Event-related potentials reveal the relations between feature representations at different levels of abstraction.

PubMed

Hannah, Samuel D; Shedden, Judith M; Brooks, Lee R; Grundy, John G

2016-11-01

In this paper, we use behavioural methods and event-related potentials (ERPs) to explore the relations between informational and instantiated features, as well as the relation between feature abstraction and rule type. Participants are trained to categorize two species of fictitious animals and then identify perceptually novel exemplars. Critically, two groups are given a perfectly predictive counting rule that, according to Hannah and Brooks (2009. Featuring familiarity: How a familiar feature instantiation influences categorization. Canadian Journal of Experimental Psychology/Revue Canadienne de Psychologie Expérimentale, 63, 263-275. Retrieved from http://doi.org/10.1037/a0017919), should orient them to using abstract informational features when categorizing the novel transfer items. A third group is taught a feature list rule, which should orient them to using detailed instantiated features. One counting-rule group were taught their rule before any exposure to the actual stimuli, and the other immediately after training, having learned the instantiations first. The feature-list group were also taught their rule after training. The ERP results suggest that at test, the two counting-rule groups processed items differently, despite their identical rule. This not only supports the distinction that informational and instantiated features are qualitatively different feature representations, but also implies that rules can readily operate over concrete inputs, in contradiction to traditional approaches that assume that rules necessarily act on abstract inputs.

Amino Acid Distribution Rules Predict Protein Fold: Protein Grammar for Beta-Strand Sandwich-Like Structures

PubMed Central

Kister, Alexander

2015-01-01

We present an alternative approach to protein 3D folding prediction based on determination of rules that specify distribution of “favorable” residues, that are mainly responsible for a given fold formation, and “unfavorable” residues, that are incompatible with that fold, in polypeptide sequences. The process of determining favorable and unfavorable residues is iterative. The starting assumptions are based on the general principles of protein structure formation as well as structural features peculiar to a protein fold under investigation. The initial assumptions are tested one-by-one for a set of all known proteins with a given structure. The assumption is accepted as a “rule of amino acid distribution” for the protein fold if it holds true for all, or near all, structures. If the assumption is not accepted as a rule, it can be modified to better fit the data and then tested again in the next step of the iterative search algorithm, or rejected. We determined the set of amino acid distribution rules for a large group of beta sandwich-like proteins characterized by a specific arrangement of strands in two beta sheets. It was shown that this set of rules is highly sensitive (~90%) and very specific (~99%) for identifying sequences of proteins with specified beta sandwich fold structure. The advantage of the proposed approach is that it does not require that query proteins have a high degree of homology to proteins with known structure. So long as the query protein satisfies residue distribution rules, it can be confidently assigned to its respective protein fold. Another advantage of our approach is that it allows for a better understanding of which residues play an essential role in protein fold formation. It may, therefore, facilitate rational protein engineering design. PMID:25625198

Modernization and multiscale databases at the U.S. geological survey

USGS Publications Warehouse

Morrison, J.L.

1992-01-01

The U.S. Geological Survey (USGS) has begun a digital cartographic modernization program. Keys to that program are the creation of a multiscale database, a feature-based file structure that is derived from a spatial data model, and a series of "templates" or rules that specify the relationships between instances of entities in reality and features in the database. The database will initially hold data collected from the USGS standard map products at scales of 1:24,000, 1:100,000, and 1:2,000,000. The spatial data model is called the digital line graph-enhanced model, and the comprehensive rule set consists of collection rules, product generation rules, and conflict resolution rules. This modernization program will affect the USGS mapmaking process because both digital and graphic products will be created from the database. In addition, non-USGS map users will have more flexibility in uses of the databases. These remarks are those of the session discussant made in response to the six papers and the keynote address given in the session. ?? 1992.

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

NASA Technical Reports Server (NTRS)

Anastasiadis, Stergios

1991-01-01

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

Local kernel nonparametric discriminant analysis for adaptive extraction of complex structures

NASA Astrophysics Data System (ADS)

Li, Quanbao; Wei, Fajie; Zhou, Shenghan

2017-05-01

The linear discriminant analysis (LDA) is one of popular means for linear feature extraction. It usually performs well when the global data structure is consistent with the local data structure. Other frequently-used approaches of feature extraction usually require linear, independence, or large sample condition. However, in real world applications, these assumptions are not always satisfied or cannot be tested. In this paper, we introduce an adaptive method, local kernel nonparametric discriminant analysis (LKNDA), which integrates conventional discriminant analysis with nonparametric statistics. LKNDA is adept in identifying both complex nonlinear structures and the ad hoc rule. Six simulation cases demonstrate that LKNDA have both parametric and nonparametric algorithm advantages and higher classification accuracy. Quartic unilateral kernel function may provide better robustness of prediction than other functions. LKNDA gives an alternative solution for discriminant cases of complex nonlinear feature extraction or unknown feature extraction. At last, the application of LKNDA in the complex feature extraction of financial market activities is proposed.

A neural learning classifier system with self-adaptive constructivism for mobile robot control.

PubMed

Hurst, Jacob; Bull, Larry

2006-01-01

For artificial entities to achieve true autonomy and display complex lifelike behavior, they will need to exploit appropriate adaptable learning algorithms. In this context adaptability implies flexibility guided by the environment at any given time and an open-ended ability to learn appropriate behaviors. This article examines the use of constructivism-inspired mechanisms within a neural learning classifier system architecture that exploits parameter self-adaptation as an approach to realize such behavior. The system uses a rule structure in which each rule is represented by an artificial neural network. It is shown that appropriate internal rule complexity emerges during learning at a rate controlled by the learner and that the structure indicates underlying features of the task. Results are presented in simulated mazes before moving to a mobile robot platform.

Layout optimization with assist features placement by model based rule tables for 2x node random contact

NASA Astrophysics Data System (ADS)

Jun, Jinhyuck; Park, Minwoo; Park, Chanha; Yang, Hyunjo; Yim, Donggyu; Do, Munhoe; Lee, Dongchan; Kim, Taehoon; Choi, Junghoe; Luk-Pat, Gerard; Miloslavsky, Alex

2015-03-01

As the industry pushes to ever more complex illumination schemes to increase resolution for next generation memory and logic circuits, sub-resolution assist feature (SRAF) placement requirements become increasingly severe. Therefore device manufacturers are evaluating improvements in SRAF placement algorithms which do not sacrifice main feature (MF) patterning capability. There are known-well several methods to generate SRAF such as Rule based Assist Features (RBAF), Model Based Assist Features (MBAF) and Hybrid Assisted Features combining features of the different algorithms using both RBAF and MBAF. Rule Based Assist Features (RBAF) continue to be deployed, even with the availability of Model Based Assist Features (MBAF) and Inverse Lithography Technology (ILT). Certainly for the 3x nm node, and even at the 2x nm nodes and lower, RBAF is used because it demands less run time and provides better consistency. Since RBAF is needed now and in the future, what is also needed is a faster method to create the AF rule tables. The current method typically involves making masks and printing wafers that contain several experiments, varying the main feature configurations, AF configurations, dose conditions, and defocus conditions - this is a time consuming and expensive process. In addition, as the technology node shrinks, wafer process changes and source shape redesigns occur more frequently, escalating the cost of rule table creation. Furthermore, as the demand on process margin escalates, there is a greater need for multiple rule tables: each tailored to a specific set of main-feature configurations. Model Assisted Rule Tables(MART) creates a set of test patterns, and evaluates the simulated CD at nominal conditions, defocused conditions and off-dose conditions. It also uses lithographic simulation to evaluate the likelihood of AF printing. It then analyzes the simulation data to automatically create AF rule tables. It means that analysis results display the cost of different AF configurations as the space grows between a pair of main features. In summary, model based rule tables method is able to make it much easier to create rule tables, leading to faster rule-table creation and a lower barrier to the creation of more rule tables.

A hierarchical fuzzy rule-based approach to aphasia diagnosis.

PubMed

Akbarzadeh-T, Mohammad-R; Moshtagh-Khorasani, Majid

2007-10-01

Aphasia diagnosis is a particularly challenging medical diagnostic task due to the linguistic uncertainty and vagueness, inconsistencies in the definition of aphasic syndromes, large number of measurements with imprecision, natural diversity and subjectivity in test objects as well as in opinions of experts who diagnose the disease. To efficiently address this diagnostic process, a hierarchical fuzzy rule-based structure is proposed here that considers the effect of different features of aphasia by statistical analysis in its construction. This approach can be efficient for diagnosis of aphasia and possibly other medical diagnostic applications due to its fuzzy and hierarchical reasoning construction. Initially, the symptoms of the disease which each consists of different features are analyzed statistically. The measured statistical parameters from the training set are then used to define membership functions and the fuzzy rules. The resulting two-layered fuzzy rule-based system is then compared with a back propagating feed-forward neural network for diagnosis of four Aphasia types: Anomic, Broca, Global and Wernicke. In order to reduce the number of required inputs, the technique is applied and compared on both comprehensive and spontaneous speech tests. Statistical t-test analysis confirms that the proposed approach uses fewer Aphasia features while also presenting a significant improvement in terms of accuracy.

Electronic structure, elasticity, bonding features and mechanical behaviour of zinc intermetallics: A DFT study

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

Fatima, Bushra, E-mail: bushrafatima25@gmail.com; Acharya, Nikita; Sanyal, Sankar P.

2016-05-06

The structural stability, electronic structure, elastic and mechanical properties of TiZn and ZrZn intermetallics have been studied using ab-initio full potential linearized augmented plane wave (FP-LAPW) method within generalized gradient approximation for exchange and correlation potentials. The various structural parameters, such as lattice constant (a{sub 0}), bulk modulus (B), and its pressure derivative (B’) are analysed and compared. The investigation of elastic constants affirm that both TiZn and ZrZn are elastically stable in CsCl (B{sub 2} phase) structure. The electronic structures have been analysed quantitatively from the band structure which reveals the metallic nature of these compounds. To better illustratemore » the nature of bonding and charge transfer, we have also studied the Fermi surfaces. The three well known criterion of ductility namely Pugh’s rule, Cauchy’s pressure and Frantsevich rule elucidate the ductile nature of these compounds.« less

Communication: Finding destructive interference features in molecular transport junctions.

PubMed

Reuter, Matthew G; Hansen, Thorsten

2014-11-14

Associating molecular structure with quantum interference features in electrode-molecule-electrode transport junctions has been difficult because existing guidelines for understanding interferences only apply to conjugated hydrocarbons. Herein we use linear algebra and the Landauer-Büttiker theory for electron transport to derive a general rule for predicting the existence and locations of interference features. Our analysis illustrates that interferences can be directly determined from the molecular Hamiltonian and the molecule-electrode couplings, and we demonstrate its utility with several examples.

A novel prosodic-information synthesizer based on recurrent fuzzy neural network for the Chinese TTS system.

PubMed

Lin, Chin-Teng; Wu, Rui-Cheng; Chang, Jyh-Yeong; Liang, Sheng-Fu

2004-02-01

In this paper, a new technique for the Chinese text-to-speech (TTS) system is proposed. Our major effort focuses on the prosodic information generation. New methodologies for constructing fuzzy rules in a prosodic model simulating human's pronouncing rules are developed. The proposed Recurrent Fuzzy Neural Network (RFNN) is a multilayer recurrent neural network (RNN) which integrates a Self-cOnstructing Neural Fuzzy Inference Network (SONFIN) into a recurrent connectionist structure. The RFNN can be functionally divided into two parts. The first part adopts the SONFIN as a prosodic model to explore the relationship between high-level linguistic features and prosodic information based on fuzzy inference rules. As compared to conventional neural networks, the SONFIN can always construct itself with an economic network size in high learning speed. The second part employs a five-layer network to generate all prosodic parameters by directly using the prosodic fuzzy rules inferred from the first part as well as other important features of syllables. The TTS system combined with the proposed method can behave not only sandhi rules but also the other prosodic phenomena existing in the traditional TTS systems. Moreover, the proposed scheme can even find out some new rules about prosodic phrase structure. The performance of the proposed RFNN-based prosodic model is verified by imbedding it into a Chinese TTS system with a Chinese monosyllable database based on the time-domain pitch synchronous overlap add (TD-PSOLA) method. Our experimental results show that the proposed RFNN can generate proper prosodic parameters including pitch means, pitch shapes, maximum energy levels, syllable duration, and pause duration. Some synthetic sounds are online available for demonstration.

Music acquisition: effects of enculturation and formal training on development.

PubMed

Hannon, Erin E; Trainor, Laurel J

2007-11-01

Musical structure is complex, consisting of a small set of elements that combine to form hierarchical levels of pitch and temporal structure according to grammatical rules. As with language, different systems use different elements and rules for combination. Drawing on recent findings, we propose that music acquisition begins with basic features, such as peripheral frequency-coding mechanisms and multisensory timing connections, and proceeds through enculturation, whereby everyday exposure to a particular music system creates, in a systematic order of acquisition, culture-specific brain structures and representations. Finally, we propose that formal musical training invokes domain-specific processes that affect salience of musical input and the amount of cortical tissue devoted to its processing, as well as domain-general processes of attention and executive functioning.

Seeking instructional specificity: An example from analogical instruction

NASA Astrophysics Data System (ADS)

Kuo, Eric; Wieman, Carl E.

2015-12-01

Broad instructional methods like "interactive engagement" have been shown to be effective, but such general characterization provides little guidance on the details of how to structure instructional materials. In this study, we seek instructional specificity by comparing two ways of using an analogy to learn a target physical principle: (i) applying the analogy to the target physical domain on a case-by-case basis and (ii) using the analogy to create a general rule in the target physical domain. In the discussion sections of a large, introductory physics course (N =2 3 1 ), students who sought a general rule were better able to discover and apply a correct physics principle than students who analyzed the examples case by case. The difference persisted at a reduced level after subsequent direct instruction. We argue that students who performed case-by-case analyses were more likely to focus on idiosyncratic problem-specific features rather than the deep structural features. This study provides an example of investigations into how the specific structure of instructional materials can be consequential for what is learned.

Structural classification of CDR-H3 revisited: a lesson in antibody modeling.

PubMed

Kuroda, Daisuke; Shirai, Hiroki; Kobori, Masato; Nakamura, Haruki

2008-11-15

Among the six complementarity-determining regions (CDRs) in the variable domains of an antibody, the third CDR of the heavy chain (CDR-H3), which lies in the center of the antigen-binding site, plays a particularly important role in antigen recognition. CDR-H3 shows significant variability in its length, sequence, and structure. Although difficult, model building of this segment is the most critical step in antibody modeling. Since our first proposal of the "H3-rules," which classify CDR-H3 structure based on amino acid sequence, the number of experimentally determined antibody structures has increased. Here, we revise these H3-rules and propose an improved classification scheme for CDR-H3 structure modeling. In addition, we determine the common features of CDR-H3 in antibody drugs as well as discuss the concept of "antibody druggability," which can be applied as an indicator of antibody evaluation during drug discovery.

A rule-based system for real-time analysis of control systems

NASA Astrophysics Data System (ADS)

Larson, Richard R.; Millard, D. Edward

1992-10-01

An approach to automate the real-time analysis of flight critical health monitoring and system status is being developed and evaluated at the NASA Dryden Flight Research Facility. A software package was developed in-house and installed as part of the extended aircraft interrogation and display system. This design features a knowledge-base structure in the form of rules to formulate interpretation and decision logic of real-time data. This technique has been applied for ground verification and validation testing and flight testing monitoring where quick, real-time, safety-of-flight decisions can be very critical. In many cases post processing and manual analysis of flight system data are not required. The processing is described of real-time data for analysis along with the output format which features a message stack display. The development, construction, and testing of the rule-driven knowledge base, along with an application using the X-31A flight test program, are presented.

A rule-based system for real-time analysis of control systems

NASA Technical Reports Server (NTRS)

Larson, Richard R.; Millard, D. Edward

1992-01-01

An approach to automate the real-time analysis of flight critical health monitoring and system status is being developed and evaluated at the NASA Dryden Flight Research Facility. A software package was developed in-house and installed as part of the extended aircraft interrogation and display system. This design features a knowledge-base structure in the form of rules to formulate interpretation and decision logic of real-time data. This technique has been applied for ground verification and validation testing and flight testing monitoring where quick, real-time, safety-of-flight decisions can be very critical. In many cases post processing and manual analysis of flight system data are not required. The processing is described of real-time data for analysis along with the output format which features a message stack display. The development, construction, and testing of the rule-driven knowledge base, along with an application using the X-31A flight test program, are presented.

Soft edges--organizational structure in dental education.

PubMed

Chambers, D W

1995-03-01

There is no one best organizational structure for dental schools or for their major subunits. The classical alternatives of functional and divisional organization are discussed in light of the rule that follows function, and the advantages and disadvantages of each are presented. Newer models--decentralization, matrix, and heterarchy--show how features of functional and divisional structure can be blended. Virtual organizations, systems theory, and networks are also considered as new expressions of classical structures. The principle of suboptimization (soft edges) is presented.

Background feature descriptor for offline handwritten numeral recognition

NASA Astrophysics Data System (ADS)

Ming, Delie; Wang, Hao; Tian, Tian; Jie, Feiran; Lei, Bo

2011-11-01

This paper puts forward an offline handwritten numeral recognition method based on background structural descriptor (sixteen-value numerical background expression). Through encoding the background pixels in the image according to a certain rule, 16 different eigenvalues were generated, which reflected the background condition of every digit, then reflected the structural features of the digits. Through pattern language description of images by these features, automatic segmentation of overlapping digits and numeral recognition can be realized. This method is characterized by great deformation resistant ability, high recognition speed and easy realization. Finally, the experimental results and conclusions are presented. The experimental results of recognizing datasets from various practical application fields reflect that with this method, a good recognition effect can be achieved.

THE New ROSIE (Rule Oriented System for Implementing Expertise) (Trade Name) Reference Manual and User’s Guide

DTIC Science & Technology

1987-06-01

advanced I/O operations * extended variations of the data types and control structures found in most symbolic languages Features such as rulesets and...paradigms. Because of its "general-purpose" flavor, it is less structured and more , flexible than many contemporary Al systems and tools. Nonetheless...operations. Such operations were hardwired into the language because they did not fit easily into any general linguistic -. structure . Some operations

Combined rule extraction and feature elimination in supervised classification.

PubMed

Liu, Sheng; Patel, Ronak Y; Daga, Pankaj R; Liu, Haining; Fu, Gang; Doerksen, Robert J; Chen, Yixin; Wilkins, Dawn E

2012-09-01

There are a vast number of biology related research problems involving a combination of multiple sources of data to achieve a better understanding of the underlying problems. It is important to select and interpret the most important information from these sources. Thus it will be beneficial to have a good algorithm to simultaneously extract rules and select features for better interpretation of the predictive model. We propose an efficient algorithm, Combined Rule Extraction and Feature Elimination (CRF), based on 1-norm regularized random forests. CRF simultaneously extracts a small number of rules generated by random forests and selects important features. We applied CRF to several drug activity prediction and microarray data sets. CRF is capable of producing performance comparable with state-of-the-art prediction algorithms using a small number of decision rules. Some of the decision rules are biologically significant.

An Interval Type-2 Neural Fuzzy System for Online System Identification and Feature Elimination.

PubMed

Lin, Chin-Teng; Pal, Nikhil R; Wu, Shang-Lin; Liu, Yu-Ting; Lin, Yang-Yin

2015-07-01

We propose an integrated mechanism for discarding derogatory features and extraction of fuzzy rules based on an interval type-2 neural fuzzy system (NFS)-in fact, it is a more general scheme that can discard bad features, irrelevant antecedent clauses, and even irrelevant rules. High-dimensional input variable and a large number of rules not only enhance the computational complexity of NFSs but also reduce their interpretability. Therefore, a mechanism for simultaneous extraction of fuzzy rules and reducing the impact of (or eliminating) the inferior features is necessary. The proposed approach, namely an interval type-2 Neural Fuzzy System for online System Identification and Feature Elimination (IT2NFS-SIFE), uses type-2 fuzzy sets to model uncertainties associated with information and data in designing the knowledge base. The consequent part of the IT2NFS-SIFE is of Takagi-Sugeno-Kang type with interval weights. The IT2NFS-SIFE possesses a self-evolving property that can automatically generate fuzzy rules. The poor features can be discarded through the concept of a membership modulator. The antecedent and modulator weights are learned using a gradient descent algorithm. The consequent part weights are tuned via the rule-ordered Kalman filter algorithm to enhance learning effectiveness. Simulation results show that IT2NFS-SIFE not only simplifies the system architecture by eliminating derogatory/irrelevant antecedent clauses, rules, and features but also maintains excellent performance.

Searching for substructures in fragment spaces.

PubMed

Ehrlich, Hans-Christian; Volkamer, Andrea; Rarey, Matthias

2012-12-21

A common task in drug development is the selection of compounds fulfilling specific structural features from a large data pool. While several methods that iteratively search through such data sets exist, their application is limited compared to the infinite character of molecular space. The introduction of the concept of fragment spaces (FSs), which are composed of molecular fragments and their connection rules, made the representation of large combinatorial data sets feasible. At the same time, search algorithms face the problem of structural features spanning over multiple fragments. Due to the combinatorial nature of FSs, an enumeration of all products is impossible. In order to overcome these time and storage issues, we present a method that is able to find substructures in FSs without explicit product enumeration. This is accomplished by splitting substructures into subsubstructures and mapping them onto fragments with respect to fragment connectivity rules. The method has been evaluated on three different drug discovery scenarios considering the exploration of a molecule class, the elaboration of decoration patterns for a molecular core, and the exhaustive query for peptides in FSs. FSs can be searched in seconds, and found products contain novel compounds not present in the PubChem database which may serve as hints for new lead structures.

Effects of Ga substitution on the structural and magnetic properties of half metallic Fe2MnSi Heusler compound

NASA Astrophysics Data System (ADS)

Pedro, S. S.; Caraballo Vivas, R. J.; Andrade, V. M.; Cruz, C.; Paixão, L. S.; Contreras, C.; Costa-Soares, T.; Caldeira, L.; Coelho, A. A.; Carvalho, A. Magnus G.; Rocco, D. L.; Reis, M. S.

2015-01-01

The so-called half-metallic magnets have been proposed as good candidates for spintronic applications due to the feature of exhibiting a hundred percent spin polarization at the Fermi level. Such materials follow the Slater-Pauling rule, which relates the magnetic moment with the valence electrons in the system. In this paper, we study the bulk polycrystalline half-metallic Fe2MnSi Heusler compound replacing Si by Ga to determine how the Ga addition changes the magnetic, the structural, and the half-metal properties of this compound. The material does not follow the Slater-Pauling rule, probably due to a minor structural disorder degree in the system, but a linear dependence on the magnetic transition temperature with the valence electron number points to the half-metallic behavior of this compound.

Integrated approach using data mining-based decision tree and object-based image analysis for high-resolution urban mapping of WorldView-2 satellite sensor data

NASA Astrophysics Data System (ADS)

Hamedianfar, Alireza; Shafri, Helmi Zulhaidi Mohd

2016-04-01

This paper integrates decision tree-based data mining (DM) and object-based image analysis (OBIA) to provide a transferable model for the detailed characterization of urban land-cover classes using WorldView-2 (WV-2) satellite images. Many articles have been published on OBIA in recent years based on DM for different applications. However, less attention has been paid to the generation of a transferable model for characterizing detailed urban land cover features. Three subsets of WV-2 images were used in this paper to generate transferable OBIA rule-sets. Many features were explored by using a DM algorithm, which created the classification rules as a decision tree (DT) structure from the first study area. The developed DT algorithm was applied to object-based classifications in the first study area. After this process, we validated the capability and transferability of the classification rules into second and third subsets. Detailed ground truth samples were collected to assess the classification results. The first, second, and third study areas achieved 88%, 85%, and 85% overall accuracies, respectively. Results from the investigation indicate that DM was an efficient method to provide the optimal and transferable classification rules for OBIA, which accelerates the rule-sets creation stage in the OBIA classification domain.

75 FR 22170 - Self-Regulatory Organizations; Chicago Board Options Exchange, Incorporated; Notice of Filing and...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-04-27

... Effectiveness of Proposed Rule Change To Remove a Feature and Revise Outdated Text Regarding Certain Execution... Proposed Rule Change The Exchange is proposing to eliminate a feature and revise outdated text regarding certain of its execution rules. The text of the proposed rule change is available on CBOE's Web site at...

Organized Dissonance and Emotionality: A Case Study of One Public Kindergarten in Moscow

ERIC Educational Resources Information Center

Konobeeva, E. A.

2016-01-01

This article investigates the organizational form of kindergarten through a particular case study. The article seeks to answer the question: how does kindergarten reconcile emotionality with formal rules and regulations, and how does this affect the structure of kindergarten as an organization? The features of bureaucratic and feminist…

Incidental Learning of Melodic Structure of North Indian Music

ERIC Educational Resources Information Center

Rohrmeier, Martin; Widdess, Richard

2017-01-01

Musical knowledge is largely implicit. It is acquired without awareness of its complex rules, through interaction with a large number of samples during musical enculturation. Whereas several studies explored implicit learning of mostly abstract and less ecologically valid features of Western music, very little work has been done with respect to…

A composite self tuning strategy for fuzzy control of dynamic systems

NASA Technical Reports Server (NTRS)

Shieh, C.-Y.; Nair, Satish S.

1992-01-01

The feature of self learning makes fuzzy logic controllers attractive in control applications. This paper proposes a strategy to tune the fuzzy logic controller on-line by tuning the data base as well as the rule base. The structure of the controller is outlined and preliminary results are presented using simulation studies.

Inferring the Limit Behavior of Some Elementary Cellular Automata

NASA Astrophysics Data System (ADS)

Ruivo, Eurico L. P.; de Oliveira, Pedro P. B.

Cellular automata locally define dynamical systems, discrete in space, time and in the state variables, capable of displaying arbitrarily complex global emergent behavior. One core question in the study of cellular automata refers to their limit behavior, that is, to the global dynamical features in an infinite time evolution. Previous works have shown that for finite time evolutions, the dynamics of one-dimensional cellular automata can be described by regular languages and, therefore, by finite automata. Such studies have shown the existence of growth patterns in the evolution of such finite automata for some elementary cellular automata rules and also inferred the limit behavior of such rules based upon the growth patterns; however, the results on the limit behavior were obtained manually, by direct inspection of the structures that arise during the time evolution. Here we present the formalization of an automatic method to compute such structures. Based on this, the rules of the elementary cellular automata space were classified according to the existence of a growth pattern in their finite automata. Also, we present a method to infer the limit graph of some elementary cellular automata rules, derived from the analysis of the regular expressions that describe their behavior in finite time. Finally, we analyze some attractors of two rules for which we could not compute the whole limit set.

ASICs Approach for the Implementation of a Symmetric Triangular Fuzzy Coprocessor and Its Application to Adaptive Filtering

NASA Technical Reports Server (NTRS)

Starks, Scott; Abdel-Hafeez, Saleh; Usevitch, Bryan

1997-01-01

This paper discusses the implementation of a fuzzy logic system using an ASICs design approach. The approach is based upon combining the inherent advantages of symmetric triangular membership functions and fuzzy singleton sets to obtain a novel structure for fuzzy logic system application development. The resulting structure utilizes a fuzzy static RAM to store the rule-base and the end-points of the triangular membership functions. This provides advantages over other approaches in which all sampled values of membership functions for all universes must be stored. The fuzzy coprocessor structure implements the fuzzification and defuzzification processes through a two-stage parallel pipeline architecture which is capable of executing complex fuzzy computations in less than 0.55us with an accuracy of more than 95%, thus making it suitable for a wide range of applications. Using the approach presented in this paper, a fuzzy logic rule-base can be directly downloaded via a host processor to an onchip rule-base memory with a size of 64 words. The fuzzy coprocessor's design supports up to 49 rules for seven fuzzy membership functions associated with each of the chip's two input variables. This feature allows designers to create fuzzy logic systems without the need for additional on-board memory. Finally, the paper reports on simulation studies that were conducted for several adaptive filter applications using the least mean squared adaptive algorithm for adjusting the knowledge rule-base.

Effects of Ga substitution on the structural and magnetic properties of half metallic Fe{sub 2}MnSi Heusler compound

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

Pedro, S. S., E-mail: sandrapedro@uerj.br; Caraballo Vivas, R. J.; Andrade, V. M.

2015-01-07

The so-called half-metallic magnets have been proposed as good candidates for spintronic applications due to the feature of exhibiting a hundred percent spin polarization at the Fermi level. Such materials follow the Slater-Pauling rule, which relates the magnetic moment with the valence electrons in the system. In this paper, we study the bulk polycrystalline half-metallic Fe{sub 2}MnSi Heusler compound replacing Si by Ga to determine how the Ga addition changes the magnetic, the structural, and the half-metal properties of this compound. The material does not follow the Slater-Pauling rule, probably due to a minor structural disorder degree in the system,more » but a linear dependence on the magnetic transition temperature with the valence electron number points to the half-metallic behavior of this compound.« less

Local Structure Theory for Cellular Automata.

NASA Astrophysics Data System (ADS)

Gutowitz, Howard Andrew

The local structure theory (LST) is a generalization of the mean field theory for cellular automata (CA). The mean field theory makes the assumption that iterative application of the rule does not introduce correlations between the states of cells in different positions. This assumption allows the derivation of a simple formula for the limit density of each possible state of a cell. The most striking feature of CA is that they may well generate correlations between the states of cells as they evolve. The LST takes the generation of correlation explicitly into account. It thus has the potential to describe statistical characteristics in detail. The basic assumption of the LST is that though correlation may be generated by CA evolution, this correlation decays with distance. This assumption allows the derivation of formulas for the estimation of the probability of large blocks of states in terms of smaller blocks of states. Given the probabilities of blocks of size n, probabilities may be assigned to blocks of arbitrary size such that these probability assignments satisfy the Kolmogorov consistency conditions and hence may be used to define a measure on the set of all possible (infinite) configurations. Measures defined in this way are called finite (or n-) block measures. A function called the scramble operator of order n maps a measure to an approximating n-block measure. The action of a CA on configurations induces an action on measures on the set of all configurations. The scramble operator is combined with the CA map on measure to form the local structure operator (LSO). The LSO of order n maps the set of n-block measures into itself. It is hypothesised that the LSO applied to n-block measures approximates the rule itself on general measures, and does so increasingly well as n increases. The fundamental advantage of the LSO is that its action is explicitly computable from a finite system of rational recursion equations. Empirical study of a number of CA rules demonstrates the potential of the LST to describe the statistical features of CA. The behavior of some simple rules is derived analytically. Other rules have more complex, chaotic behavior. Even for these rules, the LST yields an accurate portrait of both small and large time statistics.

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

PubMed

Nguyen, M N

2010-04-01

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

Null Models for Everyone: A Two-Step Approach to Teaching Null Model Analysis of Biological Community Structure

ERIC Educational Resources Information Center

McCabe, Declan J.; Knight, Evelyn J.

2016-01-01

Since being introduced by Connor and Simberloff in response to Diamond's assembly rules, null model analysis has been a controversial tool in community ecology. Despite being commonly used in the primary literature, null model analysis has not featured prominently in general textbooks. Complexity of approaches along with difficulty in interpreting…

77 FR 64025 - Special Conditions: Airbus Model A318, A319, A320, and A321 Series Airplanes; Interaction of...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-10-18

... series airplanes with modification 160023 (Sharklet). These airplanes will have novel or unusual design... novel or unusual design features on the model series of airplanes listed above. It is not a rule of... Series Airplanes; Interaction of Systems and Structures AGENCY: Federal Aviation Administration (FAA...

The role of emotion in musical improvisation: an analysis of structural features.

PubMed

McPherson, Malinda J; Lopez-Gonzalez, Monica; Rankin, Summer K; Limb, Charles J

2014-01-01

One of the primary functions of music is to convey emotion, yet how music accomplishes this task remains unclear. For example, simple correlations between mode (major vs. minor) and emotion (happy vs. sad) do not adequately explain the enormous range, subtlety or complexity of musically induced emotions. In this study, we examined the structural features of unconstrained musical improvisations generated by jazz pianists in response to emotional cues. We hypothesized that musicians would not utilize any universal rules to convey emotions, but would instead combine heterogeneous musical elements together in order to depict positive and negative emotions. Our findings demonstrate a lack of simple correspondence between emotions and musical features of spontaneous musical improvisation. While improvisations in response to positive emotional cues were more likely to be in major keys, have faster tempos, faster key press velocities and more staccato notes when compared to negative improvisations, there was a wide distribution for each emotion with components that directly violated these primary associations. The finding that musicians often combine disparate features together in order to convey emotion during improvisation suggests that structural diversity may be an essential feature of the ability of music to express a wide range of emotion.

The Role of Emotion in Musical Improvisation: An Analysis of Structural Features

PubMed Central

McPherson, Malinda J.; Lopez-Gonzalez, Monica; Rankin, Summer K.; Limb, Charles J.

2014-01-01

One of the primary functions of music is to convey emotion, yet how music accomplishes this task remains unclear. For example, simple correlations between mode (major vs. minor) and emotion (happy vs. sad) do not adequately explain the enormous range, subtlety or complexity of musically induced emotions. In this study, we examined the structural features of unconstrained musical improvisations generated by jazz pianists in response to emotional cues. We hypothesized that musicians would not utilize any universal rules to convey emotions, but would instead combine heterogeneous musical elements together in order to depict positive and negative emotions. Our findings demonstrate a lack of simple correspondence between emotions and musical features of spontaneous musical improvisation. While improvisations in response to positive emotional cues were more likely to be in major keys, have faster tempos, faster key press velocities and more staccato notes when compared to negative improvisations, there was a wide distribution for each emotion with components that directly violated these primary associations. The finding that musicians often combine disparate features together in order to convey emotion during improvisation suggests that structural diversity may be an essential feature of the ability of music to express a wide range of emotion. PMID:25144200

ChemStable: a web server for rule-embedded naïve Bayesian learning approach to predict compound stability.

PubMed

Liu, Zhihong; Zheng, Minghao; Yan, Xin; Gu, Qiong; Gasteiger, Johann; Tijhuis, Johan; Maas, Peter; Li, Jiabo; Xu, Jun

2014-09-01

Predicting compound chemical stability is important because unstable compounds can lead to either false positive or to false negative conclusions in bioassays. Experimental data (COMDECOM) measured from DMSO/H2O solutions stored at 50 °C for 105 days were used to predicted stability by applying rule-embedded naïve Bayesian learning, based upon atom center fragment (ACF) features. To build the naïve Bayesian classifier, we derived ACF features from 9,746 compounds in the COMDECOM dataset. By recursively applying naïve Bayesian learning from the data set, each ACF is assigned with an expected stable probability (p(s)) and an unstable probability (p(uns)). 13,340 ACFs, together with their p(s) and p(uns) data, were stored in a knowledge base for use by the Bayesian classifier. For a given compound, its ACFs were derived from its structure connection table with the same protocol used to drive ACFs from the training data. Then, the Bayesian classifier assigned p(s) and p(uns) values to the compound ACFs by a structural pattern recognition algorithm, which was implemented in-house. Compound instability is calculated, with Bayes' theorem, based upon the p(s) and p(uns) values of the compound ACFs. We were able to achieve performance with an AUC value of 84% and a tenfold cross validation accuracy of 76.5%. To reduce false negatives, a rule-based approach has been embedded in the classifier. The rule-based module allows the program to improve its predictivity by expanding its compound instability knowledge base, thus further reducing the possibility of false negatives. To our knowledge, this is the first in silico prediction service for the prediction of the stabilities of organic compounds.

Report on the FY17 Development of Computer Program for ASME Section III, Division 5, Subsection HB, Subpart B Rules

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

Swindeman, M. J.; Jetter, R. I.; Sham, T. -L.

One of the objectives of the high temperature design methodology activities is to develop and validate both improvements and the basic features of ASME Boiler and Pressure Vessel Code, Section III, Rules for Construction of Nuclear Facility Components, Division 5, High Temperature Reactors, Subsection HB, Subpart B (HBB). The overall scope of this task is to develop a computer program to aid assessment procedures of components under specified loading conditions in accordance with the elevated temperature design requirements for Division 5 Class A components. There are many features and alternative paths of varying complexity in HBB. The initial focus ofmore » this computer program is a basic path through the various options for a single reference material, 316H stainless steel. However, the computer program is being structured for eventual incorporation all of the features and permitted materials of HBB. This report will first provide a description of the overall computer program, particular challenges in developing numerical procedures for the assessment, and an overall approach to computer program development. This is followed by a more comprehensive appendix, which is the draft computer program manual for the program development. The strain limits rules have been implemented in the computer program. The evaluation of creep-fatigue damage will be implemented in future work scope.« less

Emergence of structural patterns out of synchronization in networks with competitive interactions

NASA Astrophysics Data System (ADS)

Assenza, Salvatore; Gutiérrez, Ricardo; Gómez-Gardeñes, Jesús; Latora, Vito; Boccaletti, Stefano

2011-09-01

Synchronization is a collective phenomenon occurring in systems of interacting units, and is ubiquitous in nature, society and technology. Recent studies have enlightened the important role played by the interaction topology on the emergence of synchronized states. However, most of these studies neglect that real world systems change their interaction patterns in time. Here, we analyze synchronization features in networks in which structural and dynamical features co-evolve. The feedback of the node dynamics on the interaction pattern is ruled by the competition of two mechanisms: homophily (reinforcing those interactions with other correlated units in the graph) and homeostasis (preserving the value of the input strength received by each unit). The competition between these two adaptive principles leads to the emergence of key structural properties observed in real world networks, such as modular and scale-free structures, together with a striking enhancement of local synchronization in systems with no global order.

AUTOGEN

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

2003-05-29

AUTOGEN computes collision-free sequences of robot motion instructions to permit traversal of three-dimensional space curves. Order and direction of curve traversal and orientation of end effector are constraided by a set of manufacturing rules. Input can be provided as a collection of solid models or in terms of wireframe objects and structural cross-section definitions. Entity juxtaposition can be inferred, with appropriate structural features automatically provided. Process control is asserted as a function of position and orientation along each space curve, and is currently implemented for welding processes.

Distributed rewiring model for complex networking: The effect of local rewiring rules on final structural properties.

PubMed

López Chavira, Magali Alexander; Marcelín-Jiménez, Ricardo

2017-01-01

The study of complex networks has become an important subject over the last decades. It has been shown that these structures have special features, such as their diameter, or their average path length, which in turn are the explanation of some functional properties in a system such as its fault tolerance, its fragility before attacks, or the ability to support routing procedures. In the present work, we study some of the forces that help a network to evolve to the point where structural properties are settled. Although our work is mainly focused on the possibility of applying our ideas to Information and Communication Technologies systems, we consider that our results may contribute to understanding different scenarios where complex networks have become an important modeling tool. Using a discrete event simulator, we get each node to discover the shortcuts that may connect it with regions away from its local environment. Based on this partial knowledge, each node can rewire some of its links, which allows modifying the topology of the entire underlying graph to achieve new structural properties. We proposed a distributed rewiring model that creates networks with features similar to those found in complex networks. Although each node acts in a distributed way and seeking to reduce only the trajectories of its packets, we observed a decrease of diameter and an increase in clustering coefficient in the global structure compared to the initial graph. Furthermore, we can find different final structures depending on slight changes in the local rewiring rules.

Two distinct superconducting phases in LiFeAs

PubMed Central

Nag, P. K.; Schlegel, R.; Baumann, D.; Grafe, H.-J.; Beck, R.; Wurmehl, S.; Büchner, B.; Hess, C.

2016-01-01

A non-trivial temperature evolution of superconductivity including a temperature-induced phase transition between two superconducting phases or even a time-reversal symmetry breaking order parameter is in principle expected in multiband superconductors such as iron-pnictides. Here we present scanning tunnelling spectroscopy data of LiFeAs which reveal two distinct superconducting phases: at = 18 K a partial superconducting gap opens, evidenced by subtle, yet clear features in the tunnelling spectra, i.e. particle-hole symmetric coherence peak and dip-hump structures. At Tc = 16 K, these features substantiate dramatically and become characteristic of full superconductivity. Remarkably, the distance between the dip-hump structures and the coherence peaks remains practically constant in the whole temperature regimeT ≤ . This rules out the connection of the dip-hump structures to an antiferromagnetic spin resonance. PMID:27297474

Simple ultrasound rules to distinguish between benign and malignant adnexal masses before surgery: prospective validation by IOTA group

PubMed Central

Ameye, Lieveke; Fischerova, Daniela; Epstein, Elisabeth; Melis, Gian Benedetto; Guerriero, Stefano; Van Holsbeke, Caroline; Savelli, Luca; Fruscio, Robert; Lissoni, Andrea Alberto; Testa, Antonia Carla; Veldman, Joan; Vergote, Ignace; Van Huffel, Sabine; Bourne, Tom; Valentin, Lil

2010-01-01

Objectives To prospectively assess the diagnostic performance of simple ultrasound rules to predict benignity/malignancy in an adnexal mass and to test the performance of the risk of malignancy index, two logistic regression models, and subjective assessment of ultrasonic findings by an experienced ultrasound examiner in adnexal masses for which the simple rules yield an inconclusive result. Design Prospective temporal and external validation of simple ultrasound rules to distinguish benign from malignant adnexal masses. The rules comprised five ultrasonic features (including shape, size, solidity, and results of colour Doppler examination) to predict a malignant tumour (M features) and five to predict a benign tumour (B features). If one or more M features were present in the absence of a B feature, the mass was classified as malignant. If one or more B features were present in the absence of an M feature, it was classified as benign. If both M features and B features were present, or if none of the features was present, the simple rules were inconclusive. Setting 19 ultrasound centres in eight countries. Participants 1938 women with an adnexal mass examined with ultrasound by the principal investigator at each centre with a standardised research protocol. Reference standard Histological classification of the excised adnexal mass as benign or malignant. Main outcome measures Diagnostic sensitivity and specificity. Results Of the 1938 patients with an adnexal mass, 1396 (72%) had benign tumours, 373 (19.2%) had primary invasive tumours, 111 (5.7%) had borderline malignant tumours, and 58 (3%) had metastatic tumours in the ovary. The simple rules yielded a conclusive result in 1501 (77%) masses, for which they resulted in a sensitivity of 92% (95% confidence interval 89% to 94%) and a specificity of 96% (94% to 97%). The corresponding sensitivity and specificity of subjective assessment were 91% (88% to 94%) and 96% (94% to 97%). In the 357 masses for which the simple rules yielded an inconclusive result and with available results of CA-125 measurements, the sensitivities were 89% (83% to 93%) for subjective assessment, 50% (42% to 58%) for the risk of malignancy index, 89% (83% to 93%) for logistic regression model 1, and 82% (75% to 87%) for logistic regression model 2; the corresponding specificities were 78% (72% to 83%), 84% (78% to 88%), 44% (38% to 51%), and 48% (42% to 55%). Use of the simple rules as a triage test and subjective assessment for those masses for which the simple rules yielded an inconclusive result gave a sensitivity of 91% (88% to 93%) and a specificity of 93% (91% to 94%), compared with a sensitivity of 90% (88% to 93%) and a specificity of 93% (91% to 94%) when subjective assessment was used in all masses. Conclusions The use of the simple rules has the potential to improve the management of women with adnexal masses. In adnexal masses for which the rules yielded an inconclusive result, subjective assessment of ultrasonic findings by an experienced ultrasound examiner was the most accurate diagnostic test; the risk of malignancy index and the two regression models were not useful. PMID:21156740

The P600 in Implicit Artificial Grammar Learning

ERIC Educational Resources Information Center

Silva, Susana; Folia, Vasiliki; Hagoort, Peter; Petersson, Karl Magnus

2017-01-01

The suitability of the artificial grammar learning (AGL) paradigm to capture relevant aspects of the acquisition of linguistic structures has been empirically tested in a number of EEG studies. Some have shown a syntax-related P600 component, but it has not been ruled out that the AGL P600 effect is a response to surface features (e.g.,…

Non-conventional rule of making a periodically varying different-pole magnetic field in low-power alternating current electrical machines with using ring coils in multiphase armature winding

NASA Astrophysics Data System (ADS)

Plastun, A. T.; Tikhonova, O. V.; Malygin, I. V.

2018-02-01

The paper presents methods of making a periodically varying different-pole magnetic field in low-power electrical machines. Authors consider classical designs of electrical machines and machines with ring windings in armature, structural features and calculated parameters of magnetic circuit for these machines.

An Eye-Tracking Study of Multiple Feature Value Category Structure Learning: The Role of Unique Features

PubMed Central

Liu, Zhiya; Song, Xiaohong; Seger, Carol A.

2015-01-01

We examined whether the degree to which a feature is uniquely characteristic of a category can affect categorization above and beyond the typicality of the feature. We developed a multiple feature value category structure with different dimensions within which feature uniqueness and typicality could be manipulated independently. Using eye tracking, we found that the highest attentional weighting (operationalized as number of fixations, mean fixation time, and the first fixation of the trial) was given to a dimension that included a feature that was both unique and highly typical of the category. Dimensions that included features that were highly typical but not unique, or were unique but not highly typical, received less attention. A dimension with neither a unique nor a highly typical feature received least attention. On the basis of these results we hypothesized that subjects categorized via a rule learning procedure in which they performed an ordered evaluation of dimensions, beginning with unique and strongly typical dimensions, and in which earlier dimensions received higher weighting in the decision. This hypothesis accounted for performance on transfer stimuli better than simple implementations of two other common theories of category learning, exemplar models and prototype models, in which all dimensions were evaluated in parallel and received equal weighting. PMID:26274332

An Eye-Tracking Study of Multiple Feature Value Category Structure Learning: The Role of Unique Features.

PubMed

Liu, Zhiya; Song, Xiaohong; Seger, Carol A

2015-01-01

We examined whether the degree to which a feature is uniquely characteristic of a category can affect categorization above and beyond the typicality of the feature. We developed a multiple feature value category structure with different dimensions within which feature uniqueness and typicality could be manipulated independently. Using eye tracking, we found that the highest attentional weighting (operationalized as number of fixations, mean fixation time, and the first fixation of the trial) was given to a dimension that included a feature that was both unique and highly typical of the category. Dimensions that included features that were highly typical but not unique, or were unique but not highly typical, received less attention. A dimension with neither a unique nor a highly typical feature received least attention. On the basis of these results we hypothesized that subjects categorized via a rule learning procedure in which they performed an ordered evaluation of dimensions, beginning with unique and strongly typical dimensions, and in which earlier dimensions received higher weighting in the decision. This hypothesis accounted for performance on transfer stimuli better than simple implementations of two other common theories of category learning, exemplar models and prototype models, in which all dimensions were evaluated in parallel and received equal weighting.

Rules for the recognition of dilysine retrieval motifs by coatomer

PubMed Central

Ma, Wenfu; Goldberg, Jonathan

2013-01-01

Cytoplasmic dilysine motifs on transmembrane proteins are captured by coatomer α-COP and β′-COP subunits and packaged into COPI-coated vesicles for Golgi-to-ER retrieval. Numerous ER/Golgi proteins contain K(x)Kxx motifs, but the rules for their recognition are unclear. We present crystal structures of α-COP and β′-COP bound to a series of naturally occurring retrieval motifs—encompassing KKxx, KxKxx and non-canonical RKxx and viral KxHxx sequences. Binding experiments show that α-COP and β′-COP have generally the same specificity for KKxx and KxKxx, but only β′-COP recognizes the RKxx signal. Dilysine motif recognition involves lysine side-chain interactions with two acidic patches. Surprisingly, however, KKxx and KxKxx motifs bind differently, with their lysine residues transposed at the binding patches. We derive rules for retrieval motif recognition from key structural features: the reversed binding modes, the recognition of the C-terminal carboxylate group which enforces lysine positional context, and the tolerance of the acidic patches for non-lysine residues. PMID:23481256

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.

Electron-Poor Polar Intermetallics: Complex Structures, Novel Clusters, and Intriguing Bonding with Pronounced Electron Delocalization

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

Lin, Qisheng; Miller, Gordon J.

Intermetallic compounds represent an extensive pool of candidates for energy related applications stemming from magnetic, electric, optic, caloric, and catalytic properties. The discovery of novel intermetallic compounds can enhance understanding of the chemical principles that govern structural stability and chemical bonding as well as finding new applications. Valence electron-poor polar intermetallics with valence electron concentrations (VECs) between 2.0 and 3.0 e –/atom show a plethora of unprecedented and fascinating structural motifs and bonding features. Furthermore, establishing simple structure-bonding-property relationships is especially challenging for this compound class because commonly accepted valence electron counting rules are inappropriate.

Electron-Poor Polar Intermetallics: Complex Structures, Novel Clusters, and Intriguing Bonding with Pronounced Electron Delocalization

DOE PAGES

Lin, Qisheng; Miller, Gordon J.

2017-12-18

Intermetallic compounds represent an extensive pool of candidates for energy related applications stemming from magnetic, electric, optic, caloric, and catalytic properties. The discovery of novel intermetallic compounds can enhance understanding of the chemical principles that govern structural stability and chemical bonding as well as finding new applications. Valence electron-poor polar intermetallics with valence electron concentrations (VECs) between 2.0 and 3.0 e –/atom show a plethora of unprecedented and fascinating structural motifs and bonding features. Furthermore, establishing simple structure-bonding-property relationships is especially challenging for this compound class because commonly accepted valence electron counting rules are inappropriate.

Knowledge Discovery in Variant Databases Using Inductive Logic Programming

PubMed Central

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

2013-01-01

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

Knowledge discovery in variant databases using inductive logic programming.

PubMed

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

2013-01-01

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

Knowledge-based approach to video content classification

NASA Astrophysics Data System (ADS)

Chen, Yu; Wong, Edward K.

2001-01-01

A framework for video content classification using a knowledge-based approach is herein proposed. This approach is motivated by the fact that videos are rich in semantic contents, which can best be interpreted and analyzed by human experts. We demonstrate the concept by implementing a prototype video classification system using the rule-based programming language CLIPS 6.05. Knowledge for video classification is encoded as a set of rules in the rule base. The left-hand-sides of rules contain high level and low level features, while the right-hand-sides of rules contain intermediate results or conclusions. Our current implementation includes features computed from motion, color, and text extracted from video frames. Our current rule set allows us to classify input video into one of five classes: news, weather, reporting, commercial, basketball and football. We use MYCIN's inexact reasoning method for combining evidences, and to handle the uncertainties in the features and in the classification results. We obtained good results in a preliminary experiment, and it demonstrated the validity of the proposed approach.

Knowledge-based approach to video content classification

NASA Astrophysics Data System (ADS)

Chen, Yu; Wong, Edward K.

2000-12-01

A framework for video content classification using a knowledge-based approach is herein proposed. This approach is motivated by the fact that videos are rich in semantic contents, which can best be interpreted and analyzed by human experts. We demonstrate the concept by implementing a prototype video classification system using the rule-based programming language CLIPS 6.05. Knowledge for video classification is encoded as a set of rules in the rule base. The left-hand-sides of rules contain high level and low level features, while the right-hand-sides of rules contain intermediate results or conclusions. Our current implementation includes features computed from motion, color, and text extracted from video frames. Our current rule set allows us to classify input video into one of five classes: news, weather, reporting, commercial, basketball and football. We use MYCIN's inexact reasoning method for combining evidences, and to handle the uncertainties in the features and in the classification results. We obtained good results in a preliminary experiment, and it demonstrated the validity of the proposed approach.

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.

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

78 FR 35650 - Self-Regulatory Organizations; Chicago Board Options Exchange, Incorporated; Notice of Filing and...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-06-13

... this new AIM feature will function as described in rule filing SR-CBOE-2013- 048. B. Self-Regulatory... the necessary system work and perform sufficient testing to ensure that this new AIM feature functions... Effectiveness of a Proposed Rule Change Relating to Rule 6.74A June 7, 2013. Pursuant to Section 19(b)(1) of the...

Assessing the impact of representational and contextual problem features on student use of right-hand rules

NASA Astrophysics Data System (ADS)

Kustusch, Mary Bridget

2016-06-01

Students in introductory physics struggle with vector algebra and these challenges are often associated with contextual and representational features of the problems. Performance on problems about cross product direction is particularly poor and some research suggests that this may be primarily due to misapplied right-hand rules. However, few studies have had the resolution to explore student use of right-hand rules in detail. This study reviews literature in several disciplines, including spatial cognition, to identify ten contextual and representational problem features that are most likely to influence performance on problems requiring a right-hand rule. Two quantitative measures of performance (correctness and response time) and two qualitative measures (methods used and type of errors made) were used to explore the impact of these problem features on student performance. Quantitative results are consistent with expectations from the literature, but reveal that some features (such as the type of reasoning required and the physical awkwardness of using a right-hand rule) have a greater impact than others (such as whether the vectors are placed together or separate). Additional insight is gained by the qualitative analysis, including identifying sources of difficulty not previously discussed in the literature and revealing that the use of supplemental methods, such as physically rotating the paper, can mitigate errors associated with certain features.

Mapping three-dimensional geological features from remotely-sensed images and digital elevation models

NASA Astrophysics Data System (ADS)

Morris, Kevin Peter

Accurate mapping of geological structures is important in numerous applications, ranging from mineral exploration through to hydrogeological modelling. Remotely sensed data can provide synoptic views of study areas enabling mapping of geological units within the area. Structural information may be derived from such data using standard manual photo-geologic interpretation techniques, although these are often inaccurate and incomplete. The aim of this thesis is, therefore, to compile a suite of automated and interactive computer-based analysis routines, designed to help a the user map geological structure. These are examined and integrated in the context of an expert system. The data used in this study include Digital Elevation Model (DEM) and Airborne Thematic Mapper images, both with a spatial resolution of 5m, for a 5 x 5 km area surrounding Llyn Cow lyd, Snowdonia, North Wales. The geology of this area comprises folded and faulted Ordo vician sediments intruded throughout by dolerite sills, providing a stringent test for the automated and semi-automated procedures. The DEM is used to highlight geomorphological features which may represent surface expressions of the sub-surface geology. The DEM is created from digitized contours, for which kriging is found to provide the best interpolation routine, based on a number of quantitative measures. Lambertian shading and the creation of slope and change of slope datasets are shown to provide the most successful enhancement of DEMs, in terms of highlighting a range of key geomorphological features. The digital image data are used to identify rock outcrops as well as lithologically controlled features in the land cover. To this end, a series of standard spectral enhancements of the images is examined. In this respect, the least correlated 3 band composite and a principal component composite are shown to give the best visual discrimination of geological and vegetation cover types. Automatic edge detection (followed by line thinning and extraction) and manual interpretation techniques are used to identify a set of 'geological primitives' (linear or arc features representing lithological boundaries) within these data. Inclusion of the DEM data provides the three-dimensional co-ordinates of these primitives enabling a least-squares fit to be employed to calculate dip and strike values, based, initially, on the assumption of a simple, linearly dipping structural model. A very large number of scene 'primitives' is identified using these procedures, only some of which have geological significance. Knowledge-based rules are therefore used to identify the relevant. For example, rules are developed to identify lake edges, forest boundaries, forest tracks, rock-vegetation boundaries, and areas of geomorphological interest. Confidence in the geological significance of some of the geological primitives is increased where they are found independently in both the DEM and remotely sensed data. The dip and strike values derived in this way are compared to information taken from the published geological map for this area, as well as measurements taken in the field. Many results are shown to correspond closely to those taken from the map and in the field, with an error of < 1°. These data and rules are incorporated into an expert system which, initially, produces a simple model of the geological structure. The system also provides a graphical user interface for manual control and interpretation, where necessary. Although the system currently only allows a relatively simple structural model (linearly dipping with faulting), in the future it will be possible to extend the system to model more complex features, such as anticlines, synclines, thrusts, nappes, and igneous intrusions.

