules can become more limiting when coupled with rules of femininity…

A Fuzzy Rule Based Decision Support System for Identifying Location of Water Harvesting Technologies in Rainfed Agricultural Regions

NASA Astrophysics Data System (ADS)

Chaubey, I.; Vema, V. K.; Sudheer, K.

2016-12-01

Site suitability evaluation of water conservation structures in water scarce rainfed agricultural areas consist of assessment of various landscape characteristics and various criterion. Many of these landscape characteristic attributes are conveyed through linguistic terms rather than precise numeric values. Fuzzy rule based system are capable of incorporating uncertainty and vagueness, when various decision making criteria expressed in linguistic terms are expressed as fuzzy rules. In this study a fuzzy rule based decision support system is developed, for optimal site selection of water harvesting technologies. Water conservation technologies like farm ponds, Check dams, Rock filled dams and percolation ponds aid in conserving water for irrigation and recharging aquifers and development of such a system will aid in improving the efficiency of the structures. Attributes and criteria involved in decision making are classified into different groups to estimate the suitability of the particular technology. The developed model is applied and tested on an Indian watershed. The input attributes are prepared in raster format in ArcGIS software and suitability of each raster cell is calculated and output is generated in the form of a thematic map showing the suitability of the cells pertaining to different technologies. The output of the developed model is compared against the already existing structures and results are satisfactory. This developed model will aid in improving the sustainability and efficiency of the watershed management programs aimed at enhancing in situ moisture content.

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…

Broken selection rule in the quantum Rabi model

PubMed Central

Forn-Díaz, P.; Romero, G.; Harmans, C. J. P. M.; Solano, E.; Mooij, J. E.

2016-01-01

Understanding the interaction between light and matter is very relevant for fundamental studies of quantum electrodynamics and for the development of quantum technologies. The quantum Rabi model captures the physics of a single atom interacting with a single photon at all regimes of coupling strength. We report the spectroscopic observation of a resonant transition that breaks a selection rule in the quantum Rabi model, implemented using an LC resonator and an artificial atom, a superconducting qubit. The eigenstates of the system consist of a superposition of bare qubit-resonator states with a relative sign. When the qubit-resonator coupling strength is negligible compared to their own frequencies, the matrix element between excited eigenstates of different sign is very small in presence of a resonator drive, establishing a sign-preserving selection rule. Here, our qubit-resonator system operates in the ultrastrong coupling regime, where the coupling strength is 10% of the resonator frequency, allowing sign-changing transitions to be activated and, therefore, detected. This work shows that sign-changing transitions are an unambiguous, distinctive signature of systems operating in the ultrastrong coupling regime of the quantum Rabi model. These results pave the way to further studies of sign-preserving selection rules in multiqubit and multiphoton models. PMID:27273346

Forty years of Clar's aromatic π-sextet rule

PubMed Central

Solà, Miquel

2013-01-01

In 1972 Erich Clar formulated his aromatic π-sextet rule that allows discussing qualitatively the aromatic character of benzenoid species. Now, 40 years later, Clar's aromatic π-sextet rule is still a source of inspiration for many chemists. This simple rule has been validated both experimentally and theoretically. In this review, we select some particular examples to highlight the achievement of Clar's aromatic π-sextet rule in many situations and we discuss two recent successful cases of its application. PMID:24790950

Obeying the Rules or Gaming the System? Delegating Random Selection for Examinations to Head Teachers within an Accountability System

ERIC Educational Resources Information Center

Elstad, Eyvind; Turmo, Are

2011-01-01

As education systems around the world move towards increased accountability based on performance measures, it is important to investigate the unintended effects of accountability systems. This article seeks to explore the extent to which head teachers in a large Norwegian municipality may resort to gaming the incentive system to boost their…

Dense matter theory: A simple classical approach

NASA Astrophysics Data System (ADS)

Savić, P.; Čelebonović, V.

1994-07-01

In the sixties, the first author and by P. Savić and R. Kašanin started developing a mean-field theory of dense matter. It is based on the Coulomb interaction, supplemented by a microscopic selection rule and a set of experimentally founded postulates. Applications of the theory range from the calculation of models of planetary internal structure to DAC experiments.

Ensemble Classifiers for Predicting HIV-1 Resistance from Three Rule-Based Genotypic Resistance Interpretation Systems.

PubMed

Raposo, Letícia M; Nobre, Flavio F

2017-08-30

Resistance to antiretrovirals (ARVs) is a major problem faced by HIV-infected individuals. Different rule-based algorithms were developed to infer HIV-1 susceptibility to antiretrovirals from genotypic data. However, there is discordance between them, resulting in difficulties for clinical decisions about which treatment to use. Here, we developed ensemble classifiers integrating three interpretation algorithms: Agence Nationale de Recherche sur le SIDA (ANRS), Rega, and the genotypic resistance interpretation system from Stanford HIV Drug Resistance Database (HIVdb). Three approaches were applied to develop a classifier with a single resistance profile: stacked generalization, a simple plurality vote scheme and the selection of the interpretation system with the best performance. The strategies were compared with the Friedman's test and the performance of the classifiers was evaluated using the F-measure, sensitivity and specificity values. We found that the three strategies had similar performances for the selected antiretrovirals. For some cases, the stacking technique with naïve Bayes as the learning algorithm showed a statistically superior F-measure. This study demonstrates that ensemble classifiers can be an alternative tool for clinical decision-making since they provide a single resistance profile from the most commonly used resistance interpretation systems.

FuzzObserver

NASA Technical Reports Server (NTRS)

Howard, Ayanna; Bayard, David

2006-01-01

Fuzzy Feature Observation Planner for Small Body Proximity Observations (FuzzObserver) is a developmental computer program, to be used along with other software, for autonomous planning of maneuvers of a spacecraft near an asteroid, comet, or other small astronomical body. Selection of terrain features and estimation of the position of the spacecraft relative to these features is an essential part of such planning. FuzzObserver contributes to the selection and estimation by generating recommendations for spacecraft trajectory adjustments to maintain the spacecraft's ability to observe sufficient terrain features for estimating position. The input to FuzzObserver consists of data from terrain images, including sets of data on features acquired during descent toward, or traversal of, a body of interest. The name of this program reflects its use of fuzzy logic to reason about the terrain features represented by the data and extract corresponding trajectory-adjustment rules. Linguistic fuzzy sets and conditional statements enable fuzzy systems to make decisions based on heuristic rule-based knowledge derived by engineering experts. A major advantage of using fuzzy logic is that it involves simple arithmetic calculations that can be performed rapidly enough to be useful for planning within the short times typically available for spacecraft maneuvers.

On Decision-Making Among Multiple Rule-Bases in Fuzzy Control Systems

NASA Technical Reports Server (NTRS)

Tunstel, Edward; Jamshidi, Mo

1997-01-01

Intelligent control of complex multi-variable systems can be a challenge for single fuzzy rule-based controllers. This class of problems cam often be managed with less difficulty by distributing intelligent decision-making amongst a collection of rule-bases. Such an approach requires that a mechanism be chosen to ensure goal-oriented interaction between the multiple rule-bases. In this paper, a hierarchical rule-based approach is described. Decision-making mechanisms based on generalized concepts from single-rule-based fuzzy control are described. Finally, the effects of different aggregation operators on multi-rule-base decision-making are examined in a navigation control problem for mobile robots.

Factor Analysis of Therapist-Identified Treatment Targets in Community-Based Children's Mental Health.

PubMed

Love, Allison R; Okado, Izumi; Orimoto, Trina E; Mueller, Charles W

2018-01-01

The present study used exploratory and confirmatory factor analyses to identify underlying latent factors affecting variation in community therapists' endorsement of treatment targets. As part of a statewide practice management program, therapist completed monthly reports of treatment targets (up to 10 per month) for a sample of youth (n = 790) receiving intensive in-home therapy. Nearly 75 % of youth were diagnosed with multiple co-occurring disorders. Five factors emerged: Disinhibition, Societal Rules Evasion, Social Engagement Deficits, Emotional Distress, and Management of Biodevelopmental Outcomes. Using logistic regression, primary diagnosis predicted therapist selection of Disinhibition and Emotional Distress targets. Client age predicted endorsement of Societal Rules Evasion targets. Practice-to-research implications are discussed.

A Total Quality-Control Plan with Right-Sized Statistical Quality-Control.

PubMed

Westgard, James O

2017-03-01

A new Clinical Laboratory Improvement Amendments option for risk-based quality-control (QC) plans became effective in January, 2016. Called an Individualized QC Plan, this option requires the laboratory to perform a risk assessment, develop a QC plan, and implement a QC program to monitor ongoing performance of the QC plan. Difficulties in performing a risk assessment may limit validity of an Individualized QC Plan. A better alternative is to develop a Total QC Plan including a right-sized statistical QC procedure to detect medically important errors. Westgard Sigma Rules provides a simple way to select the right control rules and the right number of control measurements. Copyright © 2016 Elsevier Inc. All rights reserved.

Data driven model generation based on computational intelligence

NASA Astrophysics Data System (ADS)

Gemmar, Peter; Gronz, Oliver; Faust, Christophe; Casper, Markus

2010-05-01

The simulation of discharges at a local gauge or the modeling of large scale river catchments are effectively involved in estimation and decision tasks of hydrological research and practical applications like flood prediction or water resource management. However, modeling such processes using analytical or conceptual approaches is made difficult by both complexity of process relations and heterogeneity of processes. It was shown manifold that unknown or assumed process relations can principally be described by computational methods, and that system models can automatically be derived from observed behavior or measured process data. This study describes the development of hydrological process models using computational methods including Fuzzy logic and artificial neural networks (ANN) in a comprehensive and automated manner. Methods We consider a closed concept for data driven development of hydrological models based on measured (experimental) data. The concept is centered on a Fuzzy system using rules of Takagi-Sugeno-Kang type which formulate the input-output relation in a generic structure like Ri : IFq(t) = lowAND...THENq(t+Δt) = ai0 +ai1q(t)+ai2p(t-Δti1)+ai3p(t+Δti2)+.... The rule's premise part (IF) describes process states involving available process information, e.g. actual outlet q(t) is low where low is one of several Fuzzy sets defined over variable q(t). The rule's conclusion (THEN) estimates expected outlet q(t + Δt) by a linear function over selected system variables, e.g. actual outlet q(t), previous and/or forecasted precipitation p(t ?Δtik). In case of river catchment modeling we use head gauges, tributary and upriver gauges in the conclusion part as well. In addition, we consider temperature and temporal (season) information in the premise part. By creating a set of rules R = {Ri|(i = 1,...,N)} the space of process states can be covered as concise as necessary. Model adaptation is achieved by finding on optimal set A = (aij) of conclusion parameters with respect to a defined rating function and experimental data. To find A, we use for example a linear equation solver and RMSE-function. In practical process models, the number of Fuzzy sets and the according number of rules is fairly low. Nevertheless, creating the optimal model requires some experience. Therefore, we improved this development step by methods for automatic generation of Fuzzy sets, rules, and conclusions. Basically, the model achievement depends to a great extend on the selection of the conclusion variables. It is the aim that variables having most influence on the system reaction being considered and superfluous ones being neglected. At first, we use Kohonen maps, a specialized ANN, to identify relevant input variables from the large set of available system variables. A greedy algorithm selects a comprehensive set of dominant and uncorrelated variables. Next, the premise variables are analyzed with clustering methods (e.g. Fuzzy-C-means) and Fuzzy sets are then derived from cluster centers and outlines. The rule base is automatically constructed by permutation of the Fuzzy sets of the premise variables. Finally, the conclusion parameters are calculated and the total coverage of the input space is iteratively tested with experimental data, rarely firing rules are combined and coarse coverage of sensitive process states results in refined Fuzzy sets and rules. Results The described methods were implemented and integrated in a development system for process models. A series of models has already been built e.g. for rainfall-runoff modeling or for flood prediction (up to 72 hours) in river catchments. The models required significantly less development effort and showed advanced simulation results compared to conventional models. The models can be used operationally and simulation takes only some minutes on a standard PC e.g. for a gauge forecast (up to 72 hours) for the whole Mosel (Germany) river catchment.

McTwo: a two-step feature selection algorithm based on maximal information coefficient.

PubMed

Ge, Ruiquan; Zhou, Manli; Luo, Youxi; Meng, Qinghan; Mai, Guoqin; Ma, Dongli; Wang, Guoqing; Zhou, Fengfeng

2016-03-23

High-throughput bio-OMIC technologies are producing high-dimension data from bio-samples at an ever increasing rate, whereas the training sample number in a traditional experiment remains small due to various difficulties. This "large p, small n" paradigm in the area of biomedical "big data" may be at least partly solved by feature selection algorithms, which select only features significantly associated with phenotypes. Feature selection is an NP-hard problem. Due to the exponentially increased time requirement for finding the globally optimal solution, all the existing feature selection algorithms employ heuristic rules to find locally optimal solutions, and their solutions achieve different performances on different datasets. This work describes a feature selection algorithm based on a recently published correlation measurement, Maximal Information Coefficient (MIC). The proposed algorithm, McTwo, aims to select features associated with phenotypes, independently of each other, and achieving high classification performance of the nearest neighbor algorithm. Based on the comparative study of 17 datasets, McTwo performs about as well as or better than existing algorithms, with significantly reduced numbers of selected features. The features selected by McTwo also appear to have particular biomedical relevance to the phenotypes from the literature. McTwo selects a feature subset with very good classification performance, as well as a small feature number. So McTwo may represent a complementary feature selection algorithm for the high-dimensional biomedical datasets.

Quasiparticle interference mapping of ZrSiS

NASA Astrophysics Data System (ADS)

Lodge, Michael; Hosen, Md Mofazzle; Neupane, Madhab; Ishigami, Masa; Chang, Guoqing; Singh, Bahadur; Lin, Hsin; Weber, Bent; Hellerstedt, Jack; Edmonds, Mark; Fuhrer, Michael; Kaczorowski, Dariusz

The emergent class of 3D Dirac semimetals presents intriguing new systems in which to study the rich physics of the robust, topologically-protected quasiparticles hosted within their bulk. For example, in nodal-line Dirac semimetals, the conductance and valence bands meet along a closed loop in momentum space and disperse linearly in the vicinity of the resultant line node. This results in novel scattering phenomena, owing to the unique Fermi surfaces and scattering selection rules of these systems. Here, we have performed scanning tunneling microscopy and spectroscopy of ZrSiS, one such nodal-line Dirac semimetal,at 4.5 K. We have visualized quasiparticle scattering using differential conductance mapping. In conjunction with numerical modeling, we identify at least six allowed scattering vectors in the material, which gives insight into the scattering selection rules of these novel materials. This work is based upon research supported by the National Science Foundation under Grant No. 0955625 (MSL and MI) and Fellowship No. 1614303 (MSL), and by the Australian Research Council under DECRA Fellowship No. DE160101334 (BW).

Design and static structural analysis of a race car chassis for Formula Society of Automotive Engineers (FSAE) event

NASA Astrophysics Data System (ADS)

Mohamad, M. L.; Rahman, M. T. A.; Khan, S. F.; Basha, M. H.; Adom, A. H.; Hashim, M. S. M.

2017-10-01

The main purpose of this study is to make improvement for the UniMAP Automotive Racing Team car chassis which has several problems associated with the chassis must be fixed and some changes are needed to be made in order to perform well. This study involves the process of designing three chassis that are created based on the rules stated by FSAE rules book (2017/2018). The three chassis will undergo analysis test that consists of five tests which are main roll hoop test, front roll hoop test, static shear, side impact, static torsional loading and finally one of them will be selected as the best design in term of Von Mises Stress and torsional displacement. From the results obtained, the new selected chassis design which also declared as the new improved design poses the weight of 27.66 kg which was decreased by 16.7% from the existing chassis (32.77 kg). The torsional rigidity of the improved chassis increased by 37.74%.

Knowledge-based low-level image analysis for computer vision systems

NASA Technical Reports Server (NTRS)

Dhawan, Atam P.; Baxi, Himanshu; Ranganath, M. V.

1988-01-01

Two algorithms for entry-level image analysis and preliminary segmentation are proposed which are flexible enough to incorporate local properties of the image. The first algorithm involves pyramid-based multiresolution processing and a strategy to define and use interlevel and intralevel link strengths. The second algorithm, which is designed for selected window processing, extracts regions adaptively using local histograms. The preliminary segmentation and a set of features are employed as the input to an efficient rule-based low-level analysis system, resulting in suboptimal meaningful segmentation.

The evolution of social learning rules: payoff-biased and frequency-dependent biased transmission.

PubMed

Kendal, Jeremy; Giraldeau, Luc-Alain; Laland, Kevin

2009-09-21

Humans and other animals do not use social learning indiscriminately, rather, natural selection has favoured the evolution of social learning rules that make selective use of social learning to acquire relevant information in a changing environment. We present a gene-culture coevolutionary analysis of a small selection of such rules (unbiased social learning, payoff-biased social learning and frequency-dependent biased social learning, including conformism and anti-conformism) in a population of asocial learners where the environment is subject to a constant probability of change to a novel state. We define conditions under which each rule evolves to a genetically polymorphic equilibrium. We find that payoff-biased social learning may evolve under high levels of environmental variation if the fitness benefit associated with the acquired behaviour is either high or low but not of intermediate value. In contrast, both conformist and anti-conformist biases can become fixed when environment variation is low, whereupon the mean fitness in the population is higher than for a population of asocial learners. Our examination of the population dynamics reveals stable limit cycles under conformist and anti-conformist biases and some highly complex dynamics including chaos. Anti-conformists can out-compete conformists when conditions favour a low equilibrium frequency of the learned behaviour. We conclude that evolution, punctuated by the repeated successful invasion of different social learning rules, should continuously favour a reduction in the equilibrium frequency of asocial learning, and propose that, among competing social learning rules, the dominant rule will be the one that can persist with the lowest frequency of asocial learning.

Rules and guidelines in clinical practice: a qualitative study in operating theatres of doctors' and nurses' views

PubMed Central

McDonald, R; Waring, J; Harrison, S; Walshe, K; Boaden, R

2005-01-01

Background: The current orthodoxy within patient safety research and policy is characterised by a faith in rules based systems which limit the capacity for individual discretion, and hence fallibility. However, guidelines have been seen as stifling innovation and eroding trust. Our objectives were to explore the attitudes towards guidelines of doctors and nurses working together in surgical teams and to examine the extent to which trusting relationships are maintained in a context governed by explicit rules. Methods: Fourteen consultant grade surgeons of mixed specialty, 12 consultant anaesthetists, and 15 nurses were selected to reflect a range of roles. Participant observation was combined with semi-structured interviews. Results: Doctors' views about the contribution of guidelines to safety and to clinical practice differed from those of nurses. Doctors rejected written rules, instead adhering to the unwritten rules of what constitutes acceptable behaviour for members of the medical profession. In contrast, nurses viewed guideline adherence as synonymous with professionalism and criticised doctors for failing to comply with guidelines. Conclusions: While the creation of a "safety culture" requires a shared set of beliefs, attitudes and norms in relation to what is seen as safe clinical practice, differences of opinion on these issues exist which cannot be easily reconciled since they reflect deeply ingrained beliefs about what constitutes professional conduct. While advocates of standardisation (such as nurses) view doctors as rule breakers, doctors may not necessarily regard guidelines as legitimate or identify with the rules written for them by members of other social groups. Future safety research and policy should attempt to understand the unwritten rules which govern clinical behaviour and examine the ways in which such rules are produced, maintained, and accepted as legitimate. PMID:16076795

Knowledge-based control of an adaptive interface

NASA Technical Reports Server (NTRS)

Lachman, Roy

1989-01-01

The analysis, development strategy, and preliminary design for an intelligent, adaptive interface is reported. The design philosophy couples knowledge-based system technology with standard human factors approaches to interface development for computer workstations. An expert system has been designed to drive the interface for application software. The intelligent interface will be linked to application packages, one at a time, that are planned for multiple-application workstations aboard Space Station Freedom. Current requirements call for most Space Station activities to be conducted at the workstation consoles. One set of activities will consist of standard data management services (DMS). DMS software includes text processing, spreadsheets, data base management, etc. Text processing was selected for the first intelligent interface prototype because text-processing software can be developed initially as fully functional but limited with a small set of commands. The program's complexity then can be increased incrementally. The intelligent interface includes the operator's behavior and three types of instructions to the underlying application software are included in the rule base. A conventional expert-system inference engine searches the data base for antecedents to rules and sends the consequents of fired rules as commands to the underlying software. Plans for putting the expert system on top of a second application, a database management system, will be carried out following behavioral research on the first application. The intelligent interface design is suitable for use with ground-based workstations now common in government, industrial, and educational organizations.

Multi-focus image fusion based on area-based standard deviation in dual tree contourlet transform domain

NASA Astrophysics Data System (ADS)

Dong, Min; Dong, Chenghui; Guo, Miao; Wang, Zhe; Mu, Xiaomin

2018-04-01

Multiresolution-based methods, such as wavelet and Contourlet are usually used to image fusion. This work presents a new image fusion frame-work by utilizing area-based standard deviation in dual tree Contourlet trans-form domain. Firstly, the pre-registered source images are decomposed with dual tree Contourlet transform; low-pass and high-pass coefficients are obtained. Then, the low-pass bands are fused with weighted average based on area standard deviation rather than the simple "averaging" rule. While the high-pass bands are merged with the "max-absolute' fusion rule. Finally, the modified low-pass and high-pass coefficients are used to reconstruct the final fused image. The major advantage of the proposed fusion method over conventional fusion is the approximately shift invariance and multidirectional selectivity of dual tree Contourlet transform. The proposed method is compared with wavelet- , Contourletbased methods and other the state-of-the art methods on common used multi focus images. Experiments demonstrate that the proposed fusion framework is feasible and effective, and it performs better in both subjective and objective evaluation.

RuleMonkey: software for stochastic simulation of rule-based models

PubMed Central

2010-01-01

Background The system-level dynamics of many molecular interactions, particularly protein-protein interactions, can be conveniently represented using reaction rules, which can be specified using model-specification languages, such as the BioNetGen language (BNGL). A set of rules implicitly defines a (bio)chemical reaction network. The reaction network implied by a set of rules is often very large, and as a result, generation of the network implied by rules tends to be computationally expensive. Moreover, the cost of many commonly used methods for simulating network dynamics is a function of network size. Together these factors have limited application of the rule-based modeling approach. Recently, several methods for simulating rule-based models have been developed that avoid the expensive step of network generation. The cost of these "network-free" simulation methods is independent of the number of reactions implied by rules. Software implementing such methods is now needed for the simulation and analysis of rule-based models of biochemical systems. Results Here, we present a software tool called RuleMonkey, which implements a network-free method for simulation of rule-based models that is similar to Gillespie's method. The method is suitable for rule-based models that can be encoded in BNGL, including models with rules that have global application conditions, such as rules for intramolecular association reactions. In addition, the method is rejection free, unlike other network-free methods that introduce null events, i.e., steps in the simulation procedure that do not change the state of the reaction system being simulated. We verify that RuleMonkey produces correct simulation results, and we compare its performance against DYNSTOC, another BNGL-compliant tool for network-free simulation of rule-based models. We also compare RuleMonkey against problem-specific codes implementing network-free simulation methods. Conclusions RuleMonkey enables the simulation of rule-based models for which the underlying reaction networks are large. It is typically faster than DYNSTOC for benchmark problems that we have examined. RuleMonkey is freely available as a stand-alone application http://public.tgen.org/rulemonkey. It is also available as a simulation engine within GetBonNie, a web-based environment for building, analyzing and sharing rule-based models. PMID:20673321

Learning accurate and interpretable models based on regularized random forests regression

PubMed Central

2014-01-01

Background Many biology related research works combine data from multiple sources in an effort to understand the underlying problems. It is important to find and interpret the most important information from these sources. Thus it will be beneficial to have an effective algorithm that can simultaneously extract decision rules and select critical features for good interpretation while preserving the prediction performance. Methods In this study, we focus on regression problems for biological data where target outcomes are continuous. In general, models constructed from linear regression approaches are relatively easy to interpret. However, many practical biological applications are nonlinear in essence where we can hardly find a direct linear relationship between input and output. Nonlinear regression techniques can reveal nonlinear relationship of data, but are generally hard for human to interpret. We propose a rule based regression algorithm that uses 1-norm regularized random forests. The proposed approach simultaneously extracts a small number of rules from generated random forests and eliminates unimportant features. Results We tested the approach on some biological data sets. The proposed approach is able to construct a significantly smaller set of regression rules using a subset of attributes while achieving prediction performance comparable to that of random forests regression. Conclusion It demonstrates high potential in aiding prediction and interpretation of nonlinear relationships of the subject being studied. PMID:25350120

Self-Associations Influence Task-Performance through Bayesian Inference

PubMed Central

Bengtsson, Sara L.; Penny, Will D.

