Assistance and Feedback Mechanism in an Intelligent Tutoring System for Teaching Conversion of Natural Language into Logic

ERIC Educational Resources Information Center

Perikos, Isidoros; Grivokostopoulou, Foteini; Hatzilygeroudis, Ioannis

2017-01-01

Logic as a knowledge representation and reasoning language is a fundamental topic of an Artificial Intelligence (AI) course and includes a number of sub-topics. One of them, which brings difficulties to students to deal with, is converting natural language (NL) sentences into first-order logic (FOL) formulas. To assist students to overcome those…

Artificial Intelligence Assists Ultrasonic Inspection

NASA Technical Reports Server (NTRS)

Schaefer, Lloyd A.; Willenberg, James D.

1992-01-01

Subtle indications of flaws extracted from ultrasonic waveforms. Ultrasonic-inspection system uses artificial intelligence to help in identification of hidden flaws in electron-beam-welded castings. System involves application of flaw-classification logic to analysis of ultrasonic waveforms.

Fuzzy logic and neural networks in artificial intelligence and pattern recognition

NASA Astrophysics Data System (ADS)

Sanchez, Elie

1991-10-01

With the use of fuzzy logic techniques, neural computing can be integrated in symbolic reasoning to solve complex real world problems. In fact, artificial neural networks, expert systems, and fuzzy logic systems, in the context of approximate reasoning, share common features and techniques. A model of Fuzzy Connectionist Expert System is introduced, in which an artificial neural network is designed to construct the knowledge base of an expert system from, training examples (this model can also be used for specifications of rules in fuzzy logic control). Two types of weights are associated with the synaptic connections in an AND-OR structure: primary linguistic weights, interpreted as labels of fuzzy sets, and secondary numerical weights. Cell activation is computed through min-max fuzzy equations of the weights. Learning consists in finding the (numerical) weights and the network topology. This feedforward network is described and first illustrated in a biomedical application (medical diagnosis assistance from inflammatory-syndromes/proteins profiles). Then, it is shown how this methodology can be utilized for handwritten pattern recognition (characters play the role of diagnoses): in a fuzzy neuron describing a number for example, the linguistic weights represent fuzzy sets on cross-detecting lines and the numerical weights reflect the importance (or weakness) of connections between cross-detecting lines and characters.

Tuberculosis disease diagnosis using artificial immune recognition system.

PubMed

Shamshirband, Shahaboddin; Hessam, Somayeh; Javidnia, Hossein; Amiribesheli, Mohsen; Vahdat, Shaghayegh; Petković, Dalibor; Gani, Abdullah; Kiah, Miss Laiha Mat

2014-01-01

There is a high risk of tuberculosis (TB) disease diagnosis among conventional methods. This study is aimed at diagnosing TB using hybrid machine learning approaches. Patient epicrisis reports obtained from the Pasteur Laboratory in the north of Iran were used. All 175 samples have twenty features. The features are classified based on incorporating a fuzzy logic controller and artificial immune recognition system. The features are normalized through a fuzzy rule based on a labeling system. The labeled features are categorized into normal and tuberculosis classes using the Artificial Immune Recognition Algorithm. Overall, the highest classification accuracy reached was for the 0.8 learning rate (α) values. The artificial immune recognition system (AIRS) classification approaches using fuzzy logic also yielded better diagnosis results in terms of detection accuracy compared to other empirical methods. Classification accuracy was 99.14%, sensitivity 87.00%, and specificity 86.12%.

Automated Knowledge Generation with Persistent Surveillance Video

DTIC Science & Technology

2008-03-26

5 2.1 Artificial Intelligence . . . . . . . . . . . . . . . . . . . . 5 2.1.1 Formal Logic . . . . . . . . . . . . . . . . . . . 6 2.1.2...background of Artificial Intelligence and the reasoning engines that will be applied to generate knowledge from data. Section 2.2 discusses background on...generation from persistent video. 4 II. Background In this chapter, we will discuss the background of Artificial Intelligence, Semantic Web, image

Cooperative Knowledge Bases.

DTIC Science & Technology

1988-02-01

intellegent knowledge bases. The present state of our system for concurrent evaluation of a knowledge base of logic clauses using static allocation...de Kleer, J., An assumption-based TMS, Artificial Intelligence, Vol. 28, No. 2, 1986. [Doyle 79) Doyle, J. A truth maintenance system, Artificial

Operations Monitoring Assistant System Design

DTIC Science & Technology

1986-07-01

Logic. Artificial Inteligence 25(1)::75-94. January.18. 41 -Nils J. Nilsson. Problem-Solving Methods In Artificli Intelligence. .klcG raw-Hill B3ook...operations monitoring assistant (OMA) system is designed that combines operations research, artificial intelligence, and human reasoning techniques and...KnowledgeCraft (from Carnegie Group), and 5.1 (from Teknowledze). These tools incorporate the best methods of applied artificial intelligence, and

Development of an intelligent system for cooling rate and fill control in GMAW

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

Einerson, C.J.; Smartt, H.B.; Johnson, J.A.

1992-09-01

A control strategy for gas metal arc welding (GMAW) is developed in which the welding system detects certain existing conditions and adjusts the process in accordance to pre-specified rules. This strategy is used to control the reinforcement and weld bead centerline cooling rate during welding. Relationships between heat and mass transfer rates to the base metal and the required electrode speed and welding speed for specific open circuit voltages are taught to a artificial neural network. Control rules are programmed into a fuzzy logic system. TRADITOINAL CONTROL OF THE GMAW PROCESS is based on the use of explicit welding proceduresmore » detailing allowable parameter ranges on a pass by pass basis for a given weld. The present work is an exploration of a completely different approach to welding control. In this work the objectives are to produce welds having desired weld bead reinforcements while maintaining the weld bead centerline cooling rate at preselected values. The need for this specific control is related to fabrication requirements for specific types of pressure vessels. The control strategy involves measuring weld joint transverse cross-sectional area ahead of the welding torch and the weld bead centerline cooling rate behind the weld pool, both by means of video (2), calculating the required process parameters necessary to obtain the needed heat and mass transfer rates (in appropriate dimensions) by means of an artificial neural network, and controlling the heat transfer rate by means of a fuzzy logic controller (3). The result is a welding machine that senses the welding conditions and responds to those conditions on the basis of logical rules, as opposed to producing a weld based on a specific procedure.« less

Development of an intelligent system for cooling rate and fill control in GMAW. [Gas Metal Arc Welding (GMAW)

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

Einerson, C.J.; Smartt, H.B.; Johnson, J.A.

1992-01-01

A control strategy for gas metal arc welding (GMAW) is developed in which the welding system detects certain existing conditions and adjusts the process in accordance to pre-specified rules. This strategy is used to control the reinforcement and weld bead centerline cooling rate during welding. Relationships between heat and mass transfer rates to the base metal and the required electrode speed and welding speed for specific open circuit voltages are taught to a artificial neural network. Control rules are programmed into a fuzzy logic system. TRADITOINAL CONTROL OF THE GMAW PROCESS is based on the use of explicit welding proceduresmore » detailing allowable parameter ranges on a pass by pass basis for a given weld. The present work is an exploration of a completely different approach to welding control. In this work the objectives are to produce welds having desired weld bead reinforcements while maintaining the weld bead centerline cooling rate at preselected values. The need for this specific control is related to fabrication requirements for specific types of pressure vessels. The control strategy involves measuring weld joint transverse cross-sectional area ahead of the welding torch and the weld bead centerline cooling rate behind the weld pool, both by means of video (2), calculating the required process parameters necessary to obtain the needed heat and mass transfer rates (in appropriate dimensions) by means of an artificial neural network, and controlling the heat transfer rate by means of a fuzzy logic controller (3). The result is a welding machine that senses the welding conditions and responds to those conditions on the basis of logical rules, as opposed to producing a weld based on a specific procedure.« less

Paraconsistent Annotated Logic in Viability Analysis: an Approach to Product Launching

NASA Astrophysics Data System (ADS)

Romeu de Carvalho, Fábio; Brunstein, Israel; Abe, Jair Minoro

2004-08-01

In this paper we present an application of the Para-analyzer, a logical analyzer based on the Paraconsistent Annotated Logic Pτ, introduced by Da Silva Filho and Abe in the decision-making systems. An example is analyzed in detail showing how uncertainty, inconsistency and paracompleteness can be elegantly handled with this logical system. As application for the Para-analyzer in decision-making, we developed the BAM — Baricenter Analysis Method. In order to make the presentation easier, we present the BAM applied in the viability analysis of product launching. Some of the techniques of Paraconsistent Annotated Logic have been applied in Artificial Intelligence, Robotics, Information Technolgy (Computer Sciences), etc..

Decision exploration lab: a visual analytics solution for decision management.

PubMed

Broeksema, Bertjan; Baudel, Thomas; Telea, Arthur G; Crisafulli, Paolo

2013-12-01

We present a visual analytics solution designed to address prevalent issues in the area of Operational Decision Management (ODM). In ODM, which has its roots in Artificial Intelligence (Expert Systems) and Management Science, it is increasingly important to align business decisions with business goals. In our work, we consider decision models (executable models of the business domain) as ontologies that describe the business domain, and production rules that describe the business logic of decisions to be made over this ontology. Executing a decision model produces an accumulation of decisions made over time for individual cases. We are interested, first, to get insight in the decision logic and the accumulated facts by themselves. Secondly and more importantly, we want to see how the accumulated facts reveal potential divergences between the reality as captured by the decision model, and the reality as captured by the executed decisions. We illustrate the motivation, added value for visual analytics, and our proposed solution and tooling through a business case from the car insurance industry.

Molecular processors: from qubits to fuzzy logic.

PubMed

Gentili, Pier Luigi

2011-03-14

Single molecules or their assemblies are information processing devices. Herein it is demonstrated how it is possible to process different types of logic through molecules. As long as decoherent effects are maintained far away from a pure quantum mechanical system, quantum logic can be processed. If the collapse of superimposed or entangled wavefunctions is unavoidable, molecules can still be used to process either crisp (binary or multi-valued) or fuzzy logic. The way for implementing fuzzy inference engines is declared and it is supported by the examples of molecular fuzzy logic systems devised so far. Fuzzy logic is drawing attention in the field of artificial intelligence, because it models human reasoning quite well. This ability may be due to some structural analogies between a fuzzy logic system and the human nervous system. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Ion implanted dielectric elastomer circuits

NASA Astrophysics Data System (ADS)

O'Brien, Benjamin M.; Rosset, Samuel; Anderson, Iain A.; Shea, Herbert R.

2013-06-01

Starfish and octopuses control their infinite degree-of-freedom arms with panache—capabilities typical of nature where the distribution of reflex-like intelligence throughout soft muscular networks greatly outperforms anything hard, heavy, and man-made. Dielectric elastomer actuators show great promise for soft artificial muscle networks. One way to make them smart is with piezo-resistive Dielectric Elastomer Switches (DES) that can be combined with artificial muscles to create arbitrary digital logic circuits. Unfortunately there are currently no reliable materials or fabrication process. Thus devices typically fail within a few thousand cycles. As a first step in the search for better materials we present a preliminary exploration of piezo-resistors made with filtered cathodic vacuum arc metal ion implantation. DES were formed on polydimethylsiloxane silicone membranes out of ion implanted gold nano-clusters. We propose that there are four distinct regimes (high dose, above percolation, on percolation, low dose) in which gold ion implanted piezo-resistors can operate and present experimental results on implanted piezo-resistors switching high voltages as well as a simple artificial muscle inverter. While gold ion implanted DES are limited by high hysteresis and low sensitivity, they already show promise for a range of applications including hysteretic oscillators and soft generators. With improvements to implanter process control the promise of artificial muscle circuitry for soft smart actuator networks could become a reality.

Naval Computer-Based Instruction: Cost, Implementation and Effectiveness Issues.

DTIC Science & Technology

1988-03-01

logical follow on to MITIPAC and are an attempt to use some artificial intelligence (AI) techniques with computer-based training. A good intelligent ...principles of steam plant operation and maintenance. Steamer was written in LISP on a LISP machine in an attempt to use artificial intelligence . "What... Artificial Intelligence and Speech Technology", Electronic Learning, September 1987. Montague, William. E., code 5, Navy Personnel Research and

Northeast Artificial Intelligence Consortium Annual Report. 1988 Interference Techniques for Knowledge Base Maintenance Using Logic Programming Methodologies. Volume 11

DTIC Science & Technology

1989-10-01

Northeast Aritificial Intelligence Consortium (NAIC). i Table of Contents Execu tive Sum m ary...o g~nIl ’vLr COPY o~ T- RADC-TR-89-259, Vol XI (of twelve) N Interim Report SOctober 1989 NORTHEAST ARTIFICIAL INTELLIGENCE CONSORTIUM ANNUAL REPORT...ORGANIZATION 6b. OFFICE SYMBOL 7a. NAME OF MONITORING ORGANIZATION Northeast Artificial (If applicable) Intelligence Consortium (NAIC) . Rome Air Development

An Application of Fuzzy Analytic Hierarchy Process (FAHP) for Evaluating Students' Project

ERIC Educational Resources Information Center

Çebi, Ayça; Karal, Hasan

2017-01-01

In recent years, artificial intelligence applications for understanding the human thinking process and transferring it to virtual environments come into prominence. The fuzzy logic which paves the way for modeling human behaviors and expressing even vague concepts mathematically, and is also regarded as an artificial intelligence technique has…

Inferential Processor.

DTIC Science & Technology

1982-01-01

Speed Reasoning in Propositional Logic," Proposal to AF Office of Scientific Researchp July 1981. 3. Roussel, P., OPRLOG: manuel de reference et ...dlutilization,o Groupe d’Intelligence Artificielle , Universite d’Aix- Marseille, Luminy, France, September 1975. 4. Clocksint W.F. and C.S. Mellish...for reasoning in higher-order logics such as the first-order predicate calculus; the latter is required for applications in artificial intelligence

Control of electrochemical signals from quantum dots conjugated to organic materials by using DNA structure in an analog logic gate.

PubMed

Chen, Qi; Yoo, Si-Youl; Chung, Yong-Ho; Lee, Ji-Young; Min, Junhong; Choi, Jeong-Woo

2016-10-01

Various bio-logic gates have been studied intensively to overcome the rigidity of single-function silicon-based logic devices arising from combinations of various gates. Here, a simple control tool using electrochemical signals from quantum dots (QDs) was constructed using DNA and organic materials for multiple logic functions. The electrochemical redox current generated from QDs was controlled by the DNA structure. DNA structure, in turn, was dependent on the components (organic materials) and the input signal (pH). Independent electrochemical signals from two different logic units containing QDs were merged into a single analog-type logic gate, which was controlled by two inputs. We applied this electrochemical biodevice to a simple logic system and achieved various logic functions from the controlled pH input sets. This could be further improved by choosing QDs, ionic conditions, or DNA sequences. This research provides a feasible method for fabricating an artificial intelligence system. Copyright © 2016 Elsevier B.V. All rights reserved.

An inquiry into computer understanding

NASA Technical Reports Server (NTRS)

Cheeseman, Peter

1988-01-01

The paper examines issues connected with the choice of the best method for representing and reasoning about common sense. McDermott (1978) has shown that a direct translation of common sense reasoning into logical form leads to insurmountable difficulties. It is shown, in the present work, that if Bayesian probability is used instead of logic as the language of such reasoning, none of the technical difficulties found in using logic arise. Bayesian inference is applied to a simple example of linguistic information to illustrate the potential of this type of inference for artificial intelligence.

Conceptual Memory: A Theory and Computer Program for Processing the Meaning Content of Natural Language Utterances

DTIC Science & Technology

1974-07-01

iiWU -immmemmmmm This document was generated by the Stanford Artificial Intelligence Laboratory’s document compiler, "PUB" and reproducec’ on a...for more sophisticated artificial (programming) languages. The new issues became those of how to represent a grammar as precise syntactic structures...challenge lies in discovering - either by synthesis of an artificial system, or by analysis of a natural one - the underlying logical (a. opposed to

15 CFR 970.601 - Logical mining unit.

Code of Federal Regulations, 2014 CFR

2014-01-01

... ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR EXPLORATION LICENSES Resource Development Concepts § 970.601 Logical mining unit. (a) In the case of an exploration license, a logical mining unit is an... 15 Commerce and Foreign Trade 3 2014-01-01 2014-01-01 false Logical mining unit. 970.601 Section...

15 CFR 970.601 - Logical mining unit.

Code of Federal Regulations, 2013 CFR

2013-01-01

... ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR EXPLORATION LICENSES Resource Development Concepts § 970.601 Logical mining unit. (a) In the case of an exploration license, a logical mining unit is an... 15 Commerce and Foreign Trade 3 2013-01-01 2013-01-01 false Logical mining unit. 970.601 Section...

15 CFR 970.601 - Logical mining unit.

Code of Federal Regulations, 2012 CFR

2012-01-01

... ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR EXPLORATION LICENSES Resource Development Concepts § 970.601 Logical mining unit. (a) In the case of an exploration license, a logical mining unit is an... 15 Commerce and Foreign Trade 3 2012-01-01 2012-01-01 false Logical mining unit. 970.601 Section...

15 CFR 970.601 - Logical mining unit.

Code of Federal Regulations, 2010 CFR

2010-01-01

... ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR EXPLORATION LICENSES Resource Development Concepts § 970.601 Logical mining unit. (a) In the case of an exploration license, a logical mining unit is an... 15 Commerce and Foreign Trade 3 2010-01-01 2010-01-01 false Logical mining unit. 970.601 Section...

15 CFR 970.601 - Logical mining unit.

Code of Federal Regulations, 2011 CFR

2011-01-01

... ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR EXPLORATION LICENSES Resource Development Concepts § 970.601 Logical mining unit. (a) In the case of an exploration license, a logical mining unit is an... 15 Commerce and Foreign Trade 3 2011-01-01 2011-01-01 false Logical mining unit. 970.601 Section...

Parallel Logic Programming Architecture

DTIC Science & Technology

1990-04-01

Section 3.1. 3.1. A STATIC ALLOCATION SCHEME (SAS) Methods that have been used for decomposing distributed problems in artificial intelligence...multiple agents, knowledge organization and allocation, and cooperative parallel execution. These difficulties are common to distributed artificial ...for the following reasons. First, intellegent backtracking requires much more bookkeeping and is therefore more costly during consult-time and during

How artificial intelligence tools can be used to assess individual patient risk in cardiovascular disease: problems with the current methods.

PubMed

Grossi, Enzo

2006-05-03

In recent years a number of algorithms for cardiovascular risk assessment has been proposed to the medical community. These algorithms consider a number of variables and express their results as the percentage risk of developing a major fatal or non-fatal cardiovascular event in the following 10 to 20 years The author has identified three major pitfalls of these algorithms, linked to the limitation of the classical statistical approach in dealing with this kind of non linear and complex information. The pitfalls are the inability to capture the disease complexity, the inability to capture process dynamics, and the wide confidence interval of individual risk assessment. Artificial Intelligence tools can provide potential advantage in trying to overcome these limitations. The theoretical background and some application examples related to artificial neural networks and fuzzy logic have been reviewed and discussed. The use of predictive algorithms to assess individual absolute risk of cardiovascular future events is currently hampered by methodological and mathematical flaws. The use of newer approaches, such as fuzzy logic and artificial neural networks, linked to artificial intelligence, seems to better address both the challenge of increasing complexity resulting from a correlation between predisposing factors, data on the occurrence of cardiovascular events, and the prediction of future events on an individual level.

Implementing neural nets with programmable logic

NASA Technical Reports Server (NTRS)

Vidal, Jacques J.

1988-01-01

Networks of Boolean programmable logic modules are presented as one purely digital class of artificial neural nets. The approach contrasts with the continuous analog framework usually suggested. Programmable logic networks are capable of handling many neural-net applications. They avoid some of the limitations of threshold logic networks and present distinct opportunities. The network nodes are called dynamically programmable logic modules. They can be implemented with digitally controlled demultiplexers. Each node performs a Boolean function of its inputs which can be dynamically assigned. The overall network is therefore a combinational circuit and its outputs are Boolean global functions of the network's input variables. The approach offers definite advantages for VLSI implementation, namely, a regular architecture with limited connectivity, simplicity of the control machinery, natural modularity, and the support of a mature technology.

Development of expert systems for modeling of technological process of pressure casting on the basis of artificial intelligence

NASA Astrophysics Data System (ADS)

Gavarieva, K. N.; Simonova, L. A.; Pankratov, D. L.; Gavariev, R. V.

2017-09-01

In article the main component of expert system of process of casting under pressure which consists of algorithms, united in logical models is considered. The characteristics of system showing data on a condition of an object of management are described. A number of logically interconnected steps allowing to increase quality of the received castings is developed

Logic Programming in LISP.

DTIC Science & Technology

1981-01-01

THIS PAGZ(Whan Doee Es tMord) Item 20 (Cont’d) ------ work in the area of artificial intelligence and those used in general program development into a...Controlling Gfile) IS. SECURITY CLASS. (of tis report) Same .,/ UNCLASSIFIED 13d. DECLASSIFICATION/ DOWN GRADING ..- ". .--- /A!CHEDULEI t I IS...logic programming with LISP for implementing intelligent data base query systems. Continued developments will allow for enhancements to be made to the

Design of synthetic biological logic circuits based on evolutionary algorithm.

PubMed

Chuang, Chia-Hua; Lin, Chun-Liang; Chang, Yen-Chang; Jennawasin, Tanagorn; Chen, Po-Kuei

2013-08-01

The construction of an artificial biological logic circuit using systematic strategy is recognised as one of the most important topics for the development of synthetic biology. In this study, a real-structured genetic algorithm (RSGA), which combines general advantages of the traditional real genetic algorithm with those of the structured genetic algorithm, is proposed to deal with the biological logic circuit design problem. A general model with the cis-regulatory input function and appropriate promoter activity functions is proposed to synthesise a wide variety of fundamental logic gates such as NOT, Buffer, AND, OR, NAND, NOR and XOR. The results obtained can be extended to synthesise advanced combinational and sequential logic circuits by topologically distinct connections. The resulting optimal design of these logic gates and circuits are established via the RSGA. The in silico computer-based modelling technology has been verified showing its great advantages in the purpose.

Integrated all-optical logic discriminators based on plasmonic bandgap engineering

PubMed Central

Lu, Cuicui; Hu, Xiaoyong; Yang, Hong; Gong, Qihuang

2013-01-01

Optical computing uses photons as information carriers, opening up the possibility for ultrahigh-speed and ultrawide-band information processing. Integrated all-optical logic devices are indispensible core components of optical computing systems. However, up to now, little experimental progress has been made in nanoscale all-optical logic discriminators, which have the function of discriminating and encoding incident light signals according to wavelength. Here, we report a strategy to realize a nanoscale all-optical logic discriminator based on plasmonic bandgap engineering in a planar plasmonic microstructure. Light signals falling within different operating wavelength ranges are differentiated and endowed with different logic state encodings. Compared with values previously reported, the operating bandwidth is enlarged by one order of magnitude. Also the SPP light source is integrated with the logic device while retaining its ultracompact size. This opens up a way to construct on-chip all-optical information processors and artificial intelligence systems. PMID:24071647

Conversion of the CALAP (Computer Aided Landform Analysis Program) Program from FORTRAN to DUCK.

DTIC Science & Technology

1986-09-01

J’ DUCK artificial intelligence logic programming 20 AVrACT (Cthm m reerse stabN ameeaaW idelfr by block mbae) An expert advisor program named CALAP...original program was developed in FORTRAN on an HP- 1000, a mirticomputer. CALAP was reprogrammed in an Artificial Intelligence (AI) language called DUCK...the Artificial Intelligence Center, U.S. Army Engineer Topographic Laboratory, Fort Belvoir. Z" I. S. n- Page 1 I. Introduction An expert advisor

Application of Artificial Intelligence Techniques in Unmanned Aerial Vehicle Flight

NASA Technical Reports Server (NTRS)

Bauer, Frank H. (Technical Monitor); Dufrene, Warren R., Jr.

2003-01-01

This paper describes the development of an application of Artificial Intelligence for Unmanned Aerial Vehicle (UAV) control. The project was done as part of the requirements for a class in Artificial Intelligence (AI) at Nova southeastern University and as an adjunct to a project at NASA Goddard Space Flight Center's Wallops Flight Facility for a resilient, robust, and intelligent UAV flight control system. A method is outlined which allows a base level application for applying an AI method, Fuzzy Logic, to aspects of Control Logic for UAV flight. One element of UAV flight, automated altitude hold, has been implemented and preliminary results displayed. A low cost approach was taken using freeware, gnu, software, and demo programs. The focus of this research has been to outline some of the AI techniques used for UAV flight control and discuss some of the tools used to apply AI techniques. The intent is to succeed with the implementation of applying AI techniques to actually control different aspects of the flight of an UAV.

Computing single step operators of logic programming in radial basis function neural networks

NASA Astrophysics Data System (ADS)

Hamadneh, Nawaf; Sathasivam, Saratha; Choon, Ong Hong

2014-07-01

Logic programming is the process that leads from an original formulation of a computing problem to executable programs. A normal logic program consists of a finite set of clauses. A valuation I of logic programming is a mapping from ground atoms to false or true. The single step operator of any logic programming is defined as a function (Tp:I→I). Logic programming is well-suited to building the artificial intelligence systems. In this study, we established a new technique to compute the single step operators of logic programming in the radial basis function neural networks. To do that, we proposed a new technique to generate the training data sets of single step operators. The training data sets are used to build the neural networks. We used the recurrent radial basis function neural networks to get to the steady state (the fixed point of the operators). To improve the performance of the neural networks, we used the particle swarm optimization algorithm to train the networks.

Temporal Reasoning and Default Logics.

DTIC Science & Technology

1985-10-01

Aritificial Intelligence ", Computer Science Research Report, Yale University, forthcoming (1985). . 74 .-, A Axioms for Describing Persistences and Clipping...34Circumscription - A Form of Non-Monotonic Reasoning", Artificial Intelligence , vol. 13 (1980), pp. 27-39. [13] McCarthy, John, "Applications of...and P. J. Hayes, "Some philosophical problems from the standpoint of artificial intelligence ", in: B. Meltzer and D. Michie (eds.), Machine

Involving Users to Improve the Collaborative Logical Framework

PubMed Central

2014-01-01

In order to support collaboration in web-based learning, there is a need for an intelligent support that facilitates its management during the design, development, and analysis of the collaborative learning experience and supports both students and instructors. At aDeNu research group we have proposed the Collaborative Logical Framework (CLF) to create effective scenarios that support learning through interaction, exploration, discussion, and collaborative knowledge construction. This approach draws on artificial intelligence techniques to support and foster an effective involvement of students to collaborate. At the same time, the instructors' workload is reduced as some of their tasks—especially those related to the monitoring of the students behavior—are automated. After introducing the CLF approach, in this paper, we present two formative evaluations with users carried out to improve the design of this collaborative tool and thus enrich the personalized support provided. In the first one, we analyze, following the layered evaluation approach, the results of an observational study with 56 participants. In the second one, we tested the infrastructure to gather emotional data when carrying out another observational study with 17 participants. PMID:24592196

A Wittgenstein Approach to the Learning of OO-modeling

NASA Astrophysics Data System (ADS)

Holmboe, Christian

2004-12-01

The paper uses Ludwig Wittgenstein's theories about the relationship between thought, language, and objects of the world to explore the assumption that OO-thinking resembles natural thinking. The paper imports from research in linguistic philosophy to computer science education research. I show how UML class diagrams (i.e., an artificial context-free language) correspond to the logically perfect languages described in Tractatus Logico-Philosophicus. In Philosophical Investigations Wittgenstein disputes his previous theories by showing that natural languages are not constructed by rules of mathematical logic, but are language games where the meaning of a word is constructed through its use in social contexts. Contradicting the claim that OO-thinking is easy to learn because of its similarity to natural thinking, I claim that OO-thinking is difficult to learn because of its differences from natural thinking. The nature of these differences is not currently well known or appreciated. I suggest how explicit attention to the nature and implications of different language games may improve the teaching and learning of OO-modeling as well as programming.

Automated Interpretation of LIBS Spectra using a Fuzzy Logic Inference Engine

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

Jeremy J. Hatch; Timothy R. McJunkin; Cynthia Hanson

2012-02-01

Automated interpretation of laser-induced breakdown spectroscopy (LIBS) data is necessary due to the plethora of spectra that can be acquired in a relatively short time. However, traditional chemometric and artificial neural network methods that have been employed are not always transparent to a skilled user. A fuzzy logic approach to data interpretation has now been adapted to LIBS spectral interpretation. A fuzzy logic inference engine (FLIE) was used to differentiate between various copper containing and stainless steel alloys as well as unknowns. Results using FLIE indicate a high degree of confidence in spectral assignment.

An Argumentation Framework based on Paraconsistent Logic

NASA Astrophysics Data System (ADS)

Umeda, Yuichi; Takahashi, Takehisa; Sawamura, Hajime

Argumentation is the most representative of intelligent activities of humans. Therefore, it is natural to think that it could have many implications for artificial intelligence and computer science as well. Specifically, argumentation may be considered a most primitive capability for interaction among computational agents. In this paper we present an argumentation framework based on the four-valued paraconsistent logic. Tolerance and acceptance of inconsistency that this logic has as its logical feature allow for arguments on inconsistent knowledge bases with which we are often confronted. We introduce various concepts for argumentation, such as arguments, attack relations, argument justification, preferential criteria of arguments based on social norms, and so on, in a way proper to the four-valued paraconsistent logic. Then, we provide the fixpoint semantics and dialectical proof theory for our argumentation framework. We also give the proofs of the soundness and completeness.

How artificial intelligence tools can be used to assess individual patient risk in cardiovascular disease: problems with the current methods

PubMed Central

Grossi, Enzo

2006-01-01

Background In recent years a number of algorithms for cardiovascular risk assessment has been proposed to the medical community. These algorithms consider a number of variables and express their results as the percentage risk of developing a major fatal or non-fatal cardiovascular event in the following 10 to 20 years Discussion The author has identified three major pitfalls of these algorithms, linked to the limitation of the classical statistical approach in dealing with this kind of non linear and complex information. The pitfalls are the inability to capture the disease complexity, the inability to capture process dynamics, and the wide confidence interval of individual risk assessment. Artificial Intelligence tools can provide potential advantage in trying to overcome these limitations. The theoretical background and some application examples related to artificial neural networks and fuzzy logic have been reviewed and discussed. Summary The use of predictive algorithms to assess individual absolute risk of cardiovascular future events is currently hampered by methodological and mathematical flaws. The use of newer approaches, such as fuzzy logic and artificial neural networks, linked to artificial intelligence, seems to better address both the challenge of increasing complexity resulting from a correlation between predisposing factors, data on the occurrence of cardiovascular events, and the prediction of future events on an individual level. PMID:16672045

Fuzzy logic and A* algorithm implementation on goat foraging games

NASA Astrophysics Data System (ADS)

Harsani, P.; Mulyana, I.; Zakaria, D.

2018-03-01

Goat foraging is one of the games that apply the search techniques within the scope of artificial intelligence. This game involves several actors including players and enemies. The method used in this research is fuzzy logic and Algorithm A*. Fuzzy logic is used to determine enemy behaviour. The A* algorithm is used to search for the shortest path. There are two input variables: the distance between the player and the enemy and the anger level of the goat. The output variable that has been defined is the enemy behaviour. The A* algorithm is used to determine the closest path between the player and the enemy and define the enemy's escape path to avoid the player. There are 4 types of enemies namely farmers, planters, farmers and sellers of plants. Players are goats that aims to find a meal that is a plant. In this game goats aim to spend grass in the garden in the form of a maze while avoiding the enemy. The game provides an application of artificial intelligence and is made in four difficulty levels.

Communication and Attitude Revision

DTIC Science & Technology

1992-01-01

Conference on Aritificial Intelligence , (1989) 1074- 1079 3. Clark, H., Marshal, C.: Definite reference and mutual knowledge. In Joshi, A., Sag, I.. and...21st Annual Meeting of the ACL (1983) 57-63 9. Konolige, K.: On the relation between default and autoepistemic logic. Artificial Intelligence 35(3...reasoning. Artificial Intelligence 13 (1980) 81-132 16. Richmond Thomason. Accommodation, meaning, and implicature. In Cohen, P., Morgan, J., and

Knowledge Based Consultation for Finite Element Structural Analysis.