Measurement of Electronic States of PbS Nanocrystal Quantum Dots Using Scanning Tunneling Spectroscopy: The Role of Parity Selection Rules in Optical Absorption

NASA Astrophysics Data System (ADS)

Diaconescu, Bogdan; Padilha, Lazaro A.; Nagpal, Prashant; Swartzentruber, Brian S.; Klimov, Victor I.

2013-03-01

We study the structure of electronic states in individual PbS nanocrystal quantum dots by scanning tunneling spectroscopy (STS) using one-to-two monolayer nanocrystal films treated with 1, 2-ethanedithiols (EDT). Up to six individual valence and conduction band states are resolved for a range of quantum dot sizes. The measured states’ energies are in good agreement with calculations using the k·p four-band envelope function formalism. A comparison of STS and optical absorption spectra indicates that some of the absorption features can only be explained by asymmetric transitions involving the states of different symmetries (e.g., S and P or P and D), which points towards the relaxation of the parity selection rules in these nanostructures. STS measurements also reveal a midgap feature, which is likely similar to one observed in previous charge transport studies of EDT-treated quantum dot films.

A new modulated Hebbian learning rule--biologically plausible method for local computation of a principal subspace.

PubMed

Jankovic, Marko; Ogawa, Hidemitsu

2003-08-01

This paper presents one possible implementation of a transformation that performs linear mapping to a lower-dimensional subspace. Principal component subspace will be the one that will be analyzed. Idea implemented in this paper represents generalization of the recently proposed infinity OH neural method for principal component extraction. The calculations in the newly proposed method are performed locally--a feature which is usually considered as desirable from the biological point of view. Comparing to some other wellknown methods, proposed synaptic efficacy learning rule requires less information about the value of the other efficacies to make single efficacy modification. Synaptic efficacies are modified by implementation of Modulated Hebb-type (MH) learning rule. Slightly modified MH algorithm named Modulated Hebb Oja (MHO) algorithm, will be also introduced. Structural similarity of the proposed network with part of the retinal circuit will be presented, too.

Features of development process displacement of earth’s surface when dredging coal in Eastern Donbas

NASA Astrophysics Data System (ADS)

Posylniy, Yu V.; Versilov, S. O.; Shurygin, D. N.; Kalinchenko, V. M.

2017-10-01

The results of studies of the process of the earth’s surface displacement due to the influence of the adjacent longwalls are presented. It is established that the actual distributions of soil subsidence in the fall and revolt of the reservoir with the same boundary settlement processes differ both from each other and by the distribution of subsidence, recommended by the rules of structures protection. The application of the new boundary criteria - the relative subsidence of 0.03 - allows one to go from two distributions to one distribution, which is also different from the sedimentation distribution of protection rules. The use of a new geometrical element - a virtual point of the mould - allows one to transform the actual distribution of subsidence in the model distribution of rules of constructions protection. When transforming the curves of subsidence, the boundary points vary and, consequently, the boundary corners do.

Addressing the ethical issues raised by synthetic human entities with embryo-like features

PubMed Central

Aach, John; Lunshof, Jeantine; Iyer, Eswar; Church, George M

2017-01-01

The "14-day rule" for embryo research stipulates that experiments with intact human embryos must not allow them to develop beyond 14 days or the appearance of the primitive streak. However, recent experiments showing that suitably cultured human pluripotent stem cells can self-organize and recapitulate embryonic features have highlighted difficulties with the 14-day rule and led to calls for its reassessment. Here we argue that these and related experiments raise more foundational issues that cannot be fixed by adjusting the 14-day rule, because the framework underlying the rule cannot adequately describe the ways by which synthetic human entities with embryo-like features (SHEEFs) might develop morally concerning features through altered forms of development. We propose that limits on research with SHEEFs be based as directly as possible on the generation of such features, and recommend that the research and bioethics communities lead a wide-ranging inquiry aimed at mapping out solutions to the ethical problems raised by them. DOI: http://dx.doi.org/10.7554/eLife.20674.001 PMID:28494856

Silica deposits on Mars with features resembling hot spring biosignatures at El Tatio in Chile

PubMed Central

Ruff, Steven W.; Farmer, Jack D.

2016-01-01

The Mars rover Spirit encountered outcrops and regolith composed of opaline silica (amorphous SiO2·nH2O) in an ancient volcanic hydrothermal setting in Gusev crater. An origin via either fumarole-related acid-sulfate leaching or precipitation from hot spring fluids was suggested previously. However, the potential significance of the characteristic nodular and mm-scale digitate opaline silica structures was not recognized. Here we report remarkably similar features within active hot spring/geyser discharge channels at El Tatio in northern Chile, where halite-encrusted silica yields infrared spectra that are the best match yet to spectra from Spirit. Furthermore, we show that the nodular and digitate silica structures at El Tatio that most closely resemble those on Mars include complex sedimentary structures produced by a combination of biotic and abiotic processes. Although fully abiotic processes are not ruled out for the Martian silica structures, they satisfy an a priori definition of potential biosignatures. PMID:27853166

Coping with Novelty and Human Intelligence: The Role of Counterfactual Reasoning

DTIC Science & Technology

1988-01-01

terminating relevance tests. Relevance is determined by checking whether the conceptual relation in the precue matches that in the item of the problem...found that experts tend to conceptualize dumain-related problems in abstract terms, whereas nonexperts apparently rely more on surface-level features...finally, the effects of the two surface-structural rule manipulations might for all subjects be partly due to perceptual, rather than conceptual

KOSMOS: a universal morph server for nucleic acids, proteins and their complexes.

PubMed

Seo, Sangjae; Kim, Moon Ki

2012-07-01

KOSMOS is the first online morph server to be able to address the structural dynamics of DNA/RNA, proteins and even their complexes, such as ribosomes. The key functions of KOSMOS are the harmonic and anharmonic analyses of macromolecules. In the harmonic analysis, normal mode analysis (NMA) based on an elastic network model (ENM) is performed, yielding vibrational modes and B-factor calculations, which provide insight into the potential biological functions of macromolecules based on their structural features. Anharmonic analysis involving elastic network interpolation (ENI) is used to generate plausible transition pathways between two given conformations by optimizing a topology-oriented cost function that guarantees a smooth transition without steric clashes. The quality of the computed pathways is evaluated based on their various facets, including topology, energy cost and compatibility with the NMA results. There are also two unique features of KOSMOS that distinguish it from other morph servers: (i) the versatility in the coarse-graining methods and (ii) the various connection rules in the ENM. The models enable us to analyze macromolecular dynamics with the maximum degrees of freedom by combining a variety of ENMs from full-atom to coarse-grained, backbone and hybrid models with one connection rule, such as distance-cutoff, number-cutoff or chemical-cutoff. KOSMOS is available at http://bioengineering.skku.ac.kr/kosmos.

Wavelet tree structure based speckle noise removal for optical coherence tomography

NASA Astrophysics Data System (ADS)

Yuan, Xin; Liu, Xuan; Liu, Yang

2018-02-01

We report a new speckle noise removal algorithm in optical coherence tomography (OCT). Though wavelet domain thresholding algorithms have demonstrated superior advantages in suppressing noise magnitude and preserving image sharpness in OCT, the wavelet tree structure has not been investigated in previous applications. In this work, we propose an adaptive wavelet thresholding algorithm via exploiting the tree structure in wavelet coefficients to remove the speckle noise in OCT images. The threshold for each wavelet band is adaptively selected following a special rule to retain the structure of the image across different wavelet layers. Our results demonstrate that the proposed algorithm outperforms conventional wavelet thresholding, with significant advantages in preserving image features.

Modifying Intramural Rules.

ERIC Educational Resources Information Center

Rokosz, Francis M.

1981-01-01

Standard sports rules can be altered to improve the game for intramural participants. These changes may improve players' attitudes, simplify rules for officials, and add safety features to a game. Specific rule modifications are given for volleyball, football, softball, floor hockey, basketball, and soccer. (JN)

Optimal descriptor as a translator of eclectic information into the prediction of membrane damage by means of various TiO(2) nanoparticles.

PubMed

Toropova, Alla P; Toropov, Andrey A

2013-11-01

The increasing use of nanomaterials incorporated into consumer products leads to the need for developing approaches to establish "quantitative structure-activity relationships" (QSARs) for various nanomaterials. However, the molecular structure as rule is not available for nanomaterials at least in its classic meaning. An possible alternative of classic QSAR (based on the molecular structure) is the using of data on physicochemical features of TiO(2) nanoparticles. The damage to cellular membranes (units L(-1)) by means of various TiO(2) nanoparticles is examined as the endpoint. Copyright © 2013 Elsevier Ltd. All rights reserved.

Multiple Grammars and the Logic of Learnability in Second Language Acquisition.

PubMed

Roeper, Tom W

2016-01-01

The core notion of modern Universal Grammar is that language ability requires abstract representation in terms of hierarchy, movement operations, abstract features on words, and fixed mapping to meaning. These mental structures are a step toward integrating representational knowledge of all kinds into a larger model of cognitive psychology. Examining first and second language at once provides clues as to how abstractly we should represent this knowledge. The abstract nature of grammar allows both the formulation of many grammars and the possibility that a rule of one grammar could apply to another grammar. We argue that every language contains Multiple Grammars which may reflect different language families. We develop numerous examples of how the same abstract rules can apply in various languages and develop a theory of how language modules (case-marking, topicalization, and quantification) interact to predict L2 acquisition paths. In particular we show in depth how Germanic Verb-second operations, based on Verb-final structure, can apply in English. The argument is built around how and where V2 from German can apply in English, seeking to explain the crucial contrast: "nothing" yelled out Bill/(*)"nothing" yelled Bill out in terms of the necessary abstractness of the V2 rule.

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.

Building theory-based concepts: four-year-olds preferentially seek explanations for features of kinds.

PubMed

Cimpian, Andrei; Petro, Gina

2014-05-01

Is the structure of human concepts continuous across development, or does it undergo qualitative transformations? Extensive evidence with adults has demonstrated that they are motivated to understand why categories have the features they do. To investigate whether young children display a similar motivation-an issue that bears on the question of continuity vs. transformation in conceptual structure-we conducted three studies involving 4-year-olds (N=90) and adults (N=124). Experiments 1 and 2 suggested that 4-year-olds indeed display a strong motivation to explain why categories have the features they do. Specifically, when provided with the option of asking "why?" about features of novel categories vs. features of individuals from other novel categories, children preferred to ask "why?" about the category features. Moreover, children's explanatory preference was specific to facts about categories per se and did not extend to facts that were merely presented in the context of multiple category instances. Experiment 3 also ruled out the possibility that the category facts were preferred because these facts were more surprising. In sum, these three studies reveal an early-emerging motivation to make sense of the categories encountered in the world and, more generally, speak to the richness of children's conceptual representations. Copyright © 2014 Elsevier B.V. All rights reserved.

Computer-Aided Breast Cancer Diagnosis with Optimal Feature Sets: Reduction Rules and Optimization Techniques.

PubMed

Mathieson, Luke; Mendes, Alexandre; Marsden, John; Pond, Jeffrey; Moscato, Pablo

2017-01-01

This chapter introduces a new method for knowledge extraction from databases for the purpose of finding a discriminative set of features that is also a robust set for within-class classification. Our method is generic and we introduce it here in the field of breast cancer diagnosis from digital mammography data. The mathematical formalism is based on a generalization of the k-Feature Set problem called (α, β)-k-Feature Set problem, introduced by Cotta and Moscato (J Comput Syst Sci 67(4):686-690, 2003). This method proceeds in two steps: first, an optimal (α, β)-k-feature set of minimum cardinality is identified and then, a set of classification rules using these features is obtained. We obtain the (α, β)-k-feature set in two phases; first a series of extremely powerful reduction techniques, which do not lose the optimal solution, are employed; and second, a metaheuristic search to identify the remaining features to be considered or disregarded. Two algorithms were tested with a public domain digital mammography dataset composed of 71 malignant and 75 benign cases. Based on the results provided by the algorithms, we obtain classification rules that employ only a subset of these features.

Nonlocal sparse model with adaptive structural clustering for feature extraction of aero-engine bearings

NASA Astrophysics Data System (ADS)

Zhang, Han; Chen, Xuefeng; Du, Zhaohui; Li, Xiang; Yan, Ruqiang

2016-04-01

Fault information of aero-engine bearings presents two particular phenomena, i.e., waveform distortion and impulsive feature frequency band dispersion, which leads to a challenging problem for current techniques of bearing fault diagnosis. Moreover, although many progresses of sparse representation theory have been made in feature extraction of fault information, the theory also confronts inevitable performance degradation due to the fact that relatively weak fault information has not sufficiently prominent and sparse representations. Therefore, a novel nonlocal sparse model (coined NLSM) and its algorithm framework has been proposed in this paper, which goes beyond simple sparsity by introducing more intrinsic structures of feature information. This work adequately exploits the underlying prior information that feature information exhibits nonlocal self-similarity through clustering similar signal fragments and stacking them together into groups. Within this framework, the prior information is transformed into a regularization term and a sparse optimization problem, which could be solved through block coordinate descent method (BCD), is formulated. Additionally, the adaptive structural clustering sparse dictionary learning technique, which utilizes k-Nearest-Neighbor (kNN) clustering and principal component analysis (PCA) learning, is adopted to further enable sufficient sparsity of feature information. Moreover, the selection rule of regularization parameter and computational complexity are described in detail. The performance of the proposed framework is evaluated through numerical experiment and its superiority with respect to the state-of-the-art method in the field is demonstrated through the vibration signals of experimental rig of aircraft engine bearings.

Modularising ontology and designing inference patterns to personalise health condition assessment: the case of obesity.

PubMed

Sojic, Aleksandra; Terkaj, Walter; Contini, Giorgia; Sacco, Marco

2016-05-04

The public health initiatives for obesity prevention are increasingly exploiting the advantages of smart technologies that can register various kinds of data related to physical, physiological, and behavioural conditions. Since individual features and habits vary among people, the design of appropriate intervention strategies for motivating changes in behavioural patterns towards a healthy lifestyle requires the interpretation and integration of collected information, while considering individual profiles in a personalised manner. The ontology-based modelling is recognised as a promising approach in facing the interoperability and integration of heterogeneous information related to characterisation of personal profiles. The presented ontology captures individual profiles across several obesity-related knowledge-domains structured into dedicated modules in order to support inference about health condition, physical features, behavioural habits associated with a person, and relevant changes over time. The modularisation strategy is designed to facilitate ontology development, maintenance, and reuse. The domain-specific modules formalised in the Web Ontology Language (OWL) integrate the domain-specific sets of rules formalised in the Semantic Web Rule Language (SWRL). The inference rules follow a modelling pattern designed to support personalised assessment of health condition as age- and gender-specific. The test cases exemplify a personalised assessment of the obesity-related health conditions for the population of teenagers. The paper addresses several issues concerning the modelling of normative concepts related to obesity and depicts how the public health concern impacts classification of teenagers according to their phenotypes. The modelling choices regarding the ontology-structure are explained in the context of the modelling goal to integrate multiple knowledge-domains and support reasoning about the individual changes over time. The presented modularisation pattern enhances reusability of the domain-specific modules across various health care domains.

[Hygienic risks in swimming pool: knowledge and behaviours of consumers of three structures in Crema, Parma and Naples].

PubMed

Liguori, G; Castaldi, S; Signorelli, C; Auxilia, F; Alfano, V; Saccani, E; Visciano, A; Fanti, M; Spinelli, A; Pasquarella, C

2007-01-01

The swimmers health's protection and the maintenance of good safety standards of structures can be guaranteed under observance of rules and the well management of the structures and activities. An anonymous questionnaire, with 38 items, was used in order to analyse and better understand the knowledge and behaviour of the users of three swimming pools in Crema, Naples and Parma. Socio-demographic features were similar in the three centres. One of the most important result was that the necessity of showers and foot-bath before entering the swimming pool is not well understood (77% and 78% respectively); caps and foot bath are, instead, almost always worn (98% and 97%). Knowledge on infection diseases transmitted by water is very poor, warts and mycosis being the best known. Sport structures are places where health and wellness can be affected. It is important to underline the role of behavioural rules as the use of showers, caps, and proper shoes. Authors recognize the swimming pool regulations as a valid tool for health promotion. It must be clear and easily understood and it has to be linked to a proper education pathway of all users and employees.

Discovering Fine-grained Sentiment in Suicide Notes

PubMed Central

Wang, Wenbo; Chen, Lu; Tan, Ming; Wang, Shaojun; Sheth, Amit P.

2012-01-01

This paper presents our solution for the i2b2 sentiment classification challenge. Our hybrid system consists of machine learning and rule-based classifiers. For the machine learning classifier, we investigate a variety of lexical, syntactic and knowledge-based features, and show how much these features contribute to the performance of the classifier through experiments. For the rule-based classifier, we propose an algorithm to automatically extract effective syntactic and lexical patterns from training examples. The experimental results show that the rule-based classifier outperforms the baseline machine learning classifier using unigram features. By combining the machine learning classifier and the rule-based classifier, the hybrid system gains a better trade-off between precision and recall, and yields the highest micro-averaged F-measure (0.5038), which is better than the mean (0.4875) and median (0.5027) micro-average F-measures among all participating teams. PMID:22879770

Rules versus Prototype Matching: Strategies of Perception of Emotional Facial Expressions in the Autism Spectrum

ERIC Educational Resources Information Center

Rutherford, M. D.; McIntosh, Daniel N.

2007-01-01

When perceiving emotional facial expressions, people with autistic spectrum disorders (ASD) appear to focus on individual facial features rather than configurations. This paper tests whether individuals with ASD use these features in a rule-based strategy of emotional perception, rather than a typical, template-based strategy by considering…

77 FR 26417 - Roth Feature to the Thrift Savings Plan and Miscellaneous Uniformed Services Account Amendments

Federal Register 2010, 2011, 2012, 2013, 2014

2012-05-04

... 1690 Roth Feature to the Thrift Savings Plan and Miscellaneous Uniformed Services Account Amendments... Plan. This final rule also reorganizes regulatory provisions pertaining to uniformed services accounts. DATES: This rule is effective May 7, 2012. FOR FURTHER INFORMATION CONTACT: Laurissa Stokes at (202) 942...

DISTINCTIVE FEATURES IN THE PLURALIZATION RULES OF ENGLISH SPEAKERS.

ERIC Educational Resources Information Center

ANISFELD, MOSHE; AND OTHERS

FIRST AND SECOND GRADERS, GIVEN "CVC" SINGULAR NONSENSE WORDS (E.G., NAR) ORALLY AND ASKED TO CHOOSE BETWEEN TWO PLURALS (NARF-NARK), PREFERRED FINAL SOUNDS SHARING WITH /Z/ (THE MOST COMMON SHAPE OF THE PLURAL MORPHEME IN ENGLISH) THE STRIDENCY OR CONTINUANCE FEATURES. THIS SUGGESTS THAT THEIR PLURALIZATION RULES ARE FORMULATED IN TERMS OF…

Joint trajectories for social and physical aggression as predictors of adolescent maladjustment: internalizing symptoms, rule-breaking behaviors, and borderline and narcissistic personality features.

PubMed

Underwood, Marion K; Beron, Kurt J; Rosen, Lisa H

2011-05-01

This investigation examined the relation between developmental trajectories jointly estimated for social and physical aggression and adjustment problems at age 14. Teachers provided ratings of children's social and physical aggression in Grades 3, 4, 5, 6, and 7 for a sample of 255 children (131 girls, 21% African American, 52% European American, 21% Mexican American). Participants, parents, and teachers completed measures of the adolescent's adjustment to assess internalizing symptoms, rule-breaking behaviors, and borderline and narcissistic personality features. Results showed that membership in a high and rising trajectory group predicted rule-breaking behaviors and borderline personality features. Membership in a high desister group predicted internalizing symptoms, rule-breaking behaviors, and borderline and narcissistic personality features. The findings suggest that although low levels of social and physical aggression may not bode poorly for adjustment, individuals engaging in high levels of social and physical aggression in middle childhood may be at greatest risk for adolescent psychopathology, whether they increase or desist in their aggression through early adolescence.

Joint trajectories for social and physical aggression as predictors of adolescent maladjustment: Internalizing symptoms, rule-breaking behaviors, and borderline and narcissistic personality features

PubMed Central

UNDERWOOD, MARION K.; BERON, KURT J.; ROSEN, LISA H.

2011-01-01

This investigation examined the relation between developmental trajectories jointly estimated for social and physical aggression and adjustment problems at age 14. Teachers provided ratings of children's social and physical aggression in Grades 3, 4, 5, 6, and 7 for a sample of 255 children (131 girls, 21% African American, 52% European American, 21% Mexican American). Participants, parents, and teachers completed measures of the adolescent's adjustment to assess internalizing symptoms, rule-breaking behaviors, and borderline and narcissistic personality features. Results showed that membership in a high and rising trajectory group predicted rule-breaking behaviors and borderline personality features. Membership in a high desister group predicted internalizing symptoms, rule-breaking behaviors, and borderline and narcissistic personality features. The findings suggest that although low levels of social and physical aggression may not bode poorly for adjustment, individuals engaging in high levels of social and physical aggression in middle childhood may be at greatest risk for adolescent psychopathology, whether they increase or desist in their aggression through early adolescence. PMID:21532919

Accurate crop classification using hierarchical genetic fuzzy rule-based systems

NASA Astrophysics Data System (ADS)

Topaloglou, Charalampos A.; Mylonas, Stelios K.; Stavrakoudis, Dimitris G.; Mastorocostas, Paris A.; Theocharis, John B.

2014-10-01

This paper investigates the effectiveness of an advanced classification system for accurate crop classification using very high resolution (VHR) satellite imagery. Specifically, a recently proposed genetic fuzzy rule-based classification system (GFRBCS) is employed, namely, the Hierarchical Rule-based Linguistic Classifier (HiRLiC). HiRLiC's model comprises a small set of simple IF-THEN fuzzy rules, easily interpretable by humans. One of its most important attributes is that its learning algorithm requires minimum user interaction, since the most important learning parameters affecting the classification accuracy are determined by the learning algorithm automatically. HiRLiC is applied in a challenging crop classification task, using a SPOT5 satellite image over an intensively cultivated area in a lake-wetland ecosystem in northern Greece. A rich set of higher-order spectral and textural features is derived from the initial bands of the (pan-sharpened) image, resulting in an input space comprising 119 features. The experimental analysis proves that HiRLiC compares favorably to other interpretable classifiers of the literature, both in terms of structural complexity and classification accuracy. Its testing accuracy was very close to that obtained by complex state-of-the-art classification systems, such as the support vector machines (SVM) and random forest (RF) classifiers. Nevertheless, visual inspection of the derived classification maps shows that HiRLiC is characterized by higher generalization properties, providing more homogeneous classifications that the competitors. Moreover, the runtime requirements for producing the thematic map was orders of magnitude lower than the respective for the competitors.

Analytical study of sandwich structures using Euler-Bernoulli beam equation

NASA Astrophysics Data System (ADS)

Xue, Hui; Khawaja, H.

2017-01-01

This paper presents an analytical study of sandwich structures. In this study, the Euler-Bernoulli beam equation is solved analytically for a four-point bending problem. Appropriate initial and boundary conditions are specified to enclose the problem. In addition, the balance coefficient is calculated and the Rule of Mixtures is applied. The focus of this study is to determine the effective material properties and geometric features such as the moment of inertia of a sandwich beam. The effective parameters help in the development of a generic analytical correlation for complex sandwich structures from the perspective of four-point bending calculations. The main outcomes of these analytical calculations are the lateral displacements and longitudinal stresses for each particular material in the sandwich structure.

Narrative dynamics in social groups: A discrete choice model

NASA Astrophysics Data System (ADS)

Antoci, A.; Bellanca, N.; Galdi, G.; Sodini, M.

2018-05-01

Individuals follow different rules for action: they react swiftly, grasping the short-term advantages in sight, or they waste cognitive resources to complete otherwise easy tasks, but they are able to plan ahead future complex decisions. Scholars from different disciplines studied the conditions under which either decision rule may enhance the fitness of its adopters, with a focus on the environmental features. However, we here propose that a crucial feature of the evolution of populations and their decision rules is rather inter-group interactions. Indeed, we study what happens when two groups support different decision rules, encapsulated in narratives, and their populations interact with each other. In particular, we assume that the payoff of each rule depends on the share of both social groups which adopt such rules. We then describe the most salient dynamics scenarios and identify the conditions which lead to chaotic dynamics and multistability regimes.

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.

Automatic rule generation for high-level vision

NASA Technical Reports Server (NTRS)

Rhee, Frank Chung-Hoon; Krishnapuram, Raghu

1992-01-01

Many high-level vision systems use rule-based approaches to solving problems such as autonomous navigation and image understanding. The rules are usually elaborated by experts. However, this procedure may be rather tedious. In this paper, we propose a method to generate such rules automatically from training data. The proposed method is also capable of filtering out irrelevant features and criteria from the rules.

Chemometric analysis of correlations between electronic absorption characteristics and structural and/or physicochemical parameters for ampholytic substances of biological and pharmaceutical relevance.

PubMed

Judycka-Proma, U; Bober, L; Gajewicz, A; Puzyn, T; Błażejowski, J

2015-03-05

Forty ampholytic compounds of biological and pharmaceutical relevance were subjected to chemometric analysis based on unsupervised and supervised learning algorithms. This enabled relations to be found between empirical spectral characteristics derived from electronic absorption data and structural and physicochemical parameters predicted by quantum chemistry methods or phenomenological relationships based on additivity rules. It was found that the energies of long wavelength absorption bands are correlated through multiparametric linear relationships with parameters reflecting the bulkiness features of the absorbing molecules as well as their nucleophilicity and electrophilicity. These dependences enable the quantitative analysis of spectral features of the compounds, as well as a comparison of their similarities and certain pharmaceutical and biological features. Three QSPR models to predict the energies of long-wavelength absorption in buffers with pH=2.5 and pH=7.0, as well as in methanol, were developed and validated in this study. These models can be further used to predict the long-wavelength absorption energies of untested substances (if they are structurally similar to the training compounds). Copyright © 2014 Elsevier B.V. All rights reserved.

Structural geology and geological history of the Perrine and Nun Sulci Quadrangles (Jg-2 and Jg-5), Ganymede

NASA Technical Reports Server (NTRS)

Mcgill, George E.; Squyres, Steven W.

1991-01-01

Grooves are the dominant structural features on Ganymede. While single grooves are found in many areas, it is somewhat more common to find them grouped together in groove sets (groupings of grooves with common structural trends). It is generally believed that the grooves are extensional features. Their underlying geologic nature cannot be determined from Voyager images, however. It appears likely that they are grabens, but the images are insufficient to rule out the possibility that they are modified extension fractures or some kind of ductile necking features. The oldest materials within the Nun Sulci and Perrine quadrangles occur within the cratered dark materials unit, as is generally the case for all of Ganymede. This is the most widespread of the dark units mapped in these two quadrangles. Crater densities within cratered dark materials are consistent with an age on the order of several billion years, and thus cratered dark terrain probably represents crust that has survived from the end of the primordial intense bombardment phase of solar system history. The brief geologic history is greatly oversimplified as a result of the poor resolution and unfavorable viewing geometry of the images covering the area.

The CPAT 2.0.2 Domain Model - How CPAT 2.0.2 "Thinks" From an Analyst Perspective.

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

Waddell, Lucas; Muldoon, Frank; Melander, Darryl J.

To help effectively plan the management and modernization of their large and diverse fleets of vehicles, the Program Executive Office Ground Combat Systems (PEO GCS) and the Program Executive Office Combat Support and Combat Service Support (PEO CS &CSS) commissioned the development of a large - scale portfolio planning optimization tool. This software, the Capability Portfolio Analysis Tool (CPAT), creates a detailed schedule that optimally prioritizes the modernization or replacement of vehicles within the fleet - respecting numerous business rules associated with fleet structure, budgets, industrial base, research and testing, etc., while maximizing overall fleet performance through time. This reportmore » contains a description of the organizational fleet structure and a thorough explanation of the business rules that the CPAT formulation follows involving performance, scheduling, production, and budgets. This report, which is an update to the original CPAT domain model published in 2015 (SAND2015 - 4009), covers important new CPAT features. This page intentionally left blank« less

Sensory Intelligence for Extraction of an Abstract Auditory Rule: A Cross-Linguistic Study.

PubMed

Guo, Xiao-Tao; Wang, Xiao-Dong; Liang, Xiu-Yuan; Wang, Ming; Chen, Lin

2018-02-21

In a complex linguistic environment, while speech sounds can greatly vary, some shared features are often invariant. These invariant features constitute so-called abstract auditory rules. Our previous study has shown that with auditory sensory intelligence, the human brain can automatically extract the abstract auditory rules in the speech sound stream, presumably serving as the neural basis for speech comprehension. However, whether the sensory intelligence for extraction of abstract auditory rules in speech is inherent or experience-dependent remains unclear. To address this issue, we constructed a complex speech sound stream using auditory materials in Mandarin Chinese, in which syllables had a flat lexical tone but differed in other acoustic features to form an abstract auditory rule. This rule was occasionally and randomly violated by the syllables with the rising, dipping or falling tone. We found that both Chinese and foreign speakers detected the violations of the abstract auditory rule in the speech sound stream at a pre-attentive stage, as revealed by the whole-head recordings of mismatch negativity (MMN) in a passive paradigm. However, MMNs peaked earlier in Chinese speakers than in foreign speakers. Furthermore, Chinese speakers showed different MMN peak latencies for the three deviant types, which paralleled recognition points. These findings indicate that the sensory intelligence for extraction of abstract auditory rules in speech sounds is innate but shaped by language experience. Copyright © 2018 IBRO. Published by Elsevier Ltd. All rights reserved.

Classification of document page images based on visual similarity of layout structures

NASA Astrophysics Data System (ADS)

Shin, Christian K.; Doermann, David S.

1999-12-01

Searching for documents by their type or genre is a natural way to enhance the effectiveness of document retrieval. The layout of a document contains a significant amount of information that can be used to classify a document's type in the absence of domain specific models. A document type or genre can be defined by the user based primarily on layout structure. Our classification approach is based on 'visual similarity' of the layout structure by building a supervised classifier, given examples of the class. We use image features, such as the percentages of tex and non-text (graphics, image, table, and ruling) content regions, column structures, variations in the point size of fonts, the density of content area, and various statistics on features of connected components which can be derived from class samples without class knowledge. In order to obtain class labels for training samples, we conducted a user relevance test where subjects ranked UW-I document images with respect to the 12 representative images. We implemented our classification scheme using the OC1, a decision tree classifier, and report our findings.

A Hyper-Heuristic Ensemble Method for Static Job-Shop Scheduling.

PubMed

Hart, Emma; Sim, Kevin

2016-01-01

We describe a new hyper-heuristic method NELLI-GP for solving job-shop scheduling problems (JSSP) that evolves an ensemble of heuristics. The ensemble adopts a divide-and-conquer approach in which each heuristic solves a unique subset of the instance set considered. NELLI-GP extends an existing ensemble method called NELLI by introducing a novel heuristic generator that evolves heuristics composed of linear sequences of dispatching rules: each rule is represented using a tree structure and is itself evolved. Following a training period, the ensemble is shown to outperform both existing dispatching rules and a standard genetic programming algorithm on a large set of new test instances. In addition, it obtains superior results on a set of 210 benchmark problems from the literature when compared to two state-of-the-art hyper-heuristic approaches. Further analysis of the relationship between heuristics in the evolved ensemble and the instances each solves provides new insights into features that might describe similar instances.

CLIPS: A tool for corn disease diagnostic system and an aid to neural network for automated knowledge acquisition

NASA Technical Reports Server (NTRS)

Wu, Cathy; Taylor, Pam; Whitson, George; Smith, Cathy

1990-01-01

This paper describes the building of a corn disease diagnostic expert system using CLIPS, and the development of a neural expert system using the fact representation method of CLIPS for automated knowledge acquisition. The CLIPS corn expert system diagnoses 21 diseases from 52 symptoms and signs with certainty factors. CLIPS has several unique features. It allows the facts in rules to be broken down to object-attribute-value (OAV) triples, allows rule-grouping, and fires rules based on pattern-matching. These features combined with the chained inference engine result to a natural user query system and speedy execution. In order to develop a method for automated knowledge acquisition, an Artificial Neural Expert System (ANES) is developed by a direct mapping from the CLIPS system. The ANES corn expert system uses the same OAV triples in the CLIPS system for its facts. The LHS and RHS facts of the CLIPS rules are mapped into the input and output layers of the ANES, respectively; and the inference engine of the rules is imbedded in the hidden layer. The fact representation by OAC triples gives a natural grouping of the rules. These features allow the ANES system to automate rule-generation, and make it efficient to execute and easy to expand for a large and complex domain.

Automated global structure extraction for effective local building block processing in XCS.

PubMed

Butz, Martin V; Pelikan, Martin; Llorà, Xavier; Goldberg, David E

2006-01-01

Learning Classifier Systems (LCSs), such as the accuracy-based XCS, evolve distributed problem solutions represented by a population of rules. During evolution, features are specialized, propagated, and recombined to provide increasingly accurate subsolutions. Recently, it was shown that, as in conventional genetic algorithms (GAs), some problems require efficient processing of subsets of features to find problem solutions efficiently. In such problems, standard variation operators of genetic and evolutionary algorithms used in LCSs suffer from potential disruption of groups of interacting features, resulting in poor performance. This paper introduces efficient crossover operators to XCS by incorporating techniques derived from competent GAs: the extended compact GA (ECGA) and the Bayesian optimization algorithm (BOA). Instead of simple crossover operators such as uniform crossover or one-point crossover, ECGA or BOA-derived mechanisms are used to build a probabilistic model of the global population and to generate offspring classifiers locally using the model. Several offspring generation variations are introduced and evaluated. The results show that it is possible to achieve performance similar to runs with an informed crossover operator that is specifically designed to yield ideal problem-dependent exploration, exploiting provided problem structure information. Thus, we create the first competent LCSs, XCS/ECGA and XCS/BOA, that detect dependency structures online and propagate corresponding lower-level dependency structures effectively without any information about these structures given in advance.

KOSMOS: a universal morph server for nucleic acids, proteins and their complexes

PubMed Central

Seo, Sangjae; Kim, Moon Ki

2012-01-01

KOSMOS is the first online morph server to be able to address the structural dynamics of DNA/RNA, proteins and even their complexes, such as ribosomes. The key functions of KOSMOS are the harmonic and anharmonic analyses of macromolecules. In the harmonic analysis, normal mode analysis (NMA) based on an elastic network model (ENM) is performed, yielding vibrational modes and B-factor calculations, which provide insight into the potential biological functions of macromolecules based on their structural features. Anharmonic analysis involving elastic network interpolation (ENI) is used to generate plausible transition pathways between two given conformations by optimizing a topology-oriented cost function that guarantees a smooth transition without steric clashes. The quality of the computed pathways is evaluated based on their various facets, including topology, energy cost and compatibility with the NMA results. There are also two unique features of KOSMOS that distinguish it from other morph servers: (i) the versatility in the coarse-graining methods and (ii) the various connection rules in the ENM. The models enable us to analyze macromolecular dynamics with the maximum degrees of freedom by combining a variety of ENMs from full-atom to coarse-grained, backbone and hybrid models with one connection rule, such as distance-cutoff, number-cutoff or chemical-cutoff. KOSMOS is available at http://bioengineering.skku.ac.kr/kosmos. PMID:22669912

Dependent Measure and Time Constraints Modulate the Competition between Conflicting Feature-Based and Rule-Based Generalization Processes

ERIC Educational Resources Information Center

Cobos, Pedro L.; Gutiérrez-Cobo, María J.; Morís, Joaquín; Luque, David

2017-01-01

In our study, we tested the hypothesis that feature-based and rule-based generalization involve different types of processes that may affect each other producing different results depending on time constraints and on how generalization is measured. For this purpose, participants in our experiments learned cue-outcome relationships that followed…

Assessing the Impact of Representational and Contextual Problem Features on Student Use of Right-Hand Rules

ERIC Educational Resources Information Center

Kustusch, Mary Bridget

2016-01-01

Students in introductory physics struggle with vector algebra and these challenges are often associated with contextual and representational features of the problems. Performance on problems about cross product direction is particularly poor and some research suggests that this may be primarily due to misapplied right-hand rules. However, few…

[Psychopathologic traits of patients addicted to heroin].

PubMed

Cabal Bravo, J C; Bobes García, J; Vázquez Fernández, A; González-Quirós Corujo, P; Bousoño García, M; García Prieto, A; González García-Portilla, P

1989-01-01

The aim of our work is the search for some differential psychopathologic features in the heroin addict personality, through the 16 PF of Cattell (A form), which we try to contrast with other contributions from studies carried out up to the present. Moreover, other parameters of demographic and socioeconomic interest have been evaluated. Through the results we have gotten, it seems that there is a larger number of psychopathologic elements in the personality of the heroin addict, such as greater introversion, frustration, culpability, radicalism, self-sufficiency, anxiety, over-excitement, actions influenced by their feelings, and a minor acceptance of the rules of the group, though these features do not constitute a standard structure of personality.

Fiscal rules, powerful levers for controlling the health budget? Evidence from 32 OECD countries.

PubMed

Schakel, Herman Christiaan; Wu, Erilia Hao; Jeurissen, Patrick

2018-03-01

Publicly funded healthcare forms an intricate part of government spending in most Organisation for Economic Co-operation and Development (OECD) countries, because of its reliance on entitlements and dedicated revenue streams. The impact of budgetary rules and procedures on publicly funded health care might thus be different from other spending categories. In this study we focus on the potential of fiscal rules to contain these costs and their design features. We assess the relationship between fiscal rules and the level of public health care expenditure of 32 (OECD) countries between 1985 and 2014. Our dataset consists of health care expenditure data of the OECD and data on fiscal rules of the International Monetary Fund (IMF) for that same period. Through a multivariate regression analysis, we estimate the association between fiscal rules and its subcategories and inflation adjusted public health care expenditure. We control for population, Gross Domestic Product (GDP), debt and whether countries received an IMF bailout for the specific period. In all our regressions we include country and year fixed effects. The presence of a fiscal rule on average is associated with a 3 % reduction of public health care expenditure. Supranational balanced budget rules are associated with some 8 % lower expenditure. Health service provision-oriented countries with more passive purchasing structures seem less capable of containing costs through fiscal rules. Fiscal rules demonstrate lagged effectiveness; the potential for expenditure reduction increases after one and two years of fiscal rule implementation. Finally, we find evidence that fiscal frameworks that incorporate multi-year expenditure ceilings show additional potential for cost control. Our study shows that there seems a clear relationship between the potential of fiscal rules and budgeting health expenses. Using fiscal rules to contain the level of health care expenditure can thus be a necessary precondition for successful strategies for cost control.

Hydrologic connectivity: Quantitative assessments of hydrologic-enforced drainage structures in an elevation model

USGS Publications Warehouse

Poppenga, Sandra K.; Worstell, Bruce B.

2016-01-01

Elevation data derived from light detection and ranging present challenges for hydrologic modeling as the elevation surface includes bridge decks and elevated road features overlaying culvert drainage structures. In reality, water is carried through these structures; however, in the elevation surface these features impede modeled overland surface flow. Thus, a hydrologically-enforced elevation surface is needed for hydrodynamic modeling. In the Delaware River Basin, hydrologic-enforcement techniques were used to modify elevations to simulate how constructed drainage structures allow overland surface flow. By calculating residuals between unfilled and filled elevation surfaces, artificially pooled depressions that formed upstream of constructed drainage structure features were defined, and elevation values were adjusted by generating transects at the location of the drainage structures. An assessment of each hydrologically-enforced drainage structure was conducted using field-surveyed culvert and bridge coordinates obtained from numerous public agencies, but it was discovered the disparate drainage structure datasets were not comprehensive enough to assess all remotely located depressions in need of hydrologic-enforcement. Alternatively, orthoimagery was interpreted to define drainage structures near each depression, and these locations were used as reference points for a quantitative hydrologic-enforcement assessment. The orthoimagery-interpreted reference points resulted in a larger corresponding sample size than the assessment between hydrologic-enforced transects and field-surveyed data. This assessment demonstrates the viability of rules-based hydrologic-enforcement that is needed to achieve hydrologic connectivity, which is valuable for hydrodynamic models in sensitive coastal regions. Hydrologic-enforced elevation data are also essential for merging with topographic/bathymetric elevation data that extend over vulnerable urbanized areas and dynamic coastal regions.

Big data mining analysis method based on cloud computing

NASA Astrophysics Data System (ADS)

Cai, Qing Qiu; Cui, Hong Gang; Tang, Hao

2017-08-01

Information explosion era, large data super-large, discrete and non-(semi) structured features have gone far beyond the traditional data management can carry the scope of the way. With the arrival of the cloud computing era, cloud computing provides a new technical way to analyze the massive data mining, which can effectively solve the problem that the traditional data mining method cannot adapt to massive data mining. This paper introduces the meaning and characteristics of cloud computing, analyzes the advantages of using cloud computing technology to realize data mining, designs the mining algorithm of association rules based on MapReduce parallel processing architecture, and carries out the experimental verification. The algorithm of parallel association rule mining based on cloud computing platform can greatly improve the execution speed of data mining.

Design Rules for Tailoring Antireflection Properties of Hierarchical Optical Structures

DOE PAGES

Leon, Juan J. Diaz; Hiszpanski, Anna M.; Bond, Tiziana C.; ...

2017-05-18

Hierarchical structures consisting of small sub-wavelength features stacked atop larger structures have been demonstrated as an effective means of reducing the reflectance of surfaces. However, optical devices require different antireflective properties depending on the application, and general unifying guidelines on hierarchical structures' design to attain a desired antireflection spectral response are still lacking. The type of reflectivity (diffuse, specular, or total/hemispherical) and its angular- and spectral-dependence are all dictated by the structural parameters. Through computational and experimental studies, guidelines have been devised to modify these various aspects of reflectivity across the solar spectrum by proper selection of the features ofmore » hierarchical structures. In this wavelength regime, micrometer-scale substructures dictate the long-wavelength spectral response and effectively reduce specular reflectance, whereas nanometer-scale substructures dictate primarily the visible wavelength spectral response and reduce diffuse reflectance. Coupling structures having these two length scales into hierarchical arrays impressively reduces surfaces' hemispherical reflectance across a broad spectrum of wavelengths and angles. Furthermore, such hierarchical structures in silicon are demonstrated having an average total reflectance across the solar spectrum of 1.1% (average weighted reflectance of 1% in the 280–2500 nm range of the AM 1.5 G spectrum) and specular reflectance <1% even at angles of incidence as high as 67°.« less

Multiple Grammars and the Logic of Learnability in Second Language Acquisition

PubMed Central

Roeper, Tom W.

2016-01-01

The core notion of modern Universal Grammar is that language ability requires abstract representation in terms of hierarchy, movement operations, abstract features on words, and fixed mapping to meaning. These mental structures are a step toward integrating representational knowledge of all kinds into a larger model of cognitive psychology. Examining first and second language at once provides clues as to how abstractly we should represent this knowledge. The abstract nature of grammar allows both the formulation of many grammars and the possibility that a rule of one grammar could apply to another grammar. We argue that every language contains Multiple Grammars which may reflect different language families. We develop numerous examples of how the same abstract rules can apply in various languages and develop a theory of how language modules (case-marking, topicalization, and quantification) interact to predict L2 acquisition paths. In particular we show in depth how Germanic Verb-second operations, based on Verb-final structure, can apply in English. The argument is built around how and where V2 from German can apply in English, seeking to explain the crucial contrast: “nothing” yelled out Bill/*“nothing” yelled Bill out in terms of the necessary abstractness of the V2 rule. PMID:26869945

Neural foundations to moral reasoning and antisocial behavior

PubMed Central

Yang, Yaling

2006-01-01

A common feature of the antisocial, rule-breaking behavior that is central to criminal, violent and psychopathic individuals is the failure to follow moral guidelines. This review summarizes key findings from brain imaging research on both antisocial behavior and moral reasoning, and integrates these findings into a neural moral model of antisocial behavior. Key areas found to be functionally or structurally impaired in antisocial populations include dorsal and ventral regions of the prefrontal cortex (PFC), amygdala, hippocampus, angular gyrus, anterior cingulate and temporal cortex. Regions most commonly activated in moral judgment tasks consist of the polar/medial and ventral PFC, amygdala, angular gyrus and posterior cingulate. It is hypothesized that the rule-breaking behavior common to antisocial, violent and psychopathic individuals is in part due to impairments in some of the structures (dorsal and ventral PFC, amygdala and angular gyrus) subserving moral cognition and emotion. Impairments to the emotional component that comprises the feeling of what is moral is viewed as the primary deficit in antisocials, although some disruption to the cognitive and cognitive-emotional components of morality (particularly self-referential thinking and emotion regulation) cannot be ruled out. While this neurobiological predisposition is likely only one of several biosocial processes involved in the etiology of antisocial behavior, it raises significant moral issues for the legal system and neuroethics. PMID:18985107

LipidMatch: an automated workflow for rule-based lipid identification using untargeted high-resolution tandem mass spectrometry data.

PubMed

Koelmel, Jeremy P; Kroeger, Nicholas M; Ulmer, Candice Z; Bowden, John A; Patterson, Rainey E; Cochran, Jason A; Beecher, Christopher W W; Garrett, Timothy J; Yost, Richard A

2017-07-10

Lipids are ubiquitous and serve numerous biological functions; thus lipids have been shown to have great potential as candidates for elucidating biomarkers and pathway perturbations associated with disease. Methods expanding coverage of the lipidome increase the likelihood of biomarker discovery and could lead to more comprehensive understanding of disease etiology. We introduce LipidMatch, an R-based tool for lipid identification for liquid chromatography tandem mass spectrometry workflows. LipidMatch currently has over 250,000 lipid species spanning 56 lipid types contained in in silico fragmentation libraries. Unique fragmentation libraries, compared to other open source software, include oxidized lipids, bile acids, sphingosines, and previously uncharacterized adducts, including ammoniated cardiolipins. LipidMatch uses rule-based identification. For each lipid type, the user can select which fragments must be observed for identification. Rule-based identification allows for correct annotation of lipids based on the fragments observed, unlike typical identification based solely on spectral similarity scores, where over-reporting structural details that are not conferred by fragmentation data is common. Another unique feature of LipidMatch is ranking lipid identifications for a given feature by the sum of fragment intensities. For each lipid candidate, the intensities of experimental fragments with exact mass matches to expected in silico fragments are summed. The lipid identifications with the greatest summed intensity using this ranking algorithm were comparable to other lipid identification software annotations, MS-DIAL and Greazy. For example, for features with identifications from all 3 software, 92% of LipidMatch identifications by fatty acyl constituents were corroborated by at least one other software in positive mode and 98% in negative ion mode. LipidMatch allows users to annotate lipids across a wide range of high resolution tandem mass spectrometry experiments, including imaging experiments, direct infusion experiments, and experiments employing liquid chromatography. LipidMatch leverages the most extensive in silico fragmentation libraries of freely available software. When integrated into a larger lipidomics workflow, LipidMatch may increase the probability of finding lipid-based biomarkers and determining etiology of disease by covering a greater portion of the lipidome and using annotation which does not over-report biologically relevant structural details of identified lipid molecules.

Social coordination in animal vocal interactions. Is there any evidence of turn-taking? The starling as an animal model

PubMed Central

Henry, Laurence; Craig, Adrian J. F. K.; Lemasson, Alban; Hausberger, Martine

2015-01-01

Turn-taking in conversation appears to be a common feature in various human cultures and this universality raises questions about its biological basis and evolutionary trajectory. Functional convergence is a widespread phenomenon in evolution, revealing sometimes striking functional similarities between very distant species even though the mechanisms involved may be different. Studies on mammals (including non-human primates) and bird species with different levels of social coordination reveal that temporal and structural regularities in vocal interactions may depend on the species' social structure. Here we test the hypothesis that turn-taking and associated rules of conversations may be an adaptive response to the requirements of social life, by testing the applicability of turn-taking rules to an animal model, the European starling. Birdsong has for many decades been considered as one of the best models of human language and starling songs have been well described in terms of vocal production and perception. Starlings do have vocal interactions where alternating patterns predominate. Observational and experimental data on vocal interactions reveal that (1) there are indeed clear temporal and structural regularities, (2) the temporal and structural patterning is influenced by the immediate social context, the general social situation, the individual history, and the internal state of the emitter. Comparison of phylogenetically close species of Sturnids reveals that the alternating pattern of vocal interactions varies greatly according to the species' social structure, suggesting that interactional regularities may have evolved together with social systems. These findings lead to solid bases of discussion on the evolution of communication rules in relation to social evolution. They will be discussed also in terms of processes, at the light of recent neurobiological findings. PMID:26441787

Rule-based topology system for spatial databases to validate complex geographic datasets

NASA Astrophysics Data System (ADS)

Martinez-Llario, J.; Coll, E.; Núñez-Andrés, M.; Femenia-Ribera, C.

2017-06-01

A rule-based topology software system providing a highly flexible and fast procedure to enforce integrity in spatial relationships among datasets is presented. This improved topology rule system is built over the spatial extension Jaspa. Both projects are open source, freely available software developed by the corresponding author of this paper. Currently, there is no spatial DBMS that implements a rule-based topology engine (considering that the topology rules are designed and performed in the spatial backend). If the topology rules are applied in the frontend (as in many GIS desktop programs), ArcGIS is the most advanced solution. The system presented in this paper has several major advantages over the ArcGIS approach: it can be extended with new topology rules, it has a much wider set of rules, and it can mix feature attributes with topology rules as filters. In addition, the topology rule system can work with various DBMSs, including PostgreSQL, H2 or Oracle, and the logic is performed in the spatial backend. The proposed topology system allows users to check the complex spatial relationships among features (from one or several spatial layers) that require some complex cartographic datasets, such as the data specifications proposed by INSPIRE in Europe and the Land Administration Domain Model (LADM) for Cadastral data.

Evolution of cooperation driven by incremental learning

NASA Astrophysics Data System (ADS)

Li, Pei; Duan, Haibin

2015-02-01

It has been shown that the details of microscopic rules in structured populations can have a crucial impact on the ultimate outcome in evolutionary games. So alternative formulations of strategies and their revision processes exploring how strategies are actually adopted and spread within the interaction network need to be studied. In the present work, we formulate the strategy update rule as an incremental learning process, wherein knowledge is refreshed according to one's own experience learned from the past (self-learning) and that gained from social interaction (social-learning). More precisely, we propose a continuous version of strategy update rules, by introducing the willingness to cooperate W, to better capture the flexibility of decision making behavior. Importantly, the newly gained knowledge including self-learning and social learning is weighted by the parameter ω, establishing a strategy update rule involving innovative element. Moreover, we quantify the macroscopic features of the emerging patterns to inspect the underlying mechanisms of the evolutionary process using six cluster characteristics. In order to further support our results, we examine the time evolution course for these characteristics. Our results might provide insights for understanding cooperative behaviors and have several important implications for understanding how individuals adjust their strategies under real-life conditions.

TRICARE program; clarification of benefit coverage of durable equipment and ordering or prescribing durable equipment; clarification of benefit coverage of assistive technology devises under the Extended Care Health Option Program. Final rule.

PubMed

2014-12-31

This final rule modifies the TRICARE regulation to add a definition of assistive technology (AT) devices for purposes of benefit coverage under the TRICARE Extended Care Health Option (ECHO) Program and to amend the definitions of durable equipment (DE) and durable medical equipment (DME) to better conform the language in the regulation to the statute. The final rule amends the language that specifically limits ordering or prescribing of DME to only a physician under the Basic Program, as this amendment will allow certain other TRICARE authorized individual professional providers, acting within the scope of their licensure, to order or prescribe DME. This final rule also incorporates a policy clarification relating to luxury, deluxe, or immaterial features of equipment or devices. That is, TRICARE cannot reimburse for the luxury, deluxe, or immaterial features of equipment or devices, but can reimburse for the base or basic equipment or device that meet the beneficiary's needs. Beneficiaries may choose to pay the provider for the luxury, deluxe, or immaterial features if they desire their equipment or device to have these "extra features."

A meta-structural understanding of measurement

NASA Astrophysics Data System (ADS)

Mari, Luca; Maul, Andrew; Torres Irribarra, David; Wilson, Mark

2016-11-01

It is not always clear to what extent the logic and vocabulary of measurement as used in different scientific disciplines are mutually coherent, nor how measurement can be demarcated from, say, opinion. In recent decades there have been a number of attempts to provide necessary and/or sufficient sets of conditions for when measurement is achieved, usually in terms either of inputs (e.g., whether an evaluated property is a quantity), or outputs (e.g., whether a procedure assigns numbers according to a rule). We argue instead that the public trust attributed to measurement is best justified in terms of the structural features of the process rather than of its inputs or outputs.

Style-independent document labeling: design and performance evaluation

NASA Astrophysics Data System (ADS)

Mao, Song; Kim, Jong Woo; Thoma, George R.

2003-12-01

The Medical Article Records System or MARS has been developed at the U.S. National Library of Medicine (NLM) for automated data entry of bibliographical information from medical journals into MEDLINE, the premier bibliographic citation database at NLM. Currently, a rule-based algorithm (called ZoneCzar) is used for labeling important bibliographical fields (title, author, affiliation, and abstract) on medical journal article page images. While rules have been created for medical journals with regular layout types, new rules have to be manually created for any input journals with arbitrary or new layout types. Therefore, it is of interest to label any journal articles independent of their layout styles. In this paper, we first describe a system (called ZoneMatch) for automated generation of crucial geometric and non-geometric features of important bibliographical fields based on string-matching and clustering techniques. The rule based algorithm is then modified to use these features to perform style-independent labeling. We then describe a performance evaluation method for quantitatively evaluating our algorithm and characterizing its error distributions. Experimental results show that the labeling performance of the rule-based algorithm is significantly improved when the generated features are used.

HAL/S - The programming language for Shuttle

NASA Technical Reports Server (NTRS)

Martin, F. H.

1974-01-01

HAL/S is a higher order language and system, now operational, adopted by NASA for programming Space Shuttle on-board software. Program reliability is enhanced through language clarity and readability, modularity through program structure, and protection of code and data. Salient features of HAL/S include output orientation, automatic checking (with strictly enforced compiler rules), the availability of linear algebra, real-time control, a statement-level simulator, and compiler transferability (for applying HAL/S to additional object and host computers). The compiler is described briefly.

Fuzzy expert systems using CLIPS

NASA Technical Reports Server (NTRS)

Le, Thach C.

1994-01-01

This paper describes a CLIPS-based fuzzy expert system development environment called FCLIPS and illustrates its application to the simulated cart-pole balancing problem. FCLIPS is a straightforward extension of CLIPS without any alteration to the CLIPS internal structures. It makes use of the object-oriented and module features in CLIPS version 6.0 for the implementation of fuzzy logic concepts. Systems of varying degrees of mixed Boolean and fuzzy rules can be implemented in CLIPS. Design and implementation issues of FCLIPS will also be discussed.

Geodatabase of sites, basin boundaries, and topology rules used to store drainage basin boundaries for the U.S. Geological Survey, Colorado Water Science Center

USGS Publications Warehouse

Dupree, Jean A.; Crowfoot, Richard M.