2013-01-01

The way we think about ourselves impacts greatly on our behavior. This paper describes a behavioral study and a computational model that shed new light on this important area. Participants were primed “clever” and “stupid” using a scrambled sentence task, and we measured the effect on response time and error-rate on a rule-association task. First, we observed a confirmation bias effect in that associations to being “stupid” led to a gradual decrease in performance, whereas associations to being “clever” did not. Second, we observed that the activated self-concepts selectively modified attention toward one’s performance. There was an early to late double dissociation in RTs in that primed “clever” resulted in RT increase following error responses, whereas primed “stupid” resulted in RT increase following correct responses. We propose a computational model of subjects’ behavior based on the logic of the experimental task that involves two processes; memory for rules and the integration of rules with subsequent visual cues. The model incorporates an adaptive decision threshold based on Bayes rule, whereby decision thresholds are increased if integration was inferred to be faulty. Fitting the computational model to experimental data confirmed our hypothesis that priming affects the memory process. This model explains both the confirmation bias and double dissociation effects and demonstrates that Bayesian inferential principles can be used to study the effect of self-concepts on behavior. PMID:23966937

Characterization of hidden rules linking symptoms and selection of acupoint using an artificial neural network model.

PubMed

Jung, Won-Mo; Park, In-Soo; Lee, Ye-Seul; Kim, Chang-Eop; Lee, Hyangsook; Hahm, Dae-Hyun; Park, Hi-Joon; Jang, Bo-Hyoung; Chae, Younbyoung

2018-04-12

Comprehension of the medical diagnoses of doctors and treatment of diseases is important to understand the underlying principle in selecting appropriate acupoints. The pattern recognition process that pertains to symptoms and diseases and informs acupuncture treatment in a clinical setting was explored. A total of 232 clinical records were collected using a Charting Language program. The relationship between symptom information and selected acupoints was trained using an artificial neural network (ANN). A total of 11 hidden nodes with the highest average precision score were selected through a tenfold cross-validation. Our ANN model could predict the selected acupoints based on symptom and disease information with an average precision score of 0.865 (precision, 0.911; recall, 0.811). This model is a useful tool for diagnostic classification or pattern recognition and for the prediction and modeling of acupuncture treatment based on clinical data obtained in a real-world setting. The relationship between symptoms and selected acupoints could be systematically characterized through knowledge discovery processes, such as pattern identification.

Network-Based Method for Identifying Co-Regeneration Genes in Bone, Dentin, Nerve and Vessel Tissues

PubMed Central

Pan, Hongying; Zhang, Yu-Hang; Feng, Kaiyan; Kong, XiangYin; Cai, Yu-Dong

2017-01-01

Bone and dental diseases are serious public health problems. Most current clinical treatments for these diseases can produce side effects. Regeneration is a promising therapy for bone and dental diseases, yielding natural tissue recovery with few side effects. Because soft tissues inside the bone and dentin are densely populated with nerves and vessels, the study of bone and dentin regeneration should also consider the co-regeneration of nerves and vessels. In this study, a network-based method to identify co-regeneration genes for bone, dentin, nerve and vessel was constructed based on an extensive network of protein–protein interactions. Three procedures were applied in the network-based method. The first procedure, searching, sought the shortest paths connecting regeneration genes of one tissue type with regeneration genes of other tissues, thereby extracting possible co-regeneration genes. The second procedure, testing, employed a permutation test to evaluate whether possible genes were false discoveries; these genes were excluded by the testing procedure. The last procedure, screening, employed two rules, the betweenness ratio rule and interaction score rule, to select the most essential genes. A total of seventeen genes were inferred by the method, which were deemed to contribute to co-regeneration of at least two tissues. All these seventeen genes were extensively discussed to validate the utility of the method. PMID:28974058

Network-Based Method for Identifying Co- Regeneration Genes in Bone, Dentin, Nerve and Vessel Tissues.

PubMed

Chen, Lei; Pan, Hongying; Zhang, Yu-Hang; Feng, Kaiyan; Kong, XiangYin; Huang, Tao; Cai, Yu-Dong

2017-10-02

Bone and dental diseases are serious public health problems. Most current clinical treatments for these diseases can produce side effects. Regeneration is a promising therapy for bone and dental diseases, yielding natural tissue recovery with few side effects. Because soft tissues inside the bone and dentin are densely populated with nerves and vessels, the study of bone and dentin regeneration should also consider the co-regeneration of nerves and vessels. In this study, a network-based method to identify co-regeneration genes for bone, dentin, nerve and vessel was constructed based on an extensive network of protein-protein interactions. Three procedures were applied in the network-based method. The first procedure, searching, sought the shortest paths connecting regeneration genes of one tissue type with regeneration genes of other tissues, thereby extracting possible co-regeneration genes. The second procedure, testing, employed a permutation test to evaluate whether possible genes were false discoveries; these genes were excluded by the testing procedure. The last procedure, screening, employed two rules, the betweenness ratio rule and interaction score rule, to select the most essential genes. A total of seventeen genes were inferred by the method, which were deemed to contribute to co-regeneration of at least two tissues. All these seventeen genes were extensively discussed to validate the utility of the method.

Random Walk Quantum Clustering Algorithm Based on Space

NASA Astrophysics Data System (ADS)

Xiao, Shufen; Dong, Yumin; Ma, Hongyang

2018-01-01

In the random quantum walk, which is a quantum simulation of the classical walk, data points interacted when selecting the appropriate walk strategy by taking advantage of quantum-entanglement features; thus, the results obtained when the quantum walk is used are different from those when the classical walk is adopted. A new quantum walk clustering algorithm based on space is proposed by applying the quantum walk to clustering analysis. In this algorithm, data points are viewed as walking participants, and similar data points are clustered using the walk function in the pay-off matrix according to a certain rule. The walk process is simplified by implementing a space-combining rule. The proposed algorithm is validated by a simulation test and is proved superior to existing clustering algorithms, namely, Kmeans, PCA + Kmeans, and LDA-Km. The effects of some of the parameters in the proposed algorithm on its performance are also analyzed and discussed. Specific suggestions are provided.

Effective W-state fusion strategies for electronic and photonic qubits via the quantum-dot-microcavity coupled system.

PubMed

Han, Xue; Hu, Shi; Guo, Qi; Wang, Hong-Fu; Zhu, Ai-Dong; Zhang, Shou

2015-08-05

We propose effective fusion schemes for stationary electronic W state and flying photonic W state, respectively, by using the quantum-dot-microcavity coupled system. The present schemes can fuse a n-qubit W state and a m-qubit W state to a (m + n - 1)-qubit W state, that is, these schemes can be used to not only create large W state with small ones, but also to prepare 3-qubit W states with Bell states. The schemes are based on the optical selection rules and the transmission and reflection rules of the cavity and can be achieved with high probability. We evaluate the effect of experimental imperfections and the feasibility of the schemes, which shows that the present schemes can be realized with high fidelity in both the weak coupling and the strong coupling regimes. These schemes may be meaningful for the large-scale solid-state-based quantum computation and the photon-qubit-based quantum communication.

Medication regularity of pulmonary fibrosis treatment by contemporary traditional Chinese medicine experts based on data mining.

PubMed

Zhang, Suxian; Wu, Hao; Liu, Jie; Gu, Huihui; Li, Xiujuan; Zhang, Tiansong

2018-03-01

Treatment of pulmonary fibrosis by traditional Chinese medicine (TCM) has accumulated important experience. Our interest is in exploring the medication regularity of contemporary Chinese medical specialists treating pulmonary fibrosis. Through literature search, medical records from TCM experts who treat pulmonary fibrosis, which were published in Chinese and English medical journals, were selected for this study. As the object of study, a database was established after analysing the records. After data cleaning, the rules of medicine in the treatment of pulmonary fibrosis in medical records of TCM were explored by using data mining technologies such as frequency analysis, association rule analysis, and link analysis. A total of 124 medical records from 60 doctors were selected in this study; 263 types of medicinals were used a total of 5,455 times; the herbs that were used more than 30 times can be grouped into 53 species and were used a total of 3,681 times. Using main medicinals cluster analysis, medicinals were divided into qi-tonifying, yin-tonifying, blood-activating, phlegm-resolving, cough-suppressing, panting-calming, and ten other major medicinal categories. According to the set conditions, a total of 62 drug compatibility rules have been obtained, involving mainly qi-tonifying, yin-tonifying, blood-activating, phlegm-resolving, qi-descending, and panting-calming medicinals, as well as other medicinals used in combination. The results of data mining are consistent with clinical practice and it is feasible to explore the medical rules applicable to the treatment of pulmonary fibrosis in medical records of TCM by data mining.

Where the item still rules supreme: Time-based selection, enumeration, pre-attentive processing and the target template?

PubMed

Watson, Derrick G

2017-01-01

I propose that there remains a central role for the item (or its equivalent) in a wider range of search and search-related tasks/functions than might be conveyed by the article. I consider the functional relationship between the framework and some aspects of previous theories, and suggest some challenges that the new framework might encounter.

Training sample selection based on self-training for liver cirrhosis classification using ultrasound images

NASA Astrophysics Data System (ADS)

Fujita, Yusuke; Mitani, Yoshihiro; Hamamoto, Yoshihiko; Segawa, Makoto; Terai, Shuji; Sakaida, Isao

2017-03-01

Ultrasound imaging is a popular and non-invasive tool used in the diagnoses of liver disease. Cirrhosis is a chronic liver disease and it can advance to liver cancer. Early detection and appropriate treatment are crucial to prevent liver cancer. However, ultrasound image analysis is very challenging, because of the low signal-to-noise ratio of ultrasound images. To achieve the higher classification performance, selection of training regions of interest (ROIs) is very important that effect to classification accuracy. The purpose of our study is cirrhosis detection with high accuracy using liver ultrasound images. In our previous works, training ROI selection by MILBoost and multiple-ROI classification based on the product rule had been proposed, to achieve high classification performance. In this article, we propose self-training method to select training ROIs effectively. Evaluation experiments were performed to evaluate effect of self-training, using manually selected ROIs and also automatically selected ROIs. Experimental results show that self-training for manually selected ROIs achieved higher classification performance than other approaches, including our conventional methods. The manually ROI definition and sample selection are important to improve classification accuracy in cirrhosis detection using ultrasound images.

Determination of the rockfall source in an urban settlement area by using a rule-based fuzzy evaluation

NASA Astrophysics Data System (ADS)

Aksoy, H.; Ercanoglu, M.

2006-10-01

The evaluation of the rockfall initiation mechanism and the simulation of the runout behavior is an important issue in the prevention and remedial measures for potential rockfall hazards in highway protection, in forest preservation, and especially in urban settlement areas. In most of the studies in the literature, the extent of the rockfall hazard was determined by various techniques basing on the selection of a rockfall source, generally defined as zones of rock bodies having slope angles higher than a certain value, proposed by general practice. In the present study, it was aimed to carry out a rule-based fuzzy analysis on the discontinuity data of andesites in the city of Ankara, Turkey, in order to bring a different and rather systematic approach to determine the source areas for rockfall hazard in an urban settlement, based on the discontinuity and natural slope features. First, to obtain rock source areas (RSAs), data obtained from the field studies were combined with a rule-based fuzzy evaluation, incorporating the altitude difference, the number of discontinuities, the number of wedges and the number of potential slides as the parameters of the fuzzy sets. After processing the outputs of the rule-based fuzzy system and producing the linguistic definitions, it could be possible to obtain potential RSAs. According to the RSA maps, 1.7% of the study area was found to have "high RSA", and 5.8% of the study area was assigned as "medium RSA". Then, potential rockfall hazard map was prepared. At the final stage, based upon the high and medium RSAs, 3.6% of the study area showed "high rockfall potential", while areal distribution of "medium rockfall potential" was found as 7.9%. Both RSA and potential rockfall hazard map were in accordance with the observations performed in the field.

Health Insurance: Understanding Your Health Plan's Rules

MedlinePlus

... Point of service (POS) plan Preferred provider organization (PPO) Rules for selecting doctors and hospitals Managed care ... If you have a POS plan or a PPO, the insurance company will probably pay for you ...

Analysis of the iteratively regularized Gauss-Newton method under a heuristic rule

NASA Astrophysics Data System (ADS)

Jin, Qinian; Wang, Wei

2018-03-01

The iteratively regularized Gauss-Newton method is one of the most prominent regularization methods for solving nonlinear ill-posed inverse problems when the data is corrupted by noise. In order to produce a useful approximate solution, this iterative method should be terminated properly. The existing a priori and a posteriori stopping rules require accurate information on the noise level, which may not be available or reliable in practical applications. In this paper we propose a heuristic selection rule for this regularization method, which requires no information on the noise level. By imposing certain conditions on the noise, we derive a posteriori error estimates on the approximate solutions under various source conditions. Furthermore, we establish a convergence result without using any source condition. Numerical results are presented to illustrate the performance of our heuristic selection rule.

ERIC Processing Manual. Rules and Guidelines for the Acquisition, Selection, and Technical Processing of Documents and Journal Articles by the Various Components of the ERIC Network.

ERIC Educational Resources Information Center

Brandhorst, Ted, Ed.; And Others

This loose-leaf manual provides the detailed rules, guidelines, and examples to be used by the components of the Educational Resources Information Center (ERIC) Network in acquiring and selecting documents and in processing them (i.e., cataloging, indexing, abstracting) for input to the ERIC computer system and subsequent announcement in…

76 FR 63691 - Self-Regulatory Organizations; Notice of Filing of Proposed Rule Change by International...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-10-13

... Short Term Options Series Program October 6, 2011. Pursuant to Section 19(b)(1) of the Securities... Proposed Rule Change The Exchange proposes to amend its rules to expand the Short Term Option Series... Term Option Series Program (``STOS Program'') \\3\\ so that the Exchange may select twenty-five option...

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Medicare Program; Merit-Based Incentive Payment System (MIPS) and Alternative Payment Model (APM) Incentive Under the Physician Fee Schedule, and Criteria for Physician-Focused Payment Models. Final rule with comment period.

PubMed

2016-11-04

The Medicare Access and CHIP Reauthorization Act of 2015 (MACRA) repeals the Medicare sustainable growth rate (SGR) methodology for updates to the physician fee schedule (PFS) and replaces it with a new approach to payment called the Quality Payment Program that rewards the delivery of high-quality patient care through two avenues: Advanced Alternative Payment Models (Advanced APMs) and the Merit-based Incentive Payment System (MIPS) for eligible clinicians or groups under the PFS. This final rule with comment period establishes incentives for participation in certain alternative payment models (APMs) and includes the criteria for use by the Physician-Focused Payment Model Technical Advisory Committee (PTAC) in making comments and recommendations on physician-focused payment models (PFPMs). Alternative Payment Models are payment approaches, developed in partnership with the clinician community, that provide added incentives to deliver high-quality and cost-efficient care. APMs can apply to a specific clinical condition, a care episode, or a population. This final rule with comment period also establishes the MIPS, a new program for certain Medicare-enrolled practitioners. MIPS will consolidate components of three existing programs, the Physician Quality Reporting System (PQRS), the Physician Value-based Payment Modifier (VM), and the Medicare Electronic Health Record (EHR) Incentive Program for Eligible Professionals (EPs), and will continue the focus on quality, cost, and use of certified EHR technology (CEHRT) in a cohesive program that avoids redundancies. In this final rule with comment period we have rebranded key terminology based on feedback from stakeholders, with the goal of selecting terms that will be more easily identified and understood by our stakeholders.

A rule-based software test data generator

NASA Technical Reports Server (NTRS)

Deason, William H.; Brown, David B.; Chang, Kai-Hsiung; Cross, James H., II

1991-01-01

Rule-based software test data generation is proposed as an alternative to either path/predicate analysis or random data generation. A prototype rule-based test data generator for Ada programs is constructed and compared to a random test data generator. Four Ada procedures are used in the comparison. Approximately 2000 rule-based test cases and 100,000 randomly generated test cases are automatically generated and executed. The success of the two methods is compared using standard coverage metrics. Simple statistical tests showing that even the primitive rule-based test data generation prototype is significantly better than random data generation are performed. This result demonstrates that rule-based test data generation is feasible and shows great promise in assisting test engineers, especially when the rule base is developed further.

Dynamic Querying of Mass-Storage RDF Data with Rule-Based Entailment Regimes

NASA Astrophysics Data System (ADS)

Ianni, Giovambattista; Krennwallner, Thomas; Martello, Alessandra; Polleres, Axel

RDF Schema (RDFS) as a lightweight ontology language is gaining popularity and, consequently, tools for scalable RDFS inference and querying are needed. SPARQL has become recently a W3C standard for querying RDF data, but it mostly provides means for querying simple RDF graphs only, whereas querying with respect to RDFS or other entailment regimes is left outside the current specification. In this paper, we show that SPARQL faces certain unwanted ramifications when querying ontologies in conjunction with RDF datasets that comprise multiple named graphs, and we provide an extension for SPARQL that remedies these effects. Moreover, since RDFS inference has a close relationship with logic rules, we generalize our approach to select a custom ruleset for specifying inferences to be taken into account in a SPARQL query. We show that our extensions are technically feasible by providing benchmark results for RDFS querying in our prototype system GiaBATA, which uses Datalog coupled with a persistent Relational Database as a back-end for implementing SPARQL with dynamic rule-based inference. By employing different optimization techniques like magic set rewriting our system remains competitive with state-of-the-art RDFS querying systems.

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.

Decision Aids for Airborne Intercept Operations in Advanced Aircrafts

NASA Technical Reports Server (NTRS)

Madni, A.; Freedy, A.

1981-01-01

A tactical decision aid (TDA) for the F-14 aircrew, i.e., the naval flight officer and pilot, in conducting a multitarget attack during the performance of a Combat Air Patrol (CAP) role is presented. The TDA employs hierarchical multiattribute utility models for characterizing mission objectives in operationally measurable terms, rule based AI-models for tactical posture selection, and fast time simulation for maneuver consequence prediction. The TDA makes aspect maneuver recommendations, selects and displays the optimum mission posture, evaluates attackable and potentially attackable subsets, and recommends the 'best' attackable subset along with the required course perturbation.

Cognitive Control Functions of Anterior Cingulate Cortex in Macaque Monkeys Performing a Wisconsin Card Sorting Test Analog

PubMed Central

Kuwabara, Masaru; Mansouri, Farshad A.; Buckley, Mark J.

2014-01-01

Monkeys were trained to select one of three targets by matching in color or matching in shape to a sample. Because the matching rule frequently changed and there were no cues for the currently relevant rule, monkeys had to maintain the relevant rule in working memory to select the correct target. We found that monkeys' error commission was not limited to the period after the rule change and occasionally occurred even after several consecutive correct trials, indicating that the task was cognitively demanding. In trials immediately after such error trials, monkeys' speed of selecting targets was slower. Additionally, in trials following consecutive correct trials, the monkeys' target selections for erroneous responses were slower than those for correct responses. We further found evidence for the involvement of the cortex in the anterior cingulate sulcus (ACCs) in these error-related behavioral modulations. First, ACCs cell activity differed between after-error and after-correct trials. In another group of ACCs cells, the activity differed depending on whether the monkeys were making a correct or erroneous decision in target selection. Second, bilateral ACCs lesions significantly abolished the response slowing both in after-error trials and in error trials. The error likelihood in after-error trials could be inferred by the error feedback in the previous trial, whereas the likelihood of erroneous responses after consecutive correct trials could be monitored only internally. These results suggest that ACCs represent both context-dependent and internally detected error likelihoods and promote modes of response selections in situations that involve these two types of error likelihood. PMID:24872558

The time course of explicit and implicit categorization.

PubMed

Smith, J David; Zakrzewski, Alexandria C; Herberger, Eric R; Boomer, Joseph; Roeder, Jessica L; Ashby, F Gregory; Church, Barbara A

2015-10-01

Contemporary theory in cognitive neuroscience distinguishes, among the processes and utilities that serve categorization, explicit and implicit systems of category learning that learn, respectively, category rules by active hypothesis testing or adaptive behaviors by association and reinforcement. Little is known about the time course of categorization within these systems. Accordingly, the present experiments contrasted tasks that fostered explicit categorization (because they had a one-dimensional, rule-based solution) or implicit categorization (because they had a two-dimensional, information-integration solution). In Experiment 1, participants learned categories under unspeeded or speeded conditions. In Experiment 2, they applied previously trained category knowledge under unspeeded or speeded conditions. Speeded conditions selectively impaired implicit category learning and implicit mature categorization. These results illuminate the processing dynamics of explicit/implicit categorization.

Evaluating an ensemble classification approach for crop diversity verification in Danish greening subsidy control

NASA Astrophysics Data System (ADS)

Chellasamy, Menaka; Ferré, Ty Paul Andrew; Greve, Mogens Humlekrog

2016-07-01

Beginning in 2015, Danish farmers are obliged to meet specific crop diversification rules based on total land area and number of crops cultivated to be eligible for new greening subsidies. Hence, there is a need for the Danish government to extend their subsidy control system to verify farmers' declarations to warrant greening payments under the new crop diversification rules. Remote Sensing (RS) technology has been used since 1992 to control farmers' subsidies in Denmark. However, a proper RS-based approach is yet to be finalised to validate new crop diversity requirements designed for assessing compliance under the recent subsidy scheme (2014-2020); This study uses an ensemble classification approach (proposed by the authors in previous studies) for validating the crop diversity requirements of the new rules. The approach uses a neural network ensemble classification system with bi-temporal (spring and early summer) WorldView-2 imagery (WV2) and includes the following steps: (1) automatic computation of pixel-based prediction probabilities using multiple neural networks; (2) quantification of the classification uncertainty using Endorsement Theory (ET); (3) discrimination of crop pixels and validation of the crop diversification rules at farm level; and (4) identification of farmers who are violating the requirements for greening subsidies. The prediction probabilities are computed by a neural network ensemble supplied with training samples selected automatically using farmers declared parcels (field vectors containing crop information and the field boundary of each crop). Crop discrimination is performed by considering a set of conclusions derived from individual neural networks based on ET. Verification of the diversification rules is performed by incorporating pixel-based classification uncertainty or confidence intervals with the class labels at the farmer level. The proposed approach was tested with WV2 imagery acquired in 2011 for a study area in Vennebjerg, Denmark, containing 132 farmers, 1258 fields, and 18 crops. The classification results obtained show an overall accuracy of 90.2%. The RS-based results suggest that 36 farmers did not follow the crop diversification rules that would qualify for the greening subsidies. When compared to the farmers' reported crop mixes, irrespective of the rule, the RS results indicate that false crop declarations were made by 8 farmers, covering 15 fields. If the farmers' reports had been submitted for the new greening subsidies, 3 farmers would have made a false claim; while remaining 5 farmers obey the rules of required crop proportion even though they have submitted the false crop code due to their small holding size. The RS results would have supported 96 farmers for greening subsidy claims, with no instances of suggesting a greening subsidy for a holding that the farmer did not report as meeting the required conditions. These results suggest that the proposed RS based method shows great promise for validating the new greening subsidies in Denmark.

Land cover classification of Landsat 8 satellite data based on Fuzzy Logic approach

NASA Astrophysics Data System (ADS)

Taufik, Afirah; Sakinah Syed Ahmad, Sharifah

2016-06-01

The aim of this paper is to propose a method to classify the land covers of a satellite image based on fuzzy rule-based system approach. The study uses bands in Landsat 8 and other indices, such as Normalized Difference Water Index (NDWI), Normalized difference built-up index (NDBI) and Normalized Difference Vegetation Index (NDVI) as input for the fuzzy inference system. The selected three indices represent our main three classes called water, built- up land, and vegetation. The combination of the original multispectral bands and selected indices provide more information about the image. The parameter selection of fuzzy membership is performed by using a supervised method known as ANFIS (Adaptive neuro fuzzy inference system) training. The fuzzy system is tested for the classification on the land cover image that covers Klang Valley area. The results showed that the fuzzy system approach is effective and can be explored and implemented for other areas of Landsat data.