DTIC Science & Technology

1980-05-01

Intelligence Finite Element Program Tutorial 20 ABSTRACT (Continue. on rees side If necessary and ide.n’ty b,’ bit,, k nionh.) In recent years, techniques of...involved in Artificial Intelligence at Stanford University developed the program MYCIN F2], for clinical consultation of diseases that require...and Rules The basic backward chaining logic, characteristic to Artificial Intelligence . approaching 1he problem of knowledge representation was

Parallel Logic Programming and Parallel Systems Software and Hardware

DTIC Science & Technology

1989-07-29

Conference, Dallas TX. January 1985. (55) [Rous75] Roussel, P., "PROLOG: Manuel de Reference et d’Uilisation", Group d’ Intelligence Artificielle , Universite d...completed. Tools were provided for software development using artificial intelligence techniques. Al software for massively parallel architectures was...using artificial intelligence tech- niques. Al software for massively parallel architectures was started. 1. Introduction We describe research conducted

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

Hamadneh, Nawaf; Sathasivam, Saratha; Choon, Ong Hong

Logic programming is the process that leads from an original formulation of a computing problem to executable programs. A normal logic program consists of a finite set of clauses. A valuation I of logic programming is a mapping from ground atoms to false or true. The single step operator of any logic programming is defined as a function (T{sub p}:I→I). Logic programming is well-suited to building the artificial intelligence systems. In this study, we established a new technique to compute the single step operators of logic programming in the radial basis function neural networks. To do that, we proposed amore » new technique to generate the training data sets of single step operators. The training data sets are used to build the neural networks. We used the recurrent radial basis function neural networks to get to the steady state (the fixed point of the operators). To improve the performance of the neural networks, we used the particle swarm optimization algorithm to train the networks.« less

Logic programming and metadata specifications

NASA Technical Reports Server (NTRS)

Lopez, Antonio M., Jr.; Saacks, Marguerite E.

1992-01-01

Artificial intelligence (AI) ideas and techniques are critical to the development of intelligent information systems that will be used to collect, manipulate, and retrieve the vast amounts of space data produced by 'Missions to Planet Earth.' Natural language processing, inference, and expert systems are at the core of this space application of AI. This paper presents logic programming as an AI tool that can support inference (the ability to draw conclusions from a set of complicated and interrelated facts). It reports on the use of logic programming in the study of metadata specifications for a small problem domain of airborne sensors, and the dataset characteristics and pointers that are needed for data access.

An Arbitrary First Order Theory Can Be Represented by a Program: A Theorem

NASA Technical Reports Server (NTRS)

Hosheleva, Olga

1997-01-01

How can we represent knowledge inside a computer? For formalized knowledge, classical logic seems to be the most adequate tool. Classical logic is behind all formalisms of classical mathematics, and behind many formalisms used in Artificial Intelligence. There is only one serious problem with classical logic: due to the famous Godel's theorem, classical logic is algorithmically undecidable; as a result, when the knowledge is represented in the form of logical statements, it is very difficult to check whether, based on this statement, a given query is true or not. To make knowledge representations more algorithmic, a special field of logic programming was invented. An important portion of logic programming is algorithmically decidable. To cover knowledge that cannot be represented in this portion, several extensions of the decidable fragments have been proposed. In the spirit of logic programming, these extensions are usually introduced in such a way that even if a general algorithm is not available, good heuristic methods exist. It is important to check whether the already proposed extensions are sufficient, or further extensions is necessary. In the present paper, we show that one particular extension, namely, logic programming with classical negation, introduced by M. Gelfond and V. Lifschitz, can represent (in some reasonable sense) an arbitrary first order logical theory.

Fuzzy logic and neural network technologies

NASA Technical Reports Server (NTRS)

Villarreal, James A.; Lea, Robert N.; Savely, Robert T.

1992-01-01

Applications of fuzzy logic technologies in NASA projects are reviewed to examine their advantages in the development of neural networks for aerospace and commercial expert systems and control. Examples of fuzzy-logic applications include a 6-DOF spacecraft controller, collision-avoidance systems, and reinforcement-learning techniques. The commercial applications examined include a fuzzy autofocusing system, an air conditioning system, and an automobile transmission application. The practical use of fuzzy logic is set in the theoretical context of artificial neural systems (ANSs) to give the background for an overview of ANS research programs at NASA. The research and application programs include the Network Execution and Training Simulator and faster training algorithms such as the Difference Optimized Training Scheme. The networks are well suited for pattern-recognition applications such as predicting sunspots, controlling posture maintenance, and conducting adaptive diagnoses.

Training Software in Artificial-Intelligence Computing Techniques

NASA Technical Reports Server (NTRS)

Howard, Ayanna; Rogstad, Eric; Chalfant, Eugene

2005-01-01

The Artificial Intelligence (AI) Toolkit is a computer program for training scientists, engineers, and university students in three soft-computing techniques (fuzzy logic, neural networks, and genetic algorithms) used in artificial-intelligence applications. The program promotes an easily understandable tutorial interface, including an interactive graphical component through which the user can gain hands-on experience in soft-computing techniques applied to realistic example problems. The tutorial provides step-by-step instructions on the workings of soft-computing technology, whereas the hands-on examples allow interaction and reinforcement of the techniques explained throughout the tutorial. In the fuzzy-logic example, a user can interact with a robot and an obstacle course to verify how fuzzy logic is used to command a rover traverse from an arbitrary start to the goal location. For the genetic algorithm example, the problem is to determine the minimum-length path for visiting a user-chosen set of planets in the solar system. For the neural-network example, the problem is to decide, on the basis of input data on physical characteristics, whether a person is a man, woman, or child. The AI Toolkit is compatible with the Windows 95,98, ME, NT 4.0, 2000, and XP operating systems. A computer having a processor speed of at least 300 MHz, and random-access memory of at least 56MB is recommended for optimal performance. The program can be run on a slower computer having less memory, but some functions may not be executed properly.

Fuzzy Versions of Epistemic and Deontic Logic

NASA Technical Reports Server (NTRS)

Gounder, Ramasamy S.; Esterline, Albert C.

1998-01-01

Epistemic and deontic logics are modal logics, respectively, of knowledge and of the normative concepts of obligation, permission, and prohibition. Epistemic logic is useful in formalizing systems of communicating processes and knowledge and belief in AI (Artificial Intelligence). Deontic logic is useful in computer science wherever we must distinguish between actual and ideal behavior, as in fault tolerance and database integrity constraints. We here discuss fuzzy versions of these logics. In the crisp versions, various axioms correspond to various properties of the structures used in defining the semantics of the logics. Thus, any axiomatic theory will be characterized not only by its axioms but also by the set of properties holding of the corresponding semantic structures. Fuzzy logic does not proceed with axiomatic systems, but fuzzy versions of the semantic properties exist and can be shown to correspond to some of the axioms for the crisp systems in special ways that support dependency networks among assertions in a modal domain. This in turn allows one to implement truth maintenance systems. For the technical development of epistemic logic, and for that of deontic logic. To our knowledge, we are the first to address fuzzy epistemic and fuzzy deontic logic explicitly and to consider the different systems and semantic properties available. We give the syntax and semantics of epistemic logic and discuss the correspondence between axioms of epistemic logic and properties of semantic structures. The same topics are covered for deontic logic. Fuzzy epistemic and fuzzy deontic logic discusses the relationship between axioms and semantic properties for these logics. Our results can be exploited in truth maintenance systems.

Exploring the institutional logics of health professions education scholarship units.

PubMed

Varpio, Lara; O'Brien, Bridget; Hu, Wendy; Ten Cate, Olle; Durning, Steven J; van der Vleuten, Cees; Gruppen, Larry; Irby, David; Humphrey-Murto, Susan; Hamstra, Stanley J

2017-07-01

Although health professions education scholarship units (HPESUs) share a commitment to the production and dissemination of rigorous educational practices and research, they are situated in many different contexts and have a wide range of structures and functions. In this study, the authors explore the institutional logics common across HPESUs, and how these logics influence the organisation and activities of HPESUs. The authors analysed interviews with HPESU leaders in Canada (n = 12), Australia (n = 21), New Zealand (n = 3) and the USA (n = 11). Using an iterative process, they engaged in inductive and deductive analyses to identify institutional logics across all participating HPESUs. They explored the contextual factors that influence how these institutional logics impact each HPESU's structure and function. Participants identified three institutional logics influencing the organisational structure and functions of an HPESU: (i) the logic of financial accountability; (ii) the logic of a cohesive education continuum, and (iii) the logic of academic research, service and teaching. Although most HPESUs embodied all three logics, the power of the logics varied among units. The relative power of each logic influenced leaders' decisions about how members of the unit allocate their time, and what kinds of scholarly contribution and product are valued by the HPESU. Identifying the configuration of these three logics within and across HPESUs provides insights into the reasons why individual units are structured and function in particular ways. Having a common language in which to discuss these logics can enhance transparency, facilitate evaluation, and help leaders select appropriate indicators of HPESU success. © 2017 John Wiley & Sons Ltd and The Association for the Study of Medical Education.

NASA/ARC proposed training in intelligent control

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.

1990-01-01

Viewgraphs on NASA Ames Research Center proposed training in intelligent control was presented. Topics covered include: fuzzy logic control; neural networks in control; artificial intelligence in control; hybrid approaches; hands on experience; and fuzzy controllers.

Logical Framework of Forensic Identification: Ability to Resist Fabricated DNA.

PubMed

Wang, Zheng; Zhou, Di; Zhang, Suhua; Bian, Yingnan; Hu, Zhen; Zhu, Ruxin; Lu, Daru; Li, Chengtao

2015-12-01

Over the past 30 years, DNA analysis has revolutionized forensic science and has become the most useful single tool in the multifaceted fight against crime. Today, DNA profiling with sets of highly polymorphic autosomal short tandem repeat markers is widely employed and accepted in the courts due to its high discriminating power and reliability. However, an artificial bloodstain purposefully created using molecular biology techniques succeeded in tricking a leading forensic DNA laboratory. The disturbing possibility that a forensic DNA profile can be faked shocked the general public and the mass media, and generated serious discussion about the credibility of DNA evidence. Herein, we present two exemplary assays based on tissue-specific methylation patterns and cell-specific mRNA expression, respectively. These two assays can be integrated into the DNA analysis pipelines without consumption of additional samples. We show that the two assays can not only distinguish between artificial and genuine samples, but also provide information on tissue origin. The two assays were tested on natural and artificial bloodstains (generated by polymerase chain reaction and whole genome amplification technique) and the results illustrated that the logical framework of forensic identification is still useful for forensic identification with the high credibility.

pH-programmable DNA logic arrays powered by modular DNAzyme libraries.

PubMed

Elbaz, Johann; Wang, Fuan; Remacle, Francoise; Willner, Itamar

2012-12-12

Nature performs complex information processing circuits, such the programmed transformations of versatile stem cells into targeted functional cells. Man-made molecular circuits are, however, unable to mimic such sophisticated biomachineries. To reach these goals, it is essential to construct programmable modular components that can be triggered by environmental stimuli to perform different logic circuits. We report on the unprecedented design of artificial pH-programmable DNA logic arrays, constructed by modular libraries of Mg(2+)- and UO(2)(2+)-dependent DNAzyme subunits and their substrates. By the appropriate modular design of the DNA computation units, pH-programmable logic arrays of various complexities are realized, and the arrays can be erased, reused, and/or reprogrammed. Such systems may be implemented in the near future for nanomedical applications by pH-controlled regulation of cellular functions or may be used to control biotransformations stimulated by bacteria.

Don't Fear Optimality: Sampling for Probabilistic-Logic Sequence Models

NASA Astrophysics Data System (ADS)

Thon, Ingo

One of the current challenges in artificial intelligence is modeling dynamic environments that change due to the actions or activities undertaken by people or agents. The task of inferring hidden states, e.g. the activities or intentions of people, based on observations is called filtering. Standard probabilistic models such as Dynamic Bayesian Networks are able to solve this task efficiently using approximative methods such as particle filters. However, these models do not support logical or relational representations. The key contribution of this paper is the upgrade of a particle filter algorithm for use with a probabilistic logical representation through the definition of a proposal distribution. The performance of the algorithm depends largely on how well this distribution fits the target distribution. We adopt the idea of logical compilation into Binary Decision Diagrams for sampling. This allows us to use the optimal proposal distribution which is normally prohibitively slow.

A Different Kind of Language: Prolog, Programming in Logic.

ERIC Educational Resources Information Center

Cabrol, D.

1986-01-01

Prolog is one of the most successful "very high level languages." Describes this programming language (a product of artificial intelligence research) and attempts to show how it functions by using some short examples to illustrate its essential features. (JN)

Modified Method of Adaptive Artificial Viscosity for Solution of Gas Dynamics Problems on Parallel Computer Systems

NASA Astrophysics Data System (ADS)

Popov, Igor; Sukov, Sergey

2018-02-01

A modification of the adaptive artificial viscosity (AAV) method is considered. This modification is based on one stage time approximation and is adopted to calculation of gasdynamics problems on unstructured grids with an arbitrary type of grid elements. The proposed numerical method has simplified logic, better performance and parallel efficiency compared to the implementation of the original AAV method. Computer experiments evidence the robustness and convergence of the method to difference solution.

Logics of Business Education for Sustainability

ERIC Educational Resources Information Center

Andersson, Pernilla; Öhman, Johan

2016-01-01

This paper explores various kinds of logics of "business education for sustainability" and how these "logics" position the subject business person, based on eight teachers' reasoning of their own practices. The concept of logics developed within a discourse theoretical framework is employed to analyse the teachers' reasoning.…

43 CFR 3487.1 - Logical mining units.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 43 Public Lands: Interior 2 2011-10-01 2011-10-01 false Logical mining units. 3487.1 Section 3487..., DEPARTMENT OF THE INTERIOR MINERALS MANAGEMENT (3000) COAL EXPLORATION AND MINING OPERATIONS RULES Logical Mining Unit § 3487.1 Logical mining units. (a) An LMU shall become effective only upon approval of the...

GOTO Poetry.

ERIC Educational Resources Information Center

Kern, Alfred

1983-01-01

Describes an experimental course at Allegheny College in computer-generated poetry, which required students to deal simultaneously with grammar and rhetoric, poetics, the computer and BASIC, logic and artificial intelligence in order to create programs that would generate poetry. Examples of verses produced by course participants are included.…

QUARTERLY TECHNICAL PROGRESS REPORT, JULY, AUGUST, SEPTEMBER 1966.

DTIC Science & Technology

Contents: Circuit research program; Hardware systems research; Software systems research program; Numerical methods, computer arithmetic and...artificial languages; Library automation; Illiac II service , use, and program development; IBM service , use, and program development; Problem specifications; Switching theory and logical design; General laboratory information.

Ambiguity, logic, simplicity, and dynamics: Wittgensteinian evaluative criteria in peer review of quantitative research on categorization.

PubMed

Shimp, Charles P

2004-06-30

Research on categorization has changed over time, and some of these changes resemble how Wittgenstein's views changed from his Tractatus Logico-Philosophicus to his Philosophical Investigations. Wittgenstein initially focused on unambiguous, abstract, parsimonious, logical propositions and rules, and on independent, static, "atomic facts." This approach subsequently influenced the development of logical positivism and thereby may have indirectly influenced method and theory in research on categorization: much animal research on categorization has focused on learning simple, static, logical rules unambiguously interrelating small numbers of independent features. He later rejected logical simplicity and rigor and focused instead on Gestalt ideas about figure-ground reversals and context, the ambiguity of family resemblance, and the function of details of everyday language. Contemporary contextualism has been influenced by this latter position, some features of which appear in contemporary empirical research on categorization. These developmental changes are illustrated by research on avian local and global levels of visual perceptual analysis, categorization of rectangles and moving objects, and artificial grammar learning. Implications are described for peer review of quantitative theory in which ambiguity, logical rigor, simplicity, or dynamics are designed to play important roles.

Systemic Approach for Health Risk Assessment of Ambient Air Concentrations of Benzene in Petrochemical Environments: Integration of Fuzzy Logic, Artificial Neural Network, and IRIS Toxicity Method

PubMed Central

NOVIN, Vahid; GIVEHCHI, Saeed; HOVEIDI, Hassan

2016-01-01

Background: Reliable methods are crucial to cope with uncertainties in the risk analysis process. The aim of this study is to develop an integrated approach to assessing risks of benzene in the petrochemical plant that produces benzene. We offer an integrated system to contribute imprecise variables into the health risk calculation. Methods: The project was conducted in Asaluyeh, southern Iran during the years from 2013 to 2014. Integrated method includes fuzzy logic and artificial neural networks. Each technique had specific computational properties. Fuzzy logic was used for estimation of absorption rate. Artificial neural networks can decrease the noise of the data so applied for prediction of benzene concentration. First, the actual exposure was calculated then it combined with Integrated Risk Information System (IRIS) toxicity factors to assess real health risks. Results: High correlation between the measured and predicted benzene concentration was achieved (R2= 0.941). As for variable distribution, the best estimation of risk in a population implied 33% of workers exposed less than 1×10−5 and 67% inserted between 1.0×10−5 to 9.8×10−5 risk levels. The average estimated risk of exposure to benzene for entire work zones is equal to 2.4×10−5, ranging from 1.5×10−6 to 6.9×10−5. Conclusion: The integrated model is highly flexible as well as the rules possibly will be changed according to the necessities of the user in a different circumstance. The measured exposures can be duplicated well through proposed model and realistic risk assessment data will be produced. PMID:27957464

Computer network defense through radial wave functions

NASA Astrophysics Data System (ADS)

Malloy, Ian J.

The purpose of this research is to synthesize basic and fundamental findings in quantum computing, as applied to the attack and defense of conventional computer networks. The concept focuses on uses of radio waves as a shield for, and attack against traditional computers. A logic bomb is analogous to a landmine in a computer network, and if one was to implement it as non-trivial mitigation, it will aid computer network defense. As has been seen in kinetic warfare, the use of landmines has been devastating to geopolitical regions in that they are severely difficult for a civilian to avoid triggering given the unknown position of a landmine. Thus, the importance of understanding a logic bomb is relevant and has corollaries to quantum mechanics as well. The research synthesizes quantum logic phase shifts in certain respects using the Dynamic Data Exchange protocol in software written for this work, as well as a C-NOT gate applied to a virtual quantum circuit environment by implementing a Quantum Fourier Transform. The research focus applies the principles of coherence and entanglement from quantum physics, the concept of expert systems in artificial intelligence, principles of prime number based cryptography with trapdoor functions, and modeling radio wave propagation against an event from unknown parameters. This comes as a program relying on the artificial intelligence concept of an expert system in conjunction with trigger events for a trapdoor function relying on infinite recursion, as well as system mechanics for elliptic curve cryptography along orbital angular momenta. Here trapdoor both denotes the form of cipher, as well as the implied relationship to logic bombs.

Approach for Autonomous Control of Unmanned Aerial Vehicle Using Intelligent Agents for Knowledge Creation

NASA Technical Reports Server (NTRS)

Dufrene, Warren R., Jr.

2004-01-01

This paper describes the development of a planned approach for Autonomous operation of an Unmanned Aerial Vehicle (UAV). A Hybrid approach will seek to provide Knowledge Generation through the application of Artificial Intelligence (AI) and Intelligent Agents (IA) for UAV control. The applications of several different types of AI techniques for flight are explored during this research effort. The research concentration is directed to the application of different AI methods within the UAV arena. By evaluating AI and biological system approaches. which include Expert Systems, Neural Networks. Intelligent Agents, Fuzzy Logic, and Complex Adaptive Systems, a new insight may be gained into the benefits of AI and CAS techniques applied to achieving true autonomous operation of these systems. Although flight systems were explored, the benefits should apply to many Unmanned Vehicles such as: Rovers. Ocean Explorers, Robots, and autonomous operation systems. A portion of the flight system is broken down into control agents that represent the intelligent agent approach used in AI. After the completion of a successful approach, a framework for applying an intelligent agent is presented. The initial results from simulation of a security agent for communication are presented.

A Logic Basis for Information Retrieval.

ERIC Educational Resources Information Center

Watters, C. R.; Shepherd, M. A.

1987-01-01

Discusses the potential of recent work in artificial intelligence, especially expert systems, for the development of more effective information retrieval systems. Highlights include the role of an expert bibliographic retrieval system and a prototype expert retrieval system, PROBIB-2, that uses MicroProlog to provide deductive reasoning…

Artificial intelligence-based computer modeling tools for controlling slag foaming in electric arc furnaces

NASA Astrophysics Data System (ADS)

Wilson, Eric Lee

Due to increased competition in a world economy, steel companies are currently interested in developing techniques that will allow for the improvement of the steelmaking process, either by increasing output efficiency or by improving the quality of their product, or both. Slag foaming is one practice that has been shown to contribute to both these goals. However, slag foaming is highly dynamic and difficult to model or control. This dissertation describes an effort to use artificial intelligence-based tools (genetic algorithms, fuzzy logic, and neural networks) to both model and control the slag foaming process. Specifically, a neural network is trained and tested on slag foaming data provided by a steel plant. This neural network model is then controlled by a fuzzy logic controller, which in turn is optimized by a genetic algorithm. This tuned controller is then installed at a steel plant and given control be a more efficient slag foaming controller than what was previously used by the steel plant.

On Mathematical Proving

NASA Astrophysics Data System (ADS)

Stefaneas, Petros; Vandoulakis, Ioannis M.

2015-12-01

This paper outlines a logical representation of certain aspects of the process of mathematical proving that are important from the point of view of Artificial Intelligence. Our starting-point is the concept of proof-event or proving, introduced by Goguen, instead of the traditional concept of mathematical proof. The reason behind this choice is that in contrast to the traditional static concept of mathematical proof, proof-events are understood as processes, which enables their use in Artificial Intelligence in such contexts, in which problem-solving procedures and strategies are studied. We represent proof-events as problem-centered spatio-temporal processes by means of the language of the calculus of events, which captures adequately certain temporal aspects of proof-events (i.e. that they have history and form sequences of proof-events evolving in time). Further, we suggest a "loose" semantics for the proof-events, by means of Kolmogorov's calculus of problems. Finally, we expose the intented interpretations for our logical model from the fields of automated theorem-proving and Web-based collective proving.

Acquaintance to Artificial Neural Networks and use of artificial intelligence as a diagnostic tool for tuberculosis: A review.

PubMed

Dande, Payal; Samant, Purva

2018-01-01

Tuberculosis [TB] has afflicted numerous nations in the world. As per a report by the World Health Organization [WHO], an estimated 1.4 million TB deaths in 2015 and an additional 0.4 million deaths resulting from TB disease among people living with HIV, were observed. Most of the TB deaths can be prevented if it is detected at an early stage. The existing processes of diagnosis like blood tests or sputum tests are not only tedious but also take a long time for analysis and cannot differentiate between different drug resistant stages of TB. The need to find newer prompt methods for disease detection has been aided by the latest Artificial Intelligence [AI] tools. Artificial Neural Network [ANN] is one of the important tools that is being used widely in diagnosis and evaluation of medical conditions. This review aims at providing brief introduction to various AI tools that are used in TB detection and gives a detailed description about the utilization of ANN as an efficient diagnostic technique. The paper also provides a critical assessment of ANN and the existing techniques for their diagnosis of TB. Researchers and Practitioners in the field are looking forward to use ANN and other upcoming AI tools such as Fuzzy-logic, genetic algorithms and artificial intelligence simulation as a promising current and future technology tools towards tackling the global menace of Tuberculosis. Latest advancements in the diagnostic field include the combined use of ANN with various other AI tools like the Fuzzy-logic, which has led to an increase in the efficacy and specificity of the diagnostic techniques. Copyright © 2017 Elsevier Ltd. All rights reserved.

The cognitive bases for the design of a new class of fuzzy logic controllers: The clearness transformation fuzzy logic controller

NASA Technical Reports Server (NTRS)

Sultan, Labib; Janabi, Talib

1992-01-01

This paper analyses the internal operation of fuzzy logic controllers as referenced to the human cognitive tasks of control and decision making. Two goals are targeted. The first goal focuses on the cognitive interpretation of the mechanisms employed in the current design of fuzzy logic controllers. This analysis helps to create a ground to explore the potential of enhancing the functional intelligence of fuzzy controllers. The second goal is to outline the features of a new class of fuzzy controllers, the Clearness Transformation Fuzzy Logic Controller (CT-FLC), whereby some new concepts are advanced to qualify fuzzy controllers as 'cognitive devices' rather than 'expert system devices'. The operation of the CT-FLC, as a fuzzy pattern processing controller, is explored, simulated, and evaluated.

Identification of Abnormal System Noise Temperature Patterns in Deep Space Network Antennas Using Neural Network Trained Fuzzy Logic

NASA Technical Reports Server (NTRS)

Lu, Thomas; Pham, Timothy; Liao, Jason

2011-01-01

This paper presents the development of a fuzzy logic function trained by an artificial neural network to classify the system noise temperature (SNT) of antennas in the NASA Deep Space Network (DSN). The SNT data were classified into normal, marginal, and abnormal classes. The irregular SNT pattern was further correlated with link margin and weather data. A reasonably good correlation is detected among high SNT, low link margin and the effect of bad weather; however we also saw some unexpected non-correlations which merit further study in the future.

Graphene-ferroelectric metadevices for nonvolatile memory and reconfigurable logic-gate operations.

PubMed

Kim, Woo Young; Kim, Hyeon-Don; Kim, Teun-Teun; Park, Hyun-Sung; Lee, Kanghee; Choi, Hyun Joo; Lee, Seung Hoon; Son, Jaehyeon; Park, Namkyoo; Min, Bumki

2016-01-27

Memory metamaterials are artificial media that sustain transformed electromagnetic properties without persistent external stimuli. Previous memory metamaterials were realized with phase-change materials, such as vanadium dioxide or chalcogenide glasses, which exhibit memory behaviour with respect to electrically/optically induced thermal stimuli. However, they require a thermally isolated environment for longer retention or strong optical pump for phase-change. Here we demonstrate electrically programmable nonvolatile memory metadevices realised by the hybridization of graphene, a ferroelectric and meta-atoms/meta-molecules, and extend the concept further to establish reconfigurable logic-gate metadevices. For a memory metadevice having a single electrical input, amplitude, phase and even the polarization multi-states were clearly distinguishable with a retention time of over 10 years at room temperature. Furthermore, logic-gate functionalities were demonstrated with reconfigurable logic-gate metadevices having two electrical inputs, with each connected to separate ferroelectric layers that act as the multi-level controller for the doping level of the sandwiched graphene layer.

Quantum Enhanced Inference in Markov Logic Networks

NASA Astrophysics Data System (ADS)

Wittek, Peter; Gogolin, Christian

2017-04-01

Markov logic networks (MLNs) reconcile two opposing schools in machine learning and artificial intelligence: causal networks, which account for uncertainty extremely well, and first-order logic, which allows for formal deduction. An MLN is essentially a first-order logic template to generate Markov networks. Inference in MLNs is probabilistic and it is often performed by approximate methods such as Markov chain Monte Carlo (MCMC) Gibbs sampling. An MLN has many regular, symmetric structures that can be exploited at both first-order level and in the generated Markov network. We analyze the graph structures that are produced by various lifting methods and investigate the extent to which quantum protocols can be used to speed up Gibbs sampling with state preparation and measurement schemes. We review different such approaches, discuss their advantages, theoretical limitations, and their appeal to implementations. We find that a straightforward application of a recent result yields exponential speedup compared to classical heuristics in approximate probabilistic inference, thereby demonstrating another example where advanced quantum resources can potentially prove useful in machine learning.

Graphene-ferroelectric metadevices for nonvolatile memory and reconfigurable logic-gate operations

NASA Astrophysics Data System (ADS)

Kim, Woo Young; Kim, Hyeon-Don; Kim, Teun-Teun; Park, Hyun-Sung; Lee, Kanghee; Choi, Hyun Joo; Lee, Seung Hoon; Son, Jaehyeon; Park, Namkyoo; Min, Bumki

2016-01-01

Memory metamaterials are artificial media that sustain transformed electromagnetic properties without persistent external stimuli. Previous memory metamaterials were realized with phase-change materials, such as vanadium dioxide or chalcogenide glasses, which exhibit memory behaviour with respect to electrically/optically induced thermal stimuli. However, they require a thermally isolated environment for longer retention or strong optical pump for phase-change. Here we demonstrate electrically programmable nonvolatile memory metadevices realised by the hybridization of graphene, a ferroelectric and meta-atoms/meta-molecules, and extend the concept further to establish reconfigurable logic-gate metadevices. For a memory metadevice having a single electrical input, amplitude, phase and even the polarization multi-states were clearly distinguishable with a retention time of over 10 years at room temperature. Furthermore, logic-gate functionalities were demonstrated with reconfigurable logic-gate metadevices having two electrical inputs, with each connected to separate ferroelectric layers that act as the multi-level controller for the doping level of the sandwiched graphene layer.

Quantum Enhanced Inference in Markov Logic Networks.

PubMed

Wittek, Peter; Gogolin, Christian

2017-04-19

Markov logic networks (MLNs) reconcile two opposing schools in machine learning and artificial intelligence: causal networks, which account for uncertainty extremely well, and first-order logic, which allows for formal deduction. An MLN is essentially a first-order logic template to generate Markov networks. Inference in MLNs is probabilistic and it is often performed by approximate methods such as Markov chain Monte Carlo (MCMC) Gibbs sampling. An MLN has many regular, symmetric structures that can be exploited at both first-order level and in the generated Markov network. We analyze the graph structures that are produced by various lifting methods and investigate the extent to which quantum protocols can be used to speed up Gibbs sampling with state preparation and measurement schemes. We review different such approaches, discuss their advantages, theoretical limitations, and their appeal to implementations. We find that a straightforward application of a recent result yields exponential speedup compared to classical heuristics in approximate probabilistic inference, thereby demonstrating another example where advanced quantum resources can potentially prove useful in machine learning.

Quantum Enhanced Inference in Markov Logic Networks

PubMed Central

Wittek, Peter; Gogolin, Christian

2017-01-01

Markov logic networks (MLNs) reconcile two opposing schools in machine learning and artificial intelligence: causal networks, which account for uncertainty extremely well, and first-order logic, which allows for formal deduction. An MLN is essentially a first-order logic template to generate Markov networks. Inference in MLNs is probabilistic and it is often performed by approximate methods such as Markov chain Monte Carlo (MCMC) Gibbs sampling. An MLN has many regular, symmetric structures that can be exploited at both first-order level and in the generated Markov network. We analyze the graph structures that are produced by various lifting methods and investigate the extent to which quantum protocols can be used to speed up Gibbs sampling with state preparation and measurement schemes. We review different such approaches, discuss their advantages, theoretical limitations, and their appeal to implementations. We find that a straightforward application of a recent result yields exponential speedup compared to classical heuristics in approximate probabilistic inference, thereby demonstrating another example where advanced quantum resources can potentially prove useful in machine learning. PMID:28422093

Design of Learning Model of Logic and Algorithms Based on APOS Theory

ERIC Educational Resources Information Center

Hartati, Sulis Janu

2014-01-01

This research questions were "how do the characteristics of learning model of logic & algorithm according to APOS theory" and "whether or not these learning model can improve students learning outcomes". This research was conducted by exploration, and quantitative approach. Exploration used in constructing theory about the…

Using artificial intelligence to improve identification of nanofluid gas-liquid two-phase flow pattern in mini-channel

NASA Astrophysics Data System (ADS)

Xiao, Jian; Luo, Xiaoping; Feng, Zhenfei; Zhang, Jinxin

2018-01-01

This work combines fuzzy logic and a support vector machine (SVM) with a principal component analysis (PCA) to create an artificial-intelligence system that identifies nanofluid gas-liquid two-phase flow states in a vertical mini-channel. Flow-pattern recognition requires finding the operational details of the process and doing computer simulations and image processing can be used to automate the description of flow patterns in nanofluid gas-liquid two-phase flow. This work uses fuzzy logic and a SVM with PCA to improve the accuracy with which the flow pattern of a nanofluid gas-liquid two-phase flow is identified. To acquire images of nanofluid gas-liquid two-phase flow patterns of flow boiling, a high-speed digital camera was used to record four different types of flow-pattern images, namely annular flow, bubbly flow, churn flow, and slug flow. The textural features extracted by processing the images of nanofluid gas-liquid two-phase flow patterns are used as inputs to various identification schemes such as fuzzy logic, SVM, and SVM with PCA to identify the type of flow pattern. The results indicate that the SVM with reduced characteristics of PCA provides the best identification accuracy and requires less calculation time than the other two schemes. The data reported herein should be very useful for the design and operation of industrial applications.