2012-01-01

This geodatabase and its component datasets are part of U.S. Geological Survey Digital Data Series 650 and were generated to store basin boundaries for U.S. Geological Survey streamgages and other sites in Colorado. The geodatabase and its components were created by the U.S. Geological Survey, Colorado Water Science Center, and are used to derive the numeric drainage areas for Colorado that are input into the U.S. Geological Survey's National Water Information System (NWIS) database and also published in the Annual Water Data Report and on NWISWeb. The foundational dataset used to create the basin boundaries in this geodatabase was the National Watershed Boundary Dataset. This geodatabase accompanies a U.S. Geological Survey Techniques and Methods report (Book 11, Section C, Chapter 6) entitled "Digital Database Architecture and Delineation Methodology for Deriving Drainage Basins, and Comparison of Digitally and Non-Digitally Derived Numeric Drainage Areas." The Techniques and Methods report details the geodatabase architecture, describes the delineation methodology and workflows used to develop these basin boundaries, and compares digitally derived numeric drainage areas in this geodatabase to non-digitally derived areas. 1. COBasins.gdb: This geodatabase contains site locations and basin boundaries for Colorado. It includes a single feature dataset, called BasinsFD, which groups the component feature classes and topology rules. 2. BasinsFD: This feature dataset in the "COBasins.gdb" geodatabase is a digital container that holds the feature classes used to archive site locations and basin boundaries as well as the topology rules that govern spatial relations within and among component feature classes. This feature dataset includes three feature classes: the sites for which basins have been delineated (the "Sites" feature class), basin bounding lines (the "BasinLines" feature class), and polygonal basin areas (the "BasinPolys" feature class). The feature dataset also stores the topology rules (the "BasinsFD_Topology") that constrain the relations within and among component feature classes. The feature dataset also forces any feature classes inside it to have a consistent projection system, which is, in this case, an Albers-Equal-Area projection system. 3. BasinsFD_Topology: This topology contains four persistent topology rules that constrain the spatial relations within the "BasinLines" feature class and between the "BasinLines" feature class and the "BasinPolys" feature classes. 4. Sites: This point feature class contains the digital representations of the site locations for which Colorado Water Science Center basin boundaries have been delineated. This feature class includes point locations for Colorado Water Science Center active (as of September 30, 2009) gages and for other sites. 5. BasinLines: This line feature class contains the perimeters of basins delineated for features in the "Sites" feature class, and it also contains information regarding the sources of lines used for the basin boundaries. 6. BasinPolys: This polygon feature class contains the polygonal basin areas delineated for features in the "Sites" feature class, and it is used to derive the numeric drainage areas published by the Colorado Water Science Center.

Newspaper Lesson Aids.

ERIC Educational Resources Information Center

Communication: Journalism Education Today (C:JET), 1986

1986-01-01

Provides photocopy-ready lesson aids on story ideas, interviewing, inverted pyramid writing style, newswriting, sports/scavenger hunt, finding feature material, identifying feature leads, feature lead selection, evaluating feature leads, compiling survey material, cutlines, headlines, paste-up rules, advertising, final semester project, newspaper…

CT Image Sequence Analysis for Object Recognition - A Rule-Based 3-D Computer Vision System

Treesearch

Dongping Zhu; Richard W. Conners; Daniel L. Schmoldt; Philip A. Araman

1991-01-01

Research is now underway to create a vision system for hardwood log inspection using a knowledge-based approach. In this paper, we present a rule-based, 3-D vision system for locating and identifying wood defects using topological, geometric, and statistical attributes. A number of different features can be derived from the 3-D input scenes. These features and evidence...

Use of evidence in a categorization task: analytic and holistic processing modes.

PubMed

Greco, Alberto; Moretti, Stefania

2017-11-01

Category learning performance can be influenced by many contextual factors, but the effects of these factors are not the same for all learners. The present study suggests that these differences can be due to the different ways evidence is used, according to two main basic modalities of processing information, analytically or holistically. In order to test the impact of the information provided, an inductive rule-based task was designed, in which feature salience and comparison informativeness between examples of two categories were manipulated during the learning phases, by introducing and progressively reducing some perceptual biases. To gather data on processing modalities, we devised the Active Feature Composition task, a production task that does not require classifying new items but reproducing them by combining features. At the end, an explicit rating task was performed, which entailed assessing the accuracy of a set of possible categorization rules. A combined analysis of the data collected with these two different tests enabled profiling participants in regard to the kind of processing modality, the structure of representations and the quality of categorial judgments. Results showed that despite the fact that the information provided was the same for all participants, those who adopted analytic processing better exploited evidence and performed more accurately, whereas with holistic processing categorization is perfectly possible but inaccurate. Finally, the cognitive implications of the proposed procedure, with regard to involved processes and representations, are discussed.

Rule-guided human classification of Volunteered Geographic Information

NASA Astrophysics Data System (ADS)

Ali, Ahmed Loai; Falomir, Zoe; Schmid, Falko; Freksa, Christian

2017-05-01

During the last decade, web technologies and location sensing devices have evolved generating a form of crowdsourcing known as Volunteered Geographic Information (VGI). VGI acted as a platform of spatial data collection, in particular, when a group of public participants are involved in collaborative mapping activities: they work together to collect, share, and use information about geographic features. VGI exploits participants' local knowledge to produce rich data sources. However, the resulting data inherits problematic data classification. In VGI projects, the challenges of data classification are due to the following: (i) data is likely prone to subjective classification, (ii) remote contributions and flexible contribution mechanisms in most projects, and (iii) the uncertainty of spatial data and non-strict definitions of geographic features. These factors lead to various forms of problematic classification: inconsistent, incomplete, and imprecise data classification. This research addresses classification appropriateness. Whether the classification of an entity is appropriate or inappropriate is related to quantitative and/or qualitative observations. Small differences between observations may be not recognizable particularly for non-expert participants. Hence, in this paper, the problem is tackled by developing a rule-guided classification approach. This approach exploits data mining techniques of Association Classification (AC) to extract descriptive (qualitative) rules of specific geographic features. The rules are extracted based on the investigation of qualitative topological relations between target features and their context. Afterwards, the extracted rules are used to develop a recommendation system able to guide participants to the most appropriate classification. The approach proposes two scenarios to guide participants towards enhancing the quality of data classification. An empirical study is conducted to investigate the classification of grass-related features like forest, garden, park, and meadow. The findings of this study indicate the feasibility of the proposed approach.

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.

A knowledge based application of the extended aircraft interrogation and display system

NASA Technical Reports Server (NTRS)

Glover, Richard D.; Larson, Richard R.

1991-01-01

A family of multiple-processor ground support test equipment was used to test digital flight-control systems on high-performance research aircraft. A unit recently built for the F-18 high alpha research vehicle project is the latest model in a series called the extended aircraft interrogation and display system. The primary feature emphasized monitors the aircraft MIL-STD-1553B data buses and provides real-time engineering units displays of flight-control parameters. A customized software package was developed to provide real-time data interpretation based on rules embodied in a highly structured knowledge database. The configuration of this extended aircraft interrogation and display system is briefly described, and the evolution of the rule based package and its application to failure modes and effects testing on the F-18 high alpha research vehicle is discussed.

A Darwinian approach to control-structure design

NASA Technical Reports Server (NTRS)

Zimmerman, David C.

1993-01-01

Genetic algorithms (GA's), as introduced by Holland (1975), are one form of directed random search. The form of direction is based on Darwin's 'survival of the fittest' theories. GA's are radically different from the more traditional design optimization techniques. GA's work with a coding of the design variables, as opposed to working with the design variables directly. The search is conducted from a population of designs (i.e., from a large number of points in the design space), unlike the traditional algorithms which search from a single design point. The GA requires only objective function information, as opposed to gradient or other auxiliary information. Finally, the GA is based on probabilistic transition rules, as opposed to deterministic rules. These features allow the GA to attack problems with local-global minima, discontinuous design spaces and mixed variable problems, all in a single, consistent framework.

Enhancing topology adaptation in information-sharing social networks

NASA Astrophysics Data System (ADS)

Cimini, Giulio; Chen, Duanbing; Medo, Matúš; Lü, Linyuan; Zhang, Yi-Cheng; Zhou, Tao

2012-04-01

The advent of the Internet and World Wide Web has led to unprecedent growth of the information available. People usually face the information overload by following a limited number of sources which best fit their interests. It has thus become important to address issues like who gets followed and how to allow people to discover new and better information sources. In this paper we conduct an empirical analysis of different online social networking sites and draw inspiration from its results to present different source selection strategies in an adaptive model for social recommendation. We show that local search rules which enhance the typical topological features of real social communities give rise to network configurations that are globally optimal. These rules create networks which are effective in information diffusion and resemble structures resulting from real social systems.

Eyes Matched to the Prize: The State of Matched Filters in Insect Visual Circuits.

PubMed

Kohn, Jessica R; Heath, Sarah L; Behnia, Rudy

2018-01-01

Confronted with an ever-changing visual landscape, animals must be able to detect relevant stimuli and translate this information into behavioral output. A visual scene contains an abundance of information: to interpret the entirety of it would be uneconomical. To optimally perform this task, neural mechanisms exist to enhance the detection of important features of the sensory environment while simultaneously filtering out irrelevant information. This can be accomplished by using a circuit design that implements specific "matched filters" that are tuned to relevant stimuli. Following this rule, the well-characterized visual systems of insects have evolved to streamline feature extraction on both a structural and functional level. Here, we review examples of specialized visual microcircuits for vital behaviors across insect species, including feature detection, escape, and estimation of self-motion. Additionally, we discuss how these microcircuits are modulated to weigh relevant input with respect to different internal and behavioral states.

Automatic rule generation for high-level vision

NASA Technical Reports Server (NTRS)

Rhee, Frank Chung-Hoon; Krishnapuram, Raghu

1992-01-01

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

A rule-based automatic sleep staging method.

PubMed

Liang, Sheng-Fu; Kuo, Chin-En; Hu, Yu-Han; Cheng, Yu-Shian

2012-03-30

In this paper, a rule-based automatic sleep staging method was proposed. Twelve features including temporal and spectrum analyses of the EEG, EOG, and EMG signals were utilized. Normalization was applied to each feature to eliminating individual differences. A hierarchical decision tree with fourteen rules was constructed for sleep stage classification. Finally, a smoothing process considering the temporal contextual information was applied for the continuity. The overall agreement and kappa coefficient of the proposed method applied to the all night polysomnography (PSG) of seventeen healthy subjects compared with the manual scorings by R&K rules can reach 86.68% and 0.79, respectively. This method can integrate with portable PSG system for sleep evaluation at-home in the near future. Copyright © 2012 Elsevier B.V. All rights reserved.

A Corner-Point-Grid-Based Voxelization Method for Complex Geological Structure Model with Folds

NASA Astrophysics Data System (ADS)

Chen, Qiyu; Mariethoz, Gregoire; Liu, Gang

2017-04-01

3D voxelization is the foundation of geological property modeling, and is also an effective approach to realize the 3D visualization of the heterogeneous attributes in geological structures. The corner-point grid is a representative data model among all voxel models, and is a structured grid type that is widely applied at present. When carrying out subdivision for complex geological structure model with folds, we should fully consider its structural morphology and bedding features to make the generated voxels keep its original morphology. And on the basis of which, they can depict the detailed bedding features and the spatial heterogeneity of the internal attributes. In order to solve the shortage of the existing technologies, this work puts forward a corner-point-grid-based voxelization method for complex geological structure model with folds. We have realized the fast conversion from the 3D geological structure model to the fine voxel model according to the rule of isocline in Ramsay's fold classification. In addition, the voxel model conforms to the spatial features of folds, pinch-out and other complex geological structures, and the voxels of the laminas inside a fold accords with the result of geological sedimentation and tectonic movement. This will provide a carrier and model foundation for the subsequent attribute assignment as well as the quantitative analysis and evaluation based on the spatial voxels. Ultimately, we use examples and the contrastive analysis between the examples and the Ramsay's description of isoclines to discuss the effectiveness and advantages of the method proposed in this work when dealing with the voxelization of 3D geologic structural model with folds based on corner-point grids.

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.

Channel branching ratios in CH2CN- photodetachment: Rotational structure and vibrational energy redistribution in autodetachment

NASA Astrophysics Data System (ADS)

Lyle, Justin; Wedig, Olivia; Gulania, Sahil; Krylov, Anna I.; Mabbs, Richard

2017-12-01

We report photoelectron spectra of CH2CN-, recorded at photon energies between 13 460 and 15 384 cm-1, which show rapid intensity variations in particular detachment channels. The branching ratios for various spectral features reveal rotational structure associated with autodetachment from an intermediate anion state. Calculations using equation-of-motion coupled-cluster method with single and double excitations reveal the presence of two dipole-bound excited anion states (a singlet and a triplet). The computed oscillator strength for the transition to the singlet dipole-bound state provides an estimate of the autodetachment channel contribution to the total photoelectron yield. Analysis of the different spectral features allows identification of the dipole-bound and neutral vibrational levels involved in the autodetachment processes. For the most part, the autodetachment channels are consistent with the vibrational propensity rule and normal mode expectation. However, examination of the rotational structure shows that autodetachment from the ν3 (v = 1 and v = 2) levels of the dipole-bound state displays behavior counter to the normal mode expectation with the final state vibrational level belonging to a different mode.

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.

Plasticity-Driven Self-Organization under Topological Constraints Accounts for Non-random Features of Cortical Synaptic Wiring

PubMed Central

Miner, Daniel; Triesch, Jochen

2016-01-01

Understanding the structure and dynamics of cortical connectivity is vital to understanding cortical function. Experimental data strongly suggest that local recurrent connectivity in the cortex is significantly non-random, exhibiting, for example, above-chance bidirectionality and an overrepresentation of certain triangular motifs. Additional evidence suggests a significant distance dependency to connectivity over a local scale of a few hundred microns, and particular patterns of synaptic turnover dynamics, including a heavy-tailed distribution of synaptic efficacies, a power law distribution of synaptic lifetimes, and a tendency for stronger synapses to be more stable over time. Understanding how many of these non-random features simultaneously arise would provide valuable insights into the development and function of the cortex. While previous work has modeled some of the individual features of local cortical wiring, there is no model that begins to comprehensively account for all of them. We present a spiking network model of a rodent Layer 5 cortical slice which, via the interactions of a few simple biologically motivated intrinsic, synaptic, and structural plasticity mechanisms, qualitatively reproduces these non-random effects when combined with simple topological constraints. Our model suggests that mechanisms of self-organization arising from a small number of plasticity rules provide a parsimonious explanation for numerous experimentally observed non-random features of recurrent cortical wiring. Interestingly, similar mechanisms have been shown to endow recurrent networks with powerful learning abilities, suggesting that these mechanism are central to understanding both structure and function of cortical synaptic wiring. PMID:26866369

Design rules for phase-change materials in data storage applications.

PubMed

Lencer, Dominic; Salinga, Martin; Wuttig, Matthias

2011-05-10

Phase-change materials can rapidly and reversibly be switched between an amorphous and a crystalline phase. Since both phases are characterized by very different optical and electrical properties, these materials can be employed for rewritable optical and electrical data storage. Hence, there are considerable efforts to identify suitable materials, and to optimize them with respect to specific applications. Design rules that can explain why the materials identified so far enable phase-change based devices would hence be very beneficial. This article describes materials that have been successfully employed and dicusses common features regarding both typical structures and bonding mechanisms. It is shown that typical structural motifs and electronic properties can be found in the crystalline state that are indicative for resonant bonding, from which the employed contrast originates. The occurence of resonance is linked to the composition, thus providing a design rule for phase-change materials. This understanding helps to unravel characteristic properties such as electrical and thermal conductivity which are discussed in the subsequent section. Then, turning to the transition kinetics between the phases, the current understanding and modeling of the processes of amorphization and crystallization are discussed. Finally, present approaches for improved high-capacity optical discs and fast non-volatile electrical memories, that hold the potential to succeed present-day's Flash memory, are presented. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Applications of CPL mask technology for sub-65nm gate imaging

NASA Astrophysics Data System (ADS)

Litt, Lloyd C.; Conley, Will; Wu, Wei; Peters, Richie; Parker, Colita; Cobb, Jonathan; Kasprowicz, Bryan S.; van den Broeke, Doug; Park, J. C.; Karur-Shanmugam, Ramkumar

2005-05-01

The requirements for critical dimension control on gate layer for high performance products are increasingly demanding. Phase shift techniques provide aerial image enhancement, which can translate into improved process window performance and greater critical dimension (CD) control if properly applied. Unfortunately, the application of hard shifter technology to production requires significant effort in layout and optical proximity correction (OPC) application. Chromeless Phase Lithography (CPL) has several advantages over complementary phase mask (c:PSM) such as use of a single mask, and lack of phase placement 'coloring' conflicts and phase imbalance issues. CPL does have implementation issues that must be resolved before it can be used in full-scale production. CPL mask designs can be approached by separating features into three zones based on several parameters, including size relative to the lithographic resolution of the stepper lens, wavelength, and illumination conditions defined. Features are placed into buckets for different treatment zones. Zone 1 features are constructed with 100% transmission phase shifted structures and Zone 3 features are chrome (binary) structures. Features that fall into Zone 2, which are too wide to be defined using the 100% transmission of pure CPL (i.e. have negative mask error factor, MEEF) are the most troublesome and can be approached in several ways. The authors have investigated the application of zebra structures of various sizes to product type layouts. Previous work to investigate CPL using test structures set the groundwork for the more difficult task of applying CPL rules to actual random logic design layouts, which include many zone transitions. Mask making limitations have been identified that play a role in the zebra sizing that can be applied to Zone 2 features. The elimination of Zone 2 regions was also investigated in an effort to simplify the application of CPL and improve manufacturability of reticle through data enhancements.

Evaluation of vector coastline features extracted from 'structure from motion'-derived elevation data

USGS Publications Warehouse

Kinsman, Nicole; Gibbs, Ann E.; Nolan, Matt

2015-01-01

For extensive and remote coastlines, the absence of high-quality elevation models—for example, those produced with lidar—leaves some coastal populations lacking one of the essential elements for mapping shoreline positions or flood extents. Here, we compare seven different elevation products in a lowlying area in western Alaska to establish their appropriateness for coastal mapping applications that require the delineation of elevation-based vectors. We further investigate the effective use of a Structure from Motion (SfM)-derived surface model (vertical RMSE<20 cm) by generating a tidal datum-based shoreline and an inundation extent map for a 2011 flood event. Our results suggest that SfM-derived elevation products can yield elevation-based vector features that have horizontal positional uncertainties comparable to those derived from other techniques. We also provide a rule-of-thumb equation to aid in the selection of minimum elevation model specifications based on terrain slope, vertical uncertainties, and desired horizontal accuracy.

Eclipsing the Light...Fantastic! Teaching Science.

ERIC Educational Resources Information Center

Leyden, Michael B.

1995-01-01

Features the concepts of optics and geometry of eclipses. Presents the "eclipse rule," suggesting classroom activities in which students derive this rule. Includes some triangles activities for outdoors that illustrate eclipsing and sighting phenomena. (ET)

Textural features for image classification

NASA Technical Reports Server (NTRS)

Haralick, R. M.; Dinstein, I.; Shanmugam, K.

1973-01-01

Description of some easily computable textural features based on gray-tone spatial dependances, and illustration of their application in category-identification tasks of three different kinds of image data - namely, photomicrographs of five kinds of sandstones, 1:20,000 panchromatic aerial photographs of eight land-use categories, and ERTS multispectral imagery containing several land-use categories. Two kinds of decision rules are used - one for which the decision regions are convex polyhedra (a piecewise-linear decision rule), and one for which the decision regions are rectangular parallelpipeds (a min-max decision rule). In each experiment the data set was divided into two parts, a training set and a test set. Test set identification accuracy is 89% for the photomicrographs, 82% for the aerial photographic imagery, and 83% for the satellite imagery. These results indicate that the easily computable textural features probably have a general applicability for a wide variety of image-classification applications.

GLYDE-II: The GLYcan data exchange format

PubMed Central

Ranzinger, Rene; Kochut, Krys J.; Miller, John A.; Eavenson, Matthew; Lütteke, Thomas; York, William S.

2017-01-01

Summary The GLYcan Data Exchange (GLYDE) standard has been developed for the representation of the chemical structures of monosaccharides, glycans and glycoconjugates using a connection table formalism formatted in XML. This format allows structures, including those that do not exist in any database, to be unambiguously represented and shared by diverse computational tools. GLYDE implements a partonomy model based on human language along with rules that provide consistent structural representations, including a robust namespace for specifying monosaccharides. This approach facilitates the reuse of data processing software at the level of granularity that is most appropriate for extraction of the desired information. GLYDE-II has already been used as a key element of several glycoinformatics tools. The philosophical and technical underpinnings of GLYDE-II and recent implementation of its enhanced features are described. PMID:28955652

Virtual Lead Identification of Farnesyltransferase Inhibitors Based on Ligand and Structure-Based Pharmacophore Techniques

PubMed Central

Al-Balas, Qosay A.; Amawi, Haneen A.; Hassan, Mohammad A.; Qandil, Amjad M.; Almaaytah, Ammar M.; Mhaidat, Nizar M.

2013-01-01

Farnesyltransferase enzyme (FTase) is considered an essential enzyme in the Ras signaling pathway associated with cancer. Thus, designing inhibitors for this enzyme might lead to the discovery of compounds with effective anticancer activity. In an attempt to obtain effective FTase inhibitors, pharmacophore hypotheses were generated using structure-based and ligand-based approaches built in Discovery Studio v3.1. Knowing the presence of the zinc feature is essential for inhibitor’s binding to the active site of FTase enzyme; further customization was applied to include this feature in the generated pharmacophore hypotheses. These pharmacophore hypotheses were thoroughly validated using various procedures such as ROC analysis and ligand pharmacophore mapping. The validated pharmacophore hypotheses were used to screen 3D databases to identify possible hits. Those which were both high ranked and showed sufficient ability to bind the zinc feature in active site, were further refined by applying drug-like criteria such as Lipiniski’s “rule of five” and ADMET filters. Finally, the two candidate compounds (ZINC39323901 and ZINC01034774) were allowed to dock using CDOCKER and GOLD in the active site of FTase enzyme to optimize hit selection. PMID:24276257

Virtual lead identification of farnesyltransferase inhibitors based on ligand and structure-based pharmacophore techniques.

PubMed

Al-Balas, Qosay A; Amawi, Haneen A; Hassan, Mohammad A; Qandil, Amjad M; Almaaytah, Ammar M; Mhaidat, Nizar M

2013-05-27

Farnesyltransferase enzyme (FTase) is considered an essential enzyme in the Ras signaling pathway associated with cancer. Thus, designing inhibitors for this enzyme might lead to the discovery of compounds with effective anticancer activity. In an attempt to obtain effective FTase inhibitors, pharmacophore hypotheses were generated using structure-based and ligand-based approaches built in Discovery Studio v3.1. Knowing the presence of the zinc feature is essential for inhibitor's binding to the active site of FTase enzyme; further customization was applied to include this feature in the generated pharmacophore hypotheses. These pharmacophore hypotheses were thoroughly validated using various procedures such as ROC analysis and ligand pharmacophore mapping. The validated pharmacophore hypotheses were used to screen 3D databases to identify possible hits. Those which were both high ranked and showed sufficient ability to bind the zinc feature in active site, were further refined by applying drug-like criteria such as Lipiniski's "rule of five" and ADMET filters. Finally, the two candidate compounds (ZINC39323901 and ZINC01034774) were allowed to dock using CDOCKER and GOLD in the active site of FTase enzyme to optimize hit selection.

Retrieval Capabilities of Hierarchical Networks: From Dyson to Hopfield

NASA Astrophysics Data System (ADS)

Agliari, Elena; Barra, Adriano; Galluzzi, Andrea; Guerra, Francesco; Tantari, Daniele; Tavani, Flavia

2015-01-01

We consider statistical-mechanics models for spin systems built on hierarchical structures, which provide a simple example of non-mean-field framework. We show that the coupling decay with spin distance can give rise to peculiar features and phase diagrams much richer than their mean-field counterpart. In particular, we consider the Dyson model, mimicking ferromagnetism in lattices, and we prove the existence of a number of metastabilities, beyond the ordered state, which become stable in the thermodynamic limit. Such a feature is retained when the hierarchical structure is coupled with the Hebb rule for learning, hence mimicking the modular architecture of neurons, and gives rise to an associative network able to perform single pattern retrieval as well as multiple-pattern retrieval, depending crucially on the external stimuli and on the rate of interaction decay with distance; however, those emergent multitasking features reduce the network capacity with respect to the mean-field counterpart. The analysis is accomplished through statistical mechanics, Markov chain theory, signal-to-noise ratio technique, and numerical simulations in full consistency. Our results shed light on the biological complexity shown by real networks, and suggest future directions for understanding more realistic models.

Designing using manufacturing features

NASA Astrophysics Data System (ADS)

Szecsi, T.; Hoque, A. S. M.

2012-04-01

This paper presents a design system that enables the composition of a part using manufacturing features. Features are selected from feature libraries. Upon insertion, the system ensures that the feature does not contradict the design-for-manufacture rules. This helps eliminating costly manufacturing problems. The system is developed as an extension to a commercial CAD/CAM system Pro/Engineer.

Langmuir-Blodgett Films of Supported Polyester Dendrimers

PubMed Central

Redón, Rocío; Carreón-Castro, M. Pilar; Mendoza-Martínez, F. J.

2012-01-01

Amphiphiles with a dendritic structure are attractive materials as they combine the features of dendrimers with the self-assembling properties and interfacial behavior of water-air affinities. We have synthesized three generations of polyester dendrimers and studied their interfacial properties on the Langmuir films. The behavior obtained was, as a rule, the lowest generation dendrimers behaving like traditional amphiphiles and the larger molecules presenting complicated isotherms. The Langmuir films of these compounds have been characterized by their surface pressure versus molecular area (π/A) and Brewster angle microscopy (BAM) observations. PMID:24052855

Young Children's Knowledge about the Influence of Thoughts on Emotions in Rule Situations

ERIC Educational Resources Information Center

Lagattuta, Kristin Hansen

2008-01-01

Four-year-olds, 5-year-olds, and adults (N = 48) listened to stories featuring characters that experienced one of four types of thoughts after deciding to transgress or comply with a rule: thoughts about desires, rules, future negative outcomes, or future punishment. Participants predicted and explained the characters' emotions. Results showed…

A model of Beijing drivers' scrambling behaviors.

PubMed

Shi, Jing; Bai, Yun; Tao, Li; Atchley, Paul

2011-07-01

A major, but unstudied, cause of crashes in China is drivers that "scramble" to gain the right of way in violation of traffic regulations. The motivation of this study is to explore the features of drivers' scrambling behaviors and the attitudes and driving skills that influence them. In this study, we established a scrambling behavior scale, and developed a driving attitude scale and a driving skill scale using factor analysis of an Internet survey of 486 drivers in Beijing. A structural equation model of scrambling behavior toward cars and pedestrians/cyclists was developed with attitudes and skills as predictors of behavior. Skills and attitudes of approval toward violations of traffic rules did not predict scrambling behaviors, while the motivation for safety and attitudes against violating traffic rules led to reduced scrambling behaviors. The current work highlights this peculiar aspect of Chinese roads and suggests methods to reduce the behavior. Copyright © 2011 Elsevier Ltd. All rights reserved.

Discriminant Features and Temporal Structure of Nonmanuals in American Sign Language

PubMed Central

Benitez-Quiroz, C. Fabian; Gökgöz, Kadir; Wilbur, Ronnie B.; Martinez, Aleix M.

2014-01-01

To fully define the grammar of American Sign Language (ASL), a linguistic model of its nonmanuals needs to be constructed. While significant progress has been made to understand the features defining ASL manuals, after years of research, much still needs to be done to uncover the discriminant nonmanual components. The major barrier to achieving this goal is the difficulty in correlating facial features and linguistic features, especially since these correlations may be temporally defined. For example, a facial feature (e.g., head moves down) occurring at the end of the movement of another facial feature (e.g., brows moves up), may specify a Hypothetical conditional, but only if this time relationship is maintained. In other instances, the single occurrence of a movement (e.g., brows move up) can be indicative of the same grammatical construction. In the present paper, we introduce a linguistic–computational approach to efficiently carry out this analysis. First, a linguistic model of the face is used to manually annotate a very large set of 2,347 videos of ASL nonmanuals (including tens of thousands of frames). Second, a computational approach is used to determine which features of the linguistic model are more informative of the grammatical rules under study. We used the proposed approach to study five types of sentences – Hypothetical conditionals, Yes/no questions, Wh-questions, Wh-questions postposed, and Assertions – plus their polarities – positive and negative. Our results verify several components of the standard model of ASL nonmanuals and, most importantly, identify several previously unreported features and their temporal relationship. Notably, our results uncovered a complex interaction between head position and mouth shape. These findings define some temporal structures of ASL nonmanuals not previously detected by other approaches. PMID:24516528

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

PubMed

Dawson, Colin; Gerken, Louann

2011-09-01

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

Free-form machining for micro-imaging systems

NASA Astrophysics Data System (ADS)

Barkman, Michael L.; Dutterer, Brian S.; Davies, Matthew A.; Suleski, Thomas J.

2008-02-01

While mechanical ruling and single point diamond turning has been a mainstay of optical fabrication for many years, many types of micro-optical devices and structures are not conducive to simple diamond turning or ruling, such as, for example, microlens arrays, and optical surfaces with non-radial symmetry. More recent developments in machining technology have enabled significant expansion of fabrication capabilities. Modern machine tools can generate complex three-dimensional structures with optical quality surface finish, and fabricate structures across a dynamic range of dimensions not achievable with lithographic techniques. In particular, five-axis free-form micromachining offers a great deal of promise for realization of essentially arbitrary surface structures, including surfaces not realizable through binary or analog lithographic techniques. Furthermore, these machines can generate geometric features with optical finish on scales ranging from centimeters to micrometers with accuracies of 10s of nanometers. In this paper, we discuss techniques and applications of free-form surface machining of micro-optical elements. Aspects of diamond machine tool design to realize desired surface geometries in specific materials are discussed. Examples are presented, including fabrication of aspheric lens arrays in germanium for compact infrared imaging systems. Using special custom kinematic mounting equipment and the additional axes of the machine, the lenses were turned with surface finish better than 2 nm RMS and center to center positioning accuracy of +/-0.5 μm.

Ultimate strength performance of tankers associated with industry corrosion addition practices

NASA Astrophysics Data System (ADS)

Kim, Do Kyun; Kim, Han Byul; Zhang, Xiaoming; Li, Chen Guang; Paik, Jeom Kee

2014-09-01

In the ship and offshore structure design, age-related problems such as corrosion damage, local denting, and fatigue damage are important factors to be considered in building a reliable structure as they have a significant influence on the residual structural capacity. In shipping, corrosion addition methods are widely adopted in structural design to prevent structural capacity degradation. The present study focuses on the historical trend of corrosion addition rules for ship structural design and investigates their effects on the ultimate strength performance such as hull girder and stiffened panel of double hull oil tankers. Three types of rules based on corrosion addition models, namely historic corrosion rules (pre-CSR), Common Structural Rules (CSR), and harmonised Common Structural Rules (CSRH) are considered and compared with two other corrosion models namely UGS model, suggested by the Union of Greek Shipowners (UGS), and Time-Dependent Corrosion Wastage Model (TDCWM). To identify the general trend in the effects of corrosion damage on the ultimate longitudinal strength performance, the corrosion addition rules are applied to four representative sizes of double hull oil tankers namely Panamax, Aframax, Suezmax, and VLCC. The results are helpful in understanding the trend of corrosion additions for tanker structures

DeepNeuron: an open deep learning toolbox for neuron tracing.

PubMed

Zhou, Zhi; Kuo, Hsien-Chi; Peng, Hanchuan; Long, Fuhui

2018-06-06

Reconstructing three-dimensional (3D) morphology of neurons is essential for understanding brain structures and functions. Over the past decades, a number of neuron tracing tools including manual, semiautomatic, and fully automatic approaches have been developed to extract and analyze 3D neuronal structures. Nevertheless, most of them were developed based on coding certain rules to extract and connect structural components of a neuron, showing limited performance on complicated neuron morphology. Recently, deep learning outperforms many other machine learning methods in a wide range of image analysis and computer vision tasks. Here we developed a new Open Source toolbox, DeepNeuron, which uses deep learning networks to learn features and rules from data and trace neuron morphology in light microscopy images. DeepNeuron provides a family of modules to solve basic yet challenging problems in neuron tracing. These problems include but not limited to: (1) detecting neuron signal under different image conditions, (2) connecting neuronal signals into tree(s), (3) pruning and refining tree morphology, (4) quantifying the quality of morphology, and (5) classifying dendrites and axons in real time. We have tested DeepNeuron using light microscopy images including bright-field and confocal images of human and mouse brain, on which DeepNeuron demonstrates robustness and accuracy in neuron tracing.

Phonological Concept Learning.

PubMed

Moreton, Elliott; Pater, Joe; Pertsova, Katya

2017-01-01

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

Optimal number of features as a function of sample size for various classification rules.

PubMed

Hua, Jianping; Xiong, Zixiang; Lowey, James; Suh, Edward; Dougherty, Edward R

2005-04-15

Given the joint feature-label distribution, increasing the number of features always results in decreased classification error; however, this is not the case when a classifier is designed via a classification rule from sample data. Typically (but not always), for fixed sample size, the error of a designed classifier decreases and then increases as the number of features grows. The potential downside of using too many features is most critical for small samples, which are commonplace for gene-expression-based classifiers for phenotype discrimination. For fixed sample size and feature-label distribution, the issue is to find an optimal number of features. Since only in rare cases is there a known distribution of the error as a function of the number of features and sample size, this study employs simulation for various feature-label distributions and classification rules, and across a wide range of sample and feature-set sizes. To achieve the desired end, finding the optimal number of features as a function of sample size, it employs massively parallel computation. Seven classifiers are treated: 3-nearest-neighbor, Gaussian kernel, linear support vector machine, polynomial support vector machine, perceptron, regular histogram and linear discriminant analysis. Three Gaussian-based models are considered: linear, nonlinear and bimodal. In addition, real patient data from a large breast-cancer study is considered. To mitigate the combinatorial search for finding optimal feature sets, and to model the situation in which subsets of genes are co-regulated and correlation is internal to these subsets, we assume that the covariance matrix of the features is blocked, with each block corresponding to a group of correlated features. Altogether there are a large number of error surfaces for the many cases. These are provided in full on a companion website, which is meant to serve as resource for those working with small-sample classification. For the companion website, please visit http://public.tgen.org/tamu/ofs/ e-dougherty@ee.tamu.edu.

Analysis of cell division patterns in the Arabidopsis shoot apical meristem

DOE PAGES

Shapiro, Bruce E.; Tobin, Cory; Mjolsness, Eric; ...

2015-03-30

The stereotypic pattern of cell shapes in the Arabidopsis shoot apical meristem (SAM) suggests that strict rules govern the placement of new walls during cell division. When a cell in the SAM divides, a new wall is built that connects existing walls and divides the cytoplasm of the daughter cells. Because features that are determined by the placement of new walls such as cell size, shape, and number of neighbors are highly regular, rules must exist for maintaining such order. Here in this paper we present a quantitative model of these rules that incorporates different observed features of cell division.more » Each feature is incorporated into a "potential function" that contributes a single term to a total analog of potential energy. New cell walls are predicted to occur at locations where the potential function is minimized. Quantitative terms that represent the well-known historical rules of plant cell division, such as those given by Hofmeister, Errera, and Sachs are developed and evaluated against observed cell divisions in the epidermal layer (L1) of Arabidopsis thaliana SAM. The method is general enough to allow additional terms for nongeometric properties such as internal concentration gradients and mechanical tensile forces.« less

Model-assisted template extraction SRAF application to contact holes patterns in high-end flash memory device fabrication

NASA Astrophysics Data System (ADS)

Seoud, Ahmed; Kim, Juhwan; Ma, Yuansheng; Jayaram, Srividya; Hong, Le; Chae, Gyu-Yeol; Lee, Jeong-Woo; Park, Dae-Jin; Yune, Hyoung-Soon; Oh, Se-Young; Park, Chan-Ha

2018-03-01

Sub-resolution assist feature (SRAF) insertion techniques have been effectively used for a long time now to increase process latitude in the lithography patterning process. Rule-based SRAF and model-based SRAF are complementary solutions, and each has its own benefits, depending on the objectives of applications and the criticality of the impact on manufacturing yield, efficiency, and productivity. Rule-based SRAF provides superior geometric output consistency and faster runtime performance, but the associated recipe development time can be of concern. Model-based SRAF provides better coverage for more complicated pattern structures in terms of shapes and sizes, with considerably less time required for recipe development, although consistency and performance may be impacted. In this paper, we introduce a new model-assisted template extraction (MATE) SRAF solution, which employs decision tree learning in a model-based solution to provide the benefits of both rule-based and model-based SRAF insertion approaches. The MATE solution is designed to automate the creation of rules/templates for SRAF insertion, and is based on the SRAF placement predicted by model-based solutions. The MATE SRAF recipe provides optimum lithographic quality in relation to various manufacturing aspects in a very short time, compared to traditional methods of rule optimization. Experiments were done using memory device pattern layouts to compare the MATE solution to existing model-based SRAF and pixelated SRAF approaches, based on lithographic process window quality, runtime performance, and geometric output consistency.

Entropy, pricing and productivity of pumped-storage

NASA Astrophysics Data System (ADS)

Karakatsanis, Georgios; Tyralis, Hristos; Tzouka, Katerina

2016-04-01

Pumped-storage constitutes today a mature method of bulk electricity storage in the form of hydropower. This bulk electricity storability upgrades the economic value of hydropower as it may mitigate -or even neutralize- stochastic effects deriving from various geophysical and socioeconomic factors, which produce numerous load balance inefficiencies due to increased uncertainty. Pumped-storage further holds a key role for unifying intermittent renewable (i.e. wind, solar) units with controllable non-renewable (i.e. nuclear, coal) fuel electricity generation plants into integrated energy systems. We develop a set of indicators for the measurement of performance of pumped-storage, in terms of the latter's energy and financial contribution to the energy system. More specifically, we use the concept of entropy in order to examine: (1) the statistical features -and correlations- of the energy system's intermittent components and (2) the statistical features of electricity demand prediction deviations. In this way, the macroeconomics of pumped-storage emerges naturally from its statistical features (Karakatsanis et al. 2014). In addition, these findings are combined to actual daily loads. Hence, not only the amount of energy harvested from the pumped-storage component is expected to be important, but the harvesting time as well, as the intraday price of electricity varies significantly. Additionally, the structure of the pumped-storage market proves to be a significant factor as well for the system's energy and financial performance (Paine et al. 2014). According to the above, we aim at postulating a set of general rules on the productivity of pumped-storage for (integrated) energy systems. Keywords: pumped-storage, storability, economic value of hydropower, stochastic effects, uncertainty, energy systems, entropy, intraday electricity price, productivity References 1. Karakatsanis, Georgios et al. (2014), Entropy, pricing and macroeconomics of pumped-storage systems, Vienna, Austria, April 27 - May 2 2014, "The Face of the Earth - Process and Form", European Geophysical Union General Assembly 2. Paine, Nathan et al. (2014), Why market rules matter: Optimizing pumped hydroelectric storage when compensation rules differ, Energy Economics 46, 10-19

Hierarchical structure for audio-video based semantic classification of sports video sequences

NASA Astrophysics Data System (ADS)

Kolekar, M. H.; Sengupta, S.

2005-07-01

A hierarchical structure for sports event classification based on audio and video content analysis is proposed in this paper. Compared to the event classifications in other games, those of cricket are very challenging and yet unexplored. We have successfully solved cricket video classification problem using a six level hierarchical structure. The first level performs event detection based on audio energy and Zero Crossing Rate (ZCR) of short-time audio signal. In the subsequent levels, we classify the events based on video features using a Hidden Markov Model implemented through Dynamic Programming (HMM-DP) using color or motion as a likelihood function. For some of the game-specific decisions, a rule-based classification is also performed. Our proposed hierarchical structure can easily be applied to any other sports. Our results are very promising and we have moved a step forward towards addressing semantic classification problems in general.

When More Is Less: Feedback Effects in Perceptual Category Learning

ERIC Educational Resources Information Center

Maddox, W. Todd; Love, Bradley C.; Glass, Brian D.; Filoteo, J. Vincent

2008-01-01

Rule-based and information-integration category learning were compared under minimal and full feedback conditions. Rule-based category structures are those for which the optimal rule is verbalizable. Information-integration category structures are those for which the optimal rule is not verbalizable. With minimal feedback subjects are told whether…

76 FR 12896 - References to Credit Ratings in Certain Investment Company Act Rules and Forms

Federal Register 2010, 2011, 2012, 2013, 2014

2011-03-09

... several releases that the Securities and Exchange Commission (``Commission'') will be considering relating... Conditional Demand Feature 3. Monitoring Minimal Credit Risks 4. Stress Testing B. Form N-MFP C. Rule 5b-3 D... events; and stress testing.\\20\\ The proposed amendments to rule 2a-7, which are similar to those we...

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.

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

A Novel Feature Level Fusion for Heart Rate Variability Classification Using Correntropy and Cauchy-Schwarz Divergence.

PubMed

Goshvarpour, Ateke; Goshvarpour, Atefeh

2018-04-30

Heart rate variability (HRV) analysis has become a widely used tool for monitoring pathological and psychological states in medical applications. In a typical classification problem, information fusion is a process whereby the effective combination of the data can achieve a more accurate system. The purpose of this article was to provide an accurate algorithm for classifying HRV signals in various psychological states. Therefore, a novel feature level fusion approach was proposed. First, using the theory of information, two similarity indicators of the signal were extracted, including correntropy and Cauchy-Schwarz divergence. Applying probabilistic neural network (PNN) and k-nearest neighbor (kNN), the performance of each index in the classification of meditators and non-meditators HRV signals was appraised. Then, three fusion rules, including division, product, and weighted sum rules were used to combine the information of both similarity measures. For the first time, we propose an algorithm to define the weights of each feature based on the statistical p-values. The performance of HRV classification using combined features was compared with the non-combined features. Totally, the accuracy of 100% was obtained for discriminating all states. The results showed the strong ability and proficiency of division and weighted sum rules in the improvement of the classifier accuracies.

Circuit topology of proteins and nucleic acids.

PubMed

Mashaghi, Alireza; van Wijk, Roeland J; Tans, Sander J

2014-09-02

Folded biomolecules display a bewildering structural complexity and diversity. They have therefore been analyzed in terms of generic topological features. For instance, folded proteins may be knotted, have beta-strands arranged into a Greek-key motif, or display high contact order. In this perspective, we present a method to formally describe the topology of all folded linear chains and hence provide a general classification and analysis framework for a range of biomolecules. Moreover, by identifying the fundamental rules that intrachain contacts must obey, the method establishes the topological constraints of folded linear chains. We also briefly illustrate how this circuit topology notion can be applied to study the equivalence of folded chains, the engineering of artificial RNA structures and DNA origami, the topological structure of genomes, and the role of topology in protein folding. Copyright © 2014 Elsevier Ltd. All rights reserved.

Oxytocin conditions trait-based rule adherence

PubMed Central

De Dreu, Carsten K.W.

2017-01-01

Abstract Rules, whether in the form of norms, taboos or laws, regulate and coordinate human life. Some rules, however, are arbitrary and adhering to them can be personally costly. Rigidly sticking to such rules can be considered maladaptive. Here, we test whether, at the neurobiological level, (mal)adaptive rule adherence is reduced by oxytocin—a hypothalamic neuropeptide that biases the biobehavioural approach-avoidance system. Participants (N = 139) self-administered oxytocin or placebo intranasally, and reported their need for structure and approach-avoidance sensitivity. Next, participants made binary decisions and were given an arbitrary rule that demanded to forgo financial benefits. Under oxytocin, participants violated the rule more often, especially when they had high need for structure and high approach sensitivity. Possibly, oxytocin dampens the need for a highly structured environment and enables individuals to flexibly trade-off internal desires against external restrictions. Implications for the treatment of clinical disorders marked by maladaptive rule adherence are discussed. PMID:27664999

Automated detection of qualitative spatio-temporal features in electrocardiac activation maps.

PubMed

Ironi, Liliana; Tentoni, Stefania

2007-02-01

This paper describes a piece of work aiming at the realization of a tool for the automated interpretation of electrocardiac maps. Such maps can capture a number of electrical conduction pathologies, such as arrhytmia, that can be missed by the analysis of traditional electrocardiograms. But, their introduction into the clinical practice is still far away as their interpretation requires skills that belongs to very few experts. Then, an automated interpretation tool would bridge the gap between the established research outcome and clinical practice with a consequent great impact on health care. Qualitative spatial reasoning can play a crucial role in the identification of spatio-temporal patterns and salient features that characterize the heart electrical activity. We adopted the spatial aggregation (SA) conceptual framework and an interplay of numerical and qualitative information to extract features from epicardial maps, and to make them available for reasoning tasks. Our focus is on epicardial activation isochrone maps as they are a synthetic representation of spatio-temporal aspects of the propagation of the electrical excitation. We provide a computational SA-based methodology to extract, from 3D epicardial data gathered over time, (1) the excitation wavefront structure, and (2) the salient features that characterize wavefront propagation and visually correspond to specific geometric objects. The proposed methodology provides a robust and efficient way to identify salient pieces of information in activation time maps. The hierarchical structure of the abstracted geometric objects, crucial in capturing the prominent information, facilitates the definition of general rules necessary to infer the correlation between pathophysiological patterns and wavefront structure and propagation.

Structural analysis of online handwritten mathematical symbols based on support vector machines

NASA Astrophysics Data System (ADS)

Simistira, Foteini; Papavassiliou, Vassilis; Katsouros, Vassilis; Carayannis, George

2013-01-01

Mathematical expression recognition is still a very challenging task for the research community mainly because of the two-dimensional (2d) structure of mathematical expressions (MEs). In this paper, we present a novel approach for the structural analysis between two on-line handwritten mathematical symbols of a ME, based on spatial features of the symbols. We introduce six features to represent the spatial affinity of the symbols and compare two multi-class classification methods that employ support vector machines (SVMs): one based on the "one-against-one" technique and one based on the "one-against-all", in identifying the relation between a pair of symbols (i.e. subscript, numerator, etc). A dataset containing 1906 spatial relations derived from the Competition on Recognition of Online Handwritten Mathematical Expressions (CROHME) 2012 training dataset is constructed to evaluate the classifiers and compare them with the rule-based classifier of the ILSP-1 system participated in the contest. The experimental results give an overall mean error rate of 2.61% for the "one-against-one" SVM approach, 6.57% for the "one-against-all" SVM technique and 12.31% error rate for the ILSP-1 classifier.

HCMM: Soil moisture in relation to geologic structure and lithology, northern California

NASA Technical Reports Server (NTRS)

Rich, E. I. (Principal Investigator)

1979-01-01

The author has identified the following significant results. First-look qualitative geologic evaluation of day- and night-IR images discloses several en echelon linear features extending throughout the central part of the northern coast range in California, across the Mendocino triple junction and into southern Oregon. Preliminary examination of these features with respect to topographic expression, vegetation, sun angle and azimuth, and atmospheric conditions suggests that they may be related to the intracontinental plate boundary (Lake Mountain Fault zone of Herd) of the Humbolt Plate. The linear features, which cut across several climatic zones and differently vegetated regions are not confined to topographic valleys, but cross the ridges and valleys at varying angles. Lithology within the Great Valley Sequence can be detected on a few of the images; however, preliminary evaluation suggests that the thermal banding observed may be a function of sun azimuth or late-day sun angle. Soil moisture, related to lithologic composition cannot be ruled out at this time.

Association Rule Based Feature Extraction for Character Recognition

NASA Astrophysics Data System (ADS)

Dua, Sumeet; Singh, Harpreet

Association rules that represent isomorphisms among data have gained importance in exploratory data analysis because they can find inherent, implicit, and interesting relationships among data. They are also commonly used in data mining to extract the conditions among attribute values that occur together frequently in a dataset [1]. These rules have wide range of applications, namely in the financial and retail sectors of marketing, sales, and medicine.

Special Relativity at the Quantum Scale

PubMed Central

Lam, Pui K.

2014-01-01

It has been suggested that the space-time structure as described by the theory of special relativity is a macroscopic manifestation of a more fundamental quantum structure (pre-geometry). Efforts to quantify this idea have come mainly from the area of abstract quantum logic theory. Here we present a preliminary attempt to develop a quantum formulation of special relativity based on a model that retains some geometric attributes. Our model is Feynman's “checker-board” trajectory for a 1-D relativistic free particle. We use this model to guide us in identifying (1) the quantum version of the postulates of special relativity and (2) the appropriate quantum “coordinates”. This model possesses a useful feature that it admits an interpretation both in terms of paths in space-time and in terms of quantum states. Based on the quantum version of the postulates, we derive a transformation rule for velocity. This rule reduces to the Einstein's velocity-addition formula in the macroscopic limit and reveals an interesting aspect of time. The 3-D case, time-dilation effect, and invariant interval are also discussed in term of this new formulation. This is a preliminary investigation; some results are derived, while others are interesting observations at this point. PMID:25531675

Special relativity at the quantum scale.

PubMed

Lam, Pui K

2014-01-01

It has been suggested that the space-time structure as described by the theory of special relativity is a macroscopic manifestation of a more fundamental quantum structure (pre-geometry). Efforts to quantify this idea have come mainly from the area of abstract quantum logic theory. Here we present a preliminary attempt to develop a quantum formulation of special relativity based on a model that retains some geometric attributes. Our model is Feynman's "checker-board" trajectory for a 1-D relativistic free particle. We use this model to guide us in identifying (1) the quantum version of the postulates of special relativity and (2) the appropriate quantum "coordinates". This model possesses a useful feature that it admits an interpretation both in terms of paths in space-time and in terms of quantum states. Based on the quantum version of the postulates, we derive a transformation rule for velocity. This rule reduces to the Einstein's velocity-addition formula in the macroscopic limit and reveals an interesting aspect of time. The 3-D case, time-dilation effect, and invariant interval are also discussed in term of this new formulation. This is a preliminary investigation; some results are derived, while others are interesting observations at this point.

IETS and quantum interference: Propensity rules in the presence of an interference feature

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

Lykkebo, Jacob; Solomon, Gemma C., E-mail: gsolomon@nano.ku.dk; Gagliardi, Alessio

2014-09-28

Destructive quantum interference in single molecule electronics is an intriguing phenomenon; however, distinguishing quantum interference effects from generically low transmission is not trivial. In this paper, we discuss how quantum interference effects in the transmission lead to either low current or a particular line shape in current-voltage curves, depending on the position of the interference feature. Second, we consider how inelastic electron tunneling spectroscopy can be used to probe the presence of an interference feature by identifying vibrational modes that are selectively suppressed when quantum interference effects dominate. That is, we expand the understanding of propensity rules in inelastic electronmore » tunneling spectroscopy to molecules with destructive quantum interference.« less

Object-oriented fault tree models applied to system diagnosis

NASA Technical Reports Server (NTRS)

Iverson, David L.; Patterson-Hine, F. A.

1990-01-01

When a diagnosis system is used in a dynamic environment, such as the distributed computer system planned for use on Space Station Freedom, it must execute quickly and its knowledge base must be easily updated. Representing system knowledge as object-oriented augmented fault trees provides both features. The diagnosis system described here is based on the failure cause identification process of the diagnostic system described by Narayanan and Viswanadham. Their system has been enhanced in this implementation by replacing the knowledge base of if-then rules with an object-oriented fault tree representation. This allows the system to perform its task much faster and facilitates dynamic updating of the knowledge base in a changing diagnosis environment. Accessing the information contained in the objects is more efficient than performing a lookup operation on an indexed rule base. Additionally, the object-oriented fault trees can be easily updated to represent current system status. This paper describes the fault tree representation, the diagnosis algorithm extensions, and an example application of this system. Comparisons are made between the object-oriented fault tree knowledge structure solution and one implementation of a rule-based solution. Plans for future work on this system are also discussed.

77 FR 42533 - Self-Regulatory Organizations; NYSE Arca, Inc.; Order Granting Approval of Proposed Rule Change...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-07-19

...-Regulatory Organizations; NYSE Arca, Inc.; Order Granting Approval of Proposed Rule Change Amending Its Rules... Ownership Structure of the Exchange July 13, 2012. I. Introduction On May 14, 2012, NYSE Arca, Inc. (``NYSE... Holdings from the ownership structure of the Exchange (the ``Merger''). The proposed rule changes were...

Mapping of High Value Crops Through AN Object-Based Svm Model Using LIDAR Data and Orthophoto in Agusan del Norte Philippines

NASA Astrophysics Data System (ADS)

Candare, Rudolph Joshua; Japitana, Michelle; Cubillas, James Earl; Ramirez, Cherry Bryan

2016-06-01

This research describes the methods involved in the mapping of different high value crops in Agusan del Norte Philippines using LiDAR. This project is part of the Phil-LiDAR 2 Program which aims to conduct a nationwide resource assessment using LiDAR. Because of the high resolution data involved, the methodology described here utilizes object-based image analysis and the use of optimal features from LiDAR data and Orthophoto. Object-based classification was primarily done by developing rule-sets in eCognition. Several features from the LiDAR data and Orthophotos were used in the development of rule-sets for classification. Generally, classes of objects can't be separated by simple thresholds from different features making it difficult to develop a rule-set. To resolve this problem, the image-objects were subjected to Support Vector Machine learning. SVMs have gained popularity because of their ability to generalize well given a limited number of training samples. However, SVMs also suffer from parameter assignment issues that can significantly affect the classification results. More specifically, the regularization parameter C in linear SVM has to be optimized through cross validation to increase the overall accuracy. After performing the segmentation in eCognition, the optimization procedure as well as the extraction of the equations of the hyper-planes was done in Matlab. The learned hyper-planes separating one class from another in the multi-dimensional feature-space can be thought of as super-features which were then used in developing the classifier rule set in eCognition. In this study, we report an overall classification accuracy of greater than 90% in different areas.

Pharmacophore modeling and virtual screening to identify potential RET kinase inhibitors.

PubMed

Shih, Kuei-Chung; Shiau, Chung-Wai; Chen, Ting-Shou; Ko, Ching-Huai; Lin, Chih-Lung; Lin, Chun-Yuan; Hwang, Chrong-Shiong; Tang, Chuan-Yi; Chen, Wan-Ru; Huang, Jui-Wen

2011-08-01

Chemical features based 3D pharmacophore model for REarranged during Transfection (RET) tyrosine kinase were developed by using a training set of 26 structurally diverse known RET inhibitors. The best pharmacophore hypothesis, which identified inhibitors with an associated correlation coefficient of 0.90 between their experimental and estimated anti-RET values, contained one hydrogen-bond acceptor, one hydrogen-bond donor, one hydrophobic, and one ring aromatic features. The model was further validated by a testing set, Fischer's randomization test, and goodness of hit (GH) test. We applied this pharmacophore model to screen NCI database for potential RET inhibitors. The hits were docked to RET with GOLD and CDOCKER after filtering by Lipinski's rules. Ultimately, 24 molecules were selected as potential RET inhibitors for further investigation. Copyright © 2011 Elsevier Ltd. All rights reserved.

The effect of category learning on attentional modulation of visual cortex.