Executive Control Over Cognition: Stronger and Earlier Rule-Based Modulation of Spatial Category Signals in Prefrontal Cortex Relative to Parietal Cortex

PubMed Central

Goodwin, Shikha J.; Blackman, Rachael K.; Sakellaridi, Sofia

2012-01-01

Human cognition is characterized by flexibility, the ability to select not only which action but which cognitive process to engage to best achieve the current behavioral objective. The ability to tailor information processing in the brain to rules, goals, or context is typically referred to as executive control, and although there is consensus that prefrontal cortex is importantly involved, at present we have an incomplete understanding of how computational flexibility is implemented at the level of prefrontal neurons and networks. To better understand the neural mechanisms of computational flexibility, we simultaneously recorded the electrical activity of groups of single neurons within prefrontal and posterior parietal cortex of monkeys performing a task that required executive control of spatial cognitive processing. In this task, monkeys applied different spatial categorization rules to reassign the same set of visual stimuli to alternative categories on a trial-by-trial basis. We found that single neurons were activated to represent spatially defined categories in a manner that was rule dependent, providing a physiological signature of a cognitive process that was implemented under executive control. We found also that neural signals coding rule-dependent categories were distributed between the parietal and prefrontal cortex—however, not equally. Rule-dependent category signals were stronger, more powerfully modulated by the rule, and earlier to emerge in prefrontal cortex relative to parietal cortex. This suggests that prefrontal cortex may initiate the switch in neural representation at a network level that is important for computational flexibility. PMID:22399773

75 FR 26828 - Self-Regulatory Organizations; Chicago Board Options Exchange, Incorporated; Notice of Filing and...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-05-12

... amend [sic] its rules relating to the Penny Pilot Program. The text of the rule proposal is available on... proposed rule change. The text of those statements may be examined at the places specified in Item IV below... Technology Select Sector XME SPDR S&P Metals & Mining SPDR Fund. ETF. AKS AK Steel Holding Corp... KGC...

Hamilton's rule and the causes of social evolution

PubMed Central

Bourke, Andrew F. G.

2014-01-01

Hamilton's rule is a central theorem of inclusive fitness (kin selection) theory and predicts that social behaviour evolves under specific combinations of relatedness, benefit and cost. This review provides evidence for Hamilton's rule by presenting novel syntheses of results from two kinds of study in diverse taxa, including cooperatively breeding birds and mammals and eusocial insects. These are, first, studies that empirically parametrize Hamilton's rule in natural populations and, second, comparative phylogenetic analyses of the genetic, life-history and ecological correlates of sociality. Studies parametrizing Hamilton's rule are not rare and demonstrate quantitatively that (i) altruism (net loss of direct fitness) occurs even when sociality is facultative, (ii) in most cases, altruism is under positive selection via indirect fitness benefits that exceed direct fitness costs and (iii) social behaviour commonly generates indirect benefits by enhancing the productivity or survivorship of kin. Comparative phylogenetic analyses show that cooperative breeding and eusociality are promoted by (i) high relatedness and monogamy and, potentially, by (ii) life-history factors facilitating family structure and high benefits of helping and (iii) ecological factors generating low costs of social behaviour. Overall, the focal studies strongly confirm the predictions of Hamilton's rule regarding conditions for social evolution and their causes. PMID:24686934

Hamilton's rule and the causes of social evolution.

PubMed

Bourke, Andrew F G

2014-05-19

Hamilton's rule is a central theorem of inclusive fitness (kin selection) theory and predicts that social behaviour evolves under specific combinations of relatedness, benefit and cost. This review provides evidence for Hamilton's rule by presenting novel syntheses of results from two kinds of study in diverse taxa, including cooperatively breeding birds and mammals and eusocial insects. These are, first, studies that empirically parametrize Hamilton's rule in natural populations and, second, comparative phylogenetic analyses of the genetic, life-history and ecological correlates of sociality. Studies parametrizing Hamilton's rule are not rare and demonstrate quantitatively that (i) altruism (net loss of direct fitness) occurs even when sociality is facultative, (ii) in most cases, altruism is under positive selection via indirect fitness benefits that exceed direct fitness costs and (iii) social behaviour commonly generates indirect benefits by enhancing the productivity or survivorship of kin. Comparative phylogenetic analyses show that cooperative breeding and eusociality are promoted by (i) high relatedness and monogamy and, potentially, by (ii) life-history factors facilitating family structure and high benefits of helping and (iii) ecological factors generating low costs of social behaviour. Overall, the focal studies strongly confirm the predictions of Hamilton's rule regarding conditions for social evolution and their causes.

New leads for selective GSK-3 inhibition: pharmacophore mapping and virtual screening studies.

PubMed

Patel, Dhilon S; Bharatam, Prasad V

2006-01-01

Glycogen Synthase Kinase-3 is a regulatory serine/threonine kinase, which is being targeted for the treatment of a number of human diseases including type-2 diabetes mellitus, neurodegenerative diseases, cancer and chronic inflammation. Selective GSK-3 inhibition is an important requirement owing to the possibility of side effects arising from other kinases. A pharmacophore mapping strategy is employed in this work to identify new leads for selective GSK-3 inhibition. Ligands known to show selective GSK-3 inhibition were employed in generating a pharmacophore map using distance comparison method (DISCO). The derived pharmacophore map was validated using (i) important interactions involved in selective GSK-3 inhibitions, and (ii) an in-house database containing different classes of GSK-3 selective, non-selective and inactive molecules. New Lead identification was carried out by performing virtual screening using validated pharmacophoric query and three chemical databases namely NCI, Maybridge and Leadquest. Further data reduction was carried out by employing virtual filters based on (i) Lipinski's rule of 5 (ii) van der Waals bumps and (iii) restricting the number of rotatable bonds to seven. Final screening was carried out using FlexX based molecular docking study.

New leads for selective GSK-3 inhibition: pharmacophore mapping and virtual screening studies

NASA Astrophysics Data System (ADS)

Patel, Dhilon S.; Bharatam, Prasad V.

2006-01-01

Glycogen Synthase Kinase-3 is a regulatory serine/threonine kinase, which is being targeted for the treatment of a number of human diseases including type-2 diabetes mellitus, neurodegenerative diseases, cancer and chronic inflammation. Selective GSK-3 inhibition is an important requirement owing to the possibility of side effects arising from other kinases. A pharmacophore mapping strategy is employed in this work to identify new leads for selective GSK-3 inhibition. Ligands known to show selective GSK-3 inhibition were employed in generating a pharmacophore map using distance comparison method (DISCO). The derived pharmacophore map was validated using (i) important interactions involved in selective GSK-3 inhibitions, and (ii) an in-house database containing different classes of GSK-3 selective, non-selective and inactive molecules. New Lead identification was carried out by performing virtual screening using validated pharmacophoric query and three chemical databases namely NCI, Maybridge and Leadquest. Further data reduction was carried out by employing virtual filters based on (i) Lipinski's rule of 5 (ii) van der Waals bumps and (iii) restricting the number of rotatable bonds to seven. Final screening was carried out using FlexX based molecular docking study.

Key Principles of Superfund Remedy Selection

EPA Pesticide Factsheets

Guidance on the primary considerations of remedy selection which are universally applicable at Superfund sites. Key guidance here include: Rules of Thumb for Superfund Remedy Selection and Role of the Baseline Risk Assessment.

ECONOMIC ANALYSIS FOR THE GROUND WATER RULE ...

EPA Pesticide Factsheets

The Ground Water Rule Economic Analysis provides a description of the need for the rule, consideration of regulatory alternatives, baseline analysis including national ground water system profile and an estimate of pathogen and indicator occurrence (Chapter 4), a risk assessment and benefits analysis (Chapter 5), and a cost analysis ( Chapter 6). Chapters 4, 5 and 6, selected appendices and sections of other chapters will be peer reviewed. The objective of the Economic Analysis Document is to support the final Ground Water Rule.

A rule-based named-entity recognition method for knowledge extraction of evidence-based dietary recommendations

PubMed Central

2017-01-01

Evidence-based dietary information represented as unstructured text is a crucial information that needs to be accessed in order to help dietitians follow the new knowledge arrives daily with newly published scientific reports. Different named-entity recognition (NER) methods have been introduced previously to extract useful information from the biomedical literature. They are focused on, for example extracting gene mentions, proteins mentions, relationships between genes and proteins, chemical concepts and relationships between drugs and diseases. In this paper, we present a novel NER method, called drNER, for knowledge extraction of evidence-based dietary information. To the best of our knowledge this is the first attempt at extracting dietary concepts. DrNER is a rule-based NER that consists of two phases. The first one involves the detection and determination of the entities mention, and the second one involves the selection and extraction of the entities. We evaluate the method by using text corpora from heterogeneous sources, including text from several scientifically validated web sites and text from scientific publications. Evaluation of the method showed that drNER gives good results and can be used for knowledge extraction of evidence-based dietary recommendations. PMID:28644863

HERB: A production system for programming with hierarchical expert rule bases: User's manual, HERB Version 1. 0

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

Hummel, K.E.

1987-12-01

Expert systems are artificial intelligence programs that solve problems requiring large amounts of heuristic knowledge, based on years of experience and tradition. Production systems are domain-independent tools that support the development of rule-based expert systems. This document describes a general purpose production system known as HERB. This system was developed to support the programming of expert systems using hierarchically structured rule bases. HERB encourages the partitioning of rules into multiple rule bases and supports the use of multiple conflict resolution strategies. Multiple rule bases can also be placed on a system stack and simultaneously searched during each interpreter cycle. Bothmore » backward and forward chaining rules are supported by HERB. The condition portion of each rule can contain both patterns, which are matched with facts in a data base, and LISP expressions, which are explicitly evaluated in the LISP environment. Properties of objects can also be stored in the HERB data base and referenced within the scope of each rule. This document serves both as an introduction to the principles of LISP-based production systems and as a user's manual for the HERB system. 6 refs., 17 figs.« less

Analysis on composition rules of Chinese patent drugs treating pain-related diseases based on data mining method.

PubMed

Tang, Shi-Huan; Shen, Dan; Yang, Hong-Jun

2017-08-24

To analyze the composition rules of oral prescriptions in the treatment of headache, stomachache and dysmenorrhea recorded in National Standard for Chinese Patent Drugs (NSCPD) enacted by Ministry of Public Health of China and then make comparison between them to better understand pain treatment in different regions of human body. Constructed NSCPD database had been constructed in 2014. Prescriptions treating the three pain-related diseases were searched and screened from the database. Then data mining method such as association rules analysis and complex system entropy method integrated in the data mining software Traditional Chinese Medicine Inheritance Support System (TCMISS) were applied to process the data. Top 25 drugs with high frequency in the treatment of each disease were selected, and 51, 33 and 22 core combinations treating headache, stomachache and dysmenorrhea respectively were mined out as well. The composition rules of the oral prescriptions for treating headache, stomachache and dysmenorrhea recorded in NSCPD has been summarized. Although there were similarities between them, formula varied according to different locations of pain. It can serve as an evidence and reference for clinical treatment and new drug development.

The composite load spectra project

NASA Technical Reports Server (NTRS)

Newell, J. F.; Ho, H.; Kurth, R. E.

1990-01-01

Probabilistic methods and generic load models capable of simulating the load spectra that are induced in space propulsion system components are being developed. Four engine component types (the transfer ducts, the turbine blades, the liquid oxygen posts and the turbopump oxidizer discharge duct) were selected as representative hardware examples. The composite load spectra that simulate the probabilistic loads for these components are typically used as the input loads for a probabilistic structural analysis. The knowledge-based system approach used for the composite load spectra project provides an ideal environment for incremental development. The intelligent database paradigm employed in developing the expert system provides a smooth coupling between the numerical processing and the symbolic (information) processing. Large volumes of engine load information and engineering data are stored in database format and managed by a database management system. Numerical procedures for probabilistic load simulation and database management functions are controlled by rule modules. Rules were hard-wired as decision trees into rule modules to perform process control tasks. There are modules to retrieve load information and models. There are modules to select loads and models to carry out quick load calculations or make an input file for full duty-cycle time dependent load simulation. The composite load spectra load expert system implemented today is capable of performing intelligent rocket engine load spectra simulation. Further development of the expert system will provide tutorial capability for users to learn from it.

An investigation of care-based vs. rule-based morality in frontotemporal dementia, Alzheimer's disease, and healthy controls.

PubMed

Carr, Andrew R; Paholpak, Pongsatorn; Daianu, Madelaine; Fong, Sylvia S; Mather, Michelle; Jimenez, Elvira E; Thompson, Paul; Mendez, Mario F

2015-11-01

Behavioral changes in dementia, especially behavioral variant frontotemporal dementia (bvFTD), may result in alterations in moral reasoning. Investigators have not clarified whether these alterations reflect differential impairment of care-based vs. rule-based moral behavior. This study investigated 18 bvFTD patients, 22 early onset Alzheimer's disease (eAD) patients, and 20 healthy age-matched controls on care-based and rule-based items from the Moral Behavioral Inventory and the Social Norms Questionnaire, neuropsychological measures, and magnetic resonance imaging (MRI) regions of interest. There were significant group differences with the bvFTD patients rating care-based morality transgressions less severely than the eAD group and rule-based moral behavioral transgressions more severely than controls. Across groups, higher care-based morality ratings correlated with phonemic fluency on neuropsychological tests, whereas higher rule-based morality ratings correlated with increased difficulty set-shifting and learning new rules to tasks. On neuroimaging, severe care-based reasoning correlated with cortical volume in right anterior temporal lobe, and rule-based reasoning correlated with decreased cortical volume in the right orbitofrontal cortex. Together, these findings suggest that frontotemporal disease decreases care-based morality and facilitates rule-based morality possibly from disturbed contextual abstraction and set-shifting. Future research can examine whether frontal lobe disorders and bvFTD result in a shift from empathic morality to the strong adherence to conventional rules. Published by Elsevier Ltd.

An Investigation of Care-Based vs. Rule-Based Morality in Frontotemporal Dementia, Alzheimer’s Disease, and Healthy Controls

PubMed Central

Carr, Andrew R.; Paholpak, Pongsatorn; Daianu, Madelaine; Fong, Sylvia S.; Mather, Michelle; Jimenez, Elvira E.; Thompson, Paul; Mendez, Mario F.

2015-01-01

Behavioral changes in dementia, especially behavioral variant frontotemporal dementia (bvFTD), may result in alterations in moral reasoning. Investigators have not clarified whether these alterations reflect differential impairment of care-based vs. rule-based moral behavior. This study investigated 18 bvFTD patients, 22 early onset Alzheimer’s disease (eAD) patients, and 20 healthy age-matched controls on care-based and rule-based items from the Moral Behavioral Inventory and the Social Norms Questionnaire, neuropsychological measures, and magnetic resonance imaging (MRI) regions of interest. There were significant group differences with the bvFTD patients rating care-based morality transgressions less severely than the eAD group and rule-based moral behavioral transgressions more severely than controls. Across groups, higher care-based morality ratings correlated with phonemic fluency on neuropsychological tests, whereas higher rule-based morality ratings correlated with increased difficulty set-shifting and learning new rules to tasks. On neuroimaging, severe care-based reasoning correlated with cortical volume in right anterior temporal lobe, and rule-based reasoning correlated with decreased cortical volume in the right orbitofrontal cortex. Together, these findings suggest that frontotemporal disease decreases care-based morality and facilitates rule-based morality possibly from disturbed contextual abstraction and set-shifting. Future research can examine whether frontal lobe disorders and bvFTD result in a shift from empathic morality to the strong adherence to conventional rules. PMID:26432341

FAF-Drugs2: free ADME/tox filtering tool to assist drug discovery and chemical biology projects.

PubMed

Lagorce, David; Sperandio, Olivier; Galons, Hervé; Miteva, Maria A; Villoutreix, Bruno O

2008-09-24

Drug discovery and chemical biology are exceedingly complex and demanding enterprises. In recent years there are been increasing awareness about the importance of predicting/optimizing the absorption, distribution, metabolism, excretion and toxicity (ADMET) properties of small chemical compounds along the search process rather than at the final stages. Fast methods for evaluating ADMET properties of small molecules often involve applying a set of simple empirical rules (educated guesses) and as such, compound collections' property profiling can be performed in silico. Clearly, these rules cannot assess the full complexity of the human body but can provide valuable information and assist decision-making. This paper presents FAF-Drugs2, a free adaptable tool for ADMET filtering of electronic compound collections. FAF-Drugs2 is a command line utility program (e.g., written in Python) based on the open source chemistry toolkit OpenBabel, which performs various physicochemical calculations, identifies key functional groups, some toxic and unstable molecules/functional groups. In addition to filtered collections, FAF-Drugs2 can provide, via Gnuplot, several distribution diagrams of major physicochemical properties of the screened compound libraries. We have developed FAF-Drugs2 to facilitate compound collection preparation, prior to (or after) experimental screening or virtual screening computations. Users can select to apply various filtering thresholds and add rules as needed for a given project. As it stands, FAF-Drugs2 implements numerous filtering rules (23 physicochemical rules and 204 substructure searching rules) that can be easily tuned.

A Swarm Optimization approach for clinical knowledge mining.

PubMed

Christopher, J Jabez; Nehemiah, H Khanna; Kannan, A

2015-10-01

Rule-based classification is a typical data mining task that is being used in several medical diagnosis and decision support systems. The rules stored in the rule base have an impact on classification efficiency. Rule sets that are extracted with data mining tools and techniques are optimized using heuristic or meta-heuristic approaches in order to improve the quality of the rule base. In this work, a meta-heuristic approach called Wind-driven Swarm Optimization (WSO) is used. The uniqueness of this work lies in the biological inspiration that underlies the algorithm. WSO uses Jval, a new metric, to evaluate the efficiency of a rule-based classifier. Rules are extracted from decision trees. WSO is used to obtain different permutations and combinations of rules whereby the optimal ruleset that satisfies the requirement of the developer is used for predicting the test data. The performance of various extensions of decision trees, namely, RIPPER, PART, FURIA and Decision Tables are analyzed. The efficiency of WSO is also compared with the traditional Particle Swarm Optimization. Experiments were carried out with six benchmark medical datasets. The traditional C4.5 algorithm yields 62.89% accuracy with 43 rules for liver disorders dataset where as WSO yields 64.60% with 19 rules. For Heart disease dataset, C4.5 is 68.64% accurate with 98 rules where as WSO is 77.8% accurate with 34 rules. The normalized standard deviation for accuracy of PSO and WSO are 0.5921 and 0.5846 respectively. WSO provides accurate and concise rulesets. PSO yields results similar to that of WSO but the novelty of WSO lies in its biological motivation and it is customization for rule base optimization. The trade-off between the prediction accuracy and the size of the rule base is optimized during the design and development of rule-based clinical decision support system. The efficiency of a decision support system relies on the content of the rule base and classification accuracy. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

An Investigation and Interpretation of Selected Topics in Uncertainty Reasoning

DTIC Science & Technology

1989-12-01

Characterizing seconditry uncertainty as spurious evidence and including it in the inference process , It was shown that probability ratio graphs are a...in the inference process has great impact on the computational complexity of an Inference process . viii An Investigation and Interpretation of...Systems," he outlines a five step process that incorporates Blyeslan reasoning in the development of the expert system rule base: 1. A group of

Pilot interaction with automated airborne decision making systems

NASA Technical Reports Server (NTRS)

Rouse, W. B.; Hammer, J. M.; Morris, N. M.; Knaeuper, A. E.; Brown, E. N.; Lewis, C. M.; Yoon, W. C.

1984-01-01

Two project areas were pursued: the intelligent cockpit and human problem solving. The first area involves an investigation of the use of advanced software engineering methods to aid aircraft crews in procedure selection and execution. The second area is focused on human problem solving in dynamic environments, particulary in terms of identification of rule-based models land alternative approaches to training and aiding. Progress in each area is discussed.

Automated visualization of rule-based models

PubMed Central

Tapia, Jose-Juan; Faeder, James R.

2017-01-01

Frameworks such as BioNetGen, Kappa and Simmune use “reaction rules” to specify biochemical interactions compactly, where each rule specifies a mechanism such as binding or phosphorylation and its structural requirements. Current rule-based models of signaling pathways have tens to hundreds of rules, and these numbers are expected to increase as more molecule types and pathways are added. Visual representations are critical for conveying rule-based models, but current approaches to show rules and interactions between rules scale poorly with model size. Also, inferring design motifs that emerge from biochemical interactions is an open problem, so current approaches to visualize model architecture rely on manual interpretation of the model. Here, we present three new visualization tools that constitute an automated visualization framework for rule-based models: (i) a compact rule visualization that efficiently displays each rule, (ii) the atom-rule graph that conveys regulatory interactions in the model as a bipartite network, and (iii) a tunable compression pipeline that incorporates expert knowledge and produces compact diagrams of model architecture when applied to the atom-rule graph. The compressed graphs convey network motifs and architectural features useful for understanding both small and large rule-based models, as we show by application to specific examples. Our tools also produce more readable diagrams than current approaches, as we show by comparing visualizations of 27 published models using standard graph metrics. We provide an implementation in the open source and freely available BioNetGen framework, but the underlying methods are general and can be applied to rule-based models from the Kappa and Simmune frameworks also. We expect that these tools will promote communication and analysis of rule-based models and their eventual integration into comprehensive whole-cell models. PMID:29131816

Compartmental and Spatial Rule-Based Modeling with Virtual Cell.

PubMed

Blinov, Michael L; Schaff, James C; Vasilescu, Dan; Moraru, Ion I; Bloom, Judy E; Loew, Leslie M

2017-10-03

In rule-based modeling, molecular interactions are systematically specified in the form of reaction rules that serve as generators of reactions. This provides a way to account for all the potential molecular complexes and interactions among multivalent or multistate molecules. Recently, we introduced rule-based modeling into the Virtual Cell (VCell) modeling framework, permitting graphical specification of rules and merger of networks generated automatically (using the BioNetGen modeling engine) with hand-specified reaction networks. VCell provides a number of ordinary differential equation and stochastic numerical solvers for single-compartment simulations of the kinetic systems derived from these networks, and agent-based network-free simulation of the rules. In this work, compartmental and spatial modeling of rule-based models has been implemented within VCell. To enable rule-based deterministic and stochastic spatial simulations and network-free agent-based compartmental simulations, the BioNetGen and NFSim engines were each modified to support compartments. In the new rule-based formalism, every reactant and product pattern and every reaction rule are assigned locations. We also introduce the rule-based concept of molecular anchors. This assures that any species that has a molecule anchored to a predefined compartment will remain in this compartment. Importantly, in addition to formulation of compartmental models, this now permits VCell users to seamlessly connect reaction networks derived from rules to explicit geometries to automatically generate a system of reaction-diffusion equations. These may then be simulated using either the VCell partial differential equations deterministic solvers or the Smoldyn stochastic simulator. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Revised Interim Final Consolidated Enforcement Response and Penalty Policy for the Pre-Renovation Education Rule; Renovation, Repair and Painting Rule; and Lead-Based Paint Activities Rule

EPA Pesticide Factsheets

This is the revised version of the Interim Final Consolidated Enforcement Response and Penalty Policy for the Pre-Renovation Education Rule; Renovation, Repair and Painting Rule; and Lead-Based Paint Activities Rule.

Patterns of sexual size dimorphism in horseshoe bats: Testing Rensch's rule and potential causes.

PubMed

Wu, Hui; Jiang, Tinglei; Huang, Xiaobin; Feng, Jiang

2018-02-08

Rensch's rule, stating that sexual size dimorphism (SSD) becomes more evident and male-biased with increasing body size, has been well supported for taxa that exhibit male-biased SSD. Bats, primarily having female-biased SSD, have so far been tested for whether SSD allometry conforms to Rensch's rule in only three studies. However, these studies did not consider phylogeny, and thus the mechanisms underlying SSD variations in bats remain unclear. Thus, the present study reviewed published and original data, including body size, baculum size, and habitat types in 45 bats of the family Rhinolophidae to determine whether horseshoe bats follow Rensch's rule using a phylogenetic comparative framework. We also investigated the potential effect of postcopulatory sexual selection and habitat type on SSD. Our findings indicated that Rensch's rule did not apply to Rhinolophidae, suggesting that SSD did not significantly vary with increasing size. This pattern may be attributable interactions between weak sexual selection to male body size and strong fecundity selection for on female body size. The degree of SSD among horseshoe bats may be attributed to a phylogenetic effect rather than to the intersexual competition for food or to baculum length. Interestingly, we observed that species in open habitats exhibited greater SSD than those in dense forests, suggesting that habitat types may be associated with variations in SSD in horseshoe bats.