Assessment of groundwater vulnerability using supervised committee to combine fuzzy logic models.

PubMed

Nadiri, Ata Allah; Gharekhani, Maryam; Khatibi, Rahman; Moghaddam, Asghar Asghari

2017-03-01

Vulnerability indices of an aquifer assessed by different fuzzy logic (FL) models often give rise to differing values with no theoretical or empirical basis to establish a validated baseline or to develop a comparison basis between the modeling results and baselines, if any. Therefore, this research presents a supervised committee fuzzy logic (SCFL) method, which uses artificial neural networks to overarch and combine a selection of FL models. The indices are expressed by the widely used DRASTIC framework, which include geological, hydrological, and hydrogeological parameters often subject to uncertainty. DRASTIC indices represent collectively intrinsic (or natural) vulnerability and give a sense of contaminants, such as nitrate-N, percolating to aquifers from the surface. The study area is an aquifer in Ardabil plain, the province of Ardabil, northwest Iran. Improvements on vulnerability indices are achieved by FL techniques, which comprise Sugeno fuzzy logic (SFL), Mamdani fuzzy logic (MFL), and Larsen fuzzy logic (LFL). As the correlation between estimated DRASTIC vulnerability index values and nitrate-N values is as low as 0.4, it is improved significantly by FL models (SFL, MFL, and LFL), which perform in similar ways but have differences. Their synergy is exploited by SCFL and uses the FL modeling results "conditioned" by nitrate-N values to raise their correlation to higher than 0.9.

Role of PROLOG (Programming and Logic) in natural-language processing. Report for September-December 1987

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

McHale, M.L.

The field of artificial Intelligence strives to produce computer programs that exhibit intelligent behavior. One of the areas of interest is the processing of natural language. This report discusses the role of the computer language PROLOG in Natural Language Processing (NLP) both from theoretic and pragmatic viewpoints. The reasons for using PROLOG for NLP are numerous. First, linguists can write natural-language grammars almost directly as PROLOG programs; this allows fast-prototyping of NLP systems and facilitates analysis of NLP theories. Second, semantic representations of natural-language texts that use logic formalisms are readily produced in PROLOG because of PROLOG's logical foundations. Third,more » PROLOG's built-in inferencing mechanisms are often sufficient for inferences on the logical forms produced by NLPs. Fourth, the logical, declarative nature of PROLOG may make it the language of choice for parallel computing systems. Finally, the fact that PROLOG has a de facto standard (Edinburgh) makes the porting of code from one computer system to another virtually trouble free. Perhaps the strongest tie one could make between NLP and PROLOG was stated by John Stuart Mill in his inaugural Address at St. Andrews: The structure of every sentence is a lesson in logic.« less

Artificial Intelligence and the Education of the Learning Disabled.

ERIC Educational Resources Information Center

Halpern, Noemi

1984-01-01

Computer logic is advised for teaching learning disabled children because the computer reduces complicated problems to series of subproblems, then combines solutions of subproblems to solve the initial problem. Seven examples for using the technique are given, including solving verbal math problems. Encourages teachers to learn computer…

Neurocontrol and fuzzy logic: Connections and designs

NASA Technical Reports Server (NTRS)

Werbos, Paul J.

1991-01-01

Artificial neural networks (ANNs) and fuzzy logic are complementary technologies. ANNs extract information from systems to be learned or controlled, while fuzzy techniques mainly use verbal information from experts. Ideally, both sources of information should be combined. For example, one can learn rules in a hybrid fashion, and then calibrate them for better whole-system performance. ANNs offer universal approximation theorems, pedagogical advantages, very high-throughput hardware, and links to neurophysiology. Neurocontrol - the use of ANNs to directly control motors or actuators, etc. - uses five generalized designs, related to control theory, which can work on fuzzy logic systems as well as ANNs. These designs can copy what experts do instead of what they say, learn to track trajectories, generalize adaptive control, and maximize performance or minimize cost over time, even in noisy environments. Design tradeoffs and future directions are discussed throughout.

Modelling of the automatic stabilization system of the aircraft course by a fuzzy logic method

NASA Astrophysics Data System (ADS)

Mamonova, T.; Syryamkin, V.; Vasilyeva, T.

2016-04-01

The problem of the present paper concerns the development of a fuzzy model of the system of an aircraft course stabilization. In this work modelling of the aircraft course stabilization system with the application of fuzzy logic is specified. Thus the authors have used the data taken for an ordinary passenger plane. As a result of the study the stabilization system models were realised in the environment of Matlab package Simulink on the basis of the PID-regulator and fuzzy logic. The authors of the paper have shown that the use of the method of artificial intelligence allows reducing the time of regulation to 1, which is 50 times faster than the time when standard receptions of the management theory are used. This fact demonstrates a positive influence of the use of fuzzy regulation.

Are artificial neural networks black boxes?

PubMed

Benitez, J M; Castro, J L; Requena, I

1997-01-01

Artificial neural networks are efficient computing models which have shown their strengths in solving hard problems in artificial intelligence. They have also been shown to be universal approximators. Notwithstanding, one of the major criticisms is their being black boxes, since no satisfactory explanation of their behavior has been offered. In this paper, we provide such an interpretation of neural networks so that they will no longer be seen as black boxes. This is stated after establishing the equality between a certain class of neural nets and fuzzy rule-based systems. This interpretation is built with fuzzy rules using a new fuzzy logic operator which is defined after introducing the concept of f-duality. In addition, this interpretation offers an automated knowledge acquisition procedure.

The autonomy of biological individuals and artificial models.

PubMed

Moreno, Alvaro; Etxeberria, Arantza; Umerez, Jon

2008-02-01

This paper aims to offer an overview of the meaning of autonomy for biological individuals and artificial models rooted in a specific perspective that pays attention to the historical and structural aspects of its origins and evolution. Taking autopoiesis and the recursivity characteristic of its circular logic as a starting point, we depart from some of its consequences to claim that the theory of autonomy should also take into account historical and structural features. Autonomy should not be considered only in internal or constitutive terms, the largely neglected interactive aspects stemming from it should be equally addressed. Artificial models contribute to get a better understanding of the role of autonomy for life and the varieties of its organization and phenomenological diversity.

Probability matching in perceptrons: Effects of conditional dependence and linear nonseparability.

PubMed

Dawson, Michael R W; Gupta, Maya

2017-01-01

Probability matching occurs when the behavior of an agent matches the likelihood of occurrence of events in the agent's environment. For instance, when artificial neural networks match probability, the activity in their output unit equals the past probability of reward in the presence of a stimulus. Our previous research demonstrated that simple artificial neural networks (perceptrons, which consist of a set of input units directly connected to a single output unit) learn to match probability when presented different cues in isolation. The current paper extends this research by showing that perceptrons can match probabilities when presented simultaneous cues, with each cue signaling different reward likelihoods. In our first simulation, we presented up to four different cues simultaneously; the likelihood of reward signaled by the presence of one cue was independent of the likelihood of reward signaled by other cues. Perceptrons learned to match reward probabilities by treating each cue as an independent source of information about the likelihood of reward. In a second simulation, we violated the independence between cues by making some reward probabilities depend upon cue interactions. We did so by basing reward probabilities on a logical combination (AND or XOR) of two of the four possible cues. We also varied the size of the reward associated with the logical combination. We discovered that this latter manipulation was a much better predictor of perceptron performance than was the logical structure of the interaction between cues. This indicates that when perceptrons learn to match probabilities, they do so by assuming that each signal of a reward is independent of any other; the best predictor of perceptron performance is a quantitative measure of the independence of these input signals, and not the logical structure of the problem being learned.

Probability matching in perceptrons: Effects of conditional dependence and linear nonseparability

PubMed Central

2017-01-01

Probability matching occurs when the behavior of an agent matches the likelihood of occurrence of events in the agent’s environment. For instance, when artificial neural networks match probability, the activity in their output unit equals the past probability of reward in the presence of a stimulus. Our previous research demonstrated that simple artificial neural networks (perceptrons, which consist of a set of input units directly connected to a single output unit) learn to match probability when presented different cues in isolation. The current paper extends this research by showing that perceptrons can match probabilities when presented simultaneous cues, with each cue signaling different reward likelihoods. In our first simulation, we presented up to four different cues simultaneously; the likelihood of reward signaled by the presence of one cue was independent of the likelihood of reward signaled by other cues. Perceptrons learned to match reward probabilities by treating each cue as an independent source of information about the likelihood of reward. In a second simulation, we violated the independence between cues by making some reward probabilities depend upon cue interactions. We did so by basing reward probabilities on a logical combination (AND or XOR) of two of the four possible cues. We also varied the size of the reward associated with the logical combination. We discovered that this latter manipulation was a much better predictor of perceptron performance than was the logical structure of the interaction between cues. This indicates that when perceptrons learn to match probabilities, they do so by assuming that each signal of a reward is independent of any other; the best predictor of perceptron performance is a quantitative measure of the independence of these input signals, and not the logical structure of the problem being learned. PMID:28212422

Feasibility study for future implantable neural-silicon interface devices.

PubMed

Al-Armaghany, Allann; Yu, Bo; Mak, Terrence; Tong, Kin-Fai; Sun, Yihe

2011-01-01

The emerging neural-silicon interface devices bridge nerve systems with artificial systems and play a key role in neuro-prostheses and neuro-rehabilitation applications. Integrating neural signal collection, processing and transmission on a single device will make clinical applications more practical and feasible. This paper focuses on the wireless antenna part and real-time neural signal analysis part of implantable brain-machine interface (BMI) devices. We propose to use millimeter-wave for wireless connections between different areas of a brain. Various antenna, including microstrip patch, monopole antenna and substrate integrated waveguide antenna are considered for the intra-cortical proximity communication. A Hebbian eigenfilter based method is proposed for multi-channel neuronal spike sorting. Folding and parallel design techniques are employed to explore various structures and make a trade-off between area and power consumption. Field programmable logic arrays (FPGAs) are used to evaluate various structures.

An Analysis of Categorical and Quantitative Methods for Planning Under Uncertainty

PubMed Central

Langlotz, Curtis P.; Shortliffe, Edward H.

1988-01-01

Decision theory and logical reasoning are both methods for representing and solving medical decision problems. We analyze the usefulness of these two approaches to medical therapy planning by establishing a simple correspondence between decision theory and non-monotonic logic, a formalization of categorical logical reasoning. The analysis indicates that categorical approaches to planning can be viewed as comprising two decision-theoretic concepts: probabilities (degrees of belief in planning hypotheses) and utilities (degrees of desirability of planning outcomes). We present and discuss examples of the following lessons from this decision-theoretic view of categorical (nonmonotonic) reasoning: (1) Decision theory and artificial intelligence techniques are intended to solve different components of the planning problem. (2) When considered in the context of planning under uncertainty, nonmonotonic logics do not retain the domain-independent characteristics of classical logical reasoning for planning under certainty. (3) Because certain nonmonotonic programming paradigms (e.g., frame-based inheritance, rule-based planning, protocol-based reminders) are inherently problem-specific, they may be inappropriate to employ in the solution of certain types of planning problems. We discuss how these conclusions affect several current medical informatics research issues, including the construction of “very large” medical knowledge bases.

Institutional Logics and Community Service-Learning in Higher Education

ERIC Educational Resources Information Center

Taylor, Alison; Kahlke, Renate

2017-01-01

This paper explores how community service-learning (CSL) participants negotiate competing institutional logics in Canadian higher education. Drawing theoretically from new institutionalism and work on institutional logics, we consider how CSL has developed in Canadian universities and how participants discuss CSL in relation to other dominant…

The Framingham study and treatment guidelines for stroke prevention.

PubMed

Grossi, Enzo

2008-06-01

In recent years, institutional bodies and scientific societies of principal Western countries have produced several guidelines dealing with risk assessment, primary prevention, and treatment of acute stroke. From a prospective, community-based, observational cohort of patients from the Framingham Heart Study, an absolute estimate of risk for stroke alone or stroke or death was determined based on several risk factors, including advanced age, female sex, increased systolic blood pressure, prior stroke or transient ischemic attack, and diabetes mellitus. This algorithm considers many variables and expresses their results as the percentage of risk of developing a fatal or nonfatal stroke in the following 5 years. The author has identified three major pitfalls of this algorithm, which are related to the limitation of the classic statistical approach in handling this kind of nonlinear and complex information: 1) the very large confidence interval of individual risk assessment, 2) the inability to capture the process dynamics, and 3) the inability to capture the disease complexity. The artificial intelligence armamentarium may provide an advantage in the attempt to overcome these limitations. The theoretic background and some application examples related to artificial neural networks (ANNs) and fuzzy logic are reviewed and discussed. Newer approaches linked to artificial intelligence, such as fuzzy logic and ANNs, seem better at addressing the challenge of the increasing complexity of the predisposing factors linked to cerebrovascular events and at predicting future events in an individual patient.

Spatial interpolation and radiological mapping of ambient gamma dose rate by using artificial neural networks and fuzzy logic methods.

PubMed

Yeşilkanat, Cafer Mert; Kobya, Yaşar; Taşkın, Halim; Çevik, Uğur

2017-09-01

The aim of this study was to determine spatial risk dispersion of ambient gamma dose rate (AGDR) by using both artificial neural network (ANN) and fuzzy logic (FL) methods, compare the performances of methods, make dose estimations for intermediate stations with no previous measurements and create dose rate risk maps of the study area. In order to determine the dose distribution by using artificial neural networks, two main networks and five different network structures were used; feed forward ANN; Multi-layer perceptron (MLP), Radial basis functional neural network (RBFNN), Quantile regression neural network (QRNN) and recurrent ANN; Jordan networks (JN), Elman networks (EN). In the evaluation of estimation performance obtained for the test data, all models appear to give similar results. According to the cross-validation results obtained for explaining AGDR distribution, Pearson's r coefficients were calculated as 0.94, 0.91, 0.89, 0.91, 0.91 and 0.92 and RMSE values were calculated as 34.78, 43.28, 63.92, 44.86, 46.77 and 37.92 for MLP, RBFNN, QRNN, JN, EN and FL, respectively. In addition, spatial risk maps showing distributions of AGDR of the study area were created by all models and results were compared with geological, topological and soil structure. Copyright © 2017 Elsevier Ltd. All rights reserved.

Building validation tools for knowledge-based systems

NASA Technical Reports Server (NTRS)

Stachowitz, R. A.; Chang, C. L.; Stock, T. S.; Combs, J. B.

1987-01-01

The Expert Systems Validation Associate (EVA), a validation system under development at the Lockheed Artificial Intelligence Center for more than a year, provides a wide range of validation tools to check the correctness, consistency and completeness of a knowledge-based system. A declarative meta-language (higher-order language), is used to create a generic version of EVA to validate applications written in arbitrary expert system shells. The architecture and functionality of EVA are presented. The functionality includes Structure Check, Logic Check, Extended Structure Check (using semantic information), Extended Logic Check, Semantic Check, Omission Check, Rule Refinement, Control Check, Test Case Generation, Error Localization, and Behavior Verification.

Defect Dynamics in Artificial Colloidal Ice: Real-Time Observation, Manipulation, and Logic Gate.

PubMed

Loehr, Johannes; Ortiz-Ambriz, Antonio; Tierno, Pietro

2016-10-14

We study the defect dynamics in a colloidal spin ice system realized by filling a square lattice of topographic double well islands with repulsively interacting magnetic colloids. We focus on the contraction of defects in the ground state, and contraction or expansion in a metastable biased state. Combining real-time experiments with simulations, we prove that these defects behave like emergent topological monopoles obeying a Coulomb law with an additional line tension. We further show how to realize a completely resettable "nor" gate, which provides guidelines for fabrication of nanoscale logic devices based on the motion of topological magnetic monopoles.

Leveraging Structure: Logical Necessity in the Context of Integer Arithmetic

ERIC Educational Resources Information Center

Bishop, Jessica Pierson; Lamb, Lisa L.; Philipp, Randolph A.; Whitacre, Ian; Schappelle, Bonnie P.

2016-01-01

Looking for, recognizing, and using underlying mathematical structure is an important aspect of mathematical reasoning. We explore the use of mathematical structure in children's integer strategies by developing and exemplifying the construct of logical necessity. Students in our study used logical necessity to approach and use numbers in a…

An interval logic for higher-level temporal reasoning

NASA Technical Reports Server (NTRS)

Schwartz, R. L.; Melliar-Smith, P. M.; Vogt, F. H.; Plaisted, D. A.

1983-01-01

Prior work explored temporal logics, based on classical modal logics, as a framework for specifying and reasoning about concurrent programs, distributed systems, and communications protocols, and reported on efforts using temporal reasoning primitives to express very high level abstract requirements that a program or system is to satisfy. Based on experience with those primitives, this report describes an Interval Logic that is more suitable for expressing such higher level temporal properties. The report provides a formal semantics for the Interval Logic, and several examples of its use. A description of decision procedures for the logic is also included.

Neural manufacturing: a novel concept for processing modeling, monitoring, and control

NASA Astrophysics Data System (ADS)

Fu, Chi Y.; Petrich, Loren; Law, Benjamin

1995-09-01

Semiconductor fabrication lines have become extremely costly, and achieving a good return from such a high capital investment requires efficient utilization of these expensive facilities. It is highly desirable to shorten processing development time, increase fabrication yield, enhance flexibility, improve quality, and minimize downtime. We propose that these ends can be achieved by applying recent advances in the areas of artificial neural networks, fuzzy logic, machine learning, and genetic algorithms. We use the term neural manufacturing to describe such applications. This paper describes our use of artificial neural networks to improve the monitoring and control of semiconductor process.

Understanding Understanding Mathematics. Artificial Intelligence Memo No. 488.

ERIC Educational Resources Information Center

Michener, Edwina Rissland

This document is concerned with the important extra-logical knowledge that is often outside of traditional discussions in mathematics, and looks at some of the ingredients and processes involved in the understanding of mathematics. The goal is to develop a conceptual framework in which to talk about mathematical knowledge and to understand the…

TRAINING RESEARCH UTILIZING MAN-COMPUTER INTERACTIONS, PROMISE AND REALITY.

ERIC Educational Resources Information Center

MCCLELLAND, WILLIAM A.

THE PAPER WAS PRESENTED AS PART OF THE AVIONICS PANEL PROGRAM ON NATURAL AND ARTIFICIAL LOGIC PROCESSORS, SPONSORED BY THE ADVISORY GROUP FOR AERONAUTICAL RESEARCH AND DEVELOPMENT, NATO. SEVERAL CONCEPTUAL PROPOSITIONS IN REGARD TO MAN AND THE COMPUTER ARE OFFERED. THE NATURE OF TRAINING RESEARCH IS EXAMINED. THERE IS ALSO A BRIEF CATEGORIZATION…

First CLIPS Conference Proceedings, volume 2

NASA Technical Reports Server (NTRS)

1990-01-01

The topics of volume 2 of First CLIPS Conference are associated with following applications: quality control; intelligent data bases and networks; Space Station Freedom; Space Shuttle and satellite; user interface; artificial neural systems and fuzzy logic; parallel and distributed processing; enchancements to CLIPS; aerospace; simulation and defense; advisory systems and tutors; and intelligent control.

The Design of Artificial Intelligence Robot Based on Fuzzy Logic Controller Algorithm

NASA Astrophysics Data System (ADS)

Zuhrie, M. S.; Munoto; Hariadi, E.; Muslim, S.

2018-04-01

Artificial Intelligence Robot is a wheeled robot driven by a DC motor that moves along the wall using an ultrasonic sensor as a detector of obstacles. This study uses ultrasonic sensors HC-SR04 to measure the distance between the robot with the wall based ultrasonic wave. This robot uses Fuzzy Logic Controller to adjust the speed of DC motor. When the ultrasonic sensor detects a certain distance, sensor data is processed on ATmega8 then the data goes to ATmega16. From ATmega16, sensor data is calculated based on Fuzzy rules to drive DC motor speed. The program used to adjust the speed of a DC motor is CVAVR program (Code Vision AVR). The readable distance of ultrasonic sensor is 3 cm to 250 cm with response time 0.5 s. Testing of robots on walls with a setpoint value of 9 cm to 10 cm produce an average error value of -12% on the wall of L, -8% on T walls, -8% on U wall, and -1% in square wall.

(Re) Making the Procrustean Bed? Standardization and Customization as Competing Logics in Healthcare

PubMed Central

Mannion, Russell; Exworthy, Mark

2017-01-01

Recent years have witnessed a parallel and seemingly contradictory trend towards both the standardization and the customization of healthcare and medical treatment. Here, we explore what is meant by ‘standardization’ and ‘customization’ in healthcare settings and explore the implications of these changes for healthcare delivery. We frame the paradox of these divergent and opposing factors in terms of institutional logics – the socially constructed rules, practices and beliefs which perpetuate institutional behaviour. As the tension between standardization and customization is fast becoming a critical fault-line within many health systems, there remains an urgent need for more sustained work exploring how these competing logics are articulated, adapted, resisted and co-exist on the front line of care delivery. PMID:28812821

Is Logic in the Mind or in the World? Why a Philosophical Question can Affect the Understanding of Intelligence

NASA Astrophysics Data System (ADS)

Sommer, Hanns; Schreiber, Lothar

2012-05-01

Dreyfus' call ‘to make artificial intelligence (AI) more Heideggerian‘ echoes Heidegger's affirmation that pure calculations produce no ‘intelligence’ (Dreyfus, 2007). But what exactly is it that AI needs more than mathematics? The question in the title gives rise to a reexamination of the basic principles of cognition in Husserl's Phenomenology. Using Husserl's Phenomenological Method, a formalization of these principles is presented that provides the principal idea of cognition, and as a consequence, a ‘natural logic’. Only in a second step, mathematics is obtained from this natural logic by abstraction. The limitations of pure reasoning are demonstrated for fundamental considerations (Hilbert's ‘finite Einstellung’) as well as for the task of solving practical problems. Principles will be presented for the design of general intelligent systems, which make use of a natural logic.

Autonomous vehicle motion control, approximate maps, and fuzzy logic

NASA Technical Reports Server (NTRS)

Ruspini, Enrique H.

1993-01-01

Progress on research on the control of actions of autonomous mobile agents using fuzzy logic is presented. The innovations described encompass theoretical and applied developments. At the theoretical level, results of research leading to the combined utilization of conventional artificial planning techniques with fuzzy logic approaches for the control of local motion and perception actions are presented. Also formulations of dynamic programming approaches to optimal control in the context of the analysis of approximate models of the real world are examined. Also a new approach to goal conflict resolution that does not require specification of numerical values representing relative goal importance is reviewed. Applied developments include the introduction of the notion of approximate map. A fuzzy relational database structure for the representation of vague and imprecise information about the robot's environment is proposed. Also the central notions of control point and control structure are discussed.

ANUBIS: artificial neuromodulation using a Bayesian inference system.

PubMed

Smith, Benjamin J H; Saaj, Chakravarthini M; Allouis, Elie

2013-01-01

Gain tuning is a crucial part of controller design and depends not only on an accurate understanding of the system in question, but also on the designer's ability to predict what disturbances and other perturbations the system will encounter throughout its operation. This letter presents ANUBIS (artificial neuromodulation using a Bayesian inference system), a novel biologically inspired technique for automatically tuning controller parameters in real time. ANUBIS is based on the Bayesian brain concept and modifies it by incorporating a model of the neuromodulatory system comprising four artificial neuromodulators. It has been applied to the controller of EchinoBot, a prototype walking rover for Martian exploration. ANUBIS has been implemented at three levels of the controller; gait generation, foot trajectory planning using Bézier curves, and foot trajectory tracking using a terminal sliding mode controller. We compare the results to a similar system that has been tuned using a multilayer perceptron. The use of Bayesian inference means that the system retains mathematical interpretability, unlike other intelligent tuning techniques, which use neural networks, fuzzy logic, or evolutionary algorithms. The simulation results show that ANUBIS provides significant improvements in efficiency and adaptability of the three controller components; it allows the robot to react to obstacles and uncertainties faster than the system tuned with the MLP, while maintaining stability and accuracy. As well as advancing rover autonomy, ANUBIS could also be applied to other situations where operating conditions are likely to change or cannot be accurately modeled in advance, such as process control. In addition, it demonstrates one way in which neuromodulation could fit into the Bayesian brain framework.

Study on Fault Diagnostics of a Turboprop Engine Using Inverse Performance Model and Artificial Intelligent Methods

NASA Astrophysics Data System (ADS)

Kong, Changduk; Lim, Semyeong

2011-12-01

Recently, the health monitoring system of major gas path components of gas turbine uses mostly the model based method like the Gas Path Analysis (GPA). This method is to find quantity changes of component performance characteristic parameters such as isentropic efficiency and mass flow parameter by comparing between measured engine performance parameters such as temperatures, pressures, rotational speeds, fuel consumption, etc. and clean engine performance parameters without any engine faults which are calculated by the base engine performance model. Currently, the expert engine diagnostic systems using the artificial intelligent methods such as Neural Networks (NNs), Fuzzy Logic and Genetic Algorithms (GAs) have been studied to improve the model based method. Among them the NNs are mostly used to the engine fault diagnostic system due to its good learning performance, but it has a drawback due to low accuracy and long learning time to build learning data base if there are large amount of learning data. In addition, it has a very complex structure for finding effectively single type faults or multiple type faults of gas path components. This work builds inversely a base performance model of a turboprop engine to be used for a high altitude operation UAV using measured performance data, and proposes a fault diagnostic system using the base engine performance model and the artificial intelligent methods such as Fuzzy logic and Neural Network. The proposed diagnostic system isolates firstly the faulted components using Fuzzy Logic, then quantifies faults of the identified components using the NN leaned by fault learning data base, which are obtained from the developed base performance model. In leaning the NN, the Feed Forward Back Propagation (FFBP) method is used. Finally, it is verified through several test examples that the component faults implanted arbitrarily in the engine are well isolated and quantified by the proposed diagnostic system.

Exploring the Common Ground of Rhetoric and Logic.

ERIC Educational Resources Information Center

Lamb, Catherine E.

In teaching the principles of rational discourse in advanced expository writing, it is necessary to clarify the similarities and differences between the logic and rhetoric of Aristotle and to identify a common ground between the two. The study of logic within rhetoric focuses on the inductive standards used to support two kinds of argument: the…

What It Is, What It's Not, and What's Related: Exploring Plato's "Meno"

ERIC Educational Resources Information Center

Heller, Stephen

2010-01-01

Teaching logic typically falls under the areas of argumentation and research, as students are taught the importance of "logos," or logical appeals, in their pursuit of an original point. Cohesive, cogent arguments--devoid of logical fallacy--produce more compelling points, and teachers take great strides in pointing to the problems of…

Identification of artificial groundwater recharging zone using a GIS-based fuzzy logic approach: a case study in a coal mine area of the Damodar Valley, India

NASA Astrophysics Data System (ADS)

Tiwari, Ashwani Kumar; Lavy, Muriel; Amanzio, Gianpiero; De Maio, Marina; Singh, Prasoon Kumar; Mahato, Mukesh Kumar

2017-12-01

The West Bokaro coalfield is a richest coal-mining belt in the Damodar Valley, India. The extensive mining of the area has resulted in disruption of the groundwater availability in terms of both quantity and quality. This has led to a drinking water crisis, especially during the pre-monsoon period in the West Bokaro coalfield area. The characterization of the hydrogeological system and the artificial recharging of the aquifers might help to better manage the problem of the groundwater-level depletion. For this purpose, seven important hydrogeological factors (water depth, slope, drainage, soil, infiltration, lithology, and landuse) have been considered to define the most suitable locations for artificial groundwater recharging in the mining area. Different thematic maps were prepared from existing maps and data sets, remote-sensing images, and field investigations for identification of the most suitable locations for artificial recharge. Thematic layers for these parameters were prepared, classified, weighted, and integrated into a geographic information system (GIS) environment by means of fuzzy logic. The results of the study indicate that about 29 and 31% of the area are very suitable and suitable for recharging purposes in the West Bokaro coalfield. However, the rest of the area is moderate to unsuitable for recharging due to the ongoing mining and related activities in the study area. The groundwater recharging map of the study area was validated with measured electrical conductivity (EC) values in the groundwater, and it indicated that validation can be accepted for the identification of groundwater recharging sites. These findings are providing useful information for the proper planning and sustainable management of the groundwater resources in the study area.

Artificial Intelligence in Space Platforms.

DTIC Science & Technology

1984-12-01

technician would be resposible for filling the data base with DSCS particular information concerning thrusters, 90 b...fault conditions and performing predefined self -preserving (entering a safe-hold stat9) switching actions. Is capable of storing contingency or...on-board for syntactical errors (parity, sign, logic, time). Uses coding or other self -checking techniques to minimize the effects of Internally

Implications for Intelligent Tutoring Systems for Research and Practice in Foreign Language Learning, NFLC Occasional Papers.

ERIC Educational Resources Information Center

Ginsberg, Ralph B.

Most of the now commonplace computer-assisted instruction (CAI) uses computers to increase the capacity to perform logical, numerical, and symbolic computations. However, computers are an interactive and potentially intelligent medium. The implications of artificial intelligence (AI) for learning are more radical than those for traditional CAI. AI…

Can Mathematics be Justified by Natural Logic?

NASA Astrophysics Data System (ADS)

Schreiber, Lothar; Sommer, Hanns

2010-11-01

Charles Darwin claimed that the forms and the behaviour of living beings can be explained from their will to survive. But what are the consequences of this idea for humans knowledge, their theories of nature and their mathematics?. We discuss the view that even Plato's objective world of mathematical objects does not exist absolutely, without the intentions of mathematicians. Using Husserl's Phenomenological Method, cognition can be understood as a process by which meaning is deduced from empirical data relative to intentions. Thereby the essential structure of any cognition process can be detected and this structure is mirrored in logic. A natural logic becomes the direct result of cognition. Only in a second step, mathematics is obtained by abstraction from natural logic. In this way mathematics gains a well-defined foundation and is no longer part of a dubious 'a-priori knowledge' (Kant). This access to mathematics offers a new look on many old problems, e.g. the Petersburg problem and the problem 'P = NP?'. We demonstrate that this new justification of mathematics has also important applications in Artificial Intelligence. Our method provides a procedure to construct an adequate logic to solve most efficiently the problems of a given problem class. Thus, heuristics can be tailor-made for the necessities of applications.

Logical Fallacies in Indonesian EFL Learners' Argumentative Writing: Students' Perspectives

ERIC Educational Resources Information Center

El Khoiri, Niamika; Widiati, Utami

2017-01-01

In argumentative writing, the presence of logical fallacy, which can be simply defined as error in reasoning, shows either illegitimate arguments or irrelevant points that will undermine the strength of a claim. Despite its significant role in determining the quality of an argument, the topic of logical fallacy has not been widely explored in the…

The Effects of Learning a Computer Programming Language on the Logical Reasoning of School Children.

ERIC Educational Resources Information Center

Seidman, Robert H.

The research reported in this paper explores the syntactical and semantic link between computer programming statements and logical principles, and addresses the effects of learning a programming language on logical reasoning ability. Fifth grade students in a public school in Syracuse, New York, were randomly selected as subjects, and then…

Constructing Smart Protocells with Built-In DNA Computational Core to Eliminate Exogenous Challenge.