PubMed

Folstein, Jonathan R; Fuller, Kelly; Howard, Dorothy; DePatie, Thomas

2017-09-01

Learning about visual object categories causes changes in the way we perceive those objects. One likely mechanism by which this occurs is the application of attention to potentially relevant objects. Here we test the hypothesis that category membership influences the allocation of attention, allowing attention to be applied not only to object features, but to entire categories. Participants briefly learned to categorize a set of novel cartoon animals after which EEG was recorded while participants distinguished between a target and non-target category. A second identical EEG session was conducted after two sessions of categorization practice. The category structure and task design allowed parametric manipulation of number of target features while holding feature frequency and category membership constant. We found no evidence that category membership influenced attentional selection: a postero-lateral negative component, labeled the selection negativity/N250, increased over time and was sensitive to number of target features, not target categories. In contrast, the right hemisphere N170 was not sensitive to target features. The P300 appeared sensitive to category in the first session, but showed a graded sensitivity to number of target features in the second session, possibly suggesting a transition from rule-based to similarity based categorization. Copyright © 2017. Published by Elsevier Ltd.

[Features of maxillary and mandibular nerves imaging during stem regional blockades. From paresthesia to 3D-CT guidance].

PubMed

Zaytsev, A Yu; Nazaryan, D N; Kim, S Yu; Dubrovin, K V; Svetlov, V A; Khovrin, V V

2014-01-01

There are difficulties in procedure of regional block of 2 and 3 brunches of the trigeminal nerve despite availability of many different methods of nerves imaging. The difficulties are connected with complex anatomy structure. Neurostimulation not always effective and as a rule, is accompanied with wrong interpretation of movement response on stimulation. The changing of the tactics on paraesthesia search improves the situation. The use of new methods of nerves imaging (3D-CT) also allows decreasing the frequency of fails during procedure of regional block of the brunches of the trigeminal nerve.

EPE fundamentals and impact of EUV: Will traditional design-rule calculations work in the era of EUV?

NASA Astrophysics Data System (ADS)

Gabor, Allen H.; Brendler, Andrew C.; Brunner, Timothy A.; Chen, Xuemei; Culp, James A.; Levinson, Harry J.

2018-03-01

The relationship between edge placement error, semiconductor design-rule determination and predicted yield in the era of EUV lithography is examined. This paper starts with the basics of edge placement error and then builds up to design-rule calculations. We show that edge placement error (EPE) definitions can be used as the building blocks for design-rule equations but that in the last several years the term "EPE" has been used in the literature to refer to many patterning errors that are not EPE. We then explore the concept of "Good Fields"1 and use it predict the n-sigma value needed for design-rule determination. Specifically, fundamental yield calculations based on the failure opportunities per chip are used to determine at what n-sigma "value" design-rules need to be tested to ensure high yield. The "value" can be a space between two features, an intersect area between two features, a minimum area of a feature, etc. It is shown that across chip variation of design-rule important values needs to be tested at sigma values between seven and eight which is much higher than the four-sigma values traditionally used for design-rule determination. After recommending new statistics be used for design-rule calculations the paper examines the impact of EUV lithography on sources of variation important for design-rule calculations. We show that stochastics can be treated as an effective dose variation that is fully sampled across every chip. Combining the increased within chip variation from EUV with the understanding that across chip variation of design-rule important values needs to not cause a yield loss at significantly higher sigma values than have traditionally been looked at, the conclusion is reached that across-wafer, wafer-to-wafer and lot-to-lot variation will have to overscale for any technology introducing EUV lithography where stochastic noise is a significant fraction of the effective dose variation. We will emphasize stochastic effects on edge placement error distributions and appropriate design-rule setting. While CD distributions with long tails coming from stochastic effects do bring increased risk of failure (especially on chips that may have over a billion failure opportunities per layer) there are other sources of variation that have sharp cutoffs, i.e. have no tails. We will review these sources and show how distributions with different skew and kurtosis values combine.

K-8 Pre-Service Teachers' Algebraic Thinking: Exploring the Habit of Mind "Building Rules to Represent Functions"

ERIC Educational Resources Information Center

Magiera, Marta T.; van den Kieboom, Leigh A.; Moyer, John C.

2017-01-01

In this study, we examined the ability of grades 1-8 pre-service teachers (PSTs) to engage in thinking about patterns, relationships, and functional rules. Using the algebraic habit of mind Building Rules to Represent Functions as a framework, we examined whether and how well our PSTs (n = 18) used seven features of this habit of mind: organize…

Two models for microsimulation of family life cycle and family structure.

PubMed

Bertino, S; Pinnelli, A; Vichi, M

1988-01-01

2 models are proposed for the microsimulation of the family and analysis of family structure and life cycle. These models were devised primarily for teaching purposes. The families are composed of 3 generations (parents, grandparents, children). Cohabitation is not considered. The 1st model is governed by a transition mechanism based on the rules of a Markov multidimensional, nonhonogeneous chain. The 2nd model is based on stochastic point processes. Input data comprise annual mortality probability according to 1) sex, 2) age, 3) civil status, 4) annual probability of 1st marriage, 5) age combinations between the spouses, and 6) the probability of having 1, 2, or 3 children at 6 months intervals from the previous event (marriage or birth of nth child). The applications of the 1st model are presented using 2 mortality and fertility hypotheses (high and low) and a nuptiality hypothesis (West European nature). The various features of family composition are analyzed according to the duration of a couple's marriage and the age of the individual, as well as the characteristic features of the individual and family life cycle given these 2 demographic conditions.

Using cellular automata to generate image representation for biological sequences.

PubMed

Xiao, X; Shao, S; Ding, Y; Huang, Z; Chen, X; Chou, K-C

2005-02-01

A novel approach to visualize biological sequences is developed based on cellular automata (Wolfram, S. Nature 1984, 311, 419-424), a set of discrete dynamical systems in which space and time are discrete. By transforming the symbolic sequence codes into the digital codes, and using some optimal space-time evolvement rules of cellular automata, a biological sequence can be represented by a unique image, the so-called cellular automata image. Many important features, which are originally hidden in a long and complicated biological sequence, can be clearly revealed thru its cellular automata image. With biological sequences entering into databanks rapidly increasing in the post-genomic era, it is anticipated that the cellular automata image will become a very useful vehicle for investigation into their key features, identification of their function, as well as revelation of their "fingerprint". It is anticipated that by using the concept of the pseudo amino acid composition (Chou, K.C. Proteins: Structure, Function, and Genetics, 2001, 43, 246-255), the cellular automata image approach can also be used to improve the quality of predicting protein attributes, such as structural class and subcellular location.

Oxytocin conditions trait-based rule adherence.

PubMed

Gross, Jörg; De Dreu, Carsten K W

2017-03-01

Rules, whether in the form of norms, taboos or laws, regulate and coordinate human life. Some rules, however, are arbitrary and adhering to them can be personally costly. Rigidly sticking to such rules can be considered maladaptive. Here, we test whether, at the neurobiological level, (mal)adaptive rule adherence is reduced by oxytocin-a hypothalamic neuropeptide that biases the biobehavioural approach-avoidance system. Participants (N = 139) self-administered oxytocin or placebo intranasally, and reported their need for structure and approach-avoidance sensitivity. Next, participants made binary decisions and were given an arbitrary rule that demanded to forgo financial benefits. Under oxytocin, participants violated the rule more often, especially when they had high need for structure and high approach sensitivity. Possibly, oxytocin dampens the need for a highly structured environment and enables individuals to flexibly trade-off internal desires against external restrictions. Implications for the treatment of clinical disorders marked by maladaptive rule adherence are discussed. © The Author (2016). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Simple Rules, Not So Simple: The Use of International Ovarian Tumor Analysis (IOTA) Terminology and Simple Rules in Inexperienced Hands in a Prospective Multicenter Cohort Study.

PubMed

Meys, Evelyne; Rutten, Iris; Kruitwagen, Roy; Slangen, Brigitte; Lambrechts, Sandrina; Mertens, Helen; Nolting, Ernst; Boskamp, Dieuwke; Van Gorp, Toon

2017-12-01

 To analyze how well untrained examiners - without experience in the use of International Ovarian Tumor Analysis (IOTA) terminology or simple ultrasound-based rules (simple rules) - are able to apply IOTA terminology and simple rules and to assess the level of agreement between non-experts and an expert.  This prospective multicenter cohort study enrolled women with ovarian masses. Ultrasound was performed by non-expert examiners and an expert. Ultrasound features were recorded using IOTA nomenclature, and used for classifying the mass by simple rules. Interobserver agreement was evaluated with Fleiss' kappa and percentage agreement between observers.  50 consecutive women were included. We observed 46 discrepancies in the description of ovarian masses when non-experts utilized IOTA terminology. Tumor type was misclassified often (n = 22), resulting in poor interobserver agreement between the non-experts and the expert (kappa = 0.39, 95 %-CI 0.244 - 0.529, percentage of agreement = 52.0 %). Misinterpretation of simple rules by non-experts was observed 57 times, resulting in an erroneous diagnosis in 15 patients (30 %). The agreement for classifying the mass as benign, malignant or inconclusive by simple rules was only moderate between the non-experts and the expert (kappa = 0.50, 95 %-CI 0.300 - 0.704, percentage of agreement = 70.0 %). The level of agreement for all 10 simple rules features varied greatly (kappa index range: -0.08 - 0.74, percentage of agreement 66 - 94 %).  Although simple rules are useful to distinguish benign from malignant adnexal masses, they are not that simple for untrained examiners. Training with both IOTA terminology and simple rules is necessary before simple rules can be introduced into guidelines and daily clinical practice. © Georg Thieme Verlag KG Stuttgart · New York.

Mental health nurses' experiences of managing work-related emotions through supervision.

PubMed

MacLaren, Jessica; Stenhouse, Rosie; Ritchie, Deborah

2016-10-01

The aim of this study was to explore emotion cultures constructed in supervision and consider how supervision functions as an emotionally safe space promoting critical reflection. Research published between 1995-2015 suggests supervision has a positive impact on nurses' emotional well-being, but there is little understanding of the processes involved in this and how styles of emotion interaction are established in supervision. A narrative approach was used to investigate mental health nurses' understandings and experiences of supervision. Eight semi-structured interviews were conducted with community mental health nurses in the UK during 2011. Analysis of audio data used features of speech to identify narrative discourse and illuminate meanings. A topic-centred analysis of interview narratives explored discourses shared between the participants. This supported the identification of feeling rules in participants' narratives and the exploration of the emotion context of supervision. Effective supervision was associated with three feeling rules: safety and reflexivity; staying professional; managing feelings. These feeling rules allowed the expression and exploration of emotions, promoting critical reflection. A contrast was identified between the emotion culture of supervision and the nurses' experience of their workplace cultures as requiring the suppression of difficult emotions. Despite this, contrast supervision functioned as an emotion micro-culture with its own distinctive feeling rules. The analytical construct of feeling rules allows us to connect individual emotional experiences to shared normative discourses, highlighting how these shape emotional processes taking place in supervision. This understanding supports an explanation of how supervision may positively influence nurses' emotion management and perhaps reduce burnout. © 2016 John Wiley & Sons Ltd.

"Just as the Structural Formula Does": Names, Diagrams, and the Structure of Organic Chemistry at the 1892 Geneva Nomenclature Congress.

PubMed

Hepler-Smith, Evan

2015-02-01

At the Geneva Nomenclature Congress of 1892, some of the foremost organic chemists of the late nineteenth century crafted a novel relationship between chemical substances, chemical diagrams, and chemical names that has shaped practices of chemical representation ever since. During the 1880s, the French chemist Charles Friedel organised the nomenclature reform effort that culminated in the Geneva Congress; in the disorderly nomenclature of German synthetic chemistry, Friedel saw an opportunity to advance French national interests and his own pedagogical goals. Friedel and a group of close colleagues reconceived nomenclature as a unified field, in which all chemical names ought to relate clearly to one another and to the structure of the compounds they represented. The German chemist Adolf von Baeyer went a step farther, arguing for names that precisely and uniquely corresponded to the structural formula of each compound, tailored for use in chemical dictionaries and handbooks. Baeyer's vision prevailed at the Geneva Congress, which consequently codified rules for rigorously mapping structural formulas into names, resulting in names that faithfully represented the features of these diagrams but not always the chemical behaviour of the compounds themselves. This approach ultimately limited both the number of chemical compounds that the Geneva rules were able to encompass and the breadth of their application. However, the relationship between diagram and name established at the Geneva Congress became the foundation not only of subsequent systems of chemical nomenclature but of methods of organising information that have supported the modern chemical sciences.

Monitoring the Depth of Anesthesia Using a New Adaptive Neurofuzzy System.

PubMed

Shalbaf, Ahmad; Saffar, Mohsen; Sleigh, Jamie W; Shalbaf, Reza

2018-05-01

Accurate and noninvasive monitoring of the depth of anesthesia (DoA) is highly desirable. Since the anesthetic drugs act mainly on the central nervous system, the analysis of brain activity using electroencephalogram (EEG) is very useful. This paper proposes a novel automated method for assessing the DoA using EEG. First, 11 features including spectral, fractal, and entropy are extracted from EEG signal and then, by applying an algorithm according to exhaustive search of all subsets of features, a combination of the best features (Beta-index, sample entropy, shannon permutation entropy, and detrended fluctuation analysis) is selected. Accordingly, we feed these extracted features to a new neurofuzzy classification algorithm, adaptive neurofuzzy inference system with linguistic hedges (ANFIS-LH). This structure can successfully model systems with nonlinear relationships between input and output, and also classify overlapped classes accurately. ANFIS-LH, which is based on modified classical fuzzy rules, reduces the effects of the insignificant features in input space, which causes overlapping and modifies the output layer structure. The presented method classifies EEG data into awake, light, general, and deep states during anesthesia with sevoflurane in 17 patients. Its accuracy is 92% compared to a commercial monitoring system (response entropy index) successfully. Moreover, this method reaches the classification accuracy of 93% to categorize EEG signal to awake and general anesthesia states by another database of propofol and volatile anesthesia in 50 patients. To sum up, this method is potentially applicable to a new real-time monitoring system to help the anesthesiologist with continuous assessment of DoA quickly and accurately.

Similar Task Features Shape Judgment and Categorization Processes

ERIC Educational Resources Information Center

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

2016-01-01

The distinction between similarity-based and rule-based strategies has instigated a large body of research in categorization and judgment. Within both domains, the task characteristics guiding strategy shifts are increasingly well documented. Across domains, past research has observed shifts from rule-based strategies in judgment to…

Decision Tree Repository and Rule Set Based Mingjiang River Estuarine Wetlands Classifaction

NASA Astrophysics Data System (ADS)

Zhang, W.; Li, X.; Xiao, W.

2018-05-01

The increasing urbanization and industrialization have led to wetland losses in estuarine area of Mingjiang River over past three decades. There has been increasing attention given to produce wetland inventories using remote sensing and GIS technology. Due to inconsistency training site and training sample, traditionally pixel-based image classification methods can't achieve a comparable result within different organizations. Meanwhile, object-oriented image classification technique shows grate potential to solve this problem and Landsat moderate resolution remote sensing images are widely used to fulfill this requirement. Firstly, the standardized atmospheric correct, spectrally high fidelity texture feature enhancement was conducted before implementing the object-oriented wetland classification method in eCognition. Secondly, we performed the multi-scale segmentation procedure, taking the scale, hue, shape, compactness and smoothness of the image into account to get the appropriate parameters, using the top and down region merge algorithm from single pixel level, the optimal texture segmentation scale for different types of features is confirmed. Then, the segmented object is used as the classification unit to calculate the spectral information such as Mean value, Maximum value, Minimum value, Brightness value and the Normalized value. The Area, length, Tightness and the Shape rule of the image object Spatial features and texture features such as Mean, Variance and Entropy of image objects are used as classification features of training samples. Based on the reference images and the sampling points of on-the-spot investigation, typical training samples are selected uniformly and randomly for each type of ground objects. The spectral, texture and spatial characteristics of each type of feature in each feature layer corresponding to the range of values are used to create the decision tree repository. Finally, with the help of high resolution reference images, the random sampling method is used to conduct the field investigation, achieve an overall accuracy of 90.31 %, and the Kappa coefficient is 0.88. The classification method based on decision tree threshold values and rule set developed by the repository, outperforms the results obtained from the traditional methodology. Our decision tree repository and rule set based object-oriented classification technique was an effective method for producing comparable and consistency wetlands data set.

Simple neural substrate predicts complex rhythmic structure in duetting birds

NASA Astrophysics Data System (ADS)

Amador, Ana; Trevisan, M. A.; Mindlin, G. B.

2005-09-01

Horneros (Furnarius Rufus) are South American birds well known for their oven-looking nests and their ability to sing in couples. Previous work has analyzed the rhythmic organization of the duets, unveiling a mathematical structure behind the songs. In this work we analyze in detail an extended database of duets. The rhythms of the songs are compatible with the dynamics presented by a wide class of dynamical systems: forced excitable systems. Compatible with this nonlinear rule, we build a biologically inspired model for how the neural and the anatomical elements may interact to produce the observed rhythmic patterns. This model allows us to synthesize songs presenting the acoustic and rhythmic features observed in real songs. We also make testable predictions in order to support our hypothesis.

A graph grammar approach to artificial life.

PubMed

Kniemeyer, Ole; Buck-Sorlin, Gerhard H; Kurth, Winfried

2004-01-01

We present the high-level language of relational growth grammars (RGGs) as a formalism designed for the specification of ALife models. RGGs can be seen as an extension of the well-known parametric Lindenmayer systems and contain rule-based, procedural, and object-oriented features. They are defined as rewriting systems operating on graphs with the edges coming from a set of user-defined relations, whereas the nodes can be associated with objects. We demonstrate their ability to represent genes, regulatory networks of metabolites, and morphologically structured organisms, as well as developmental aspects of these entities, in a common formal framework. Mutation, crossing over, selection, and the dynamics of a network of gene regulation can all be represented with simple graph rewriting rules. This is demonstrated in some detail on the classical example of Dawkins' biomorphs and the ABC model of flower morphogenesis: other applications are briefly sketched. An interactive program was implemented, enabling the execution of the formalism and the visualization of the results.

[Changes of Forest Canopy Spectral Reflectance with Seasons in Lang Ya Mountains].

PubMed

Li, Wei-tao; Peng, Dao-li; Zhang, Yan; Wu, Jian; Chen, Tai-sheng

2015-08-01

The physiological mechanism and ecological structure of forest trees can change with the changes of years. In a certain extent, the changes were expressed through the canopy spectral features. The mastery of changing rules about spectral characteristics of trees over the years is benefit to remote sensing interpretation and provide scientific basis for the classification of different trees. The study adopted high-resolution spectrometer to measure the canopy spectral characteristics for seven major deciduous trees and seven evergreen trees to gain the spectrum curve of four different ages and calculate the first derivative curve. The analysis of changing rules about spectral characteristics of different deciduous trees and evergreen trees and the comparison of changes about spectrum of various trees in the visible and infrared band could find the best year and best band for identification of trees. The results showed that the canopy spectral reflectance of deciduous and evergreen trees increases with the increase of age. And the spectral changes of two species were most obvious in the near infrared band.

Primacy and ranking of UEFA soccer teams from biasing organization rules

NASA Astrophysics Data System (ADS)

Ausloos, Marcel; Gadomski, Adam; Vitanov, Nikolay K.

2014-10-01

A question is raised on whether some implied regularity or structure, as found in the soccer team ranking by the Union of European Football Associations (UEFA), is due to an implicit game result value or score competition conditions. The analysis is based on considerations of complex systems, i.e. finding whether power or other simple law fits are appropriate to describe some internal dynamics. It is observed that the ranking is specifically organized: a major class comprising a few teams emerges after each season. Other classes, which apparently have regular sizes, occur subsequently. Thus, the notion of the Sheppard primacy index is envisaged to describe the findings. Additional primacy indices are discussed for enhancing the features. These measures can be used to sort out peer classes in more general terms. A very simplified toy model containing components of the UEFA ranking rules suggests that such peer classes are an extrinsic property of the ranking, as obtained in many nonlinear systems under boundary condition constraints.

Multiscale infrared and visible image fusion using gradient domain guided image filtering

NASA Astrophysics Data System (ADS)

Zhu, Jin; Jin, Weiqi; Li, Li; Han, Zhenghao; Wang, Xia

2018-03-01

For better surveillance with infrared and visible imaging, a novel hybrid multiscale decomposition fusion method using gradient domain guided image filtering (HMSD-GDGF) is proposed in this study. In this method, hybrid multiscale decomposition with guided image filtering and gradient domain guided image filtering of source images are first applied before the weight maps of each scale are obtained using a saliency detection technology and filtering means with three different fusion rules at different scales. The three types of fusion rules are for small-scale detail level, large-scale detail level, and base level. Finally, the target becomes more salient and can be more easily detected in the fusion result, with the detail information of the scene being fully displayed. After analyzing the experimental comparisons with state-of-the-art fusion methods, the HMSD-GDGF method has obvious advantages in fidelity of salient information (including structural similarity, brightness, and contrast), preservation of edge features, and human visual perception. Therefore, visual effects can be improved by using the proposed HMSD-GDGF method.

On a common circle: natural scenes and Gestalt rules.

PubMed

Sigman, M; Cecchi, G A; Gilbert, C D; Magnasco, M O

2001-02-13

To understand how the human visual system analyzes images, it is essential to know the structure of the visual environment. In particular, natural images display consistent statistical properties that distinguish them from random luminance distributions. We have studied the geometric regularities of oriented elements (edges or line segments) present in an ensemble of visual scenes, asking how much information the presence of a segment in a particular location of the visual scene carries about the presence of a second segment at different relative positions and orientations. We observed strong long-range correlations in the distribution of oriented segments that extend over the whole visual field. We further show that a very simple geometric rule, cocircularity, predicts the arrangement of segments in natural scenes, and that different geometrical arrangements show relevant differences in their scaling properties. Our results show similarities to geometric features of previous physiological and psychophysical studies. We discuss the implications of these findings for theories of early vision.

Search for Minimal and Semi-Minimal Rule Sets in Incremental Learning of Context-Free and Definite Clause Grammars

NASA Astrophysics Data System (ADS)

Imada, Keita; Nakamura, Katsuhiko

This paper describes recent improvements to Synapse system for incremental learning of general context-free grammars (CFGs) and definite clause grammars (DCGs) from positive and negative sample strings. An important feature of our approach is incremental learning, which is realized by a rule generation mechanism called “bridging” based on bottom-up parsing for positive samples and the search for rule sets. The sizes of rule sets and the computation time depend on the search strategies. In addition to the global search for synthesizing minimal rule sets and serial search, another method for synthesizing semi-optimum rule sets, we incorporate beam search to the system for synthesizing semi-minimal rule sets. The paper shows several experimental results on learning CFGs and DCGs, and we analyze the sizes of rule sets and the computation time.

Mechanisms underlying transfer of task-defined rules across feature dimensions.

PubMed

Baroni, Giulia; Yamaguchi, Motonori; Chen, Jing; Proctor, Robert W

2013-01-01

The Simon effect can be reversed, favoring spatially noncorresponding responses, when people respond to stimulus colors (e.g., green) by pressing a key labeled with the alternative color (i.e., red). This Hedge and Marsh reversal is most often attributed to transfer of logical recoding rules from the color dimension to the location dimension. A recent study showed that this transfer of logical recoding rules can occur not only within a single task but also across two separate tasks that are intermixed. The present study investigated the conditions that determine the transfer of logical recoding rules across tasks. Experiment 1 examined whether it occurs in a transfer paradigm, that is when the two tasks are performed separately, but provided little support for this possibility. Experiment 2 investigated the role of task-set readiness, using a mixed-task paradigm with a predictable trials sequence, which indicated that there is no transfer of task-defined rules across tasks even when they are highly active during the Simon task. Finally, Experiments 3 and 4 used a mixed-task paradigm, where trials of the two tasks were mixed randomly and unpredictably, and manipulated the amount of feature overlap between tasks. Results indicated that task similarity is a determining factor for transfer of task-defined rules to occur. Overall, the study provides evidence that transfer of logical recoding rules tends to occur across two tasks when tasks are unpredictably intermixed and use stimuli that are highly similar and confusable.

Unsupervised Feature Learning With Winner-Takes-All Based STDP

PubMed Central

Ferré, Paul; Mamalet, Franck; Thorpe, Simon J.

2018-01-01

We present a novel strategy for unsupervised feature learning in image applications inspired by the Spike-Timing-Dependent-Plasticity (STDP) biological learning rule. We show equivalence between rank order coding Leaky-Integrate-and-Fire neurons and ReLU artificial neurons when applied to non-temporal data. We apply this to images using rank-order coding, which allows us to perform a full network simulation with a single feed-forward pass using GPU hardware. Next we introduce a binary STDP learning rule compatible with training on batches of images. Two mechanisms to stabilize the training are also presented : a Winner-Takes-All (WTA) framework which selects the most relevant patches to learn from along the spatial dimensions, and a simple feature-wise normalization as homeostatic process. This learning process allows us to train multi-layer architectures of convolutional sparse features. We apply our method to extract features from the MNIST, ETH80, CIFAR-10, and STL-10 datasets and show that these features are relevant for classification. We finally compare these results with several other state of the art unsupervised learning methods. PMID:29674961

Collaborative Brain-Computer Interface for Aiding Decision-Making

PubMed Central

Poli, Riccardo; Valeriani, Davide; Cinel, Caterina

2014-01-01

We look at the possibility of integrating the percepts from multiple non-communicating observers as a means of achieving better joint perception and better group decisions. Our approach involves the combination of a brain-computer interface with human behavioural responses. To test ideas in controlled conditions, we asked observers to perform a simple matching task involving the rapid sequential presentation of pairs of visual patterns and the subsequent decision as whether the two patterns in a pair were the same or different. We recorded the response times of observers as well as a neural feature which predicts incorrect decisions and, thus, indirectly indicates the confidence of the decisions made by the observers. We then built a composite neuro-behavioural feature which optimally combines the two measures. For group decisions, we uses a majority rule and three rules which weigh the decisions of each observer based on response times and our neural and neuro-behavioural features. Results indicate that the integration of behavioural responses and neural features can significantly improve accuracy when compared with the majority rule. An analysis of event-related potentials indicates that substantial differences are present in the proximity of the response for correct and incorrect trials, further corroborating the idea of using hybrids of brain-computer interfaces and traditional strategies for improving decision making. PMID:25072739

Automatic prediction of facial trait judgments: appearance vs. structural models.

PubMed

Rojas, Mario; Masip, David; Todorov, Alexander; Vitria, Jordi

2011-01-01

Evaluating other individuals with respect to personality characteristics plays a crucial role in human relations and it is the focus of attention for research in diverse fields such as psychology and interactive computer systems. In psychology, face perception has been recognized as a key component of this evaluation system. Multiple studies suggest that observers use face information to infer personality characteristics. Interactive computer systems are trying to take advantage of these findings and apply them to increase the natural aspect of interaction and to improve the performance of interactive computer systems. Here, we experimentally test whether the automatic prediction of facial trait judgments (e.g. dominance) can be made by using the full appearance information of the face and whether a reduced representation of its structure is sufficient. We evaluate two separate approaches: a holistic representation model using the facial appearance information and a structural model constructed from the relations among facial salient points. State of the art machine learning methods are applied to a) derive a facial trait judgment model from training data and b) predict a facial trait value for any face. Furthermore, we address the issue of whether there are specific structural relations among facial points that predict perception of facial traits. Experimental results over a set of labeled data (9 different trait evaluations) and classification rules (4 rules) suggest that a) prediction of perception of facial traits is learnable by both holistic and structural approaches; b) the most reliable prediction of facial trait judgments is obtained by certain type of holistic descriptions of the face appearance; and c) for some traits such as attractiveness and extroversion, there are relationships between specific structural features and social perceptions.

A Novel Modulation Classification Approach Using Gabor Filter Network

PubMed Central

Ghauri, Sajjad Ahmed; Qureshi, Ijaz Mansoor; Cheema, Tanveer Ahmed; Malik, Aqdas Naveed

2014-01-01

A Gabor filter network based approach is used for feature extraction and classification of digital modulated signals by adaptively tuning the parameters of Gabor filter network. Modulation classification of digitally modulated signals is done under the influence of additive white Gaussian noise (AWGN). The modulations considered for the classification purpose are PSK 2 to 64, FSK 2 to 64, and QAM 4 to 64. The Gabor filter network uses the network structure of two layers; the first layer which is input layer constitutes the adaptive feature extraction part and the second layer constitutes the signal classification part. The Gabor atom parameters are tuned using Delta rule and updating of weights of Gabor filter using least mean square (LMS) algorithm. The simulation results show that proposed novel modulation classification algorithm has high classification accuracy at low signal to noise ratio (SNR) on AWGN channel. PMID:25126603

Plasmonic spectral tunability of conductive ternary nitrides

NASA Astrophysics Data System (ADS)

Kassavetis, S.; Bellas, D. V.; Abadias, G.; Lidorikis, E.; Patsalas, P.

2016-06-01

Conductive binary transition metal nitrides, such as TiN and ZrN, have emerged as a category of promising alternative plasmonic materials. In this work, we show that ternary transition metal nitrides such as TixTa1-xN, TixZr1-xN, TixAl1-xN, and ZrxTa1-xN share the important plasmonic features with their binary counterparts, while having the additional asset of the exceptional spectral tunability in the entire visible (400-700 nm) and UVA (315-400 nm) spectral ranges depending on their net valence electrons. In particular, we demonstrate that such ternary nitrides can exhibit maximum field enhancement factors comparable with gold in the aforementioned broadband range. We also critically evaluate the structural features that affect the quality factor of the plasmon resonance and we provide rules of thumb for the selection and growth of materials for nitride plasmonics.

Analysis of X-ray adsorption edges: L 2,3 edge of FeCl 4 -

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

Bagus, Paul S.; Nelin, Connie J.; Ilton, Eugene S.

We describe a detailed analysis of the features of the X-ray adsorption spectra at the Fe L 2,3 edge of FeCl 4. The objective of this analysis is to explain the origin of the complex features in relation to properties of the wavefunctions, especially for the excited states. These properties include spin-orbit and ligand field splittings where a novel aspect of the dipole selection rules is applied to understand the influence of these splittings on the spectra. We also explicitly take account of the intermediate coupling of the open core and valence shell electrons. Our analysis also includes comparison ofmore » theory and experiment for the Fe L 2,3 edge and comparison of theoretical predictions for the Fe 3+ cation and FeCl 4-. The electronic structure is obtained from theoretical wavefunctions for the ground and excited states.« less

Generating Concise Rules for Human Motion Retrieval

NASA Astrophysics Data System (ADS)

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

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

Emergent explosive synchronization in adaptive complex networks

NASA Astrophysics Data System (ADS)

Avalos-Gaytán, Vanesa; Almendral, Juan A.; Leyva, I.; Battiston, F.; Nicosia, V.; Latora, V.; Boccaletti, S.

2018-04-01

Adaptation plays a fundamental role in shaping the structure of a complex network and improving its functional fitting. Even when increasing the level of synchronization in a biological system is considered as the main driving force for adaptation, there is evidence of negative effects induced by excessive synchronization. This indicates that coherence alone cannot be enough to explain all the structural features observed in many real-world networks. In this work, we propose an adaptive network model where the dynamical evolution of the node states toward synchronization is coupled with an evolution of the link weights based on an anti-Hebbian adaptive rule, which accounts for the presence of inhibitory effects in the system. We found that the emergent networks spontaneously develop the structural conditions to sustain explosive synchronization. Our results can enlighten the shaping mechanisms at the heart of the structural and dynamical organization of some relevant biological systems, namely, brain networks, for which the emergence of explosive synchronization has been observed.

Molecules Without Atoms

NASA Astrophysics Data System (ADS)

Ruth, Anthony; Collins, Laura; Gomes, Kenjiro; Janko, Boldizsar

We present a real-space representation of molecules which results in the normal bonding rules and electronic structure of chemistry without atom-centered coulomb potentials. Using a simple mapping, we can generate atomless molecules from the structure of real molecules. Additionally, molecules without atoms show similar covalent bonding energies and transfer of charge in ionic bonds as real molecules. The atomless molecules contain only the valence and conduction electronic structure of the real molecule. Using the framework of the Atoms in Molecules (AIM) theory of Bader, we prove that the topological features of the valence charge distribution of molecules without atoms are identical to that of real molecules. In particular, the charge basins of atomless molecules show identical location and quantities of representative charge. We compare the accuracy, computational cost, and intuition gained from electronic structure calculations of molecules without atoms with the use of pseudopotentials to represent atomic cores in density functional theory. A. R. acknowledges support from a NASA Space Technology Research Fellowship.

Growth optimization and electronic structure of ultrathin CoO films on Ag(001): A LEED and photoemission study

NASA Astrophysics Data System (ADS)

Barman, Sukanta; Menon, Krishnakumar S. R.

2018-04-01

We present here a detailed growth optimization of CoO thin film on Ag(001) involving the effects of different growth parameters on the electronic structure. A well-ordered stoichiometric growth of 5 ML CoO film has been observed at 473 K substrate temperature and 1 × 10-6 mbar oxygen partial pressure. The growth at lower substrate temperature and oxygen partial pressure show non-stoichiometric impurity phases which have been investigated further to correlate the growth parameters with surface electronic structure. The coverage dependent valence band electronic structure of the films grown at optimized condition reveals the presence of interfacial states near the Fermi edge (EF) for lower film coverages. Presence of interfacial states in the stoichiometric films rules out their defect-induced origin. We argue that this is an intrinsic feature of transition metal monoxides like NiO, CoO, MnO in the low coverage regime.

Emergent explosive synchronization in adaptive complex networks.

PubMed

Avalos-Gaytán, Vanesa; Almendral, Juan A; Leyva, I; Battiston, F; Nicosia, V; Latora, V; Boccaletti, S

2018-04-01

Adaptation plays a fundamental role in shaping the structure of a complex network and improving its functional fitting. Even when increasing the level of synchronization in a biological system is considered as the main driving force for adaptation, there is evidence of negative effects induced by excessive synchronization. This indicates that coherence alone cannot be enough to explain all the structural features observed in many real-world networks. In this work, we propose an adaptive network model where the dynamical evolution of the node states toward synchronization is coupled with an evolution of the link weights based on an anti-Hebbian adaptive rule, which accounts for the presence of inhibitory effects in the system. We found that the emergent networks spontaneously develop the structural conditions to sustain explosive synchronization. Our results can enlighten the shaping mechanisms at the heart of the structural and dynamical organization of some relevant biological systems, namely, brain networks, for which the emergence of explosive synchronization has been observed.

Competition.

PubMed

Chambers, D W

1997-01-01

Our ambivalence toward competition can be traced to an unspoken preference for certain types of competition which give us an advantage over the types we value less. Four types are defined (a) pure (same rules, same objectives), (b) collaborative (same rules, shared objective), (c) market share (different rules, same objectives), and (d) market growth (different rules, value added orientation). The defining characteristics of the four types of competition are respectively: needing a referee, arguing over the spoils, differentiation and substitutability, and customer focus. Dentistry has features of all four types of competition, thus making it difficult to have a meaningful discussion or frame a coherent policy on this topic.

Intelligent Gearbox Diagnosis Methods Based on SVM, Wavelet Lifting and RBR

PubMed Central

Gao, Lixin; Ren, Zhiqiang; Tang, Wenliang; Wang, Huaqing; Chen, Peng

2010-01-01

Given the problems in intelligent gearbox diagnosis methods, it is difficult to obtain the desired information and a large enough sample size to study; therefore, we propose the application of various methods for gearbox fault diagnosis, including wavelet lifting, a support vector machine (SVM) and rule-based reasoning (RBR). In a complex field environment, it is less likely for machines to have the same fault; moreover, the fault features can also vary. Therefore, a SVM could be used for the initial diagnosis. First, gearbox vibration signals were processed with wavelet packet decomposition, and the signal energy coefficients of each frequency band were extracted and used as input feature vectors in SVM for normal and faulty pattern recognition. Second, precision analysis using wavelet lifting could successfully filter out the noisy signals while maintaining the impulse characteristics of the fault; thus effectively extracting the fault frequency of the machine. Lastly, the knowledge base was built based on the field rules summarized by experts to identify the detailed fault type. Results have shown that SVM is a powerful tool to accomplish gearbox fault pattern recognition when the sample size is small, whereas the wavelet lifting scheme can effectively extract fault features, and rule-based reasoning can be used to identify the detailed fault type. Therefore, a method that combines SVM, wavelet lifting and rule-based reasoning ensures effective gearbox fault diagnosis. PMID:22399894

Intelligent gearbox diagnosis methods based on SVM, wavelet lifting and RBR.

PubMed

Gao, Lixin; Ren, Zhiqiang; Tang, Wenliang; Wang, Huaqing; Chen, Peng

2010-01-01

Given the problems in intelligent gearbox diagnosis methods, it is difficult to obtain the desired information and a large enough sample size to study; therefore, we propose the application of various methods for gearbox fault diagnosis, including wavelet lifting, a support vector machine (SVM) and rule-based reasoning (RBR). In a complex field environment, it is less likely for machines to have the same fault; moreover, the fault features can also vary. Therefore, a SVM could be used for the initial diagnosis. First, gearbox vibration signals were processed with wavelet packet decomposition, and the signal energy coefficients of each frequency band were extracted and used as input feature vectors in SVM for normal and faulty pattern recognition. Second, precision analysis using wavelet lifting could successfully filter out the noisy signals while maintaining the impulse characteristics of the fault; thus effectively extracting the fault frequency of the machine. Lastly, the knowledge base was built based on the field rules summarized by experts to identify the detailed fault type. Results have shown that SVM is a powerful tool to accomplish gearbox fault pattern recognition when the sample size is small, whereas the wavelet lifting scheme can effectively extract fault features, and rule-based reasoning can be used to identify the detailed fault type. Therefore, a method that combines SVM, wavelet lifting and rule-based reasoning ensures effective gearbox fault diagnosis.

Mitosis detection using generic features and an ensemble of cascade adaboosts.

PubMed

Tek, F Boray

2013-01-01

Mitosis count is one of the factors that pathologists use to assess the risk of metastasis and survival of the patients, which are affected by the breast cancer. We investigate an application of a set of generic features and an ensemble of cascade adaboosts to the automated mitosis detection. Calculation of the features rely minimally on object-level descriptions and thus require minimal segmentation. The proposed work was developed and tested on International Conference on Pattern Recognition (ICPR) 2012 mitosis detection contest data. We plotted receiver operating characteristics curves of true positive versus false positive rates; calculated recall, precision, F-measure, and region overlap ratio measures. WE TESTED OUR FEATURES WITH TWO DIFFERENT CLASSIFIER CONFIGURATIONS: 1) An ensemble of single adaboosts, 2) an ensemble of cascade adaboosts. On the ICPR 2012 mitosis detection contest evaluation, the cascade ensemble scored 54, 62.7, and 58, whereas the non-cascade version scored 68, 28.1, and 39.7 for the recall, precision, and F-measure measures, respectively. Mostly used features in the adaboost classifier rules were a shape-based feature, which counted granularity and a color-based feature, which relied on Red, Green, and Blue channel statistics. The features, which express the granular structure and color variations, are found useful for mitosis detection. The ensemble of adaboosts performs better than the individual adaboost classifiers. Moreover, the ensemble of cascaded adaboosts was better than the ensemble of single adaboosts for mitosis detection.

Reply to David Kemmerer's "a critique of Mark D. Allen's 'the preservation of verb subcategory knowledge in a spoken language comprehension deficit'".

PubMed

Allen, Mark D; Owens, Tyler E

2008-07-01

Allen [Allen, M. D. (2005). The preservation of verb subcategory knowledge in a spoken language comprehension deficit. Brain and Language, 95, 255-264] presents evidence from a single patient, WBN, to motivate a theory of lexical processing and representation in which syntactic information may be encoded and retrieved independently of semantic information. In his critique, Kemmerer argues that because Allen depended entirely on preposition-based verb subcategory violations to test WBN's knowledge of correct argument structure, his results, at best, address a "strawman" theory. This argument rests on the assumption that preposition subcategory options are superficial syntactic phenomena which are not represented by argument structure proper. We demonstrate that preposition subcategory is in fact treated as semantically determined argument structure in the theories that Allen evaluated, and thus far from irrelevant. In further discussion of grammatically relevant versus irrelevant semantic features, Kemmerer offers a review of his own studies. However, due to an important design shortcoming in these experiments, we remain unconvinced. Reemphasizing the fact the Allen (2005) never claimed to rule out all semantic contributions to syntax, we propose an improvement in Kemmerer's approach that might provide more satisfactory evidence on the distinction between the kinds of relevant versus irrelevant features his studies have addressed.

Electron Beam Freeform Fabrication of Titanium Alloy Gradient Structures

NASA Technical Reports Server (NTRS)

Brice, Craig A.; Newman, John A.; Bird, Richard Keith; Shenoy, Ravi N.; Baughman, James M.; Gupta, Vipul K.

2014-01-01

Historically, the structural optimization of aerospace components has been done through geometric methods. A monolithic material is chosen based on the best compromise between the competing design limiting criteria. Then the structure is geometrically optimized to give the best overall performance using the single material chosen. Functionally graded materials offer the potential to further improve structural efficiency by allowing the material composition and/or microstructural features to spatially vary within a single structure. Thus, local properties could be tailored to the local design limiting criteria. Additive manufacturing techniques enable the fabrication of such graded materials and structures. This paper presents the results of a graded material study using two titanium alloys processed using electron beam freeform fabrication, an additive manufacturing process. The results show that the two alloys uniformly mix at various ratios and the resultant static tensile properties of the mixed alloys behave according to rule-of-mixtures. Additionally, the crack growth behavior across an abrupt change from one alloy to the other shows no discontinuity and the crack smoothly transitions from one crack growth regime into another.

31 CFR 1024.314 - Structured transactions.

Code of Federal Regulations, 2011 CFR

2011-07-01

...) FINANCIAL CRIMES ENFORCEMENT NETWORK, DEPARTMENT OF THE TREASURY RULES FOR MUTUAL FUNDS Reports Required To Be Made By Mutual Funds § 1024.314 Structured transactions. Refer to § 1010.314 of this chapter for rules regarding structured transactions for mutual funds. ...

Application of text mining for customer evaluations in commercial banking

NASA Astrophysics Data System (ADS)

Tan, Jing; Du, Xiaojiang; Hao, Pengpeng; Wang, Yanbo J.

2015-07-01

Nowadays customer attrition is increasingly serious in commercial banks. To combat this problem roundly, mining customer evaluation texts is as important as mining customer structured data. In order to extract hidden information from customer evaluations, Textual Feature Selection, Classification and Association Rule Mining are necessary techniques. This paper presents all three techniques by using Chinese Word Segmentation, C5.0 and Apriori, and a set of experiments were run based on a collection of real textual data that includes 823 customer evaluations taken from a Chinese commercial bank. Results, consequent solutions, some advice for the commercial bank are given in this paper.

Tuning topological phases in the XMnSb2 system via chemical substitution from first principles

NASA Astrophysics Data System (ADS)

Griffin, Sinead M.; Neaton, Jeffrey B.

New Dirac materials are sought for their interesting fundamental physics and for their potential technological applications. Protected symmetries offer a route to potential zero mass Dirac and Weyl fermions, and can lead unique transport properties and spectroscopic signatures. In this work, we use first-principles calculations to study the XMnSb2 family of materials and show how varying X changes the nature of bulk protected topological features in their electronic structure. We further discuss new design rules for predicting new topological materials suggested by our calculations. SG is supported by the Early Postdoc Mobility Fellowship of the SNF.

On the effect of memory in one-dimensional K=4 automata on networks

NASA Astrophysics Data System (ADS)

Alonso-Sanz, Ramón; Cárdenas, Juan Pablo

2008-12-01

The effect of implementing memory in cells of one-dimensional CA, and on nodes of various types of automata on networks with increasing degrees of random rewiring is studied in this article, paying particular attention to the case of four inputs. As a rule, memory induces a moderation in the rate of changing nodes and in the damage spreading, albeit in the latter case memory turns out to be ineffective in the control of the damage as the wiring network moves away from the ordered structure that features proper one-dimensional CA. This article complements the previous work done in the two-dimensional context.

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

Spin excitations used to probe the nature of exchange coupling in the magnetically ordered ground state of Pr 0.5 Ca 0.5 MnO 3

DOE PAGES

Ewings, R. A.; Perring, T. G.; Sikora, O.; ...

2016-07-06

We have used time-of-flight inelastic neutron scattering to measure the spin wave spectrum of the canonical half-doped manganite Pr 0.5Ca 0.5MnO 3 in its magnetic and orbitally ordered phase. Comparison of the data, which cover multiple Brillouin zones and the entire energy range of the excitations, with several different models shows that only the CE-type ordered state provides an adequate description of the magnetic ground state, provided interactions beyond nearest neighbor are included. We are able to rule out a ground state in which there exist pairs of dimerized spins which interact only with their nearest neighbors. The Zener polaronmore » ground state, which comprises strongly bound magnetic dimers, can be ruled out on the basis of gross features of the observed spin wave spectrum. A model with weaker dimerization reproduces the observed dispersion but can be ruled out on the basis of subtle discrepancies between the calculated and observed structure factors at certain positions in reciprocal space. Adding further neighbor interactions results in almost no dimerization, i.e. interpolating back to the CE model. These results are consistent with theoretical analysis of the degenerate double exchange model for half-doping.« less

Rules and Self-Organizing Properties of Post-embryonic Plant Organ Cell Division Patterns.

PubMed

von Wangenheim, Daniel; Fangerau, Jens; Schmitz, Alexander; Smith, Richard S; Leitte, Heike; Stelzer, Ernst H K; Maizel, Alexis

2016-02-22

Plants form new organs with patterned tissue organization throughout their lifespan. It is unknown whether this robust post-embryonic organ formation results from stereotypic dynamic processes, in which the arrangement of cells follows rigid rules. Here, we combine modeling with empirical observations of whole-organ development to identify the principles governing lateral root formation in Arabidopsis. Lateral roots derive from a small pool of founder cells in which some take a dominant role as seen by lineage tracing. The first division of the founders is asymmetric, tightly regulated, and determines the formation of a layered structure. Whereas the pattern of subsequent cell divisions is not stereotypic between different samples, it is characterized by a regular switch in division plane orientation. This switch is also necessary for the appearance of patterned layers as a result of the apical growth of the primordium. Our data suggest that lateral root morphogenesis is based on a limited set of rules. They determine cell growth and division orientation. The organ-level coupling of the cell behavior ensures the emergence of the lateral root's characteristic features. We propose that self-organizing, non-deterministic modes of development account for the robustness of plant organ morphogenesis. Copyright © 2016 Elsevier Ltd. All rights reserved.

78 FR 36084 - Special Conditions: The Boeing Company, Model 717-200 Series Airplanes; Seats With Inflatable...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-06-17

... 717- 200 series airplanes. These airplanes will have a novel or unusual design feature [[Page 36085... series airplanes will incorporate the following novel or unusual design features: inflatable lapbelts on... certain novel or unusual design features on one model series of airplanes. It is not a rule of general...

Infant Learning Is Influenced by Local Spurious Generalizations

ERIC Educational Resources Information Center

Gerken, LouAnn; Quam, Carolyn

2017-01-01

In previous work, 11-month-old infants were able to learn rules about the relation of the consonants in CVCV words from just four examples. The rules involved phonetic feature relations (same voicing or same place of articulation), and infants' learning was impeded when pairs of words allowed alternative possible generalizations (e.g. two words…

Impact of Consciousness-Raising Activities on Young English Language Learners' Grammar Performance

ERIC Educational Resources Information Center

Fatemipour, Hamidreza; Hemmati, Shiva

2015-01-01

Grammar Consciousness-Raising (GCR) is an approach to teaching of grammar which learners instead of being taught the given rules, experience language data. The data challenge them to rethink, restructure their existing mental grammar and construct an explicit rule to describe the grammatical feature which the data illustrate (Ellis, 2002). And…

Optimal Test Design with Rule-Based Item Generation

ERIC Educational Resources Information Center

Geerlings, Hanneke; van der Linden, Wim J.; Glas, Cees A. W.

2013-01-01

Optimal test-design methods are applied to rule-based item generation. Three different cases of automated test design are presented: (a) test assembly from a pool of pregenerated, calibrated items; (b) test generation on the fly from a pool of calibrated item families; and (c) test generation on the fly directly from calibrated features defining…

Nonstandard American English of Socially Disadvantaged Negro Children. Final Report.

ERIC Educational Resources Information Center

Marwit, Samuel, J.; And Others

It has recently been noted that Negro children, especially those of lower socioeconomic status, have a language system whose phonological and grammatical rules differ in predictable ways from the rules governing the standard English used by most white Americans. Four features of Negro non- standard American English have been noted with predictable…

God: Do I Have Your Attention?

ERIC Educational Resources Information Center

Colzato, Lorenza S.; van Beest, Ilja; van den Wildenberg, Wery P. M.; Scorolli, Claudia; Dorchin, Shirley; Meiran, Nachshon; Borghi, Anna M.; Hommel, Bernhard

2010-01-01

Religion is commonly defined as a set of rules, developed as part of a culture. Here we provide evidence that practice in following these rules systematically changes the way people attend to visual stimuli, as indicated by the individual sizes of the global precedence effect (better performance to global than to local features). We show that this…

Uptake and localization mechanisms of fluorescent and colored lipid probes. Part 2. QSAR models that predict localization of fluorescent probes used to identify ("specifically stain") various biomembranes and membranous organelles.

PubMed

Horobin, R W; Stockert, J C; Rashid-Doubell, F

2015-05-01

We discuss a variety of biological targets including generic biomembranes and the membranes of the endoplasmic reticulum, endosomes/lysosomes, Golgi body, mitochondria (outer and inner membranes) and the plasma membrane of usual fluidity. For each target, we discuss the access of probes to the target membrane, probe uptake into the membrane and the mechanism of selectivity of the probe uptake. A statement of the QSAR decision rule that describes the required physicochemical features of probes that enable selective staining also is provided, followed by comments on exceptions and limits. Examples of probes typically used to demonstrate each target structure are noted and decision rule tabulations are provided for probes that localize in particular targets; these tabulations show distribution of probes in the conceptual space defined by the relevant structure parameters ("parameter space"). Some general implications and limitations of the QSAR models for probe targeting are discussed including the roles of certain cell and protocol factors that play significant roles in lipid staining. A case example illustrates the predictive ability of QSAR models. Key limiting values of the head group hydrophilicity parameter associated with membrane-probe interactions are discussed in an appendix.

Comparing T-odd and T-even spin sum rules

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

Teryaev, O.V.

2015-04-10

Sum rules for T-even and T-odd structure functions and parton distributions are considered. The case of spin-dependent distributions related to energy-momentum tensor (EMT) is specifically addressed. The Burkardt sum rule for T-odd Sivers functions may be related to EMT provided the imaginary prescription for gluonic pole correlator is incorporated. The momentum sum rule for deuteron tensor spin structure function allows one to probe indirectly the gravity couplings to quarks and gluons.

26 CFR 1.1446-5 - Tiered partnership structures.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 26 Internal Revenue 12 2010-04-01 2010-04-01 false Tiered partnership structures. 1.1446-5 Section...-Free Covenant Bonds § 1.1446-5 Tiered partnership structures. (a) In general. The rules of this section... prescribes rules applicable to a publicly traded partnership in a tiered partnership structure. Paragraph (e...

Cellular scaling rules for the brain of afrotherians

PubMed Central

Neves, Kleber; Ferreira, Fernanda M.; Tovar-Moll, Fernanda; Gravett, Nadine; Bennett, Nigel C.; Kaswera, Consolate; Gilissen, Emmanuel; Manger, Paul R.; Herculano-Houzel, Suzana

2014-01-01

Quantitative analysis of the cellular composition of rodent, primate and eulipotyphlan brains has shown that non-neuronal scaling rules are similar across these mammalian orders that diverged about 95 million years ago, and therefore appear to be conserved in evolution, while neuronal scaling rules appear to be free to vary in evolution in a clade-specific manner. Here we analyze the cellular scaling rules that apply to the brain of afrotherians, believed to be the first clade to radiate from the common eutherian ancestor. We find that afrotherians share non-neuronal scaling rules with rodents, primates and eulipotyphlans, as well as the coordinated scaling of numbers of neurons in the cerebral cortex and cerebellum. Afrotherians share with rodents and eulipotyphlans, but not with primates, the scaling of number of neurons in the cortex and in the cerebellum as a function of the number of neurons in the rest of the brain. Afrotheria also share with rodents and eulipotyphlans the neuronal scaling rules that apply to the cerebral cortex. Afrotherians share with rodents, but not with eulipotyphlans nor primates, the neuronal scaling rules that apply to the cerebellum. Importantly, the scaling of the folding index of the cerebral cortex with the number of neurons in the cerebral cortex is not shared by either afrotherians, rodents, or primates. The sharing of some neuronal scaling rules between afrotherians and rodents, and of some additional features with eulipotyphlans and primates, raise the interesting possibility that these shared characteristics applied to the common eutherian ancestor. In turn, the clade-specific characteristics that relate to the distribution of neurons along the surface of the cerebral cortex and to its degree of gyrification suggest that these characteristics compose an evolutionarily plastic suite of features that may have defined and distinguished mammalian groups in evolution. PMID:24596544

Get over it. New overtime rules a mixed bag for group practices.

PubMed

Tesdahl, D Benson; Saner, Robert J

2004-01-01

New overtime pay rules went into effect Aug. 23, 2004, that will have a dramatic impact on many employers. The rules have several features of particular significance to physician practices. They are the first extensive overhaul of federal overtime regulations, as part of the Fair Labor Standards Act, in more than 30 years. Because the government has given new definitions to exempt administrative and executive employees, medical groups should have considerable flexibility in developing overtime pay strategies.

Ergonomics and regulatory politics: the Washington State case.

PubMed

Silverstein, Michael

2007-05-01

Every year in the State of Washington more than 50,000 workers experience a work related musculoskeletal disorder (WMSD), making up more than 30% of all worker compensation cases. In 2000, the Washington State Department of Labor and Industries (L&I) adopted a workplace ergonomics rule requiring employers to reduce worker exposure to hazards that cause or contribute to WMSDs. In 2003, the ergonomics rule was repealed by a margin of 53.5-46.5 in a statewide voter initiative. The official rulemaking record of approximately 100,000 pages, along with supplementary published and unpublished material, was reviewed. The relationship between scientific deliberation and the public policy process in adopting and repealing the ergonomics rule was assessed and described. The deliberative features of the regulatory, judicial, legislative, and ballot processes were compared. The ergonomics rule was successful in the regulatory and legal arenas where the process was most transparent and open to public involvement, differing views could be presented fully, and decision makers were expected to explain their decisions in light of the record. The rule fared most poorly in the legislature and at the ballot box when these features were lost and where considered deliberation was replaced by unconstrained political conflict. Additional checks and balances are needed.

Towards automated processing of clinical Finnish: sublanguage analysis and a rule-based parser.

PubMed

Laippala, Veronika; Ginter, Filip; Pyysalo, Sampo; Salakoski, Tapio

2009-12-01

In this paper, we present steps taken towards more efficient automated processing of clinical Finnish, focusing on daily nursing notes in a Finnish Intensive Care Unit (ICU). First, we analyze ICU Finnish as a sublanguage, identifying its specific features facilitating, for example, the development of a specialized syntactic analyser. The identified features include frequent omission of finite verbs, limitations in allowed syntactic structures, and domain-specific vocabulary. Second, we develop a formal grammar and a parser for ICU Finnish, thus providing better tools for the development of further applications in the clinical domain. The grammar is implemented in the LKB system in a typed feature structure formalism. The lexicon is automatically generated based on the output of the FinTWOL morphological analyzer adapted to the clinical domain. As an additional experiment, we study the effect of using Finnish constraint grammar to reduce the size of the lexicon. The parser construction thus makes efficient use of existing resources for Finnish. The grammar currently covers 76.6% of ICU Finnish sentences, producing highly accurate best-parse analyzes with F-score of 91.1%. We find that building a parser for the highly specialized domain sublanguage is not only feasible, but also surprisingly efficient, given an existing morphological analyzer with broad vocabulary coverage. The resulting parser enables a deeper analysis of the text than was previously possible.