Sideline Coverage

PubMed Central

Gould, Sara J.; Cardone, Dennis A.; Munyak, John; Underwood, Philipp J.; Gould, Stephen A.

2014-01-01

Context: Sidelines coverage presents unique challenges in the evaluation of injured athletes. Health care providers may be confronted with the question of when to obtain radiographs following an injury. Given that most sidelines coverage occurs outside the elite level, radiographs are not readily available at the time of injury, and the decision of when to send a player for radiographs must be made based on physical examination. Clinical tools have been developed to aid in identifying injuries that are likely to result in radiographically important fractures or dislocations. Evidence Acquisition: A search for the keywords x-ray and decision rule along with the anatomic locations shoulder, elbow, wrist, knee, and ankle was performed using the PubMed database. No limits were set regarding year of publication. We selected meta-analyses, randomized controlled trials, and survey results. Our selection focused on the largest, most well-studied published reports. We also attempted to include studies that reported the application of the rules to the field of sports medicine. Study Design: Retrospective literature review. Level of Evidence: Level 4. Results: The Ottawa Foot and Ankle Rules have been validated and implemented and are appropriate for use in both pediatric and adult populations. The Ottawa Knee Rules have been widely studied, validated, and accepted for evaluation of knee injuries. There are promising studies of decision rules for clinically important fractures of the wrist, but these studies have not been validated. The elbow has been evaluated with good outcomes via the elbow extension test, which has been validated in both single and multicenter studies. Currently, there are no reliable clinical decision tools for traumatic sports injuries to the shoulder to aid in the decision of when to obtain radiographs. Conclusion: Clinical decision tools have been developed to aid in the diagnosis and management of injuries commonly sustained during sporting events. Tools that have been appropriately validated in populations outside the initial study population can assist sports medicine physicians in the decision of when to get radiographs from the sidelines. PMID:24790698

Sideline coverage: when to get radiographs? A review of clinical decision tools.

PubMed

Gould, Sara J; Cardone, Dennis A; Munyak, John; Underwood, Philipp J; Gould, Stephen A

2014-05-01

Sidelines coverage presents unique challenges in the evaluation of injured athletes. Health care providers may be confronted with the question of when to obtain radiographs following an injury. Given that most sidelines coverage occurs outside the elite level, radiographs are not readily available at the time of injury, and the decision of when to send a player for radiographs must be made based on physical examination. Clinical tools have been developed to aid in identifying injuries that are likely to result in radiographically important fractures or dislocations. A search for the keywords x-ray and decision rule along with the anatomic locations shoulder, elbow, wrist, knee, and ankle was performed using the PubMed database. No limits were set regarding year of publication. We selected meta-analyses, randomized controlled trials, and survey results. Our selection focused on the largest, most well-studied published reports. We also attempted to include studies that reported the application of the rules to the field of sports medicine. Retrospective literature review. Level 4. The Ottawa Foot and Ankle Rules have been validated and implemented and are appropriate for use in both pediatric and adult populations. The Ottawa Knee Rules have been widely studied, validated, and accepted for evaluation of knee injuries. There are promising studies of decision rules for clinically important fractures of the wrist, but these studies have not been validated. The elbow has been evaluated with good outcomes via the elbow extension test, which has been validated in both single and multicenter studies. Currently, there are no reliable clinical decision tools for traumatic sports injuries to the shoulder to aid in the decision of when to obtain radiographs. Clinical decision tools have been developed to aid in the diagnosis and management of injuries commonly sustained during sporting events. Tools that have been appropriately validated in populations outside the initial study population can assist sports medicine physicians in the decision of when to get radiographs from the sidelines.

Clinical Decision Support Tools for Selecting Interventions for Patients with Disabling Musculoskeletal Disorders: A Scoping Review.

PubMed

Gross, Douglas P; Armijo-Olivo, Susan; Shaw, William S; Williams-Whitt, Kelly; Shaw, Nicola T; Hartvigsen, Jan; Qin, Ziling; Ha, Christine; Woodhouse, Linda J; Steenstra, Ivan A

2016-09-01

Purpose We aimed to identify and inventory clinical decision support (CDS) tools for helping front-line staff select interventions for patients with musculoskeletal (MSK) disorders. Methods We used Arksey and O'Malley's scoping review framework which progresses through five stages: (1) identifying the research question; (2) identifying relevant studies; (3) selecting studies for analysis; (4) charting the data; and (5) collating, summarizing and reporting results. We considered computer-based, and other available tools, such as algorithms, care pathways, rules and models. Since this research crosses multiple disciplines, we searched health care, computing science and business databases. Results Our search resulted in 4605 manuscripts. Titles and abstracts were screened for relevance. The reliability of the screening process was high with an average percentage of agreement of 92.3 %. Of the located articles, 123 were considered relevant. Within this literature, there were 43 CDS tools located. These were classified into 3 main areas: computer-based tools/questionnaires (n = 8, 19 %), treatment algorithms/models (n = 14, 33 %), and clinical prediction rules/classification systems (n = 21, 49 %). Each of these areas and the associated evidence are described. The state of evidentiary support for CDS tools is still preliminary and lacks external validation, head-to-head comparisons, or evidence of generalizability across different populations and settings. Conclusions CDS tools, especially those employing rapidly advancing computer technologies, are under development and of potential interest to health care providers, case management organizations and funders of care. Based on the results of this scoping review, we conclude that these tools, models and systems should be subjected to further validation before they can be recommended for large-scale implementation for managing patients with MSK disorders.

A graphical, rule based robotic interface system

NASA Technical Reports Server (NTRS)

Mckee, James W.; Wolfsberger, John

1988-01-01

The ability of a human to take control of a robotic system is essential in any use of robots in space in order to handle unforeseen changes in the robot's work environment or scheduled tasks. But in cases in which the work environment is known, a human controlling a robot's every move by remote control is both time consuming and frustrating. A system is needed in which the user can give the robotic system commands to perform tasks but need not tell the system how. To be useful, this system should be able to plan and perform the tasks faster than a telerobotic system. The interface between the user and the robot system must be natural and meaningful to the user. A high level user interface program under development at the University of Alabama, Huntsville, is described. A graphical interface is proposed in which the user selects objects to be manipulated by selecting representations of the object on projections of a 3-D model of the work environment. The user may move in the work environment by changing the viewpoint of the projections. The interface uses a rule based program to transform user selection of items on a graphics display of the robot's work environment into commands for the robot. The program first determines if the desired task is possible given the abilities of the robot and any constraints on the object. If the task is possible, the program determines what movements the robot needs to make to perform the task. The movements are transformed into commands for the robot. The information defining the robot, the work environment, and how objects may be moved is stored in a set of data bases accessible to the program and displayable to the user.

Rules based process window OPC

NASA Astrophysics Data System (ADS)

O'Brien, Sean; Soper, Robert; Best, Shane; Mason, Mark

2008-03-01

As a preliminary step towards Model-Based Process Window OPC we have analyzed the impact of correcting post-OPC layouts using rules based methods. Image processing on the Brion Tachyon was used to identify sites where the OPC model/recipe failed to generate an acceptable solution. A set of rules for 65nm active and poly were generated by classifying these failure sites. The rules were based upon segment runlengths, figure spaces, and adjacent figure widths. 2.1 million sites for active were corrected in a small chip (comparing the pre and post rules based operations), and 59 million were found at poly. Tachyon analysis of the final reticle layout found weak margin sites distinct from those sites repaired by rules-based corrections. For the active layer more than 75% of the sites corrected by rules would have printed without a defect indicating that most rulesbased cleanups degrade the lithographic pattern. Some sites were missed by the rules based cleanups due to either bugs in the DRC software or gaps in the rules table. In the end dramatic changes to the reticle prevented catastrophic lithography errors, but this method is far too blunt. A more subtle model-based procedure is needed changing only those sites which have unsatisfactory lithographic margin.

A Decision Support System for Evaluating and Selecting Information Systems Projects

NASA Astrophysics Data System (ADS)

Deng, Hepu; Wibowo, Santoso

2009-01-01

This chapter presents a decision support system (DSS) for effectively solving the information systems (IS) project selection problem. The proposed DSS recognizes the multidimensional nature of the IS project selection problem, the availability of multicriteria analysis (MA) methods, and the preferences of the decision-maker (DM) on the use of specific MA methods in a given situation. A knowledge base consisting of IF-THEN production rules is developed for assisting the DM with a systematic adoption of the most appropriate method with the efficient use of the powerful reasoning and explanation capabilities of intelligent DSS. The idea of letting the problem to be solved determines the method to be used is incorporated into the proposed DSS. As a result, effective decisions can be made for solving the IS project selection problem. An example is presented to demonstrate the applicability of the proposed DSS for solving the problem of selecting IS projects in real world situations.

Region Based CNN for Foreign Object Debris Detection on Airfield Pavement

PubMed Central

Cao, Xiaoguang; Wang, Peng; Meng, Cai; Gong, Guoping; Liu, Miaoming; Qi, Jun

2018-01-01

In this paper, a novel algorithm based on convolutional neural network (CNN) is proposed to detect foreign object debris (FOD) based on optical imaging sensors. It contains two modules, the improved region proposal network (RPN) and spatial transformer network (STN) based CNN classifier. In the improved RPN, some extra select rules are designed and deployed to generate high quality candidates with fewer numbers. Moreover, the efficiency of CNN detector is significantly improved by introducing STN layer. Compared to faster R-CNN and single shot multiBox detector (SSD), the proposed algorithm achieves better result for FOD detection on airfield pavement in the experiment. PMID:29494524

Region Based CNN for Foreign Object Debris Detection on Airfield Pavement.

PubMed

Cao, Xiaoguang; Wang, Peng; Meng, Cai; Bai, Xiangzhi; Gong, Guoping; Liu, Miaoming; Qi, Jun

2018-03-01

In this paper, a novel algorithm based on convolutional neural network (CNN) is proposed to detect foreign object debris (FOD) based on optical imaging sensors. It contains two modules, the improved region proposal network (RPN) and spatial transformer network (STN) based CNN classifier. In the improved RPN, some extra select rules are designed and deployed to generate high quality candidates with fewer numbers. Moreover, the efficiency of CNN detector is significantly improved by introducing STN layer. Compared to faster R-CNN and single shot multiBox detector (SSD), the proposed algorithm achieves better result for FOD detection on airfield pavement in the experiment.

Evaluation of alternative model selection criteria in the analysis of unimodal response curves using CART

USGS Publications Warehouse

Ribic, C.A.; Miller, T.W.

1998-01-01

We investigated CART performance with a unimodal response curve for one continuous response and four continuous explanatory variables, where two variables were important (ie directly related to the response) and the other two were not. We explored performance under three relationship strengths and two explanatory variable conditions: equal importance and one variable four times as important as the other. We compared CART variable selection performance using three tree-selection rules ('minimum risk', 'minimum risk complexity', 'one standard error') to stepwise polynomial ordinary least squares (OLS) under four sample size conditions. The one-standard-error and minimum-risk-complexity methods performed about as well as stepwise OLS with large sample sizes when the relationship was strong. With weaker relationships, equally important explanatory variables and larger sample sizes, the one-standard-error and minimum-risk-complexity rules performed better than stepwise OLS. With weaker relationships and explanatory variables of unequal importance, tree-structured methods did not perform as well as stepwise OLS. Comparing performance within tree-structured methods, with a strong relationship and equally important explanatory variables, the one-standard-error-rule was more likely to choose the correct model than were the other tree-selection rules 1) with weaker relationships and equally important explanatory variables; and 2) under all relationship strengths when explanatory variables were of unequal importance and sample sizes were lower.

Quantitative genetic versions of Hamilton's rule with empirical applications

PubMed Central

McGlothlin, Joel W.; Wolf, Jason B.; Brodie, Edmund D.; Moore, Allen J.

2014-01-01

Hamilton's theory of inclusive fitness revolutionized our understanding of the evolution of social interactions. Surprisingly, an incorporation of Hamilton's perspective into the quantitative genetic theory of phenotypic evolution has been slow, despite the popularity of quantitative genetics in evolutionary studies. Here, we discuss several versions of Hamilton's rule for social evolution from a quantitative genetic perspective, emphasizing its utility in empirical applications. Although evolutionary quantitative genetics offers methods to measure each of the critical parameters of Hamilton's rule, empirical work has lagged behind theory. In particular, we lack studies of selection on altruistic traits in the wild. Fitness costs and benefits of altruism can be estimated using a simple extension of phenotypic selection analysis that incorporates the traits of social interactants. We also discuss the importance of considering the genetic influence of the social environment, or indirect genetic effects (IGEs), in the context of Hamilton's rule. Research in social evolution has generated an extensive body of empirical work focusing—with good reason—almost solely on relatedness. We argue that quantifying the roles of social and non-social components of selection and IGEs, in addition to relatedness, is now timely and should provide unique additional insights into social evolution. PMID:24686930

Long-range prediction of Indian summer monsoon rainfall using data mining and statistical approaches

NASA Astrophysics Data System (ADS)

H, Vathsala; Koolagudi, Shashidhar G.

2017-10-01

This paper presents a hybrid model to better predict Indian summer monsoon rainfall. The algorithm considers suitable techniques for processing dense datasets. The proposed three-step algorithm comprises closed itemset generation-based association rule mining for feature selection, cluster membership for dimensionality reduction, and simple logistic function for prediction. The application of predicting rainfall into flood, excess, normal, deficit, and drought based on 36 predictors consisting of land and ocean variables is presented. Results show good accuracy in the considered study period of 37years (1969-2005).

A knowledge-based approach to improving optimization techniques in system planning

NASA Technical Reports Server (NTRS)

Momoh, J. A.; Zhang, Z. Z.

1990-01-01

A knowledge-based (KB) approach to improve mathematical programming techniques used in the system planning environment is presented. The KB system assists in selecting appropriate optimization algorithms, objective functions, constraints and parameters. The scheme is implemented by integrating symbolic computation of rules derived from operator and planner's experience and is used for generalized optimization packages. The KB optimization software package is capable of improving the overall planning process which includes correction of given violations. The method was demonstrated on a large scale power system discussed in the paper.

Diagnosis and treatment of dementia: 2. Diagnosis

PubMed Central

Feldman, Howard H.; Jacova, Claudia; Robillard, Alain; Garcia, Angeles; Chow, Tiffany; Borrie, Michael; Schipper, Hyman M.; Blair, Mervin; Kertesz, Andrew; Chertkow, Howard

2008-01-01

Background Dementia can now be accurately diagnosed through clinical evaluation, cognitive screening, basic laboratory evaluation and structural imaging. A large number of ancillary techniques are also available to aid in diagnosis, but their role in the armamentarium of family physicians remains controversial. In this article, we provide physicians with practical guidance on the diagnosis of dementia based on recommendations from the Third Canadian Consensus Conference on the Diagnosis and Treatment of Dementia, held in March 2006. Methods We developed evidence-based guidelines using systematic literature searches, with specific criteria for study selection and quality assessment, and a clear and transparent decision-making process. We selected studies published from January 1996 to December 2005 that pertained to key diagnostic issues in dementia. We graded the strength of evidence using the criteria of the Canadian Task Force on Preventive Health Care. Results Of the 1591 articles we identified on all aspects of dementia diagnosis, 1095 met our inclusion criteria; 620 were deemed to be of good or fair quality. From a synthesis of the evidence in these studies, we made 32 recommendations related to the diagnosis of dementia. There are clinical criteria for diagnosing most forms of dementia. A standard diagnostic evaluation can be performd by family physicians over multiple visits. It involves a clinical history (from patient and caregiver), a physical examination and brief cognitive testing. A list of core laboratory tests is recommended. Structural imaging with computed tomography or magnetic resonance imaging is recommended in selected cases to rule out treatable causes of dementia or to rule in cerebrovascular disease. There is insufficient evidence to recommend routine functional imaging, measurement of biomarkers or neuropsychologic testing. Interpretation The diagnosis of dementia remains clinically integrative based on history, physical examination and brief cognitive testing. A number of core laboratory tests are also recommended. Structural neuroimaging is advised in selected cases. Other diagnostic approaches, including functional neuroimaging, neuropsychological testing and measurement of biomarkers, have shown promise but are not yet recommended for routine use by family physicians. PMID:18362376

Estimation of Handgrip Force from SEMG Based on Wavelet Scale Selection.

PubMed

Wang, Kai; Zhang, Xianmin; Ota, Jun; Huang, Yanjiang

2018-02-24

This paper proposes a nonlinear correlation-based wavelet scale selection technology to select the effective wavelet scales for the estimation of handgrip force from surface electromyograms (SEMG). The SEMG signal corresponding to gripping force was collected from extensor and flexor forearm muscles during the force-varying analysis task. We performed a computational sensitivity analysis on the initial nonlinear SEMG-handgrip force model. To explore the nonlinear correlation between ten wavelet scales and handgrip force, a large-scale iteration based on the Monte Carlo simulation was conducted. To choose a suitable combination of scales, we proposed a rule to combine wavelet scales based on the sensitivity of each scale and selected the appropriate combination of wavelet scales based on sequence combination analysis (SCA). The results of SCA indicated that the scale combination VI is suitable for estimating force from the extensors and the combination V is suitable for the flexors. The proposed method was compared to two former methods through prolonged static and force-varying contraction tasks. The experiment results showed that the root mean square errors derived by the proposed method for both static and force-varying contraction tasks were less than 20%. The accuracy and robustness of the handgrip force derived by the proposed method is better than that obtained by the former methods.

Multiagent optimization system for solving the traveling salesman problem (TSP).

PubMed

Xie, Xiao-Feng; Liu, Jiming

2009-04-01

The multiagent optimization system (MAOS) is a nature-inspired method, which supports cooperative search by the self-organization of a group of compact agents situated in an environment with certain sharing public knowledge. Moreover, each agent in MAOS is an autonomous entity with personal declarative memory and behavioral components. In this paper, MAOS is refined for solving the traveling salesman problem (TSP), which is a classic hard computational problem. Based on a simplified MAOS version, in which each agent manipulates on extremely limited declarative knowledge, some simple and efficient components for solving TSP, including two improving heuristics based on a generalized edge assembly recombination, are implemented. Compared with metaheuristics in adaptive memory programming, MAOS is particularly suitable for supporting cooperative search. The experimental results on two TSP benchmark data sets show that MAOS is competitive as compared with some state-of-the-art algorithms, including the Lin-Kernighan-Helsgaun, IBGLK, PHGA, etc., although MAOS does not use any explicit local search during the runtime. The contributions of MAOS components are investigated. It indicates that certain clues can be positive for making suitable selections before time-consuming computation. More importantly, it shows that the cooperative search of agents can achieve an overall good performance with a macro rule in the switch mode, which deploys certain alternate search rules with the offline performance in negative correlations. Using simple alternate rules may prevent the high difficulty of seeking an omnipotent rule that is efficient for a large data set.

Classification Based on Pruning and Double Covered Rule Sets for the Internet of Things Applications

PubMed Central

Zhou, Zhongmei; Wang, Weiping

2014-01-01

The Internet of things (IOT) is a hot issue in recent years. It accumulates large amounts of data by IOT users, which is a great challenge to mining useful knowledge from IOT. Classification is an effective strategy which can predict the need of users in IOT. However, many traditional rule-based classifiers cannot guarantee that all instances can be covered by at least two classification rules. Thus, these algorithms cannot achieve high accuracy in some datasets. In this paper, we propose a new rule-based classification, CDCR-P (Classification based on the Pruning and Double Covered Rule sets). CDCR-P can induce two different rule sets A and B. Every instance in training set can be covered by at least one rule not only in rule set A, but also in rule set B. In order to improve the quality of rule set B, we take measure to prune the length of rules in rule set B. Our experimental results indicate that, CDCR-P not only is feasible, but also it can achieve high accuracy. PMID:24511304

Classification based on pruning and double covered rule sets for the internet of things applications.

PubMed

Li, Shasha; Zhou, Zhongmei; Wang, Weiping

2014-01-01

The Internet of things (IOT) is a hot issue in recent years. It accumulates large amounts of data by IOT users, which is a great challenge to mining useful knowledge from IOT. Classification is an effective strategy which can predict the need of users in IOT. However, many traditional rule-based classifiers cannot guarantee that all instances can be covered by at least two classification rules. Thus, these algorithms cannot achieve high accuracy in some datasets. In this paper, we propose a new rule-based classification, CDCR-P (Classification based on the Pruning and Double Covered Rule sets). CDCR-P can induce two different rule sets A and B. Every instance in training set can be covered by at least one rule not only in rule set A, but also in rule set B. In order to improve the quality of rule set B, we take measure to prune the length of rules in rule set B. Our experimental results indicate that, CDCR-P not only is feasible, but also it can achieve high accuracy.

The cost-effectiveness of diagnostic management strategies for adults with minor head injury.

PubMed

Holmes, M W; Goodacre, S; Stevenson, M D; Pandor, A; Pickering, A

2012-09-01

To estimate the cost-effectiveness of diagnostic management strategies for adults with minor head injury. A mathematical model was constructed to evaluate the incremental costs and effectiveness (Quality Adjusted Life years Gained, QALYs) of ten diagnostic management strategies for adults with minor head injuries. Secondary analyses were undertaken to determine the cost-effectiveness of hospital admission compared to discharge home and to explore the cost-effectiveness of strategies when no responsible adult was available to observe the patient after discharge. The apparent optimal strategy was based on the high and medium risk Canadian CT Head Rule (CCHRhm), although the costs and outcomes associated with each strategy were broadly similar. Hospital admission for patients with non-neurosurgical injury on CT dominated discharge home, whilst hospital admission for clinically normal patients with a normal CT was not cost-effective compared to discharge home with or without a responsible adult at £39 and £2.5 million per QALY, respectively. A selective CT strategy with discharge home if the CT scan was normal remained optimal compared to not investigating or CT scanning all patients when there was no responsible adult available to observe them after discharge. Our economic analysis confirms that the recent extension of access to CT scanning for minor head injury is appropriate. Liberal use of CT scanning based on a high sensitivity decision rule is not only effective but also cost-saving. The cost of CT scanning is very small compared to the estimated cost of caring for patients with brain injury worsened by delayed treatment. It is recommended therefore that all hospitals receiving patients with minor head injury should have unrestricted access to CT scanning for use in conjunction with evidence based guidelines. Provisionally the CCHRhm decision rule appears to be the best strategy although there is considerable uncertainty around the optimal decision rule. However, the CCHRhm rule appears to be the most widely validated and it therefore seems appropriate to conclude that the CCHRhm rule has the best evidence to support its use. Copyright © 2011 Elsevier Ltd. All rights reserved.

A simple rule for the evolution of cooperation on graphs and social networks.

PubMed

Ohtsuki, Hisashi; Hauert, Christoph; Lieberman, Erez; Nowak, Martin A

2006-05-25

A fundamental aspect of all biological systems is cooperation. Cooperative interactions are required for many levels of biological organization ranging from single cells to groups of animals. Human society is based to a large extent on mechanisms that promote cooperation. It is well known that in unstructured populations, natural selection favours defectors over cooperators. There is much current interest, however, in studying evolutionary games in structured populations and on graphs. These efforts recognize the fact that who-meets-whom is not random, but determined by spatial relationships or social networks. Here we describe a surprisingly simple rule that is a good approximation for all graphs that we have analysed, including cycles, spatial lattices, random regular graphs, random graphs and scale-free networks: natural selection favours cooperation, if the benefit of the altruistic act, b, divided by the cost, c, exceeds the average number of neighbours, k, which means b/c > k. In this case, cooperation can evolve as a consequence of 'social viscosity' even in the absence of reputation effects or strategic complexity.