PubMed

Lyu, Yifan; Wu, Cuichen; Heinke, Charles; Han, Da; Cai, Ren; Teng, I-Ting; Liu, Yuan; Liu, Hui; Zhang, Xiaobing; Liu, Qiaoling; Tan, Weihong

2018-06-06

A DNA reaction network is like a biological algorithm that can respond to "molecular input signals", such as biological molecules, while the artificial cell is like a microrobot whose function is powered by the encapsulated DNA reaction network. In this work, we describe the feasibility of using a DNA reaction network as the computational core of a protocell, which will perform an artificial immune response in a concise way to eliminate a mimicked pathogenic challenge. Such a DNA reaction network (RN)-powered protocell can realize the connection of logical computation and biological recognition due to the natural programmability and biological properties of DNA. Thus, the biological input molecules can be easily involved in the molecular computation and the computation process can be spatially isolated and protected by artificial bilayer membrane. We believe the strategy proposed in the current paper, i.e., using DNA RN to power artificial cells, will lay the groundwork for understanding the basic design principles of DNA algorithm-based nanodevices which will, in turn, inspire the construction of artificial cells, or protocells, that will find a place in future biomedical research.

Artificial immune system algorithm in VLSI circuit configuration

NASA Astrophysics Data System (ADS)

Mansor, Mohd. Asyraf; Sathasivam, Saratha; Kasihmuddin, Mohd Shareduwan Mohd

2017-08-01

In artificial intelligence, the artificial immune system is a robust bio-inspired heuristic method, extensively used in solving many constraint optimization problems, anomaly detection, and pattern recognition. This paper discusses the implementation and performance of artificial immune system (AIS) algorithm integrated with Hopfield neural networks for VLSI circuit configuration based on 3-Satisfiability problems. Specifically, we emphasized on the clonal selection technique in our binary artificial immune system algorithm. We restrict our logic construction to 3-Satisfiability (3-SAT) clauses in order to outfit with the transistor configuration in VLSI circuit. The core impetus of this research is to find an ideal hybrid model to assist in the VLSI circuit configuration. In this paper, we compared the artificial immune system (AIS) algorithm (HNN-3SATAIS) with the brute force algorithm incorporated with Hopfield neural network (HNN-3SATBF). Microsoft Visual C++ 2013 was used as a platform for training, simulating and validating the performances of the proposed network. The results depict that the HNN-3SATAIS outperformed HNN-3SATBF in terms of circuit accuracy and CPU time. Thus, HNN-3SATAIS can be used to detect an early error in the VLSI circuit design.

Logic of discovery or psychology of invention?

NASA Astrophysics Data System (ADS)

Woodward, James F.

1992-02-01

It is noted that Popper separates the creation of concepts, conjectures, hypotheses and theories—the context of invention—from the testing thereof—the context of justification—arguing that only the latter is susceptible of rigorous logical analysis. Efforts on the part of others to shift or eradicate the demarcation established by this distinction are discussed and the relationship of these considerations to the claims of “strong artificial intelligence” is pointed out. It is argued that the mode of education of scientists, as well as reports of celebrated scientists, support Popper's judgement in this matter. An historical episode from Faraday's later career is used to illustrate the historiographical strength of Lakatos' “methodology of research programs.”

Application of fuzzy logic in multicomponent analysis by optodes.

PubMed

Wollenweber, M; Polster, J; Becker, T; Schmidt, H L

1997-01-01

Fuzzy logic can be a useful tool for the determination of substrate concentrations applying optode arrays in combination with flow injection analysis, UV-VIS spectroscopy and kinetics. The transient diffuse reflectance spectra in the visible wavelength region from four optodes were evaluated to carry out the simultaneous determination of artificial mixtures of ampicillin and penicillin. The discrimination of the samples was achieved by changing the composition of the receptor gel and working pH. Different algorithms of pre-processing were applied on the data to reduce the spectral information to a few analytic-specific variables. These variables were used to develop the fuzzy model. After calibration the model was validated by an independent test data set.

The Diagonal Model of Job Satisfaction and Motivation: Extracted from the Logical Comparison of Content and Process Theories

ERIC Educational Resources Information Center

Sahito, Zafarullah; Vaisanen, Pertti

2017-01-01

The purpose of this study is to explore the strongest areas of all prime theories of job satisfaction and motivation to create a new multidimensional model. This model relies on all explored areas from the logical comparison of content and process theories to understand the phenomenon of job satisfaction and motivation of employees. The model…

A feedforward artificial neural network based on quantum effect vector-matrix multipliers.

PubMed

Levy, H J; McGill, T C

1993-01-01

The vector-matrix multiplier is the engine of many artificial neural network implementations because it can simulate the way in which neurons collect weighted input signals from a dendritic arbor. A new technology for building analog weighting elements that is theoretically capable of densities and speeds far beyond anything that conventional VLSI in silicon could ever offer is presented. To illustrate the feasibility of such a technology, a small three-layer feedforward prototype network with five binary neurons and six tri-state synapses was built and used to perform all of the fundamental logic functions: XOR, AND, OR, and NOT.

Research and applications: Artificial intelligence

NASA Technical Reports Server (NTRS)

Raphael, B.; Fikes, R. E.; Chaitin, L. J.; Hart, P. E.; Duda, R. O.; Nilsson, N. J.

1971-01-01

A program of research in the field of artificial intelligence is presented. The research areas discussed include automatic theorem proving, representations of real-world environments, problem-solving methods, the design of a programming system for problem-solving research, techniques for general scene analysis based upon television data, and the problems of assembling an integrated robot system. Major accomplishments include the development of a new problem-solving system that uses both formal logical inference and informal heuristic methods, the development of a method of automatic learning by generalization, and the design of the overall structure of a new complete robot system. Eight appendices to the report contain extensive technical details of the work described.

Instilling exploitable INHIBIT logic gate response for F-/H+ in 'end-off' anthracene-diamine hybrid by simple functional group manipulation: Experimental study aided by DFT calculations

NASA Astrophysics Data System (ADS)

Bhattacharyya, Arghyadeep; Makhal, Subhash Chandra; Ganguly, Aniruddha; Guchhait, Nikhil

2018-03-01

Two anthracene based receptors ADAMN and ANOPD were synthesized and characterized. The response of both towards F- ion has been monitored by UV-Vis and 1H NMR spectroscopy as well as naked eye color change. Interestingly, change in acceptor unit endows ADAMN to behave as a INHIBIT logic gate with F- and H+ as inputs whereas ANOPD remains totally silent towards F-. The reason for this differential behavior has been explored by DFT calculations. The practical utility of the logic gate response of ADAMN was explored by successful paper strip experiment.

EDITORIAL: Opposites attract: nanomagnetism in theory and practice Opposites attract: nanomagnetism in theory and practice

NASA Astrophysics Data System (ADS)

Demming, Anna

2012-09-01

Putting theory into practice in nanotechnology can be far from trivial. Magnetic artificial atoms have been an example of the gulf that can sometimes separate idea from experiment. The step from regular semiconductor artificial atoms to magnetic may not confound the imagination, but it poses no mean fabrication challenge to experimental physicists. In this issue researchers in Germany have successfully fabricated a magnetic artificial atom [1]. As the researchers point out, the systems look promising for further study of the transport properties of 0D magnetic objects. Magnetic behavior in nanoscale systems has inspired a number of technological developments, such as energetically efficient digital logic circuitry [2]. Theory dictates that less energy is dissipated in the manipulation of nanomagnet logic bits than in the manipulation of electrical charges in transistor switches. Among the challenges when putting this into practice is the issue of sequential clocking. The nanomagnets' polarizations need to be rotated through 90° from the easy to the hard axis ready to be set before propagating the logic bits from one stage to the next. Ideally this would be a localized process to allow the efficiencies of a pipe-line computer architecture. Researchers at Virginia Commonwealth University in the US showed that a small voltage applied to a multiferroic nanomagnet can cause this polarization rotation [3]. They further showed that the switching delay of this process is not impracticably long, suggesting that the process is promising for logic circuits that are very fast as well as energy efficient [4]. Researchers in Germany have demonstrated magnetic force microscopy for high resolution imaging using a carbon nanotube filled with iron [5]. A magnetic dipole moment in the iron extends from end to end of the iron nanowire in the carbon nanotube. As a result of the extreme aspect ratio of the nanowire only the pole at one end is involved in the imaging process. The authors describe the system in terms of a magnetic monopole—a notorious theoretical element yet to make the transition to experimental observations. Yet the description works well and as the authors claim, 'The magnetic resolution comes remarkably close to the maximum reported value and can still be improved by choosing iron-filled carbon nanotubes with optimized dimensions'. Artificial atoms, or superatoms, were used in the 1970s as theoretical constructs to investigate molecular structures [6]. Later studies of fullerenes [7, 8] and then other semiconductor artificial atom systems [9] rooted the concept firmly in experimental physics. The electronic behavior in these systems has inspired some fascinating technological developments [10]. Artificial atom quantum dots are small enough to be considered zero-dimensional, giving rise to quantum confinement effects: electrons added to quantum dots occupy discrete quantum levels, and spin-paired electrons can produce spin-zero electron states. The systems have demonstrated great promise for potential qubits for quantum computers. Silicon has a number of advantages for these applications including scalability and long spin coherence times. However, progress has been hindered in practice by difficulties in creating devices with sufficiently low disorder particularly at the Si/SiO2 interface. Researchers at the University of New South Wales in Australia have overcome these fabrication challenges and demonstrated a low-disorder silicon metal-oxide-semiconductor quantum dot where the number of electrons can be tuned between 0 and 27 [11]. In this issue R-G Dengel, A Frey, K Brunner, C Gould and L W Molenkamp from Universität Würzburg in Germany create magnetic artificial atoms by replacing the traditionally used GaAs-based heterostructure with a ZnSe-based system where doping the quantum well with Mn gives it magnetic properties [1]. As they point out, 'From the fabrication point of view, three technical issues make this straightforward seeming idea very challenging to realize'. The interface between the III-V substrate and the ZnSe gives rise to strong polar fields. The lattice mismatch means that the heterostructure must be kept very thin raising further fabrication challenges, and finally there is also the issue of a lack of Schottky contact material for ZnSe. The authors demonstrate impressive ingenuity to develop a multi-step electron beam lithography process to produce the ZnSe dots. They also present preliminary transport data that confirm the magnetic nature of the resulting artificial atom. We are all familiar with the old adage: 'In theory there is no difference between theory and practice. But in practice there is.' While great progress in scientific research often builds on important synergies between theory and experiment, what the mind can conceive may take a great deal of cunning and skill in the laboratory to achieve. Yet as all these examples in nanotechnology fabrication research show, with each triumph in nanofabrication, progress is made to bridge the gap between theory and practice. References [1] Dengel R-G, Frey A, Brunner K, Gould C and Molenkamp L W 2012 Fabrication of magnetic artificial atoms Nanotechnology 23 395301 [2] Imre A, Csaba G, Ji L, Orlov A, Bernstein G H and Porod W 2006 Majority logic gate for magnetic quantum-dot cellular automata Science 311 205-8 [3] Atalusimha J and Bandyopadhyay S 2010 Bennett clocking of nanomagnetic logic using multiferroic single-domain nanomagnets Appl. Phys. Lett. 97 173105 [4] Fashami M S, Roy K, Atulasimha J and Bandyopadhyay S 2011 Magnetization dynamics, Bennett clocking and associated energy dissipation in multiferroic logic Nanotechnology 22 155201 [5] Wolny F, Mühl T, Weissker U, Lipert K, Schumann J, Leonhardt A and Büchner B 2010 Iron filled carbon nanotubes as novel monopole-like sensors for quantitative magnetic force microscopy Nanotechnology 21 435501 [6]Carhart R E, Smith D H, Brown H and Djerassi C 1975 Applications of artificial intelligence for chemical inference. XVII. An approach to computer-assisted elucidation of molecular structure J. Am. Chem. Soc. 97 5755-62 [7] Saito S, Oshiyama A, Miyamoto Y, Hamada N and Sawada S 1992 Electronic structure of fullerenes and fullerides: artificial atoms and their solids Nanotechnology 3 167-72 [8] Shinohara H 2000 Endohedral metallofullerenes Rep. Prog. Phys. 63 843-92 [9] Heitmann D, Kern K, Demel T, Grambow P, Ploog K and Zhang Y H 1992 Spectroscopy of quantum dots and antidots Surf. Sci. 267 245-52 [10] Andergassen S, Meen V, Schoeller H, Splettstoesser J and Wegewijs M R 2010 Charge transport through single molecules, quantum dots and quantum wires Nanotechnology 21 272001 [11] Lim W H, Yang C H, Zwanenburg F A and Dzurak A S 2011 Spin filling of valley-orbit states in a silicon quantum dot Nanotechnology 22 335704

A Review of Intelligent Driving Style Analysis Systems and Related Artificial Intelligence Algorithms

PubMed Central

Meiring, Gys Albertus Marthinus; Myburgh, Hermanus Carel

2015-01-01

In this paper the various driving style analysis solutions are investigated. An in-depth investigation is performed to identify the relevant machine learning and artificial intelligence algorithms utilised in current driver behaviour and driving style analysis systems. This review therefore serves as a trove of information, and will inform the specialist and the student regarding the current state of the art in driver style analysis systems, the application of these systems and the underlying artificial intelligence algorithms applied to these applications. The aim of the investigation is to evaluate the possibilities for unique driver identification utilizing the approaches identified in other driver behaviour studies. It was found that Fuzzy Logic inference systems, Hidden Markov Models and Support Vector Machines consist of promising capabilities to address unique driver identification algorithms if model complexity can be reduced. PMID:26690164

A Review of Intelligent Driving Style Analysis Systems and Related Artificial Intelligence Algorithms.

PubMed

Meiring, Gys Albertus Marthinus; Myburgh, Hermanus Carel

2015-12-04

In this paper the various driving style analysis solutions are investigated. An in-depth investigation is performed to identify the relevant machine learning and artificial intelligence algorithms utilised in current driver behaviour and driving style analysis systems. This review therefore serves as a trove of information, and will inform the specialist and the student regarding the current state of the art in driver style analysis systems, the application of these systems and the underlying artificial intelligence algorithms applied to these applications. The aim of the investigation is to evaluate the possibilities for unique driver identification utilizing the approaches identified in other driver behaviour studies. It was found that Fuzzy Logic inference systems, Hidden Markov Models and Support Vector Machines consist of promising capabilities to address unique driver identification algorithms if model complexity can be reduced.

Group Solutions, Too! More Cooperative Logic Activities for Grades K-4. Teacher's Guide. LHS GEMS.

ERIC Educational Resources Information Center

Goodman, Jan M.; Kopp, Jaine

There is evidence that structured cooperative logic is an effective way to introduce or reinforce mathematics concepts, explore thinking processes basic to both math and science, and develop the important social skills of cooperative problem-solving. This book contains a number of cooperative logic activities for grades K-4 in order to improve…

Recent Trends in Spintronics-Based Nanomagnetic Logic

NASA Astrophysics Data System (ADS)

Das, Jayita; Alam, Syed M.; Bhanja, Sanjukta

2014-09-01

With the growing concerns of standby power in sub-100-nm CMOS technologies, alternative computing techniques and memory technologies are explored. Spin transfer torque magnetoresistive RAM (STT-MRAM) is one such nonvolatile memory relying on magnetic tunnel junctions (MTJs) to store information. It uses spin transfer torque to write information and magnetoresistance to read information. In 2012, Everspin Technologies, Inc. commercialized the first 64Mbit Spin Torque MRAM. On the computing end, nanomagnetic logic (NML) is a promising technique with zero leakage and high data retention. In 2000, Cowburn and Welland first demonstrated its potential in logic and information propagation through magnetostatic interaction in a chain of single domain circular nanomagnetic dots of Supermalloy (Ni80Fe14Mo5X1, X is other metals). In 2006, Imre et al. demonstrated wires and majority gates followed by coplanar cross wire systems demonstration in 2010 by Pulecio et al. Since 2004 researchers have also investigated the potential of MTJs in logic. More recently with dipolar coupling between MTJs demonstrated in 2012, logic-in-memory architecture with STT-MRAM have been investigated. The architecture borrows the computing concept from NML and read and write style from MRAM. The architecture can switch its operation between logic and memory modes with clock as classifier. Further through logic partitioning between MTJ and CMOS plane, a significant performance boost has been observed in basic computing blocks within the architecture. In this work, we have explored the developments in NML, in MTJs and more recent developments in hybrid MTJ/CMOS logic-in-memory architecture and its unique logic partitioning capability.

Night glucose control with MD-Logic artificial pancreas in home setting: a single blind, randomized crossover trial-interim analysis.

PubMed

Nimri, Revital; Muller, Ido; Atlas, Eran; Miller, Shahar; Kordonouri, Olga; Bratina, Natasa; Tsioli, Christiana; Stefanija, Magdalena A; Danne, Thomas; Battelino, Tadej; Phillip, Moshe

2014-03-01

Artificial pancreas (AP) systems have shown an improvement in glucose control and a reduced risk of nocturnal hypoglycemia under controlled conditions but remain to be evaluated under daily-life conditions. To assess the feasibility, safety, and efficacy of the MD-Logic AP in controlling nocturnal glucose levels in the patient's home. Two-arm study, each covering four consecutive nights comparing the MD-Logic AP ('closed-loop' arm) with sensor-augmented pump therapy ('control' arm). Fifteen patients (mean age 19 ± 10.4 yr, A1c 7.5 ± 0.5% or 58 ± 5.9 mmol/mol, diabetes duration 9.9 ± 8.2 yr) were randomly assigned either to 'Group A' (first 'closed-loop', then 'control' arm) or to 'Group B' (vice versa). Investigators were masked to treatment intervention. Primary endpoints were the time spent with glucose levels below 70 mg/dL and the percentage of nights in which the mean overnight glucose levels were within 90-140 mg/dL. Endpoint analyses were based on unmodified sensor glucose readings of the four study nights. Time of glucose levels spent below 70 mg/dL was significantly shorter on the closed-loop nights than on control nights, median and interquartile range 3.8 (0, 11.6) and 48.7 (0.6, 67.9) min, respectively; p = 0.0034. The percentage of individual nights in which mean overnight glucose level was within 90-140 mg/dL was 67 (33, 88), and 50 (25, 75), under closed-loop and control nights, respectively, with no statistical difference. Secondary endpoint analyses demonstrated significant improvements in hypoglycemia parameters. No serious adverse events were reported. This interim analysis demonstrates the feasibility, safety, and efficiency of the MD-Logic AP system in home use, and demonstrates an improvement over sensor-augmented pump therapy. (ClinicalTrials.gov identifier NCT01726829). © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Knowledge-Intensive, Interactive and Efficient Relational Pattern Learning

DTIC Science & Technology

2006-09-01

insightful comments. References 1. E. Alphonse and C. Rouveirol. Lazy propositionalisation for relational learning. In H. W., editor, 14th European...their atom-and-bond structures. Some other work, especially on propositionalization of First Order Logic (FOL) ( Alphonse and Rouveirol 2000), has been...Applications of Artificial Intelligence Conference (IAAI-04), page To Appear, 2004. E. Alphonse and C. Rouveirol. Lazy propositionalisation for

Effect of humidity during artificial extraction on the subsequent vigor of pine pollen

Treesearch

Russell A. Ryker

1963-01-01

Controlled pollination of pines generally has been disappointing because cones contain too few seeds. We need to develop better techniques for collecting, extracting, and storing pollen, as well as better bagging procedures. A logical first step is to learn more about collecting and extracting pollen. In a recent study I found that extracting pollen of jack pine (Pinus...

Neuro-fuzzy controller to navigate an unmanned vehicle.

PubMed

Selma, Boumediene; Chouraqui, Samira

2013-12-01

A Neuro-fuzzy control method for an Unmanned Vehicle (UV) simulation is described. The objective is guiding an autonomous vehicle to a desired destination along a desired path in an environment characterized by a terrain and a set of distinct objects, such as obstacles like donkey traffic lights and cars circulating in the trajectory. The autonomous navigate ability and road following precision are mainly influenced by its control strategy and real-time control performance. Fuzzy Logic Controller can very well describe the desired system behavior with simple "if-then" relations owing the designer to derive "if-then" rules manually by trial and error. On the other hand, Neural Networks perform function approximation of a system but cannot interpret the solution obtained neither check if its solution is plausible. The two approaches are complementary. Combining them, Neural Networks will allow learning capability while Fuzzy-Logic will bring knowledge representation (Neuro-Fuzzy). In this paper, an artificial neural network fuzzy inference system (ANFIS) controller is described and implemented to navigate the autonomous vehicle. Results show several improvements in the control system adjusted by neuro-fuzzy techniques in comparison to the previous methods like Artificial Neural Network (ANN).

Synthetic Ion Channels and DNA Logic Gates as Components of Molecular Robots.

PubMed

Kawano, Ryuji

2018-02-19

A molecular robot is a next-generation biochemical machine that imitates the actions of microorganisms. It is made of biomaterials such as DNA, proteins, and lipids. Three prerequisites have been proposed for the construction of such a robot: sensors, intelligence, and actuators. This Minireview focuses on recent research on synthetic ion channels and DNA computing technologies, which are viewed as potential candidate components of molecular robots. Synthetic ion channels, which are embedded in artificial cell membranes (lipid bilayers), sense ambient ions or chemicals and import them. These artificial sensors are useful components for molecular robots with bodies consisting of a lipid bilayer because they enable the interface between the inside and outside of the molecular robot to function as gates. After the signal molecules arrive inside the molecular robot, they can operate DNA logic gates, which perform computations. These functions will be integrated into the intelligence and sensor sections of molecular robots. Soon, these molecular machines will be able to be assembled to operate as a mass microrobot and play an active role in environmental monitoring and in vivo diagnosis or therapy. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Heat wave hazard classification and risk assessment using artificial intelligence fuzzy logic.

PubMed

Keramitsoglou, Iphigenia; Kiranoudis, Chris T; Maiheu, Bino; De Ridder, Koen; Daglis, Ioannis A; Manunta, Paolo; Paganini, Marc

2013-10-01

The average summer temperatures as well as the frequency and intensity of hot days and heat waves are expected to increase due to climate change. Motivated by this consequence, we propose a methodology to evaluate the monthly heat wave hazard and risk and its spatial distribution within large cities. A simple urban climate model with assimilated satellite-derived land surface temperature images was used to generate a historic database of urban air temperature fields. Heat wave hazard was then estimated from the analysis of these hourly air temperatures distributed at a 1-km grid over Athens, Greece, by identifying the areas that are more likely to suffer higher temperatures in the case of a heat wave event. Innovation lies in the artificial intelligence fuzzy logic model that was used to classify the heat waves from mild to extreme by taking into consideration their duration, intensity and time of occurrence. The monthly hazard was subsequently estimated as the cumulative effect from the individual heat waves that occurred at each grid cell during a month. Finally, monthly heat wave risk maps were produced integrating geospatial information on the population vulnerability to heat waves calculated from socio-economic variables.

Fuzzy logic, artificial neural network and mathematical model for prediction of white mulberry drying kinetics

NASA Astrophysics Data System (ADS)

Jahedi Rad, Shahpour; Kaveh, Mohammad; Sharabiani, Vali Rasooli; Taghinezhad, Ebrahim

2018-05-01

The thin-layer convective- infrared drying behavior of white mulberry was experimentally studied at infrared power levels of 500, 1000 and 1500 W, drying air temperatures of 40, 55 and 70 °C and inlet drying air speeds of 0.4, 1 and 1.6 m/s. Drying rate raised with the rise of infrared power levels at a distinct air temperature and velocity and thus decreased the drying time. Five mathematical models describing thin-layer drying have been fitted to the drying data. Midlli et al. model could satisfactorily describe the convective-infrared drying of white mulberry fruit with the values of the correlation coefficient (R 2=0.9986) and root mean square error of (RMSE= 0.04795). Artificial neural network (ANN) and fuzzy logic methods was desirably utilized for modeling output parameters (moisture ratio (MR)) regarding input parameters. Results showed that output parameters were more accurately predicted by fuzzy model than by the ANN and mathematical models. Correlation coefficient (R 2) and RMSE generated by the fuzzy model (respectively 0.9996 and 0.01095) were higher than referred values for the ANN model (0.9990 and 0.01988 respectively).

Regulatory Anatomy: How "Safety Logics" Structure European Transplant Medicine.

PubMed

Hoeyer, Klaus

2015-07-01

This article proposes the term "safety logics" to understand attempts within the European Union (EU) to harmonize member state legislation to ensure a safe and stable supply of human biological material for transplants and transfusions. With safety logics, I refer to assemblages of discourses, legal documents, technological devices, organizational structures, and work practices aimed at minimizing risk. I use this term to reorient the analytical attention with respect to safety regulation. Instead of evaluating whether safety is achieved, the point is to explore the types of "safety" produced through these logics as well as to consider the sometimes unintended consequences of such safety work. In fact, the EU rules have been giving rise to complaints from practitioners finding the directives problematic and inadequate. In this article, I explore the problems practitioners face and why they arise. In short, I expose the regulatory anatomy of the policy landscape.

Classification of reflected signals from cavitated tooth surfaces using an artificial intelligence technique incorporating a fiber optic displacement sensor

NASA Astrophysics Data System (ADS)

Rahman, Husna Abdul; Harun, Sulaiman Wadi; Arof, Hamzah; Irawati, Ninik; Musirin, Ismail; Ibrahim, Fatimah; Ahmad, Harith

2014-05-01

An enhanced dental cavity diameter measurement mechanism using an intensity-modulated fiber optic displacement sensor (FODS) scanning and imaging system, fuzzy logic as well as a single-layer perceptron (SLP) neural network, is presented. The SLP network was employed for the classification of the reflected signals, which were obtained from the surfaces of teeth samples and captured using FODS. Two features were used for the classification of the reflected signals with one of them being the output of a fuzzy logic. The test results showed that the combined fuzzy logic and SLP network methodology contributed to a 100% classification accuracy of the network. The high-classification accuracy significantly demonstrates the suitability of the proposed features and classification using SLP networks for classifying the reflected signals from teeth surfaces, enabling the sensor to accurately measure small diameters of tooth cavity of up to 0.6 mm. The method remains simple enough to allow its easy integration in existing dental restoration support systems.

A.I.-based real-time support for high performance aircraft operations

NASA Technical Reports Server (NTRS)

Vidal, J. J.

1985-01-01

Artificial intelligence (AI) based software and hardware concepts are applied to the handling system malfunctions during flight tests. A representation of malfunction procedure logic using Boolean normal forms are presented. The representation facilitates the automation of malfunction procedures and provides easy testing for the embedded rules. It also forms a potential basis for a parallel implementation in logic hardware. The extraction of logic control rules, from dynamic simulation and their adaptive revision after partial failure are examined. It uses a simplified 2-dimensional aircraft model with a controller that adaptively extracts control rules for directional thrust that satisfies a navigational goal without exceeding pre-established position and velocity limits. Failure recovery (rule adjusting) is examined after partial actuator failure. While this experiment was performed with primitive aircraft and mission models, it illustrates an important paradigm and provided complexity extrapolations for the proposed extraction of expertise from simulation, as discussed. The use of relaxation and inexact reasoning in expert systems was also investigated.

Classification of reflected signals from cavitated tooth surfaces using an artificial intelligence technique incorporating a fiber optic displacement sensor.

PubMed

Rahman, Husna Abdul; Harun, Sulaiman Wadi; Arof, Hamzah; Irawati, Ninik; Musirin, Ismail; Ibrahim, Fatimah; Ahmad, Harith

2014-05-01

An enhanced dental cavity diameter measurement mechanism using an intensity-modulated fiber optic displacement sensor (FODS) scanning and imaging system, fuzzy logic as well as a single-layer perceptron (SLP) neural network, is presented. The SLP network was employed for the classification of the reflected signals, which were obtained from the surfaces of teeth samples and captured using FODS. Two features were used for the classification of the reflected signals with one of them being the output of a fuzzy logic. The test results showed that the combined fuzzy logic and SLP network methodology contributed to a 100% classification accuracy of the network. The high-classification accuracy significantly demonstrates the suitability of the proposed features and classification using SLP networks for classifying the reflected signals from teeth surfaces, enabling the sensor to accurately measure small diameters of tooth cavity of up to 0.6 mm. The method remains simple enough to allow its easy integration in existing dental restoration support systems.

Using fuzzy logic to integrate neural networks and knowledge-based systems

NASA Technical Reports Server (NTRS)

Yen, John

1991-01-01

Outlined here is a novel hybrid architecture that uses fuzzy logic to integrate neural networks and knowledge-based systems. The author's approach offers important synergistic benefits to neural nets, approximate reasoning, and symbolic processing. Fuzzy inference rules extend symbolic systems with approximate reasoning capabilities, which are used for integrating and interpreting the outputs of neural networks. The symbolic system captures meta-level information about neural networks and defines its interaction with neural networks through a set of control tasks. Fuzzy action rules provide a robust mechanism for recognizing the situations in which neural networks require certain control actions. The neural nets, on the other hand, offer flexible classification and adaptive learning capabilities, which are crucial for dynamic and noisy environments. By combining neural nets and symbolic systems at their system levels through the use of fuzzy logic, the author's approach alleviates current difficulties in reconciling differences between low-level data processing mechanisms of neural nets and artificial intelligence systems.

Logic Learning Machine and standard supervised methods for Hodgkin's lymphoma prognosis using gene expression data and clinical variables.

PubMed

Parodi, Stefano; Manneschi, Chiara; Verda, Damiano; Ferrari, Enrico; Muselli, Marco

2018-03-01

This study evaluates the performance of a set of machine learning techniques in predicting the prognosis of Hodgkin's lymphoma using clinical factors and gene expression data. Analysed samples from 130 Hodgkin's lymphoma patients included a small set of clinical variables and more than 54,000 gene features. Machine learning classifiers included three black-box algorithms ( k-nearest neighbour, Artificial Neural Network, and Support Vector Machine) and two methods based on intelligible rules (Decision Tree and the innovative Logic Learning Machine method). Support Vector Machine clearly outperformed any of the other methods. Among the two rule-based algorithms, Logic Learning Machine performed better and identified a set of simple intelligible rules based on a combination of clinical variables and gene expressions. Decision Tree identified a non-coding gene ( XIST) involved in the early phases of X chromosome inactivation that was overexpressed in females and in non-relapsed patients. XIST expression might be responsible for the better prognosis of female Hodgkin's lymphoma patients.

Intelligent systems for the autonomous exploration of Titan and Enceladus

NASA Astrophysics Data System (ADS)

Furfaro, Roberto; Lunine, Jonathan I.; Kargel, Jeffrey S.; Fink, Wolfgang

2008-04-01

Future planetary exploration of the outer satellites of the Solar System will require higher levels of onboard automation, including autonomous determination of sites where the probability of significant scientific findings is highest. Generally, the level of needed automation is heavily influenced by the distance between Earth and the robotic explorer(s) (e.g. spacecraft(s), rover(s), and balloon(s)). Therefore, planning missions to the outer satellites mandates the analysis, design and integration within the mission architecture of semi- and/or completely autonomous intelligence systems. Such systems should (1) include software packages that enable fully automated and comprehensive identification, characterization, and quantification of feature information within an operational region with subsequent target prioritization and selection for close-up reexamination; and (2) integrate existing information with acquired, "in transit" spatial and temporal sensor data to automatically perform intelligent planetary reconnaissance, which includes identification of sites with the highest potential to yield significant geological and astrobiological information. In this paper we review and compare some of the available Artificial Intelligence (AI) schemes and their adaptation to the problem of designing expert systems for onboard-based, autonomous science to be performed in the course of outer satellites exploration. More specifically, the fuzzy-logic framework proposed is analyzed in some details to show the effectiveness of such a scheme when applied to the problem of designing expert systems capable of identifying and further exploring regions on Titan and/or Enceladus that have the highest potential to yield evidence for past or present life. Based on available information (e.g., Cassini data), the current knowledge and understanding of Titan and Enceladus environments is evaluated to define a path for the design of a fuzzy-based system capable of reasoning over collected data and capable of providing the inference required to autonomously optimize future outer satellites explorations.

A DNA network as an information processing system.