Student Understanding of Cross Product Direction and Use of Right-hand Rules: An Exploration of Representation and Context-dependence

NASA Astrophysics Data System (ADS)

Kustusch, Mary Bridget

2011-12-01

Students in introductory physics struggle with vector algebra and with cross product direction in particular. Some have suggested that this may be due to misapplied right-hand rules, but there are few studies that have had the resolution to explore this. Additionally, previous research on student understanding has noted several kinds of representation-dependence of student performance with vector algebra in both physics and non-physics (or math) contexts (e.g. Hawkins et al., 2009; Van Deventer, 2008). Yet with few exceptions (e.g. Scaife and Heckler, 2010), these findings have not been applied to cross product direction questions or the use of right-hand rules. Also, the extensive work in spatial cognition is particularly applicable to cross product direction due to the spatial and kinesthetic nature of the right-hand rule. A synthesis of the literature from these various fields reveals four categories of problem features likely to impact the understanding of cross product direction: (1) the type of reasoning required, (2) the orientation of the vectors, (3) the need for parallel transport, and (4) the physics context and features (or lack thereof). These features formed the basis of the present effort to systematically explore the context-dependence and representation- dependence of student performance on cross product direction questions. This study used a mix of qualitative and quantitative techniques to analyze twenty-seven individual think-aloud interviews. During these interviews, second semester introductory physics students answered 80-100 cross product direction questions in different contexts and with varying problem features. These features were then used as the predictors in regression analyses for correctness and response time. In addition, each problem was coded for the methods used and the errors made to gain a deeper understanding of student behavior and the impact of these features. The results revealed a wide variety of methods (including six different right-hand rules), many different types of errors, and significant context-dependence and representation-dependence for the features mentioned above. Problems that required reasoning backward to find A⃗ (for C⃗=A⃗ xB⃗ ) presented the biggest challenge for students. Participants who recognized the non-commutativity of the cross product would often reverse the order ( B⃗xA⃗ ) on these problems. Also, this error occurred less frequently when a Guess and Check method was used in addition to the right-hand rule. Three different aspects of orientation had a significant impact on performance: (1) the physical discomfort of using a right-hand rule, (2) the plane of the given vectors, and to a lesser extent, (3) the angle between the vectors. One participant was more likely to switch the order of the vectors for the physically awkward orientations than for the physically easy orientations; and there was evidence that some of the difficulty with vector orientations that were not in the xy-plane was due to misinterpretations of the into and out of the page symbols. The impact of both physical discomfort and the plane of the vectors was reduced when participants rotated the paper. Unlike other problem features, the issue of parallel transport did not appear to be nearly as prevalent for cross product direction as it is for vector addition and subtraction. In addition to these findings, this study confirmed earlier findings regarding physics difficulties with magnetic field and magnetic force, such as differences in performance based on the representation of magnetic field (Scaife and Heckler, 2010) and confusion between electric and magnetic fields (Maloney et al., 2001). It also provided evidence of physics difficulties with magnetic field and magnetic force that have been suspected but never explored, specifically the impact of the sign of the charge and the observation location. This study demonstrated that student difficulty with cross product direction is not as simple as misapplied right-hand rules, although this is an issue. Student behavior on cross product direction questions is significantly dependent on both the context of the question and the representation of various problem features. Although more research is necessary, particularly in regard to individual differences, this study represents a significant step forward in our understanding of student difficulties with cross product direction.

Intrusion detection using rough set classification.

PubMed

Zhang, Lian-hua; Zhang, Guan-hua; Zhang, Jie; Bai, Ying-cai

2004-09-01

Recently machine learning-based intrusion detection approaches have been subjected to extensive researches because they can detect both misuse and anomaly. In this paper, rough set classification (RSC), a modern learning algorithm, is used to rank the features extracted for detecting intrusions and generate intrusion detection models. Feature ranking is a very critical step when building the model. RSC performs feature ranking before generating rules, and converts the feature ranking to minimal hitting set problem addressed by using genetic algorithm (GA). This is done in classical approaches using Support Vector Machine (SVM) by executing many iterations, each of which removes one useless feature. Compared with those methods, our method can avoid many iterations. In addition, a hybrid genetic algorithm is proposed to increase the convergence speed and decrease the training time of RSC. The models generated by RSC take the form of "IF-THEN" rules, which have the advantage of explication. Tests and comparison of RSC with SVM on DARPA benchmark data showed that for Probe and DoS attacks both RSC and SVM yielded highly accurate results (greater than 99% accuracy on testing set).

A systematic analysis of atomic protein-ligand interactions in the PDB.

PubMed

Ferreira de Freitas, Renato; Schapira, Matthieu

2017-10-01

As the protein databank (PDB) recently passed the cap of 123 456 structures, it stands more than ever as an important resource not only to analyze structural features of specific biological systems, but also to study the prevalence of structural patterns observed in a large body of unrelated structures, that may reflect rules governing protein folding or molecular recognition. Here, we compiled a list of 11 016 unique structures of small-molecule ligands bound to proteins - 6444 of which have experimental binding affinity - representing 750 873 protein-ligand atomic interactions, and analyzed the frequency, geometry and impact of each interaction type. We find that hydrophobic interactions are generally enriched in high-efficiency ligands, but polar interactions are over-represented in fragment inhibitors. While most observations extracted from the PDB will be familiar to seasoned medicinal chemists, less expected findings, such as the high number of C-H···O hydrogen bonds or the relatively frequent amide-π stacking between the backbone amide of proteins and aromatic rings of ligands, uncover underused ligand design strategies.

Comparison of inkjet-printed silver conductors on different microsystem substrates

NASA Astrophysics Data System (ADS)

Kruger, Jené; Bezuidenhout, Petroné H.; Joubert, Trudi-Heleen

2016-02-01

Applications for diagnostic and environmental point-of-need require processes and building blocks to add smart features to disposable biosensors on low-cost substrates. A novel method for producing such biosensors is printing electronics using additive technologies. This work contributes to the toolbox of processes, materials and components for printed electronics manufacturing - as well as rapid prototyping - of circuits. Printing protocols were developed to facilitate successful inkjet printing of nanosilver ink (Harima NPS-JL) onto different microsystem substrates using a functional printer (Dimatix DMP-3281). Photo paper is a standard inkjet substrate, which were compared with glass, polycarbonate (PC), plastic projector transparency foil, and polydimethylsiloxane (PDMS). Comparison attributes include physical and electrical properties. The layout design comprised dogbone elements of 8 mm length, and widths varying between 100 μm and 2 mm. All printed features were thermally cured for 1 hour at 120 °C. The physical characteristics were measured with a laser scanning microscope (Zeiss LSM-5) to determine the width, thickness and surface roughness of the printed features. An LCR meter (GW-Instek 8110) was used to measure the printed structures' electrical characteristics (resistance, capacitance and inductance). A lumped element model and layout design rules were extracted to assist in standardized design procedures. The model incorporates prediction of the bandwidth attainable with these structures. The layer thickness on all substrates is larger than the 1 μm on photo paper, and varies between 1.6 μm (PC) and 7 μm (PDMS). The spreading for PDMS is similar to photo paper, but since for the other substrates it is between 5 (glass) and 10 (PC) times larger than for photo paper, the layout design rules require large spacing, leading to larger area networks. Electrical probing on the PDMS is not consistent and results are inconclusive. For the other substrates, the comparative dogbone resistance (100 μm width) is significantly larger than the 2 Ω standard, varying from 12.6 Ω (PC) to 19.3 Ω (glass). The bandwidth relative to photo paper is smaller by a factor of between 6 (PC) and 9.5 (glass).

75 FR 47141 - Review of Personal Radio Services Rules

Federal Register 2010, 2011, 2012, 2013, 2014

2010-08-04

...In this document, the Commission proposes to update, reorganize, simplify and streamline its Personal Radio Services rules to reflect technological advances and other changes in the way the American public uses the Personal Radio Services. In addition to improving the clarity of the rules, this document includes proposals intended to reduce unnecessary regulatory burdens on users, improve spectrum use, provide for enhanced equipment operating features, and promote the safety and consumer interests of operators. The document also proposes to reclassify one of the existing Personal Radio Services, specifically the 218-219 MHz service, as a Miscellaneous Wireless Communications Service, and accordingly move its rules from one part to another.

Fusion of multichannel local and global structural cues for photo aesthetics evaluation.

PubMed

Luming Zhang; Yue Gao; Zimmermann, Roger; Qi Tian; Xuelong Li

2014-03-01

Photo aesthetic quality evaluation is a fundamental yet under addressed task in computer vision and image processing fields. Conventional approaches are frustrated by the following two drawbacks. First, both the local and global spatial arrangements of image regions play an important role in photo aesthetics. However, existing rules, e.g., visual balance, heuristically define which spatial distribution among the salient regions of a photo is aesthetically pleasing. Second, it is difficult to adjust visual cues from multiple channels automatically in photo aesthetics assessment. To solve these problems, we propose a new photo aesthetics evaluation framework, focusing on learning the image descriptors that characterize local and global structural aesthetics from multiple visual channels. In particular, to describe the spatial structure of the image local regions, we construct graphlets small-sized connected graphs by connecting spatially adjacent atomic regions. Since spatially adjacent graphlets distribute closely in their feature space, we project them onto a manifold and subsequently propose an embedding algorithm. The embedding algorithm encodes the photo global spatial layout into graphlets. Simultaneously, the importance of graphlets from multiple visual channels are dynamically adjusted. Finally, these post-embedding graphlets are integrated for photo aesthetics evaluation using a probabilistic model. Experimental results show that: 1) the visualized graphlets explicitly capture the aesthetically arranged atomic regions; 2) the proposed approach generalizes and improves four prominent aesthetic rules; and 3) our approach significantly outperforms state-of-the-art algorithms in photo aesthetics prediction.

Intrinsic information carriers in combinatorial dynamical systems.

PubMed

Harmer, Russ; Danos, Vincent; Feret, Jérôme; Krivine, Jean; Fontana, Walter

2010-09-01

Many proteins are composed of structural and chemical features--"sites" for short--characterized by definite interaction capabilities, such as noncovalent binding or covalent modification of other proteins. This modularity allows for varying degrees of independence, as the behavior of a site might be controlled by the state of some but not all sites of the ambient protein. Independence quickly generates a startling combinatorial complexity that shapes most biological networks, such as mammalian signaling systems, and effectively prevents their study in terms of kinetic equations-unless the complexity is radically trimmed. Yet, if combinatorial complexity is key to the system's behavior, eliminating it will prevent, not facilitate, understanding. A more adequate representation of a combinatorial system is provided by a graph-based framework of rewrite rules where each rule specifies only the information that an interaction mechanism depends on. Unlike reactions, which deal with molecular species, rules deal with patterns, i.e., multisets of molecular species. Although the stochastic dynamics induced by a collection of rules on a mixture of molecules can be simulated, it appears useful to capture the system's average or deterministic behavior by means of differential equations. However, expansion of the rules into kinetic equations at the level of molecular species is not only impractical, but conceptually indefensible. If rules describe bona fide patterns of interaction, molecular species are unlikely to constitute appropriate units of dynamics. Rather, we must seek aggregate variables reflective of the causal structure laid down by the rules. We call these variables "fragments" and the process of identifying them "fragmentation." Ideally, fragments are aspects of the system's microscopic population that the set of rules can actually distinguish on average; in practice, it may only be feasible to identify an approximation to this. Most importantly, fragments are self-consistent descriptors of system dynamics in that their time-evolution is governed by a closed system of kinetic equations. Taken together, fragments are endogenous distinctions that matter for the dynamics of a system, which warrants viewing them as the carriers of information. Although fragments can be thought of as multisets of molecular species (an extensional view), their self-consistency suggests treating them as autonomous aspects cut off from their microscopic realization (an intensional view). Fragmentation is a seeded process that depends on the choice of observables whose dynamics one insists to describe. Different observables can cause distinct fragmentations, in effect altering the set of information carriers that govern the behavior of a system, even though nothing has changed in its microscopic constitution. In this contribution, we present a mathematical specification of fragments, but not an algorithmic implementation. We have described the latter elsewhere in rather technical terms that, although effective, were lacking an embedding into a more general conceptual framework, which we here provide.

A New Approach to Automated Labeling of Internal Features of Hardwood Logs Using CT Images

Treesearch

Daniel L. Schmoldt; Pei Li; A. Lynn Abbott

1996-01-01

The feasibility of automatically identifying internal features of hardwood logs using CT imagery has been established previously. Features of primary interest are bark, knots, voids, decay, and clear wood. Our previous approach: filtered original CT images, applied histogram segmentation, grew volumes to extract 3-d regions, and applied a rule base, with Dempster-...

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.

Probabilistic combination of static and dynamic gait features for verification

NASA Astrophysics Data System (ADS)

Bazin, Alex I.; Nixon, Mark S.

2005-03-01

This paper describes a novel probabilistic framework for biometric identification and data fusion. Based on intra and inter-class variation extracted from training data, posterior probabilities describing the similarity between two feature vectors may be directly calculated from the data using the logistic function and Bayes rule. Using a large publicly available database we show the two imbalanced gait modalities may be fused using this framework. All fusion methods tested provide an improvement over the best modality, with the weighted sum rule giving the best performance, hence showing that highly imbalanced classifiers may be fused in a probabilistic setting; improving not only the performance, but also generalized application capability.

A hierarchical structure for representing and learning fuzzy rules

NASA Technical Reports Server (NTRS)

Yager, Ronald R.

1993-01-01

Yager provides an example in which the flat representation of fuzzy if-then rules leads to unsatisfactory results. Consider a rule base consisting to two rules: if U is 12 the V is 29; if U is (10-15) the V is (25-30). If U = 12 we would get V is G where G = (25-30). The application of the defuzzification process leads to a selection of V = 27.5. Thus we see that the very specific instruction was not followed. The problem with the technique used is that the most specific information was swamped by the less specific information. In this paper we shall provide for a new structure for the representation of fuzzy if-then rules. The representational form introduced here is called a Hierarchical Prioritized Structure (HPS) representation. Most importantly in addition to overcoming the problem illustrated in the previous example this HPS representation has an inherent capability to emulate the learning of general rules and provides a reasonable accurate cognitive mapping of how human beings store information.

A Second Look at Brian Simon's "Bending the Rules"

ERIC Educational Resources Information Center

Cox, Sue

2016-01-01

In this article the author revisits an important book: Brian Simon's "Bending the Rules: the Baker reform of education." Written by a key figure in the history of the journal FORUM as well as in the history of education, Simon's book documented the features of the Education Reform Bill of 1987 (the precursor to the Education Reform Act…

77 FR 46781 - Self-Regulatory Organizations; Chicago Board Options Exchange, Incorporated; Order Approving a...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-08-06

... rules. See id. A. SAL SAL is a feature within CBOE's Hybrid System designed to provide price improvement... before being booked in the electronic complex order book (``COB'') or on a PAR workstation.\\22\\ To the... rules of a national securities exchange be designed to prevent fraudulent and manipulative acts and...

Preterite/Imperfect Half-Truths: Problems with Spanish Textbook Rules for Usage.

ERIC Educational Resources Information Center

Frantzen, Diana

1995-01-01

Preterite/Imperfect (PI) usage is one of the hardest grammatical features of Spanish to learn. Some of the blame lies with misleading textbook explanations. A discussion of problematic P/I textbook explanations shows why the presentation of a more reliable set of principles is a preferable alternative to questionable rules of thumb. (18…

Bridging Theory of Mind and the Personal Domain: Children's Reasoning about Resistance to Parental Control

ERIC Educational Resources Information Center

Lagattuta, Kristin Hansen; Nucci, Larry; Bosacki, Sandra Leanne

2010-01-01

Four-, 5-, and 7-year-olds (N = 60) listened to vignettes featuring characters that wanted to do actions that conflicted with parental rules. Desires included behaviors associated with the personal domain: friend, activity, and clothing choice. Scenarios involving moral rules served as a comparison. Children predicted and explained characters'…

The development and testing of the thermal break divertor monoblock target design delivering 20 MW m-2 heat load capability

NASA Astrophysics Data System (ADS)

Fursdon, M.; Barrett, T.; Domptail, F.; Evans, Ll M.; Luzginova, N.; Greuner, N. H.; You, J.-H.; Li, M.; Richou, M.; Gallay, F.; Visca, E.

2017-12-01

The design and development of a novel plasma facing component (for fusion power plants) is described. The component uses the existing ‘monoblock’ construction which consists of a tungsten ‘block’ joined via a copper interlayer to a through CuCrZr cooling pipe. In the new concept the interlayer stiffness and conductivity properties are tuned so that stress in the principal structural element of the component (the cooling pipe) is reduced. Following initial trials with off-the-shelf materials, the concept was realized by machined features in an otherwise solid copper interlayer. The shape and distribution of the features were tuned by finite element analyses subject to ITER structural design criterion in-vessel components (SDC-IC) design rules. Proof of concept mock-ups were manufactured using a two stage brazing process verified by tomography and micrographic inspection. Full assemblies were inspected using ultrasound and thermographic (SATIR) test methods at ENEA and CEA respectively. High heat flux tests using IPP’s GLADIS facility showed that 200 cycles at 20 MW m-2 and five cycles at 25 MW m-2 could be sustained without apparent component damage. Further testing and component development is planned.

One Shot Detection with Laplacian Object and Fast Matrix Cosine Similarity.

PubMed

Biswas, Sujoy Kumar; Milanfar, Peyman

2016-03-01

One shot, generic object detection involves searching for a single query object in a larger target image. Relevant approaches have benefited from features that typically model the local similarity patterns. In this paper, we combine local similarity (encoded by local descriptors) with a global context (i.e., a graph structure) of pairwise affinities among the local descriptors, embedding the query descriptors into a low dimensional but discriminatory subspace. Unlike principal components that preserve global structure of feature space, we actually seek a linear approximation to the Laplacian eigenmap that permits us a locality preserving embedding of high dimensional region descriptors. Our second contribution is an accelerated but exact computation of matrix cosine similarity as the decision rule for detection, obviating the computationally expensive sliding window search. We leverage the power of Fourier transform combined with integral image to achieve superior runtime efficiency that allows us to test multiple hypotheses (for pose estimation) within a reasonably short time. Our approach to one shot detection is training-free, and experiments on the standard data sets confirm the efficacy of our model. Besides, low computation cost of the proposed (codebook-free) object detector facilitates rather straightforward query detection in large data sets including movie videos.

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

PubMed

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

2006-01-01

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

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.

Unambiguous UML Composite Structures: The OMEGA2 Experience

NASA Astrophysics Data System (ADS)

Ober, Iulian; Dragomir, Iulia

Starting from version 2.0, UML introduced hierarchical composite structures, which are a very expressive way of defining complex software architectures, but which have a very loosely defined semantics in the standard. In this paper we propose a set of consistency rules that ensure UML composite structures are unambiguous and can be given a precise semantics. Our primary application of the static consistency rules defined in this paper is within the OMEGA UML profile [6], but these rules are general and applicable to other hierarchical component models based on the same concepts, such as MARTE GCM or SysML. The rule set has been formalized in OCL and is currently used in the OMEGA UML compiler.

Learning Semantic Tags from Big Data for Clinical Text Representation.

PubMed

Li, Yanpeng; Liu, Hongfang

2015-01-01

In clinical text mining, it is one of the biggest challenges to represent medical terminologies and n-gram terms in sparse medical reports using either supervised or unsupervised methods. Addressing this issue, we propose a novel method for word and n-gram representation at semantic level. We first represent each word by its distance with a set of reference features calculated by reference distance estimator (RDE) learned from labeled and unlabeled data, and then generate new features using simple techniques of discretization, random sampling and merging. The new features are a set of binary rules that can be interpreted as semantic tags derived from word and n-grams. We show that the new features significantly outperform classical bag-of-words and n-grams in the task of heart disease risk factor extraction in i2b2 2014 challenge. It is promising to see that semantics tags can be used to replace the original text entirely with even better prediction performance as well as derive new rules beyond lexical level.

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.

Aspiration dynamics in structured population acts as if in a well-mixed one.

PubMed

Du, Jinming; Wu, Bin; Wang, Long

2015-01-26

Understanding the evolution of human interactive behaviors is important. Recent experimental results suggest that human cooperation in spatial structured population is not enhanced as predicted in previous works, when payoff-dependent imitation updating rules are used. This constraint opens up an avenue to shed light on how humans update their strategies in real life. Studies via simulations show that, instead of comparison rules, self-evaluation driven updating rules may explain why spatial structure does not alter the evolutionary outcome. Though inspiring, there is a lack of theoretical result to show the existence of such evolutionary updating rule. Here we study the aspiration dynamics, and show that it does not alter the evolutionary outcome in various population structures. Under weak selection, by analytical approximation, we find that the favored strategy in regular graphs is invariant. Further, we show that this is because the criterion under which a strategy is favored is the same as that of a well-mixed population. By simulation, we show that this holds for random networks. Although how humans update their strategies is an open question to be studied, our results provide a theoretical foundation of the updating rules that may capture the real human updating rules.

Interaction rules for symbol-oriented graphical user interfaces

NASA Astrophysics Data System (ADS)

Brinkschulte, Uwe; Vogelsang, Holger; Wolf, Luc

1999-03-01

This work describes a way of interactive manipulation of structured objects by interaction rules. Symbols are used as graphical representation of object states. State changes lead to different visual symbol instances. The manipulation of symbols using interactive devices lead to an automatic state change of the corresponding structured object without any intervention of the application. Therefore, interaction rules are introduced. These rules describe the way a symbol may be manipulated and the effects this manipulation has on the corresponding structured object. The rules are interpreted by the visualization and interaction service. For each symbol used, a set of interaction rules can be defined. In order to be the more general as possible, all the interactions on a symbol are defined as a triple, which specifies the preconditions of all the manipulations of this symbol, the manipulations themselves, and the postconditions of all the manipulations of this symbol. A manipulation is a quintuplet, which describes the possible initial events of the manipulation, the possible places of these events, the preconditions of this manipulation, the results of this manipulation, and the postconditions of this manipulation. Finally, reflection functions map the results of a manipulation to the new state of a structured object.

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.

46 CFR 116.300 - Structural design.

Code of Federal Regulations, 2013 CFR

2013-10-01

... Structure § 116.300 Structural design. Except as otherwise allowed by this subpart, a vessel must comply... the vessel. (a) Steel hull vessels: (1) Rules and Regulations for the Classification of Yachts and Small Craft, Lloyd's Register of Shipping (Lloyd's); or (2) Rules for Building and Classing Steel...

46 CFR 116.300 - Structural design.

Code of Federal Regulations, 2012 CFR

2012-10-01

... Structure § 116.300 Structural design. Except as otherwise allowed by this subpart, a vessel must comply... the vessel. (a) Steel hull vessels: (1) Rules and Regulations for the Classification of Yachts and Small Craft, Lloyd's Register of Shipping (Lloyd's); or (2) Rules for Building and Classing Steel...

46 CFR 116.300 - Structural design.

Code of Federal Regulations, 2010 CFR

2010-10-01

... Structure § 116.300 Structural design. Except as otherwise allowed by this subpart, a vessel must comply... the vessel. (a) Steel hull vessels: (1) Rules and Regulations for the Classification of Yachts and Small Craft, Lloyd's Register of Shipping (Lloyd's); or (2) Rules for Building and Classing Steel...

46 CFR 116.300 - Structural design.

Code of Federal Regulations, 2011 CFR

2011-10-01

... Structure § 116.300 Structural design. Except as otherwise allowed by this subpart, a vessel must comply... the vessel. (a) Steel hull vessels: (1) Rules and Regulations for the Classification of Yachts and Small Craft, Lloyd's Register of Shipping (Lloyd's); or (2) Rules for Building and Classing Steel...

46 CFR 116.300 - Structural design.

Code of Federal Regulations, 2014 CFR

2014-10-01

... Structure § 116.300 Structural design. Except as otherwise allowed by this subpart, a vessel must comply... the vessel. (a) Steel hull vessels: (1) Rules and Regulations for the Classification of Yachts and Small Craft, Lloyd's Register of Shipping (Lloyd's); or (2) Rules for Building and Classing Steel...

Structure-activity relationships and prediction of the phototoxicity and phototoxic potential of new drugs.

PubMed

Barratt, Martin D

2004-11-01

Relationships between the structure and properties of chemicals can be programmed into knowledge-based systems such as DEREK for Windows (DEREK is an acronym for "Deductive Estimation of Risk from Existing Knowledge"). The DEREK for Windows computer system contains a subset of over 60 rules describing chemical substructures (toxophores) responsible for skin sensitisation. As part of the European Phototox Project, the rule base was supplemented by a number of rules for the prospective identification of photoallergens, either by extension of the scope of existing rules or by the generation of new rules where a sound mechanistic rationale for the biological activity could be established. The scope of the rules for photoallergenicity was then further refined by assessment against a list of chemicals identified as photosensitisers by the Centro de Farmacovigilancia de la Comunidad Valenciana, Valencia, Spain. This paper contains an analysis of the mechanistic bases of activity for eight important groups of photoallergens and phototoxins, together with rules for the prospective identification of the photobiological activity of new or untested chemicals belonging to those classes. The mechanism of action of one additional chemical, nitrofurantoin, is well established; however, it was deemed inappropriate to write a rule on the basis of a single chemical structure.

76 FR 68642 - Structure and Practices of the Video Relay Service Program

Federal Register 2010, 2011, 2012, 2013, 2014

2011-11-07

... Practices of the Video Relay Service Program AGENCY: Federal Communications Commission. ACTION: Final rule... with the Commission's Structure and Practices of the Video Relay Service Program, Memorandum Opinion... effective date of these rule sections. See, In the Matter of Structure and Practices of the Video Relay...

76 FR 68328 - Structure and Practices of the Video Relay Service Program

Federal Register 2010, 2011, 2012, 2013, 2014

2011-11-04

... Practices of the Video Relay Service Program AGENCY: Federal Communications Commission. ACTION: Final rule... with the Commission's Structure and Practices of the Video Relay Service Program, Second Report and... effective date of these rule sections. See, In the Matter of Structure and Practices of the Video Relay...

Analysis of Physicochemical and Structural Properties Determining HIV-1 Coreceptor Usage

PubMed Central

Bozek, Katarzyna; Lengauer, Thomas; Sierra, Saleta; Kaiser, Rolf; Domingues, Francisco S.

2013-01-01

The relationship of HIV tropism with disease progression and the recent development of CCR5-blocking drugs underscore the importance of monitoring virus coreceptor usage. As an alternative to costly phenotypic assays, computational methods aim at predicting virus tropism based on the sequence and structure of the V3 loop of the virus gp120 protein. Here we present a numerical descriptor of the V3 loop encoding its physicochemical and structural properties. The descriptor allows for structure-based prediction of HIV tropism and identification of properties of the V3 loop that are crucial for coreceptor usage. Use of the proposed descriptor for prediction results in a statistically significant improvement over the prediction based solely on V3 sequence with 3 percentage points improvement in AUC and 7 percentage points in sensitivity at the specificity of the 11/25 rule (95%). We additionally assessed the predictive power of the new method on clinically derived ‘bulk’ sequence data and obtained a statistically significant improvement in AUC of 3 percentage points over sequence-based prediction. Furthermore, we demonstrated the capacity of our method to predict therapy outcome by applying it to 53 samples from patients undergoing Maraviroc therapy. The analysis of structural features of the loop informative of tropism indicates the importance of two loop regions and their physicochemical properties. The regions are located on opposite strands of the loop stem and the respective features are predominantly charge-, hydrophobicity- and structure-related. These regions are in close proximity in the bound conformation of the loop potentially forming a site determinant for the coreceptor binding. The method is available via server under http://structure.bioinf.mpi-inf.mpg.de/. PMID:23555214

IRS proposed "physician recruitment" revenue ruling offers few kernels in search for.

PubMed

Reaves, C F

1995-07-01

Not to sound corny, but things have really been popping since the Internal Revenue Service (IRS) recently released a proposed revenue ruling regarding the scope of recruitment incentives that may be offered to nonemployee physician members of tax-exempt hospital medical staffs. Commentators have criticized the proposed revenue ruling, however, because it offers little in the way of guidance in all but the most obvious cases of recruitment violations. Nonetheless, the proposed ruling may provide insight that may assist hospitals to prepare permissible recruitment incentives for physicians. The IRS provided a public comment period within which individuals and groups could submit proposals to improve or revise the proposed ruling. However, with or without such comments, clarification of the ruling is called for. "Health Law" is a regular feature of Physician Executive from the Washington, D.C., law firm Epstein Becker & Green. Mark Lutes of the law firm serves as editor of the column.

The expert explorer: a tool for hospital data visualization and adverse drug event rules validation.

PubMed

Băceanu, Adrian; Atasiei, Ionuţ; Chazard, Emmanuel; Leroy, Nicolas

2009-01-01

An important part of adverse drug events (ADEs) detection is the validation of the clinical cases and the assessment of the decision rules to detect ADEs. For that purpose, a software called "Expert Explorer" has been designed by Ideea Advertising. Anonymized datasets have been extracted from hospitals into a common repository. The tool has 3 main features. (1) It can display hospital stays in a visual and comprehensive way (diagnoses, drugs, lab results, etc.) using tables and pretty charts. (2) It allows designing and executing dashboards in order to generate knowledge about ADEs. (3) It finally allows uploading decision rules obtained from data mining. Experts can then review the rules, the hospital stays that match the rules, and finally give their advice thanks to specialized forms. Then the rules can be validated, invalidated, or improved (knowledge elicitation phase).

A knowledge-based object recognition system for applications in the space station

NASA Technical Reports Server (NTRS)

Dhawan, Atam P.

1988-01-01

A knowledge-based three-dimensional (3D) object recognition system is being developed. The system uses primitive-based hierarchical relational and structural matching for the recognition of 3D objects in the two-dimensional (2D) image for interpretation of the 3D scene. At present, the pre-processing, low-level preliminary segmentation, rule-based segmentation, and the feature extraction are completed. The data structure of the primitive viewing knowledge-base (PVKB) is also completed. Algorithms and programs based on attribute-trees matching for decomposing the segmented data into valid primitives were developed. The frame-based structural and relational descriptions of some objects were created and stored in a knowledge-base. This knowledge-base of the frame-based descriptions were developed on the MICROVAX-AI microcomputer in LISP environment. The simulated 3D scene of simple non-overlapping objects as well as real camera data of images of 3D objects of low-complexity have been successfully interpreted.

The design and characterization of protein based block polymers

NASA Astrophysics Data System (ADS)

Haghpanah, Jennifer Shorah

Over the past decades, protein engineering has provided noteworthy advances in basic science as well as in medicine and industry. Protein engineers are currently focusing their efforts on developing elementary rules to design proteins with a specific structure and function. Proteins derived from natural sources have been used generate a plethora of materials with remarkable structural and functional properties. In the first chapter, we show how we can fabricate protein polymers comprised of two different self-assembling domains (SADs). From our studies, we discover that SADs in different orientations have a large impact on their overall microscopic and macroscopic features. In the second chapter, we explore the impact of cellulose (Tc) on the diblocks EC and CE. We discover that Tc is able to selectively impact the mechanical propertied of CE because CE has smaller particle sizes and more E domain exposed on its surface at RT. In the third chapter, we appended an extra C domain to CE to generate CEC with improved mechanical properties, structure and small molecule recognition.

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.

Pattern recognition and image processing for environmental monitoring

NASA Astrophysics Data System (ADS)

Siddiqui, Khalid J.; Eastwood, DeLyle

1999-12-01

Pattern recognition (PR) and signal/image processing methods are among the most powerful tools currently available for noninvasively examining spectroscopic and other chemical data for environmental monitoring. Using spectral data, these systems have found a variety of applications employing analytical techniques for chemometrics such as gas chromatography, fluorescence spectroscopy, etc. An advantage of PR approaches is that they make no a prior assumption regarding the structure of the patterns. However, a majority of these systems rely on human judgment for parameter selection and classification. A PR problem is considered as a composite of four subproblems: pattern acquisition, feature extraction, feature selection, and pattern classification. One of the basic issues in PR approaches is to determine and measure the features useful for successful classification. Selection of features that contain the most discriminatory information is important because the cost of pattern classification is directly related to the number of features used in the decision rules. The state of the spectral techniques as applied to environmental monitoring is reviewed. A spectral pattern classification system combining the above components and automatic decision-theoretic approaches for classification is developed. It is shown how such a system can be used for analysis of large data sets, warehousing, and interpretation. In a preliminary test, the classifier was used to classify synchronous UV-vis fluorescence spectra of relatively similar petroleum oils with reasonable success.

77 FR 46135 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-08-02

... Proposed Rule Change To Modify the Post-Only Order Type on NOM July 27, 2012. Pursuant to Section 19(b)(1... Proposed Rule Change NASDAQ proposes to add an additional feature to the Post-Only Order type on the NASDAQ... called Post-Only Order.\\3\\ Thereafter, the Exchange amended the order type and delayed implementation...

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

PubMed

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

2008-07-01

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

Structural difference rule for amorphous alloy formation by ion mixing

NASA Technical Reports Server (NTRS)

Liu, B.-X.; Johnson, W. L.; Nicolet, M.A.; Lau, S. S.

1983-01-01

A rule is formulated which establishes a sufficient condition that an amorphous binary alloy will be formed by ion mixing of multilayered samples when the two constituent metals are of different crystalline structure, regardless of their atomic sizes and electronegativities. The rule is supported by the experimental results obtained on six selected binary metal systems, as well as by the previous data reported in the literature. The amorphization mechanism is discussed in terms of the competition between two different structures resulting in frustration of the crystallization process.

Inorganic nanotubes and fullerenes . Structure and properties of hypothetical phosphorus fullerenes

NASA Astrophysics Data System (ADS)

Seifert, G.; Heine, T.; Fowler, P. W.

The possibility of stable non-carbon fullerenes is discussed for the case of phosphorus fullerene-like cage structures. On the basis of Density Functional Tight Binding calculations it is shown that many such cages correspond to metastable structures, but with increasing nuclearity become less stable with respect to separate molecular P4 units. Stability rules, known for carbon fullerenes, such as the ``isolated pentagon rule'', do not reflect the different electronic and steric requirements of the phosphorus atom. The computational results tend to rule out phosphorus fullerenes.

Probabilistic grammatical model for helix‐helix contact site classification

PubMed Central

2013-01-01

Background Hidden Markov Models power many state‐of‐the‐art tools in the field of protein bioinformatics. While excelling in their tasks, these methods of protein analysis do not convey directly information on medium‐ and long‐range residue‐residue interactions. This requires an expressive power of at least context‐free grammars. However, application of more powerful grammar formalisms to protein analysis has been surprisingly limited. Results In this work, we present a probabilistic grammatical framework for problem‐specific protein languages and apply it to classification of transmembrane helix‐helix pairs configurations. The core of the model consists of a probabilistic context‐free grammar, automatically inferred by a genetic algorithm from only a generic set of expert‐based rules and positive training samples. The model was applied to produce sequence based descriptors of four classes of transmembrane helix‐helix contact site configurations. The highest performance of the classifiers reached AUCROC of 0.70. The analysis of grammar parse trees revealed the ability of representing structural features of helix‐helix contact sites. Conclusions We demonstrated that our probabilistic context‐free framework for analysis of protein sequences outperforms the state of the art in the task of helix‐helix contact site classification. However, this is achieved without necessarily requiring modeling long range dependencies between interacting residues. A significant feature of our approach is that grammar rules and parse trees are human‐readable. Thus they could provide biologically meaningful information for molecular biologists. PMID:24350601

PSG-EXPERT. An expert system for the diagnosis of sleep disorders.

PubMed

Fred, A; Filipe, J; Partinen, M; Paiva, T

2000-01-01

This paper describes PSG-EXPERT, an expert system in the domain of sleep disorders exploring polysomnographic data. The developed software tool is addressed from two points of view: (1)--as an integrated environment for the development of diagnosis-oriented expert systems; (2)--as an auxiliary diagnosis tool in the particular domain of sleep disorders. Developed over a Windows platform, this software tool extends one of the most popular shells--CLIPS (C Language Integrated Production System) with the following features: backward chaining engine; graph-based explanation facilities; knowledge editor including a fuzzy fact editor and a rules editor, with facts-rules integrity checking; belief revision mechanism; built-in case generator and validation module. It therefore provides graphical support for knowledge acquisition, edition, explanation and validation. From an application domain point of view, PSG-Expert is an auxiliary diagnosis system for sleep disorders based on polysomnographic data, that aims at assisting the medical expert in his diagnosis task by providing automatic analysis of polysomnographic data, summarising the results of this analysis in terms of a report of major findings and possible diagnosis consistent with the polysomnographic data. Sleep disorders classification follows the International Classification of Sleep Disorders. Major features of the system include: browsing on patients data records; structured navigation on Sleep Disorders descriptions according to ASDA definitions; internet links to related pages; diagnosis consistent with polysomnographic data; graphical user-interface including graph-based explanatory facilities; uncertainty modelling and belief revision; production of reports; connection to remote databases.

Applications of rule-induction in the derivation of quantitative structure-activity relationships.

PubMed

A-Razzak, M; Glen, R C

1992-08-01

Recently, methods have been developed in the field of Artificial Intelligence (AI), specifically in the expert systems area using rule-induction, designed to extract rules from data. We have applied these methods to the analysis of molecular series with the objective of generating rules which are predictive and reliable. The input to rule-induction consists of a number of examples with known outcomes (a training set) and the output is a tree-structured series of rules. Unlike most other analysis methods, the results of the analysis are in the form of simple statements which can be easily interpreted. These are readily applied to new data giving both a classification and a probability of correctness. Rule-induction has been applied to in-house generated and published QSAR datasets and the methodology, application and results of these analyses are discussed. The results imply that in some cases it would be advantageous to use rule-induction as a complementary technique in addition to conventional statistical and pattern-recognition methods.

Applications of rule-induction in the derivation of quantitative structure-activity relationships

NASA Astrophysics Data System (ADS)

A-Razzak, Mohammed; Glen, Robert C.

1992-08-01

Recently, methods have been developed in the field of Artificial Intelligence (AI), specifically in the expert systems area using rule-induction, designed to extract rules from data. We have applied these methods to the analysis of molecular series with the objective of generating rules which are predictive and reliable. The input to rule-induction consists of a number of examples with known outcomes (a training set) and the output is a tree-structured series of rules. Unlike most other analysis methods, the results of the analysis are in the form of simple statements which can be easily interpreted. These are readily applied to new data giving both a classification and a probability of correctness. Rule-induction has been applied to in-house generated and published QSAR datasets and the methodology, application and results of these analyses are discussed. The results imply that in some cases it would be advantageous to use rule-induction as a complementary technique in addition to conventional statistical and pattern-recognition methods.

Machine vision based quality inspection of flat glass products

NASA Astrophysics Data System (ADS)

Zauner, G.; Schagerl, M.

2014-03-01

This application paper presents a machine vision solution for the quality inspection of flat glass products. A contact image sensor (CIS) is used to generate digital images of the glass surfaces. The presented machine vision based quality inspection at the end of the production line aims to classify five different glass defect types. The defect images are usually characterized by very little `image structure', i.e. homogeneous regions without distinct image texture. Additionally, these defect images usually consist of only a few pixels. At the same time the appearance of certain defect classes can be very diverse (e.g. water drops). We used simple state-of-the-art image features like histogram-based features (std. deviation, curtosis, skewness), geometric features (form factor/elongation, eccentricity, Hu-moments) and texture features (grey level run length matrix, co-occurrence matrix) to extract defect information. The main contribution of this work now lies in the systematic evaluation of various machine learning algorithms to identify appropriate classification approaches for this specific class of images. In this way, the following machine learning algorithms were compared: decision tree (J48), random forest, JRip rules, naive Bayes, Support Vector Machine (multi class), neural network (multilayer perceptron) and k-Nearest Neighbour. We used a representative image database of 2300 defect images and applied cross validation for evaluation purposes.

Social and physical aggression trajectories from childhood through late adolescence: Predictors of psychosocial maladjustment at age 18.

PubMed

Ehrenreich, Samuel E; Beron, Kurt J; Underwood, Marion K

2016-03-01

This research examined whether following social and physical aggression trajectories across Grades 3-12 predicted psychological maladjustment. Teachers rated participants' (n = 287, 138 boys) aggressive behavior at the end of each school year. Following the 12th grade, psychosocial outcomes were measured: rule-breaking behaviors, internalizing symptoms, and narcissistic and borderline personality features. Following the highest social aggression trajectory predicted rule-breaking behavior; the medium social aggression trajectory was not a significant predictor of any outcome. Following the highest physical aggression trajectory predicted rule-breaking, internalizing symptoms, and narcissism, whereas the medium physical aggression trajectory predicted rule-breaking and internalizing symptoms. (c) 2016 APA, all rights reserved).

Social and physical aggression trajectories from childhood through late adolescence: Predictors of psychosocial maladjustment at age 18

PubMed Central

Ehrenreich, Samuel E.; Beron, Kurt J.; Underwood, Marion K.

2016-01-01

This research examined whether following social and physical aggression trajectories across grades 3–12 predicted psychological maladjustment. Teachers rated participants’ (n=287, 138 boys) aggressive behavior at the end of each school year. Following the 12th grade, psychosocial outcomes were measured: rule-breaking behaviors, internalizing symptoms, and narcissistic and borderline personality features. Following the highest social aggression trajectory predicted rule-breaking behavior; the medium social aggression trajectory was not a significant predictor of any outcome. Following the highest physical aggression trajectory predicted rule-breaking, internalizing symptoms and narcissism, whereas the medium physical aggression trajectory predicted rule-breaking and internalizing symptoms. PMID:26891018

Devil's staircase and the absence of chaos in the dc- and ac-driven overdamped Frenkel-Kontorova model

NASA Astrophysics Data System (ADS)

Sokolović, I.; Mali, P.; Odavić, J.; Radošević, S.; Medvedeva, S. Yu.; Botha, A. E.; Shukrinov, Yu. M.; Tekić, J.

2017-08-01

The devil's staircase structure arising from the complete mode locking of an entirely nonchaotic system, the overdamped dc+ac driven Frenkel-Kontorova model with deformable substrate potential, was observed. Even though no chaos was found, a hierarchical ordering of the Shapiro steps was made possible through the use of a previously introduced continued fraction formula. The absence of chaos, deduced here from Lyapunov exponent analyses, can be attributed to the overdamped character and the Middleton no-passing rule. A comparative analysis of a one-dimensional stack of Josephson junctions confirmed the disappearance of chaos with increasing dissipation. Other common dynamic features were also identified through this comparison. A detailed analysis of the amplitude dependence of the Shapiro steps revealed that only for the case of a purely sinusoidal substrate potential did the relative sizes of the steps follow a Farey sequence. For nonsinusoidal (deformed) potentials, the symmetry of the Stern-Brocot tree, depicting all members of particular Farey sequence, was seen to be increasingly broken, with certain steps being more prominent and their relative sizes not following the Farey rule.

Machine learning-, rule- and pharmacophore-based classification on the inhibition of P-glycoprotein and NorA.

PubMed

Ngo, T-D; Tran, T-D; Le, M-T; Thai, K-M

2016-09-01

The efflux pumps P-glycoprotein (P-gp) in humans and NorA in Staphylococcus aureus are of great interest for medicinal chemists because of their important roles in multidrug resistance (MDR). The high polyspecificity as well as the unavailability of high-resolution X-ray crystal structures of these transmembrane proteins lead us to combining ligand-based approaches, which in the case of this study were machine learning, perceptual mapping and pharmacophore modelling. For P-gp inhibitory activity, individual models were developed using different machine learning algorithms and subsequently combined into an ensemble model which showed a good discrimination between inhibitors and noninhibitors (acctrain-diverse = 84%; accinternal-test = 92% and accexternal-test = 100%). For ligand promiscuity between P-gp and NorA, perceptual maps and pharmacophore models were generated for the detection of rules and features. Based on these in silico tools, hit compounds for reversing MDR were discovered from the in-house and DrugBank databases through virtual screening in an attempt to restore drug sensitivity in cancer cells and bacteria.

Ultrasonographic findings of the various diseases presenting as calf pain.

PubMed

Lee, Sun Joo; Kim, Ok Hwa; Choo, Hye Jung; Park, Jun Ho; Park, Yeong-Mi; Jeong, Hae Woong; Lee, Sung Moon; Cho, Kil Ho; Choi, Jung-Ah; Jacobson, Jon A

2016-01-01

There are various causes of calf pain. The differential diagnoses affecting the lower leg include cystic lesions, trauma-related lesions, infection or inflammation, vascular lesions, neoplasms, and miscellaneous entities. Ultrasound (US) provide detailed anatomical information of the calf structures, and it offers the ability to confirm, other calf abnormalities, particularly when deep vein thrombosis (DVT) is ruled out. The purpose of this article is to review the causes of a painful calf presenting as DVT and incidental findings found as part of the work-up of DVT, and to provide a broad overview of US findings and clinical features of these pathologies. Copyright © 2015 Elsevier Inc. All rights reserved.

Linked supramolecular building blocks for enhanced cluster formation

DOE PAGES

McLellan, Ross; Palacios, Maria A.; Beavers, Christine M.; ...

2015-01-09

Methylene-bridged calix[4]arenes have emerged as extremely versatile ligand supports in the formation of new polymetallic clusters possessing fascinating magnetic properties. Metal ion binding rules established for this building block allow one to partially rationalise the complex assembly process. The ability to covalently link calix[4]arenes at the methylene bridge provides significantly improved control over the introduction of different metal centres to resulting cluster motifs. Clusters assembled from bis-calix[4]arenes and transition metal ions or 3d-4f combinations display characteristic features of the analogous calix[4]arene supported clusters, thereby demonstrating an enhanced and rational approach towards the targeted synthesis of complex and challenging structures.

Basic sanitation policy in Brazil: discussion of a path.

PubMed

Sousa, Ana Cristina A de; Costa, Nilson do Rosário

2016-01-01

This article demonstrates that the position of dominance enjoyed by state sanitation companies dictates the public policy decision-making process for sanitation in Brazil. These companies' hegemony is explained here through the analysis of a path that generated political and economic incentives that have permitted its consolidation over time. Through the content analysis of the legislation proposed for the sector and the material produced by the stakeholders involved in the approval of new regulations for the sector in 2007, the study identifies the main sources of incentive introduced by the adoption of the National Sanitation Plan, which explain certain structural features of the current sanitation policy and its strong capacity to withstand the innovations proposed under democratic rule.

Drugs and Drug-Like Compounds: Discriminating Approved Pharmaceuticals from Screening-Library Compounds

NASA Astrophysics Data System (ADS)

Schierz, Amanda C.; King, Ross D.

Compounds in drug screening-libraries should resemble pharmaceuticals. To operationally test this, we analysed the compounds in terms of known drug-like filters and developed a novel machine learning method to discriminate approved pharmaceuticals from “drug-like” compounds. This method uses both structural features and molecular properties for discrimination. The method has an estimated accuracy of 91% in discriminating between the Maybridge HitFinder library and approved pharmaceuticals, and 99% between the NATDiverse collection (from Analyticon Discovery) and approved pharmaceuticals. These results show that Lipinski’s Rule of 5 for oral absorption is not sufficient to describe “drug-likeness” and be the main basis of screening-library design.

Automated anatomical labeling method for abdominal arteries extracted from 3D abdominal CT images

NASA Astrophysics Data System (ADS)

Oda, Masahiro; Hoang, Bui Huy; Kitasaka, Takayuki; Misawa, Kazunari; Fujiwara, Michitaka; Mori, Kensaku

2012-02-01

This paper presents an automated anatomical labeling method of abdominal arteries. In abdominal surgery, understanding of blood vessel structure concerning with a target organ is very important. Branching pattern of blood vessels differs among individuals. It is required to develop a system that can assist understanding of a blood vessel structure and anatomical names of blood vessels of a patient. Previous anatomical labbeling methods for abdominal arteries deal with either of the upper or lower abdominal arteries. In this paper, we present an automated anatomical labeling method of both of the upper and lower abdominal arteries extracted from CT images. We obtain a tree structure of artery regions and calculate feature values for each branch. These feature values include the diameter, curvature, direction, and running vectors of a branch. Target arteries of this method are grouped based on branching conditions. The following processes are separately applied for each group. We compute candidate artery names by using classifiers that are trained to output artery names. A correction process of the candidate anatomical names based on the rule of majority is applied to determine final names. We applied the proposed method to 23 cases of 3D abdominal CT images. Experimental results showed that the proposed method is able to perform nomenclature of entire major abdominal arteries. The recall and the precision rates of labeling are 79.01% and 80.41%, respectively.

Computational study of the melting-freezing transition in the quantum hard-sphere system for intermediate densities. II. Structural features.

PubMed

Sesé, Luis M; Bailey, Lorna E

2007-04-28

The structural features of the quantum hard-sphere system in the region of the fluid-face-centered-cubic-solid transition, for reduced number densities 0.45

Multifractal analysis of white matter structural changes on 3D magnetic resonance imaging between normal aging and early Alzheimer’s disease

NASA Astrophysics Data System (ADS)

Ni, Huang-Jing; Zhou, Lu-Ping; Zeng, Peng; Huang, Xiao-Lin; Liu, Hong-Xing; Ning, Xin-Bao

2015-07-01

Applications of multifractal analysis to white matter structure changes on magnetic resonance imaging (MRI) have recently received increasing attentions. Although some progresses have been made, there is no evident study on applying multifractal analysis to evaluate the white matter structural changes on MRI for Alzheimer’s disease (AD) research. In this paper, to explore multifractal analysis of white matter structural changes on 3D MRI volumes between normal aging and early AD, we not only extend the traditional box-counting multifractal analysis (BCMA) into the 3D case, but also propose a modified integer ratio based BCMA (IRBCMA) algorithm to compensate for the rigid division rule in BCMA. We verify multifractal characteristics in 3D white matter MRI volumes. In addition to the previously well studied multifractal feature, Δα, we also demonstrated Δf as an alternative and effective multifractal feature to distinguish NC from AD subjects. Both Δα and Δf are found to have strong positive correlation with the clinical MMSE scores with statistical significance. Moreover, the proposed IRBCMA can be an alternative and more accurate algorithm for 3D volume analysis. Our findings highlight the potential usefulness of multifractal analysis, which may contribute to clarify some aspects of the etiology of AD through detection of structural changes in white matter. Project supported by the National Natural Science Foundation of China (Grant No. 61271079), the Vice Chancellor Research Grant in University of Wollongong, and the Priority Academic Program Development of Jiangsu Higher Education Institutions, China.

Design of 240,000 orthogonal 25mer DNA barcode probes.

PubMed

Xu, Qikai; Schlabach, Michael R; Hannon, Gregory J; Elledge, Stephen J

2009-02-17

DNA barcodes linked to genetic features greatly facilitate screening these features in pooled formats using microarray hybridization, and new tools are needed to design large sets of barcodes to allow construction of large barcoded mammalian libraries such as shRNA libraries. Here we report a framework for designing large sets of orthogonal barcode probes. We demonstrate the utility of this framework by designing 240,000 barcode probes and testing their performance by hybridization. From the test hybridizations, we also discovered new probe design rules that significantly reduce cross-hybridization after their introduction into the framework of the algorithm. These rules should improve the performance of DNA microarray probe designs for many applications.

Design of 240,000 orthogonal 25mer DNA barcode probes

PubMed Central

Xu, Qikai; Schlabach, Michael R.; Hannon, Gregory J.; Elledge, Stephen J.

2009-01-01

DNA barcodes linked to genetic features greatly facilitate screening these features in pooled formats using microarray hybridization, and new tools are needed to design large sets of barcodes to allow construction of large barcoded mammalian libraries such as shRNA libraries. Here we report a framework for designing large sets of orthogonal barcode probes. We demonstrate the utility of this framework by designing 240,000 barcode probes and testing their performance by hybridization. From the test hybridizations, we also discovered new probe design rules that significantly reduce cross-hybridization after their introduction into the framework of the algorithm. These rules should improve the performance of DNA microarray probe designs for many applications. PMID:19171886

Compliance with railroad operating rules and corporate culture influences : results of a focus group and structured interviews

DOT National Transportation Integrated Search

1999-10-01

A focus group was held at the November 11, 1996 meeting of the Operating Rules Association of North American Railroads to discuss the general issue of compliance and operating rules. Twelve operating rules officers participated, representing Class I,...

Relaxation-type nonlocal inertial-number rheology for dry granular flows

NASA Astrophysics Data System (ADS)

Lee, Keng-lin; Yang, Fu-ling

2017-12-01

We propose a constitutive model to describe the nonlocality, hysteresis, and several flow features of dry granular materials. Taking the well-known inertial number I as a measure of sheared-induced local fluidization, we derive a relaxation model for I according to the evolution of microstructure during avalanche and dissipation processes. The model yields a nonmonotonic flow law for a homogeneous flow, accounting for hysteretic solid-fluid transition and intermittency in quasistatic flows. For an inhomogeneous flow, the model predicts a generalized Bagnold shear stress revealing the interplay of two microscopic nonlocal mechanisms: collisions among correlated structures and the diffusion of fluidization within the structures. In describing a uniform flow down an incline, the model reproduces the hysteretic starting and stopping heights and the Pouliquen flow rule for mean velocity. Moreover, a dimensionless parameter reflecting the nonlocal effect on the flow is discovered, which controls the transition between Bagnold and creeping flow dynamics.

Modelling biological invasions: species traits, species interactions, and habitat heterogeneity.

PubMed

Cannas, Sergio A; Marco, Diana E; Páez, Sergio A

2003-05-01

In this paper we explore the integration of different factors to understand, predict and control ecological invasions, through a general cellular automaton model especially developed. The model includes life history traits of several species in a modular structure interacting multiple cellular automata. We performed simulations using field values corresponding to the exotic Gleditsia triacanthos and native co-dominant trees in a montane area. Presence of G. triacanthos juvenile bank was a determinant condition for invasion success. Main parameters influencing invasion velocity were mean seed dispersal distance and minimum reproductive age. Seed production had a small influence on the invasion velocity. Velocities predicted by the model agreed well with estimations from field data. Values of population density predicted matched field values closely. The modular structure of the model, the explicit interaction between the invader and the native species, and the simplicity of parameters and transition rules are novel features of the model.

A mixing evolution model for bidirectional microblog user networks

NASA Astrophysics Data System (ADS)

Yuan, Wei-Guo; Liu, Yun

2015-08-01

Microblogs have been widely used as a new form of online social networking. Based on the user profile data collected from Sina Weibo, we find that the number of microblog user bidirectional friends approximately corresponds with the lognormal distribution. We then build two microblog user networks with real bidirectional relationships, both of which have not only small-world and scale-free but also some special properties, such as double power-law degree distribution, disassortative network, hierarchical and rich-club structure. Moreover, by detecting the community structures of the two real networks, we find both of their community scales follow an exponential distribution. Based on the empirical analysis, we present a novel evolution network model with mixed connection rules, including lognormal fitness preferential and random attachment, nearest neighbor interconnected in the same community, and global random associations in different communities. The simulation results show that our model is consistent with real network in many topology features.

Parallel functional category deficits in clauses and nominal phrases: The case of English agrammatism

PubMed Central

Wang, Honglei; Yoshida, Masaya; Thompson, Cynthia K.