A Modified Monte Carlo Method for Carrier Transport in Germanium, Free of Isotropic Rates

NASA Astrophysics Data System (ADS)

Sundqvist, Kyle

2010-03-01

We present a new method for carrier transport simulation, relevant for high-purity germanium < 100 > at a temperature of 40 mK. In this system, the scattering of electrons and holes is dominated by spontaneous phonon emission. Free carriers are always out of equilibrium with the lattice. We must also properly account for directional effects due to band structure, but there are many cautions in the literature about treating germanium in particular. These objections arise because the germanium electron system is anisotropic to an extreme degree, while standard Monte Carlo algorithms maintain a reliance on isotropic, integrated rates. We re-examine Fermi's Golden Rule to produce a Monte Carlo method free of isotropic rates. Traditional Monte Carlo codes implement particle scattering based on an isotropically averaged rate, followed by a separate selection of the particle's final state via a momentum-dependent probability. In our method, the kernel of Fermi's Golden Rule produces analytical, bivariate rates which allow for the simultaneous choice of scatter and final state selection. Energy and momentum are automatically conserved. We compare our results to experimental data.

A Bayesian Theory of Sequential Causal Learning and Abstract Transfer.

PubMed

Lu, Hongjing; Rojas, Randall R; Beckers, Tom; Yuille, Alan L

2016-03-01

Two key research issues in the field of causal learning are how people acquire causal knowledge when observing data that are presented sequentially, and the level of abstraction at which learning takes place. Does sequential causal learning solely involve the acquisition of specific cause-effect links, or do learners also acquire knowledge about abstract causal constraints? Recent empirical studies have revealed that experience with one set of causal cues can dramatically alter subsequent learning and performance with entirely different cues, suggesting that learning involves abstract transfer, and such transfer effects involve sequential presentation of distinct sets of causal cues. It has been demonstrated that pre-training (or even post-training) can modulate classic causal learning phenomena such as forward and backward blocking. To account for these effects, we propose a Bayesian theory of sequential causal learning. The theory assumes that humans are able to consider and use several alternative causal generative models, each instantiating a different causal integration rule. Model selection is used to decide which integration rule to use in a given learning environment in order to infer causal knowledge from sequential data. Detailed computer simulations demonstrate that humans rely on the abstract characteristics of outcome variables (e.g., binary vs. continuous) to select a causal integration rule, which in turn alters causal learning in a variety of blocking and overshadowing paradigms. When the nature of the outcome variable is ambiguous, humans select the model that yields the best fit with the recent environment, and then apply it to subsequent learning tasks. Based on sequential patterns of cue-outcome co-occurrence, the theory can account for a range of phenomena in sequential causal learning, including various blocking effects, primacy effects in some experimental conditions, and apparently abstract transfer of causal knowledge. Copyright © 2015 Cognitive Science Society, Inc.

Rules and Regulations: Minimum Schoolhouse Construction Standards.

ERIC Educational Resources Information Center

Arkansas State Dept. of Education, Little Rock.

Regulatory guidelines governing the minimum schoolhouse construction standards as well as rules for new construction applications, school site selection, and approval procedures are presented. Appendices (comprising 95 percent of the publication) document the following: educational space guidelines; planning for modern education; school…

Rule groupings: A software engineering approach towards verification of expert systems

NASA Technical Reports Server (NTRS)

Mehrotra, Mala

1991-01-01

Currently, most expert system shells do not address software engineering issues for developing or maintaining expert systems. As a result, large expert systems tend to be incomprehensible, difficult to debug or modify and almost impossible to verify or validate. Partitioning rule based systems into rule groups which reflect the underlying subdomains of the problem should enhance the comprehensibility, maintainability, and reliability of expert system software. Attempts were made to semiautomatically structure a CLIPS rule base into groups of related rules that carry the same type of information. Different distance metrics that capture relevant information from the rules for grouping are discussed. Two clustering algorithms that partition the rule base into groups of related rules are given. Two independent evaluation criteria are developed to measure the effectiveness of the grouping strategies. Results of the experiment with three sample rule bases are presented.

Role of Utility and Inference in the Evolution of Functional Information

PubMed Central

Sharov, Alexei A.

2009-01-01

Functional information means an encoded network of functions in living organisms from molecular signaling pathways to an organism’s behavior. It is represented by two components: code and an interpretation system, which together form a self-sustaining semantic closure. Semantic closure allows some freedom between components because small variations of the code are still interpretable. The interpretation system consists of inference rules that control the correspondence between the code and the function (phenotype) and determines the shape of the fitness landscape. The utility factor operates at multiple time scales: short-term selection drives evolution towards higher survival and reproduction rate within a given fitness landscape, and long-term selection favors those fitness landscapes that support adaptability and lead to evolutionary expansion of certain lineages. Inference rules make short-term selection possible by shaping the fitness landscape and defining possible directions of evolution, but they are under control of the long-term selection of lineages. Communication normally occurs within a set of agents with compatible interpretation systems, which I call communication system. Functional information cannot be directly transferred between communication systems with incompatible inference rules. Each biological species is a genetic communication system that carries unique functional information together with inference rules that determine evolutionary directions and constraints. This view of the relation between utility and inference can resolve the conflict between realism/positivism and pragmatism. Realism overemphasizes the role of inference in evolution of human knowledge because it assumes that logic is embedded in reality. Pragmatism substitutes usefulness for truth and therefore ignores the advantage of inference. The proposed concept of evolutionary pragmatism rejects the idea that logic is embedded in reality; instead, inference rules are constructed within each communication system to represent reality and they evolve towards higher adaptability on a long time scale. PMID:20160960

A novel artificial immune clonal selection classification and rule mining with swarm learning model

NASA Astrophysics Data System (ADS)

Al-Sheshtawi, Khaled A.; Abdul-Kader, Hatem M.; Elsisi, Ashraf B.

2013-06-01

Metaheuristic optimisation algorithms have become popular choice for solving complex problems. By integrating Artificial Immune clonal selection algorithm (CSA) and particle swarm optimisation (PSO) algorithm, a novel hybrid Clonal Selection Classification and Rule Mining with Swarm Learning Algorithm (CS2) is proposed. The main goal of the approach is to exploit and explore the parallel computation merit of Clonal Selection and the speed and self-organisation merits of Particle Swarm by sharing information between clonal selection population and particle swarm. Hence, we employed the advantages of PSO to improve the mutation mechanism of the artificial immune CSA and to mine classification rules within datasets. Consequently, our proposed algorithm required less training time and memory cells in comparison to other AIS algorithms. In this paper, classification rule mining has been modelled as a miltiobjective optimisation problem with predictive accuracy. The multiobjective approach is intended to allow the PSO algorithm to return an approximation to the accuracy and comprehensibility border, containing solutions that are spread across the border. We compared our proposed algorithm classification accuracy CS2 with five commonly used CSAs, namely: AIRS1, AIRS2, AIRS-Parallel, CLONALG, and CSCA using eight benchmark datasets. We also compared our proposed algorithm classification accuracy CS2 with other five methods, namely: Naïve Bayes, SVM, MLP, CART, and RFB. The results show that the proposed algorithm is comparable to the 10 studied algorithms. As a result, the hybridisation, built of CSA and PSO, can develop respective merit, compensate opponent defect, and make search-optimal effect and speed better.

An evaluation and implementation of rule-based Home Energy Management System using the Rete algorithm.

PubMed

Kawakami, Tomoya; Fujita, Naotaka; Yoshihisa, Tomoki; Tsukamoto, Masahiko

2014-01-01

In recent years, sensors become popular and Home Energy Management System (HEMS) takes an important role in saving energy without decrease in QoL (Quality of Life). Currently, many rule-based HEMSs have been proposed and almost all of them assume "IF-THEN" rules. The Rete algorithm is a typical pattern matching algorithm for IF-THEN rules. Currently, we have proposed a rule-based Home Energy Management System (HEMS) using the Rete algorithm. In the proposed system, rules for managing energy are processed by smart taps in network, and the loads for processing rules and collecting data are distributed to smart taps. In addition, the number of processes and collecting data are reduced by processing rules based on the Rete algorithm. In this paper, we evaluated the proposed system by simulation. In the simulation environment, rules are processed by a smart tap that relates to the action part of each rule. In addition, we implemented the proposed system as HEMS using smart taps.

A real-time expert system for self-repairing flight control

NASA Technical Reports Server (NTRS)

Gaither, S. A.; Agarwal, A. K.; Shah, S. C.; Duke, E. L.

1989-01-01

An integrated environment for specifying, prototyping, and implementing a self-repairing flight-control (SRFC) strategy is described. At an interactive workstation, the user can select paradigms such as rule-based expert systems, state-transition diagrams, and signal-flow graphs and hierarchically nest them, assign timing and priority attributes, establish blackboard-type communication, and specify concurrent execution on single or multiple processors. High-fidelity nonlinear simulations of aircraft and SRFC systems can be performed off-line, with the possibility of changing SRFC rules, inference strategies, and other heuristics to correct for control deficiencies. Finally, the off-line-generated SRFC can be transformed into highly optimized application-specific real-time C-language code. An application of this environment to the design of aircraft fault detection, isolation, and accommodation algorithms is presented in detail.

The Time Course of Explicit and Implicit Categorization

PubMed Central

Zakrzewski, Alexandria C.; Herberger, Eric; Boomer, Joseph; Roeder, Jessica; Ashby, F. Gregory; Church, Barbara A.

2015-01-01

Contemporary theory in cognitive neuroscience distinguishes, among the processes and utilities that serve categorization, explicit and implicit systems of category learning that learn, respectively, category rules by active hypothesis testing or adaptive behaviors by association and reinforcement. Little is known about the time course of categorization within these systems. Accordingly, the present experiments contrasted tasks that fostered explicit categorization (because they had a one-dimensional, rule-based solution) or implicit categorization (because they had a two-dimensional, information-integration solution). In Experiment 1, participants learned categories under unspeeded or speeded conditions. In Experiment 2, they applied previously trained category knowledge under unspeeded or speeded conditions. Speeded conditions selectively impaired implicit category learning and implicit mature categorization. These results illuminate the processing dynamics of explicit/implicit categorization. PMID:26025556

System for selecting relevant information for decision support.

PubMed

Kalina, Jan; Seidl, Libor; Zvára, Karel; Grünfeldová, Hana; Slovák, Dalibor; Zvárová, Jana

2013-01-01

We implemented a prototype of a decision support system called SIR which has a form of a web-based classification service for diagnostic decision support. The system has the ability to select the most relevant variables and to learn a classification rule, which is guaranteed to be suitable also for high-dimensional measurements. The classification system can be useful for clinicians in primary care to support their decision-making tasks with relevant information extracted from any available clinical study. The implemented prototype was tested on a sample of patients in a cardiological study and performs an information extraction from a high-dimensional set containing both clinical and gene expression data.

Conditional maximum-entropy method for selecting prior distributions in Bayesian statistics

NASA Astrophysics Data System (ADS)

Abe, Sumiyoshi

2014-11-01

The conditional maximum-entropy method (abbreviated here as C-MaxEnt) is formulated for selecting prior probability distributions in Bayesian statistics for parameter estimation. This method is inspired by a statistical-mechanical approach to systems governed by dynamics with largely separated time scales and is based on three key concepts: conjugate pairs of variables, dimensionless integration measures with coarse-graining factors and partial maximization of the joint entropy. The method enables one to calculate a prior purely from a likelihood in a simple way. It is shown, in particular, how it not only yields Jeffreys's rules but also reveals new structures hidden behind them.

N Reasons Why Production-Rules are Insufficient Models for Expert System Knowledge Representation Schemes

DTIC Science & Technology

1991-02-01

3 2.2 Hybrid Rule/Fact Schemas .............................................................. 3 3 THE LIMITATIONS OF RULE BASED KNOWLEDGE...or hybrid rule/fact schemas. 2 UNCLASSIFIED .WA UNCLASSIFIED ERL-0520-RR 2.1 Propositional Logic The simplest form of production-rules are based upon...requirements which may lead to poor system performance. 2.2 Hybrid Rule/Fact Schemas Hybrid rule/fact relationships (also known as Predicate Calculus ) have

Transformation of Arden Syntax's medical logic modules into ArdenML for a business rules management system.

PubMed

Jung, Chai Young; Choi, Jong-Ye; Jeong, Seong Jik; Cho, Kyunghee; Koo, Yong Duk; Bae, Jin Hee; Kim, Sukil

2016-05-16

Arden Syntax is a Health Level Seven International (HL7) standard language that is used for representing medical knowledge as logic statements. Arden Syntax Markup Language (ArdenML) is a new representation of Arden Syntax based on XML. Compilers are required to execute medical logic modules (MLMs) in the hospital environment. However, ArdenML may also replace the compiler. The purpose of this study is to demonstrate that MLMs, encoded in ArdenML, can be transformed into a commercial rule engine format through an XSLT stylesheet and made executable in a target system. The target rule engine selected was Blaze Advisor. We developed an XSLT stylesheet to transform MLMs in ArdenML into Structured Rules Language (SRL) in Blaze Advisor, through a comparison of syntax between the two languages. The stylesheet was then refined recursively, by building and applying rules collected from the billing and coding guidelines of the Korean health insurance service. Two nurse coders collected and verified the rules and two information technology (IT) specialists encoded the MLMs and built the XSLT stylesheet. Finally, the stylesheet was validated by importing the MLMs into Blaze Advisor and applying them to claims data. The language comparison revealed that Blaze Advisor requires the declaration of variables with explicit types. We used both integer and real numbers for numeric types in ArdenML. "IF∼THEN" statements and assignment statements in ArdenML become rules in Blaze Advisor. We designed an XSLT stylesheet to solve this issue. In addition, we maintained the order of rule execution in the transformed rules, and added two small programs to support variable declarations and action statements. A total of 1489 rules were reviewed during this study, of which 324 rules were collected. We removed duplicate rules and encoded 241 unique MLMs in ArdenML, which were successfully transformed into SRL and imported to Blaze Advisor via the XSLT stylesheet. When applied to 73,841 outpatients' insurance claims data, the review result was the same as that of the legacy system. We have demonstrated that ArdenML can replace a compiler for transforming MLMs into commercial rule engine format. While the proposed XSLT stylesheet requires refinement for general use, we anticipate that the development of further XSLT stylesheets will support various rule engines. Copyright © 2016 Elsevier B.V. All rights reserved.

Design of high entropy alloys based on the experience from commercial superalloys

NASA Astrophysics Data System (ADS)

Wang, Z.; Huang, Y.; Wang, J.; Liu, C. T.

2015-01-01

High entropy alloys (HEAs) have been drawing increasing attention recently and gratifying results have been obtained. However, the existing metallurgic rules of HEAs could not provide specific information of selecting candidate alloys for structural applications. Our brief survey reveals that many commercial superalloys have medium and even to high configurational entropies. The experience of commercial superalloys provides a clue for helping us in the development of HEAs for structural applications.

Multi-Criteria selection of technology for processing ore raw materials

NASA Astrophysics Data System (ADS)

Gorbatova, E. A.; Emelianenko, E. A.; Zaretckii, M. V.

2017-10-01

The development of Computer-Aided Process Planning (CAPP) for the Ore Beneficiation process is considered. The set of parameters to define the quality of the Ore Beneficiation process is identified. The ontological model of CAPP for the Ore Beneficiation process is described. The hybrid choice method of the most appropriate variant of the Ore Beneficiation process based on the Logical Conclusion Rules and the Fuzzy Multi-Criteria Decision Making (MCDM) approach is proposed.

76 FR 18274 - Self-Regulatory Organizations; Notice of Filing and Immediate Effectiveness of Proposed Rule...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-04-01

... in all other Select Symbols, except SPY, QQQ and AAPL which would receive the $0.25 per contract... Exchange Act of 1934 (``Act''),\\1\\ and Rule 19b-4 thereunder,\\2\\ notice is hereby given that on March 21... on the proposed rule change from interested persons. \\1\\ 15 U.S.C. 78s(b)(1). \\2\\ 17 CFR 240.19b-4. I...

Risk management. National Aeronautics and Space Administration (NASA). Interim rule adopted as final with changes.

PubMed

2000-11-22

This is a final rule amending the NASA FAR Supplement (NFS) to emphasize considerations of risk management, including safety, security (including information technology security), health, export control, and damage to the environment, within the acquisition process. This final rule addresses risk management within the context of acquisition planning, selecting sources, choosing contract type, structuring award fee incentives, administering contracts, and conducting contractor surveillance.

Challenges for Rule Systems on the Web

NASA Astrophysics Data System (ADS)

Hu, Yuh-Jong; Yeh, Ching-Long; Laun, Wolfgang

The RuleML Challenge started in 2007 with the objective of inspiring the issues of implementation for management, integration, interoperation and interchange of rules in an open distributed environment, such as the Web. Rules are usually classified as three types: deductive rules, normative rules, and reactive rules. The reactive rules are further classified as ECA rules and production rules. The study of combination rule and ontology is traced back to an earlier active rule system for relational and object-oriented (OO) databases. Recently, this issue has become one of the most important research problems in the Semantic Web. Once we consider a computer executable policy as a declarative set of rules and ontologies that guides the behavior of entities within a system, we have a flexible way to implement real world policies without rewriting the computer code, as we did before. Fortunately, we have de facto rule markup languages, such as RuleML or RIF to achieve the portability and interchange of rules for different rule systems. Otherwise, executing real-life rule-based applications on the Web is almost impossible. Several commercial or open source rule engines are available for the rule-based applications. However, we still need a standard rule language and benchmark for not only to compare the rule systems but also to measure the progress in the field. Finally, a number of real-life rule-based use cases will be investigated to demonstrate the applicability of current rule systems on the Web.

[Analysis on traditional Chinese medicine prescriptions treating cancer based on traditional Chinese medicine inheritance assistance system and discovery of new prescriptions].

PubMed

Yu, Ming; Cao, Qi-chen; Su, Yu-xi; Sui, Xin; Yang, Hong-jun; Huang, Lu-qi; Wang, Wen-ping

2015-08-01

Malignant tumor is one of the main causes for death in the world at present as well as a major disease seriously harming human health and life and restricting the social and economic development. There are many kinds of reports about traditional Chinese medicine patent prescriptions, empirical prescriptions and self-made prescriptions treating cancer, and prescription rules were often analyzed based on medication frequency. Such methods were applicable for discovering dominant experience but hard to have an innovative discovery and knowledge. In this paper, based on the traditional Chinese medicine inheritance assistance system, the software integration of mutual information improvement method, complex system entropy clustering and unsupervised entropy-level clustering data mining methods was adopted to analyze the rules of traditional Chinese medicine prescriptions for cancer. Totally 114 prescriptions were selected, the frequency of herbs in prescription was determined, and 85 core combinations and 13 new prescriptions were indentified. The traditional Chinese medicine inheritance assistance system, as a valuable traditional Chinese medicine research-supporting tool, can be used to record, manage, inquire and analyze prescription data.

A decision-support system for the analysis of clinical practice patterns.

PubMed

Balas, E A; Li, Z R; Mitchell, J A; Spencer, D C; Brent, E; Ewigman, B G

1994-01-01

Several studies documented substantial variation in medical practice patterns, but physicians often do not have adequate information on the cumulative clinical and financial effects of their decisions. The purpose of developing an expert system for the analysis of clinical practice patterns was to assist providers in analyzing and improving the process and outcome of patient care. The developed QFES (Quality Feedback Expert System) helps users in the definition and evaluation of measurable quality improvement objectives. Based on objectives and actual clinical data, several measures can be calculated (utilization of procedures, annualized cost effect of using a particular procedure, and expected utilization based on peer-comparison and case-mix adjustment). The quality management rules help to detect important discrepancies among members of the selected provider group and compare performance with objectives. The system incorporates a variety of data and knowledge bases: (i) clinical data on actual practice patterns, (ii) frames of quality parameters derived from clinical practice guidelines, and (iii) rules of quality management for data analysis. An analysis of practice patterns of 12 family physicians in the management of urinary tract infections illustrates the use of the system.

- and Scene-Guided Integration of Tls and Photogrammetric Point Clouds for Landslide Monitoring

NASA Astrophysics Data System (ADS)

Zieher, T.; Toschi, I.; Remondino, F.; Rutzinger, M.; Kofler, Ch.; Mejia-Aguilar, A.; Schlögel, R.

2018-05-01

Terrestrial and airborne 3D imaging sensors are well-suited data acquisition systems for the area-wide monitoring of landslide activity. State-of-the-art surveying techniques, such as terrestrial laser scanning (TLS) and photogrammetry based on unmanned aerial vehicle (UAV) imagery or terrestrial acquisitions have advantages and limitations associated with their individual measurement principles. In this study we present an integration approach for 3D point clouds derived from these techniques, aiming at improving the topographic representation of landslide features while enabling a more accurate assessment of landslide-induced changes. Four expert-based rules involving local morphometric features computed from eigenvectors, elevation and the agreement of the individual point clouds, are used to choose within voxels of selectable size which sensor's data to keep. Based on the integrated point clouds, digital surface models and shaded reliefs are computed. Using an image correlation technique, displacement vectors are finally derived from the multi-temporal shaded reliefs. All results show comparable patterns of landslide movement rates and directions. However, depending on the applied integration rule, differences in spatial coverage and correlation strength emerge.

Distributed Fair Auto Rate Medium Access Control for IEEE 802.11 Based WLANs

NASA Astrophysics Data System (ADS)

Zhu, Yanfeng; Niu, Zhisheng

Much research has shown that a carefully designed auto rate medium access control can utilize the underlying physical multi-rate capability to exploit the time-variation of the channel. In this paper, we develop a simple analytical model to elucidate the rule that maximizes the throughput of RTS/CTS based multi-rate wireless local area networks. Based on the discovered rule, we propose two distributed fair auto rate medium access control schemes called FARM and FARM+ from the view-point of throughput fairness and time-share fairness, respectively. With the proposed schemes, after receiving a RTS frame, the receiver selectively returns the CTS frame to inform the transmitter the maximum feasible rate probed by the signal-to-noise ratio of the received RTS frame. The key feature of the proposed schemes is that they are capable of maintaining throughput/time-share fairness in asymmetric situation where the distribution of SNR varies with stations. Extensive simulation results show that the proposed schemes outperform the existing throughput/time-share fair auto rate schemes in time-varying channel conditions.

Band-selective filter in a zigzag graphene nanoribbon.

PubMed

Nakabayashi, Jun; Yamamoto, Daisuke; Kurihara, Susumu

2009-02-13

Electric transport of a zigzag graphene nanoribbon through a steplike potential and a barrier potential is investigated by using the recursive Green's function method. In the case of the steplike potential, we demonstrate numerically that scattering processes obey a selection rule for the band indices when the number of zigzag chains is even; the electrons belonging to the "even" ("odd") bands are scattered only into the even (odd) bands so that the parity of the wave functions is preserved. In the case of the barrier potential, by tuning the barrier height to be an appropriate value, we show that it can work as the "band-selective filter", which transmits electrons selectively with respect to the indices of the bands to which the incident electrons belong. Finally, we suggest that this selection rule can be observed in the conductance by applying two barrier potentials.

Structure identification in fuzzy inference using reinforcement learning

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.; Khedkar, Pratap

1993-01-01

In our previous work on the GARIC architecture, we have shown that the system can start with surface structure of the knowledge base (i.e., the linguistic expression of the rules) and learn the deep structure (i.e., the fuzzy membership functions of the labels used in the rules) by using reinforcement learning. Assuming the surface structure, GARIC refines the fuzzy membership functions used in the consequents of the rules using a gradient descent procedure. This hybrid fuzzy logic and reinforcement learning approach can learn to balance a cart-pole system and to backup a truck to its docking location after a few trials. In this paper, we discuss how to do structure identification using reinforcement learning in fuzzy inference systems. This involves identifying both surface as well as deep structure of the knowledge base. The term set of fuzzy linguistic labels used in describing the values of each control variable must be derived. In this process, splitting a label refers to creating new labels which are more granular than the original label and merging two labels creates a more general label. Splitting and merging of labels directly transform the structure of the action selection network used in GARIC by increasing or decreasing the number of hidden layer nodes.