PubMed

Santini, Cristina Costa; Bath, Jonathan; Turberfield, Andrew J; Tyrrell, Andy M

2012-01-01

Biomolecular systems that can process information are sought for computational applications, because of their potential for parallelism and miniaturization and because their biocompatibility also makes them suitable for future biomedical applications. DNA has been used to design machines, motors, finite automata, logic gates, reaction networks and logic programs, amongst many other structures and dynamic behaviours. Here we design and program a synthetic DNA network to implement computational paradigms abstracted from cellular regulatory networks. These show information processing properties that are desirable in artificial, engineered molecular systems, including robustness of the output in relation to different sources of variation. We show the results of numerical simulations of the dynamic behaviour of the network and preliminary experimental analysis of its main components.

DNA-Based Dynamic Reaction Networks.

PubMed

Fu, Ting; Lyu, Yifan; Liu, Hui; Peng, Ruizi; Zhang, Xiaobing; Ye, Mao; Tan, Weihong

2018-05-21

Deriving from logical and mechanical interactions between DNA strands and complexes, DNA-based artificial reaction networks (RNs) are attractive for their high programmability, as well as cascading and fan-out ability, which are similar to the basic principles of electronic logic gates. Arising from the dream of creating novel computing mechanisms, researchers have placed high hopes on the development of DNA-based dynamic RNs and have strived to establish the basic theories and operative strategies of these networks. This review starts by looking back on the evolution of DNA dynamic RNs; in particular' the most significant applications in biochemistry occurring in recent years. Finally, we discuss the perspectives of DNA dynamic RNs and give a possible direction for the development of DNA circuits. Copyright © 2018. Published by Elsevier Ltd.

Logic-Gate Functions in Chemomechanical Materials.

PubMed

Schneider, Hans-Jörg

2017-09-06

Chemomechanical polymers that change their shape or volume on stimulation by multiple external chemical signals, particularly on the basis of selective molecular recognition, are discussed. Several examples illustrate how such materials, usually in the form of hydrogels, can be used for the design of chemically triggered valves or artificial muscles and applied, for example, in self-healing materials or drug delivery. The most attractive feature of such materials is that they can combine sensor and actuator within single units, from nano- to macrosize. Simultaneous action of a cofactor allows selective response in the sense of AND logic gates by, for example, amino acids and peptides, which without the presence of a second effector do not induce any changes. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Decade Review (1999-2009): Artificial Intelligence Techniques in Student Modeling

NASA Astrophysics Data System (ADS)

Drigas, Athanasios S.; Argyri, Katerina; Vrettaros, John

Artificial Intelligence applications in educational field are getting more and more popular during the last decade (1999-2009) and that is why much relevant research has been conducted. In this paper, we present the most interesting attempts to apply artificial intelligence methods such as fuzzy logic, neural networks, genetic programming and hybrid approaches such as neuro - fuzzy systems and genetic programming neural networks (GPNN) in student modeling. This latest research trend is a part of every Intelligent Tutoring System and aims at generating and updating a student model in order to modify learning content to fit individual needs or to provide reliable assessment and feedback to student's answers. In this paper, we make a brief presentation of methods used to point out their qualities and then we attempt a navigation to the most representative studies sought in the decade of our interest after classifying them according to the principal aim they attempted to serve.

Artificial transmembrane ion channels from self-assembling peptide nanotubes

NASA Astrophysics Data System (ADS)

Ghadiri, M. Reza; Granja, Juan R.; Buehler, Lukas K.

1994-05-01

NATURALLY occurring membrane channels and pores are formed from a large family of diverse proteins, peptides and organic secon-dary metabolites whose vital biological functions include control of ion flow, signal transduction, molecular transport and produc-tion of cellular toxins. But despite the availability of a large amount of biochemical information about these molecules1, the design and synthesis of artificial systems that can mimic the bio-logical function of natural compounds remains a formidable task2-12. Here we present a simple strategy for the design of artifi-cial membrane ion channels based on a self-assembled cylindrical β-sheet peptide architecture13. Our systems-essentially stacks of peptide rings-display good channel-mediated ion-transport activ-ity with rates exceeding 107 ions s-1, rivalling the performance of many naturally occurring counterparts. Such molecular assemblies should find use in the design of novel cytotoxic agents, membrane transport vehicles and drug-delivery systems.

CI Controls for Energy and Environment

NASA Technical Reports Server (NTRS)

Biondo, Samuel J.

1996-01-01

Computational intelligence (CI) is a rapidly evolving field that utilizes life imitating metaphors for guiding model building including, but not limited to neural networks, fuzzy logic, genetic algorithms, artificial life, and hybrid CI paradigms. Although the boundaries between artificial intelligence (AI) and CI are not distinct, their research communities are separate and distinct. CI researchers tend to focus on processing numerical data from sensors, while the AI community generally relies on symbolic computing to capture human knowledge. In both areas, there is a great deal of interest and activity in hybrid systems that can offset the limitations of individual methods, extend their capabilities, and create new capabilities. Examples of the benefits that can accrue from hybrid systems are contained.

Zero-Energy Optical Logic: Can It Be Practical?

NASA Astrophysics Data System (ADS)

Caulfield, H. John

The thermodynamic “permission” to build a device that can evaluate a sequence of logic operations that operate at zero energy has existed for about 40 years. That is, physics allows it in principle. Conceptual solutions have been explored ever since then. A great number of important concepts were developed in so doing. Over the last four years, my colleagues and I have explored the possibility of a constructive proof. And we finally succeeded. Somewhat unexpectedly, we found such a proof and found that lossless logic systems could actually be built. And, as we had anticipated, it can only be implemented by optics. That raises a new question: Might an optical zero-energy logic system actually be good enough to displace electronic versions in some cases? In this paper, I do not even try to answer that question, but I do lay out some problems now blocking practical applications and show some promising approaches to solving them. The problems addressed are speed, size, and error rate. The anticipated speed problem simply vanishes, as it was an inference from the implicit assumption that the logic would be electronic. But the other two problems are real and must be addressed if energy-free logic is to have any significant applications. Initial steps in solving the size and error rate are addressed in more detail.

An Overview of the Runtime Verification Tool Java PathExplorer

NASA Technical Reports Server (NTRS)

Havelund, Klaus; Rosu, Grigore; Clancy, Daniel (Technical Monitor)

2002-01-01

We present an overview of the Java PathExplorer runtime verification tool, in short referred to as JPAX. JPAX can monitor the execution of a Java program and check that it conforms with a set of user provided properties formulated in temporal logic. JPAX can in addition analyze the program for concurrency errors such as deadlocks and data races. The concurrency analysis requires no user provided specification. The tool facilitates automated instrumentation of a program's bytecode, which when executed will emit an event stream, the execution trace, to an observer. The observer dispatches the incoming event stream to a set of observer processes, each performing a specialized analysis, such as the temporal logic verification, the deadlock analysis and the data race analysis. Temporal logic specifications can be formulated by the user in the Maude rewriting logic, where Maude is a high-speed rewriting system for equational logic, but here extended with executable temporal logic. The Maude rewriting engine is then activated as an event driven monitoring process. Alternatively, temporal specifications can be translated into efficient automata, which check the event stream. JPAX can be used during program testing to gain increased information about program executions, and can potentially furthermore be applied during operation to survey safety critical systems.

Knowledge-Based Systems Research

DTIC Science & Technology

1990-08-24

P. S., Laird, J. E., Newell, A. and McCarl, R. 1991. A Preliminary Analysis of the SOAR Architecture as a Basis for General Intelligence . Artifcial ...on reverse of neceSSjr’y gnd identify by block nhmber) FIELD I GRO’= SUB-C.OROUC Artificial Intelligence , Blackboard Systems, U°nstraint Satisfaction...knowledge acquisition; symbolic simulation; logic-based systems with self-awareness; SOAR, an architecture for general intelligence and learning

Boolean and brain-inspired computing using spin-transfer torque devices

NASA Astrophysics Data System (ADS)

Fan, Deliang

Several completely new approaches (such as spintronic, carbon nanotube, graphene, TFETs, etc.) to information processing and data storage technologies are emerging to address the time frame beyond current Complementary Metal-Oxide-Semiconductor (CMOS) roadmap. The high speed magnetization switching of a nano-magnet due to current induced spin-transfer torque (STT) have been demonstrated in recent experiments. Such STT devices can be explored in compact, low power memory and logic design. In order to truly leverage STT devices based computing, researchers require a re-think of circuit, architecture, and computing model, since the STT devices are unlikely to be drop-in replacements for CMOS. The potential of STT devices based computing will be best realized by considering new computing models that are inherently suited to the characteristics of STT devices, and new applications that are enabled by their unique capabilities, thereby attaining performance that CMOS cannot achieve. The goal of this research is to conduct synergistic exploration in architecture, circuit and device levels for Boolean and brain-inspired computing using nanoscale STT devices. Specifically, we first show that the non-volatile STT devices can be used in designing configurable Boolean logic blocks. We propose a spin-memristor threshold logic (SMTL) gate design, where memristive cross-bar array is used to perform current mode summation of binary inputs and the low power current mode spintronic threshold device carries out the energy efficient threshold operation. Next, for brain-inspired computing, we have exploited different spin-transfer torque device structures that can implement the hard-limiting and soft-limiting artificial neuron transfer functions respectively. We apply such STT based neuron (or 'spin-neuron') in various neural network architectures, such as hierarchical temporal memory and feed-forward neural network, for performing "human-like" cognitive computing, which show more than two orders of lower energy consumption compared to state of the art CMOS implementation. Finally, we show the dynamics of injection locked Spin Hall Effect Spin-Torque Oscillator (SHE-STO) cluster can be exploited as a robust multi-dimensional distance metric for associative computing, image/ video analysis, etc. Our simulation results show that the proposed system architecture with injection locked SHE-STOs and the associated CMOS interface circuits can be suitable for robust and energy efficient associative computing and pattern matching.

Clinical Outcome Prediction in Aneurysmal Subarachnoid Hemorrhage Using Bayesian Neural Networks with Fuzzy Logic Inferences

PubMed Central

Lo, Benjamin W. Y.; Macdonald, R. Loch; Baker, Andrew; Levine, Mitchell A. H.

2013-01-01

Objective. The novel clinical prediction approach of Bayesian neural networks with fuzzy logic inferences is created and applied to derive prognostic decision rules in cerebral aneurysmal subarachnoid hemorrhage (aSAH). Methods. The approach of Bayesian neural networks with fuzzy logic inferences was applied to data from five trials of Tirilazad for aneurysmal subarachnoid hemorrhage (3551 patients). Results. Bayesian meta-analyses of observational studies on aSAH prognostic factors gave generalizable posterior distributions of population mean log odd ratios (ORs). Similar trends were noted in Bayesian and linear regression ORs. Significant outcome predictors include normal motor response, cerebral infarction, history of myocardial infarction, cerebral edema, history of diabetes mellitus, fever on day 8, prior subarachnoid hemorrhage, admission angiographic vasospasm, neurological grade, intraventricular hemorrhage, ruptured aneurysm size, history of hypertension, vasospasm day, age and mean arterial pressure. Heteroscedasticity was present in the nontransformed dataset. Artificial neural networks found nonlinear relationships with 11 hidden variables in 1 layer, using the multilayer perceptron model. Fuzzy logic decision rules (centroid defuzzification technique) denoted cut-off points for poor prognosis at greater than 2.5 clusters. Discussion. This aSAH prognostic system makes use of existing knowledge, recognizes unknown areas, incorporates one's clinical reasoning, and compensates for uncertainty in prognostication. PMID:23690884

A Computer Model for Determining Operational Centers of Gravity

DTIC Science & Technology

2002-05-31

current state of AI. For the beginner , the student text Artificial Intelligence: An Executive Overview (USMA 1994) is still useful for surveying the... flowchart that guides the determination. In preparing the model, the authors consulted numerous sources of opinion on the topic, to include doctrine...the logic of the general model in this manner resulted in a compact, unambiguous flowchart -style representation. The depiction of the general model

A neural networks-based hybrid routing protocol for wireless mesh networks.

PubMed

Kojić, Nenad; Reljin, Irini; Reljin, Branimir

2012-01-01

The networking infrastructure of wireless mesh networks (WMNs) is decentralized and relatively simple, but they can display reliable functioning performance while having good redundancy. WMNs provide Internet access for fixed and mobile wireless devices. Both in urban and rural areas they provide users with high-bandwidth networks over a specific coverage area. The main problems affecting these networks are changes in network topology and link quality. In order to provide regular functioning, the routing protocol has the main influence in WMN implementations. In this paper we suggest a new routing protocol for WMN, based on good results of a proactive and reactive routing protocol, and for that reason it can be classified as a hybrid routing protocol. The proposed solution should avoid flooding and creating the new routing metric. We suggest the use of artificial logic-i.e., neural networks (NNs). This protocol is based on mobile agent technologies controlled by a Hopfield neural network. In addition to this, our new routing metric is based on multicriteria optimization in order to minimize delay and blocking probability (rejected packets or their retransmission). The routing protocol observes real network parameters and real network environments. As a result of artificial logic intelligence, the proposed routing protocol should maximize usage of network resources and optimize network performance.

Comparison of four approaches to a rock facies classification problem

USGS Publications Warehouse

Dubois, M.K.; Bohling, Geoffrey C.; Chakrabarti, S.

2007-01-01

In this study, seven classifiers based on four different approaches were tested in a rock facies classification problem: classical parametric methods using Bayes' rule, and non-parametric methods using fuzzy logic, k-nearest neighbor, and feed forward-back propagating artificial neural network. Determining the most effective classifier for geologic facies prediction in wells without cores in the Panoma gas field, in Southwest Kansas, was the objective. Study data include 3600 samples with known rock facies class (from core) with each sample having either four or five measured properties (wire-line log curves), and two derived geologic properties (geologic constraining variables). The sample set was divided into two subsets, one for training and one for testing the ability of the trained classifier to correctly assign classes. Artificial neural networks clearly outperformed all other classifiers and are effective tools for this particular classification problem. Classical parametric models were inadequate due to the nature of the predictor variables (high dimensional and not linearly correlated), and feature space of the classes (overlapping). The other non-parametric methods tested, k-nearest neighbor and fuzzy logic, would need considerable improvement to match the neural network effectiveness, but further work, possibly combining certain aspects of the three non-parametric methods, may be justified. ?? 2006 Elsevier Ltd. All rights reserved.

Cracking the barcode of fullerene-like cortical microcolumns.

PubMed

Tozzi, Arturo; Peters, James F; Ori, Ottorino

2017-03-22

Artificial neural systems and nervous graph theoretical analysis rely upon the stance that the neural code is embodied in logic circuits, e.g., spatio-temporal sequences of ON/OFF spiking neurons. Nevertheless, this assumption does not fully explain complex brain functions. Here we show how nervous activity, other than logic circuits, could instead depend on topological transformations and symmetry constraints occurring at the micro-level of the cortical microcolumn, i.e., the embryological, anatomical and functional basic unit of the brain. Tubular microcolumns can be flattened in fullerene-like two-dimensional lattices, equipped with about 80 nodes standing for pyramidal neurons where neural computations take place. We show how the countless possible combinations of activated neurons embedded in the lattice resemble a barcode. Despite the fact that further experimental verification is required in order to validate our claim, different assemblies of firing neurons might have the appearance of diverse codes, each one responsible for a single mental activity. A two-dimensional fullerene-like lattice, grounded on simple topological changes standing for pyramidal neurons' activation, not just displays analogies with the real microcolumn's microcircuitry and the neural connectome, but also the potential for the manufacture of plastic, robust and fast artificial networks in robotic forms of full-fledged neural systems. Copyright © 2017 Elsevier B.V. All rights reserved.

Selective Snapshot of State-of-the-Art Artificial Intelligence & Robotics with Reference to the Icarus Starship

NASA Astrophysics Data System (ADS)

Ellery, A.

Since the remarkable British Interplanetary Society starship study of the late 1970s - Daedalus - there have been significant developments in the areas of artificial intelligence and robotics. These will be critical technologies for any starship as indeed they are for the current generation of exploratory spacecraft and in-situ planetary robotic explorers. Although early visions of truly intelligent robots have yet to materialize (reasons for which will be outlined), there are nonetheless revolutionary developments which have attempted to address at least some of these earlier unperceived deficiencies. The current state of the art comprises a number of separate strands of research which provide components of robotic intelligence though no over- arching approach has been forthcoming. The first question to be considered is the level of intelligent functionality required to support a long-duration starship mission. This will, at a minimum, need to be extensive imposed by the requirement for complex reconfigurability and repair. The second question concerns the tools that we have at our disposal to implement the required intelligent functions of the starship. These are based on two very different approaches - good old-fashioned artificial intelligence (GOFAI) based on logical theorem-proving and knowledge-encoding recently augmented by modal, temporal, circumscriptive and fuzzy logics to address the well-known “frame problem”; and the more recent soft computing approaches based on artificial neural networks, evolutionary algorithms and immunity models and their variants to implement learning. The former has some flight heritage through the Remote Agent architecture whilst the latter has yet to be deployed on any space mission. However, the notion of reconfigurable hardware of recent interest in the space community warrants the use of evolutionary algorithms and neural networks implemented on field programmable gate array technology, blurring the distinction between hardware and software. The primary question in space engineering has traditionally been one of predictability and controllability which online learning compromises. A further factor to be accounted for is the notion that intelligence is derived primarily from robot-environment interaction which stresses the sensory and actuation capabilities (exemplified by the behavioural or situated robotics paradigm). One major concern is whether the major deficiency of current methods in terms of lack of scalability can be overcome using a highly distributed approach rather than the hierarchical approach suggested by the NASREM architecture. It is contended here that a mixed solution will be required where a priori programming is augmented by a posteriori learning resembling the biological distinction between fixed genetically inherited and learned neurally implemented behaviour in animals. In particular, a biomimetic approach is proferred which exploits the neural processes and architecture of the human brain through the use of forward models which attempts to marry the conflicting requirements of learning with predictability. Some small-scale efforts in this direction will be outlined.

A Simplified Version of the Fuzzy Decision Method and its Comparison with the Paraconsistent Decision Method

NASA Astrophysics Data System (ADS)

de Carvalho, Fábio Romeu; Abe, Jair Minoro

2010-11-01

Two recent non-classical logics have been used to make decision: fuzzy logic and paraconsistent annotated evidential logic Et. In this paper we present a simplified version of the fuzzy decision method and its comparison with the paraconsistent one. Paraconsistent annotated evidential logic Et, introduced by Da Costa, Vago and Subrahmanian (1991), is capable of handling uncertain and contradictory data without becoming trivial. It has been used in many applications such as information technology, robotics, artificial intelligence, production engineering, decision making etc. Intuitively, one Et logic formula is type p(a, b), in which a and b belong to [0, 1] (real interval) and represent respectively the degree of favorable evidence (or degree of belief) and the degree of contrary evidence (or degree of disbelief) found in p. The set of all pairs (a; b), called annotations, when plotted, form the Cartesian Unitary Square (CUS). This set, containing a similar order relation of real number, comprises a network, called lattice of the annotations. Fuzzy logic was introduced by Zadeh (1965). It tries to systematize the knowledge study, searching mainly to study the fuzzy knowledge (you don't know what it means) and distinguish it from the imprecise one (you know what it means, but you don't know its exact value). This logic is similar to paraconsistent annotated one, since it attributes a numeric value (only one, not two values) to each proposition (then we can say that it is an one-valued logic). This number translates the intensity (the degree) with which the preposition is true. Let's X a set and A, a subset of X, identified by the function f(x). For each element x∈X, you have y = f(x)∈[0, 1]. The number y is called degree of pertinence of x in A. Decision making theories based on these logics have shown to be powerful in many aspects regarding more traditional methods, like the one based on Statistics. In this paper we present a first study for a simplified version of decision making theory based on Fuzzy Logic (SVMFD) and a comparison with the Paraconsistent Decision Method (PDM) based on Paraconsistent Annotated Evidential Logic Eτ, already presented and summarized in this paper. An example showing the two methods is presented in the paper, as well as a comparison between them.

(Re) Making the Procrustean Bed? Standardization and Customization as Competing Logics in Healthcare.

PubMed

Mannion, Russell; Exworthy, Mark

2017-03-28

Recent years have witnessed a parallel and seemingly contradictory trend towards both the standardization and the customization of healthcare and medical treatment. Here, we explore what is meant by 'standardization' and 'customization' in healthcare settings and explore the implications of these changes for healthcare delivery. We frame the paradox of these divergent and opposing factors in terms of institutional logics - the socially constructed rules, practices and beliefs which perpetuate institutional behaviour. As the tension between standardization and customization is fast becoming a critical fault-line within many health systems, there remains an urgent need for more sustained work exploring how these competing logics are articulated, adapted, resisted and co-exist on the front line of care delivery. © 2017 The Author(s); Published by Kerman University of Medical Sciences. This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Efficient Digital Implementation of The Sigmoidal Function For Artificial Neural Network

NASA Astrophysics Data System (ADS)

Pratap, Rana; Subadra, M.

2011-10-01

An efficient piecewise linear approximation of a nonlinear function (PLAN) is proposed. This uses simulink environment design to perform a direct transformation from X to Y, where X is the input and Y is the approximated sigmoidal output. This PLAN is then used within the outputs of an artificial neural network to perform the nonlinear approximation. In This paper, is proposed a method to implement in FPGA (Field Programmable Gate Array) circuits different approximation of the sigmoid function.. The major benefit of the proposed method resides in the possibility to design neural networks by means of predefined block systems created in System Generator environment and the possibility to create a higher level design tools used to implement neural networks in logical circuits.

An intercomparison of artificial intelligence approaches for polar scene identification

NASA Technical Reports Server (NTRS)

Tovinkere, V. R.; Penaloza, M.; Logar, A.; Lee, J.; Weger, R. C.; Berendes, T. A.; Welch, R. M.

1993-01-01

The following six different artificial-intelligence (AI) approaches to polar scene identification are examined: (1) a feed forward back propagation neural network, (2) a probabilistic neural network, (3) a hybrid neural network, (4) a 'don't care' feed forward perception model, (5) a 'don't care' feed forward back propagation neural network, and (6) a fuzzy logic based expert system. The ten classes into which six AVHRR local-coverage arctic scenes were classified were: water, solid sea ice, broken sea ice, snow-covered mountains, land, stratus over ice, stratus over water, cirrus over water, cumulus over water, and multilayer cloudiness. It was found that 'don't care' back propagation neural network produced the highest accuracies. This approach has also low CPU requirement.

Application of artificial intelligence to the management of urological cancer.

PubMed

Abbod, Maysam F; Catto, James W F; Linkens, Derek A; Hamdy, Freddie C

2007-10-01

Artificial intelligence techniques, such as artificial neural networks, Bayesian belief networks and neuro-fuzzy modeling systems, are complex mathematical models based on the human neuronal structure and thinking. Such tools are capable of generating data driven models of biological systems without making assumptions based on statistical distributions. A large amount of study has been reported of the use of artificial intelligence in urology. We reviewed the basic concepts behind artificial intelligence techniques and explored the applications of this new dynamic technology in various aspects of urological cancer management. A detailed and systematic review of the literature was performed using the MEDLINE and Inspec databases to discover reports using artificial intelligence in urological cancer. The characteristics of machine learning and their implementation were described and reports of artificial intelligence use in urological cancer were reviewed. While most researchers in this field were found to focus on artificial neural networks to improve the diagnosis, staging and prognostic prediction of urological cancers, some groups are exploring other techniques, such as expert systems and neuro-fuzzy modeling systems. Compared to traditional regression statistics artificial intelligence methods appear to be accurate and more explorative for analyzing large data cohorts. Furthermore, they allow individualized prediction of disease behavior. Each artificial intelligence method has characteristics that make it suitable for different tasks. The lack of transparency of artificial neural networks hinders global scientific community acceptance of this method but this can be overcome by neuro-fuzzy modeling systems.

Artificial neural networks using complex numbers and phase encoded weights.

PubMed

Michel, Howard E; Awwal, Abdul Ahad S

2010-04-01

The model of a simple perceptron using phase-encoded inputs and complex-valued weights is proposed. The aggregation function, activation function, and learning rule for the proposed neuron are derived and applied to Boolean logic functions and simple computer vision tasks. The complex-valued neuron (CVN) is shown to be superior to traditional perceptrons. An improvement of 135% over the theoretical maximum of 104 linearly separable problems (of three variables) solvable by conventional perceptrons is achieved without additional logic, neuron stages, or higher order terms such as those required in polynomial logic gates. The application of CVN in distortion invariant character recognition and image segmentation is demonstrated. Implementation details are discussed, and the CVN is shown to be very attractive for optical implementation since optical computations are naturally complex. The cost of the CVN is less in all cases than the traditional neuron when implemented optically. Therefore, all the benefits of the CVN can be obtained without additional cost. However, on those implementations dependent on standard serial computers, CVN will be more cost effective only in those applications where its increased power can offset the requirement for additional neurons.

Application of AI methods to aircraft guidance and control

NASA Technical Reports Server (NTRS)

Hueschen, Richard M.; Mcmanus, John W.

1988-01-01

A research program for integrating artificial intelligence (AI) techniques with tools and methods used for aircraft flight control system design, development, and implementation is discussed. The application of the AI methods for the development and implementation of the logic software which operates with the control mode panel (CMP) of an aircraft is presented. The CMP is the pilot control panel for the automatic flight control system of a commercial-type research aircraft of Langley Research Center's Advanced Transport Operating Systems (ATOPS) program. A mouse-driven color-display emulation of the CMP, which was developed with AI methods and used to test the AI software logic implementation, is discussed. The operation of the CMP was enhanced with the addition of a display which was quickly developed with AI methods. The display advises the pilot of conditions not satisfied when a mode does not arm or engage. The implementation of the CMP software logic has shown that the time required to develop, implement, and modify software systems can be significantly reduced with the use of the AI methods.

Applied statistics in ecology: common pitfalls and simple solutions

Treesearch

E. Ashley Steel; Maureen C. Kennedy; Patrick G. Cunningham; John S. Stanovick

2013-01-01

The most common statistical pitfalls in ecological research are those associated with data exploration, the logic of sampling and design, and the interpretation of statistical results. Although one can find published errors in calculations, the majority of statistical pitfalls result from incorrect logic or interpretation despite correct numerical calculations. There...

Institutional Complexity and Policy Implementation: How Underlying Logics Drive Teacher Interpretations of Reform

ERIC Educational Resources Information Center

Bridwell-Mitchell, E. N.; Sherer, David G.

2017-01-01

One critical factor in policy implementation is how teachers interpret policy. Previous research largely overlooks how the broader culture shapes teachers' interpretations. In the current research, we explore how teachers' interpretations of instructional reforms are associated with the logics of broad societal institutions. Our longitudinal…

Formal Modeling of Multi-Agent Systems using the Pi-Calculus and Epistemic Logic

NASA Technical Reports Server (NTRS)

Rorie, Toinette; Esterline, Albert

1998-01-01

Multi-agent systems have become important recently in computer science, especially in artificial intelligence (AI). We allow a broad sense of agent, but require at least that an agent has some measure of autonomy and interacts with other agents via some kind of agent communication language. We are concerned in this paper with formal modeling of multi-agent systems, with emphasis on communication. We propose for this purpose to use the pi-calculus, an extension of the process algebra CCS. Although the literature on the pi-calculus refers to agents, the term is used there in the sense of a process in general. It is our contention, however, that viewing agents in the AI sense as agents in the pi-calculus sense affords significant formal insight. One formalism that has been applied to agents in the AI sense is epistemic logic, the logic of knowledge. The success of epistemic logic in computer science in general has come in large part from its ability to handle concepts of knowledge that apply to groups. We maintain that the pi-calculus affords a natural yet rigorous means by which groups that are significant to epistemic logic may be identified, encapsulated, structured into hierarchies, and restructured in a principled way. This paper is organized as follows: Section 2 introduces the pi-calculus; Section 3 takes a scenario from the classical paper on agent-oriented programming [Sh93] and translates it into a very simple subset of the n-calculus; Section 4 then shows how more sophisticated features of the pi-calculus may bc brought into play; Section 5 discusses how the pi-calculus may be used to define groups for epistemic logic; and Section 6 is the conclusion.

A hybrid neural networks-fuzzy logic-genetic algorithm for grade estimation

NASA Astrophysics Data System (ADS)

Tahmasebi, Pejman; Hezarkhani, Ardeshir

2012-05-01

The grade estimation is a quite important and money/time-consuming stage in a mine project, which is considered as a challenge for the geologists and mining engineers due to the structural complexities in mineral ore deposits. To overcome this problem, several artificial intelligence techniques such as Artificial Neural Networks (ANN) and Fuzzy Logic (FL) have recently been employed with various architectures and properties. However, due to the constraints of both methods, they yield the desired results only under the specific circumstances. As an example, one major problem in FL is the difficulty of constructing the membership functions (MFs).Other problems such as architecture and local minima could also be located in ANN designing. Therefore, a new methodology is presented in this paper for grade estimation. This method which is based on ANN and FL is called "Coactive Neuro-Fuzzy Inference System" (CANFIS) which combines two approaches, ANN and FL. The combination of these two artificial intelligence approaches is achieved via the verbal and numerical power of intelligent systems. To improve the performance of this system, a Genetic Algorithm (GA) - as a well-known technique to solve the complex optimization problems - is also employed to optimize the network parameters including learning rate, momentum of the network and the number of MFs for each input. A comparison of these techniques (ANN, Adaptive Neuro-Fuzzy Inference System or ANFIS) with this new method (CANFIS-GA) is also carried out through a case study in Sungun copper deposit, located in East-Azerbaijan, Iran. The results show that CANFIS-GA could be a faster and more accurate alternative to the existing time-consuming methodologies for ore grade estimation and that is, therefore, suggested to be applied for grade estimation in similar problems.

A hybrid neural networks-fuzzy logic-genetic algorithm for grade estimation

PubMed Central

Tahmasebi, Pejman; Hezarkhani, Ardeshir

2012-01-01

The grade estimation is a quite important and money/time-consuming stage in a mine project, which is considered as a challenge for the geologists and mining engineers due to the structural complexities in mineral ore deposits. To overcome this problem, several artificial intelligence techniques such as Artificial Neural Networks (ANN) and Fuzzy Logic (FL) have recently been employed with various architectures and properties. However, due to the constraints of both methods, they yield the desired results only under the specific circumstances. As an example, one major problem in FL is the difficulty of constructing the membership functions (MFs).Other problems such as architecture and local minima could also be located in ANN designing. Therefore, a new methodology is presented in this paper for grade estimation. This method which is based on ANN and FL is called “Coactive Neuro-Fuzzy Inference System” (CANFIS) which combines two approaches, ANN and FL. The combination of these two artificial intelligence approaches is achieved via the verbal and numerical power of intelligent systems. To improve the performance of this system, a Genetic Algorithm (GA) – as a well-known technique to solve the complex optimization problems – is also employed to optimize the network parameters including learning rate, momentum of the network and the number of MFs for each input. A comparison of these techniques (ANN, Adaptive Neuro-Fuzzy Inference System or ANFIS) with this new method (CANFIS–GA) is also carried out through a case study in Sungun copper deposit, located in East-Azerbaijan, Iran. The results show that CANFIS–GA could be a faster and more accurate alternative to the existing time-consuming methodologies for ore grade estimation and that is, therefore, suggested to be applied for grade estimation in similar problems. PMID:25540468

Fabrication of magnetic tunnel junctions connected through a continuous free layer to enable spin logic devices

NASA Astrophysics Data System (ADS)

Wan, Danny; Manfrini, Mauricio; Vaysset, Adrien; Souriau, Laurent; Wouters, Lennaert; Thiam, Arame; Raymenants, Eline; Sayan, Safak; Jussot, Julien; Swerts, Johan; Couet, Sebastien; Rassoul, Nouredine; Babaei Gavan, Khashayar; Paredis, Kristof; Huyghebaert, Cedric; Ercken, Monique; Wilson, Christopher J.; Mocuta, Dan; Radu, Iuliana P.