2015-01-01

Individuals with agrammatic aphasia exhibit restricted patterns of impairment of functional morphemes, however, syntactic characterization of the impairment is controversial. Previous studies have focused on functional morphology in clauses only. This study extends the empirical domain by testing functional morphemes in English nominal phrases in aphasia and comparing patients’ impairment to their impairment of functional morphemes in English clauses. In the linguistics literature, it is assumed that clauses and nominal phrases are structurally parallel but exhibit inflectional differences. The results of the present study indicated that aphasic speakers evinced similar impairment patterns in clauses and nominal phrases. These findings are consistent with the Distributed Morphology Hypothesis (DMH), suggesting that the source of functional morphology deficits among agrammatics relates to difficulty implementing rules that convert inflectional features into morphemes. Our findings, however, are inconsistent with the Tree Pruning Hypothesis (TPH), which suggests that patients have difficulty building complex hierarchical structures. PMID:26379370

An expert system for the evaluation of reinforced concrete structure durability

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

Berra, M.; Bertolini, L.; Briglia, M.C.

1999-11-01

A user-friendly expert system has been developed to evaluate primarily the durability of reinforced concrete structures, either in the design phase or during service life related to reinforcement corrosion. Besides the durability module, the ES has been provided with three other expert modules in order to support the user during the following activities: inspections, corrosion diagnosis and repair strategy (of concrete and reinforcement). Corrosion induced by carbonation and chlorides penetration and caused by concrete degradation such as sulfate attack, freeze/thaw cycles, alkali silica reaction are considered. The knowledge used for the expert system is based both on open literature andmore » international standards as well as on specific experiences and proprietary databases. The paper describes main features of the system, including the modeling of the knowledge, input data, the algorithms, the rules and the outputs for each module.« less

Crystal Graph Convolutional Neural Networks for an Accurate and Interpretable Prediction of Material Properties

NASA Astrophysics Data System (ADS)

Xie, Tian; Grossman, Jeffrey C.

2018-04-01

The use of machine learning methods for accelerating the design of crystalline materials usually requires manually constructed feature vectors or complex transformation of atom coordinates to input the crystal structure, which either constrains the model to certain crystal types or makes it difficult to provide chemical insights. Here, we develop a crystal graph convolutional neural networks framework to directly learn material properties from the connection of atoms in the crystal, providing a universal and interpretable representation of crystalline materials. Our method provides a highly accurate prediction of density functional theory calculated properties for eight different properties of crystals with various structure types and compositions after being trained with 1 04 data points. Further, our framework is interpretable because one can extract the contributions from local chemical environments to global properties. Using an example of perovskites, we show how this information can be utilized to discover empirical rules for materials design.

76 FR 68116 - Structure and Practices of the Video Relay Service Program

Federal Register 2010, 2011, 2012, 2013, 2014

2011-11-03

... Practices of the Video Relay Service Program AGENCY: Federal Communications Commission. ACTION: Interim rule... with the Commission's Structure and Practices of the Video Relay Service Program, Second Report and... announcement of the effective date of the rules. See, In the Matter of Structure and Practices of the Video...

The P600 in Implicit Artificial Grammar Learning.

PubMed

Silva, Susana; Folia, Vasiliki; Hagoort, Peter; Petersson, Karl Magnus

2017-01-01

The suitability of the artificial grammar learning (AGL) paradigm to capture relevant aspects of the acquisition of linguistic structures has been empirically tested in a number of EEG studies. Some have shown a syntax-related P600 component, but it has not been ruled out that the AGL P600 effect is a response to surface features (e.g., subsequence familiarity) rather than the underlying syntax structure. Therefore, in this study, we controlled for the surface characteristics of the test sequences (associative chunk strength) and recorded the EEG before (baseline preference classification) and after (preference and grammaticality classification) exposure to a grammar. After exposure, a typical, centroparietal P600 effect was elicited by grammatical violations and not by unfamiliar subsequences, suggesting that the AGL P600 effect signals a response to structural irregularities. Moreover, preference and grammaticality classification showed a qualitatively similar ERP profile, strengthening the idea that the implicit structural mere-exposure paradigm in combination with preference classification is a suitable alternative to the traditional grammaticality classification test. Copyright © 2016 Cognitive Science Society, Inc.

Exploring space-time structure of human mobility in urban space

NASA Astrophysics Data System (ADS)

Sun, J. B.; Yuan, J.; Wang, Y.; Si, H. B.; Shan, X. M.

2011-03-01

Understanding of human mobility in urban space benefits the planning and provision of municipal facilities and services. Due to the high penetration of cell phones, mobile cellular networks provide information for urban dynamics with a large spatial extent and continuous temporal coverage in comparison with traditional approaches. The original data investigated in this paper were collected by cellular networks in a southern city of China, recording the population distribution by dividing the city into thousands of pixels. The space-time structure of urban dynamics is explored by applying Principal Component Analysis (PCA) to the original data, from temporal and spatial perspectives between which there is a dual relation. Based on the results of the analysis, we have discovered four underlying rules of urban dynamics: low intrinsic dimensionality, three categories of common patterns, dominance of periodic trends, and temporal stability. It implies that the space-time structure can be captured well by remarkably few temporal or spatial predictable periodic patterns, and the structure unearthed by PCA evolves stably over time. All these features play a critical role in the applications of forecasting and anomaly detection.

Computationally assisted screening and design of cell-interactive peptides by a cell-based assay using peptide arrays and a fuzzy neural network algorithm.

PubMed

Kaga, Chiaki; Okochi, Mina; Tomita, Yasuyuki; Kato, Ryuji; Honda, Hiroyuki

2008-03-01

We developed a method of effective peptide screening that combines experiments and computational analysis. The method is based on the concept that screening efficiency can be enhanced from even limited data by use of a model derived from computational analysis that serves as a guide to screening and combining the model with subsequent repeated experiments. Here we focus on cell-adhesion peptides as a model application of this peptide-screening strategy. Cell-adhesion peptides were screened by use of a cell-based assay of a peptide array. Starting with the screening data obtained from a limited, random 5-mer library (643 sequences), a rule regarding structural characteristics of cell-adhesion peptides was extracted by fuzzy neural network (FNN) analysis. According to this rule, peptides with unfavored residues in certain positions that led to inefficient binding were eliminated from the random sequences. In the restricted, second random library (273 sequences), the yield of cell-adhesion peptides having an adhesion rate more than 1.5-fold to that of the basal array support was significantly high (31%) compared with the unrestricted random library (20%). In the restricted third library (50 sequences), the yield of cell-adhesion peptides increased to 84%. We conclude that a repeated cycle of experiments screening limited numbers of peptides can be assisted by the rule-extracting feature of FNN.

Search asymmetries: parallel processing of uncertain sensory information.

PubMed

Vincent, Benjamin T

2011-08-01

What is the mechanism underlying search phenomena such as search asymmetry? Two-stage models such as Feature Integration Theory and Guided Search propose parallel pre-attentive processing followed by serial post-attentive processing. They claim search asymmetry effects are indicative of finding pairs of features, one processed in parallel, the other in serial. An alternative proposal is that a 1-stage parallel process is responsible, and search asymmetries occur when one stimulus has greater internal uncertainty associated with it than another. While the latter account is simpler, only a few studies have set out to empirically test its quantitative predictions, and many researchers still subscribe to the 2-stage account. This paper examines three separate parallel models (Bayesian optimal observer, max rule, and a heuristic decision rule). All three parallel models can account for search asymmetry effects and I conclude that either people can optimally utilise the uncertain sensory data available to them, or are able to select heuristic decision rules which approximate optimal performance. Copyright © 2011 Elsevier Ltd. All rights reserved.

Brick and Structural Clay Products: National Emission Standards for Hazardous Air Pollutants (NESHAP)

EPA Pesticide Factsheets

Learn about the NESHAP regulation for brick and structural clay products by reading the rule summary, rule history, code of federal regulations, and the additional resources like fact sheets and background information documents

The Precise and Efficient Identification of Medical Order Forms Using Shape Trees

NASA Astrophysics Data System (ADS)

Henker, Uwe; Petersohn, Uwe; Ultsch, Alfred

A powerful and flexible technique to identify, classify and process documents using images from a scanning process is presented. The types of documents can be described to the system as a set of differentiating features in a case base using shape trees. The features are filtered and abstracted from an extremely reduced scanner image of the document. Classification rules are stored with the cases to enable precise recognition and further mark reading and Optical Character Recognition (OCR) process. The method is implemented in a system which actually processes the majority of requests for medical lab procedures in Germany. A large practical experiment with data from practitioners was performed. An average of 97% of the forms were correctly identified; none were identified incorrectly. This meets the quality requirements for most medical applications. The modular description of the recognition process allows for a flexible adaptation of future changes to the form and content of the document’s structures.

Plasmonic spectral tunability of conductive ternary nitrides

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

Kassavetis, S.; Patsalas, P., E-mail: ppats@physics.auth.gr; Bellas, D. V.

2016-06-27

Conductive binary transition metal nitrides, such as TiN and ZrN, have emerged as a category of promising alternative plasmonic materials. In this work, we show that ternary transition metal nitrides such as Ti{sub x}Ta{sub 1−x}N, Ti{sub x}Zr{sub 1−x}N, Ti{sub x}Al{sub 1−x}N, and Zr{sub x}Ta{sub 1−x}N share the important plasmonic features with their binary counterparts, while having the additional asset of the exceptional spectral tunability in the entire visible (400–700 nm) and UVA (315–400 nm) spectral ranges depending on their net valence electrons. In particular, we demonstrate that such ternary nitrides can exhibit maximum field enhancement factors comparable with gold in the aforementionedmore » broadband range. We also critically evaluate the structural features that affect the quality factor of the plasmon resonance and we provide rules of thumb for the selection and growth of materials for nitride plasmonics.« less

Characteristics of sports-based youth development programs.

PubMed

Perkins, Daniel F; Noam, Gil G

2007-01-01

The term "sports-based youth development programs" is coined and defined in the context of the community youth development framework. Sports-based youth development programs are out-of-school-time programs that use a particular sport to facilitate learning and life skill development in youth. Community youth development programs use a community youth development approach to create opportunities for youth to connect to others, develop skills, and use those skills to contribute to their communities. This, in turn, increases their ability to succeed. The authors describe how sports-based youth development programs can be contexts that promote positive youth development. The features of positive developmental settings for youth from the work of the National Research Council and the Institute of Medicine, as well as the features identified by other researchers, are presented in the context of sports-based youth development programs. For example, a sports program that provides appropriate structure has delineated clear rules, expectations, and responsibilities for youth, parents, coaches, officials, and other organizers.

Mixing Languages during Learning? Testing the One Subject-One Language Rule.

PubMed

Antón, Eneko; Thierry, Guillaume; Duñabeitia, Jon Andoni

2015-01-01

In bilingual communities, mixing languages is avoided in formal schooling: even if two languages are used on a daily basis for teaching, only one language is used to teach each given academic subject. This tenet known as the one subject-one language rule avoids mixing languages in formal schooling because it may hinder learning. The aim of this study was to test the scientific ground of this assumption by investigating the consequences of acquiring new concepts using a method in which two languages are mixed as compared to a purely monolingual method. Native balanced bilingual speakers of Basque and Spanish-adults (Experiment 1) and children (Experiment 2)-learnt new concepts by associating two different features to novel objects. Half of the participants completed the learning process in a multilingual context (one feature was described in Basque and the other one in Spanish); while the other half completed the learning phase in a purely monolingual context (both features were described in Spanish). Different measures of learning were taken, as well as direct and indirect indicators of concept consolidation. We found no evidence in favor of the non-mixing method when comparing the results of two groups in either experiment, and thus failed to give scientific support for the educational premise of the one subject-one language rule.

Mixing Languages during Learning? Testing the One Subject—One Language Rule

PubMed Central

2015-01-01

In bilingual communities, mixing languages is avoided in formal schooling: even if two languages are used on a daily basis for teaching, only one language is used to teach each given academic subject. This tenet known as the one subject-one language rule avoids mixing languages in formal schooling because it may hinder learning. The aim of this study was to test the scientific ground of this assumption by investigating the consequences of acquiring new concepts using a method in which two languages are mixed as compared to a purely monolingual method. Native balanced bilingual speakers of Basque and Spanish—adults (Experiment 1) and children (Experiment 2)—learnt new concepts by associating two different features to novel objects. Half of the participants completed the learning process in a multilingual context (one feature was described in Basque and the other one in Spanish); while the other half completed the learning phase in a purely monolingual context (both features were described in Spanish). Different measures of learning were taken, as well as direct and indirect indicators of concept consolidation. We found no evidence in favor of the non-mixing method when comparing the results of two groups in either experiment, and thus failed to give scientific support for the educational premise of the one subject—one language rule. PMID:26107624

Adaptive structured dictionary learning for image fusion based on group-sparse-representation

NASA Astrophysics Data System (ADS)

Yang, Jiajie; Sun, Bin; Luo, Chengwei; Wu, Yuzhong; Xu, Limei

2018-04-01

Dictionary learning is the key process of sparse representation which is one of the most widely used image representation theories in image fusion. The existing dictionary learning method does not use the group structure information and the sparse coefficients well. In this paper, we propose a new adaptive structured dictionary learning algorithm and a l1-norm maximum fusion rule that innovatively utilizes grouped sparse coefficients to merge the images. In the dictionary learning algorithm, we do not need prior knowledge about any group structure of the dictionary. By using the characteristics of the dictionary in expressing the signal, our algorithm can automatically find the desired potential structure information that hidden in the dictionary. The fusion rule takes the physical meaning of the group structure dictionary, and makes activity-level judgement on the structure information when the images are being merged. Therefore, the fused image can retain more significant information. Comparisons have been made with several state-of-the-art dictionary learning methods and fusion rules. The experimental results demonstrate that, the dictionary learning algorithm and the fusion rule both outperform others in terms of several objective evaluation metrics.

Predicting the risk of malignancy in adnexal masses based on the Simple Rules from the International Ovarian Tumor Analysis group.

PubMed

Timmerman, Dirk; Van Calster, Ben; Testa, Antonia; Savelli, Luca; Fischerova, Daniela; Froyman, Wouter; Wynants, Laure; Van Holsbeke, Caroline; Epstein, Elisabeth; Franchi, Dorella; Kaijser, Jeroen; Czekierdowski, Artur; Guerriero, Stefano; Fruscio, Robert; Leone, Francesco P G; Rossi, Alberto; Landolfo, Chiara; Vergote, Ignace; Bourne, Tom; Valentin, Lil

2016-04-01

Accurate methods to preoperatively characterize adnexal tumors are pivotal for optimal patient management. A recent metaanalysis concluded that the International Ovarian Tumor Analysis algorithms such as the Simple Rules are the best approaches to preoperatively classify adnexal masses as benign or malignant. We sought to develop and validate a model to predict the risk of malignancy in adnexal masses using the ultrasound features in the Simple Rules. This was an international cross-sectional cohort study involving 22 oncology centers, referral centers for ultrasonography, and general hospitals. We included consecutive patients with an adnexal tumor who underwent a standardized transvaginal ultrasound examination and were selected for surgery. Data on 5020 patients were recorded in 3 phases from 2002 through 2012. The 5 Simple Rules features indicative of a benign tumor (B-features) and the 5 features indicative of malignancy (M-features) are based on the presence of ascites, tumor morphology, and degree of vascularity at ultrasonography. Gold standard was the histopathologic diagnosis of the adnexal mass (pathologist blinded to ultrasound findings). Logistic regression analysis was used to estimate the risk of malignancy based on the 10 ultrasound features and type of center. The diagnostic performance was evaluated by area under the receiver operating characteristic curve, sensitivity, specificity, positive likelihood ratio (LR+), negative likelihood ratio (LR-), positive predictive value (PPV), negative predictive value (NPV), and calibration curves. Data on 4848 patients were analyzed. The malignancy rate was 43% (1402/3263) in oncology centers and 17% (263/1585) in other centers. The area under the receiver operating characteristic curve on validation data was very similar in oncology centers (0.917; 95% confidence interval, 0.901-0.931) and other centers (0.916; 95% confidence interval, 0.873-0.945). Risk estimates showed good calibration. In all, 23% of patients in the validation data set had a very low estimated risk (<1%) and 48% had a high estimated risk (≥30%). For the 1% risk cutoff, sensitivity was 99.7%, specificity 33.7%, LR+ 1.5, LR- 0.010, PPV 44.8%, and NPV 98.9%. For the 30% risk cutoff, sensitivity was 89.0%, specificity 84.7%, LR+ 5.8, LR- 0.13, PPV 75.4%, and NPV 93.9%. Quantification of the risk of malignancy based on the Simple Rules has good diagnostic performance both in oncology centers and other centers. A simple classification based on these risk estimates may form the basis of a clinical management system. Patients with a high risk may benefit from surgery by a gynecological oncologist, while patients with a lower risk may be managed locally. Copyright © 2016 Elsevier Inc. All rights reserved.

Construction of a Phonotactic Dialect Corpus using Semiautomatic Annotation

DTIC Science & Technology

2007-01-01

phonological or phonetic feature is speaker specific or commonly found in that speaker’s dialect. Historically, the sociolinguistic study of dialect...variation in speech has been limited to small-scale population studies , usually conducted through sociolinguistic interviews [1]. Dialect analysis of... study , we created a superset of rules 943 derived from phenomena described in the sociolinguistic literature [8][9][10][11]. Rule Example ROI [r]->0

Supervised Learning in CINets

DTIC Science & Technology

2011-07-01

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

78 FR 1889 - Self-Regulatory Organizations; C2 Options Exchange, Incorporated; Notice of Filing and Immediate...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-01-09

... Rule Change, as Modified by Amendment No. 1 Thereto, To Adopt a HAL System January 3, 2013. Pursuant to... Substance of the Proposed Rule Change The Exchange proposes to adopt a HAL system. The text of the proposed... the operation of its new HAL system (``HAL''). HAL is a feature within the C2 System that provides...

Phonological reduplication in sign language: Rules rule

PubMed Central

Berent, Iris; Dupuis, Amanda; Brentari, Diane

2014-01-01

Productivity—the hallmark of linguistic competence—is typically attributed to algebraic rules that support broad generalizations. Past research on spoken language has documented such generalizations in both adults and infants. But whether algebraic rules form part of the linguistic competence of signers remains unknown. To address this question, here we gauge the generalization afforded by American Sign Language (ASL). As a case study, we examine reduplication (X→XX)—a rule that, inter alia, generates ASL nouns from verbs. If signers encode this rule, then they should freely extend it to novel syllables, including ones with features that are unattested in ASL. And since reduplicated disyllables are preferred in ASL, such a rule should favor novel reduplicated signs. Novel reduplicated signs should thus be preferred to nonreduplicative controls (in rating), and consequently, such stimuli should also be harder to classify as nonsigns (in the lexical decision task). The results of four experiments support this prediction. These findings suggest that the phonological knowledge of signers includes powerful algebraic rules. The convergence between these conclusions and previous evidence for phonological rules in spoken language suggests that the architecture of the phonological mind is partly amodal. PMID:24959158

Incidental Learning of Melodic Structure of North Indian Music.

PubMed

Rohrmeier, Martin; Widdess, Richard

2017-07-01

Musical knowledge is largely implicit. It is acquired without awareness of its complex rules, through interaction with a large number of samples during musical enculturation. Whereas several studies explored implicit learning of mostly abstract and less ecologically valid features of Western music, very little work has been done with respect to ecologically valid stimuli as well as non-Western music. The present study investigated implicit learning of modal melodic features in North Indian classical music in a realistic and ecologically valid way. It employed a cross-grammar design, using melodic materials from two modes (rāgas) that use the same scale. Findings indicated that Western participants unfamiliar with Indian music incidentally learned to identify distinctive features of each mode. Confidence ratings suggest that participants' performance was consistently correlated with confidence, indicating that they became aware of whether they were right in their responses; that is, they possessed explicit judgment knowledge. Altogether our findings show incidental learning in a realistic ecologically valid context during only a very short exposure, they provide evidence that incidental learning constitutes a powerful mechanism that plays a fundamental role in musical acquisition. Copyright © 2016 Cognitive Science Society, Inc.

Assessing the effects of management on forest growth across France: insights from a new functional-structural model.

PubMed

Guillemot, Joannès; Delpierre, Nicolas; Vallet, Patrick; François, Christophe; Martin-StPaul, Nicolas K; Soudani, Kamel; Nicolas, Manuel; Badeau, Vincent; Dufrêne, Eric

2014-09-01

The structure of a forest stand, i.e. the distribution of tree size features, has strong effects on its functioning. The management of the structure is therefore an important tool in mitigating the impact of predicted changes in climate on forests, especially with respect to drought. Here, a new functional-structural model is presented and is used to assess the effects of management on forest functioning at a national scale. The stand process-based model (PBM) CASTANEA was coupled to a stand structure module (SSM) based on empirical tree-to-tree competition rules. The calibration of the SSM was based on a thorough analysis of intersite and interannual variability of competition asymmetry. The coupled CASTANEA-SSM model was evaluated across France using forest inventory data, and used to compare the effect of contrasted silvicultural practices on simulated stand carbon fluxes and growth. The asymmetry of competition varied consistently with stand productivity at both spatial and temporal scales. The modelling of the competition rules enabled efficient prediction of changes in stand structure within the CASTANEA PBM. The coupled model predicted an increase in net primary productivity (NPP) with management intensity, resulting in higher growth. This positive effect of management was found to vary at a national scale across France: the highest increases in NPP were attained in forests facing moderate to high water stress; however, the absolute effect of management on simulated stand growth remained moderate to low because stand thinning involved changes in carbon allocation at the tree scale. This modelling approach helps to identify the areas where management efforts should be concentrated in order to mitigate near-future drought impact on national forest productivity. Around a quarter of the French temperate oak and beech forests are currently in zones of high vulnerability, where management could thus mitigate the influence of climate change on forest yield.

Double Linear Damage Rule for Fatigue Analysis

NASA Technical Reports Server (NTRS)

Halford, G.; Manson, S.

1985-01-01

Double Linear Damage Rule (DLDR) method for use by structural designers to determine fatigue-crack-initiation life when structure subjected to unsteady, variable-amplitude cyclic loadings. Method calculates in advance of service how many loading cycles imposed on structural component before macroscopic crack initiates. Approach eventually used in design of high performance systems and incorporated into design handbooks and codes.

A cluster version of the GGT sum rule

NASA Astrophysics Data System (ADS)

Hencken, Kai; Baur, Gerhard; Trautmann, Dirk

2004-03-01

We discuss the derivation of a "cluster sum rule" from the Gellmann-Goldberger-Thirring (GGT) sum rule as an alternative to the Thomas-Reiche-Kuhn (TRK) sum rule, which was used as the basis up to now. We compare differences in the assumptions and approximations. Some applications of the sum rule for halo nuclei, as well as, nuclei with a pronounced cluster structure are discussed.

Ocular Aberrations Across the Visual Field During Accommodation

NASA Astrophysics Data System (ADS)

Liu, Tao

Myopia is classically defined as a mismatch between the optical power of the relaxed eye and its dioptric length. This definition is entirely foveocentric without concern for the contributions of peripheral refractive errors to myopia development. Long periods of steady near-work was considered to cause myopia development due to inadequate accommodation. Consequently, not only the on-axis optical features but also off-axis ones should be probed to gain insight about myopia progression. Moreover, these features need to be understood not only for the relaxed eye, but also for the accommodating eye. To acquire complete data set, a custom-built Indiana Scanning Aberrometer for Wavefront (I SAW) was developed to measure wavefront aberration along 37 line-of-sights at 8 different accommodation states in the central 30 degree visual field. We found that ocular refractive state changed uniformly over the central visual field as the eye accommodates up to 6D, and the accuracy of accommodation across the central visual field is similar to that measured in the fovea. No systematic difference between emmetropic and myopic eyes was evident. Then, a linear vector-summation rule for axial and oblique astigmatism was found to account for their interaction over the central visual field. Using this combination rule, our experimental evidence revealed no systematic effect of accommodation on axial or oblique astigmatism for two adult populations. The axial and oblique astigmatism of the whole eye is less than for the cornea alone, indicating a compensatory role for internal optics at all accommodative states. This compensation mechanism was further validated theoretically with schematic eye model. Lastly, we developed a hybrid method yielding customized eye models that accurately reproduce the empirical measurements and reasonably represent the anatomical structure, thus providing a mechanistic explanation for the changes in the eye's aberration structure that occur over the central visual field during accommodation.

Multiple-rule bias in the comparison of classification rules

PubMed Central

Yousefi, Mohammadmahdi R.; Hua, Jianping; Dougherty, Edward R.

2011-01-01

Motivation: There is growing discussion in the bioinformatics community concerning overoptimism of reported results. Two approaches contributing to overoptimism in classification are (i) the reporting of results on datasets for which a proposed classification rule performs well and (ii) the comparison of multiple classification rules on a single dataset that purports to show the advantage of a certain rule. Results: This article provides a careful probabilistic analysis of the second issue and the ‘multiple-rule bias’, resulting from choosing a classification rule having minimum estimated error on the dataset. It quantifies this bias corresponding to estimating the expected true error of the classification rule possessing minimum estimated error and it characterizes the bias from estimating the true comparative advantage of the chosen classification rule relative to the others by the estimated comparative advantage on the dataset. The analysis is applied to both synthetic and real data using a number of classification rules and error estimators. Availability: We have implemented in C code the synthetic data distribution model, classification rules, feature selection routines and error estimation methods. The code for multiple-rule analysis is implemented in MATLAB. The source code is available at http://gsp.tamu.edu/Publications/supplementary/yousefi11a/. Supplementary simulation results are also included. Contact: edward@ece.tamu.edu Supplementary Information: Supplementary data are available at Bioinformatics online. PMID:21546390

Computer based interpretation of infrared spectra-structure of the knowledge-base, automatic rule generation and interpretation

NASA Astrophysics Data System (ADS)

Ehrentreich, F.; Dietze, U.; Meyer, U.; Abbas, S.; Schulz, H.

1995-04-01

It is a main task within the SpecInfo-Project to develop interpretation tools that can handle a great deal more of the complicated, more specific spectrum-structure-correlations. In the first step the empirical knowledge about the assignment of structural groups and their characteristic IR-bands has been collected from literature and represented in a computer readable well-structured form. Vague, verbal rules are managed by introduction of linguistic variables. The next step was the development of automatic rule generating procedures. We had combined and enlarged the IDIOTS algorithm with the algorithm by Blaffert relying on set theory. The procedures were successfully applied to the SpecInfo database. The realization of the preceding items is a prerequisite for the improvement of the computerized structure elucidation procedure.

77 FR 37722 - Self-Regulatory Organizations; International Securities Exchange, LLC; Notice of Filing and...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-06-22

... Rule Change To Eliminate the Rules and Fees Related to the Second Market June 18, 2012. Pursuant to... Statement of the Terms of Substance of the Proposed Rule Change The Exchange proposes to eliminate the rules... Second Market. Accordingly, ISE proposes to eliminate the Second Market structure altogether and...

When more is less: Feedback effects in perceptual category learning ☆

PubMed Central

Maddox, W. Todd; Love, Bradley C.; Glass, Brian D.; Filoteo, J. Vincent

2008-01-01

Rule-based and information-integration category learning were compared under minimal and full feedback conditions. Rule-based category structures are those for which the optimal rule is verbalizable. Information-integration category structures are those for which the optimal rule is not verbalizable. With minimal feedback subjects are told whether their response was correct or incorrect, but are not informed of the correct category assignment. With full feedback subjects are informed of the correctness of their response and are also informed of the correct category assignment. An examination of the distinct neural circuits that subserve rule-based and information-integration category learning leads to the counterintuitive prediction that full feedback should facilitate rule-based learning but should also hinder information-integration learning. This prediction was supported in the experiment reported below. The implications of these results for theories of learning are discussed. PMID:18455155

Computing multiple aggregation levels and contextual features for road facilities recognition using mobile laser scanning data

NASA Astrophysics Data System (ADS)

Yang, Bisheng; Dong, Zhen; Liu, Yuan; Liang, Fuxun; Wang, Yongjun

2017-04-01

In recent years, updating the inventory of road infrastructures based on field work is labor intensive, time consuming, and costly. Fortunately, vehicle-based mobile laser scanning (MLS) systems provide an efficient solution to rapidly capture three-dimensional (3D) point clouds of road environments with high flexibility and precision. However, robust recognition of road facilities from huge volumes of 3D point clouds is still a challenging issue because of complicated and incomplete structures, occlusions and varied point densities. Most existing methods utilize point or object based features to recognize object candidates, and can only extract limited types of objects with a relatively low recognition rate, especially for incomplete and small objects. To overcome these drawbacks, this paper proposes a semantic labeling framework by combing multiple aggregation levels (point-segment-object) of features and contextual features to recognize road facilities, such as road surfaces, road boundaries, buildings, guardrails, street lamps, traffic signs, roadside-trees, power lines, and cars, for highway infrastructure inventory. The proposed method first identifies ground and non-ground points, and extracts road surfaces facilities from ground points. Non-ground points are segmented into individual candidate objects based on the proposed multi-rule region growing method. Then, the multiple aggregation levels of features and the contextual features (relative positions, relative directions, and spatial patterns) associated with each candidate object are calculated and fed into a SVM classifier to label the corresponding candidate object. The recognition performance of combining multiple aggregation levels and contextual features was compared with single level (point, segment, or object) based features using large-scale highway scene point clouds. Comparative studies demonstrated that the proposed semantic labeling framework significantly improves road facilities recognition precision (90.6%) and recall (91.2%), particularly for incomplete and small objects.

Resource-Bounded Information Acquisition and Learning

DTIC Science & Technology

2012-05-01

candidate features arrive one at a time, and the learner’s task is to select a ‘best so far’ set of features from streaming features. Krause et al...on Artificial Intelligence. [31] Gatterbauer, Wolfgang . Estimating required recall for successful knowledge acquisition from the web. In Proceedings of...the 15th international conference on World Wide Web (New York, NY, USA, 2006), WWW ’06, ACM, pp. 969– 970. [32] Gatterbauer, Wolfgang . Rules of thumb

Self-Similarity of Plasmon Edge Modes on Koch Fractal Antennas.

PubMed

Bellido, Edson P; Bernasconi, Gabriel D; Rossouw, David; Butet, Jérémy; Martin, Olivier J F; Botton, Gianluigi A

2017-11-28

We investigate the plasmonic behavior of Koch snowflake fractal geometries and their possible application as broadband optical antennas. Lithographically defined planar silver Koch fractal antennas were fabricated and characterized with high spatial and spectral resolution using electron energy loss spectroscopy. The experimental data are supported by numerical calculations carried out with a surface integral equation method. Multiple surface plasmon edge modes supported by the fractal structures have been imaged and analyzed. Furthermore, by isolating and reproducing self-similar features in long silver strip antennas, the edge modes present in the Koch snowflake fractals are identified. We demonstrate that the fractal response can be obtained by the sum of basic self-similar segments called characteristic edge units. Interestingly, the plasmon edge modes follow a fractal-scaling rule that depends on these self-similar segments formed in the structure after a fractal iteration. As the size of a fractal structure is reduced, coupling of the modes in the characteristic edge units becomes relevant, and the symmetry of the fractal affects the formation of hybrid modes. This analysis can be utilized not only to understand the edge modes in other planar structures but also in the design and fabrication of fractal structures for nanophotonic applications.

A machine learning heuristic to identify biologically relevant and minimal biomarker panels from omics data

PubMed Central

2015-01-01

Background Investigations into novel biomarkers using omics techniques generate large amounts of data. Due to their size and numbers of attributes, these data are suitable for analysis with machine learning methods. A key component of typical machine learning pipelines for omics data is feature selection, which is used to reduce the raw high-dimensional data into a tractable number of features. Feature selection needs to balance the objective of using as few features as possible, while maintaining high predictive power. This balance is crucial when the goal of data analysis is the identification of highly accurate but small panels of biomarkers with potential clinical utility. In this paper we propose a heuristic for the selection of very small feature subsets, via an iterative feature elimination process that is guided by rule-based machine learning, called RGIFE (Rule-guided Iterative Feature Elimination). We use this heuristic to identify putative biomarkers of osteoarthritis (OA), articular cartilage degradation and synovial inflammation, using both proteomic and transcriptomic datasets. Results and discussion Our RGIFE heuristic increased the classification accuracies achieved for all datasets when no feature selection is used, and performed well in a comparison with other feature selection methods. Using this method the datasets were reduced to a smaller number of genes or proteins, including those known to be relevant to OA, cartilage degradation and joint inflammation. The results have shown the RGIFE feature reduction method to be suitable for analysing both proteomic and transcriptomics data. Methods that generate large ‘omics’ datasets are increasingly being used in the area of rheumatology. Conclusions Feature reduction methods are advantageous for the analysis of omics data in the field of rheumatology, as the applications of such techniques are likely to result in improvements in diagnosis, treatment and drug discovery. PMID:25923811

LLWnotes - Volume 11, Number 3

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

NONE

1996-04-01

This document is the April 1996 issue of LLWnotes. It contains articles and news items on the following topics: news items related to states and compacts, Low-Level Radioactive Waste (LLW) Forum activities, and court rulings and calendars. State and compact items featured include Texas licensing procedures, renewal of Envirocare`s license, and Ward Valley. Massachusetts Board suspension of some siting tasks and Massachusetts Court rules for US DOE regarding rebates are also reported.

Indexation Rules for Metallurgy in PASCAL. Original Title: Regles d'Indexation de la Metallurgie'--Technical Note Issued by Informascience--January 1980. Translated by Marie Wallin.

ERIC Educational Resources Information Center

Royal Inst. of Tech., Stockholm (Sweden). Library.

The indexing rules presented are designed for use with a new French-German database on metallurgy being developed under an agreement by CNRS (Centre National de la Recherche Scientifique, Paris) and BAM (Bundesanstalt fur Materialprufung, Berlin). The new database, which will feature multilingual titles and index terms (French-German-English-) and…

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

PubMed Central

Batal, Iyad; Cooper, Gregory; Hauskrecht, Milos

2015-01-01

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

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

PubMed

Batal, Iyad; Cooper, Gregory; Hauskrecht, Milos

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

The Eighteen-Electron Rule

ERIC Educational Resources Information Center

Mitchell, P. R.; Parish, R. V.

1969-01-01

Discusses the stability of the structures of transition metal complexes (primarily carbonyls and organometallic compounds) having 18 electrons or less in their valence shell. Presents molecular orbital diagrams for various structures involving alpha and pi bonding and describes the conditions under which the 18 electron rule applies. (RR)

An overview of bipolar qualitative decision rules

NASA Astrophysics Data System (ADS)

Bonnefon, Jean-Francois; Dubois, Didier; Fargier, Hélène

Making a good decision is often a matter of listing and comparing positive and negative arguments, as studies in cognitive psychology have shown. In such cases, the evaluation scale should be considered bipolar, that is, negative and positive values are explicitly distinguished. Generally, positive and negative features are evaluated separately, as done in Cumulative Prospect Theory. However, contrary to the latter framework that presupposes genuine numerical assessments, decisions are often made on the basis of an ordinal ranking of the pros and the cons, and focusing on the most salient features, i.e., the decision process is qualitative. In this paper, we report on a project aiming at characterizing several decision rules, based on possibilistic order of magnitude reasoning, and tailored for the joint handling of positive and negative affects, and at testing their empirical validity. The simplest rules can be viewed as extensions of the maximin and maximax criteria to the bipolar case and, like them, suffer from a lack of discrimination power. More decisive rules that refine them are also proposed. They account for both the principle of Pareto-efficiency and the notion of order of magnitude reasoning. The most decisive one uses a lexicographic ranking of the pros and cons. It comes down to a special case of Cumulative Prospect Theory, and subsumes the “Take the best” heuristic.

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.

On structuring the rules of a fuzzy controller

NASA Technical Reports Server (NTRS)

Zhou, Jun; Raju, G. V. S.

1993-01-01

Since the pioneering work of Zadeh and Mamdani and Assilian, fuzzy logic control has emerged as one of the most active and fruitful research areas. The applications of fuzzy logic control can be found in many fields such as control of stream generators, automatic train operation systems, elevator control, nuclear reactor control, automobile transmission control, etc. In this paper, two new structures of hierarchical fuzzy rule-based controller are proposed to reduce the number of rules in a complete rule set of a controller. In one approach, the overall system is split into sub-systems which are treated independently in parallel. A coordinator is then used to take into account the interactions. This is done via an iterating information exchange between the lower level and the coordinator level. From the point of view of information used, this structure is very similar to central structure in that the coordinator can have at least in principle, all the information that the local controllers have.

Inhibition of amyloid oligomerization into different supramolecular architectures by small molecules: mechanistic insights and design rules.

PubMed

Brahmachari, Sayanti; Paul, Ashim; Segal, Daniel; Gazit, Ehud

2017-05-01

Protein misfolding and aggregation have been associated with several human disorders, including Alzheimer's, Parkinson's and Huntington's diseases, as well as senile systemic amyloidosis and Type II diabetes. However, there is no current disease-modifying therapy available for the treatment of these disorders. In spite of extensive academic, pharmaceutical, medicinal and clinical research, a complete mechanistic model for this family of diseases is still lacking. In this review, we primarily discuss the different types of small molecular entities which have been used for the inhibition of the aggregation process of different amyloidogenic proteins under diseased conditions. These include small peptides, polyphenols, inositols, quinones and their derivatives, and metal chelator molecules. In recent years, these groups of molecules have been extensively studied using in vitro, in vivo and computational models to understand their mechanism of action and common structural features underlying the process of inhibition. A salient feature found to be instrumental in the process of inhibition is the balance between the aromatic unit that functions as the amyloid recognition unit and the hydrophilic amyloid breaker unit. The establishment of structure-function relationship for amyloid-modifying therapies by the various functional entities should serve as an important step toward the development of efficient therapeutics.

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.

77 FR 18477 - Energy Conservation Program: Energy Conservation Standards for Battery Chargers and External...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-03-27

... Interstate Rule (CAIR, 70 FR 25162 (May 12, 2005)), but not the Clean Air Mercury Rule (CAMR, 70 FR 28606 (May 18, 2005)). Subsequent regulations, including the finalized CAIR replacement rule, the Cross-State... Air Interstate Rule (CAIR, which has a similar structure, but with less stringent budgets and less...

Computational modeling of spiking neural network with learning rules from STDP and intrinsic plasticity

NASA Astrophysics Data System (ADS)

Li, Xiumin; Wang, Wei; Xue, Fangzheng; Song, Yongduan

2018-02-01

Recently there has been continuously increasing interest in building up computational models of spiking neural networks (SNN), such as the Liquid State Machine (LSM). The biologically inspired self-organized neural networks with neural plasticity can enhance the capability of computational performance, with the characteristic features of dynamical memory and recurrent connection cycles which distinguish them from the more widely used feedforward neural networks. Despite a variety of computational models for brain-like learning and information processing have been proposed, the modeling of self-organized neural networks with multi-neural plasticity is still an important open challenge. The main difficulties lie in the interplay among different forms of neural plasticity rules and understanding how structures and dynamics of neural networks shape the computational performance. In this paper, we propose a novel approach to develop the models of LSM with a biologically inspired self-organizing network based on two neural plasticity learning rules. The connectivity among excitatory neurons is adapted by spike-timing-dependent plasticity (STDP) learning; meanwhile, the degrees of neuronal excitability are regulated to maintain a moderate average activity level by another learning rule: intrinsic plasticity (IP). Our study shows that LSM with STDP+IP performs better than LSM with a random SNN or SNN obtained by STDP alone. The noticeable improvement with the proposed method is due to the better reflected competition among different neurons in the developed SNN model, as well as the more effectively encoded and processed relevant dynamic information with its learning and self-organizing mechanism. This result gives insights to the optimization of computational models of spiking neural networks with neural plasticity.

75 FR 48395 - Self-Regulatory Organizations; International Securities Exchange, LLC; Notice of Filing and...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-08-10

... Proposed Rule Change The Exchange proposes to adopt changes to its crossing mechanisms to adopt an auto... proposal is to add step-up-and-match functionality (the ``auto-match feature'') to both mechanisms for an...-side order specifies the auction start price. With the auto-match feature, the contra-side order will...

Using the structure of natural scenes and sounds to predict neural response properties in the brain

NASA Astrophysics Data System (ADS)

Deweese, Michael

2014-03-01

The natural scenes and sounds we encounter in the world are highly structured. The fact that animals and humans are so efficient at processing these sensory signals compared with the latest algorithms running on the fastest modern computers suggests that our brains can exploit this structure. We have developed a sparse mathematical representation of speech that minimizes the number of active model neurons needed to represent typical speech sounds. The model learns several well-known acoustic features of speech such as harmonic stacks, formants, onsets and terminations, but we also find more exotic structures in the spectrogra representation of sound such as localized checkerboard patterns and frequency-modulated excitatory subregions flanked by suppressive sidebands. Moreover, several of these novel features resemble neuronal receptive fields reported in the Inferior Colliculus (IC), as well as auditory thalamus (MGBv) and primary auditory cortex (A1), and our model neurons exhibit the same tradeoff in spectrotemporal resolution as has been observed in IC. To our knowledge, this is the first demonstration that receptive fields of neurons in the ascending mammalian auditory pathway beyond the auditory nerve can be predicted based on coding principles and the statistical properties of recorded sounds. We have also developed a biologically-inspired neural network model of primary visual cortex (V1) that can learn a sparse representation of natural scenes using spiking neurons and strictly local plasticity rules. The representation learned by our model is in good agreement with measured receptive fields in V1, demonstrating that sparse sensory coding can be achieved in a realistic biological setting.

Semantic modeling and structural synthesis of onboard electronics protection means as open information system

NASA Astrophysics Data System (ADS)

Zhevnerchuk, D. V.; Surkova, A. S.; Lomakina, L. S.; Golubev, A. S.

2018-05-01

The article describes the component representation approach and semantic models of on-board electronics protection from ionizing radiation of various nature. Semantic models are constructed, the feature of which is the representation of electronic elements, protection modules, sources of impact in the form of blocks with interfaces. The rules of logical inference and algorithms for synthesizing the object properties of the semantic network, imitating the interface between the components of the protection system and the sources of radiation, are developed. The results of the algorithm are considered using the example of radiation-resistant microcircuits 1645RU5U, 1645RT2U and the calculation and experimental method for estimating the durability of on-board electronics.

A hybrid learning method for constructing compact rule-based fuzzy models.

PubMed

Zhao, Wanqing; Niu, Qun; Li, Kang; Irwin, George W

2013-12-01

The Takagi–Sugeno–Kang-type rule-based fuzzy model has found many applications in different fields; a major challenge is, however, to build a compact model with optimized model parameters which leads to satisfactory model performance. To produce a compact model, most existing approaches mainly focus on selecting an appropriate number of fuzzy rules. In contrast, this paper considers not only the selection of fuzzy rules but also the structure of each rule premise and consequent, leading to the development of a novel compact rule-based fuzzy model. Here, each fuzzy rule is associated with two sets of input attributes, in which the first is used for constructing the rule premise and the other is employed in the rule consequent. A new hybrid learning method combining the modified harmony search method with a fast recursive algorithm is hereby proposed to determine the structure and the parameters for the rule premises and consequents. This is a hard mixed-integer nonlinear optimization problem, and the proposed hybrid method solves the problem by employing an embedded framework, leading to a significantly reduced number of model parameters and a small number of fuzzy rules with each being as simple as possible. Results from three examples are presented to demonstrate the compactness (in terms of the number of model parameters and the number of rules) and the performance of the fuzzy models obtained by the proposed hybrid learning method, in comparison with other techniques from the literature.

Emotional display rules and emotional labor: the moderating role of commitment.

PubMed

Gosserand, Robin H; Diefendorff, James M

2005-11-01

The authors examined whether commitment to emotional display rules is a necessary condition for emotional display rules to affect behavior at work. Results using structural equation modeling revealed that display rule commitment moderated the relationships of emotional display rule perceptions with surface acting, deep acting, and positive affective delivery at work, such that the relationships were strong and positive when commitment to display rules was high and weak when commitment to display rules was low. These findings suggest that motivation plays a role in the emotional labor process in that individuals must be committed to display rules for these rules to affect behavior. ((c) 2005 APA, all rights reserved).

Discovering body site and severity modifiers in clinical texts

PubMed Central

Dligach, Dmitriy; Bethard, Steven; Becker, Lee; Miller, Timothy; Savova, Guergana K

2014-01-01

Objective To research computational methods for discovering body site and severity modifiers in clinical texts. Methods We cast the task of discovering body site and severity modifiers as a relation extraction problem in the context of a supervised machine learning framework. We utilize rich linguistic features to represent the pairs of relation arguments and delegate the decision about the nature of the relationship between them to a support vector machine model. We evaluate our models using two corpora that annotate body site and severity modifiers. We also compare the model performance to a number of rule-based baselines. We conduct cross-domain portability experiments. In addition, we carry out feature ablation experiments to determine the contribution of various feature groups. Finally, we perform error analysis and report the sources of errors. Results The performance of our method for discovering body site modifiers achieves F1 of 0.740–0.908 and our method for discovering severity modifiers achieves F1 of 0.905–0.929. Discussion Results indicate that both methods perform well on both in-domain and out-domain data, approaching the performance of human annotators. The most salient features are token and named entity features, although syntactic dependency features also contribute to the overall performance. The dominant sources of errors are infrequent patterns in the data and inability of the system to discern deeper semantic structures. Conclusions We investigated computational methods for discovering body site and severity modifiers in clinical texts. Our best system is released open source as part of the clinical Text Analysis and Knowledge Extraction System (cTAKES). PMID:24091648

Discovering body site and severity modifiers in clinical texts.

PubMed

Dligach, Dmitriy; Bethard, Steven; Becker, Lee; Miller, Timothy; Savova, Guergana K

2014-01-01

To research computational methods for discovering body site and severity modifiers in clinical texts. We cast the task of discovering body site and severity modifiers as a relation extraction problem in the context of a supervised machine learning framework. We utilize rich linguistic features to represent the pairs of relation arguments and delegate the decision about the nature of the relationship between them to a support vector machine model. We evaluate our models using two corpora that annotate body site and severity modifiers. We also compare the model performance to a number of rule-based baselines. We conduct cross-domain portability experiments. In addition, we carry out feature ablation experiments to determine the contribution of various feature groups. Finally, we perform error analysis and report the sources of errors. The performance of our method for discovering body site modifiers achieves F1 of 0.740-0.908 and our method for discovering severity modifiers achieves F1 of 0.905-0.929. Results indicate that both methods perform well on both in-domain and out-domain data, approaching the performance of human annotators. The most salient features are token and named entity features, although syntactic dependency features also contribute to the overall performance. The dominant sources of errors are infrequent patterns in the data and inability of the system to discern deeper semantic structures. We investigated computational methods for discovering body site and severity modifiers in clinical texts. Our best system is released open source as part of the clinical Text Analysis and Knowledge Extraction System (cTAKES).

Learning Optimal Individualized Treatment Rules from Electronic Health Record Data

PubMed Central

Wang, Yuanjia; Wu, Peng; Liu, Ying; Weng, Chunhua; Zeng, Donglin

2016-01-01

Medical research is experiencing a paradigm shift from “one-size-fits-all” strategy to a precision medicine approach where the right therapy, for the right patient, and at the right time, will be prescribed. We propose a statistical method to estimate the optimal individualized treatment rules (ITRs) that are tailored according to subject-specific features using electronic health records (EHR) data. Our approach merges statistical modeling and medical domain knowledge with machine learning algorithms to assist personalized medical decision making using EHR. We transform the estimation of optimal ITR into a classification problem and account for the non-experimental features of the EHR data and confounding by clinical indication. We create a broad range of feature variables that reflect both patient health status and healthcare data collection process. Using EHR data collected at Columbia University clinical data warehouse, we construct a decision tree for choosing the best second line therapy for treating type 2 diabetes patients. PMID:28503676

Mass wasting features in Juventae Chasma, Mars

NASA Astrophysics Data System (ADS)

Sarkar, Ranjan; Singh, Pragya; Porwal, Alok; Ganesh, Indujaa

2016-07-01

Introduction : We report mass-wasting features preserved as debris aprons from Juventae Chasma. Diverse lines of evidence and associated geomorphological features indicate that fluidized ice or water within the wall rocks of the chasma could be responsible for mobilizing the debris. Description : The distinctive features of the landslides in Juvenate Chasma are: (1) lack of a well-defined crown or a clear-cut section at their point of origin and instead the presence of amphitheatre-headed tributary canyons; (2) absence of slump blocks; (3) overlapping of debris aprons; (4) a variety of surface textures from fresh and grooved to degraded and chaotic; (5) rounded lobes of debris aprons; (6) large variation of sizes from small lumps (~0.52 m2) to large tongue shaped ones (~ 80 m2); (7) smaller average size of landslides as compared to other chasmas; and (8) occasional preservation of fresh surficial features indicating recent emplacement. Discussion : Amphitheatre-headed tributary canyons, which are formed due to ground water sapping, indicate that the same was responsible for wall-section collapse, although a structural control cannot be completely ruled out. The emplacement of the mass wasting features preferentially at the mouths of amphitheatre-headed tributary canyons along with the rounded flow fronts of the debris suggest fluids may have played a vital role in their emplacement. The mass-wasting features in Juventae Chasma are unique compared to other landslides in Valles Marineris despite commonalities such as the radial furrows, fan-shaped outlines, overlapping aprons and overtopped obstacles. The unique set of features and close association with amphitheatre-headed tributary canyons imply that the trigger of the landslides was not structural or tectonic but possibly weakness imparted by the presence of water or ice in the pore-spaces of the wall. Craters with fluidized ejecta blankets and scalloped depressions in the surrounding plateau also support this possibility. Depending on the amounts of fluids involved at the time of emplacement, these mass movements may also qualify as debris flows. The role of fluids in the Valles Marineris landslides is still debated; however, in the Juventae Chasma landslides we see unique features which set these apart from other landslides in Valles Marineris. Further study is required to fully investigate the mechanism of emplacement of these debris.

76 FR 8659 - Structure and Practices of the Video Relay Service Program

Federal Register 2010, 2011, 2012, 2013, 2014

2011-02-15

... Practices of the Video Relay Service Program AGENCY: Federal Communications Commission. ACTION: Final rule... with the Commission's Structure and Practices of the Video Relay Service Program, Declaratory Ruling... Practices of the Video Relay Service Program, CG Docket No. 10-51. Form Number: N/A. Respondents: Business...

Complex Problem Solving--More than Reasoning?

ERIC Educational Resources Information Center

Wustenberg, Sascha; Greiff, Samuel; Funke, Joachim

2012-01-01

This study investigates the internal structure and construct validity of Complex Problem Solving (CPS), which is measured by a "Multiple-Item-Approach." It is tested, if (a) three facets of CPS--"rule identification" (adequateness of strategies), "rule knowledge" (generated knowledge) and "rule application"…

Evaluation of the performance of statistical tests used in making cleanup decisions at Superfund sites. Part 1: Choosing an appropriate statistical test

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

Berman, D.W.; Allen, B.C.; Van Landingham, C.B.

1998-12-31

The decision rules commonly employed to determine the need for cleanup are evaluated both to identify conditions under which they lead to erroneous conclusions and to quantify the rate that such errors occur. Their performance is also compared with that of other applicable decision rules. The authors based the evaluation of decision rules on simulations. Results are presented as power curves. These curves demonstrate that the degree of statistical control achieved is independent of the form of the null hypothesis. The loss of statistical control that occurs when a decision rule is applied to a data set that does notmore » satisfy the rule`s validity criteria is also clearly demonstrated. Some of the rules evaluated do not offer the formal statistical control that is an inherent design feature of other rules. Nevertheless, results indicate that such informal decision rules may provide superior overall control of error rates, when their application is restricted to data exhibiting particular characteristics. The results reported here are limited to decision rules applied to uncensored and lognormally distributed data. To optimize decision rules, it is necessary to evaluate their behavior when applied to data exhibiting a range of characteristics that bracket those common to field data. The performance of decision rules applied to data sets exhibiting a broader range of characteristics is reported in the second paper of this study.« less

Examining the Rule of Thumb of Not Using Multilevel Modeling: The "Design Effect Smaller than Two" Rule

ERIC Educational Resources Information Center

Lai, Mark H. C.; Kwok, Oi-man

2015-01-01

Educational researchers commonly use the rule of thumb of "design effect smaller than 2" as the justification of not accounting for the multilevel or clustered structure in their data. The rule, however, has not yet been systematically studied in previous research. In the present study, we generated data from three different models…

Iron K Features in the Quasar E 1821+643: Evidence for Gravitationally Redshifted Absorption?

NASA Technical Reports Server (NTRS)

Yaqoob, Tahir; Serlemitsos, Peter

2005-01-01

We report a Chandra high-energy grating detection of a narrow, redshifted absorption line superimposed on the red wing of a broad Fe K line in the z = 0.297 quasar E 1821+643. The absorption line is detected at a confidence level, estimated by two different methods, in the range approx. 2 - 3 sigma. Although the detection significance is not high enough to exclude a non-astrophysical origin, accounting for the absorption feature when modeling the X-ray spectrum implies that the Fe-K emission line is broad, and consistent with an origin in a relativistic accretion disk. Ignoring the apparent absorption feature leads to the conclusion that the Fe-K emission line is narrower, and also affects the inferred peak energy of the line (and hence the inferred ionization state of Fe). If the absorption line (at approx. 6.2 keV in the quasar frame) is real, we argue that it could be due to gravitationally redshifted Fe XXV or Fe XXVI resonance absorption within approx. 10 - 20 gravitational radii of the putative central black hole. The absorption line is not detected in earlier ASCA and Chandra low-energy grating observations, but the absorption line is not unequivocally ruled out by these data. The Chandra high-energy grating Fe-K emission line is consistent with an origin predominantly in Fe I-XVII or so. In an ASCA observation eight years earlier, the Fe-K line peaked at approx. 6.6 keV, closer to the energies of He-like Fe triplet lines. Further, in a Chandra low-energy grating observation the Fe-K line profile was double-peaked, one peak corresponding to Fe I-XVII or so, the other peak to Fe XXVI Ly alpha. Such a wide range in ionization state of Fe is not ruled out by the HEG and ASCA data either, and is suggestive of a complex structure for the line-emitter.