Novel determinants of mammalian primary microRNA processing revealed by systematic evaluation of hairpin-containing transcripts and human genetic variation

PubMed Central

Roden, Christine; Gaillard, Jonathan; Kanoria, Shaveta; Rennie, William; Barish, Syndi; Cheng, Jijun; Pan, Wen; Liu, Jun; Cotsapas, Chris; Ding, Ye; Lu, Jun

2017-01-01

Mature microRNAs (miRNAs) are processed from hairpin-containing primary miRNAs (pri-miRNAs). However, rules that distinguish pri-miRNAs from other hairpin-containing transcripts in the genome are incompletely understood. By developing a computational pipeline to systematically evaluate 30 structural and sequence features of mammalian RNA hairpins, we report several new rules that are preferentially utilized in miRNA hairpins and govern efficient pri-miRNA processing. We propose that a hairpin stem length of 36 ± 3 nt is optimal for pri-miRNA processing. We identify two bulge-depleted regions on the miRNA stem, located ∼16–21 nt and ∼28–32 nt from the base of the stem, that are less tolerant of unpaired bases. We further show that the CNNC primary sequence motif selectively enhances the processing of optimal-length hairpins. We predict that a small but significant fraction of human single-nucleotide polymorphisms (SNPs) alter pri-miRNA processing, and confirm several predictions experimentally including a disease-causing mutation. Our study enhances the rules governing mammalian pri-miRNA processing and suggests a diverse impact of human genetic variation on miRNA biogenesis. PMID:28087842

Color image encryption based on hybrid hyper-chaotic system and cellular automata

NASA Astrophysics Data System (ADS)

Yaghouti Niyat, Abolfazl; Moattar, Mohammad Hossein; Niazi Torshiz, Masood

2017-03-01

This paper proposes an image encryption scheme based on Cellular Automata (CA). CA is a self-organizing structure with a set of cells in which each cell is updated by certain rules that are dependent on a limited number of neighboring cells. The major disadvantages of cellular automata in cryptography include limited number of reversal rules and inability to produce long sequences of states by these rules. In this paper, a non-uniform cellular automata framework is proposed to solve this problem. This proposed scheme consists of confusion and diffusion steps. In confusion step, the positions of the original image pixels are replaced by chaos mapping. Key image is created using non-uniform cellular automata and then the hyper-chaotic mapping is used to select random numbers from the image key for encryption. The main contribution of the paper is the application of hyper chaotic functions and non-uniform CA for robust key image generation. Security analysis and experimental results show that the proposed method has a very large key space and is resistive against noise and attacks. The correlation between adjacent pixels in the encrypted image is reduced and the amount of entropy is equal to 7.9991 which is very close to 8 which is ideal.

Semantic photo books: leveraging blogs and social media for photo book creation

NASA Astrophysics Data System (ADS)

Rabbath, Mohamad; Sandhaus, Philipp; Boll, Susanne

2011-03-01

Recently, we observed a substantial increase in the users' interest in sharing their photos online in travel blogs, social communities and photo sharing websites. An interesting aspect of these web platforms is their high level of user-media interaction and thus a high-quality source of semantic annotations: Users comment on the photos of each others, add external links to their travel blogs, tag each other in the social communities and add captions and descriptions to their photos. However, while those media assets are shared online, many users still highly appreciate the representation of these media in appealing physical photo books where the semantics are represented in form of descriptive text, maps, and external elements in addition to their related photos. Thus, in this paper we aim at fulfilling this need and provide an approach for creating photo books from Web 2.0 resources. We concentrate on two kinds of online shared media as resources for printable photo books: (a) Blogs especially travel blogs (b) Social community websites like Facebook which witness a rapidly growing number of shared media elements including photos. We introduce an approach to select media elements including photos, geographical maps and texts from both blogs and social networks semi-automatically, and then use these elements to create a printable photo book with an appealing layout. Because the selected media elements can be too many for the resulting book, we choose the most proper ones by exploiting content based, social based, and interactive based criteria. Additionally we add external media elements such as geographical maps, texts and externally hosted photos from linked resources. Having selected the important media, our approach uses a genetic algorithm to create an appealing layout using aesthetical rules, such as positioning the photo with the related text or map in a way that respects the golden ratio and symmetry. Distributing the media over the pages is done by optimizing the distribution according to several rules such that no pages with purely textual elements without photos are produced. For the page layout appropriate photos are chosen for the background based on their salience. Other media assets, such as texts, photos and geographical maps are positioned in the foreground by a dynamic page layout algorithm respecting both the content of the photos and the background, and common rules for visual layout. The result of our system is a photo book in a printable format. We implemented our approach as web services that analyze the media elements, enrich them, and create the layout in order to finally publish a photo book. The connection to those services is implemented in two interfaces. The first is a tool to select entries from personal blogs, and the second is a Facebook application that allows the user to select photos from his albums.

Multi-objective evolutionary algorithms for fuzzy classification in survival prediction.

PubMed

Jiménez, Fernando; Sánchez, Gracia; Juárez, José M

2014-03-01

This paper presents a novel rule-based fuzzy classification methodology for survival/mortality prediction in severe burnt patients. Due to the ethical aspects involved in this medical scenario, physicians tend not to accept a computer-based evaluation unless they understand why and how such a recommendation is given. Therefore, any fuzzy classifier model must be both accurate and interpretable. The proposed methodology is a three-step process: (1) multi-objective constrained optimization of a patient's data set, using Pareto-based elitist multi-objective evolutionary algorithms to maximize accuracy and minimize the complexity (number of rules) of classifiers, subject to interpretability constraints; this step produces a set of alternative (Pareto) classifiers; (2) linguistic labeling, which assigns a linguistic label to each fuzzy set of the classifiers; this step is essential to the interpretability of the classifiers; (3) decision making, whereby a classifier is chosen, if it is satisfactory, according to the preferences of the decision maker. If no classifier is satisfactory for the decision maker, the process starts again in step (1) with a different input parameter set. The performance of three multi-objective evolutionary algorithms, niched pre-selection multi-objective algorithm, elitist Pareto-based multi-objective evolutionary algorithm for diversity reinforcement (ENORA) and the non-dominated sorting genetic algorithm (NSGA-II), was tested using a patient's data set from an intensive care burn unit and a standard machine learning data set from an standard machine learning repository. The results are compared using the hypervolume multi-objective metric. Besides, the results have been compared with other non-evolutionary techniques and validated with a multi-objective cross-validation technique. Our proposal improves the classification rate obtained by other non-evolutionary techniques (decision trees, artificial neural networks, Naive Bayes, and case-based reasoning) obtaining with ENORA a classification rate of 0.9298, specificity of 0.9385, and sensitivity of 0.9364, with 14.2 interpretable fuzzy rules on average. Our proposal improves the accuracy and interpretability of the classifiers, compared with other non-evolutionary techniques. We also conclude that ENORA outperforms niched pre-selection and NSGA-II algorithms. Moreover, given that our multi-objective evolutionary methodology is non-combinational based on real parameter optimization, the time cost is significantly reduced compared with other evolutionary approaches existing in literature based on combinational optimization. Copyright © 2014 Elsevier B.V. All rights reserved.

Development and Characterization of a Rate-Dependent Three-Dimensional Macroscopic Plasticity Model Suitable for Use in Composite Impact Problems

NASA Technical Reports Server (NTRS)

Goldberg, Robert K.; Carney, Kelly S.; DuBois, Paul; Hoffarth, Canio; Rajan, Subramaniam; Blankenhorn, Gunther

2015-01-01

Several key capabilities have been identified by the aerospace community as lacking in the material/models for composite materials currently available within commercial transient dynamic finite element codes such as LS-DYNA. Some of the specific desired features that have been identified include the incorporation of both plasticity and damage within the material model, the capability of using the material model to analyze the response of both three-dimensional solid elements and two dimensional shell elements, and the ability to simulate the response of composites composed with a variety of composite architectures, including laminates, weaves and braids. In addition, a need has been expressed to have a material model that utilizes tabulated experimentally based input to define the evolution of plasticity and damage as opposed to utilizing discrete input parameters (such as modulus and strength) and analytical functions based on curve fitting. To begin to address these needs, an orthotropic macroscopic plasticity based model suitable for implementation within LS-DYNA has been developed. Specifically, the Tsai-Wu composite failure model has been generalized and extended to a strain-hardening based orthotropic plasticity model with a non-associative flow rule. The coefficients in the yield function are determined based on tabulated stress-strain curves in the various normal and shear directions, along with selected off-axis curves. Incorporating rate dependence into the yield function is achieved by using a series of tabluated input curves, each at a different constant strain rate. The non-associative flow-rule is used to compute the evolution of the effective plastic strain. Systematic procedures have been developed to determine the values of the various coefficients in the yield function and the flow rule based on the tabulated input data. An algorithm based on the radial return method has been developed to facilitate the numerical implementation of the material model. The presented paper will present in detail the development of the orthotropic plasticity model and the procedures used to obtain the required material parameters. Methods in which a combination of actual testing and selective numerical testing can be combined to yield the appropriate input data for the model will be described. A specific laminated polymer matrix composite will be examined to demonstrate the application of the model.

Collective Movement in the Tibetan Macaques (Macaca thibetana): Early Joiners Write the Rule of the Game.

PubMed

Wang, Xi; Sun, Lixing; Li, Jinhua; Xia, Dongpo; Sun, Binghua; Zhang, Dao

2015-01-01

Collective behavior has recently attracted a great deal of interest in both natural and social sciences. While the role of leadership has been closely scrutinized, the rules used by joiners in collective decision making have received far less attention. Two main hypotheses have been proposed concerning these rules: mimetism and quorum. Mimetism predicts that individuals are increasingly likely to join collective behavior as the number of participants increases. It can be further divided into selective mimetism, where relationships among the participants affect the process, and anonymous mimetism, where no such effect exists. Quorum predicts that a collective behavior occurs when the number of participants reaches a threshold. To probe into which rule is used in collective decision making, we conducted a study on the joining process in a group of free-ranging Tibetan macaques (Macaca thibetana) in Huangshan, China using a combination of all-occurrence and focal animal sampling methods. Our results show that the earlier individuals joined movements, the more central a role they occupied among the joining network. We also found that when less than three adults participated in the first five minutes of the joining process, no entire group movement occurred subsequently. When the number of these early joiners ranged from three to six, selective mimetism was used. This means higher rank or closer social affiliation of early joiners could be among the factors of deciding whether to participate in movements by group members. When the number of early joiners reached or exceeded seven, which was the simple majority of the group studied, entire group movement always occurred, meaning that the quorum rule was used. Putting together, Macaca thibetana used a combination of selective mimetism and quorum, and early joiners played a key role in deciding which rule should be used.

ConGEMs: Condensed Gene Co-Expression Module Discovery Through Rule-Based Clustering and Its Application to Carcinogenesis.

PubMed

Mallik, Saurav; Zhao, Zhongming

2017-12-28

For transcriptomic analysis, there are numerous microarray-based genomic data, especially those generated for cancer research. The typical analysis measures the difference between a cancer sample-group and a matched control group for each transcript or gene. Association rule mining is used to discover interesting item sets through rule-based methodology. Thus, it has advantages to find causal effect relationships between the transcripts. In this work, we introduce two new rule-based similarity measures-weighted rank-based Jaccard and Cosine measures-and then propose a novel computational framework to detect condensed gene co-expression modules ( C o n G E M s) through the association rule-based learning system and the weighted similarity scores. In practice, the list of evolved condensed markers that consists of both singular and complex markers in nature depends on the corresponding condensed gene sets in either antecedent or consequent of the rules of the resultant modules. In our evaluation, these markers could be supported by literature evidence, KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway and Gene Ontology annotations. Specifically, we preliminarily identified differentially expressed genes using an empirical Bayes test. A recently developed algorithm-RANWAR-was then utilized to determine the association rules from these genes. Based on that, we computed the integrated similarity scores of these rule-based similarity measures between each rule-pair, and the resultant scores were used for clustering to identify the co-expressed rule-modules. We applied our method to a gene expression dataset for lung squamous cell carcinoma and a genome methylation dataset for uterine cervical carcinogenesis. Our proposed module discovery method produced better results than the traditional gene-module discovery measures. In summary, our proposed rule-based method is useful for exploring biomarker modules from transcriptomic data.

[Traditional Chinese medicine inheritance system analysis of professor Ding Yuanqing in treating tic disorder medication based on experience].

PubMed

Sun, Lu-yan; Li, Qing-peng; Zhao, Li-li; Ding, Yuan-qing

2015-08-01

In recent years, the incidence of tic disorders has increased, and it is not uncommon for the patients to treat the disease. The pathogenesis and pathogenesis of Western medicine are not yet clear, the clinical commonly used western medicine has many adverse reactions, traditional Chinese medicine (TCM) research is increasingly valued. Based on the software of TCM inheritance assistant system, this paper discusses Ding Yuanqing's experience in treating tic disorder with Professor. Collect yuan Qing Ding professor in treating tic disorder of medical records by association rules Apriori algorithm, complex system entropy clustering without supervision and data mining method, carries on the analysis to the selected 800 prescriptions, to determine the frequency of use of prescription drugs, the association rules between the drug and digging out the 12 core combination and the first six new prescription, medication transferred to the liver and extinguish wind, cooling blood and relieving convulsion, Qingxin soothe the nerves, with the card cut, flexible application, strict compatibility.

Expectations for inflationary observables: simple or natural?

NASA Astrophysics Data System (ADS)

Musoke, Nathan; Easther, Richard

2017-12-01

We describe the general inflationary dynamics that can arise with a single, canonically coupled field where the inflaton potential is a 4-th order polynomial. This scenario yields a wide range of combinations of the empirical spectral observables, ns, r and αs. However, not all combinations are possible and next-generation cosmological experiments have the ability to rule out all inflationary scenarios based on this potential. Further, we construct inflationary priors for this potential based on physically motivated choices for its free parameters. These can be used to determine the degree of tuning associated with different combinations of ns, r and αs and will facilitate treatments of the inflationary model selection problem. Finally, we comment on the implications of these results for the naturalness of the overall inflationary paradigm. We argue that ruling out all simple, renormalizable potentials would not necessarily imply that the inflationary paradigm itself was unnatural, but that this eventuality would increase the importance of building inflationary scenarios in the context of broader paradigms of ultra-high energy physics.

Selection rules for harmonic generation in solids

NASA Astrophysics Data System (ADS)

Moiseyev, Nimrod

2015-05-01

High-order harmonic generation (HHG) in a bulk crystal was first observed in 2011 [S. Ghimire, A. D. DiChiara, E. Sistrunk, P. Agostini, L. F. DiMauro, and D. A. Reis, Nat. Phys. 7, 138 (2011), 10.1038/nphys1847]. Only odd-order harmonics were observed as expected on the basis of the selection rules in solids, which were derived when only the interband currents were taken into consideration. Here we study HHG in solids when the intraband currents are taken into consideration as well. We show that the dynamical selection rules are broken in solids and the possibility of generation of even-order harmonics cannot be excluded on the basis of the dynamical symmetry analysis. However, a simple analysis of the expression we obtained for the amplitude of the emitted high-order harmonics shows, without the need to carry out numerical calculations, that the even-order harmonics are suppressed due to the localization of the field-free one-electron density probability on the atoms in the solids.

Use of mathematics to guide target selection in systems pharmacology; application to receptor tyrosine kinase (RTK) pathways.

PubMed

Benson, Neil; van der Graaf, Piet H; Peletier, Lambertus A

2017-11-15

A key element of the drug discovery process is target selection. Although the topic is subject to much discussion and experimental effort, there are no defined quantitative rules around optimal selection. Often 'rules of thumb', that have not been subject to rigorous exploration, are used. In this paper we explore the 'rule of thumb' notion that the molecule that initiates a pathway signal is the optimal target. Given the multi-factorial and complex nature of this question, we have simplified an example pathway to its logical minimum of two steps and used a mathematical model of this to explore the different options in the context of typical small and large molecule drugs. In this paper, we report the conclusions of our analysis and describe the analysis tool and methods used. These provide a platform to enable a more extensive enquiry into this important topic. Copyright © 2017 Elsevier B.V. All rights reserved.

Design of highly selective ethanol dehydration nanocatalysts for ethylene production.

PubMed

Austin, Natalie; Kostetskyy, Pavlo; Mpourmpakis, Giannis

2018-02-22

Rational design of catalysts for selective conversion of alcohols to olefins is key since product selectivity remains an issue due to competing etherification reactions. Using first principles calculations and chemical rules, we designed novel metal-oxide-protected metal nanoclusters (M 13 X 4 O 12 , with M = Cu, Ag, and Au and X = Al, Ga, and In) exhibiting strong Lewis acid sites on their surface, active for the selective formation of olefins from alcohols. These symmetrical nanocatalysts, due to their curvature, show unfavorable etherification chemistries, while favoring the olefin production. Furthermore, we determined that water removal and regeneration of the nanocatalysts is more feasible compared to the equivalent strong acid sites on solid acids used for alcohol dehydration. Our results demonstrate an exceptional stability of these new nanostructures with the most energetically favorable being Cu-based. Thus, the high selectivity and stability of these in-silico-predicted novel nanoclusters (e.g. Cu 13 Al 4 O 12 ) make them attractive catalysts for the selective dehydration of alcohols to olefins.

Selectivity in reversed-phase separations: general influence of solvent type and mobile phase pH.

PubMed

Neue, Uwe D; Méndez, Alberto

2007-05-01

The influence of the mobile phase on retention is studied in this paper for a group of over 70 compounds with a broad range of multiple functional groups. We varied the pH of the mobile phase (pH 3, 7, and 10) and the organic modifier (methanol, acetonitrile (ACN), and tetrahydrofuran (THF)), using 15 different stationary phases. In this paper, we describe the overall retention and selectivity changes observed with these variables. We focus on the primary effects of solvent choice and pH. For example, transfer rules for solvent composition resulting in equivalent retention depend on the packing as well as on the type of analyte. Based on the retention patterns, one can calculate selectivity difference values for different variables. The selectivity difference is a measure of the importance of the different variables involved in method development. Selectivity changes specific to the type of analyte are described. The largest selectivity differences are obtained with pH changes.

14 CFR 91.409 - Inspections.

Code of Federal Regulations, 2012 CFR

2012-01-01

... (e) of this section must select, identify in the aircraft maintenance records, and use one of the... AND GENERAL OPERATING RULES GENERAL OPERATING AND FLIGHT RULES Maintenance, Preventive Maintenance... person may operate an aircraft unless, within the preceding 12 calendar months, it has had— (1) An annual...

14 CFR 91.409 - Inspections.

Code of Federal Regulations, 2011 CFR

2011-01-01

... (e) of this section must select, identify in the aircraft maintenance records, and use one of the... AND GENERAL OPERATING RULES GENERAL OPERATING AND FLIGHT RULES Maintenance, Preventive Maintenance... person may operate an aircraft unless, within the preceding 12 calendar months, it has had— (1) An annual...

14 CFR 91.409 - Inspections.

Code of Federal Regulations, 2014 CFR

2014-01-01

... (e) of this section must select, identify in the aircraft maintenance records, and use one of the... AND GENERAL OPERATING RULES GENERAL OPERATING AND FLIGHT RULES Maintenance, Preventive Maintenance... person may operate an aircraft unless, within the preceding 12 calendar months, it has had— (1) An annual...

14 CFR 91.409 - Inspections.

Code of Federal Regulations, 2013 CFR

2013-01-01

... (e) of this section must select, identify in the aircraft maintenance records, and use one of the... AND GENERAL OPERATING RULES GENERAL OPERATING AND FLIGHT RULES Maintenance, Preventive Maintenance... person may operate an aircraft unless, within the preceding 12 calendar months, it has had— (1) An annual...

42 CFR 422.205 - Provider antidiscrimination rules.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 42 Public Health 3 2011-10-01 2011-10-01 false Provider antidiscrimination rules. 422.205 Section 422.205 Public Health CENTERS FOR MEDICARE & MEDICAID SERVICES, DEPARTMENT OF HEALTH AND HUMAN... policies and procedures concerning provider selection and credentialing established under § 422.204, and...

Sexual selection explains sex-specific growth plasticity and positive allometry for sexual size dimorphism in a reef fish

PubMed Central

Walker, Stefan P. W.; McCormick, Mark I.

2009-01-01

In 1950, Rensch noted that in clades where males are the larger sex, sexual size dimorphism (SSD) tends to be more pronounced in larger species. This fundamental allometric relationship is now known as ‘Rensch's rule’. While most researchers attribute Rensch's rule to sexual selection for male size, experimental evidence is lacking. Here, we suggest that ultimate hypotheses for Rensch's rule should also apply to groups of individuals and that individual trait plasticity can be used to test those hypotheses experimentally. Specifically, we show that in the sex-changing fish Parapercis cylindrica, larger males have larger harems with larger females, and that SSD increases with harem size. Thus, sexual selection for male body size is the ultimate cause of sexual size allometry. In addition, we experimentally illustrate a positive relationship between polygyny potential and individual growth rate during sex change from female to male. Thus, sexual selection is the ultimate cause of variation in growth rate, and variation in growth rate is the proximate cause of sexual size allometry. Taken together, our results provide compelling evidence in support of the sexual selection hypothesis for Rensch's rule and highlight the potential importance of individual growth modification in the shaping of morphological patterns in Nature. PMID:19553253

A Study on Human Oriented Autonomous Distributed Manufacturing System —Real-time Scheduling Method Based on Preference of Human Operators

NASA Astrophysics Data System (ADS)

Iwamura, Koji; Kuwahara, Shinya; Tanimizu, Yoshitaka; Sugimura, Nobuhiro

Recently, new distributed architectures of manufacturing systems are proposed, aiming at realizing more flexible control structures of the manufacturing systems. Many researches have been carried out to deal with the distributed architectures for planning and control of the manufacturing systems. However, the human operators have not yet been discussed for the autonomous components of the distributed manufacturing systems. A real-time scheduling method is proposed, in this research, to select suitable combinations of the human operators, the resources and the jobs for the manufacturing processes. The proposed scheduling method consists of following three steps. In the first step, the human operators select their favorite manufacturing processes which they will carry out in the next time period, based on their preferences. In the second step, the machine tools and the jobs select suitable combinations for the next machining processes. In the third step, the automated guided vehicles and the jobs select suitable combinations for the next transportation processes. The second and third steps are carried out by using the utility value based method and the dispatching rule-based method proposed in the previous researches. Some case studies have been carried out to verify the effectiveness of the proposed method.

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

Automated revision of CLIPS rule-bases

NASA Technical Reports Server (NTRS)

Murphy, Patrick M.; Pazzani, Michael J.

1994-01-01

This paper describes CLIPS-R, a theory revision system for the revision of CLIPS rule-bases. CLIPS-R may be used for a variety of knowledge-base revision tasks, such as refining a prototype system, adapting an existing system to slightly different operating conditions, or improving an operational system that makes occasional errors. We present a description of how CLIPS-R revises rule-bases, and an evaluation of the system on three rule-bases.

Entropy-based gene ranking without selection bias for the predictive classification of microarray data.

PubMed

Furlanello, Cesare; Serafini, Maria; Merler, Stefano; Jurman, Giuseppe

2003-11-06

We describe the E-RFE method for gene ranking, which is useful for the identification of markers in the predictive classification of array data. The method supports a practical modeling scheme designed to avoid the construction of classification rules based on the selection of too small gene subsets (an effect known as the selection bias, in which the estimated predictive errors are too optimistic due to testing on samples already considered in the feature selection process). With E-RFE, we speed up the recursive feature elimination (RFE) with SVM classifiers by eliminating chunks of uninteresting genes using an entropy measure of the SVM weights distribution. An optimal subset of genes is selected according to a two-strata model evaluation procedure: modeling is replicated by an external stratified-partition resampling scheme, and, within each run, an internal K-fold cross-validation is used for E-RFE ranking. Also, the optimal number of genes can be estimated according to the saturation of Zipf's law profiles. Without a decrease of classification accuracy, E-RFE allows a speed-up factor of 100 with respect to standard RFE, while improving on alternative parametric RFE reduction strategies. Thus, a process for gene selection and error estimation is made practical, ensuring control of the selection bias, and providing additional diagnostic indicators of gene importance.

Do humans (Homo sapiens) and fish (Pterophyllum scalare) make similar numerosity judgments?