2018-04-01

Magnetic tunnel junctions (MTJs) interconnected via a continuous ferromagnetic free layer were fabricated for spin torque majority gate (STMG) logic. The MTJs are biased independently and show magnetoelectric response under spin transfer torque. The electrical control of these devices paves the way to future spin logic devices based on domain wall (DW) motion. In particular, it is a significant step towards the realization of a majority gate. To our knowledge, this is the first fabrication of a cross-shaped free layer shared by several perpendicular MTJs. The fabrication process can be generalized to any geometry and any number of MTJs. Thus, this framework can be applied to other spin logic concepts based on magnetic interconnect. Moreover, it allows exploration of spin dynamics for logic applications.

Approach for Autonomous Control of Unmanned Aerial Vehicle Using Intelligent Agents for Knowledge Creation

NASA Technical Reports Server (NTRS)

Dufrene, Warren R., Jr.

2004-01-01

This paper describes the development of a planned approach for Autonomous operation of an Unmanned Aerial Vehicle (UAV). A Hybrid approach will seek to provide Knowledge Generation thru the application of Artificial Intelligence (AI) and Intelligent Agents (IA) for UAV control. The application of many different types of AI techniques for flight will be explored during this research effort. The research concentration will be directed to the application of different AI methods within the UAV arena. By evaluating AI approaches, which will include Expert Systems, Neural Networks, Intelligent Agents, Fuzzy Logic, and Complex Adaptive Systems, a new insight may be gained into the benefits of AI techniques applied to achieving true autonomous operation of these systems thus providing new intellectual merit to this research field. The major area of discussion will be limited to the UAV. The systems of interest include small aircraft, insects, and miniature aircraft. Although flight systems will be explored, the benefits should apply to many Unmanned Vehicles such as: Rovers, Ocean Explorers, Robots, and autonomous operation systems. The flight system will be broken down into control agents that will represent the intelligent agent approach used in AI. After the completion of a successful approach, a framework of applying a Security Overseer will be added in an attempt to address errors, emergencies, failures, damage, or over dynamic environment. The chosen control problem was the landing phase of UAV operation. The initial results from simulation in FlightGear are presented.

Recent developments of artificial intelligence in drying of fresh food: A review.

PubMed

Sun, Qing; Zhang, Min; Mujumdar, Arun S

2018-03-01

Intellectualization is an important direction of drying development and artificial intelligence (AI) technologies have been widely used to solve problems of nonlinear function approximation, pattern detection, data interpretation, optimization, simulation, diagnosis, control, data sorting, clustering, and noise reduction in different food drying technologies due to the advantages of self-learning ability, adaptive ability, strong fault tolerance and high degree robustness to map the nonlinear structures of arbitrarily complex and dynamic phenomena. This article presents a comprehensive review on intelligent drying technologies and their applications. The paper starts with the introduction of basic theoretical knowledge of ANN, fuzzy logic and expert system. Then, we summarize the AI application of modeling, predicting, and optimization of heat and mass transfer, thermodynamic performance parameters, and quality indicators as well as physiochemical properties of dried products in artificial biomimetic technology (electronic nose, computer vision) and different conventional drying technologies. Furthermore, opportunities and limitations of AI technique in drying are also outlined to provide more ideas for researchers in this area.

Development of a coupled expert system for the spacecraft attitude control problem

NASA Technical Reports Server (NTRS)

Kawamura, K.; Beale, G.; Schaffer, J.; Hsieh, B.-J.; Padalkar, S.; Rodriguezmoscoso, J.; Vinz, F.; Fernandez, K.

1987-01-01

A majority of the current expert systems focus on the symbolic-oriented logic and inference mechanisms of artificial intelligence (AI). Common rule-based systems employ empirical associations and are not well suited to deal with problems often arising in engineering. Described is a prototype expert system which combines both symbolic and numeric computing. The expert system's configuration is presented and its application to a spacecraft attitude control problem is discussed.

Northeast Artificial Intelligence Consortium (NAIC). Volume 12. Computer Architecture for Very Large Knowledge Bases

DTIC Science & Technology

1990-12-01

data rate to the electronics would be much lower on the average and the data much "richer" in information. Intelligent use of...system bottleneck, a high data rate should be provided by I/O systems. 2. machines with intelligent storage management specially designed for logic...management information processing, surveillance sensors, intelligence data collection and handling, solid state sciences, electromagnetics, and propagation, and electronic reliability/maintainability and compatibility.

The next generation of similarity measures that fully explore the semantics in biomedical ontologies.

PubMed

Couto, Francisco M; Pinto, H Sofia

2013-10-01

There is a prominent trend to augment and improve the formality of biomedical ontologies. For example, this is shown by the current effort on adding description logic axioms, such as disjointness. One of the key ontology applications that can take advantage of this effort is the conceptual (functional) similarity measurement. The presence of description logic axioms in biomedical ontologies make the current structural or extensional approaches weaker and further away from providing sound semantics-based similarity measures. Although beneficial in small ontologies, the exploration of description logic axioms by semantics-based similarity measures is computational expensive. This limitation is critical for biomedical ontologies that normally contain thousands of concepts. Thus in the process of gaining their rightful place, biomedical functional similarity measures have to take the journey of finding how this rich and powerful knowledge can be fully explored while keeping feasible computational costs. This manuscript aims at promoting and guiding the development of compelling tools that deliver what the biomedical community will require in a near future: a next-generation of biomedical similarity measures that efficiently and fully explore the semantics present in biomedical ontologies.

An Institutional Perspective on Accountable Care Organizations.

PubMed

Goodrick, Elizabeth; Reay, Trish

2016-12-01

We employ aspects of institutional theory to explore how Accountable Care Organizations (ACOs) can effectively manage the multiplicity of ideas and pressures within which they are embedded and consequently better serve patients and their communities. More specifically, we draw on the concept of institutional logics to highlight the importance of understanding the conflicting principles upon which ACOs were founded. Based on previous research conducted both inside and outside health care settings, we argue that ACOs can combine attention to these principles (or institutional logics) in different ways; the options fall on a continuum from (a) segregating the effects of multiple logics from each other by compartmentalizing responses to multiple logics to (b) fully hybridizing the different logics. We suggest that the most productive path for ACOs is to situate their approach between the two extremes of "segregating" and "fully hybridizing." This strategic approach allows ACOs to develop effective responses that combine logics without fully integrating them. We identify three ways that ACOs can embrace institutional complexity short of fully hybridizing disparate logics: (1) reinterpreting practices to make them compatible with other logics; (2) engaging in strategies that take advantage of existing synergy between conflicting logics; (3) creating opportunities for people at frontline to develop innovative ways of working that combine multiple logics. © The Author(s) 2016.

The importance of context in logic model construction for a multi-site community-based Aboriginal driver licensing program.

PubMed

Cullen, Patricia; Clapham, Kathleen; Byrne, Jake; Hunter, Kate; Senserrick, Teresa; Keay, Lisa; Ivers, Rebecca

2016-08-01

Evidence indicates that Aboriginal people are underrepresented among driver licence holders in New South Wales, which has been attributed to licensing barriers for Aboriginal people. The Driving Change program was developed to provide culturally responsive licensing services that engage Aboriginal communities and build local capacity. This paper outlines the formative evaluation of the program, including logic model construction and exploration of contextual factors. Purposive sampling was used to identify key informants (n=12) from a consultative committee of key stakeholders and program staff. Semi-structured interviews were transcribed and thematically analysed. Data from interviews informed development of the logic model. Participants demonstrated high level of support for the program and reported that it filled an important gap. The program context revealed systemic barriers to licensing that were correspondingly targeted by specific program outputs in the logic model. Addressing underlying assumptions of the program involved managing local capacity and support to strengthen implementation. This formative evaluation highlights the importance of exploring program context as a crucial first step in logic model construction. The consultation process assisted in clarifying program goals and ensuring that the program was responding to underlying systemic factors that contribute to inequitable licensing access for Aboriginal people. Copyright © 2016 Elsevier Ltd. All rights reserved.

International Multidisciplinary Artificial Gravity (IMAG) Project

NASA Technical Reports Server (NTRS)

Laurini, Kathy

2007-01-01

This viewgraph presentation reviews the efforts of the International Multidisciplinary Artificial Gravity Project. Specifically it reviews the NASA Exploration Planning Status, NASA Exploration Roadmap, Status of Planning for the Moon, Mars Planning, Reference health maintenance scenario, and The Human Research Program.

Monitoring Java Programs with Java PathExplorer

NASA Technical Reports Server (NTRS)

Havelund, Klaus; Rosu, Grigore; Clancy, Daniel (Technical Monitor)

2001-01-01

We present recent work on the development Java PathExplorer (JPAX), a tool for monitoring the execution of Java programs. JPAX can be used during program testing to gain increased information about program executions, and can potentially furthermore be applied during operation to survey safety critical systems. The tool facilitates automated instrumentation of a program's late code which will then omit events to an observer during its execution. The observer checks the events against user provided high level requirement specifications, for example temporal logic formulae, and against lower level error detection procedures, for example concurrency related such as deadlock and data race algorithms. High level requirement specifications together with their underlying logics are defined in the Maude rewriting logic, and then can either be directly checked using the Maude rewriting engine, or be first translated to efficient data structures and then checked in Java.

Conceptualizing Magnification and Scale: The Roles of Spatial Visualization and Logical Thinking

ERIC Educational Resources Information Center

Jones, M. Gail; Gardner, Grant; Taylor, Amy R.; Wiebe, Eric; Forrester, Jennifer

2011-01-01

This study explored factors that contribute to students' concepts of magnification and scale. Spatial visualization, logical thinking, and concepts of magnification and scale were measured for 46 middle school students. Scores on the "Zoom Assessment" (an assessment of knowledge of magnification and scale) were correlated with the "Test of Logical…

The Logic of Quantum Measurements

NASA Astrophysics Data System (ADS)

Vanni, Leonardo; Laura, Roberto

2013-07-01

We apply our previously developed formalism of contexts of histories, suitable to deal with quantum properties at different times, to the measurement process. We explore the logical implications which are allowed by the quantum theory, about the realization of properties of the microscopic measured system, before and after the measurement process with a given pointer value.

Application of Dynamic Logic Algorithm to Inverse Scattering Problems Related to Plasma Diagnostics

NASA Astrophysics Data System (ADS)

Perlovsky, L.; Deming, R. W.; Sotnikov, V.

2010-11-01

In plasma diagnostics scattering of electromagnetic waves is widely used for identification of density and wave field perturbations. In the present work we use a powerful mathematical approach, dynamic logic (DL), to identify the spectra of scattered electromagnetic (EM) waves produced by the interaction of the incident EM wave with a Langmuir soliton in the presence of noise. The problem is especially difficult since the spectral amplitudes of the noise pattern are comparable with the amplitudes of the scattered waves. In the past DL has been applied to a number of complex problems in artificial intelligence, pattern recognition, and signal processing, resulting in revolutionary improvements. Here we demonstrate its application to plasma diagnostic problems. [4pt] Perlovsky, L.I., 2001. Neural Networks and Intellect: using model-based concepts. Oxford University Press, New York, NY.

Robot Wars: US Empire and geopolitics in the robotic age

PubMed Central

Shaw, Ian GR

2017-01-01

How will the robot age transform warfare? What geopolitical futures are being imagined by the US military? This article constructs a robotic futurology to examine these crucial questions. Its central concern is how robots – driven by leaps in artificial intelligence and swarming – are rewiring the spaces and logics of US empire, warfare, and geopolitics. The article begins by building a more-than-human geopolitics to de-center the role of humans in conflict and foreground a worldly understanding of robots. The article then analyzes the idea of US empire, before speculating upon how and why robots are materializing new forms of proxy war. A three-part examination of the shifting spaces of US empire then follows: (1) Swarm Wars explores the implications of miniaturized drone swarming; (2) Roboworld investigates how robots are changing US military basing strategy and producing new topological spaces of violence; and (3) The Autogenic Battle-Site reveals how autonomous robots will produce emergent, technologically event-ful sites of security and violence – revolutionizing the battlespace. The conclusion reflects on the rise of a robotic US empire and its consequences for democracy. PMID:29081605

Robot Wars: US Empire and geopolitics in the robotic age.

PubMed

Shaw, Ian Gr

2017-10-01

How will the robot age transform warfare? What geopolitical futures are being imagined by the US military? This article constructs a robotic futurology to examine these crucial questions. Its central concern is how robots - driven by leaps in artificial intelligence and swarming - are rewiring the spaces and logics of US empire, warfare, and geopolitics. The article begins by building a more-than-human geopolitics to de-center the role of humans in conflict and foreground a worldly understanding of robots. The article then analyzes the idea of US empire, before speculating upon how and why robots are materializing new forms of proxy war. A three-part examination of the shifting spaces of US empire then follows: (1) Swarm Wars explores the implications of miniaturized drone swarming; (2) Roboworld investigates how robots are changing US military basing strategy and producing new topological spaces of violence; and (3) The Autogenic Battle-Site reveals how autonomous robots will produce emergent, technologically event-ful sites of security and violence - revolutionizing the battlespace. The conclusion reflects on the rise of a robotic US empire and its consequences for democracy.

Logic Design Pathology and Space Flight Electronics

NASA Technical Reports Server (NTRS)

Katz, Richard; Barto, Rod L.; Erickson, K.

1997-01-01

Logic design errors have been observed in space flight missions and the final stages of ground test. The technologies used by designers and their design/analysis methodologies will be analyzed. This will give insight to the root causes of the failures. These technologies include discrete integrated circuit based systems, systems based on field and mask programmable logic, and the use computer aided engineering (CAE) systems. State-of-the-art (SOTA) design tools and methodologies will be analyzed with respect to high-reliability spacecraft design and potential pitfalls are discussed. Case studies of faults from large expensive programs to "smaller, faster, cheaper" missions will be used to explore the fundamental reasons for logic design problems.

Précis of bayesian rationality: The probabilistic approach to human reasoning.

PubMed

Oaksford, Mike; Chater, Nick

2009-02-01

According to Aristotle, humans are the rational animal. The borderline between rationality and irrationality is fundamental to many aspects of human life including the law, mental health, and language interpretation. But what is it to be rational? One answer, deeply embedded in the Western intellectual tradition since ancient Greece, is that rationality concerns reasoning according to the rules of logic--the formal theory that specifies the inferential connections that hold with certainty between propositions. Piaget viewed logical reasoning as defining the end-point of cognitive development; and contemporary psychology of reasoning has focussed on comparing human reasoning against logical standards. Bayesian Rationality argues that rationality is defined instead by the ability to reason about uncertainty. Although people are typically poor at numerical reasoning about probability, human thought is sensitive to subtle patterns of qualitative Bayesian, probabilistic reasoning. In Chapters 1-4 of Bayesian Rationality (Oaksford & Chater 2007), the case is made that cognition in general, and human everyday reasoning in particular, is best viewed as solving probabilistic, rather than logical, inference problems. In Chapters 5-7 the psychology of "deductive" reasoning is tackled head-on: It is argued that purportedly "logical" reasoning problems, revealing apparently irrational behaviour, are better understood from a probabilistic point of view. Data from conditional reasoning, Wason's selection task, and syllogistic inference are captured by recasting these problems probabilistically. The probabilistic approach makes a variety of novel predictions which have been experimentally confirmed. The book considers the implications of this work, and the wider "probabilistic turn" in cognitive science and artificial intelligence, for understanding human rationality.

Fuzzy Logic Decoupled Lateral Control for General Aviation Airplanes

NASA Technical Reports Server (NTRS)

Duerksen, Noel

1997-01-01

It has been hypothesized that a human pilot uses the same set of generic skills to control a wide variety of aircraft. If this is true, then it should be possible to construct an electronic controller which embodies this generic skill set such that it can successfully control different airplanes without being matched to a specific airplane. In an attempt to create such a system, a fuzzy logic controller was devised to control aileron or roll spoiler position. This controller was used to control bank angle for both a piston powered single engine aileron equipped airplane simulation and a business jet simulation which used spoilers for primary roll control. Overspeed, stall and overbank protection were incorporated in the form of expert systems supervisors and weighted fuzzy rules. It was found that by using the artificial intelligence techniques of fuzzy logic and expert systems, a generic lateral controller could be successfully used on two general aviation aircraft types that have very different characteristics. These controllers worked for both airplanes over their entire flight envelopes. The controllers for both airplanes were identical except for airplane specific limits (maximum allowable airspeed, throttle ]ever travel, etc.). This research validated the fact that the same fuzzy logic based controller can control two very different general aviation airplanes. It also developed the basic controller architecture and specific control parameters required for such a general controller.

Notes on stochastic (bio)-logic gates: computing with allosteric cooperativity

PubMed Central

Agliari, Elena; Altavilla, Matteo; Barra, Adriano; Dello Schiavo, Lorenzo; Katz, Evgeny

2015-01-01

Recent experimental breakthroughs have finally allowed to implement in-vitro reaction kinetics (the so called enzyme based logic) which code for two-inputs logic gates and mimic the stochastic AND (and NAND) as well as the stochastic OR (and NOR). This accomplishment, together with the already-known single-input gates (performing as YES and NOT), provides a logic base and paves the way to the development of powerful biotechnological devices. However, as biochemical systems are always affected by the presence of noise (e.g. thermal), standard logic is not the correct theoretical reference framework, rather we show that statistical mechanics can work for this scope: here we formulate a complete statistical mechanical description of the Monod-Wyman-Changeaux allosteric model for both single and double ligand systems, with the purpose of exploring their practical capabilities to express noisy logical operators and/or perform stochastic logical operations. Mixing statistical mechanics with logics, and testing quantitatively the resulting findings on the available biochemical data, we successfully revise the concept of cooperativity (and anti-cooperativity) for allosteric systems, with particular emphasis on its computational capabilities, the related ranges and scaling of the involved parameters and its differences with classical cooperativity (and anti-cooperativity). PMID:25976626

Notes on stochastic (bio)-logic gates: computing with allosteric cooperativity.

PubMed

Agliari, Elena; Altavilla, Matteo; Barra, Adriano; Dello Schiavo, Lorenzo; Katz, Evgeny

2015-05-15

Recent experimental breakthroughs have finally allowed to implement in-vitro reaction kinetics (the so called enzyme based logic) which code for two-inputs logic gates and mimic the stochastic AND (and NAND) as well as the stochastic OR (and NOR). This accomplishment, together with the already-known single-input gates (performing as YES and NOT), provides a logic base and paves the way to the development of powerful biotechnological devices. However, as biochemical systems are always affected by the presence of noise (e.g. thermal), standard logic is not the correct theoretical reference framework, rather we show that statistical mechanics can work for this scope: here we formulate a complete statistical mechanical description of the Monod-Wyman-Changeaux allosteric model for both single and double ligand systems, with the purpose of exploring their practical capabilities to express noisy logical operators and/or perform stochastic logical operations. Mixing statistical mechanics with logics, and testing quantitatively the resulting findings on the available biochemical data, we successfully revise the concept of cooperativity (and anti-cooperativity) for allosteric systems, with particular emphasis on its computational capabilities, the related ranges and scaling of the involved parameters and its differences with classical cooperativity (and anti-cooperativity).

Notes on stochastic (bio)-logic gates: computing with allosteric cooperativity

NASA Astrophysics Data System (ADS)

Agliari, Elena; Altavilla, Matteo; Barra, Adriano; Dello Schiavo, Lorenzo; Katz, Evgeny

2015-05-01

Recent experimental breakthroughs have finally allowed to implement in-vitro reaction kinetics (the so called enzyme based logic) which code for two-inputs logic gates and mimic the stochastic AND (and NAND) as well as the stochastic OR (and NOR). This accomplishment, together with the already-known single-input gates (performing as YES and NOT), provides a logic base and paves the way to the development of powerful biotechnological devices. However, as biochemical systems are always affected by the presence of noise (e.g. thermal), standard logic is not the correct theoretical reference framework, rather we show that statistical mechanics can work for this scope: here we formulate a complete statistical mechanical description of the Monod-Wyman-Changeaux allosteric model for both single and double ligand systems, with the purpose of exploring their practical capabilities to express noisy logical operators and/or perform stochastic logical operations. Mixing statistical mechanics with logics, and testing quantitatively the resulting findings on the available biochemical data, we successfully revise the concept of cooperativity (and anti-cooperativity) for allosteric systems, with particular emphasis on its computational capabilities, the related ranges and scaling of the involved parameters and its differences with classical cooperativity (and anti-cooperativity).

Artificial Life Art, Creativity, and Techno-hybridization (editor's introduction).

PubMed

Dorin, Alan

2015-01-01

Artists and engineers have devised lifelike technology for millennia. Their ingenious devices have often prompted inquiry into our preferences, prejudices, and beliefs about living systems, especially regarding their origins, status, constitution, and behavior. A recurring fabrication technique is shared across artificial life art, science, and engineering. This involves aggregating representations or re-creations of familiar biological parts-techno-hybridization-but the motives of practitioners may differ markedly. This article, and the special issue it introduces, explores how ground familiar to contemporary artificial life science and engineering has been assessed and interpreted in parallel by (a) artists and (b) theorists studying creativity explicitly. This activity offers thoughtful, alternative perspectives on artificial life science and engineering, highlighting and sometimes undermining the fields' underlying assumptions, or exposing avenues that are yet to be explored outside of art. Additionally, art has the potential to engage the general public, supporting and exploring the findings of scientific research and engineering. This adds considerably to the maturity of a culture tackling the issues the discipline of artificial life raises.

Modeling the Effects of Light and Sucrose on In Vitro Propagated Plants: A Multiscale System Analysis Using Artificial Intelligence Technology

PubMed Central

Gago, Jorge; Martínez-Núñez, Lourdes; Landín, Mariana; Flexas, Jaume; Gallego, Pedro P.

2014-01-01

Background Plant acclimation is a highly complex process, which cannot be fully understood by analysis at any one specific level (i.e. subcellular, cellular or whole plant scale). Various soft-computing techniques, such as neural networks or fuzzy logic, were designed to analyze complex multivariate data sets and might be used to model large such multiscale data sets in plant biology. Methodology and Principal Findings In this study we assessed the effectiveness of applying neuro-fuzzy logic to modeling the effects of light intensities and sucrose content/concentration in the in vitro culture of kiwifruit on plant acclimation, by modeling multivariate data from 14 parameters at different biological scales of organization. The model provides insights through application of 14 sets of straightforward rules and indicates that plants with lower stomatal aperture areas and higher photoinhibition and photoprotective status score best for acclimation. The model suggests the best condition for obtaining higher quality acclimatized plantlets is the combination of 2.3% sucrose and photonflux of 122–130 µmol m−2 s−1. Conclusions Our results demonstrate that artificial intelligence models are not only successful in identifying complex non-linear interactions among variables, by integrating large-scale data sets from different levels of biological organization in a holistic plant systems-biology approach, but can also be used successfully for inferring new results without further experimental work. PMID:24465829

Artificial bee colony in neuro - Symbolic integration

NASA Astrophysics Data System (ADS)

Kasihmuddin, Mohd Shareduwan Mohd; Sathasivam, Saratha; Mansor, Mohd. Asyraf

2017-08-01

Swarm intelligence is a research area that models the population of the swarm based on natural computation. Artificial bee colony (ABC) algorithm is a swarm based metaheuristic algorithm introduced by Karaboga to optimize numerical problem. Pattern-SAT is a pattern reconstruction paradigm that utilized 2SAT logical rule in representing the behavior of the desired pattern. The information of the desired pattern in terms of 2SAT logic is embedded to Hopfield neural network (HNN-P2SAT) and the desired pattern is reconstructed during the retrieval phase. Since the performance of HNN-P2SAT in Pattern-SAT deteriorates when the number of 2SAT clause increased, newly improved ABC is used to reduce the computation burden during the learning phase of HNN-P2SAT (HNN-P2SATABC). The aim of this study is to investigate the performance of Pattern-SAT produced by ABC incorporated with HNN-P2SAT and compare it with conventional standalone HNN. The comparison is examined by using Microsoft Visual Basic C++ 2013 software. The detailed comparison in doing Pattern-SAT is discussed based on global Pattern-SAT, ratio of activated clauses and computation time. The result obtained from computer simulation indicates the beneficial features of HNN-P2SATABC in doing Pattern-SAT. This finding is expected to result in a significant implication on the choice of searching method used to do Pattern-SAT.

Modeling the effects of light and sucrose on in vitro propagated plants: a multiscale system analysis using artificial intelligence technology.

PubMed

Gago, Jorge; Martínez-Núñez, Lourdes; Landín, Mariana; Flexas, Jaume; Gallego, Pedro P

2014-01-01

Plant acclimation is a highly complex process, which cannot be fully understood by analysis at any one specific level (i.e. subcellular, cellular or whole plant scale). Various soft-computing techniques, such as neural networks or fuzzy logic, were designed to analyze complex multivariate data sets and might be used to model large such multiscale data sets in plant biology. In this study we assessed the effectiveness of applying neuro-fuzzy logic to modeling the effects of light intensities and sucrose content/concentration in the in vitro culture of kiwifruit on plant acclimation, by modeling multivariate data from 14 parameters at different biological scales of organization. The model provides insights through application of 14 sets of straightforward rules and indicates that plants with lower stomatal aperture areas and higher photoinhibition and photoprotective status score best for acclimation. The model suggests the best condition for obtaining higher quality acclimatized plantlets is the combination of 2.3% sucrose and photonflux of 122-130 µmol m(-2) s(-1). Our results demonstrate that artificial intelligence models are not only successful in identifying complex non-linear interactions among variables, by integrating large-scale data sets from different levels of biological organization in a holistic plant systems-biology approach, but can also be used successfully for inferring new results without further experimental work.

Prediction of Compressional, Shear, and Stoneley Wave Velocities from Conventional Well Log Data Using a Committee Machine with Intelligent Systems

NASA Astrophysics Data System (ADS)

Asoodeh, Mojtaba; Bagheripour, Parisa

2012-01-01

Measurement of compressional, shear, and Stoneley wave velocities, carried out by dipole sonic imager (DSI) logs, provides invaluable data in geophysical interpretation, geomechanical studies and hydrocarbon reservoir characterization. The presented study proposes an improved methodology for making a quantitative formulation between conventional well logs and sonic wave velocities. First, sonic wave velocities were predicted from conventional well logs using artificial neural network, fuzzy logic, and neuro-fuzzy algorithms. Subsequently, a committee machine with intelligent systems was constructed by virtue of hybrid genetic algorithm-pattern search technique while outputs of artificial neural network, fuzzy logic and neuro-fuzzy models were used as inputs of the committee machine. It is capable of improving the accuracy of final prediction through integrating the outputs of aforementioned intelligent systems. The hybrid genetic algorithm-pattern search tool, embodied in the structure of committee machine, assigns a weight factor to each individual intelligent system, indicating its involvement in overall prediction of DSI parameters. This methodology was implemented in Asmari formation, which is the major carbonate reservoir rock of Iranian oil field. A group of 1,640 data points was used to construct the intelligent model, and a group of 800 data points was employed to assess the reliability of the proposed model. The results showed that the committee machine with intelligent systems performed more effectively compared with individual intelligent systems performing alone.

Boggle Logic Puzzles: Minimal Solutions

ERIC Educational Resources Information Center

Needleman, Jonathan

2013-01-01

Boggle logic puzzles are based on the popular word game Boggle played backwards. Given a list of words, the problem is to recreate the board. We explore these puzzles on a 3 x 3 board and find the minimum number of three-letter words needed to create a puzzle with a unique solution. We conclude with a series of open questions.

Exploring a Customer Orientation: Free-Market Logic and College Students

ERIC Educational Resources Information Center

Saunders, Daniel B.

2014-01-01

This article provides a synthesis of literature on the conceptualization of students as customers and connects the rise of this understanding of students to the expansion of free-market logic into higher education. It details the ways in which the customer orientation appears to be incongruent with the educational lives of college students, and…

Some Practical Approaches to a Course on Paraconsistent Logic for Engineers

ERIC Educational Resources Information Center

Lambert-Torres, Germano; de Moraes, Carlos Henrique Valerio; Coutinho, Maurilio Pereira; Martins, Helga Gonzaga; Borges da Silva, Luiz Eduardo

2017-01-01

This paper describes a non-classical logic course primarily indicated for graduate students in electrical engineering and energy engineering. The content of this course is based on the vision that it is not enough for a student to indefinitely accumulate knowledge; it is necessary to explore all the occasions to update, deepen, and enrich that…

Emotions Targeting Moral Exemplarity: Making Sense of the Logical Geography of Admiration, Emulation and Elevation

ERIC Educational Resources Information Center

Kristjánsson, Kristján

2017-01-01

Despite renewed interest in moral role-modelling and its emotional underpinnings, further conceptual work is needed on the logical geography of the emotions purportedly driving it, in particular, admiration, emulation and elevation. In this article, I explore admiration (as understood by Linda Zagzebski), emulation (as understood by Aristotle) and…

Risk, Error and Accountability: Improving the Practice of School Leaders

ERIC Educational Resources Information Center

Perry, Lee-Anne

2006-01-01

This paper seeks to explore the notion of risk as an organisational logic within schools, the impact of contemporary accountability regimes on managing risk and then, in turn, to posit a systems-based process of risk management underpinned by a positive logic of risk. It moves through a number of steps beginning with the development of an…

Dynamic Fuzzy Logic-Based Quality of Interaction within Blended-Learning: The Rare and Contemporary Dance Cases

ERIC Educational Resources Information Center

Dias, Sofia B.; Diniz, José A.; Hadjileontiadis, Leontios J.

2014-01-01

The combination of the process of pedagogical planning within the Blended (b-) learning environment with the users' quality of interaction ("QoI") with the Learning Management System (LMS) is explored here. The required "QoI" (both for professors and students) is estimated by adopting a fuzzy logic-based modeling approach,…

Beyond a Logic of Quality: Opening Space for Material-Discursive Practices of "Readiness" in Early Years Education

ERIC Educational Resources Information Center

Evans, Katherine

2016-01-01

This article is an exploration of the possibilities encountered through shifting from a "logic of quality" to a "space of meaning-making" within early years education. Focusing on ideas of "readiness", this discussion aims to challenge normative understandings that relate this concept to the predictable achievement of…

High-speed all-optical logic inverter based on stimulated Raman scattering in silicon nanocrystal.

PubMed

Sen, Mrinal; Das, Mukul K

2015-11-01

In this paper, we propose a new device architecture for an all-optical logic inverter (NOT gate), which is cascadable with a similar device. The inverter is based on stimulated Raman scattering in silicon nanocrystal waveguides, which are embedded in a silicon photonic crystal structure. The Raman response function of silicon nanocrystal is evaluated to explore the transfer characteristic of the inverter. A maximum product criterion for the noise margin is taken to analyze the cascadability of the inverter. The time domain response of the inverter, which explores successful inversion operation at 100 Gb/s, is analyzed. Propagation delay of the inverter is on the order of 5 ps, which is less than the delay in most of the electronic logic families as of today. Overall dimension of the device is around 755  μm ×15  μm, which ensures integration compatibility with the matured silicon industry.

On Logic and Standards for Structuring Documents

NASA Astrophysics Data System (ADS)

Eyers, David M.; Jones, Andrew J. I.; Kimbrough, Steven O.

The advent of XML has been widely seized upon as an opportunity to develop document representation standards that lend themselves to automated processing. This is a welcome development and much good has come of it. That said, present standardization efforts may be criticized on a number of counts. We explore two issues associated with document XML standardization efforts. We label them (i) the dynamic point and (ii) the logical point. Our dynamic point is that in many cases experience has shown that the search for a final, or even reasonably permanent, document representation standard is futile. The case is especially strong for electronic data interchange (EDI). Our logical point is that formalization into symbolic logic is materially helpful for understanding and designing dynamic document standards.

Controlled data storage for non-volatile memory cells embedded in nano magnetic logic

NASA Astrophysics Data System (ADS)

Riente, Fabrizio; Ziemys, Grazvydas; Mattersdorfer, Clemens; Boche, Silke; Turvani, Giovanna; Raberg, Wolfgang; Luber, Sebastian; Breitkreutz-v. Gamm, Stephan

2017-05-01

Among the beyond-CMOS technologies, perpendicular Nano Magnetic Logic (pNML) is a promising candidate due to its low power consumption, its non-volatility and its monolithic 3D integrability, which makes it possible to integrate memory and logic into the same device by exploiting the interaction of bi-stable nanomagnets with perpendicular magnetic anisotropy. Logic computation and signal synchronization are achieved by focus ion beam irradiation and by pinning domain walls in magnetic notches. However, in realistic circuits, the information storage and their read-out are crucial issues, often ignored in the exploration of beyond-CMOS devices. In this paper we address these issues by experimentally demonstrating a pNML memory element, whose read and write operations can be controlled by two independent pulsed currents. Our results prove the correct behavior of the proposed structure that enables high density memory embedded in the logic plane of 3D-integrated pNML circuits.