Synthesis and structural characterization of the Zintl phases Na{sub 3}Ca{sub 3}TrPn{sub 4}, Na{sub 3}Sr{sub 3}TrPn{sub 4}, and Na{sub 3}Eu{sub 3}TrPn{sub 4} (Tr=Al, Ga, In; Pn=P, As, Sb)

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

Wang, Yi; Suen, Nian-Tzu; College of Chemistry and Chemical Engineering, Yangzhou University, Yangzhou 225002

15 new quaternary Zintl phases have been synthesized by solid-state reactions from the respective elements, and their structures have been determined by single-crystal X-ray diffraction. Na{sub 3}E{sub 3}TrPn{sub 4} (E=Ca, Sr, Eu; Tr=Al, Ga, In; Pn=P, As, Sb) crystallize in the hexagonal crystal system with the non-centrosymmetric space group P6{sub 3}mc (No. 186). The structure represents a variant of the K{sub 6}HgS{sub 4} structure type (Pearson index hP22) and features [TrPn{sub 4}]{sup 9–} tetrahedral units, surrounded by Na{sup +} and Ca{sup 2+}, Sr{sup 2+}, Eu{sup 2+} cations. The nominal formula rationalization [Na{sup +}]{sub 3}[E{sup 2+}]{sub 3}[TrPn{sub 4}]{sup 9–} follows themore » octet rule, suggesting closed-shell configurations for all atoms and intrinsic semiconducting behavior. However, structure refinements for several members hint at disorder and mixing of cations that potentially counteract the optimal valence electron count. - Graphical abstract: The hexagonal, non-centrosymmetric structure of Na{sub 3}E{sub 3}TrPn{sub 4} (E=Ca, Sr, Eu; Tr=Al, Ga, In; Pn=P, As, Sb) features [TrPn{sub 4}]{sup 9–} tetrahedral units, surrounded by Na{sup +} and Ca{sup 2+}, Sr{sup 2+}, Eu{sup 2+} cations. - Highlights: • 15 quaternary phosphides, arsenides, and antimonides are synthesized and structurally characterized. • The structure is a variant of the hexagonal K{sub 6}HgS{sub 4}-type, with distinctive pattern for the cations. • Occupational and/or positional disorder of yet unknown origin exists for some members of the series.« less

Forward Compton scattering with weak neutral current: Constraints from sum rules

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

Gorchtein, Mikhail; Zhang, Xilin

2015-06-09

We generalize forward real Compton amplitude to the case of the interference of the electromagnetic and weak neutral current, formulate a low-energy theorem, relate the new amplitudes to the interference structure functions and obtain a new set of sum rules. Furthermore, we address a possible new sum rule that relates the product of the axial charge and magnetic moment of the nucleon to the 0th moment of the structure function g5(ν, 0). For the dispersive γ Z-box correction to the proton’s weak charge, the application of the GDH sum rule allows us to reduce the uncertainty due to resonance contributionsmore » by a factor of two. Finally, the finite energy sum rule helps addressing the uncertainty in that calculation due to possible duality violations.« less

Rule-Based Expert Systems in the Command Estimate: An Operational Perspective

DTIC Science & Technology

1990-06-01

control measures. 5. Prepare COA statement(s) and sketch(es). The key inputs for developing courses of action are the DFD process of IPB, data stores...mission, or a change of information provides new direction to this process for that particular operation." Formal scientific analysis of the command...30 5. Delivery of outside news . This feature contributes to the commanders insatiable need for current information. Artificial intelligence ana rule

Rough Evaluation Structure: Application of Rough Set Theory to Generate Simple Rules for Inconsistent Preference Relation

NASA Astrophysics Data System (ADS)

Gehrmann, Andreas; Nagai, Yoshimitsu; Yoshida, Osamu; Ishizu, Syohei

Since management decision-making becomes complex and preferences of the decision-maker frequently becomes inconsistent, multi-attribute decision-making problems were studied. To represent inconsistent preference relation, the concept of evaluation structure was introduced. We can generate simple rules to represent inconsistent preference relation by the evaluation structures. Further rough set theory for the preference relation was studied and the concept of approximation was introduced. One of our main aims of this paper is to introduce a concept of rough evaluation structure for representing inconsistent preference relation. We apply rough set theory to the evaluation structure, and develop a method for generating simple rules for inconsistent preference relations. In this paper, we introduce concepts of totally ordered information system, similarity class of preference relation, upper and lower approximation of preference relations. We also show the properties of rough evaluation structure and provide a simple example. As an application of rough evaluation structure, we analyze questionnaire survey of customer preferences about audio players.

How children perceive fractals: Hierarchical self-similarity and cognitive development

PubMed Central

Martins, Maurício Dias; Laaha, Sabine; Freiberger, Eva Maria; Choi, Soonja; Fitch, W. Tecumseh

2014-01-01

The ability to understand and generate hierarchical structures is a crucial component of human cognition, available in language, music, mathematics and problem solving. Recursion is a particularly useful mechanism for generating complex hierarchies by means of self-embedding rules. In the visual domain, fractals are recursive structures in which simple transformation rules generate hierarchies of infinite depth. Research on how children acquire these rules can provide valuable insight into the cognitive requirements and learning constraints of recursion. Here, we used fractals to investigate the acquisition of recursion in the visual domain, and probed for correlations with grammar comprehension and general intelligence. We compared second (n = 26) and fourth graders (n = 26) in their ability to represent two types of rules for generating hierarchical structures: Recursive rules, on the one hand, which generate new hierarchical levels; and iterative rules, on the other hand, which merely insert items within hierarchies without generating new levels. We found that the majority of fourth graders, but not second graders, were able to represent both recursive and iterative rules. This difference was partially accounted by second graders’ impairment in detecting hierarchical mistakes, and correlated with between-grade differences in grammar comprehension tasks. Empirically, recursion and iteration also differed in at least one crucial aspect: While the ability to learn recursive rules seemed to depend on the previous acquisition of simple iterative representations, the opposite was not true, i.e., children were able to acquire iterative rules before they acquired recursive representations. These results suggest that the acquisition of recursion in vision follows learning constraints similar to the acquisition of recursion in language, and that both domains share cognitive resources involved in hierarchical processing. PMID:24955884

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.

On the eddy-resolving capability of high-order discontinuous Galerkin approaches to implicit LES / under-resolved DNS of Euler turbulence

NASA Astrophysics Data System (ADS)

Moura, R. C.; Mengaldo, G.; Peiró, J.; Sherwin, S. J.

2017-02-01

We present estimates of spectral resolution power for under-resolved turbulent Euler flows obtained with high-order discontinuous Galerkin (DG) methods. The '1% rule' based on linear dispersion-diffusion analysis introduced by Moura et al. (2015) [10] is here adapted for 3D energy spectra and validated through the inviscid Taylor-Green vortex problem. The 1% rule estimates the wavenumber beyond which numerical diffusion induces an artificial dissipation range on measured energy spectra. As the original rule relies on standard upwinding, different Riemann solvers are tested. Very good agreement is found for solvers which treat the different physical waves in a consistent manner. Relatively good agreement is still found for simpler solvers. The latter however displayed spurious features attributed to the inconsistent treatment of different physical waves. It is argued that, in the limit of vanishing viscosity, such features might have a significant impact on robustness and solution quality. The estimates proposed are regarded as useful guidelines for no-model DG-based simulations of free turbulence at very high Reynolds numbers.

Self-Organization of Microcircuits in Networks of Spiking Neurons with Plastic Synapses.

PubMed

Ocker, Gabriel Koch; Litwin-Kumar, Ashok; Doiron, Brent

2015-08-01

The synaptic connectivity of cortical networks features an overrepresentation of certain wiring motifs compared to simple random-network models. This structure is shaped, in part, by synaptic plasticity that promotes or suppresses connections between neurons depending on their joint spiking activity. Frequently, theoretical studies focus on how feedforward inputs drive plasticity to create this network structure. We study the complementary scenario of self-organized structure in a recurrent network, with spike timing-dependent plasticity driven by spontaneous dynamics. We develop a self-consistent theory for the evolution of network structure by combining fast spiking covariance with a slow evolution of synaptic weights. Through a finite-size expansion of network dynamics we obtain a low-dimensional set of nonlinear differential equations for the evolution of two-synapse connectivity motifs. With this theory in hand, we explore how the form of the plasticity rule drives the evolution of microcircuits in cortical networks. When potentiation and depression are in approximate balance, synaptic dynamics depend on weighted divergent, convergent, and chain motifs. For additive, Hebbian STDP these motif interactions create instabilities in synaptic dynamics that either promote or suppress the initial network structure. Our work provides a consistent theoretical framework for studying how spiking activity in recurrent networks interacts with synaptic plasticity to determine network structure.

Self-Organization of Microcircuits in Networks of Spiking Neurons with Plastic Synapses

PubMed Central

Ocker, Gabriel Koch; Litwin-Kumar, Ashok; Doiron, Brent

2015-01-01

The synaptic connectivity of cortical networks features an overrepresentation of certain wiring motifs compared to simple random-network models. This structure is shaped, in part, by synaptic plasticity that promotes or suppresses connections between neurons depending on their joint spiking activity. Frequently, theoretical studies focus on how feedforward inputs drive plasticity to create this network structure. We study the complementary scenario of self-organized structure in a recurrent network, with spike timing-dependent plasticity driven by spontaneous dynamics. We develop a self-consistent theory for the evolution of network structure by combining fast spiking covariance with a slow evolution of synaptic weights. Through a finite-size expansion of network dynamics we obtain a low-dimensional set of nonlinear differential equations for the evolution of two-synapse connectivity motifs. With this theory in hand, we explore how the form of the plasticity rule drives the evolution of microcircuits in cortical networks. When potentiation and depression are in approximate balance, synaptic dynamics depend on weighted divergent, convergent, and chain motifs. For additive, Hebbian STDP these motif interactions create instabilities in synaptic dynamics that either promote or suppress the initial network structure. Our work provides a consistent theoretical framework for studying how spiking activity in recurrent networks interacts with synaptic plasticity to determine network structure. PMID:26291697

Can mathematics explain the evolution of human language?

PubMed

Witzany, Guenther

2011-09-01

Investigation into the sequence structure of the genetic code by means of an informatic approach is a real success story. The features of human language are also the object of investigation within the realm of formal language theories. They focus on the common rules of a universal grammar that lies behind all languages and determine generation of syntactic structures. This universal grammar is a depiction of material reality, i.e., the hidden logical order of things and its relations determined by natural laws. Therefore mathematics is viewed not only as an appropriate tool to investigate human language and genetic code structures through computer science-based formal language theory but is itself a depiction of material reality. This confusion between language as a scientific tool to describe observations/experiences within cognitive constructed models and formal language as a direct depiction of material reality occurs not only in current approaches but was the central focus of the philosophy of science debate in the twentieth century, with rather unexpected results. This article recalls these results and their implications for more recent mathematical approaches that also attempt to explain the evolution of human language.

Nonlocal response with local optics

NASA Astrophysics Data System (ADS)

Kong, Jiantao; Shvonski, Alexander J.; Kempa, Krzysztof

2018-04-01

For plasmonic systems too small for classical, local simulations to be valid, but too large for ab initio calculations to be computationally feasible, we developed a practical approach—a nonlocal-to-local mapping that enables the use of a modified local system to obtain the response due to nonlocal effects to lowest order, at the cost of higher structural complexity. In this approach, the nonlocal surface region of a metallic structure is mapped onto a local dielectric film, mathematically preserving the nonlocality of the entire system. The most significant feature of this approach is its full compatibility with conventional, highly efficient finite difference time domain (FDTD) simulation codes. Our optimized choice of mapping is based on the Feibelman's d -function formalism, and it produces an effective dielectric function of the local film that obeys all required sum rules, as well as the Kramers-Kronig causality relations. We demonstrate the power of our approach combined with an FDTD scheme, in a series of comparisons with experiments and ab initio density functional theory calculations from the literature, for structures with dimensions from the subnanoscopic to microscopic range.

Atomic dynamics and the problem of the structural stability of free clusters of solidified inert gases

NASA Astrophysics Data System (ADS)

Verkhovtseva, É. T.; Gospodarev, I. A.; Grishaev, A. V.; Kovalenko, S. I.; Solnyshkin, D. D.; Syrkin, E. S.; Feodos'ev, S. B.

2003-05-01

The dependence of the rms amplitudes of atoms in free clusters of solidified inert gases on the cluster size is investigated theoretically and experimentally. Free clusters are produced by homogeneous nucleation in an adiabatically expanding supersonic stream. Electron diffraction is used to measure the rms amplitudes of the atoms; the Jacobi-matrix method is used for theoretical calculations. A series of distinguishing features of the atomic dynamics of microclusters was found. This was necessary to determine the character of the formation and the stability conditions of the crystal structure. It wass shown that for clusters consisting of less than N˜103 atoms, as the cluster size decreases, the rms amplitudes grow much more rapidly than expected from the increase in the specific contribution of the surface. It is also established that an fcc structure of a free cluster, as a rule, contains twinning defects (nuclei of an hcp phase). One reason for the appearance of such defects is the so-called vertex instability (anomalously large oscillation amplitudes) of the atoms in coordination spheres.

Modulated Hebb-Oja learning rule--a method for principal subspace analysis.

PubMed

Jankovic, Marko V; Ogawa, Hidemitsu

2006-03-01

This paper presents analysis of the recently proposed modulated Hebb-Oja (MHO) method that performs linear mapping to a lower-dimensional subspace. Principal component subspace is the method that will be analyzed. Comparing to some other well-known methods for yielding principal component subspace (e.g., Oja's Subspace Learning Algorithm), the proposed method has one feature that could be seen as desirable from the biological point of view--synaptic efficacy learning rule does not need the explicit information about the value of the other efficacies to make individual efficacy modification. Also, the simplicity of the "neural circuits" that perform global computations and a fact that their number does not depend on the number of input and output neurons, could be seen as good features of the proposed method.

Estimation of tool wear length in finish milling using a fuzzy inference algorithm

NASA Astrophysics Data System (ADS)

Ko, Tae Jo; Cho, Dong Woo

1993-10-01

The geometric accuracy and surface roughness are mainly affected by the flank wear at the minor cutting edge in finish machining. A fuzzy estimator obtained by a fuzzy inference algorithm with a max-min composition rule to evaluate the minor flank wear length in finish milling is introduced. The features sensitive to minor flank wear are extracted from the dispersion analysis of a time series AR model of the feed directional acceleration of the spindle housing. Linguistic rules for fuzzy estimation are constructed using these features, and then fuzzy inferences are carried out with test data sets under various cutting conditions. The proposed system turns out to be effective for estimating minor flank wear length, and its mean error is less than 12%.

A hierarchical classification method for finger knuckle print recognition

NASA Astrophysics Data System (ADS)

Kong, Tao; Yang, Gongping; Yang, Lu

2014-12-01

Finger knuckle print has recently been seen as an effective biometric technique. In this paper, we propose a hierarchical classification method for finger knuckle print recognition, which is rooted in traditional score-level fusion methods. In the proposed method, we firstly take Gabor feature as the basic feature for finger knuckle print recognition and then a new decision rule is defined based on the predefined threshold. Finally, the minor feature speeded-up robust feature is conducted for these users, who cannot be recognized by the basic feature. Extensive experiments are performed to evaluate the proposed method, and experimental results show that it can achieve a promising performance.

Numerical Simulation and Optimization of Directional Solidification Process of Single Crystal Superalloy Casting

PubMed Central

Zhang, Hang; Xu, Qingyan; Liu, Baicheng

2014-01-01

The rapid development of numerical modeling techniques has led to more accurate results in modeling metal solidification processes. In this study, the cellular automaton-finite difference (CA-FD) method was used to simulate the directional solidification (DS) process of single crystal (SX) superalloy blade samples. Experiments were carried out to validate the simulation results. Meanwhile, an intelligent model based on fuzzy control theory was built to optimize the complicate DS process. Several key parameters, such as mushy zone width and temperature difference at the cast-mold interface, were recognized as the input variables. The input variables were functioned with the multivariable fuzzy rule to get the output adjustment of withdrawal rate (v) (a key technological parameter). The multivariable fuzzy rule was built, based on the structure feature of casting, such as the relationship between section area, and the delay time of the temperature change response by changing v, and the professional experience of the operator as well. Then, the fuzzy controlling model coupled with CA-FD method could be used to optimize v in real-time during the manufacturing process. The optimized process was proven to be more flexible and adaptive for a steady and stray-grain free DS process. PMID:28788535

Evolutionary potential games on lattices

NASA Astrophysics Data System (ADS)

Szabó, György; Borsos, István

2016-04-01

Game theory provides a general mathematical background to study the effect of pair interactions and evolutionary rules on the macroscopic behavior of multi-player games where players with a finite number of strategies may represent a wide scale of biological objects, human individuals, or even their associations. In these systems the interactions are characterized by matrices that can be decomposed into elementary matrices (games) and classified into four types. The concept of decomposition helps the identification of potential games and also the evaluation of the potential that plays a crucial role in the determination of the preferred Nash equilibrium, and defines the Boltzmann distribution towards which these systems evolve for suitable types of dynamical rules. This survey draws parallel between the potential games and the kinetic Ising type models which are investigated for a wide scale of connectivity structures. We discuss briefly the applicability of the tools and concepts of statistical physics and thermodynamics. Additionally the general features of ordering phenomena, phase transitions and slow relaxations are outlined and applied to evolutionary games. The discussion extends to games with three or more strategies. Finally we discuss what happens when the system is weakly driven out of the "equilibrium state" by adding non-potential components representing games of cyclic dominance.

Differences between Caucasian and Asian attractive faces.

PubMed

Rhee, S C

2018-02-01

There are discrepancies between the public's current beauty desires and conventional theories and historical rules regarding facial beauty. This photogrammetric study aims to describe in detail mathematical differences in facial configuration between attractive Caucasian and attractive Asian faces. To analyse the structural differences between attractive Caucasian and attractive Asian faces, frontal face and lateral face views for each race were morphed; facial landmarks were defined, and the relative photographic pixel distances and angles were measured. Absolute values were acquired by arithmetic conversion for comparison. The data indicate that some conventional beliefs of facial attractiveness can be applied but others are no longer valid in explaining perspectives of beauty between Caucasians and Asians. Racial differences in the perceptions of attractive faces were evident. Common features as a phenomenon of global fusion in the perspectives on facial beauty were revealed. Beauty standards differ with race and ethnicity, and some conventional rules for ideal facial attractiveness were found to be inappropriate. We must reexamine old principles of facial beauty and continue to fundamentally question it according to its racial, cultural, and neuropsychological aspects. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Learning Parsimonious Classification Rules from Gene Expression Data Using Bayesian Networks with Local Structure.

PubMed

Lustgarten, Jonathan Lyle; Balasubramanian, Jeya Balaji; Visweswaran, Shyam; Gopalakrishnan, Vanathi

2017-03-01

The comprehensibility of good predictive models learned from high-dimensional gene expression data is attractive because it can lead to biomarker discovery. Several good classifiers provide comparable predictive performance but differ in their abilities to summarize the observed data. We extend a Bayesian Rule Learning (BRL-GSS) algorithm, previously shown to be a significantly better predictor than other classical approaches in this domain. It searches a space of Bayesian networks using a decision tree representation of its parameters with global constraints, and infers a set of IF-THEN rules. The number of parameters and therefore the number of rules are combinatorial to the number of predictor variables in the model. We relax these global constraints to a more generalizable local structure (BRL-LSS). BRL-LSS entails more parsimonious set of rules because it does not have to generate all combinatorial rules. The search space of local structures is much richer than the space of global structures. We design the BRL-LSS with the same worst-case time-complexity as BRL-GSS while exploring a richer and more complex model space. We measure predictive performance using Area Under the ROC curve (AUC) and Accuracy. We measure model parsimony performance by noting the average number of rules and variables needed to describe the observed data. We evaluate the predictive and parsimony performance of BRL-GSS, BRL-LSS and the state-of-the-art C4.5 decision tree algorithm, across 10-fold cross-validation using ten microarray gene-expression diagnostic datasets. In these experiments, we observe that BRL-LSS is similar to BRL-GSS in terms of predictive performance, while generating a much more parsimonious set of rules to explain the same observed data. BRL-LSS also needs fewer variables than C4.5 to explain the data with similar predictive performance. We also conduct a feasibility study to demonstrate the general applicability of our BRL methods on the newer RNA sequencing gene-expression data.

Computer-aided diagnostic approach of dermoscopy images acquiring relevant features

NASA Astrophysics Data System (ADS)

Castillejos-Fernández, H.; Franco-Arcega, A.; López-Ortega, O.

2016-09-01

In skin cancer detection, automated analysis of borders, colors, and structures of a lesion relies upon an accurate segmentation process and it is an important first step in any Computer-Aided Diagnosis (CAD) system. However, irregular and disperse lesion borders, low contrast, artifacts in images and variety of colors within the interest region make the problem difficult. In this paper, we propose an efficient approach of automatic classification which considers specific lesion features. First, for the selection of lesion skin we employ the segmentation algorithm W-FCM.1 Then, in the feature extraction stage we consider several aspects: the area of the lesion, which is calculated by correlating axes and we calculate the specific the value of asymmetry in both axes. For color analysis we employ an ensemble of clusterers including K-Means, Fuzzy K-Means and Kohonep maps, all of which estimate the presence of one or more colors defined in ABCD rule and the values for each of the segmented colors. Another aspect to consider is the type of structures that appear in the lesion Those are defined by using the ell-known GLCM method. During the classification stage we compare several methods in order to define if the lesion is benign or malignant. An important contribution of the current approach in segmentation-classification problem resides in the use of information from all color channels together, as well as the measure of each color in the lesion and the axes correlation. The segmentation and classification measures have been performed using sensibility, specificity, accuracy and AUC metric over a set of dermoscopy images from ISDIS data set

BioJazz: in silico evolution of cellular networks with unbounded complexity using rule-based modeling.

PubMed

Feng, Song; Ollivier, Julien F; Swain, Peter S; Soyer, Orkun S

2015-10-30

Systems biologists aim to decipher the structure and dynamics of signaling and regulatory networks underpinning cellular responses; synthetic biologists can use this insight to alter existing networks or engineer de novo ones. Both tasks will benefit from an understanding of which structural and dynamic features of networks can emerge from evolutionary processes, through which intermediary steps these arise, and whether they embody general design principles. As natural evolution at the level of network dynamics is difficult to study, in silico evolution of network models can provide important insights. However, current tools used for in silico evolution of network dynamics are limited to ad hoc computer simulations and models. Here we introduce BioJazz, an extendable, user-friendly tool for simulating the evolution of dynamic biochemical networks. Unlike previous tools for in silico evolution, BioJazz allows for the evolution of cellular networks with unbounded complexity by combining rule-based modeling with an encoding of networks that is akin to a genome. We show that BioJazz can be used to implement biologically realistic selective pressures and allows exploration of the space of network architectures and dynamics that implement prescribed physiological functions. BioJazz is provided as an open-source tool to facilitate its further development and use. Source code and user manuals are available at: http://oss-lab.github.io/biojazz and http://osslab.lifesci.warwick.ac.uk/BioJazz.aspx. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Optimization of RET flow using test layout

NASA Astrophysics Data System (ADS)

Zhang, Yunqiang; Sethi, Satyendra; Lucas, Kevin

2008-11-01

At advanced technology nodes with extremely low k1 lithography, it is very hard to achieve image fidelity requirements and process window for some layout configurations. Quite often these layouts are within simple design rule constraints for a given technology node. It is important to have these layouts included during early RET flow development. Most of RET developments are based on shrunk layout from the previous technology node, which is possibly not good enough. A better methodology in creating test layout is required for optical proximity correction (OPC) recipe and assists feature development. In this paper we demonstrate the application of programmable test layouts in RET development. Layout pattern libraries are developed and embedded in a layout tool (ICWB). Assessment gauges are generated together with patterns for quick correction accuracy assessment. Several groups of test pattern libraries have been developed based on learning from product patterns and a layout DOE approach. The interaction between layout patterns and OPC recipe has been studied. Correction of a contact layer is quite challenge because of poor convergence and low process window. We developed test pattern library with many different contact configurations. Different OPC schemes are studied on these test layouts. The worst process window patterns are pinpointed for a given illumination condition. Assist features (AF) are frequently placed according to pre-determined rules to improve lithography process window. These rules are usually derived from lithographic models and experiments. Direct validation of AF rules is required at development phase. We use the test layout approach to determine rules in order to eliminate AF printability problem.

27 The DiPEP (Diagnosis of PE in Pregnancy) study: can clinical assessment, d-dimer or chest x-ray be used to select pregnant or postpartum women with suspected PE for diagnostic imaging?

PubMed

Goodacre, Steve; Horspool, Kimberley; Nelson-Piercy, Catherine; Knight, Marian; Shephard, Neil; Lecky, Fiona; Thomas, Steven; Hunt, Beverley; Fuller, Gordon

2017-12-01

To determine whether clinical features (in the form of a clinical decision rule) or d-dimer can be used to select pregnant or postpartum women with suspected PE for diagnostic imaging. Observational cohort study augmented with additional cases. Consultant-led maternity units participating in the UK Obstetric Surveillance System (UKOSS) and emergency departments and maternity units at eleven prospectively recruiting sites. 198 pregnant or postpartum women with diagnosed PE identified through UKOSS and 324 pregnant or postpartum women with suspected PE from prospectively recruiting sites. Data were collected relating to clinical features, elements of clinical decision rules, d-dimer measurements, diagnostic imaging, treatment for PE and adverse outcomes. Women were classified as having or not having PE on the basis of diagnostic imaging, treatment and subsequent adverse outcomes. Primary analysis was limited to women with conclusive diagnostic imaging. Secondary analyses included women with clinically diagnosed or ruled out PE. The primary analysis included 181 women with PE and 259 without. Most clinical features showed no association with PE. The only exceptions were number of previous pregnancies over 24 weeks (p=0.017), no varicose veins (p=0.045), no recent long haul travel (p=0.006), recent surgery including caesarean section (p=0.001), increased temperature (p=0.003), low oxygen saturation (p<0.001), PE-related chest x-ray abnormality (p=0.01) and other chest x-ray abnormality (p=0.001).Clinical decision rules had areas under the receiver-operator characteristic curve ranging from 0.577 to 0.732. No clinically useful threshold for decision-making was identified for any rule. The sensitivities and specificities of d-dimer were 88.4% and 8.8% using the standard laboratory threshold and 69.8% and 32.8% using a pregnancy-specific threshold. Clinical decision rules, d-dimer and chest x-ray should not be used to select pregnant or postpartum women with suspected PE for diagnostic imaging. © 2017, Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

76 FR 64403 - Self-Regulatory Organizations; The Fixed Income Clearing Corporation; Notice of Filing and...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-10-18

... Schedule of Timeframes, and Fee Structure in the GSD Rules. II. Self-Regulatory Organization's Statement of...-Regulatory Organizations; The Fixed Income Clearing Corporation; Notice of Filing and Immediate Effectiveness... Timeframes, and Fee Structure in the GSD Rules October 12, 2011. Pursuant to Section 19(b)(1) of the...

Protein linguistics - a grammar for modular protein assembly?

PubMed

Gimona, Mario

2006-01-01

The correspondence between biology and linguistics at the level of sequence and lexical inventories, and of structure and syntax, has fuelled attempts to describe genome structure by the rules of formal linguistics. But how can we define protein linguistic rules? And how could compositional semantics improve our understanding of protein organization and functional plasticity?

78 FR 40581 - Structure and Practices of the Video Relay Service Program; Telecommunications Relay Services and...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-07-05

... Relay Service (IP Relay) providers; Adopts rules to protect the privacy of customer information relating... Structure and Practices of the Video Relay Service Program; Telecommunications Relay Services and Speech-to-Speech Services for Individuals With Hearing and Speech Disabilities; Final Rule #0;#0;Federal Register...

Predictions of Crystal Structure Based on Radius Ratio: How Reliable Are They?

ERIC Educational Resources Information Center

Nathan, Lawrence C.

1985-01-01

Discussion of crystalline solids in undergraduate curricula often includes the use of radius ratio rules as a method for predicting which type of crystal structure is likely to be adopted by a given ionic compound. Examines this topic, establishing more definitive guidelines for the use and reliability of the rules. (JN)

Cutoff Criteria for Fit Indexes in Covariance Structure Analysis: Conventional Criteria versus New Alternatives.

ERIC Educational Resources Information Center

Hu, Li-tze; Bentler, Peter M.

1999-01-01

The adequacy of "rule of thumb" conventional cutoff criteria and several alternatives for fit indices in covariance structure analysis was evaluated through simulation. Analyses suggest that, for all recommended fit indexes except one, a cutoff criterion greater than (or sometimes smaller than) the conventional rule of thumb is required…

Origin of spin gapless semiconductor behavior in CoFeCrGa: Theory and Experiment

DOE PAGES

Bainsla, Lakhan; Mallick, A. I.; Raja, M. Manivel; ...

2015-07-08

Despite a plethora of materials suggested for spintronic applications, a new class of materials has emerged, namely spin gapless semiconductors (SGS), which offers potentially more advantageous properties than existing ones. These magnetic semiconductors exhibit a finite band gap for one spin channel and a closed gap for the other. Supported by electronic-structure calculations, we report evidence of SGS behavior in equiatomic quaternary CoFeCrGa, having a cubic Heusler (prototype LiMgPdSn) structure but exhibiting chemical disorder (DO 3 structure). CoFeCrGa is found to transform from SGS to half-metallic phase under pressure, which is attributed to unique electronic-structure features. The saturation magnetization (Mmore » S) was obtained at 8K agrees with the Slater-Pauling rule and the Curie temperature (T C) is found to exceed 400K. Carrier concentration (up to 250K) and electrical conductivity are observed to be nearly temperature independent, prerequisites for SGS. The anomalous Hall coefficient is estimated to be 185S/cm at 5K. Considering the SGS properties and high T C, this material appears to be promising for spintronic applications.« less

Discrete particle swarm optimization for identifying community structures in signed social networks.

PubMed

Cai, Qing; Gong, Maoguo; Shen, Bo; Ma, Lijia; Jiao, Licheng

2014-10-01

Modern science of networks has facilitated us with enormous convenience to the understanding of complex systems. Community structure is believed to be one of the notable features of complex networks representing real complicated systems. Very often, uncovering community structures in networks can be regarded as an optimization problem, thus, many evolutionary algorithms based approaches have been put forward. Particle swarm optimization (PSO) is an artificial intelligent algorithm originated from social behavior such as birds flocking and fish schooling. PSO has been proved to be an effective optimization technique. However, PSO was originally designed for continuous optimization which confounds its applications to discrete contexts. In this paper, a novel discrete PSO algorithm is suggested for identifying community structures in signed networks. In the suggested method, particles' status has been redesigned in discrete form so as to make PSO proper for discrete scenarios, and particles' updating rules have been reformulated by making use of the topology of the signed network. Extensive experiments compared with three state-of-the-art approaches on both synthetic and real-world signed networks demonstrate that the proposed method is effective and promising. Copyright © 2014 Elsevier Ltd. All rights reserved.

The optical gap in VO2 insulating phases is dominated by Coulomb repulsion

NASA Astrophysics Data System (ADS)

Hendriks, Christopher; Walter, Eric; Krakauer, Henry; Huffman, Tyler; Qazilbash, Mumtaz

Under doping, tensile strain or heating, vanadium dioxide (VO2) transforms from an insulating monoclinic (M1) to a metallic rutile (R) phase, progressing through intermediate insulating triclinic (T) and magnetic (M2) phases. Broadband optical spectroscopy data have been obtained on the T and M2 phases in the same sample. While only half the V atoms are dimerized in M2 compared to M1 and T, the measured optical gap is essentially unaltered by the first-order structural phase transition between them. Moreover, the optical interband features in the T and M2 phases are remarkably similar to those previously observed in the well-studied M1 phase. This shows that the electronic structure is insensitive to the lattice structure. Our ab-initio HSE optical conductivity calculations on the insulating phases of VO2 are in excellent agreement with the experimental measurements. We will discuss the choice of α, the fraction of exact exchange. As the energy gap is insensitive to the different lattice structures of the three insulating phases, we rule out Peierls effects as the dominant contributor to the opening of the gap. Rather, the energy gap arises from intra-atomic Coulomb correlations. Supported by ONR.

Strength Analysis on Ship Ladder Using Finite Element Method

NASA Astrophysics Data System (ADS)

Budianto; Wahyudi, M. T.; Dinata, U.; Ruddianto; Eko P., M. M.

2018-01-01

In designing the ship’s structure, it should refer to the rules in accordance with applicable classification standards. In this case, designing Ladder (Staircase) on a Ferry Ship which is set up, it must be reviewed based on the loads during ship operations, either during sailing or at port operations. The classification rules in ship design refer to the calculation of the structure components described in Classification calculation method and can be analysed using the Finite Element Method. Classification Regulations used in the design of Ferry Ships used BKI (Bureau of Classification Indonesia). So the rules for the provision of material composition in the mechanical properties of the material should refer to the classification of the used vessel. The analysis in this structure used program structure packages based on Finite Element Method. By using structural analysis on Ladder (Ladder), it obtained strength and simulation structure that can withstand load 140 kg both in static condition, dynamic, and impact. Therefore, the result of the analysis included values of safety factors in the ship is to keep the structure safe but the strength of the structure is not excessive.

Using pattern enumeration to accelerate process development and ramp yield

NASA Astrophysics Data System (ADS)

Zhuang, Linda; Pang, Jenny; Xu, Jessy; Tsai, Mengfeng; Wang, Amy; Zhang, Yifan; Sweis, Jason; Lai, Ya-Chieh; Ding, Hua

2016-03-01

During a new technology node process setup phase, foundries do not initially have enough product chip designs to conduct exhaustive process development. Different operational teams use manually designed simple test keys to set up their process flows and recipes. When the very first version of the design rule manual (DRM) is ready, foundries enter the process development phase where new experiment design data is manually created based on these design rules. However, these IP/test keys contain very uniform or simple design structures. This kind of design normally does not contain critical design structures or process unfriendly design patterns that pass design rule checks but are found to be less manufacturable. It is desired to have a method to generate exhaustive test patterns allowed by design rules at development stage to verify the gap of design rule and process. This paper presents a novel method of how to generate test key patterns which contain known problematic patterns as well as any constructs which designers could possibly draw based on current design rules. The enumerated test key patterns will contain the most critical design structures which are allowed by any particular design rule. A layout profiling method is used to do design chip analysis in order to find potential weak points on new incoming products so fab can take preemptive action to avoid yield loss. It can be achieved by comparing different products and leveraging the knowledge learned from previous manufactured chips to find possible yield detractors.

Landscape features, standards, and semantics in U.S. national topographic mapping databases

USGS Publications Warehouse

Varanka, Dalia

2009-01-01

The objective of this paper is to examine the contrast between local, field-surveyed topographical representation and feature representation in digital, centralized databases and to clarify their ontological implications. The semantics of these two approaches are contrasted by examining the categorization of features by subject domains inherent to national topographic mapping. When comparing five USGS topographic mapping domain and feature lists, results indicate that multiple semantic meanings and ontology rules were applied to the initial digital database, but were lost as databases became more centralized at national scales, and common semantics were replaced by technological terms.

Stochastic formulation of patient positioning using linac-mounted cone beam imaging with prior knowledge

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

Hoegele, W.; Loeschel, R.; Dobler, B.

2011-02-15

Purpose: In this work, a novel stochastic framework for patient positioning based on linac-mounted CB projections is introduced. Based on this formulation, the most probable shifts and rotations of the patient are estimated, incorporating interfractional deformations of patient anatomy and other uncertainties associated with patient setup. Methods: The target position is assumed to be defined by and is stochastically determined from positions of various features such as anatomical landmarks or markers in CB projections, i.e., radiographs acquired with a CB-CT system. The patient positioning problem of finding the target location from CB projections is posed as an inverse problem withmore » prior knowledge and is solved using a Bayesian maximum a posteriori (MAP) approach. The prior knowledge is three-fold and includes the accuracy of an initial patient setup (such as in-room laser and skin marks), the plasticity of the body (relative shifts between target and features), and the feature detection error in CB projections (which may vary depending on specific detection algorithm and feature type). For this purpose, MAP estimators are derived and a procedure of using them in clinical practice is outlined. Furthermore, a rule of thumb is theoretically derived, relating basic parameters of the prior knowledge (initial setup accuracy, plasticity of the body, and number of features) and the parameters of CB data acquisition (number of projections and accuracy of feature detection) to the expected estimation accuracy. Results: MAP estimation can be applied to arbitrary features and detection algorithms. However, to experimentally demonstrate its applicability and to perform the validation of the algorithm, a water-equivalent, deformable phantom with features represented by six 1 mm chrome balls were utilized. These features were detected in the cone beam projections (XVI, Elekta Synergy) by a local threshold method for demonstration purposes only. The accuracy of estimation (strongly varying for different plasticity parameters of the body) agreed with the rule of thumb formula. Moreover, based on this rule of thumb formula, about 20 projections for 6 detectable features seem to be sufficient for a target estimation accuracy of 0.2 cm, even for relatively large feature detection errors with standard deviation of 0.5 cm and spatial displacements of the features with standard deviation of 0.5 cm. Conclusions: The authors have introduced a general MAP-based patient setup algorithm accounting for different sources of uncertainties, which are utilized as the prior knowledge in a transparent way. This new framework can be further utilized for different clinical sites, as well as theoretical developments in the field of patient positioning for radiotherapy.« less

Contrast normalization contributes to a biologically-plausible model of receptive-field development in primary visual cortex (V1)

PubMed Central

Willmore, Ben D.B.; Bulstrode, Harry; Tolhurst, David J.

2012-01-01

Neuronal populations in the primary visual cortex (V1) of mammals exhibit contrast normalization. Neurons that respond strongly to simple visual stimuli – such as sinusoidal gratings – respond less well to the same stimuli when they are presented as part of a more complex stimulus which also excites other, neighboring neurons. This phenomenon is generally attributed to generalized patterns of inhibitory connections between nearby V1 neurons. The Bienenstock, Cooper and Munro (BCM) rule is a neural network learning rule that, when trained on natural images, produces model neurons which, individually, have many tuning properties in common with real V1 neurons. However, when viewed as a population, a BCM network is very different from V1 – each member of the BCM population tends to respond to the same dominant features of visual input, producing an incomplete, highly redundant code for visual information. Here, we demonstrate that, by adding contrast normalization into the BCM rule, we arrive at a neurally-plausible Hebbian learning rule that can learn an efficient sparse, overcomplete representation that is a better model for stimulus selectivity in V1. This suggests that one role of contrast normalization in V1 is to guide the neonatal development of receptive fields, so that neurons respond to different features of visual input. PMID:22230381

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

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.

Riparian Protection Rules for Oregon Forests

Treesearch

George G. Ice; Robert L. Beschta; Raymond S. Craig; James R. Sedell

1989-01-01

Forest Practice Rules under the Oregon Forest Practices Act were modified in 1987 to increase protection of riparian areas adjacent to timber harvest operations. These modifications addressed concerns about water quality protection and retaining trees as sources of large woody debris for future stream channel structure. The rule changes triggered debate about the...

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

NASA Technical Reports Server (NTRS)

Hendler, James

1986-01-01

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

The typical structure of tornado proximity soundings

NASA Astrophysics Data System (ADS)

Schaefer, Joseph T.; Livingston, Richard L.

1988-05-01

An objective scheme based on empirical orthogonal function analysis to detect patterns in a single or multivariate data set is developed and applied to rawinsonde observations taken in the near-tornado environment. If only temperature data are considered, two distinct categories, differentiated chiefly by the tropopause height, are found. When moisture observations are included with the temperatures, the separation between categories becomes less distinct. However, it is noted that within the near-tornado environment there is an inverse relationship between the degree of observed convective and conditional instability. Analysis of only the winds shows that a low-level veering with height is the rule. However, the strength of the veering can vary considerably. When the temperature, moisture, and winds are treated in concert, two categories again appear. One group occurs with strong winds and a low tropopause, while the other group features weak winds and a high tropopause. These groups correspond to "springtime" and "summertime" synoptic situations, respectively. Comparisons of the various analyses indicate that the near-tornado environment typically features a balance between the strength of the veering of the winds and the amount of conditional instability present. Summer tornadoes feature strong conditional instability and weak winds, while springtime tornadoes occur with stronger veering and convective instability. The strongest tornadoes occur with springtime-type conditions.

Breaking the rules of the game: Ethical implications for nursing practice and education.

PubMed

Milton, Constance L

2006-07-01

Rules in games are fundamental to the ethics of practice. Rules provide a context or space where a game is defined and played. Throughout human life, games may be formalized with written and unwritten rules. Imaginations may be sparked in the creative structuring of new, informal games. Formal and informal rules can serve to provide direction for what may be viewed as decorum and appropriate behavior with professional groups. In this column, the author illuminates possible ethical meanings for rule-making and breaking with implications for nursing practice and education from a nursing theoretical perspective.

The diversity of H3 loops determines the antigen-binding tendencies of antibody CDR loops.

PubMed

Tsuchiya, Yuko; Mizuguchi, Kenji

2016-04-01

Of the complementarity-determining regions (CDRs) of antibodies, H3 loops, with varying amino acid sequences and loop lengths, adopt particularly diverse loop conformations. The diversity of H3 conformations produces an array of antigen recognition patterns involving all the CDRs, in which the residue positions actually in contact with the antigen vary considerably. Therefore, for a deeper understanding of antigen recognition, it is necessary to relate the sequence and structural properties of each residue position in each CDR loop to its ability to bind antigens. In this study, we proposed a new method for characterizing the structural features of the CDR loops and obtained the antigen-binding ability of each residue position in each CDR loop. This analysis led to a simple set of rules for identifying probable antigen-binding residues. We also found that the diversity of H3 loop lengths and conformations affects the antigen-binding tendencies of all the CDR loops. © 2016 The Protein Society.

Microfluidic perfusion shows intersarcomere dynamics within single skeletal muscle myofibrils

PubMed Central

Minozzo, Fabio C.; Altman, David; Rassier, Dilson E.

2017-01-01

The sarcomere is the smallest functional unit of myofibrils in striated muscles. Sarcomeres are connected in series through a network of elastic and structural proteins. During myofibril activation, sarcomeres develop forces that are regulated through complex dynamics among their structures. The mechanisms that regulate intersarcomere dynamics are unclear, which limits our understanding of fundamental muscle features. Such dynamics are associated with the loss in forces caused by mechanical instability encountered in muscle diseases and cardiomyopathy and may underlie potential target treatments for such conditions. In this study, we developed a microfluidic perfusion system to control one sarcomere within a myofibril, while measuring the individual behavior of all sarcomeres. We found that the force from one sarcomere leads to adjustments of adjacent sarcomeres in a mechanism that is dependent on the sarcomere length and the myofibril stiffness. We concluded that the cooperative work of the contractile and the elastic elements within a myofibril rules the intersarcomere dynamics, with important consequences for muscle contraction. PMID:28765372

Examining Neuronal Connectivity and Its Role in Learning and Memory

NASA Astrophysics Data System (ADS)

Gala, Rohan

Learning and long-term memory formation are accompanied with changes in the patterns and weights of synaptic connections in the underlying neuronal network. However, the fundamental rules that drive connectivity changes, and the precise structure-function relationships within neuronal networks remain elusive. Technological improvements over the last few decades have enabled the observation of large but specific subsets of neurons and their connections in unprecedented detail. Devising robust and automated computational methods is critical to distill information from ever-increasing volumes of raw experimental data. Moreover, statistical models and theoretical frameworks are required to interpret the data and assemble evidence into understanding of brain function. In this thesis, I first describe computational methods to reconstruct connectivity based on light microscopy imaging experiments. Next, I use these methods to quantify structural changes in connectivity based on in vivo time-lapse imaging experiments. Finally, I present a theoretical model of associative learning that can explain many stereotypical features of experimentally observed connectivity.

[Connections between fiscal federalism and the funding of the Brazilian health care policy].

PubMed

de Lima, Luciana Dias

2007-01-01

In the Brazilian society's context of meager financial resources for health care, associated with structural features of fiscal federalism and with the current model of funding transfers for the Unified Health System's (SUS), important inequities directly impact political negotiations and the deployment of federal financing alternatives which are not directly linked to the supply and production of health care activities and services by states and municipalities. We observed that health policies, since the second half of the nineties, have developed their own mechanisms that, in the above mentioned context, tend to accommodate different interests and federative conflicts generated by structural factors and by institutional rules. However, the absence of an integrated planning program between the criteria to establish resource redistribution for financing the Unified Health System and the Brazilian Federation's fiscal sharing system, end up reinforcing certain asymmetric patterns and generating new imbalances, making the compensation of inequities difficult in public health spending at the sub-national domain.

Absence of Local Fluctuating Dimers in Superconducting Ir 1-x(Pt,Rh) xTe 2

DOE PAGES

Yu, Runze; Banerjee, S.; Lei, H. C.; ...

2018-06-01

The compound IrTe2 is known to exhibit a transition to a modulated state featuring Ir-Ir dimers, with large associated atomic displacements. Partial substitution of Pt or Rh for Ir destabilizes the modulated structure and induces superconductivity. It has been proposed that quantum critical dimer fluctuations might be associated with the superconductivity. Here we test for such local dimer correlations and demonstrate their absence. X-ray pair distribution function approach reveals that the local structure of Ir 0.95Pt 0.05Te 2 and Ir 0.8Rh 0.2Te 2 dichalcogenide superconductors with compositions just past the dimer/superconductor boundary is explained well by a dimer-free model downmore » to 10 K, ruling out the possibility of there being nanoscale dimer fluctuations in this regime. This is inconsistent with the proposed quantum-critical-point-like interplay of the dimer state and superconductivity, and precludes scenarios for dimer fluctuations mediated superconducting pairing.« less

Absence of Local Fluctuating Dimers in Superconducting Ir 1-x(Pt,Rh) xTe 2

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

Yu, Runze; Banerjee, S.; Lei, H. C.

The compound IrTe2 is known to exhibit a transition to a modulated state featuring Ir-Ir dimers, with large associated atomic displacements. Partial substitution of Pt or Rh for Ir destabilizes the modulated structure and induces superconductivity. It has been proposed that quantum critical dimer fluctuations might be associated with the superconductivity. Here we test for such local dimer correlations and demonstrate their absence. X-ray pair distribution function approach reveals that the local structure of Ir 0.95Pt 0.05Te 2 and Ir 0.8Rh 0.2Te 2 dichalcogenide superconductors with compositions just past the dimer/superconductor boundary is explained well by a dimer-free model downmore » to 10 K, ruling out the possibility of there being nanoscale dimer fluctuations in this regime. This is inconsistent with the proposed quantum-critical-point-like interplay of the dimer state and superconductivity, and precludes scenarios for dimer fluctuations mediated superconducting pairing.« less

Absence of local fluctuating dimers in superconducting Ir1 -x(Pt,Rh ) xTe2

NASA Astrophysics Data System (ADS)

Yu, Runze; Banerjee, S.; Lei, H. C.; Sinclair, Ryan; Abeykoon, M.; Zhou, H. D.; Petrovic, C.; Guguchia, Z.; Bozin, E. S.

2018-05-01

The compound IrTe2 is known to exhibit a transition to a modulated state featuring Ir-Ir dimers, with large associated atomic displacements. Partial substitution of Pt or Rh for Ir destabilizes the modulated structure and induces superconductivity. It has been proposed that quantum critical dimer fluctuations might be associated with the superconductivity. Here we test for such local dimer correlations and demonstrate their absence. X-ray pair distribution function approach reveals that the local structure of Ir0 :95Pt0 :05Te2 and Ir0 :8Rh0 :2Te2 dichalcogenide superconductors with compositions just past the dimer/superconductor boundary is explained well by a dimer-free model down to 10 K, ruling out the possibility of there being nanoscale dimer fluctuations in this regime. This is inconsistent with the proposed quantum-critical-point-like interplay of the dimer state and superconductivity, and precludes scenarios for dimer fluctuations mediated superconducting pairing.

Vibrational monitor of early demineralization in tooth enamel after in vitro exposure to phosphoridic liquid

NASA Astrophysics Data System (ADS)

Pezzotti, Giuseppe; Adachi, Tetsuya; Gasparutti, Isabella; Vincini, Giulio; Zhu, Wenliang; Boffelli, Marco; Rondinella, Alfredo; Marin, Elia; Ichioka, Hiroaki; Yamamoto, Toshiro; Marunaka, Yoshinori; Kanamura, Narisato

2017-02-01

The Raman spectroscopic method has been applied to quantitatively assess the in vitro degree of demineralization in healthy human teeth. Based on previous evaluations of Raman selection rules (empowered by an orientation distribution function (ODF) statistical algorithm) and on a newly proposed analysis of phonon density of states (PDOS) for selected vibrational modes of the hexagonal structure of hydroxyapatite, a molecular-scale evaluation of the demineralization process upon in vitro exposure to a highly acidic beverage (i.e., CocaCola™ Classic, pH = 2.5) could be obtained. The Raman method proved quite sensitive and spectroscopic features could be directly related to an increase in off-stoichiometry of the enamel surface structure since the very early stage of the demineralization process (i.e., when yet invisible to other conventional analytical techniques). The proposed Raman spectroscopic algorithm might possess some generality for caries risk assessment, allowing a prompt non-contact diagnostic practice in dentistry.

Dendritic branching angles of pyramidal cells across layers of the juvenile rat somatosensory cortex.

PubMed

Leguey, Ignacio; Bielza, Concha; Larrañaga, Pedro; Kastanauskaite, Asta; Rojo, Concepción; Benavides-Piccione, Ruth; DeFelipe, Javier

2016-09-01

The characterization of the structural design of cortical microcircuits is essential for understanding how they contribute to function in both health and disease. Since pyramidal neurons represent the most abundant neuronal type and their dendritic spines constitute the major postsynaptic elements of cortical excitatory synapses, our understanding of the synaptic organization of the neocortex largely depends on the available knowledge regarding the structure of pyramidal cells. Previous studies have identified several apparently common rules in dendritic geometry. We study the dendritic branching angles of pyramidal cells across layers to further shed light on the principles that determine the geometric shapes of these cells. We find that the dendritic branching angles of pyramidal cells from layers II-VI of the juvenile rat somatosensory cortex suggest common design principles, despite the particular morphological and functional features that are characteristic of pyramidal cells in each cortical layer. J. Comp. Neurol. 524:2567-2576, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Co-assembly in chitosan-surfactant mixtures: thermodynamics, structures, interfacial properties and applications.

PubMed

Chiappisi, Leonardo; Gradzielski, Michael

2015-06-01

In this review, different aspects characterizing chitosan-surfactant mixtures are summarized and compared. Chitosan is a bioderived cationic polysaccharide that finds wide-ranged applications in various field, e.g., medical or food industry, in which synergistic effects with surfactant can play a fundamental role. In particular, the behavior of chitosan interacting with strong and weak anionic, nonionic as well as cationic surfactants is reviewed. We put a focus on oppositely charged systems, as they exhibit the most interesting features. In that context, we discuss the thermodynamic description of the interaction and in particular the structural changes as they occur as a function of the mixed systems and external parameters. Moreover, peculiar properties of chitosan coated phospholipid vesicles are summarized. Finally, their co-assembly at interfaces is briefly reviewed. Despite the behavior of the mentioned systems might strongly differ, resulting in a high variety of properties, few general rules can be pointed out which improve the understanding of such complex systems. Copyright © 2015 Elsevier B.V. All rights reserved.

Salient contour extraction from complex natural scene in night vision image

NASA Astrophysics Data System (ADS)

Han, Jing; Yue, Jiang; Zhang, Yi; Bai, Lian-fa

2014-03-01

The theory of center-surround interaction in non-classical receptive field can be applied in night vision information processing. In this work, an optimized compound receptive field modulation method is proposed to extract salient contour from complex natural scene in low-light-level (LLL) and infrared images. The kernel idea is that multi-feature analysis can recognize the inhomogeneity in modulatory coverage more accurately and that center and surround with the grouping structure satisfying Gestalt rule deserves high connection-probability. Computationally, a multi-feature contrast weighted inhibition model is presented to suppress background and lower mutual inhibition among contour elements; a fuzzy connection facilitation model is proposed to achieve the enhancement of contour response, the connection of discontinuous contour and the further elimination of randomly distributed noise and texture; a multi-scale iterative attention method is designed to accomplish dynamic modulation process and extract contours of targets in multi-size. This work provides a series of biologically motivated computational visual models with high-performance for contour detection from cluttered scene in night vision images.

GraDit: graph-based data repair algorithm for multiple data edits rule violations

NASA Astrophysics Data System (ADS)

Ode Zuhayeni Madjida, Wa; Gusti Bagus Baskara Nugraha, I.

2018-03-01

Constraint-based data cleaning captures data violation to a set of rule called data quality rules. The rules consist of integrity constraint and data edits. Structurally, they are similar, where the rule contain left hand side and right hand side. Previous research proposed a data repair algorithm for integrity constraint violation. The algorithm uses undirected hypergraph as rule violation representation. Nevertheless, this algorithm can not be applied for data edits because of different rule characteristics. This study proposed GraDit, a repair algorithm for data edits rule. First, we use bipartite-directed hypergraph as model representation of overall defined rules. These representation is used for getting interaction between violation rules and clean rules. On the other hand, we proposed undirected graph as violation representation. Our experimental study showed that algorithm with undirected graph as violation representation model gave better data quality than algorithm with undirected hypergraph as representation model.

Experimental validation of 3D printed material behaviors and their influence on the structural topology design

NASA Astrophysics Data System (ADS)

Yang, Kai Ke; Zhu, Ji Hong; Wang, Chuang; Jia, Dong Sheng; Song, Long Long; Zhang, Wei Hong

2018-05-01

The purpose of this paper is to investigate the structures achieved by topology optimization and their fabrications by 3D printing considering the particular features of material microstructures and macro mechanical performances. Combining Digital Image Correlation and Optical Microscope, this paper experimentally explored the anisotropies of stiffness and strength existing in the 3D printed polymer material using Stereolithography (SLA) and titanium material using Selective Laser Melting (SLM). The standard specimens and typical structures obtained by topology optimization were fabricated along different building directions. On the one hand, the experimental results of these SLA produced structures showed stable properties and obviously anisotropic rules in stiffness, ultimate strengths and places of fractures. Further structural designs were performed using topology optimization when the particular mechanical behaviors of SLA printed materials were considered, which resulted in better structural performances compared to the optimized designs using `ideal' isotropic material model. On the other hand, this paper tested the mechanical behaviors of SLM printed multiscale lattice structures which were fabricated using the same metal powder and the same machine. The structural stiffness values are generally similar while the strength behaviors show a difference, which are mainly due to the irregular surface quality of the tiny structural branches of the lattice. The above evidences clearly show that the consideration of the particular behaviors of 3D printed materials is therefore indispensable for structural design and optimization in order to improve the structural performance and strengthen their practical significance.

Experimental validation of 3D printed material behaviors and their influence on the structural topology design

NASA Astrophysics Data System (ADS)

Yang, Kai Ke; Zhu, Ji Hong; Wang, Chuang; Jia, Dong Sheng; Song, Long Long; Zhang, Wei Hong

2018-02-01

The purpose of this paper is to investigate the structures achieved by topology optimization and their fabrications by 3D printing considering the particular features of material microstructures and macro mechanical performances. Combining Digital Image Correlation and Optical Microscope, this paper experimentally explored the anisotropies of stiffness and strength existing in the 3D printed polymer material using Stereolithography (SLA) and titanium material using Selective Laser Melting (SLM). The standard specimens and typical structures obtained by topology optimization were fabricated along different building directions. On the one hand, the experimental results of these SLA produced structures showed stable properties and obviously anisotropic rules in stiffness, ultimate strengths and places of fractures. Further structural designs were performed using topology optimization when the particular mechanical behaviors of SLA printed materials were considered, which resulted in better structural performances compared to the optimized designs using `ideal' isotropic material model. On the other hand, this paper tested the mechanical behaviors of SLM printed multiscale lattice structures which were fabricated using the same metal powder and the same machine. The structural stiffness values are generally similar while the strength behaviors show a difference, which are mainly due to the irregular surface quality of the tiny structural branches of the lattice. The above evidences clearly show that the consideration of the particular behaviors of 3D printed materials is therefore indispensable for structural design and optimization in order to improve the structural performance and strengthen their practical significance.

Learning of Monotonic and Nonmonotonic Sequences in Domesticated Horses ("Equus Callabus") and Chickens ("Gallus Domesticus")

ERIC Educational Resources Information Center

Kundey, Shannon M. A.; Strandell, Brittany; Mathis, Heather; Rowan, James D.