PubMed

Miletto Petrazzini, Maria Elena; Agrillo, Christian; Izard, Véronique; Bisazza, Angelo

2016-11-01

Numerous studies have shown that many animal species can be trained to discriminate between stimuli differing in numerosity. However, in the absence of generalization tests with untrained numerosities, what decision criterion was used by subjects remains unclear: the subjects may succeed by selecting a specific number of items (a criterion over absolute numerosities), or by applying a more general relative numerosity rule, for example, selecting the larger/smaller quantity of items. The latter case may require more powerful representations, supporting judgments of order ("more/less") beyond simple "same/different" judgments, but a relative numerosity rule may also be more adaptive. In previous research, we showed that guppies (Poecilia reticulata) spontaneously prefer relative numerosity rules. To date it is unclear whether this preference is shared by other fish and, more broadly, other species. Here we compared the performance of angelfish (Pterophyllum scalare) with that of human adults (Homo sapiens) in a task in which subjects were initially trained to select arrays containing 10 dots (either in 5 vs. 10 or 10 vs. 20 comparisons). Subsequently they were tested with the previously trained numerosity and a novel numerosity (respectively, 20 or 5). In the absence of explicit instructions, both species spontaneously favored a relative rule, selecting the novel numerosity. These similarities demonstrate that, beyond shared representations for numerical quantities, vertebrate species may also share a system for taking decisions about quantities. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

ARNetMiT R Package: association rules based gene co-expression networks of miRNA targets.

PubMed

Özgür Cingiz, M; Biricik, G; Diri, B

2017-03-31

miRNAs are key regulators that bind to target genes to suppress their gene expression level. The relations between miRNA-target genes enable users to derive co-expressed genes that may be involved in similar biological processes and functions in cells. We hypothesize that target genes of miRNAs are co-expressed, when they are regulated by multiple miRNAs. With the usage of these co-expressed genes, we can theoretically construct co-expression networks (GCNs) related to 152 diseases. In this study, we introduce ARNetMiT that utilize a hash based association rule algorithm in a novel way to infer the GCNs on miRNA-target genes data. We also present R package of ARNetMiT, which infers and visualizes GCNs of diseases that are selected by users. Our approach assumes miRNAs as transactions and target genes as their items. Support and confidence values are used to prune association rules on miRNA-target genes data to construct support based GCNs (sGCNs) along with support and confidence based GCNs (scGCNs). We use overlap analysis and the topological features for the performance analysis of GCNs. We also infer GCNs with popular GNI algorithms for comparison with the GCNs of ARNetMiT. Overlap analysis results show that ARNetMiT outperforms the compared GNI algorithms. We see that using high confidence values in scGCNs increase the ratio of the overlapped gene-gene interactions between the compared methods. According to the evaluation of the topological features of ARNetMiT based GCNs, the degrees of nodes have power-law distribution. The hub genes discovered by ARNetMiT based GCNs are consistent with the literature.

Training self-assessment and task-selection skills to foster self-regulated learning: Do trained skills transfer across domains?

PubMed

Raaijmakers, Steven F; Baars, Martine; Paas, Fred; van Merriënboer, Jeroen J G; van Gog, Tamara

2018-01-01

Students' ability to accurately self-assess their performance and select a suitable subsequent learning task in response is imperative for effective self-regulated learning. Video modeling examples have proven effective for training self-assessment and task-selection skills, and-importantly-such training fostered self-regulated learning outcomes. It is unclear, however, whether trained skills would transfer across domains. We investigated whether skills acquired from training with either a specific, algorithmic task-selection rule or a more general heuristic task-selection rule in biology would transfer to self-regulated learning in math. A manipulation check performed after the training confirmed that both algorithmic and heuristic training improved task-selection skills on the biology problems compared with the control condition. However, we found no evidence that students subsequently applied the acquired skills during self-regulated learning in math. Future research should investigate how to support transfer of task-selection skills across domains.

Training self‐assessment and task‐selection skills to foster self‐regulated learning: Do trained skills transfer across domains?

PubMed Central

Baars, Martine; Paas, Fred; van Merriënboer, Jeroen J. G.; van Gog, Tamara

2018-01-01

Summary Students' ability to accurately self‐assess their performance and select a suitable subsequent learning task in response is imperative for effective self‐regulated learning. Video modeling examples have proven effective for training self‐assessment and task‐selection skills, and—importantly—such training fostered self‐regulated learning outcomes. It is unclear, however, whether trained skills would transfer across domains. We investigated whether skills acquired from training with either a specific, algorithmic task‐selection rule or a more general heuristic task‐selection rule in biology would transfer to self‐regulated learning in math. A manipulation check performed after the training confirmed that both algorithmic and heuristic training improved task‐selection skills on the biology problems compared with the control condition. However, we found no evidence that students subsequently applied the acquired skills during self‐regulated learning in math. Future research should investigate how to support transfer of task‐selection skills across domains. PMID:29610547

Scaling-up strategic purchasing: analysis of health system governance imperatives for strategic purchasing in a free maternal and child healthcare programme in Enugu State, Nigeria.

PubMed

Ogbuabor, Daniel Chukwuemeka; Onwujekwe, Obinna Emmanuel

2018-04-05

Significant knowledge gaps exist in the functioning of institutional designs and organisational practices in purchasing within free healthcare schemes in low resource countries. The study provides evidence of the governance requirements to scale up strategic purchasing in free healthcare policies in Nigeria and other low-resource settings facing similar approaches. The study was conducted at the Ministry of Health and in two health districts in Enugu State, Nigeria, using a qualitative case study design. Semi-structured interviews were conducted with 44 key health system actors (16 policymakers, 16 providers and 12 health facility committee leaders) purposively selected from the Ministry of Health and the two health districts. Data collection and analysis were guided by Siddiqi and colleagues' health system governance framework. Data were analysed using a framework approach. The key findings show that supportive governance practices in purchasing included systems to verify questionable provider claims, pay providers directly for services, compel providers to procure drugs centrally and track transfer of funds to providers. However, strategic vision was undermined by institutional conflicts, absence of purchaser-provider split and lack of selective contracting of providers. Benefit design was not based on stakeholder involvement. Rule of law was limited by delays in provider payment. Benefits and obligations to users were not transparent. The criteria and procedure for resource allocation were unclear. Some target beneficiaries seemed excluded from the scheme. Effectiveness and efficiency was constrained by poor adherence to purchasing rules. Accountability of purchasers and providers to users was weak. Intelligence and information is constrained by paper-based system. Rationing of free services by providers and users' non-adherence to primary gate-keeping role hindered ethics. Weak governance of purchasing function limits potential of FMCHP to contribute towards universal health coverage. Appropriate governance model for strengthening strategic purchasing in the FMCHP and possibly free healthcare interventions in other low-resource countries must pay attention to the creation of an autonomous purchasing agency, clear framework for selective contracting, stakeholder involvement, transparent benefit design, need-based resource allocation, efficient provider payment methods, stronger roles for citizens, enforcement of gatekeeping rules and use of data for decision-making.

42 CFR 438.214 - Provider selection.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 42 Public Health 4 2010-10-01 2010-10-01 false Provider selection. 438.214 Section 438.214 Public... Operation Standards § 438.214 Provider selection. (a) General rules. The State must ensure, through its contracts, that each MCO, PIHP, or PAHP implements written policies and procedures for selection and...

42 CFR 422.204 - Provider selection and credentialing.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 42 Public Health 3 2010-10-01 2010-10-01 false Provider selection and credentialing. 422.204... Provider selection and credentialing. (a) General rule. An MA organization must have written policies and procedures for the selection and evaluation of providers. These policies must conform with the credential and...

Concurrence of rule- and similarity-based mechanisms in artificial grammar learning.

PubMed

Opitz, Bertram; Hofmann, Juliane

2015-03-01

A current theoretical debate regards whether rule-based or similarity-based learning prevails during artificial grammar learning (AGL). Although the majority of findings are consistent with a similarity-based account of AGL it has been argued that these results were obtained only after limited exposure to study exemplars, and performance on subsequent grammaticality judgment tests has often been barely above chance level. In three experiments the conditions were investigated under which rule- and similarity-based learning could be applied. Participants were exposed to exemplars of an artificial grammar under different (implicit and explicit) learning instructions. The analysis of receiver operating characteristics (ROC) during a final grammaticality judgment test revealed that explicit but not implicit learning led to rule knowledge. It also demonstrated that this knowledge base is built up gradually while similarity knowledge governed the initial state of learning. Together these results indicate that rule- and similarity-based mechanisms concur during AGL. Moreover, it could be speculated that two different rule processes might operate in parallel; bottom-up learning via gradual rule extraction and top-down learning via rule testing. Crucially, the latter is facilitated by performance feedback that encourages explicit hypothesis testing. Copyright © 2015 Elsevier Inc. All rights reserved.

Feeding on Multiple Sources: Towards a Universal Parameterization of the Functional Response of a Generalist Predator Allowing for Switching

PubMed Central

Morozov, Andrew; Petrovskii, Sergei

2013-01-01

Understanding of complex trophic interactions in ecosystems requires correct descriptions of the rate at which predators consume a variety of different prey species. Field and laboratory data on multispecies communities are rarely sufficient and usually cannot provide an unambiguous test for the theory. As a result, the conventional way of constructing a multi-prey functional response is speculative, and often based on assumptions that are difficult to verify. Predator responses allowing for prey selectivity and active switching are thought to be more biologically relevant compared to the standard proportion-based consumption. However, here we argue that the functional responses with switching may not be applicable to communities with a broad spectrum of resource types. We formulate a set of general rules that a biologically sound parameterization of a predator functional response should satisfy, and show that all existing formulations for the multispecies response with prey selectivity and switching fail to do so. Finally, we propose a universal framework for parameterization of a multi-prey functional response by combining patterns of food selectivity and proportion-based feeding. PMID:24086356

Efficient and Accurate Optimal Linear Phase FIR Filter Design Using Opposition-Based Harmony Search Algorithm

PubMed Central

Saha, S. K.; Dutta, R.; Choudhury, R.; Kar, R.; Mandal, D.; Ghoshal, S. P.

2013-01-01

In this paper, opposition-based harmony search has been applied for the optimal design of linear phase FIR filters. RGA, PSO, and DE have also been adopted for the sake of comparison. The original harmony search algorithm is chosen as the parent one, and opposition-based approach is applied. During the initialization, randomly generated population of solutions is chosen, opposite solutions are also considered, and the fitter one is selected as a priori guess. In harmony memory, each such solution passes through memory consideration rule, pitch adjustment rule, and then opposition-based reinitialization generation jumping, which gives the optimum result corresponding to the least error fitness in multidimensional search space of FIR filter design. Incorporation of different control parameters in the basic HS algorithm results in the balancing of exploration and exploitation of search space. Low pass, high pass, band pass, and band stop FIR filters are designed with the proposed OHS and other aforementioned algorithms individually for comparative optimization performance. A comparison of simulation results reveals the optimization efficacy of the OHS over the other optimization techniques for the solution of the multimodal, nondifferentiable, nonlinear, and constrained FIR filter design problems. PMID:23844390

Efficient and accurate optimal linear phase FIR filter design using opposition-based harmony search algorithm.

PubMed

Saha, S K; Dutta, R; Choudhury, R; Kar, R; Mandal, D; Ghoshal, S P

2013-01-01

In this paper, opposition-based harmony search has been applied for the optimal design of linear phase FIR filters. RGA, PSO, and DE have also been adopted for the sake of comparison. The original harmony search algorithm is chosen as the parent one, and opposition-based approach is applied. During the initialization, randomly generated population of solutions is chosen, opposite solutions are also considered, and the fitter one is selected as a priori guess. In harmony memory, each such solution passes through memory consideration rule, pitch adjustment rule, and then opposition-based reinitialization generation jumping, which gives the optimum result corresponding to the least error fitness in multidimensional search space of FIR filter design. Incorporation of different control parameters in the basic HS algorithm results in the balancing of exploration and exploitation of search space. Low pass, high pass, band pass, and band stop FIR filters are designed with the proposed OHS and other aforementioned algorithms individually for comparative optimization performance. A comparison of simulation results reveals the optimization efficacy of the OHS over the other optimization techniques for the solution of the multimodal, nondifferentiable, nonlinear, and constrained FIR filter design problems.

An Enhanced Artificial Bee Colony Algorithm with Solution Acceptance Rule and Probabilistic Multisearch.

PubMed

Yurtkuran, Alkın; Emel, Erdal

2016-01-01

The artificial bee colony (ABC) algorithm is a popular swarm based technique, which is inspired from the intelligent foraging behavior of honeybee swarms. This paper proposes a new variant of ABC algorithm, namely, enhanced ABC with solution acceptance rule and probabilistic multisearch (ABC-SA) to address global optimization problems. A new solution acceptance rule is proposed where, instead of greedy selection between old solution and new candidate solution, worse candidate solutions have a probability to be accepted. Additionally, the acceptance probability of worse candidates is nonlinearly decreased throughout the search process adaptively. Moreover, in order to improve the performance of the ABC and balance the intensification and diversification, a probabilistic multisearch strategy is presented. Three different search equations with distinctive characters are employed using predetermined search probabilities. By implementing a new solution acceptance rule and a probabilistic multisearch approach, the intensification and diversification performance of the ABC algorithm is improved. The proposed algorithm has been tested on well-known benchmark functions of varying dimensions by comparing against novel ABC variants, as well as several recent state-of-the-art algorithms. Computational results show that the proposed ABC-SA outperforms other ABC variants and is superior to state-of-the-art algorithms proposed in the literature.

Detection of pseudosinusoidal epileptic seizure segments in the neonatal EEG by cascading a rule-based algorithm with a neural network.

PubMed

Karayiannis, Nicolaos B; Mukherjee, Amit; Glover, John R; Ktonas, Periklis Y; Frost, James D; Hrachovy, Richard A; Mizrahi, Eli M

2006-04-01

This paper presents an approach to detect epileptic seizure segments in the neonatal electroencephalogram (EEG) by characterizing the spectral features of the EEG waveform using a rule-based algorithm cascaded with a neural network. A rule-based algorithm screens out short segments of pseudosinusoidal EEG patterns as epileptic based on features in the power spectrum. The output of the rule-based algorithm is used to train and compare the performance of conventional feedforward neural networks and quantum neural networks. The results indicate that the trained neural networks, cascaded with the rule-based algorithm, improved the performance of the rule-based algorithm acting by itself. The evaluation of the proposed cascaded scheme for the detection of pseudosinusoidal seizure segments reveals its potential as a building block of the automated seizure detection system under development.

Selective skepticism: American and Chinese children's reasoning about evaluative academic feedback.

PubMed

Heyman, Gail D; Fu, Genyue; Lee, Kang

2013-03-01

Children's reasoning about the credibility of positive and negative evaluations of academic performance was examined. Across 2 studies, 7- and 10-year-olds from the United States and China (N = 334) judged the credibility of academic evaluations that were directed toward an unfamiliar peer. In Study 1, participants from China responded that criticism should be accepted to a greater extent than did participants from the United States, and children from both countries demonstrated a selective skepticism effect by treating negative feedback more skeptically than positive feedback. Study 2 replicated the selective skepticism effect among children from both countries and ruled out the possibility that it can be explained as a rational analysis of perceived base rates. The results suggest that children are selective in their trust of evaluative feedback and that their credibility judgments may be influenced by the desirability of the information that is being conveyed or its anticipated consequences.

77 FR 73498 - Self-Regulatory Organizations; Chicago Board Options Exchange, Incorporated; Notice of Filing and...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-12-10

... Effectiveness of a Proposed Rule Change To Amend Its Rule Related to Multi-Class Broad- Based Index Option... Rule Change The Exchange proposes to amend its rule related to multi-class broad-based index option... is to (i) clarify that the term ``Multi-Class Broad-Based Index Option Spread Order (Multi-Class...

Can parental monitoring and peer management reduce the selection or influence of delinquent peers? Testing the question using a dynamic social network approach.

PubMed

Tilton-Weaver, Lauree C; Burk, William J; Kerr, Margaret; Stattin, Håkan

2013-11-01

We tested whether parents can reduce affiliation with delinquent peers through 3 forms of peer management: soliciting information, monitoring rules, and communicating disapproval of peers. We examined whether peer management interrupted 2 peer processes: selection and influence of delinquent peers. Adolescents' feelings of being overcontrolled by parents were examined as an additional moderator of delinquent selection and influence. Using network data from a community sample (N = 1,730), we tested whether selection and influence processes varied across early, middle, and late adolescent cohorts. Selection and influence of delinquent peers were evident in all 3 cohorts and did not differ in strength. Parental monitoring rules reduced the selection of delinquent peers in the oldest cohort. A similar effect was found in the early adolescent cohort, but only for adolescents who did not feel overcontrolled by parents. Monitoring rules increased the likelihood of selecting a delinquent friend among those who felt overcontrolled. The effectiveness of communicating disapproval was also mixed: in the middle adolescent network, communicating disapproval increased the likelihood of an adolescent selecting a delinquent friend. Among late adolescents, high levels of communicating disapproval were effective, reducing the influence of delinquent peers for adolescents reporting higher rates of delinquency. For those who reported lower levels of delinquency, high levels of communicating disapproval increased the influence of delinquent peers. The results of this study suggest that the effectiveness of monitoring and peer management depend on the type of behavior, the timing of its use, and whether adolescents feel overcontrolled by parents.

75 FR 4463 - Race to the Top Fund

Federal Register 2010, 2011, 2012, 2013, 2014

2010-01-27

..., requirements, definitions, and selection criteria; correction. SUMMARY: On November 18, 2009, the Department of... the November 18 Final Rule was the Scoring Rubric that the Department developed for the scoring of... to the November 18 Final Rule. DATES: Effective Date: January 27, 2010. FOR FURTHER INFORMATION...

Domain repertoires as a tool to derive protein recognition rules.

PubMed

Zucconi, A; Panni, S; Paoluzi, S; Castagnoli, L; Dente, L; Cesareni, G

2000-08-25

Several approaches, some of which are described in this issue, have been proposed to assemble a complete protein interaction map. These are often based on high throughput methods that explore the ability of each gene product to bind any other element of the proteome of the organism. Here we propose that a large number of interactions can be inferred by revealing the rules underlying recognition specificity of a small number (a few hundreds) of families of protein recognition modules. This can be achieved through the construction and characterization of domain repertoires. A domain repertoire is assembled in a combinatorial fashion by allowing each amino acid position in the binding site of a given protein recognition domain to vary to include all the residues allowed at that position in the domain family. The repertoire is then searched by phage display techniques with any target of interest and from the primary structure of the binding site of the selected domains one derives rules that are used to infer the formation of complexes between natural proteins in the cell.

Sequence-based design of bioactive small molecules that target precursor microRNAs.

PubMed

Velagapudi, Sai Pradeep; Gallo, Steven M; Disney, Matthew D

2014-04-01

Oligonucleotides are designed to target RNA using base pairing rules, but they can be hampered by poor cellular delivery and nonspecific stimulation of the immune system. Small molecules are preferred as lead drugs or probes but cannot be designed from sequence. Herein, we describe an approach termed Inforna that designs lead small molecules for RNA from solely sequence. Inforna was applied to all human microRNA hairpin precursors, and it identified bioactive small molecules that inhibit biogenesis by binding nuclease-processing sites (44% hit rate). Among 27 lead interactions, the most avid interaction is between a benzimidazole (1) and precursor microRNA-96. Compound 1 selectively inhibits biogenesis of microRNA-96, upregulating a protein target (FOXO1) and inducing apoptosis in cancer cells. Apoptosis is ablated when FOXO1 mRNA expression is knocked down by an siRNA, validating compound selectivity. Markedly, microRNA profiling shows that 1 only affects microRNA-96 biogenesis and is at least as selective as an oligonucleotide.

Sequence-based design of bioactive small molecules that target precursor microRNAs

PubMed Central

Velagapudi, Sai Pradeep; Gallo, Steven M.; Disney, Matthew D.

2014-01-01

Oligonucleotides are designed to target RNA using base pairing rules, however, they are hampered by poor cellular delivery and non-specific stimulation of the immune system. Small molecules are preferred as lead drugs or probes, but cannot be designed from sequence. Herein, we describe an approach termed Inforna that designs lead small molecules for RNA from solely sequence. Inforna was applied to all human microRNA precursors and identified bioactive small molecules that inhibit biogenesis by binding to nuclease processing sites (41% hit rate). Amongst 29 lead interactions, the most avid interaction is between a benzimidazole (1) and precursor microRNA-96. Compound 1 selectively inhibits biogenesis of microRNA-96, upregulating a protein target (FOXO1) and inducing apoptosis in cancer cells. Apoptosis is ablated when FOXO1 mRNA expression is knocked down by an siRNA, validating compound selectivity. Importantly, microRNA profiling shows that 1 only significantly effects microRNA-96 biogenesis and is more selective than an oligonucleotide. PMID:24509821

Mimic expert judgement through automated procedure for selecting rainfall events responsible for shallow landslide: A statistical approach to validation

NASA Astrophysics Data System (ADS)

Giovanna, Vessia; Luca, Pisano; Carmela, Vennari; Mauro, Rossi; Mario, Parise

2016-01-01

This paper proposes an automated method for the selection of rainfall data (duration, D, and cumulated, E), responsible for shallow landslide initiation. The method mimics an expert person identifying D and E from rainfall records through a manual procedure whose rules are applied according to her/his judgement. The comparison between the two methods is based on 300 D-E pairs drawn from temporal rainfall data series recorded in a 30 days time-lag before the landslide occurrence. Statistical tests, employed on D and E samples considered both paired and independent values to verify whether they belong to the same population, show that the automated procedure is able to replicate the expert pairs drawn by the expert judgment. Furthermore, a criterion based on cumulated distribution functions (CDFs) is proposed to select the most related D-E pairs to the expert one among the 6 drawn from the coded procedure for tracing the empirical rainfall threshold line.

Image Fusion Algorithms Using Human Visual System in Transform Domain

NASA Astrophysics Data System (ADS)

Vadhi, Radhika; Swamy Kilari, Veera; Samayamantula, Srinivas Kumar

2017-08-01

The endeavor of digital image fusion is to combine the important visual parts from various sources to advance the visibility eminence of the image. The fused image has a more visual quality than any source images. In this paper, the Human Visual System (HVS) weights are used in the transform domain to select appropriate information from various source images and then to attain a fused image. In this process, mainly two steps are involved. First, apply the DWT to the registered source images. Later, identify qualitative sub-bands using HVS weights. Hence, qualitative sub-bands are selected from different sources to form high quality HVS based fused image. The quality of the HVS based fused image is evaluated with general fusion metrics. The results show the superiority among the state-of-the art resolution Transforms (MRT) such as Discrete Wavelet Transform (DWT), Stationary Wavelet Transform (SWT), Contourlet Transform (CT), and Non Sub Sampled Contourlet Transform (NSCT) using maximum selection fusion rule.

Parallel inferencing method and apparatus for rule-based expert systems

NASA Technical Reports Server (NTRS)

Schwuttke, Ursula M. (Inventor); Moldovan, Dan (Inventor); Kuo, Steve (Inventor)

1993-01-01

The invention analyzes areas of conditions with an expert knowledge base of rules using plural separate nodes which fire respective rules of said knowledge base, each of said rules upon being fired altering certain of said conditions predicated upon the existence of other said conditions. The invention operates by constructing a P representation of all pairs of said rules which are input dependent or output dependent; constructing a C representation of all pairs of said rules which are communication dependent or input dependent; determining which of the rules are ready to fire by matching the predicate conditions of each rule with the conditions of said set; enabling said node means to simultaneously fire those of the rules ready to fire which are defined by said P representation as being free of input and output dependencies; and communicating from each node enabled by said enabling step the alteration of conditions by the corresponding rule to other nodes whose rules are defined by said C matrix means as being input or communication dependent upon the rule of said enabled node.

Application Development for Optimizing Patient Placement on Aeromedical Evacuation Flights: Proof-of-Concept

DTIC Science & Technology

2018-01-12

outcomes. This study included three phases: knowledge elicitation, establishment of rule-based, logic requirements, and the development of the POC iOS ...establish the logic needed for a mobile app prior to programming for iOS platforms. The study team selected Microsoft Excel because it enabled the...distribution of these plans would streamline the plan development process. Thus, as a proof-of-concept, the study team conducted a multi-phased effort

Standards and reliability in evaluation: when rules of thumb don't apply.

PubMed

Norcini, J J

1999-10-01

The purpose of this paper is to identify situations in which two rules of thumb in evaluation do not apply. The first rule is that all standards should be absolute. When selection decisions are being made or when classroom tests are given, however, relative standards may be better. The second rule of thumb is that every test should have a reliability of .80 or better. Depending on the circumstances, though, the standard error of measurement, the consistency of pass/fail classifications, and the domain-referenced reliability coefficients may be better indicators of reproducibility.