Do institutional logics predict interpretation of contract rules at the dental chair-side?

PubMed Central

Harris, Rebecca; Brown, Stephen; Holt, Robin; Perkins, Elizabeth

2014-01-01

In quasi-markets, contracts find purchasers influencing health care providers, although problems exist where providers use personal bias and heuristics to respond to written agreements, tending towards the moral hazard of opportunism. Previous research on quasi-market contracts typically understands opportunism as fully rational, individual responses selecting maximally efficient outcomes from a set of possibilities. We take a more emotive and collective view of contracting, exploring the influence of institutional logics in relation to the opportunistic behaviour of dentists. Following earlier qualitative work where we identified four institutional logics in English general dental practice, and six dental contract areas where there was scope for opportunism; in 2013 we surveyed 924 dentists to investigate these logics and whether they had predictive purchase over dentists' chair-side behaviour. Factor analysis involving 300 responses identified four logics entwined in (often technical) behaviour: entrepreneurial commercialism, duty to staff and patients, managerialism, public good. PMID:25441320

Human action quality evaluation based on fuzzy logic with application in underground coal mining.

PubMed

Ionica, Andreea; Leba, Monica

2015-01-01

The work system is defined by its components, their roles and the relationships between them. Any work system gravitates around the human resource and the interdependencies between human factor and the other components of it. Researches in this field agreed that the human factor and its actions are difficult to quantify and predict. The objective of this paper is to apply a method of human actions evaluation in order to estimate possible risks and prevent possible system faults, both at human factor level and at equipment level. In order to point out the importance of the human factor influence on all the elements of the working systems we propose a fuzzy logic based methodology for quality evaluation of human actions. This methodology has a multidisciplinary character, as it gathers ideas and methods from: quality management, ergonomics, work safety and artificial intelligence. The results presented refer to a work system with a high degree of specificity, namely, underground coal mining and are valuable for human resources risk evaluation pattern. The fuzzy logic evaluation of the human actions leads to early detection of possible dangerous evolutions of the work system and alarm the persons in charge.

Universal computing by DNA origami robots in a living animal

PubMed Central

Levner, Daniel; Ittah, Shmulik; Abu-Horowitz, Almogit; Bachelet, Ido

2014-01-01

Biological systems are collections of discrete molecular objects that move around and collide with each other. Cells carry out elaborate processes by precisely controlling these collisions, but developing artificial machines that can interface with and control such interactions remains a significant challenge. DNA is a natural substrate for computing and has been used to implement a diverse set of mathematical problems1-3, logic circuits4-6 and robotics7-9. The molecule also naturally interfaces with living systems, and different forms of DNA-based biocomputing have previously been demonstrated10-13. Here we show that DNA origami14-16 can be used to fabricate nanoscale robots that are capable of dynamically interacting with each other17-18 in a living animal. The interactions generate logical outputs, which are relayed to switch molecular payloads on or off. As a proof-of-principle, we use the system to create architectures that emulate various logic gates (AND, OR, XOR, NAND, NOT, CNOT, and a half adder). Following an ex vivo prototyping phase, we successfully employed the DNA origami robots in living cockroaches (Blaberus discoidalis) to control a molecule that targets the cells of the animal. PMID:24705510

A study of fuzzy logic ensemble system performance on face recognition problem

NASA Astrophysics Data System (ADS)

Polyakova, A.; Lipinskiy, L.

2017-02-01

Some problems are difficult to solve by using a single intelligent information technology (IIT). The ensemble of the various data mining (DM) techniques is a set of models which are able to solve the problem by itself, but the combination of which allows increasing the efficiency of the system as a whole. Using the IIT ensembles can improve the reliability and efficiency of the final decision, since it emphasizes on the diversity of its components. The new method of the intellectual informational technology ensemble design is considered in this paper. It is based on the fuzzy logic and is designed to solve the classification and regression problems. The ensemble consists of several data mining algorithms: artificial neural network, support vector machine and decision trees. These algorithms and their ensemble have been tested by solving the face recognition problems. Principal components analysis (PCA) is used for feature selection.

Development and experimentation of LQR/APF guidance and control for autonomous proximity maneuvers of multiple spacecraft

NASA Astrophysics Data System (ADS)

Bevilacqua, R.; Lehmann, T.; Romano, M.

2011-04-01

This work introduces a novel control algorithm for close proximity multiple spacecraft autonomous maneuvers, based on hybrid linear quadratic regulator/artificial potential function (LQR/APF), for applications including autonomous docking, on-orbit assembly and spacecraft servicing. Both theoretical developments and experimental validation of the proposed approach are presented. Fuel consumption is sub-optimized in real-time through re-computation of the LQR at each sample time, while performing collision avoidance through the APF and a high level decisional logic. The underlying LQR/APF controller is integrated with a customized wall-following technique and a decisional logic, overcoming problems such as local minima. The algorithm is experimentally tested on a four spacecraft simulators test bed at the Spacecraft Robotics Laboratory of the Naval Postgraduate School. The metrics to evaluate the control algorithm are: autonomy of the system in making decisions, successful completion of the maneuver, required time, and propellant consumption.

Targeting of Gold Deposits in Amazonian Exploration Frontiers using Knowledge- and Data-Driven Spatial Modeling of Geophysical, Geochemical, and Geological Data

NASA Astrophysics Data System (ADS)

Magalhães, Lucíola Alves; Souza Filho, Carlos Roberto

2012-03-01

This paper reports the application of weights-of-evidence, artificial neural networks, and fuzzy logic spatial modeling techniques to generate prospectivity maps for gold mineralization in the neighborhood of the Amapari Au mine, Brazil. The study area comprises one of the last Brazilian mineral exploration frontiers. The Amapari mine is located in the Maroni-Itaicaiúnas Province, which regionally hosts important gold, iron, manganese, chromite, diamond, bauxite, kaolinite, and cassiterite deposits. The Amapari Au mine is characterized as of the orogenic gold deposit type. The highest gold grades are associated with highly deformed rocks and are concentrated in sulfide-rich veins mainly composed of pyrrhotite. The data used for the generation of gold prospectivity models include aerogeophysical and geological maps as well as the gold content of stream sediment samples. The prospectivity maps provided by these three methods showed that the Amapari mine stands out as an area of high potential for gold mineralization. The prospectivity maps also highlight new targets for gold exploration. These new targets were validated by means of detailed maps of gold geochemical anomalies in soil and by fieldwork. The identified target areas exhibit good spatial coincidence with the main soil geochemical anomalies and prospects, thus demonstrating that the delineation of exploration targets by analysis and integration of indirect datasets in a geographic information system (GIS) is consistent with direct prospecting. Considering that work of this nature has never been developed in the Amazonian region, this is an important example of the applicability and functionality of geophysical data and prospectivity analysis in regions where geologic and metallogenetic information is scarce.

TexTile Math: Multicultural Explorations through Patterns. Grades 3-6.

ERIC Educational Resources Information Center

Franco, Betsy

This book features 34 reproducible student activities exploring textile design through a combination of mathematics, art, and multicultural education. Using colorful squares and triangles, students explore geometry, numbers, area, fractions, logic, and discrete mathematics, while incorporating multicultural themes in the study. The teacher page…

The Performance Blueprint: An Integrated Logic Model Developed To Enhance Performance Measurement Literacy: The Case of Performance-Based Contract Management.

ERIC Educational Resources Information Center

Longo, Paul J.

This study explored the mechanics of using an enhanced, comprehensive multipurpose logic model, the Performance Blueprint, as a means of building evaluation capacity, referred to in this paper as performance measurement literacy, to facilitate the attainment of both service-delivery oriented and community-oriented outcomes. The application of this…

An Experience of Social Rising of Logical Tools in a Primary School Classroom: The Role of Language

ERIC Educational Resources Information Center

Coppola, Cristina; Mollo, Monica; Pacelli, Tiziana

2011-01-01

In this paper we explore the relationship between language and developmental processes of logical tools through the analysis at different levels of some "linguistic-manipulative" activities in a primary school classroom. We believe that this kind of activities can spur in the children a reflection and a change in their language…

Assessment and the Logic of Instructional Practice in Secondary 3 English and Mathematics Classrooms in Singapore

ERIC Educational Resources Information Center

Hogan, David; Chan, Melvin; Rahim, Ridzuan; Kwek, Dennis; Aye, Khin Maung; Loo, Siok Chen; Sheng, Yee Zher; Luo, Wenshu

2013-01-01

By any measure, Singapore's educational system has generated an extraordinary record of achievement over the past two or three decades. In this article, we report on one key component of a broader three year investigation into why Singapore has done so well, and explore the logic, strength, resilience and limits of the underlying pedagogical model…

Conceptual Boundaries and Pathways: Exploring the Institutional Logics of Higher Education Scholarship on College Student Social Movements and Activism, 1967-2008

ERIC Educational Resources Information Center

Mars, Matthew M.

2009-01-01

This study has focused on the institutional logics that influenced how higher education scholars patrolled and shaped the conceptual boundaries of college student movement and activism research published between the years 1967 and 2008. A keyword search of four prestigious higher education journals ("The Journal of Higher Education", "Review of…

Artificial Intelligence in Medicine and Radiation Oncology

PubMed Central

Weidlich, Vincent

2018-01-01

Artifical Intelligence (AI) was reviewed with a focus on its potential applicability to radiation oncology. The improvement of process efficiencies and the prevention of errors were found to be the most significant contributions of AI to radiation oncology. It was found that the prevention of errors is most effective when data transfer processes were automated and operational decisions were based on logical or learned evaluations by the system. It was concluded that AI could greatly improve the efficiency and accuracy of radiation oncology operations. PMID:29904616

Artificial Intelligence in Medicine and Radiation Oncology.

PubMed

Weidlich, Vincent; Weidlich, Georg A

2018-04-13

Artifical Intelligence (AI) was reviewed with a focus on its potential applicability to radiation oncology. The improvement of process efficiencies and the prevention of errors were found to be the most significant contributions of AI to radiation oncology. It was found that the prevention of errors is most effective when data transfer processes were automated and operational decisions were based on logical or learned evaluations by the system. It was concluded that AI could greatly improve the efficiency and accuracy of radiation oncology operations.

AiGERM: A logic programming front end for GERM

NASA Technical Reports Server (NTRS)

Hashim, Safaa H.

1990-01-01

AiGerm (Artificially Intelligent Graphical Entity Relation Modeler) is a relational data base query and programming language front end for MCC (Mission Control Center)/STP's (Space Test Program) Germ (Graphical Entity Relational Modeling) system. It is intended as an add-on component of the Germ system to be used for navigating very large networks of information. It can also function as an expert system shell for prototyping knowledge-based systems. AiGerm provides an interface between the programming language and Germ.

Flexible Ionic-Electronic Hybrid Oxide Synaptic TFTs with Programmable Dynamic Plasticity for Brain-Inspired Neuromorphic Computing.

PubMed

John, Rohit Abraham; Ko, Jieun; Kulkarni, Mohit R; Tiwari, Naveen; Chien, Nguyen Anh; Ing, Ng Geok; Leong, Wei Lin; Mathews, Nripan

2017-08-01

Emulation of biological synapses is necessary for future brain-inspired neuromorphic computational systems that could look beyond the standard von Neuman architecture. Here, artificial synapses based on ionic-electronic hybrid oxide-based transistors on rigid and flexible substrates are demonstrated. The flexible transistors reported here depict a high field-effect mobility of ≈9 cm 2 V -1 s -1 with good mechanical performance. Comprehensive learning abilities/synaptic rules like paired-pulse facilitation, excitatory and inhibitory postsynaptic currents, spike-time-dependent plasticity, consolidation, superlinear amplification, and dynamic logic are successfully established depicting concurrent processing and memory functionalities with spatiotemporal correlation. The results present a fully solution processable approach to fabricate artificial synapses for next-generation transparent neural circuits. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Elements of decisional dynamics: An agent-based approach applied to artificial financial market

NASA Astrophysics Data System (ADS)

Lucas, Iris; Cotsaftis, Michel; Bertelle, Cyrille

2018-02-01

This paper introduces an original mathematical description for describing agents' decision-making process in the case of problems affected by both individual and collective behaviors in systems characterized by nonlinear, path dependent, and self-organizing interactions. An application to artificial financial markets is proposed by designing a multi-agent system based on the proposed formalization. In this application, agents' decision-making process is based on fuzzy logic rules and the price dynamics is purely deterministic according to the basic matching rules of a central order book. Finally, while putting most parameters under evolutionary control, the computational agent-based system is able to replicate several stylized facts of financial time series (distributions of stock returns showing a heavy tail with positive excess kurtosis, absence of autocorrelations in stock returns, and volatility clustering phenomenon).

Conceptual model of a logical system processor of selection to electrical filters for correction of harmonics in low voltage lines

NASA Astrophysics Data System (ADS)

Lastre, Arlys; Torriente, Ives; Méndez, Erik F.; Cordovés, Alexis

2017-06-01

In the present investigation, the authors propose a conceptual model for the analysis and the decision making of the corrective models to use in the mitigation of the harmonic distortion. The authors considered the setting of conventional models, and such adaptive models like the filters incorporation to networks neuronal artificial (RNA's) for the mitigating effect. In addition to the present work is a showing of the experimental model that learns by means of a flowchart denoting the need to use artificial intelligence skills for the exposition of the proposed model. The other aspect considered and analyzed are the adaptability and usage of the same, considering a local reference of the laws and lineaments of energy quality that demands the Department of Electricity and Energy Renewable (MEER) of Equator.

Elements of decisional dynamics: An agent-based approach applied to artificial financial market.

PubMed

Lucas, Iris; Cotsaftis, Michel; Bertelle, Cyrille

2018-02-01

This paper introduces an original mathematical description for describing agents' decision-making process in the case of problems affected by both individual and collective behaviors in systems characterized by nonlinear, path dependent, and self-organizing interactions. An application to artificial financial markets is proposed by designing a multi-agent system based on the proposed formalization. In this application, agents' decision-making process is based on fuzzy logic rules and the price dynamics is purely deterministic according to the basic matching rules of a central order book. Finally, while putting most parameters under evolutionary control, the computational agent-based system is able to replicate several stylized facts of financial time series (distributions of stock returns showing a heavy tail with positive excess kurtosis, absence of autocorrelations in stock returns, and volatility clustering phenomenon).

Microbial Communities as Experimental Units

PubMed Central

DAY, MITCH D.; BECK, DANIEL; FOSTER, JAMES A.

2011-01-01

Artificial ecosystem selection is an experimental technique that treats microbial communities as though they were discrete units by applying selection on community-level properties. Highly diverse microbial communities associated with humans and other organisms can have significant impacts on the health of the host. It is difficult to find correlations between microbial community composition and community-associated diseases, in part because it may be impossible to define a universal and robust species concept for microbes. Microbial communities are composed of potentially thousands of unique populations that evolved in intimate contact, so it is appropriate in many situations to view the community as the unit of analysis. This perspective is supported by recent discoveries using metagenomics and pangenomics. Artificial ecosystem selection experiments can be costly, but they bring the logical rigor of biological model systems to the emerging field of microbial community analysis. PMID:21731083

Applications of Some Artificial Intelligence Methods to Satellite Soundings

NASA Technical Reports Server (NTRS)

Munteanu, M. J.; Jakubowicz, O.

1985-01-01

Hard clustering of temperature profiles and regression temperature retrievals were used to refine the method using the probabilities of membership of each pattern vector in each of the clusters derived with discriminant analysis. In hard clustering the maximum probability is taken and the corresponding cluster as the correct cluster are considered discarding the rest of the probabilities. In fuzzy partitioned clustering these probabilities are kept and the final regression retrieval is a weighted regression retrieval of several clusters. This method was used in the clustering of brightness temperatures where the purpose was to predict tropopause height. A further refinement is the division of temperature profiles into three major regions for classification purposes. The results are summarized in the tables total r.m.s. errors are displayed. An approach based on fuzzy logic which is intimately related to artificial intelligence methods is recommended.

Towards a first implementation of the WLIMES approach in living system studies advancing the diagnostics and therapy in augmented personalized medicine.

PubMed

Simeonov, Plamen L

2017-12-01

The goal of this paper is to advance an extensible theory of living systems using an approach to biomathematics and biocomputation that suitably addresses self-organized, self-referential and anticipatory systems with multi-temporal multi-agents. Our first step is to provide foundations for modelling of emergent and evolving dynamic multi-level organic complexes and their sustentative processes in artificial and natural life systems. Main applications are in life sciences, medicine, ecology and astrobiology, as well as robotics, industrial automation, man-machine interface and creative design. Since 2011 over 100 scientists from a number of disciplines have been exploring a substantial set of theoretical frameworks for a comprehensive theory of life known as Integral Biomathics. That effort identified the need for a robust core model of organisms as dynamic wholes, using advanced and adequately computable mathematics. The work described here for that core combines the advantages of a situation and context aware multivalent computational logic for active self-organizing networks, Wandering Logic Intelligence (WLI), and a multi-scale dynamic category theory, Memory Evolutive Systems (MES), hence WLIMES. This is presented to the modeller via a formal augmented reality language as a first step towards practical modelling and simulation of multi-level living systems. Initial work focuses on the design and implementation of this visual language and calculus (VLC) and its graphical user interface. The results will be integrated within the current methodology and practices of theoretical biology and (personalized) medicine to deepen and to enhance the holistic understanding of life. Copyright © 2017 Elsevier B.V. All rights reserved.

Challenges And Results of the Applications of Fuzzy Logic in the Classification of Rich Galaxy Clusters

NASA Astrophysics Data System (ADS)

Girola Schneider, R.

2017-07-01

The fuzzy logic is a branch of the artificial intelligence founded on the concept that everything is a matter of degree. It intends to create mathematical approximations on the resolution of certain types of problems. In addition, it aims to produce exact results obtained from imprecise data, for which it is particularly useful for electronic and computer applications. This enables it to handle vague or unspecific information when certain parts of a system are unknown or ambiguous and, therefore, they cannot be measured in a reliable manner. Also, when the variation of a variable can produce an alteration on the others The main focus of this paper is to prove the importance of these techniques formulated from a theoretical analysis on its application on ambiguous situations in the field of the rich clusters of galaxies. The purpose is to show its applicability in the several classification systems proposed for the rich clusters, which are based on criteria such as the level of richness of the cluster, the distribution of the brightest galaxies, whether there are signs of type-cD galaxies or not or the existence of sub-clusters. Fuzzy logic enables the researcher to work with "imprecise" information implementing fuzzy sets and combining rules to define actions. The control systems based on fuzzy logic join input variables that are defined in terms of fuzzy sets through rule groups that produce one or several output values of the system under study. From this context, the application of the fuzzy logic's techniques approximates the solution of the mathematical models in abstractions about the rich galaxy cluster classification of physical properties in order to solve the obscurities that must be confronted by an investigation group in order to make a decision.

System identification of smart structures using a wavelet neuro-fuzzy model

NASA Astrophysics Data System (ADS)

Mitchell, Ryan; Kim, Yeesock; El-Korchi, Tahar

2012-11-01

This paper proposes a complex model of smart structures equipped with magnetorheological (MR) dampers. Nonlinear behavior of the structure-MR damper systems is represented by the use of a wavelet-based adaptive neuro-fuzzy inference system (WANFIS). The WANFIS is developed through the integration of wavelet transforms, artificial neural networks, and fuzzy logic theory. To evaluate the effectiveness of the WANFIS model, a three-story building employing an MR damper under a variety of natural hazards is investigated. An artificial earthquake is used for training the input-output mapping of the WANFIS model. The artificial earthquake is generated such that the characteristics of a variety of real recorded earthquakes are included. It is demonstrated that this new WANFIS approach is effective in modeling nonlinear behavior of the structure-MR damper system subjected to a variety of disturbances while resulting in shorter training times in comparison with an adaptive neuro-fuzzy inference system (ANFIS) model. Comparison with high fidelity data proves the viability of the proposed approach in a structural health monitoring setting, and it is validated using known earthquake signals such as El-Centro, Kobe, Northridge, and Hachinohe.

Artificial Intelligence Based Selection of Optimal Cutting Tool and Process Parameters for Effective Turning and Milling Operations

NASA Astrophysics Data System (ADS)

Saranya, Kunaparaju; John Rozario Jegaraj, J.; Ramesh Kumar, Katta; Venkateshwara Rao, Ghanta

2016-06-01

With the increased trend in automation of modern manufacturing industry, the human intervention in routine, repetitive and data specific activities of manufacturing is greatly reduced. In this paper, an attempt has been made to reduce the human intervention in selection of optimal cutting tool and process parameters for metal cutting applications, using Artificial Intelligence techniques. Generally, the selection of appropriate cutting tool and parameters in metal cutting is carried out by experienced technician/cutting tool expert based on his knowledge base or extensive search from huge cutting tool database. The present proposed approach replaces the existing practice of physical search for tools from the databooks/tool catalogues with intelligent knowledge-based selection system. This system employs artificial intelligence based techniques such as artificial neural networks, fuzzy logic and genetic algorithm for decision making and optimization. This intelligence based optimal tool selection strategy is developed using Mathworks Matlab Version 7.11.0 and implemented. The cutting tool database was obtained from the tool catalogues of different tool manufacturers. This paper discusses in detail, the methodology and strategies employed for selection of appropriate cutting tool and optimization of process parameters based on multi-objective optimization criteria considering material removal rate, tool life and tool cost.

Experiments on neural network architectures for fuzzy logic

NASA Technical Reports Server (NTRS)

Keller, James M.

1991-01-01

The use of fuzzy logic to model and manage uncertainty in a rule-based system places high computational demands on an inference engine. In an earlier paper, the authors introduced a trainable neural network structure for fuzzy logic. These networks can learn and extrapolate complex relationships between possibility distributions for the antecedents and consequents in the rules. Here, the power of these networks is further explored. The insensitivity of the output to noisy input distributions (which are likely if the clauses are generated from real data) is demonstrated as well as the ability of the networks to internalize multiple conjunctive clause and disjunctive clause rules. Since different rules with the same variables can be encoded in a single network, this approach to fuzzy logic inference provides a natural mechanism for rule conflict resolution.

Exploring expressivity and emotion with artificial voice and speech technologies.

PubMed

Pauletto, Sandra; Balentine, Bruce; Pidcock, Chris; Jones, Kevin; Bottaci, Leonardo; Aretoulaki, Maria; Wells, Jez; Mundy, Darren P; Balentine, James

2013-10-01

Emotion in audio-voice signals, as synthesized by text-to-speech (TTS) technologies, was investigated to formulate a theory of expression for user interface design. Emotional parameters were specified with markup tags, and the resulting audio was further modulated with post-processing techniques. Software was then developed to link a selected TTS synthesizer with an automatic speech recognition (ASR) engine, producing a chatbot that could speak and listen. Using these two artificial voice subsystems, investigators explored both artistic and psychological implications of artificial speech emotion. Goals of the investigation were interdisciplinary, with interest in musical composition, augmentative and alternative communication (AAC), commercial voice announcement applications, human-computer interaction (HCI), and artificial intelligence (AI). The work-in-progress points towards an emerging interdisciplinary ontology for artificial voices. As one study output, HCI tools are proposed for future collaboration.

Fuzzy Logic Decoupled Longitudinal Control for General Aviation Airplanes

NASA Technical Reports Server (NTRS)

Duerksen, Noel

1996-01-01

It has been hypothesized that a human pilot uses the same set of generic skills to control a wide variety of aircraft. If this is true, then it should be possible to construct an electronic controller which embodies this generic skill set such that it can successfully control difference airplanes without being matched to a specific airplane. In an attempt to create such a system, a fuzzy logic controller was devised to control throttle position and another to control elevator position. These two controllers were used to control flight path angle and airspeed for both a piston powered single engine airplane simulation and a business jet simulation. Overspeed protection and stall protection were incorporated in the form of expert systems supervisors. It was found that by using the artificial intelligence techniques of fuzzy logic and expert systems, a generic longitudinal controller could be successfully used on two general aviation aircraft types that have very difference characteristics. These controllers worked for both airplanes over their entire flight envelopes including configuration changes. The controllers for both airplanes were identical except for airplane specific limits (maximum allowable airspeed, throttle lever travel, etc.). The controllers also handled configuration changes without mode switching or knowledge of the current configuration. This research validated the fact that the same fuzzy logic based controller can control two very different general aviation airplanes. It also developed the basic controller architecture and specific control parameters required for such a general controller.

The Politics of Logic in Early Childhood Research: A Case of the Brain, Hard Facts, Trees and Rhizomes

ERIC Educational Resources Information Center

MacNaughton, Glenda

2004-01-01

This paper engages with questions of logic and its politics to explore how those of us in early childhood education can become critical consumers of "brain research". The research truths we use to construct classroom practices decide the meanings of our actions, thoughts and feelings and our interactions with children. Following Foucault (1980), I…

The Artificial Intelligence Applications to Learning Programme.

ERIC Educational Resources Information Center

Williams, Noel

1992-01-01

Explains the Artificial Intelligence Applications to Learning Programme, which was developed in the United Kingdom to explore and accelerate the use of artificial intelligence (AI) technologies in learning in both the educational and industrial sectors. Highlights include program evaluation, marketing, ownership of information, consortia, and cost…

Quantum entanglement in photoactive prebiotic systems.

PubMed

Tamulis, Arvydas; Grigalavicius, Mantas

2014-06-01

This paper contains the review of quantum entanglement investigations in living systems, and in the quantum mechanically modelled photoactive prebiotic kernel systems. We define our modelled self-assembled supramolecular photoactive centres, composed of one or more sensitizer molecules, precursors of fatty acids and a number of water molecules, as a photoactive prebiotic kernel systems. We propose that life first emerged in the form of such minimal photoactive prebiotic kernel systems and later in the process of evolution these photoactive prebiotic kernel systems would have produced fatty acids and covered themselves with fatty acid envelopes to become the minimal cells of the Fatty Acid World. Specifically, we model self-assembling of photoactive prebiotic systems with observed quantum entanglement phenomena. We address the idea that quantum entanglement was important in the first stages of origins of life and evolution of the biospheres because simultaneously excite two prebiotic kernels in the system by appearance of two additional quantum entangled excited states, leading to faster growth and self-replication of minimal living cells. The quantum mechanically modelled possibility of synthesizing artificial self-reproducing quantum entangled prebiotic kernel systems and minimal cells also impacts the possibility of the most probable path of emergence of protocells on the Earth or elsewhere. We also examine the quantum entangled logic gates discovered in the modelled systems composed of two prebiotic kernels. Such logic gates may have application in the destruction of cancer cells or becoming building blocks of new forms of artificial cells including magnetically active ones.

Synthesis of capillary pressure curves from post-stack seismic data with the use of intelligent estimators: A case study from the Iranian part of the South Pars gas field, Persian Gulf Basin

NASA Astrophysics Data System (ADS)

Golsanami, Naser; Kadkhodaie-Ilkhchi, Ali; Erfani, Amir

2015-01-01

Capillary pressure curves are important data for reservoir rock typing, analyzing pore throat distribution, determining height above free water level, and reservoir simulation. Laboratory experiments provide accurate data, however they are expensive, time-consuming and discontinuous through the reservoir intervals. The current study focuses on synthesizing artificial capillary pressure (Pc) curves from seismic attributes with the use of artificial intelligent systems including Artificial Neural Networks (ANNs), Fuzzy logic (FL) and Adaptive Neuro-Fuzzy Inference Systems (ANFISs). The synthetic capillary pressure curves were achieved by estimating pressure values at six mercury saturation points. These points correspond to mercury filled pore volumes of core samples (Hg-saturation) at 5%, 20%, 35%, 65%, 80%, and 90% saturations. To predict the synthetic Pc curve at each saturation point, various FL, ANFIS and ANN models were constructed. The varying neural network models differ in their training algorithm. Based on the performance function, the most accurately functioning models were selected as the final solvers to do the prediction process at each of the above-mentioned mercury saturation points. The constructed models were then tested at six depth points of the studied well which were already unforeseen by the models. The results show that the Fuzzy logic and neuro-fuzzy models were not capable of making reliable estimations, while the predictions from the ANN models were satisfyingly trustworthy. The obtained results showed a good agreement between the laboratory derived and synthetic capillary pressure curves. Finally, a 3D seismic cube was captured for which the required attributes were extracted and the capillary pressure cube was estimated by using the developed models. In the next step, the synthesized Pc cube was compared with the seismic cube and an acceptable correspondence was observed.

Air Quality Forecasting through Different Statistical and Artificial Intelligence Techniques

NASA Astrophysics Data System (ADS)

Mishra, D.; Goyal, P.

2014-12-01

Urban air pollution forecasting has emerged as an acute problem in recent years because there are sever environmental degradation due to increase in harmful air pollutants in the ambient atmosphere. In this study, there are different types of statistical as well as artificial intelligence techniques are used for forecasting and analysis of air pollution over Delhi urban area. These techniques are principle component analysis (PCA), multiple linear regression (MLR) and artificial neural network (ANN) and the forecasting are observed in good agreement with the observed concentrations through Central Pollution Control Board (CPCB) at different locations in Delhi. But such methods suffers from disadvantages like they provide limited accuracy as they are unable to predict the extreme points i.e. the pollution maximum and minimum cut-offs cannot be determined using such approach. Also, such methods are inefficient approach for better output forecasting. But with the advancement in technology and research, an alternative to the above traditional methods has been proposed i.e. the coupling of statistical techniques with artificial Intelligence (AI) can be used for forecasting purposes. The coupling of PCA, ANN and fuzzy logic is used for forecasting of air pollutant over Delhi urban area. The statistical measures e.g., correlation coefficient (R), normalized mean square error (NMSE), fractional bias (FB) and index of agreement (IOA) of the proposed model are observed in better agreement with the all other models. Hence, the coupling of statistical and artificial intelligence can be use for the forecasting of air pollutant over urban area.

Developing and Optimising the Use of Logic Models in Systematic Reviews: Exploring Practice and Good Practice in the Use of Programme Theory in Reviews.

PubMed

Kneale, Dylan; Thomas, James; Harris, Katherine

2015-01-01

Logic models are becoming an increasingly common feature of systematic reviews, as is the use of programme theory more generally in systematic reviewing. Logic models offer a framework to help reviewers to 'think' conceptually at various points during the review, and can be a useful tool in defining study inclusion and exclusion criteria, guiding the search strategy, identifying relevant outcomes, identifying mediating and moderating factors, and communicating review findings. In this paper we critique the use of logic models in systematic reviews and protocols drawn from two databases representing reviews of health interventions and international development interventions. Programme theory featured only in a minority of the reviews and protocols included. Despite drawing from different disciplinary traditions, reviews and protocols from both sources shared several limitations in their use of logic models and theories of change, and these were used almost unanimously to solely depict pictorially the way in which the intervention worked. Logic models and theories of change were consequently rarely used to communicate the findings of the review. Logic models have the potential to be an aid integral throughout the systematic reviewing process. The absence of good practice around their use and development may be one reason for the apparent limited utility of logic models in many existing systematic reviews. These concerns are addressed in the second half of this paper, where we offer a set of principles in the use of logic models and an example of how we constructed a logic model for a review of school-based asthma interventions.

Do institutional logics predict interpretation of contract rules at the dental chair-side?