2010-01-01

(Hulse and Dorsky, 1977) and (Hulse and Dorsky, 1979) found that rats, like humans, learn sequences following a simple rule-based structure more quickly than those lacking a rule-based structure. Through two experiments, we explored whether two additional species--domesticated horses ("Equus callabus") and chickens ("Gallus domesticus")--would…

Implications and challenges for implementation of the FDA’s final deeming rule for waterpipe tobacco

PubMed Central

Sutfin, Erin L; Soule, Eric K; McKelvey, Karma; Jenson, Desmond

2017-01-01

For the first time, the Food and Drug Administration’s (FDAs) Center for Tobacco Products now has regulatory authority over all tobacco products, including waterpipe tobacco. In the rule expanding its authority to cover all tobacco products, the FDA uses largely a one-size-fits-all approach. However, several aspects of waterpipe tobacco smoking make it unique from other tobacco products, which may require more specific, tailored rules. This paper describes the distinct features of waterpipe tobacco products and accessories, and identifies unique challenges to the current regulation posed by this form of tobacco use. Additionally, we highlight the need for further research-generated evidence to support additional rulemaking. PMID:28667092

Multilocality and fusion rules on the generalized structure functions in two-dimensional and three-dimensional Navier-Stokes turbulence.

PubMed

Gkioulekas, Eleftherios

2016-09-01

Using the fusion-rules hypothesis for three-dimensional and two-dimensional Navier-Stokes turbulence, we generalize a previous nonperturbative locality proof to multiple applications of the nonlinear interactions operator on generalized structure functions of velocity differences. We call this generalization of nonperturbative locality to multiple applications of the nonlinear interactions operator "multilocality." The resulting cross terms pose a new challenge requiring a new argument and the introduction of a new fusion rule that takes advantage of rotational symmetry. Our main result is that the fusion-rules hypothesis implies both locality and multilocality in both the IR and UV limits for the downscale energy cascade of three-dimensional Navier-Stokes turbulence and the downscale enstrophy cascade and inverse energy cascade of two-dimensional Navier-Stokes turbulence. We stress that these claims relate to nonperturbative locality of generalized structure functions on all orders and not the term-by-term perturbative locality of diagrammatic theories or closure models that involve only two-point correlation and response functions.

Leonardo's branching rule in trees: How self-similar structures resist wind

NASA Astrophysics Data System (ADS)

Eloy, Christophe

2011-11-01

In his notebooks, Leonardo da Vinci observed that ``all the branches of a tree at every stage of its height when put together are equal in thickness to the trunk,'' which means that the total cross-sectional area of branches is conserved across branching nodes. The usual explanation for this rule involves vascular transport of sap, but this argument is questionable because the portion of wood devoted to transport varies across species and can be as low as 5%. It is proposed here that Leonardo's rule is a consequence of the tree skeleton having a self-similar structure and the branch diameters being adjusted to resist wind-induced loads. To address this problem, a continuous model is first considered by neglecting the geometrical details of branching and wind incident angles. The robustness of this analytical model is then assessed with numerical simulations on tree skeletons generated with a simple branching rule producing self-similar structures. This study was supported by the European Union through the fellowship PIOF-GA-2009-252542.

Spin structure of the neutron ({sup 3}He) and the Bjoerken sum rule

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

Meziani, Z.E.

1994-12-01

A first measurement of the longitudinal asymmetry of deep-inelastic scattering of polarized electrons from a polarized {sup 3}He target at energies ranging from 19 to 26 GeV has been performed at the Stanford Linear Accelerator Center (SLAC). The spin-structure function of the neutron g{sub 1}{sup n} has been extracted from the measured asymmetries. The Quark Parton Model (QPM) interpretation of the nucleon spin-structure function is examined in light of the new results. A test of the Ellis-Jaffe sum rule (E-J) on the neutron is performed at high momentum transfer and found to be satisfied. Furthermore, combining the proton results ofmore » the European Muon Collaboration (EMC) and the neutron results of E-142, the Bjoerken sum rule test is carried at high Q{sup 2} where higher order Perturbative Quantum Chromodynamics (PQCD) corrections and higher-twist corrections are smaller. The sum rule is saturated to within one standard deviation.« less

Spatial-pattern-induced evolution of a self-replicating loop network.

PubMed

Suzuki, Keisuke; Ikegami, Takashi

2006-01-01

We study a system of self-replicating loops in which interaction rules between individuals allow competition that leads to the formation of a hypercycle-like network. The main feature of the model is the multiple layers of interaction between loops, which lead to both global spatial patterns and local replication. The network of loops manifests itself as a spiral structure from which new kinds of self-replicating loops emerge at the boundaries between different species. In these regions, larger and more complex self-replicating loops live for longer periods of time, managing to self-replicate in spite of their slower replication. Of particular interest is how micro-scale interactions between replicators lead to macro-scale spatial pattern formation, and how these macro-scale patterns in turn perturb the micro-scale replication dynamics.

The molecular dynamics simulation on the mechanical properties of Ni glass with external pressure

NASA Astrophysics Data System (ADS)

Zhang, Chuan-Hui; Wang, Ying; Sun, Dong-Bai

2017-08-01

In this paper, rapid quenching of Ni from crystal to metallic glass (MG) at different external pressures is simulated by molecular dynamics. The pair distribution functions (PDFs), mean-square displacement, glass transition temperature (Tg) and elastic property are calculated and compared with each other. The split of the second PDF peak means the liquid’s transition to glass state starts as previously reported for other MGs. And the Ri/R1 ratio rule is found to hold very well in Ni MG and reveals the SPO structural feature in the configurations. Moreover, with high external pressure, Tg values are more approximated by density-temperature and enthalpy-temperature curves. At last, the elastic modulus and mechanics modulus of quenching models produced a monotonous effect with increasing external pressure and temperature.

English Voicing in Dimensional Theory*

PubMed Central

Iverson, Gregory K.; Ahn, Sang-Cheol

2007-01-01

Assuming a framework of privative features, this paper interprets two apparently disparate phenomena in English phonology as structurally related: the lexically specific voicing of fricatives in plural nouns like wives or thieves and the prosodically governed “flapping” of medial /t/ (and /d/) in North American varieties, which we claim is itself not a rule per se, but rather a consequence of the laryngeal weakening of fortis /t/ in interaction with speech-rate determined segmental abbreviation. Taking as our point of departure the Dimensional Theory of laryngeal representation developed by Avery & Idsardi (2001), along with their assumption that English marks voiceless obstruents but not voiced ones (Iverson & Salmons 1995), we find that an unexpected connection between fricative voicing and coronal flapping emerges from the interplay of familiar phonemic and phonetic factors in the phonological system. PMID:18496590

Energy Extraction from a Slider-Crank Wave Energy under Irregular Wave Conditions: Preprint

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

Sang, Yuanrui; Karayaka, H. Bora; Yan, Yanjun

2015-08-24

A slider-crank wave energy converter (WEC) is a novel energy conversion device. It converts wave energy into electricity at a relatively high efficiency, and it features a simple structure. Past analysis on this particular WEC has been done under regular sinusoidal wave conditions, and suboptimal energy could be achieved. This paper presents the analysis of the system under irregular wave conditions; a time-domain hydrodynamics model is adopted and a rule-based control methodology is introduced to better serve the irregular wave conditions. Results from the simulations show that the performance of the system under irregular wave conditions is different from thatmore » under regular sinusoidal wave conditions, but a reasonable amount of energy can still be extracted.« less

Energy Extraction from a Slider-Crank Wave Energy Converter under Irregular Wave Conditions

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

Sang, Yuanrui; Karayaka, H. Bora; Yan, Yanjun

2015-10-19

A slider-crank wave energy converter (WEC) is a novel energy conversion device. It converts wave energy into electricity at a relatively high efficiency, and it features a simple structure. Past analysis on this particular WEC has been done under regular sinusoidal wave conditions, and suboptimal energy could be achieved. This paper presents the analysis of the system under irregular wave conditions; a time-domain hydrodynamics model is adopted and a rule-based control methodology is introduced to better serve the irregular wave conditions. Results from the simulations show that the performance of the system under irregular wave conditions is different from thatmore » under regular sinusoidal wave conditions, but a reasonable amount of energy can still be extracted.« less

The complete O (αs2) non-singlet heavy flavor corrections to the structure functions g1,2ep (x ,Q2), F1,2,Lep (x ,Q2), F1,2,3ν (ν bar) (x ,Q2) and the associated sum rules

NASA Astrophysics Data System (ADS)

Blümlein, Johannes; Falcioni, Giulio; De Freitas, Abilio

2016-09-01

We calculate analytically the flavor non-singlet O (αs2) massive Wilson coefficients for the inclusive neutral current non-singlet structure functions F1,2,Lep (x ,Q2) and g1,2ep (x ,Q2) and charged current non-singlet structure functions F1,2,3ν (ν bar) p (x ,Q2), at general virtualities Q2 in the deep-inelastic region. Numerical results are presented. We illustrate the transition from low to large virtualities for these observables, which may be contrasted to basic assumptions made in the so-called variable flavor number scheme. We also derive the corresponding results for the Adler sum rule, the unpolarized and polarized Bjorken sum rules and the Gross-Llewellyn Smith sum rule. There are no logarithmic corrections at large scales Q2 and the effects of the power corrections due to the heavy quark mass are of the size of the known O (αs4) corrections in the case of the sum rules. The complete charm and bottom corrections are compared to the approach using asymptotic representations in the region Q2 ≫mc,b2. We also study the target mass corrections to the above sum rules.

The mass media destabilizes the cultural homogenous regime in Axelrod's model

NASA Astrophysics Data System (ADS)

Peres, Lucas R.; Fontanari, José F.

2010-02-01

An important feature of Axelrod's model for culture dissemination or social influence is the emergence of many multicultural absorbing states, despite the fact that the local rules that specify the agents interactions are explicitly designed to decrease the cultural differences between agents. Here we re-examine the problem of introducing an external, global interaction—the mass media—in the rules of Axelrod's model: in addition to their nearest neighbors, each agent has a certain probability p to interact with a virtual neighbor whose cultural features are fixed from the outset. Most surprisingly, this apparently homogenizing effect actually increases the cultural diversity of the population. We show that, contrary to previous claims in the literature, even a vanishingly small value of p is sufficient to destabilize the homogeneous regime for very large lattice sizes.

A Short Note on Rules and Higher Order Rules.

ERIC Educational Resources Information Center

Scandura, Joseph M.

This brief paper argues that structural analysis--an extended form of cognitive task analysis--demonstrates that both domain dependent and domain independent knowledge can be derived from specific content domains. It is noted that the major difference between the two is that lower order rules (specific knowledge) are derived directly from specific…

Mathematics and Structural Learning. Final Report.

ERIC Educational Resources Information Center

Scandura, Joseph M.

This report contains four papers describing research based on the view of mathematical knowledge as a hierarchy of "rules." The first paper: "The Role of Rules in Behavior" was abstracted in ED 040 036 (October 1970). The second paper: "A Theory of Mathematical Knowledge" defends the thesis that rules are the basic building blocks of mathematical…

Rule-Based and Information-Integration Category Learning in Normal Aging

ERIC Educational Resources Information Center

Maddox, W. Todd; Pacheco, Jennifer; Reeves, Maia; Zhu, Bo; Schnyer, David M.

2010-01-01

The basal ganglia and prefrontal cortex play critical roles in category learning. Both regions evidence age-related structural and functional declines. The current study examined rule-based and information-integration category learning in a group of older and younger adults. Rule-based learning is thought to involve explicit, frontally mediated…

Learning General Phonological Rules from Distributional Information: A Computational Model

ERIC Educational Resources Information Center

Calamaro, Shira; Jarosz, Gaja

2015-01-01

Phonological rules create alternations in the phonetic realizations of related words. These rules must be learned by infants in order to identify the phonological inventory, the morphological structure, and the lexicon of a language. Recent work proposes a computational model for the learning of one kind of phonological alternation, allophony…

Parental Monitoring Behaviors: A Model of Rules, Supervision, and Conflict

ERIC Educational Resources Information Center

Hayes, Louise; Hudson, Alan; Matthews, Jan

2004-01-01

A model of parental monitoring behaviors, comprising rule setting and supervision, was proposed. The hypothesized relationship between rules, supervision, conflict, and adolescent problem behavior was tested using structured equation modeling on self-report data from 1,285 adolescents aged 14 to 15 years. The model was an adequate fit of the data,…

Using the Functional Prerequisites to Communication Rules as a Structure for Rule-Behavior Research.

ERIC Educational Resources Information Center

Fairhurst, Gail Theus

This paper points out that the available research on communication rules tends to be descriptive (or humanistic) in nature and characterized by a conspicuous absence of prediction along with experimental methods and parametric interpretations of social behavior. The paper first argues that current scientific methodology is consistent with a…

Progressive multifocal leukoence--phalopathy presenting as homonymous hemianopia in a patient with acquired immunodeficiency syndrome.

PubMed

Pandey, Amit; Bandivdekar, Karishma; Ramchandani, Suresh; Ramchandani, Sushama

2012-01-01

We present a case of a Human Immunodeficiency Virus (HIV) positive patient who was referred for retinal evaluation to rule out ophthalmic manifestations of Acquired Immunodeficiency Syndrome (AIDS). She complained of some disturbance in vision in both eyes. Fundus examination showed no abnormality. Perimetry, done to rule out optic nerve pathology, showed a left homonymous hemianopia. Magnetic Resonance Imaging (MRI) scan showed features of Progressive Multifocal Leukoencephalopathy (PML). She had no other neurological symptoms or signs.

Assembly of objects with not fully predefined shapes

NASA Technical Reports Server (NTRS)

Arlotti, M. A.; Dimartino, V.

1989-01-01

An assembly problem in a non-deterministic environment, i.e., where parts to be assembled have unknown shape, size and location, is described. The only knowledge used by the robot to perform the assembly operation is given by a connectivity rule and geometrical constraints concerning parts. Once a set of geometrical features of parts has been extracted by a vision system, applying such a rule allows the dtermination of the composition sequence. A suitable sensory apparatus allows the control the whole operation.

RCRA, superfund and EPCRA hotline training module. Introduction to: RCRA corrective action updated July 1996

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

NONE

1996-07-01

The module discusses the regulatory and statutory requirements and authorities governing the Resource Conservation and Recovery Act (RCRA) corrective action process. There are minimal regulatory requirements at present, but the Agency has issued a proposed rule (55 FR 30798; July 27, 1990) that would establish a comprehensive regulatory framework for implementing the corrective action program. This proposed rule and other guidance developed pursuant to statutory authorities are used to structure corrective action requirements in facility permits and orders. This module describes the current statutory and regulatory structure and discusses the future of the proposed rule.

Evaluation of SARs for the prediction of eye irritation/corrosion potential: structural inclusion rules in the BfR decision support system.

PubMed

Tsakovska, I; Saliner, A Gallegos; Netzeva, T; Pavan, M; Worth, A P

2007-01-01

The proposed REACH regulation within the European Union (EU) aims to minimise the number of laboratory animals used for human hazard and risk assessment while ensuring adequate protection of human health and the environment. One way to achieve this goal is to develop non-testing methods, such as (quantitative) structure-activity relationships ([Q]SARs), suitable for identifying toxicological hazard from chemical structure and physicochemical properties alone. A database containing data submitted within the EU New Chemicals Notification procedure was compiled by the German Bundesinstitut für Risikobewertung (BfR). On the basis of these data, the BfR built a decision support system (DSS) for the prediction of several toxicological endpoints. For the prediction of eye irritation and corrosion potential, the DSS contains 31 physicochemical exclusion rules evaluated previously by the European Chemicals Bureau (ECB), and 27 inclusion rules that define structural alerts potentially responsible for eye irritation and/or corrosion. This work summarises the results of a study carried out by the ECB to assess the performance of the BfR structural rulebase. The assessment included: (a) evaluation of the structural alerts by using the training set of 1341 substances with experimental data for eye irritation and corrosion; and (b) external validation by using an independent test set of 199 chemicals. Recommendations are made for the further development of the structural rules in order to increase the overall predictivity of the DSS.

Nondeterministic data base for computerized visual perception

NASA Technical Reports Server (NTRS)

Yakimovsky, Y.

1976-01-01

A description is given of the knowledge representation data base in the perception subsystem of the Mars robot vehicle prototype. Two types of information are stored. The first is generic information that represents general rules that are conformed to by structures in the expected environments. The second kind of information is a specific description of a structure, i.e., the properties and relations of objects in the specific case being analyzed. The generic knowledge is represented so that it can be applied to extract and infer the description of specific structures. The generic model of the rules is substantially a Bayesian representation of the statistics of the environment, which means it is geared to representation of nondeterministic rules relating properties of, and relations between, objects. The description of a specific structure is also nondeterministic in the sense that all properties and relations may take a range of values with an associated probability distribution.

Multimap formation in visual cortex

PubMed Central

Jain, Rishabh; Millin, Rachel; Mel, Bartlett W.

2015-01-01

An extrastriate visual area such as V2 or V4 contains neurons selective for a multitude of complex shapes, all sharing a common topographic organization. Simultaneously developing multiple interdigitated maps—hereafter a “multimap”—is challenging in that neurons must compete to generate a diversity of response types locally, while cooperating with their dispersed same-type neighbors to achieve uniform visual field coverage for their response type at all orientations, scales, etc. Previously proposed map development schemes have relied on smooth spatial interaction functions to establish both topography and columnar organization, but by locally homogenizing cells' response properties, local smoothing mechanisms effectively rule out multimap formation. We found in computer simulations that the key requirements for multimap development are that neurons are enabled for plasticity only within highly active regions of cortex designated “learning eligibility regions” (LERs), but within an LER, each cell's learning rate is determined only by its activity level with no dependence on location. We show that a hybrid developmental rule that combines spatial and activity-dependent learning criteria in this way successfully produces multimaps when the input stream contains multiple distinct feature types, or in the degenerate case of a single feature type, produces a V1-like map with “salt-and-pepper” structure. Our results support the hypothesis that cortical maps containing a fine mixture of different response types, whether in monkey extrastriate cortex, mouse V1 or elsewhere in the cortex, rather than signaling a breakdown of map formation mechanisms at the fine scale, are a product of a generic cortical developmental scheme designed to map cells with a diversity of response properties across a shared topographic space. PMID:26641946

The Effects of Focused/Unfocused Audio-Appended Reading Tasks on Intermediate Female EFL Learners' Written Accuracy

ERIC Educational Resources Information Center

Alavinia, Parviz; Shafaei, Ali; Salimi, Asghar

2018-01-01

The current research study was conducted to examine the impacts of focused and unfocused audio-appended reading tasks on female EFL learners' acquisition of a rule-bound structure (passive voice) and a non-rule-bound structure (prepositions). The participants of this study involved ninety intermediate female English learners. They were assigned…

Human-like, population-level specialization in the manufacture of pandanus tools by New Caledonian crows Corvus moneduloides.

PubMed Central

Hunt, G R

2000-01-01

The main way of gaining insight into the behaviour and neurological faculties of our early ancestors is to study artefactual evidence for the making and use of tools, but this places severe constraints on what knowledge can be obtained. New Caledonian crows, however, offer a potential analogous model system for learning about these difficult-to-establish aspects of prehistoric humans. I found new evidence of human-like specialization in crows' manufacture of hook tools from pandanus leaves: functional lateralization or 'handedness' and the shaping of these tools to a rule system. These population-level features are unprecedented in the tool behaviour of free-living non-humans and provide the first demonstration that a population bias for handedness in tool-making and the shaping of tools to rule systems are not concomitant with symbolic thought and language. It is unknown how crows obtain their tool behaviour. Nevertheless, at the least they can be studied in order to learn about the neuropsychology associated with early specialized and/or advanced population features in tool-making such as hook use, handedness and the shaping of tools to rule systems. PMID:10722223

Evaluating MEDEVAC Force Structure Requirements Using an Updated Army Scenario, Total Army Analysis Admission Data, Monte Carlo Simulation, and Theater Structure.

PubMed

Fulton, Lawrence; Kerr, Bernie; Inglis, James M; Brooks, Matthew; Bastian, Nathaniel D

2015-07-01

In this study, we re-evaluate air ambulance requirements (rules of allocation) and planning considerations based on an Army-approved, Theater Army Analysis scenario. A previous study using workload only estimated a requirement of 0.4 to 0.6 aircraft per admission, a significant bolus over existence-based rules. In this updated study, we estimate requirements for Phase III (major combat operations) using a simulation grounded in previously published work and Phase IV (stability operations) based on four rules of allocation: unit existence rules, workload factors, theater structure (geography), and manual input. This study improves upon previous work by including the new air ambulance mission requirements of Department of Defense 51001.1, Roles and Functions of the Services, by expanding the analysis over two phases, and by considering unit rotation requirements known as Army Force Generation based on Department of Defense policy. The recommendations of this study are intended to inform future planning factors and already provided decision support to the Army Aviation Branch in determining force structure requirements. Reprint & Copyright © 2015 Association of Military Surgeons of the U.S.

Tendency to occupy a statistically dominant spatial state of the flow as a driving force for turbulent transition.

PubMed

Chekmarev, Sergei F

2013-03-01

The transition from laminar to turbulent fluid motion occurring at large Reynolds numbers is generally associated with the instability of the laminar flow. On the other hand, since the turbulent flow characteristically appears in the form of spatially localized structures (e.g., eddies) filling the flow field, a tendency to occupy such a structured state of the flow cannot be ruled out as a driving force for turbulent transition. To examine this possibility, we propose a simple analytical model that treats the flow as a collection of localized spatial structures, each of which consists of elementary cells in which the behavior of the particles (atoms or molecules) is uncorrelated. This allows us to introduce the Reynolds number, associating it with the ratio between the total phase volume for the system and that for the elementary cell. Using the principle of maximum entropy to calculate the most probable size distribution of the localized structures, we show that as the Reynolds number increases, the elementary cells group into the localized structures, which successfully explains turbulent transition and some other general properties of turbulent flows. An important feature of the present model is that a bridge between the spatial-statistical description of the flow and hydrodynamic equations is established. We show that the basic assumptions underlying the model, i.e., that the particles are indistinguishable and elementary volumes of phase space exist in which the state of the particles is uncertain, are involved in the derivation of the Navier-Stokes equation. Taking into account that the model captures essential features of turbulent flows, this suggests that the driving force for the turbulent transition is basically the same as in the present model, i.e., the tendency of the system to occupy a statistically dominant state plays a key role. The instability of the flow at high Reynolds numbers can then be a mechanism to initiate structural rearrangement of the flow to find this state.

Effective Diagnosis of Alzheimer's Disease by Means of Association Rules

NASA Astrophysics Data System (ADS)

Chaves, R.; Ramírez, J.; Górriz, J. M.; López, M.; Salas-Gonzalez, D.; Illán, I.; Segovia, F.; Padilla, P.

In this paper we present a novel classification method of SPECT images for the early diagnosis of the Alzheimer's disease (AD). The proposed method is based on Association Rules (ARs) aiming to discover interesting associations between attributes contained in the database. The system uses firstly voxel-as-features (VAF) and Activation Estimation (AE) to find tridimensional activated brain regions of interest (ROIs) for each patient. These ROIs act as inputs to secondly mining ARs between activated blocks for controls, with a specified minimum support and minimum confidence. ARs are mined in supervised mode, using information previously extracted from the most discriminant rules for centering interest in the relevant brain areas, reducing the computational requirement of the system. Finally classification process is performed depending on the number of previously mined rules verified by each subject, yielding an up to 95.87% classification accuracy, thus outperforming recent developed methods for AD diagnosis.

A neuro-fuzzy architecture for real-time applications

NASA Technical Reports Server (NTRS)

Ramamoorthy, P. A.; Huang, Song

1992-01-01

Neural networks and fuzzy expert systems perform the same task of functional mapping using entirely different approaches. Each approach has certain unique features. The ability to learn specific input-output mappings from large input/output data possibly corrupted by noise and the ability to adapt or continue learning are some important features of neural networks. Fuzzy expert systems are known for their ability to deal with fuzzy information and incomplete/imprecise data in a structured, logical way. Since both of these techniques implement the same task (that of functional mapping--we regard 'inferencing' as one specific category under this class), a fusion of the two concepts that retains their unique features while overcoming their individual drawbacks will have excellent applications in the real world. In this paper, we arrive at a new architecture by fusing the two concepts. The architecture has the trainability/adaptibility (based on input/output observations) property of the neural networks and the architectural features that are unique to fuzzy expert systems. It also does not require specific information such as fuzzy rules, defuzzification procedure used, etc., though any such information can be integrated into the architecture. We show that this architecture can provide better performance than is possible from a single two or three layer feedforward neural network. Further, we show that this new architecture can be used as an efficient vehicle for hardware implementation of complex fuzzy expert systems for real-time applications. A numerical example is provided to show the potential of this approach.

A Cloudy View of Exoplanets

NASA Technical Reports Server (NTRS)

Deming, Drake

2010-01-01

The lack of absorption features in the transmission spectrum of exoplanet GJ1214b rules out a hydrogen-rich atmosphere for the planet. It is consistent with an atmosphere rich in water vapour or abundant in clouds.

78 FR 15925 - Endangered and Threatened Wildlife and Plants; Endangered Status and Critical Habitat Designation...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-13

... proposed rules. We particularly seek comments concerning: (1) The species' biology, range, and population... ``physical or biological features essential to the conservation of the species,'' within the geographical...

Grey matter volume in the cerebellum is related to the processing of grammatical rules in a second language: a structural voxel-based morphometry study.

PubMed

Pliatsikas, Christos; Johnstone, Tom; Marinis, Theodoros

2014-02-01

The experience of learning and using a second language (L2) has been shown to affect the grey matter (GM) structure of the brain. Importantly, GM density in several cortical and subcortical areas has been shown to be related to performance in L2 tasks. Here, we show that bilingualism can lead to increased GM volume in the cerebellum, a structure that has been related to the processing of grammatical rules. Additionally, the cerebellar GM volume of highly proficient L2 speakers is correlated to their performance in a task tapping on grammatical processing in an L2, demonstrating the importance of the cerebellum for the establishment and use of grammatical rules in an L2.

Help Design Software Project

DTIC Science & Technology

1988-11-30

discrete guidelines or rules to be used in the design. They pay little if any attention to how the developer can utilize the guidance. At best, they...designer’s attention on the critical design features and present ihe rationale for those features. It also describes alternative designs that were...more leading between lines, and careful attention to the selection of fonts (Rubens and Krull, 1985 ; Brockman, 1986). Bradford (1984) outlines the

Computer-Aided Diagnostic (CAD) Scheme by Use of Contralateral Subtraction Technique

NASA Astrophysics Data System (ADS)

Nagashima, Hiroyuki; Harakawa, Tetsumi

We developed a computer-aided diagnostic (CAD) scheme for detection of subtle image findings of acute cerebral infarction in brain computed tomography (CT) by using a contralateral subtraction technique. In our computerized scheme, the lateral inclination of image was first corrected automatically by rotating and shifting. The contralateral subtraction image was then derived by subtraction of reversed image from original image. Initial candidates for acute cerebral infarctions were identified using the multiple-thresholding and image filtering techniques. As the 1st step for removing false positive candidates, fourteen image features were extracted in each of the initial candidates. Halfway candidates were detected by applying the rule-based test with these image features. At the 2nd step, five image features were extracted using the overlapping scale with halfway candidates in interest slice and upper/lower slice image. Finally, acute cerebral infarction candidates were detected by applying the rule-based test with five image features. The sensitivity in the detection for 74 training cases was 97.4% with 3.7 false positives per image. The performance of CAD scheme for 44 testing cases had an approximate result to training cases. Our CAD scheme using the contralateral subtraction technique can reveal suspected image findings of acute cerebral infarctions in CT images.

Playing by the Rules: Instruction and Acculturation in Role-Playing Games

ERIC Educational Resources Information Center

Neuenschwander, Bryn

2008-01-01

The open-ended, informal, and socially negotiated nature of role-playing games creates a distinct learning challenge for newcomers to the hobby. The explicit rules of the game provide only an incomplete framework for structuring the actions of players, and the expectations and mores of a given group will add other, unspoken rules that discourage…

Differential impact of relevant and irrelevant dimension primes on rule-based and information-integration category learning.

PubMed

Grimm, Lisa R; Maddox, W Todd

2013-11-01

Research has identified multiple category-learning systems with each being "tuned" for learning categories with different task demands and each governed by different neurobiological systems. Rule-based (RB) classification involves testing verbalizable rules for category membership while information-integration (II) classification requires the implicit learning of stimulus-response mappings. In the first study to directly test rule priming with RB and II category learning, we investigated the influence of the availability of information presented at the beginning of the task. Participants viewed lines that varied in length, orientation, and position on the screen, and were primed to focus on stimulus dimensions that were relevant or irrelevant to the correct classification rule. In Experiment 1, we used an RB category structure, and in Experiment 2, we used an II category structure. Accuracy and model-based analyses suggested that a focus on relevant dimensions improves RB task performance later in learning while a focus on an irrelevant dimension improves II task performance early in learning. © 2013.

Explanation-based learning in infancy.

PubMed

Baillargeon, Renée; DeJong, Gerald F

2017-10-01

In explanation-based learning (EBL), domain knowledge is leveraged in order to learn general rules from few examples. An explanation is constructed for initial exemplars and is then generalized into a candidate rule that uses only the relevant features specified in the explanation; if the rule proves accurate for a few additional exemplars, it is adopted. EBL is thus highly efficient because it combines both analytic and empirical evidence. EBL has been proposed as one of the mechanisms that help infants acquire and revise their physical rules. To evaluate this proposal, 11- and 12-month-olds (n = 260) were taught to replace their current support rule (that an object is stable when half or more of its bottom surface is supported) with a more sophisticated rule (that an object is stable when half or more of the entire object is supported). Infants saw teaching events in which asymmetrical objects were placed on a base, followed by static test displays involving a novel asymmetrical object and a novel base. When the teaching events were designed to facilitate EBL, infants learned the new rule with as few as two (12-month-olds) or three (11-month-olds) exemplars. When the teaching events were designed to impede EBL, however, infants failed to learn the rule. Together, these results demonstrate that even infants, with their limited knowledge about the world, benefit from the knowledge-based approach of EBL.

REDEX - The ranging equipment diagnostic expert system

NASA Technical Reports Server (NTRS)

Luczak, Edward C.; Gopalakrishnan, K.; Zillig, David J.

1989-01-01

REDEX, an advanced prototype expert system that diagnoses hardware failures in the Ranging Equipment (RE) at NASA's Ground Network tracking stations is described. REDEX will help the RE technician identify faulty circuit cards or modules that must be replaced, and thereby reduce troubleshooting time. It features a highly graphical user interface that uses color block diagrams and layout diagrams to illustrate the location of a fault. A semantic network knowledge representation technique was used to model the design structure of the RE. A catalog of generic troubleshooting rules was compiled to represent heuristics that are applied in diagnosing electronic equipment. Specific troubleshooting rules were identified to represent additional diagnostic knowledge that is unique to the RE. Over 50 generic and 250 specific troubleshooting rules have been derived. REDEX is implemented in Prolog on an IBM PC AT-compatible workstation. Block diagram graphics displays are color-coded to identify signals that have been monitored or inferred to have nominal values, signals that are out of tolerance, and circuit cards and functions that are diagnosed as faulty. A hypertext-like scheme is used to allow the user to easily navigate through the space of diagrams and tables. Over 50 graphic and tabular displays have been implemented. REDEX is currently being evaluated in a stand-alone mode using simulated RE fault scenarios. It will soon be interfaced to the RE and tested in an online environment. When completed and fielded, REDEX will be a concrete example of the application of expert systems technology to the problem of improving performance and reducing the lifecycle costs of operating NASA's communications networks in the 1990s.

REDEX: The ranging equipment diagnostic expert system

NASA Technical Reports Server (NTRS)

Luczak, Edward C.; Gopalakrishnan, K.; Zillig, David J.

1989-01-01

REDEX, an advanced prototype expert system that diagnoses hardware failures in the Ranging Equipment (RE) at NASA's Ground Network tracking stations is described. REDEX will help the RE technician identify faulty circuit cards or modules that must be replaced, and thereby reduce troubleshooting time. It features a highly graphical user interface that uses color block diagrams and layout diagrams to illustrate the location of a fault. A semantic network knowledge representation technique was used to model the design structure of the RE. A catalog of generic troubleshooting rules was compiled to represent heuristics that are applied in diagnosing electronic equipment. Specific troubleshooting rules were identified to represent additional diagnostic knowledge that is unique to the RE. Over 50 generic and 250 specific troubleshooting rules have been derived. REDEX is implemented in Prolog on an IBM PC AT-compatible workstation. Block diagram graphics displays are color-coded to identify signals that have been monitored or inferred to have nominal values, signals that are out of tolerance, and circuit cards and functions that are diagnosed as faulty. A hypertext-like scheme is used to allow the user to easily navigate through the space of diagrams and tables. Over 50 graphic and tabular displays have been implemented. REDEX is currently being evaluated in a stand-alone mode using simulated RE fault scenarios. It will soon be interfaced to the RE and tested in an online environment. When completed and fielded, REDEX will be a concrete example of the application of expert systems technology to the problem of improving performance and reducing the lifecycle costs of operating NASA's communications networks in the 1990's.

REDEX - The ranging equipment diagnostic expert system

NASA Astrophysics Data System (ADS)

Luczak, Edward C.; Gopalakrishnan, K.; Zillig, David J.

REDEX, an advanced prototype expert system that diagnoses hardware failures in the Ranging Equipment (RE) at NASA's Ground Network tracking stations is described. REDEX will help the RE technician identify faulty circuit cards or modules that must be replaced, and thereby reduce troubleshooting time. It features a highly graphical user interface that uses color block diagrams and layout diagrams to illustrate the location of a fault. A semantic network knowledge representation technique was used to model the design structure of the RE. A catalog of generic troubleshooting rules was compiled to represent heuristics that are applied in diagnosing electronic equipment. Specific troubleshooting rules were identified to represent additional diagnostic knowledge that is unique to the RE. Over 50 generic and 250 specific troubleshooting rules have been derived. REDEX is implemented in Prolog on an IBM PC AT-compatible workstation. Block diagram graphics displays are color-coded to identify signals that have been monitored or inferred to have nominal values, signals that are out of tolerance, and circuit cards and functions that are diagnosed as faulty. A hypertext-like scheme is used to allow the user to easily navigate through the space of diagrams and tables. Over 50 graphic and tabular displays have been implemented. REDEX is currently being evaluated in a stand-alone mode using simulated RE fault scenarios. It will soon be interfaced to the RE and tested in an online environment. When completed and fielded, REDEX will be a concrete example of the application of expert systems technology to the problem of improving performance and reducing the lifecycle costs of operating NASA's communications networks in the 1990s.

REDEX: The ranging equipment diagnostic expert system

NASA Astrophysics Data System (ADS)

Luczak, Edward C.; Gopalakrishnan, K.; Zillig, David J.

1989-04-01

REDEX, an advanced prototype expert system that diagnoses hardware failures in the Ranging Equipment (RE) at NASA's Ground Network tracking stations is described. REDEX will help the RE technician identify faulty circuit cards or modules that must be replaced, and thereby reduce troubleshooting time. It features a highly graphical user interface that uses color block diagrams and layout diagrams to illustrate the location of a fault. A semantic network knowledge representation technique was used to model the design structure of the RE. A catalog of generic troubleshooting rules was compiled to represent heuristics that are applied in diagnosing electronic equipment. Specific troubleshooting rules were identified to represent additional diagnostic knowledge that is unique to the RE. Over 50 generic and 250 specific troubleshooting rules have been derived. REDEX is implemented in Prolog on an IBM PC AT-compatible workstation. Block diagram graphics displays are color-coded to identify signals that have been monitored or inferred to have nominal values, signals that are out of tolerance, and circuit cards and functions that are diagnosed as faulty. A hypertext-like scheme is used to allow the user to easily navigate through the space of diagrams and tables. Over 50 graphic and tabular displays have been implemented. REDEX is currently being evaluated in a stand-alone mode using simulated RE fault scenarios. It will soon be interfaced to the RE and tested in an online environment. When completed and fielded, REDEX will be a concrete example of the application of expert systems technology to the problem of improving performance and reducing the lifecycle costs of operating NASA's communications networks in the 1990's.

Leveraging Modeling Approaches: Reaction Networks and Rules

PubMed Central

Blinov, Michael L.; Moraru, Ion I.

2012-01-01

We have witnessed an explosive growth in research involving mathematical models and computer simulations of intracellular molecular interactions, ranging from metabolic pathways to signaling and gene regulatory networks. Many software tools have been developed to aid in the study of such biological systems, some of which have a wealth of features for model building and visualization, and powerful capabilities for simulation and data analysis. Novel high resolution and/or high throughput experimental techniques have led to an abundance of qualitative and quantitative data related to the spatio-temporal distribution of molecules and complexes, their interactions kinetics, and functional modifications. Based on this information, computational biology researchers are attempting to build larger and more detailed models. However, this has proved to be a major challenge. Traditionally, modeling tools require the explicit specification of all molecular species and interactions in a model, which can quickly become a major limitation in the case of complex networks – the number of ways biomolecules can combine to form multimolecular complexes can be combinatorially large. Recently, a new breed of software tools has been created to address the problems faced when building models marked by combinatorial complexity. These have a different approach for model specification, using reaction rules and species patterns. Here we compare the traditional modeling approach with the new rule-based methods. We make a case for combining the capabilities of conventional simulation software with the unique features and flexibility of a rule-based approach in a single software platform for building models of molecular interaction networks. PMID:22161349

Leveraging modeling approaches: reaction networks and rules.

PubMed

Blinov, Michael L; Moraru, Ion I

2012-01-01

We have witnessed an explosive growth in research involving mathematical models and computer simulations of intracellular molecular interactions, ranging from metabolic pathways to signaling and gene regulatory networks. Many software tools have been developed to aid in the study of such biological systems, some of which have a wealth of features for model building and visualization, and powerful capabilities for simulation and data analysis. Novel high-resolution and/or high-throughput experimental techniques have led to an abundance of qualitative and quantitative data related to the spatiotemporal distribution of molecules and complexes, their interactions kinetics, and functional modifications. Based on this information, computational biology researchers are attempting to build larger and more detailed models. However, this has proved to be a major challenge. Traditionally, modeling tools require the explicit specification of all molecular species and interactions in a model, which can quickly become a major limitation in the case of complex networks - the number of ways biomolecules can combine to form multimolecular complexes can be combinatorially large. Recently, a new breed of software tools has been created to address the problems faced when building models marked by combinatorial complexity. These have a different approach for model specification, using reaction rules and species patterns. Here we compare the traditional modeling approach with the new rule-based methods. We make a case for combining the capabilities of conventional simulation software with the unique features and flexibility of a rule-based approach in a single software platform for building models of molecular interaction networks.

Rule Systems for Runtime Verification: A Short Tutorial

NASA Astrophysics Data System (ADS)

Barringer, Howard; Havelund, Klaus; Rydeheard, David; Groce, Alex

In this tutorial, we introduce two rule-based systems for on and off-line trace analysis, RuleR and LogScope. RuleR is a conditional rule-based system, which has a simple and easily implemented algorithm for effective runtime verification, and into which one can compile a wide range of temporal logics and other specification formalisms used for runtime verification. Specifications can be parameterized with data, or even with specifications, allowing for temporal logic combinators to be defined. We outline a number of simple syntactic extensions of core RuleR that can lead to further conciseness of specification but still enabling easy and efficient implementation. RuleR is implemented in Java and we will demonstrate its ease of use in monitoring Java programs. LogScope is a derivation of RuleR adding a simple very user-friendly temporal logic. It was developed in Python, specifically for supporting testing of spacecraft flight software for NASA’s next 2011 Mars mission MSL (Mars Science Laboratory). The system has been applied by test engineers to analysis of log files generated by running the flight software. Detailed logging is already part of the system design approach, and hence there is no added instrumentation overhead caused by this approach. While post-mortem log analysis prevents the autonomous reaction to problems possible with traditional runtime verification, it provides a powerful tool for test automation. A new system is being developed that integrates features from both RuleR and LogScope.

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.

Fermi’s golden rule, the origin and breakdown of Markovian master equations, and the relationship between oscillator baths and the random matrix model

NASA Astrophysics Data System (ADS)

Santra, Siddhartha; Cruikshank, Benjamin; Balu, Radhakrishnan; Jacobs, Kurt

2017-10-01

Fermi’s golden rule applies to a situation in which a single quantum state \\vert \\psi> is coupled to a near-continuum. This ‘quasi-continuum coupling’ structure results in a rate equation for the population of \\vert \\psi> . Here we show that the coupling of a quantum system to the standard model of a thermal environment, a bath of harmonic oscillators, can be decomposed into a ‘cascade’ made up of the quasi-continuum coupling structures of Fermi’s golden rule. This clarifies the connection between the physics of the golden rule and that of a thermal bath, and provides a non-rigorous but physically intuitive derivation of the Markovian master equation directly from the former. The exact solution to the Hamiltonian of the golden rule, known as the Bixon-Jortner model, generalized for an asymmetric spectrum, provides a window on how the evolution induced by the bath deviates from the master equation as one moves outside the Markovian regime. Our analysis also reveals the relationship between the oscillator bath and the ‘random matrix model’ (RMT) of a thermal bath. We show that the cascade structure is the one essential difference between the two models, and the lack of it prevents the RMT from generating transition rates that are independent of the initial state of the system. We suggest that the cascade structure is one of the generic elements of thermalizing many-body systems.

The coming changes in tax-exempt health care finance.

PubMed

Carlile, L L; Serchuk, B M

1995-01-01

On December 30, 1994, the Internal Revenue Service (IRS) published proposed regulations (Proposed Regulations) that if enacted would significantly change the climate and rules of federal income tax law controlling the issuance and maintenance of tax-exempt bonds for governmental and 501(c)(3) health care borrowers. This article (1) summarizes the aspects of the Proposed Regulations dealing with private activity tests, management contracts, allocation and accounting rules, change in use of financed facilities, and antiabuse rules, and (2) summarizes the possible interrelationship of the IRS's audit program for tax-exempt bonds and the Proposed Regulations. The article reviews features of the Proposed Regulations that will affect either the costs or administrative burdens of managing the federal tax compliance of future tax-exempt health care borrowings.

Decision rules for unbiased inventory estimates

NASA Technical Reports Server (NTRS)

Argentiero, P. D.; Koch, D.

1979-01-01

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

Multispectral processing based on groups of resolution elements

NASA Technical Reports Server (NTRS)

Richardson, W.; Gleason, J. M.

1975-01-01

Several nine-point rules are defined and compared with previously studied rules. One of the rules performed well in boundary areas, but with reduced efficiency in field interiors; another combined best performance on field interiors with good sensitivity to boundary detail. The basic threshold gradient and some modifications were investigated as a means of boundary point detection. The hypothesis testing methods of closed-boundary formation were also tested and evaluated. An analysis of the boundary detection problem was initiated, employing statistical signal detection and parameter estimation techniques to analyze various formulations of the problem. These formulations permit the atmospheric and sensor system effects on the data to be thoroughly analyzed. Various boundary features and necessary assumptions can also be investigated in this manner.

CLIPS: A tool for the development and delivery of expert systems

NASA Technical Reports Server (NTRS)

Riley, Gary

1991-01-01

The C Language Integrated Production System (CLIPS) is a forward chaining rule-based language developed by the Software Technology Branch at the Johnson Space Center. CLIPS provides a complete environment for the construction of rule-based expert systems. CLIPS was designed specifically to provide high probability, low cost, and easy integration with external systems. Other key features of CLIPS include a powerful rule syntax, an interactive development environment, high performance, extensibility, a verification/validation tool, extensive documentation, and source code availability. The current release of CLIPS, version 4.3, is being used by over 2,500 users throughout the public and private community including: all NASA sites and branches of the military, numerous Federal bureaus, government contractors, 140 universities, and many companies.

Combining Landform Thematic Layer and Object-Oriented Image Analysis to Map the Surface Features of Mountainous Flood Plain Areas

NASA Astrophysics Data System (ADS)

Chuang, H.-K.; Lin, M.-L.; Huang, W.-C.

2012-04-01

The Typhoon Morakot on August 2009 brought more than 2,000 mm of cumulative rainfall in southern Taiwan, the extreme rainfall event caused serious damage to the Kaoping River basin. The losses were mostly blamed on the landslides along sides of the river, and shifting of the watercourse even led to the failure of roads and bridges, as well as flooding and levees damage happened around the villages on flood bank and terraces. Alluvial fans resulted from debris flow of stream feeders blocked the main watercourse and debris dam was even formed and collapsed. These disasters have highlighted the importance of identification and map the watercourse alteration, surface features of flood plain area and artificial structures soon after the catastrophic typhoon event for natural hazard mitigation. Interpretation of remote sensing images is an efficient approach to acquire spatial information for vast areas, therefore making it suitable for the differentiation of terrain and objects near the vast flood plain areas in a short term. The object-oriented image analysis program (Definiens Developer 7.0) and multi-band high resolution satellite images (QuickBird, DigitalGlobe) was utilized to interpret the flood plain features from Liouguei to Baolai of the the Kaoping River basin after Typhoon Morakot. Object-oriented image interpretation is the process of using homogenized image blocks as elements instead of pixels for different shapes, textures and the mutual relationships of adjacent elements, as well as categorized conditions and rules for semi-artificial interpretation of surface features. Digital terrain models (DTM) are also employed along with the above process to produce layers with specific "landform thematic layers". These layers are especially helpful in differentiating some confusing categories in the spectrum analysis with improved accuracy, such as landslides and riverbeds, as well as terraces, riverbanks, which are of significant engineering importance in disaster mitigation. In this study, an automatic and fast image interpretation process for eight surface features including main channel, secondary channel, sandbar, flood plain, river terrace, alluvial fan, landslide, and the nearby artificial structures in the mountainous flood plain is proposed. Images along timelines can even be compared in order to differentiate historical events such as village inundations, failure of roads, bridges and levees, as well as alternation of watercourse, and therefore can be used as references for safety evaluation of engineering structures near rivers, disaster prevention and mitigation, and even future land-use planning. Keywords: Flood plain area, Remote sensing, Object-oriented, Surface feature interpretation, Terrain analysis, Thematic layer, Typhoon Morakot

Use of standard vocabulary services in validation of water resources data

NASA Astrophysics Data System (ADS)

Yu, Jonathan; Cox, Simon; Ratcliffe, David

2010-05-01

Ontology repositories are increasingly being exposed through vocabulary and concept services. Primarily this is in support of resource discovery. Thesaurus functionality and even more sophisticated reasoning offers the possibility of overcoming the limitations of simple text-matching and tagging which is the basis of most search. However, controlled vocabularies have other important roles in distributed systems: in particular in constraining content validity. A national water information system established by the Australian Bureau of Meterorology ('the Bureau') has deployed a system for ingestion of data from multiple providers. This uses a http interface onto separately maintained vocabulary services as part of the quality assurance chain. With over 200 data providers potentially transferring data to the Bureau, a standard XML-based Water Data Transfer Format (WDTF) was developed for receipt of data into an integrated national water information system. The WDTF schema was built upon standards from the Open Geospatial Consortium (OGC). The structure and syntax specified by a W3C XML Schema is complemented by additional constraints described using Schematron. These implement important content requirements and business rules including: • Restricted cardinality: where optional elements and attributes inherited from the base standards become mandatory in the application, or repeatable elements or attributes are limited to one or omitted. For example, the sampledFeature element from O&M is optional but is mandatory for a samplingPoint element in WDTF. • Vocabulary checking: WDTF data use seventeen vocabularies or code lists derived from Regulations under the Commonwealth Water Act 2007. Examples of codelists are the Australian Water Regulations list, observed property vocabulary, and units of measures. • Contextual constraints: in many places, the permissible value is dependent on the value of another field. For example, within observations the unit of measure must be commensurate with the observed property type Validation of data submitted in WDTF uses a two-pass approach. First, syntax and structural validation is performed by standard XML Schema validation tools. Second, validation of contextual constraints and code list checking is performed using a hybrid method combining context-sensitive rule-based validation (allowing the rules to be expressed within a given context) and semantic vocabulary services. Schematron allows rules to incorporate assertions of XPath expressions to access and constrain element content, therefore enabling contextual constraints. Schematron is also used to perform element cardinality checking. The vocabularies or code lists are formalized in SKOS (Simple Knowledge Organization System), an RDF-based language. SKOS provides mechanisms to define concepts, associate them with (multi-lingual) labels or terms, and record thesaurus-like relationships between them. The vocabularies are managed in a RDF database or semantic triple store. Querying is implemented as a semantic vocabulary service, with an http-based API that allows queries to be issued from rules written in Schematron. WDTF has required development and deployment of some ontologies whose scope is much more general than this application, in particular covering 'observed properties' and 'units of measure', which also have to be related to each other and consistent with the dimensional analysis. Separation of the two validation passes reflects the separate governance and stability of the structural and content rules, and allows an organisation's business rules to be moved out of the XML schema definition and the XML schema to be reused by other businesses with their own specific rules. With the general approach proven, harmonization opportunities with more generic services are being explored, such as the GEMET API for SKOS, developed by the European Environment Agency. Acknowledgements: The authors would like to thank the AUSCOPE team for their development and support provided of the vocabulary services.

Compliance & operating rules : results of a focus group

DOT National Transportation Integrated Search

1997-05-01

This interim report presents the results ofa focus group session onrailroad : operating rules and compliance. In addition, it summarizes information gathered from : structured interviews with various railroad managers, government officials, and other...

50 CFR 648.20 - Mid-Atlantic Fishery Management Council ABC control rules.

Code of Federal Regulations, 2014 CFR

2014-10-01

... biology of the stock, fisheries that exploit the stock, and data collection methods; (iv) The stock... SSC to determine the following: (i) Key features of the stock biology, the fisheries that exploit it...

50 CFR 648.20 - Mid-Atlantic Fishery Management Council ABC control rules.

Code of Federal Regulations, 2013 CFR

2013-10-01

... biology of the stock, fisheries that exploit the stock, and data collection methods; (iv) The stock... SSC to determine the following: (i) Key features of the stock biology, the fisheries that exploit it...

50 CFR 648.20 - Mid-Atlantic Fishery Management Council ABC control rules.

Code of Federal Regulations, 2012 CFR

2012-10-01

... biology of the stock, fisheries that exploit the stock, and data collection methods; (iv) The stock... SSC to determine the following: (i) Key features of the stock biology, the fisheries that exploit it...

76 FR 27755 - Endangered and Threatened Wildlife and Plants; Withdrawal of the Proposed Rule To List the...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-05-12

..., low precipitation, and wind scour, features they predicted would persist over time, especially on... Christmas Bird Count (CBC), suffer from a variety of problems, including the inherent difficulties...

Jungle Act Featured in RPLR Road Show.

ERIC Educational Resources Information Center

Kozlowski, James C.

1984-01-01

Some rules of law and legal analysis applied by courts to resolve issues of personal injury and negligence liability in youth sports programs are discussed in this article. Assumption of risk and responsibility for injury are explored. (DF)

A decision tree-based on-line preventive control strategy for power system transient instability prevention

NASA Astrophysics Data System (ADS)

Xu, Yan; Dong, Zhao Yang; Zhang, Rui; Wong, Kit Po

2014-02-01

Maintaining transient stability is a basic requirement for secure power system operations. Preventive control deals with modifying the system operating point to withstand probable contingencies. In this article, a decision tree (DT)-based on-line preventive control strategy is proposed for transient instability prevention of power systems. Given a stability database, a distance-based feature estimation algorithm is first applied to identify the critical generators, which are then used as features to develop a DT. By interpreting the splitting rules of DT, preventive control is realised by formulating the rules in a standard optimal power flow model and solving it. The proposed method is transparent in control mechanism, on-line computation compatible and convenient to deal with multi-contingency. The effectiveness and efficiency of the method has been verified on New England 10-machine 39-bus test system.

Combining High Spatial Resolution Optical and LIDAR Data for Object-Based Image Classification

NASA Astrophysics Data System (ADS)

Li, R.; Zhang, T.; Geng, R.; Wang, L.

2018-04-01

In order to classify high spatial resolution images more accurately, in this research, a hierarchical rule-based object-based classification framework was developed based on a high-resolution image with airborne Light Detection and Ranging (LiDAR) data. The eCognition software is employed to conduct the whole process. In detail, firstly, the FBSP optimizer (Fuzzy-based Segmentation Parameter) is used to obtain the optimal scale parameters for different land cover types. Then, using the segmented regions as basic units, the classification rules for various land cover types are established according to the spectral, morphological and texture features extracted from the optical images, and the height feature from LiDAR respectively. Thirdly, the object classification results are evaluated by using the confusion matrix, overall accuracy and Kappa coefficients. As a result, a method using the combination of an aerial image and the airborne Lidar data shows higher accuracy.

A proposed computer diagnostic system for malignant melanoma (CDSMM).

PubMed

Shao, S; Grams, R R

1994-04-01

This paper describes a computer diagnostic system for malignant melanoma. The diagnostic system is a rule base system based on image analyses and works under the PC windows environment. It consists of seven modules: I/O module, Patient/Clinic database, image processing module, classification module, rule base module and system control module. In the system, the image analyses are automatically carried out, and database management is efficient and fast. Both final clinic results and immediate results from various modules such as measured features, feature pictures and history records of the disease lesion can be presented on screen or printed out from each corresponding module or from the I/O module. The system can also work as a doctor's office-based tool to aid dermatologists with details not perceivable by the human eye. Since the system operates on a general purpose PC, it can be made portable if the I/O module is disconnected.

Building of fuzzy decision trees using ID3 algorithm

NASA Astrophysics Data System (ADS)

Begenova, S. B.; Avdeenko, T. V.

2018-05-01

Decision trees are widely used in the field of machine learning and artificial intelligence. Such popularity is due to the fact that with the help of decision trees graphic models, text rules can be built and they are easily understood by the final user. Because of the inaccuracy of observations, uncertainties, the data, collected in the environment, often take an unclear form. Therefore, fuzzy decision trees becoming popular in the field of machine learning. This article presents a method that includes the features of the two above-mentioned approaches: a graphical representation of the rules system in the form of a tree and a fuzzy representation of the data. The approach uses such advantages as high comprehensibility of decision trees and the ability to cope with inaccurate and uncertain information in fuzzy representation. The received learning method is suitable for classifying problems with both numerical and symbolic features. In the article, solution illustrations and numerical results are given.

Atomic clusters and atomic surfaces in icosahedral quasicrystals.

PubMed

Quiquandon, Marianne; Portier, Richard; Gratias, Denis

2014-05-01

This paper presents the basic tools commonly used to describe the atomic structures of quasicrystals with a specific focus on the icosahedral phases. After a brief recall of the main properties of quasiperiodic objects, two simple physical rules are discussed that lead one to eventually obtain a surprisingly small number of atomic structures as ideal quasiperiodic models for real quasicrystals. This is due to the fact that the atomic surfaces (ASs) used to describe all known icosahedral phases are located on high-symmetry special points in six-dimensional space. The first rule is maximizing the density using simple polyhedral ASs that leads to two possible sets of ASs according to the value of the six-dimensional lattice parameter A between 0.63 and 0.79 nm. The second rule is maximizing the number of complete orbits of high symmetry to construct as large as possible atomic clusters similar to those observed in complex intermetallic structures and approximant phases. The practical use of these two rules together is demonstrated on two typical examples of icosahedral phases, i-AlMnSi and i-CdRE (RE = Gd, Ho, Tm).

Art as a Singular Rule

ERIC Educational Resources Information Center

Avital, Doron

2007-01-01

This paper will examine an unresolved tension inherent in the question of art and argue for the idea of a singular rule as a natural resolution. In so doing, the structure of a singular rule will be fully outlined and its paradoxical constitution will be resolved. The tension I mention above unfolds both as a matter of history and as a product of…