49 CFR 236.9 - Selection of circuits through indicating or annunciating instruments.

Code of Federal Regulations, 2010 CFR

2010-10-01

... (Continued) FEDERAL RAILROAD ADMINISTRATION, DEPARTMENT OF TRANSPORTATION RULES, STANDARDS, AND INSTRUCTIONS... indicating or annunciating instruments. Signal control and electric locking circuits shall not be selected...

Using Rule-Based Computer Programming to Unify Communication Rules Research.

ERIC Educational Resources Information Center

Sanford, David L.; Roach, J. W.

This paper proposes the use of a rule-based computer programming language as a standard for the expression of rules, arguing that the adoption of a standard would enable researchers to communicate about rules in a consistent and significant way. Focusing on the formal equivalence of artificial intelligence (AI) programming to different types of…

Compliance monitoring in business processes: Functionalities, application, and tool-support.

PubMed

Ly, Linh Thao; Maggi, Fabrizio Maria; Montali, Marco; Rinderle-Ma, Stefanie; van der Aalst, Wil M P

2015-12-01

In recent years, monitoring the compliance of business processes with relevant regulations, constraints, and rules during runtime has evolved as major concern in literature and practice. Monitoring not only refers to continuously observing possible compliance violations, but also includes the ability to provide fine-grained feedback and to predict possible compliance violations in the future. The body of literature on business process compliance is large and approaches specifically addressing process monitoring are hard to identify. Moreover, proper means for the systematic comparison of these approaches are missing. Hence, it is unclear which approaches are suitable for particular scenarios. The goal of this paper is to define a framework for Compliance Monitoring Functionalities (CMF) that enables the systematic comparison of existing and new approaches for monitoring compliance rules over business processes during runtime. To define the scope of the framework, at first, related areas are identified and discussed. The CMFs are harvested based on a systematic literature review and five selected case studies. The appropriateness of the selection of CMFs is demonstrated in two ways: (a) a systematic comparison with pattern-based compliance approaches and (b) a classification of existing compliance monitoring approaches using the CMFs. Moreover, the application of the CMFs is showcased using three existing tools that are applied to two realistic data sets. Overall, the CMF framework provides powerful means to position existing and future compliance monitoring approaches.

Machine Learning to Improve the Effectiveness of ANRS in Predicting HIV Drug Resistance.

PubMed

Singh, Yashik

2017-10-01

Human immunodeficiency virus infection and acquired immune deficiency syndrome (HIV/AIDS) is one of the major burdens of disease in developing countries, and the standard-of-care treatment includes prescribing antiretroviral drugs. However, antiretroviral drug resistance is inevitable due to selective pressure associated with the high mutation rate of HIV. Determining antiretroviral resistance can be done by phenotypic laboratory tests or by computer-based interpretation algorithms. Computer-based algorithms have been shown to have many advantages over laboratory tests. The ANRS (Agence Nationale de Recherches sur le SIDA) is regarded as a gold standard in interpreting HIV drug resistance using mutations in genomes. The aim of this study was to improve the prediction of the ANRS gold standard in predicting HIV drug resistance. A genome sequence and HIV drug resistance measures were obtained from the Stanford HIV database (http://hivdb.stanford.edu/). Feature selection was used to determine the most important mutations associated with resistance prediction. These mutations were added to the ANRS rules, and the difference in the prediction ability was measured. This study uncovered important mutations that were not associated with the original ANRS rules. On average, the ANRS algorithm was improved by 79% ± 6.6%. The positive predictive value improved by 28%, and the negative predicative value improved by 10%. The study shows that there is a significant improvement in the prediction ability of ANRS gold standard.

Compliance monitoring in business processes: Functionalities, application, and tool-support

PubMed Central

Ly, Linh Thao; Maggi, Fabrizio Maria; Montali, Marco; Rinderle-Ma, Stefanie; van der Aalst, Wil M.P.

2015-01-01

In recent years, monitoring the compliance of business processes with relevant regulations, constraints, and rules during runtime has evolved as major concern in literature and practice. Monitoring not only refers to continuously observing possible compliance violations, but also includes the ability to provide fine-grained feedback and to predict possible compliance violations in the future. The body of literature on business process compliance is large and approaches specifically addressing process monitoring are hard to identify. Moreover, proper means for the systematic comparison of these approaches are missing. Hence, it is unclear which approaches are suitable for particular scenarios. The goal of this paper is to define a framework for Compliance Monitoring Functionalities (CMF) that enables the systematic comparison of existing and new approaches for monitoring compliance rules over business processes during runtime. To define the scope of the framework, at first, related areas are identified and discussed. The CMFs are harvested based on a systematic literature review and five selected case studies. The appropriateness of the selection of CMFs is demonstrated in two ways: (a) a systematic comparison with pattern-based compliance approaches and (b) a classification of existing compliance monitoring approaches using the CMFs. Moreover, the application of the CMFs is showcased using three existing tools that are applied to two realistic data sets. Overall, the CMF framework provides powerful means to position existing and future compliance monitoring approaches. PMID:26635430

Receptive field optimisation and supervision of a fuzzy spiking neural network.

PubMed

Glackin, Cornelius; Maguire, Liam; McDaid, Liam; Sayers, Heather

2011-04-01

This paper presents a supervised training algorithm that implements fuzzy reasoning on a spiking neural network. Neuron selectivity is facilitated using receptive fields that enable individual neurons to be responsive to certain spike train firing rates and behave in a similar manner as fuzzy membership functions. The connectivity of the hidden and output layers in the fuzzy spiking neural network (FSNN) is representative of a fuzzy rule base. Fuzzy C-Means clustering is utilised to produce clusters that represent the antecedent part of the fuzzy rule base that aid classification of the feature data. Suitable cluster widths are determined using two strategies; subjective thresholding and evolutionary thresholding respectively. The former technique typically results in compact solutions in terms of the number of neurons, and is shown to be particularly suited to small data sets. In the latter technique a pool of cluster candidates is generated using Fuzzy C-Means clustering and then a genetic algorithm is employed to select the most suitable clusters and to specify cluster widths. In both scenarios, the network is supervised but learning only occurs locally as in the biological case. The advantages and disadvantages of the network topology for the Fisher Iris and Wisconsin Breast Cancer benchmark classification tasks are demonstrated and directions of current and future work are discussed. Copyright © 2010 Elsevier Ltd. All rights reserved.

Multi-Layer Approach for the Detection of Selective Forwarding Attacks

PubMed Central

Alajmi, Naser; Elleithy, Khaled

2015-01-01

Security breaches are a major threat in wireless sensor networks (WSNs). WSNs are increasingly used due to their broad range of important applications in both military and civilian domains. WSNs are prone to several types of security attacks. Sensor nodes have limited capacities and are often deployed in dangerous locations; therefore, they are vulnerable to different types of attacks, including wormhole, sinkhole, and selective forwarding attacks. Security attacks are classified as data traffic and routing attacks. These security attacks could affect the most significant applications of WSNs, namely, military surveillance, traffic monitoring, and healthcare. Therefore, there are different approaches to detecting security attacks on the network layer in WSNs. Reliability, energy efficiency, and scalability are strong constraints on sensor nodes that affect the security of WSNs. Because sensor nodes have limited capabilities in most of these areas, selective forwarding attacks cannot be easily detected in networks. In this paper, we propose an approach to selective forwarding detection (SFD). The approach has three layers: MAC pool IDs, rule-based processing, and anomaly detection. It maintains the safety of data transmission between a source node and base station while detecting selective forwarding attacks. Furthermore, the approach is reliable, energy efficient, and scalable. PMID:26610499

Development of a fuzzy logic expert system for pile selection. Master's thesis

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

Ulshafer, M.L.

1989-01-01

This thesis documents the development of prototype expert system for pile selection for use on microcomputers. It concerns the initial selection of a pile foundation taking into account the parameters such as soil condition, pile length, loading scenario, material availability, contractor experience, and noise or vibration constraints. The prototype expert system called Pile Selection, version 1 (PS1) was developed using an expert system shell FLOPS. FLOPS is a shell based on the AI language OPS5 with many unique features. The system PS1 utilizes all of these unique features. Among the features used are approximate reasoning with fuzzy set theory, themore » blackboard architecture, and the emulated parallel processing of fuzzy production rules. A comprehensive review of the parameters used in selecting a pile was made, and the effects of the uncertainties associated with the vagueness of these parameters was examined in detail. Fuzzy set theory was utilized to deal with such uncertainties and provides the basis for developing a method for determining the best possible choice of piles for a given situation. Details of the development of PS1, including documenting and collating pile information for use in the expert knowledge data bases, are discussed.« less

Multi-Layer Approach for the Detection of Selective Forwarding Attacks.

PubMed

Alajmi, Naser; Elleithy, Khaled

2015-11-19

Security breaches are a major threat in wireless sensor networks (WSNs). WSNs are increasingly used due to their broad range of important applications in both military and civilian domains. WSNs are prone to several types of security attacks. Sensor nodes have limited capacities and are often deployed in dangerous locations; therefore, they are vulnerable to different types of attacks, including wormhole, sinkhole, and selective forwarding attacks. Security attacks are classified as data traffic and routing attacks. These security attacks could affect the most significant applications of WSNs, namely, military surveillance, traffic monitoring, and healthcare. Therefore, there are different approaches to detecting security attacks on the network layer in WSNs. Reliability, energy efficiency, and scalability are strong constraints on sensor nodes that affect the security of WSNs. Because sensor nodes have limited capabilities in most of these areas, selective forwarding attacks cannot be easily detected in networks. In this paper, we propose an approach to selective forwarding detection (SFD). The approach has three layers: MAC pool IDs, rule-based processing, and anomaly detection. It maintains the safety of data transmission between a source node and base station while detecting selective forwarding attacks. Furthermore, the approach is reliable, energy efficient, and scalable.

Reducing the Conflict Factors Strategies in Question Answering System

NASA Astrophysics Data System (ADS)

Suwarningsih, W.; Purwarianti, A.; Supriana, I.

2017-03-01

A rule-based system is prone to conflict as new knowledge every time will emerge and indirectly must sign in to the knowledge base that is used by the system. A conflict occurred between the rules in the knowledge base can lead to the errors of reasoning or reasoning circulation. Therefore, when added, the new rules will lead to conflict with other rules, and the only rules that really can be added to the knowledge base. From these conditions, this paper aims to propose a conflict resolution strategy for a medical debriefing system by analyzing scenarios based upon the runtime to improve the efficiency and reliability of systems.

Towards collaborative filtering recommender systems for tailored health communications.

PubMed

Marlin, Benjamin M; Adams, Roy J; Sadasivam, Rajani; Houston, Thomas K

2013-01-01

The goal of computer tailored health communications (CTHC) is to promote healthy behaviors by sending messages tailored to individual patients. Current CTHC systems collect baseline patient "profiles" and then use expert-written, rule-based systems to target messages to subsets of patients. Our main interest in this work is the study of collaborative filtering-based CTHC systems that can learn to tailor future message selections to individual patients based explicit feedback about past message selections. This paper reports the results of a study designed to collect explicit feedback (ratings) regarding four aspects of messages from 100 subjects in the smoking cessation support domain. Our results show that most users have positive opinions of most messages and that the ratings for all four aspects of the messages are highly correlated with each other. Finally, we conduct a range of rating prediction experiments comparing several different model variations. Our results show that predicting future ratings based on each user's past ratings contributes the most to predictive accuracy.

Towards Collaborative Filtering Recommender Systems for Tailored Health Communications

PubMed Central

Marlin, Benjamin M.; Adams, Roy J.; Sadasivam, Rajani; Houston, Thomas K.

2013-01-01

The goal of computer tailored health communications (CTHC) is to promote healthy behaviors by sending messages tailored to individual patients. Current CTHC systems collect baseline patient “profiles” and then use expert-written, rule-based systems to target messages to subsets of patients. Our main interest in this work is the study of collaborative filtering-based CTHC systems that can learn to tailor future message selections to individual patients based explicit feedback about past message selections. This paper reports the results of a study designed to collect explicit feedback (ratings) regarding four aspects of messages from 100 subjects in the smoking cessation support domain. Our results show that most users have positive opinions of most messages and that the ratings for all four aspects of the messages are highly correlated with each other. Finally, we conduct a range of rating prediction experiments comparing several different model variations. Our results show that predicting future ratings based on each user’s past ratings contributes the most to predictive accuracy. PMID:24551430

Models of Quantitative Estimations: Rule-Based and Exemplar-Based Processes Compared

ERIC Educational Resources Information Center

von Helversen, Bettina; Rieskamp, Jorg

2009-01-01

The cognitive processes underlying quantitative estimations vary. Past research has identified task-contingent changes between rule-based and exemplar-based processes (P. Juslin, L. Karlsson, & H. Olsson, 2008). B. von Helversen and J. Rieskamp (2008), however, proposed a simple rule-based model--the mapping model--that outperformed the…

Design of impact-resistant boron/aluminum large fan blade

NASA Technical Reports Server (NTRS)

Salemme, C. T.; Yokel, S. A.

1978-01-01

The technical program was comprised of two technical tasks. Task 1 encompassed the preliminary boron/aluminum fan blade design effort. Two preliminary designs were evolved. An initial design consisted of 32 blades per stage and was based on material properties extracted from manufactured blades. A final design of 36 blades per stage was based on rule-of-mixture material properties. In Task 2, the selected preliminary blade design was refined via more sophisticated analytical tools. Detailed finite element stress analysis and aero performance analysis were carried out to determine blade material frequencies and directional stresses.

A neural mechanism of cognitive control for resolving conflict between abstract task rules.

PubMed

Sheu, Yi-Shin; Courtney, Susan M

2016-12-01

Conflict between multiple sensory stimuli or potential motor responses is thought to be resolved via bias signals from prefrontal cortex (PFC). However, population codes in the PFC also represent abstract information, such as task rules. How is conflict between active abstract representations resolved? We used functional neuroimaging to investigate the mechanism responsible for resolving conflict between abstract representations of task rules. Participants performed two different tasks based on a cue. We manipulated the degree of conflict at the task-rule level by training participants to associate the color and shape dimensions of the cue with either the same task rule (congruent cues) or different ones (incongruent cues). Phonological and semantic tasks were used in which performance depended on learned, abstract representations of information, rather than sensory features of the target stimulus or on any habituated stimulus-response associations. In addition, these tasks activate distinct regions that allowed us to measure magnitude of conflict between tasks. We found that incongruent cues were associated with increased activity in several cognitive control areas, including the inferior frontal gyrus, inferior parietal lobule, insula, and subcortical regions. Conflict between abstract representations appears to be resolved by rule-specific activity in the inferior frontal gyrus that is correlated with enhanced activity related to the relevant information. Furthermore, multi-voxel pattern analysis of the activity in the inferior frontal gyrus was shown to carry information about both the currently relevant rule (semantic/phonological) and the currently relevant cue context (color/shape). Similar to models of attentional selection of conflicting sensory or motor representations, the current findings indicate part of the frontal cortex provides a bias signal, representing task rules, that enhances task-relevant information. However, the frontal cortex can also be the target of these bias signals in order to enhance abstract representations that are independent of particular stimuli or motor responses. Copyright © 2016 Elsevier Ltd. All rights reserved.

A neural mechanism of cognitive control for resolving conflict between abstract task rules

PubMed Central

Sheu, Yi-Shin; Courtney, Susan M.

2016-01-01

Conflict between multiple sensory stimuli or potential motor responses is thought to be resolved via bias signals from prefrontal cortex. However, population codes in the prefrontal cortex also represent abstract information, such as task rules. How is conflict between active abstract representations resolved? We used functional neuroimaging to investigate the mechanism responsible for resolving conflict between abstract representations of task rules. Participants performed two different tasks based on a cue. We manipulated the degree of conflict at the task-rule level by training participants to associate the color and shape dimensions of the cue with either the same task rule (congruent cues) or different ones (incongruent cues). Phonological and semantic tasks were used in which performance depended on learned, abstract representations of information, rather than sensory features of the target stimulus or on any habituated stimulus-response associations. In addition, these tasks activate distinct regions that allowed us to measure magnitude of conflict between tasks. We found that incongruent cues were associated with increased activity in several cognitive control areas, including the inferior frontal gyrus, inferior parietal lobule, insula, and subcortical regions. Conflict between abstract representations appears to be resolved by rule-specific activity in the inferior frontal gyrus that is correlated with enhanced activity related to the relevant information. Furthermore, multivoxel pattern analysis of the activity in the inferior frontal gyrus was shown to carry information about both the currently relevant rule (semantic/phonological) and the currently relevant cue context (color/shape). Similar to models of attentional selection of conflicting sensory or motor representations, the current findings indicate part of the frontal cortex provides a bias signal, representing task rules, that enhances task-relevant information. However, the frontal cortex can also be the target of these bias signals in order to enhance abstract representations that are independent of particular stimuli or motor responses. PMID:27771559

I Plan Therefore I Choose: Free-Choice Bias Due to Prior Action-Probability but Not Action-Value

PubMed Central

Suriya-Arunroj, Lalitta; Gail, Alexander

2015-01-01

According to an emerging view, decision-making, and motor planning are tightly entangled at the level of neural processing. Choice is influenced not only by the values associated with different options, but also biased by other factors. Here we test the hypothesis that preliminary action planning can induce choice biases gradually and independently of objective value when planning overlaps with one of the potential action alternatives. Subjects performed center-out reaches obeying either a clockwise or counterclockwise cue-response rule in two tasks. In the probabilistic task, a pre-cue indicated the probability of each of the two potential rules to become valid. When the subsequent rule-cue unambiguously indicated which of the pre-cued rules was actually valid (instructed trials), subjects responded faster to rules pre-cued with higher probability. When subjects were allowed to choose freely between two equally rewarded rules (choice trials) they chose the originally more likely rule more often and faster, despite the lack of an objective advantage in selecting this target. In the amount task, the pre-cue indicated the amount of potential reward associated with each rule. Subjects responded faster to rules pre-cued with higher reward amount in instructed trials of the amount task, equivalent to the more likely rule in the probabilistic task. Yet, in contrast, subjects showed hardly any choice bias and no increase in response speed in favor of the original high-reward target in the choice trials of the amount task. We conclude that free-choice behavior is robustly biased when predictability encourages the planning of one of the potential responses, while prior reward expectations without action planning do not induce such strong bias. Our results provide behavioral evidence for distinct contributions of expected value and action planning in decision-making and a tight interdependence of motor planning and action selection, supporting the idea that the underlying neural mechanisms overlap. PMID:26635565

Significance testing of rules in rule-based models of human problem solving

NASA Technical Reports Server (NTRS)

Lewis, C. M.; Hammer, J. M.

1986-01-01

Rule-based models of human problem solving have typically not been tested for statistical significance. Three methods of testing rules - analysis of variance, randomization, and contingency tables - are presented. Advantages and disadvantages of the methods are also described.

Derivation of Optimal Operating Rules for Large-scale Reservoir Systems Considering Multiple Trade-off

NASA Astrophysics Data System (ADS)

Zhang, J.; Lei, X.; Liu, P.; Wang, H.; Li, Z.

2017-12-01

Flood control operation of multi-reservoir systems such as parallel reservoirs and hybrid reservoirs often suffer from complex interactions and trade-off among tributaries and the mainstream. The optimization of such systems is computationally intensive due to nonlinear storage curves, numerous constraints and complex hydraulic connections. This paper aims to derive the optimal flood control operating rules based on the trade-off among tributaries and the mainstream using a new algorithm known as weighted non-dominated sorting genetic algorithm II (WNSGA II). WNSGA II could locate the Pareto frontier in non-dominated region efficiently due to the directed searching by weighted crowding distance, and the results are compared with those of conventional operating rules (COR) and single objective genetic algorithm (GA). Xijiang river basin in China is selected as a case study, with eight reservoirs and five flood control sections within four tributaries and the mainstream. Furthermore, the effects of inflow uncertainty have been assessed. Results indicate that: (1) WNSGA II could locate the non-dominated solutions faster and provide better Pareto frontier than the traditional non-dominated sorting genetic algorithm II (NSGA II) due to the weighted crowding distance; (2) WNSGA II outperforms COR and GA on flood control in the whole basin; (3) The multi-objective operating rules from WNSGA II deal with the inflow uncertainties better than COR. Therefore, the WNSGA II can be used to derive stable operating rules for large-scale reservoir systems effectively and efficiently.

Game theory in models of pedestrian room evacuation

NASA Astrophysics Data System (ADS)

Bouzat, S.; Kuperman, M. N.

2014-03-01

We analyze the pedestrian evacuation of a rectangular room with a single door considering a lattice gas scheme with the addition of behavioral aspects of the pedestrians. The movement of the individuals is based on random and rational choices and is affected by conflicts between two or more agents that want to advance to the same position. Such conflicts are solved according to certain rules closely related to the concept of strategies in game theory, cooperation and defection. We consider game rules analogous to those from the Prisoner's Dilemma and Stag Hunt games, with payoffs associated to the probabilities of the individuals to advance to the selected site. We find that, even when defecting is the rational choice for any agent, under certain conditions, cooperators can take advantage from mutual cooperation and leave the room more rapidly than defectors.

Game theory in models of pedestrian room evacuation.

PubMed

Bouzat, S; Kuperman, M N

2014-03-01

We analyze the pedestrian evacuation of a rectangular room with a single door considering a lattice gas scheme with the addition of behavioral aspects of the pedestrians. The movement of the individuals is based on random and rational choices and is affected by conflicts between two or more agents that want to advance to the same position. Such conflicts are solved according to certain rules closely related to the concept of strategies in game theory, cooperation and defection. We consider game rules analogous to those from the Prisoner's Dilemma and Stag Hunt games, with payoffs associated to the probabilities of the individuals to advance to the selected site. We find that, even when defecting is the rational choice for any agent, under certain conditions, cooperators can take advantage from mutual cooperation and leave the room more rapidly than defectors.

The Calibration Reference Data System

NASA Astrophysics Data System (ADS)

Greenfield, P.; Miller, T.

2016-07-01

We describe a software architecture and implementation for using rules to determine which calibration files are appropriate for calibrating a given observation. This new system, the Calibration Reference Data System (CRDS), replaces what had been previously used for the Hubble Space Telescope (HST) calibration pipelines, the Calibration Database System (CDBS). CRDS will be used for the James Webb Space Telescope (JWST) calibration pipelines, and is currently being used for HST calibration pipelines. CRDS can be easily generalized for use in similar applications that need a rules-based system for selecting the appropriate item for a given dataset; we give some examples of such generalizations that will likely be used for JWST. The core functionality of the Calibration Reference Data System is available under an Open Source license. CRDS is briefly contrasted with a sampling of other similar systems used at other observatories.

From assessment to improvement of elderly care in general practice using decision support to increase adherence to ACOVE quality indicators: study protocol for randomized control trial

PubMed Central

2014-01-01

Background Previous efforts such as Assessing Care of Vulnerable Elders (ACOVE) provide quality indicators for assessing the care of elderly patients, but thus far little has been done to leverage this knowledge to improve care for these patients. We describe a clinical decision support system to improve general practitioner (GP) adherence to ACOVE quality indicators and a protocol for investigating impact on GPs’ adherence to the rules. Design We propose two randomized controlled trials among a group of Dutch GP teams on adherence to ACOVE quality indicators. In both trials a clinical decision support system provides un-intrusive feedback appearing as a color-coded, dynamically updated, list of items needing attention. The first trial pertains to real-time automatically verifiable rules. The second trial concerns non-automatically verifiable rules (adherence cannot be established by the clinical decision support system itself, but the GPs report whether they will adhere to the rules). In both trials we will randomize teams of GPs caring for the same patients into two groups, A and B. For the automatically verifiable rules, group A GPs receive support only for a specific inter-related subset of rules, and group B GPs receive support only for the remainder of the rules. For non-automatically verifiable rules, group A GPs receive feedback framed as actions with positive consequences, and group B GPs receive feedback framed as inaction with negative consequences. GPs indicate whether they adhere to non-automatically verifiable rules. In both trials, the main outcome measure is mean adherence, automatically derived or self-reported, to the rules. Discussion We relied on active end-user involvement in selecting the rules to support, and on a model for providing feedback displayed as color-coded real-time messages concerning the patient visiting the GP at that time, without interrupting the GP’s workflow with pop-ups. While these aspects are believed to increase clinical decision support system acceptance and its impact on adherence to the selected clinical rules, systems with these properties have not yet been evaluated. Trial registration Controlled Trials NTR3566 PMID:24642339

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.