PubMed

Harris, Rebecca; Brown, Stephen; Holt, Robin; Perkins, Elizabeth

2014-12-01

In quasi-markets, contracts find purchasers influencing health care providers, although problems exist where providers use personal bias and heuristics to respond to written agreements, tending towards the moral hazard of opportunism. Previous research on quasi-market contracts typically understands opportunism as fully rational, individual responses selecting maximally efficient outcomes from a set of possibilities. We take a more emotive and collective view of contracting, exploring the influence of institutional logics in relation to the opportunistic behaviour of dentists. Following earlier qualitative work where we identified four institutional logics in English general dental practice, and six dental contract areas where there was scope for opportunism; in 2013 we surveyed 924 dentists to investigate these logics and whether they had predictive purchase over dentists' chair-side behaviour. Factor analysis involving 300 responses identified four logics entwined in (often technical) behaviour: entrepreneurial commercialism, duty to staff and patients, managerialism, public good. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

F-OWL: An Inference Engine for Semantic Web

NASA Technical Reports Server (NTRS)

Zou, Youyong; Finin, Tim; Chen, Harry

2004-01-01

Understanding and using the data and knowledge encoded in semantic web documents requires an inference engine. F-OWL is an inference engine for the semantic web language OWL language based on F-logic, an approach to defining frame-based systems in logic. F-OWL is implemented using XSB and Flora-2 and takes full advantage of their features. We describe how F-OWL computes ontology entailment and compare it with other description logic based approaches. We also describe TAGA, a trading agent environment that we have used as a test bed for F-OWL and to explore how multiagent systems can use semantic web concepts and technology.

Understanding HMIS Implementation in a Developing Country Ministry of Health Context - an Institutional Logics Perspective

PubMed Central

Asangansi, Ime

2012-01-01

Globally, health management information systems (HMIS) have been hailed as important tools for health reform (1). However, their implementation has become a major challenge for researchers and practitioners because of the significant proportion of failure of implementation efforts (2; 3). Researchers have attributed this significant failure of HMIS implementation, in part, to the complexity of meeting with and satisfying multiple (poorly understood) logics in the implementation process. This paper focuses on exploring the multiple logics, including how they may conflict and affect the HMIS implementation process. Particularly, I draw on an institutional logics perspective to analyze empirical findings from an action research project, which involved HMIS implementation in a state government Ministry of Health in (Northern) Nigeria. The analysis highlights the important HMIS institutional logics, where they conflict and how they are resolved. I argue for an expanded understanding of HMIS implementation that recognizes various institutional logics that participants bring to the implementation process, and how these are inscribed in the decision making process in ways that may be conflicting, and increasing the risk of failure. Furthermore, I propose that the resolution of conflicting logics can be conceptualized as involving deinstitutionalization, changeover resolution or dialectical resolution mechanisms. I conclude by suggesting that HMIS implementation can be improved by implementation strategies that are made based on an understanding of these conflicting logics. PMID:23569646

Understanding HMIS Implementation in a Developing Country Ministry of Health Context - an Institutional Logics Perspective.

PubMed

Asangansi, Ime

2012-01-01

Globally, health management information systems (HMIS) have been hailed as important tools for health reform (1). However, their implementation has become a major challenge for researchers and practitioners because of the significant proportion of failure of implementation efforts (2; 3). Researchers have attributed this significant failure of HMIS implementation, in part, to the complexity of meeting with and satisfying multiple (poorly understood) logics in the implementation process. This paper focuses on exploring the multiple logics, including how they may conflict and affect the HMIS implementation process. Particularly, I draw on an institutional logics perspective to analyze empirical findings from an action research project, which involved HMIS implementation in a state government Ministry of Health in (Northern) Nigeria. The analysis highlights the important HMIS institutional logics, where they conflict and how they are resolved. I argue for an expanded understanding of HMIS implementation that recognizes various institutional logics that participants bring to the implementation process, and how these are inscribed in the decision making process in ways that may be conflicting, and increasing the risk of failure. Furthermore, I propose that the resolution of conflicting logics can be conceptualized as involving deinstitutionalization, changeover resolution or dialectical resolution mechanisms. I conclude by suggesting that HMIS implementation can be improved by implementation strategies that are made based on an understanding of these conflicting logics.

An Empirical Study of Students' Understanding of a Logical Structure in the Definition of Limit via the epsilon-Strip Activity

ERIC Educational Resources Information Center

Roh, Kyeong Hah

2010-01-01

This study explored students' understanding of a logical structure in defining the limit of a sequence, focusing on the relationship between epsilon and N. The subjects of this study were college students who had already encountered the concept of limit but did not have any experience with rigorous proofs using the epsilon-N definition. This study…

Dc microgrid stabilization through fuzzy control of interleaved, heterogeneous storage elements

NASA Astrophysics Data System (ADS)

Smith, Robert David

As microgrid power systems gain prevalence and renewable energy comprises greater and greater portions of distributed generation, energy storage becomes important to offset the higher variance of renewable energy sources and maximize their usefulness. One of the emerging techniques is to utilize a combination of lead-acid batteries and ultracapacitors to provide both short and long-term stabilization to microgrid systems. The different energy and power characteristics of batteries and ultracapacitors imply that they ought to be utilized in different ways. Traditional linear controls can use these energy storage systems to stabilize a power grid, but cannot effect more complex interactions. This research explores a fuzzy logic approach to microgrid stabilization. The ability of a fuzzy logic controller to regulate a dc bus in the presence of source and load fluctuations, in a manner comparable to traditional linear control systems, is explored and demonstrated. Furthermore, the expanded capabilities (such as storage balancing, self-protection, and battery optimization) of a fuzzy logic system over a traditional linear control system are shown. System simulation results are presented and validated through hardware-based experiments. These experiments confirm the capabilities of the fuzzy logic control system to regulate bus voltage, balance storage elements, optimize battery usage, and effect self-protection.

Non-Intrusive Gaze Tracking Using Artificial Neural Networks

DTIC Science & Technology

1994-01-05

We have developed an artificial neural network based gaze tracking, system which can be customized to individual users. A three layer feed forward...empirical analysis of the performance of a large number of artificial neural network architectures for this task. Suggestions for further explorations...for neurally based gaze trackers are presented, and are related to other similar artificial neural network applications such as autonomous road following.

Bacterial Artificial Chromosome Clones of Viruses Comprising the Towne Cytomegalovirus Vaccine

PubMed Central

Cui, Xiaohong; Adler, Stuart P.; Davison, Andrew J.; Smith, Larry; Habib, EL-Sayed E.; McVoy, Michael A.

2012-01-01

Bacterial artificial chromosome (BAC) clones have proven invaluable for genetic manipulation of herpesvirus genomes. BAC cloning can also be useful for capturing representative genomes that comprise a viral stock or mixture. The Towne live attenuated cytomegalovirus vaccine was developed in the 1970s by serial passage in cultured fibroblasts. Although its safety, immunogenicity, and efficacy have been evaluated in nearly a thousand human subjects, the vaccine itself has been little studied. Instead, genetic composition and in vitro growth properties have been inferred from studies of laboratory stocks that may not always accurately represent the viruses that comprise the vaccine. Here we describe the use of BAC cloning to define the genotypic and phenotypic properties of viruses from the Towne vaccine. Given the extensive safety history of the Towne vaccine, these BACs provide a logical starting point for the development of next-generation rationally engineered cytomegalovirus vaccines. PMID:22187535

Cognitive and artificial representations in handwriting recognition

NASA Astrophysics Data System (ADS)

Lenaghan, Andrew P.; Malyan, Ron

1996-03-01

Both cognitive processes and artificial recognition systems may be characterized by the forms of representation they build and manipulate. This paper looks at how handwriting is represented in current recognition systems and the psychological evidence for its representation in the cognitive processes responsible for reading. Empirical psychological work on feature extraction in early visual processing is surveyed to show that a sound psychological basis for feature extraction exists and to describe the features this approach leads to. The first stage of the development of an architecture for a handwriting recognition system which has been strongly influenced by the psychological evidence for the cognitive processes and representations used in early visual processing, is reported. This architecture builds a number of parallel low level feature maps from raw data. These feature maps are thresholded and a region labeling algorithm is used to generate sets of features. Fuzzy logic is used to quantify the uncertainty in the presence of individual features.

Application of Artificial Intelligence (AI) programming techniques to tactical guidance for fighter aircraft

NASA Technical Reports Server (NTRS)

Mcmanus, John W.; Goodrich, Kenneth H.

1989-01-01

A research program investigating the use of Artificial Intelligence (AI) programming techniques to aid in the development of a Tactical Decision Generator (TDG) for Within-Visual-Range (WVR) air combat engagements is discussed. The application of AI methods for development and implementation of the TDG is presented. The history of the Adaptive Maneuvering Logic (AML) program is traced and current versions of the (AML) program is traced and current versions of the AML program are compared and contrasted with the TDG system. The Knowledge-Based Systems (KBS) used by the TDG to aid in the decision-making process are outlined and example rules are presented. The results of tests to evaluate the performance of the TDG against a version of AML and against human pilots in the Langley Differential Maneuvering Simulator (DMS) are presented. To date, these results have shown significant performance gains in one-versus-one air combat engagements.

Bacterial artificial chromosome clones of viruses comprising the towne cytomegalovirus vaccine.

PubMed

Cui, Xiaohong; Adler, Stuart P; Davison, Andrew J; Smith, Larry; Habib, El-Sayed E; McVoy, Michael A

2012-01-01

Bacterial artificial chromosome (BAC) clones have proven invaluable for genetic manipulation of herpesvirus genomes. BAC cloning can also be useful for capturing representative genomes that comprise a viral stock or mixture. The Towne live attenuated cytomegalovirus vaccine was developed in the 1970s by serial passage in cultured fibroblasts. Although its safety, immunogenicity, and efficacy have been evaluated in nearly a thousand human subjects, the vaccine itself has been little studied. Instead, genetic composition and in vitro growth properties have been inferred from studies of laboratory stocks that may not always accurately represent the viruses that comprise the vaccine. Here we describe the use of BAC cloning to define the genotypic and phenotypic properties of viruses from the Towne vaccine. Given the extensive safety history of the Towne vaccine, these BACs provide a logical starting point for the development of next-generation rationally engineered cytomegalovirus vaccines.

Artificial intelligence (AI) based tactical guidance for fighter aircraft

NASA Technical Reports Server (NTRS)

Mcmanus, John W.; Goodrich, Kenneth H.

1990-01-01

A research program investigating the use of artificial intelligence (AI) techniques to aid in the development of a Tactical Decision Generator (TDG) for Within Visual Range air combat engagements is discussed. The application of AI programming and problem solving methods in the development and implementation of the Computerized Logic For Air-to-Air Warfare Simulations (CLAWS), a second generation TDG, is presented. The knowledge-based systems used by CLAWS to aid in the tactical decision-making process are outlined in detail, and the results of tests to evaluate the performance of CLAWS versus a baseline TDG developed in FORTRAN to run in real time in the Langley Differential Maneuvering Simulator, are presented. To date, these test results have shown significant performance gains with respect to the TDG baseline in one-versus-one air combat engagements, and the AI-based TDG software has proven to be much easier to modify and maintain than the baseline FORTRAN TDG programs.

Foundations and Emerging Paradigms for Computing in Living Cells.

PubMed

Ma, Kevin C; Perli, Samuel D; Lu, Timothy K

2016-02-27

Genetic circuits, composed of complex networks of interacting molecular machines, enable living systems to sense their dynamic environments, perform computation on the inputs, and formulate appropriate outputs. By rewiring and expanding these circuits with novel parts and modules, synthetic biologists have adapted living systems into vibrant substrates for engineering. Diverse paradigms have emerged for designing, modeling, constructing, and characterizing such artificial genetic systems. In this paper, we first provide an overview of recent advances in the development of genetic parts and highlight key engineering approaches. We then review the assembly of these parts into synthetic circuits from the perspectives of digital and analog logic, systems biology, and metabolic engineering, three areas of particular theoretical and practical interest. Finally, we discuss notable challenges that the field of synthetic biology still faces in achieving reliable and predictable forward-engineering of artificial biological circuits. Copyright © 2016. Published by Elsevier Ltd.

Web Intelligence and Artificial Intelligence in Education

ERIC Educational Resources Information Center

Devedzic, Vladan

2004-01-01

This paper surveys important aspects of Web Intelligence (WI) in the context of Artificial Intelligence in Education (AIED) research. WI explores the fundamental roles as well as practical impacts of Artificial Intelligence (AI) and advanced Information Technology (IT) on the next generation of Web-related products, systems, services, and…

The comparison of manual and LabVIEW-based fuzzy control on mechanical ventilation.

PubMed

Guler, Hasan; Ata, Fikret

2014-09-01

The aim of this article is to develop a knowledge-based therapy for management of rats with respiratory distress. A mechanical ventilator was designed to achieve this aim. The designed ventilator is called an intelligent mechanical ventilator since fuzzy logic was used to control the pneumatic equipment according to the rat's status. LabVIEW software was used to control all equipments in the ventilator prototype and to monitor respiratory variables in the experiment. The designed ventilator can be controlled both manually and by fuzzy logic. Eight female Wistar-Albino rats were used to test the designed ventilator and to show the effectiveness of fuzzy control over manual control on pressure control ventilation mode. The anesthetized rats were first ventilated for 20 min manually. After that time, they were ventilated for 20 min by fuzzy logic. Student's t-test for p < 0.05 was applied to the measured minimum, maximum and mean peak inspiration pressures to analyze the obtained results. The results show that there is no statistical difference in the rat's lung parameters before and after the experiments. It can be said that the designed ventilator and developed knowledge-based therapy support artificial respiration of living things successfully. © IMechE 2014.

Globalisation and Education for Sustainable Development: Exploring the Global in Motion

ERIC Educational Resources Information Center

Bengtsson, Stefan L.; Östman, Leif O.

2016-01-01

The article explores education for sustainable development (ESD) as a policy concept in different spaces and how it is re-articulated as part of a process of globalisation. The objective is to explore empirically an alternative set of logics in order to conceive of this process of globalisation. With this objective in mind, the article…

Human Artificial Chromosomes with Alpha Satellite-Based De Novo Centromeres Show Increased Frequency of Nondisjunction and Anaphase Lag

PubMed Central

Rudd, M. Katharine; Mays, Robert W.; Schwartz, Stuart; Willard, Huntington F.

2003-01-01

Human artificial chromosomes have been used to model requirements for human chromosome segregation and to explore the nature of sequences competent for centromere function. Normal human centromeres require specialized chromatin that consists of alpha satellite DNA complexed with epigenetically modified histones and centromere-specific proteins. While several types of alpha satellite DNA have been used to assemble de novo centromeres in artificial chromosome assays, the extent to which they fully recapitulate normal centromere function has not been explored. Here, we have used two kinds of alpha satellite DNA, DXZ1 (from the X chromosome) and D17Z1 (from chromosome 17), to generate human artificial chromosomes. Although artificial chromosomes are mitotically stable over many months in culture, when we examined their segregation in individual cell divisions using an anaphase assay, artificial chromosomes exhibited more segregation errors than natural human chromosomes (P < 0.001). Naturally occurring, but abnormal small ring chromosomes derived from chromosome 17 and the X chromosome also missegregate more than normal chromosomes, implicating overall chromosome size and/or structure in the fidelity of chromosome segregation. As different artificial chromosomes missegregate over a fivefold range, the data suggest that variable centromeric DNA content and/or epigenetic assembly can influence the mitotic behavior of artificial chromosomes. PMID:14560014

Human artificial chromosomes with alpha satellite-based de novo centromeres show increased frequency of nondisjunction and anaphase lag.

PubMed

Rudd, M Katharine; Mays, Robert W; Schwartz, Stuart; Willard, Huntington F

2003-11-01

Human artificial chromosomes have been used to model requirements for human chromosome segregation and to explore the nature of sequences competent for centromere function. Normal human centromeres require specialized chromatin that consists of alpha satellite DNA complexed with epigenetically modified histones and centromere-specific proteins. While several types of alpha satellite DNA have been used to assemble de novo centromeres in artificial chromosome assays, the extent to which they fully recapitulate normal centromere function has not been explored. Here, we have used two kinds of alpha satellite DNA, DXZ1 (from the X chromosome) and D17Z1 (from chromosome 17), to generate human artificial chromosomes. Although artificial chromosomes are mitotically stable over many months in culture, when we examined their segregation in individual cell divisions using an anaphase assay, artificial chromosomes exhibited more segregation errors than natural human chromosomes (P < 0.001). Naturally occurring, but abnormal small ring chromosomes derived from chromosome 17 and the X chromosome also missegregate more than normal chromosomes, implicating overall chromosome size and/or structure in the fidelity of chromosome segregation. As different artificial chromosomes missegregate over a fivefold range, the data suggest that variable centromeric DNA content and/or epigenetic assembly can influence the mitotic behavior of artificial chromosomes.

Implementation of Multivariable Logic Functions in Parallel by Electrically Addressing a Molecule of Three Dopants in Silicon.

PubMed

Fresch, Barbara; Bocquel, Juanita; Hiluf, Dawit; Rogge, Sven; Levine, Raphael D; Remacle, Françoise

2017-07-05

To realize low-power, compact logic circuits, one can explore parallel operation on single nanoscale devices. An added incentive is to use multivalued (as distinct from Boolean) logic. Here, we theoretically demonstrate that the computation of all the possible outputs of a multivariate, multivalued logic function can be implemented in parallel by electrical addressing of a molecule made up of three interacting dopant atoms embedded in Si. The electronic states of the dopant molecule are addressed by pulsing a gate voltage. By simulating the time evolution of the non stationary electronic density built by the gate voltage, we show that one can implement a molecular decision tree that provides in parallel all the outputs for all the inputs of the multivariate, multivalued logic function. The outputs are encoded in the populations and in the bond orders of the dopant molecule, which can be measured using an STM tip. We show that the implementation of the molecular logic tree is equivalent to a spectral function decomposition. The function that is evaluated can be field-programmed by changing the time profile of the pulsed gate voltage. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

A Concurrent Distributed System for Aircraft Tactical Decision Generation

NASA Technical Reports Server (NTRS)

McManus, John W.

1990-01-01

A research program investigating the use of artificial intelligence (AI) techniques to aid in the development of a Tactical Decision Generator (TDG) for Within Visual Range (WVR) air combat engagements is discussed. The application of AI programming and problem solving methods in the development and implementation of a concurrent version of the Computerized Logic For Air-to-Air Warfare Simulations (CLAWS) program, a second generation TDG, is presented. Concurrent computing environments and programming approaches are discussed and the design and performance of a prototype concurrent TDG system are presented.

Artificial intelligence techniques for modeling database user behavior

NASA Technical Reports Server (NTRS)

Tanner, Steve; Graves, Sara J.

1990-01-01

The design and development of the adaptive modeling system is described. This system models how a user accesses a relational database management system in order to improve its performance by discovering use access patterns. In the current system, these patterns are used to improve the user interface and may be used to speed data retrieval, support query optimization and support a more flexible data representation. The system models both syntactic and semantic information about the user's access and employs both procedural and rule-based logic to manipulate the model.

Robust Control Analysis of Hydraulic Turbine Speed

NASA Astrophysics Data System (ADS)

Jekan, P.; Subramani, C.

2018-04-01

An effective control strategy for the hydro-turbine governor in time scenario is adjective for this paper. Considering the complex dynamic characteristic and the uncertainty of the hydro-turbine governor model and taking the static and dynamic performance of the governing system as the ultimate goal, the designed logic combined the classical PID control theory with artificial intelligence used to obtain the desired output. The used controller will be a variable control techniques, therefore, its parameters can be adaptively adjusted according to the information about the control error signal.

Developing and Optimising the Use of Logic Models in Systematic Reviews: Exploring Practice and Good Practice in the Use of Programme Theory in Reviews

PubMed Central

Kneale, Dylan; Thomas, James; Harris, Katherine

2015-01-01

Background Logic models are becoming an increasingly common feature of systematic reviews, as is the use of programme theory more generally in systematic reviewing. Logic models offer a framework to help reviewers to ‘think’ conceptually at various points during the review, and can be a useful tool in defining study inclusion and exclusion criteria, guiding the search strategy, identifying relevant outcomes, identifying mediating and moderating factors, and communicating review findings. Methods and Findings In this paper we critique the use of logic models in systematic reviews and protocols drawn from two databases representing reviews of health interventions and international development interventions. Programme theory featured only in a minority of the reviews and protocols included. Despite drawing from different disciplinary traditions, reviews and protocols from both sources shared several limitations in their use of logic models and theories of change, and these were used almost unanimously to solely depict pictorially the way in which the intervention worked. Logic models and theories of change were consequently rarely used to communicate the findings of the review. Conclusions Logic models have the potential to be an aid integral throughout the systematic reviewing process. The absence of good practice around their use and development may be one reason for the apparent limited utility of logic models in many existing systematic reviews. These concerns are addressed in the second half of this paper, where we offer a set of principles in the use of logic models and an example of how we constructed a logic model for a review of school-based asthma interventions. PMID:26575182

A fuzzy-logic-based model to predict biogas and methane production rates in a pilot-scale mesophilic UASB reactor treating molasses wastewater.

PubMed

Turkdogan-Aydinol, F Ilter; Yetilmezsoy, Kaan

2010-10-15

A MIMO (multiple inputs and multiple outputs) fuzzy-logic-based model was developed to predict biogas and methane production rates in a pilot-scale 90-L mesophilic up-flow anaerobic sludge blanket (UASB) reactor treating molasses wastewater. Five input variables such as volumetric organic loading rate (OLR), volumetric total chemical oxygen demand (TCOD) removal rate (R(V)), influent alkalinity, influent pH and effluent pH were fuzzified by the use of an artificial intelligence-based approach. Trapezoidal membership functions with eight levels were conducted for the fuzzy subsets, and a Mamdani-type fuzzy inference system was used to implement a total of 134 rules in the IF-THEN format. The product (prod) and the centre of gravity (COG, centroid) methods were employed as the inference operator and defuzzification methods, respectively. Fuzzy-logic predicted results were compared with the outputs of two exponential non-linear regression models derived in this study. The UASB reactor showed a remarkable performance on the treatment of molasses wastewater, with an average TCOD removal efficiency of 93 (+/-3)% and an average volumetric TCOD removal rate of 6.87 (+/-3.93) kg TCOD(removed)/m(3)-day, respectively. Findings of this study clearly indicated that, compared to non-linear regression models, the proposed MIMO fuzzy-logic-based model produced smaller deviations and exhibited a superior predictive performance on forecasting of both biogas and methane production rates with satisfactory determination coefficients over 0.98. 2010 Elsevier B.V. All rights reserved.

Artificial Intelligence Measurement System, Overview and Lessons Learned. Final Project Report.

ERIC Educational Resources Information Center

Baker, Eva L.; Butler, Frances A.

This report summarizes the work conducted for the Artificial Intelligence Measurement System (AIMS) Project which was undertaken as an exploration of methodology to consider how the effects of artificial intelligence systems could be compared to human performance. The research covered four areas of inquiry: (1) natural language processing and…

The Potential of Artificial Intelligence in Aids for the Disabled.

ERIC Educational Resources Information Center

Boyer, John J.

The paper explores the possibilities for applying the knowledge of artificial intelligence (AI) research to aids for the disabled. Following a definition of artificial intelligence, the paper reviews areas of basic AI research, such as computer vision, machine learning, and planning and problem solving. Among application areas relevant to the…

NMR Parameters Determination through ACE Committee Machine with Genetic Implanted Fuzzy Logic and Genetic Implanted Neural Network

NASA Astrophysics Data System (ADS)

Asoodeh, Mojtaba; Bagheripour, Parisa; Gholami, Amin

2015-06-01

Free fluid porosity and rock permeability, undoubtedly the most critical parameters of hydrocarbon reservoir, could be obtained by processing of nuclear magnetic resonance (NMR) log. Despite conventional well logs (CWLs), NMR logging is very expensive and time-consuming. Therefore, idea of synthesizing NMR log from CWLs would be of a great appeal among reservoir engineers. For this purpose, three optimization strategies are followed. Firstly, artificial neural network (ANN) is optimized by virtue of hybrid genetic algorithm-pattern search (GA-PS) technique, then fuzzy logic (FL) is optimized by means of GA-PS, and eventually an alternative condition expectation (ACE) model is constructed using the concept of committee machine to combine outputs of optimized and non-optimized FL and ANN models. Results indicated that optimization of traditional ANN and FL model using GA-PS technique significantly enhances their performances. Furthermore, the ACE committee of aforementioned models produces more accurate and reliable results compared with a singular model performing alone.

Development of the automatic test pattern generation for NPP digital electronic circuits using the degree of freedom concept

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

Kim, D.S.; Seong, P.H.

1995-08-01

In this paper, an improved algorithm for automatic test pattern generation (ATG) for nuclear power plant digital electronic circuits--the combinational type of logic circuits is presented. For accelerating and improving the ATG process for combinational circuits the presented ATG algorithm has the new concept--the degree of freedom (DF). The DF, directly computed from the system descriptions such as types of gates and their interconnections, is the criterion to decide which among several alternate lines` logic values required along each path promises to be the most effective in order to accelerate and improve the ATG process. Based on the DF themore » proposed ATG algorithm is implemented in the automatic fault diagnosis system (AFDS) which incorporates the advanced fault diagnosis method of artificial intelligence technique, it is shown that the AFDS using the ATG algorithm makes Universal Card (UV Card) testing much faster than the present testing practice or by using exhaustive testing sets.« less

Artificial neuron synapse transistor based on silicon nanomembrane on plastic substrate

NASA Astrophysics Data System (ADS)

Liu, Minjie; Huang, Gaoshan; Feng, Ping; Guo, Qinglei; Shao, Feng; Tian, Ziao; Li, Gongjin; Wan, Qing; Mei, Yongfeng

2017-06-01

Silicon nanomembrane (SiNM) transistors gated by chitosan membrane were fabricated on plastic substrate to mimic synapse behaviors. The device has both a bottom proton gate (BG) and multiple side gates (SG). Electrical transfer properties of BG show hysteresis curves different from those of typical SiO2 gate dielectric. Synaptic behaviors and functions by linear accumulation and release of protons have been mimicked on this device: excitatory post-synaptic current (EPSC) and paired pulse facilitation behavior of biological synapses were mimicked and the paired-pulse facilitation index could be effectively tuned by the spike interval applied on the BG. Synaptic behaviors and functions, including short-term memory and long-term memory, were also experimentally demonstrated in BG mode. Meanwhile, spiking logic operation and logic modulation were realized in SG mode. Project supported by the National Natural Science Foundation of China (No. 51322201), the Specialized Research Fund for the Doctoral Program of Higher Education (No. 20120071110025), and Science and Technology Commission of Shanghai Municipality (No. 14JC1400200).

The genotype-phenotype map of an evolving digital organism.

PubMed

Fortuna, Miguel A; Zaman, Luis; Ofria, Charles; Wagner, Andreas

2017-02-01

To understand how evolving systems bring forth novel and useful phenotypes, it is essential to understand the relationship between genotypic and phenotypic change. Artificial evolving systems can help us understand whether the genotype-phenotype maps of natural evolving systems are highly unusual, and it may help create evolvable artificial systems. Here we characterize the genotype-phenotype map of digital organisms in Avida, a platform for digital evolution. We consider digital organisms from a vast space of 10141 genotypes (instruction sequences), which can form 512 different phenotypes. These phenotypes are distinguished by different Boolean logic functions they can compute, as well as by the complexity of these functions. We observe several properties with parallels in natural systems, such as connected genotype networks and asymmetric phenotypic transitions. The likely common cause is robustness to genotypic change. We describe an intriguing tension between phenotypic complexity and evolvability that may have implications for biological evolution. On the one hand, genotypic change is more likely to yield novel phenotypes in more complex organisms. On the other hand, the total number of novel phenotypes reachable through genotypic change is highest for organisms with simple phenotypes. Artificial evolving systems can help us study aspects of biological evolvability that are not accessible in vastly more complex natural systems. They can also help identify properties, such as robustness, that are required for both human-designed artificial systems and synthetic biological systems to be evolvable.

The genotype-phenotype map of an evolving digital organism

PubMed Central

Zaman, Luis; Wagner, Andreas

2017-01-01

To understand how evolving systems bring forth novel and useful phenotypes, it is essential to understand the relationship between genotypic and phenotypic change. Artificial evolving systems can help us understand whether the genotype-phenotype maps of natural evolving systems are highly unusual, and it may help create evolvable artificial systems. Here we characterize the genotype-phenotype map of digital organisms in Avida, a platform for digital evolution. We consider digital organisms from a vast space of 10141 genotypes (instruction sequences), which can form 512 different phenotypes. These phenotypes are distinguished by different Boolean logic functions they can compute, as well as by the complexity of these functions. We observe several properties with parallels in natural systems, such as connected genotype networks and asymmetric phenotypic transitions. The likely common cause is robustness to genotypic change. We describe an intriguing tension between phenotypic complexity and evolvability that may have implications for biological evolution. On the one hand, genotypic change is more likely to yield novel phenotypes in more complex organisms. On the other hand, the total number of novel phenotypes reachable through genotypic change is highest for organisms with simple phenotypes. Artificial evolving systems can help us study aspects of biological evolvability that are not accessible in vastly more complex natural systems. They can also help identify properties, such as robustness, that are required for both human-designed artificial systems and synthetic biological systems to be evolvable. PMID:28241039

Switchable geometric frustration in an artificial-spin-ice-superconductor heterosystem.

PubMed

Wang, Yong-Lei; Ma, Xiaoyu; Xu, Jing; Xiao, Zhi-Li; Snezhko, Alexey; Divan, Ralu; Ocola, Leonidas E; Pearson, John E; Janko, Boldizsar; Kwok, Wai-Kwong

2018-06-11

Geometric frustration emerges when local interaction energies in an ordered lattice structure cannot be simultaneously minimized, resulting in a large number of degenerate states. The numerous degenerate configurations may lead to practical applications in microelectronics 1 , such as data storage, memory and logic 2 . However, it is difficult to achieve very high degeneracy, especially in a two-dimensional system 3,4 . Here, we showcase in situ controllable geometric frustration with high degeneracy in a two-dimensional flux-quantum system. We create this in a superconducting thin film placed underneath a reconfigurable artificial-spin-ice structure 5 . The tunable magnetic charges in the artificial-spin-ice strongly interact with the flux quanta in the superconductor, enabling switching between frustrated and crystallized flux quanta states. The different states have measurable effects on the superconducting critical current profile, which can be reconfigured by precise selection of the spin-ice magnetic state through the application of an external magnetic field. We demonstrate the applicability of these effects by realizing a reprogrammable flux quanta diode. The tailoring of the energy landscape of interacting 'particles' using artificial-spin-ices provides a new paradigm for the design of geometric frustration, which could illuminate a path to control new functionalities in other material systems, such as magnetic skyrmions 6 , electrons and holes in two-dimensional materials 7,8 , and topological insulators 9 , as well as colloids in soft materials 10-13 .

Fuzzy pharmacology: theory and applications.

PubMed

Sproule, Beth A; Naranjo, Claudio A; Türksen, I Burhan

2002-09-01

Fuzzy pharmacology is a term coined to represent the application of fuzzy logic and fuzzy set theory to pharmacological problems. Fuzzy logic is the science of reasoning, thinking and inference that recognizes and uses the real world phenomenon that everything is a matter of degree. It is an extension of binary logic that is able to deal with complex systems because it does not require crisp definitions and distinctions for the system components. In pharmacology, fuzzy modeling has been used for the mechanical control of drug delivery in surgical settings, and work has begun evaluating its use in other pharmacokinetic and pharmacodynamic applications. Fuzzy pharmacology is an emerging field that, based on these initial explorations, warrants further investigation.

Mixing Categories and Modal Logics in the Quantum Setting

NASA Astrophysics Data System (ADS)

Cinà, Giovanni

The study of the foundations of Quantum Mechanics, especially after the advent of Quantum Computation and Information, has benefited from the application of category-theoretic tools and modal logics to the analysis of Quantum processes: we witness a wealth of theoretical frameworks casted in either of the two languages. This paper explores the interplay of the two formalisms in the peculiar context of Quantum Theory. After a review of some influential abstract frameworks, we show how different modal logic frames can be extracted from the category of finite dimensional Hilbert spaces, connecting the Categorical Quantum Mechanics approach to some modal logics that have been proposed for Quantum Computing. We then apply a general version of the same technique to two other categorical frameworks, the `topos approach' of Doering and Isham and the sheaf-theoretic work on contextuality by Abramsky and Brandenburger, suggesting how some key features can be expressed with modal languages.

A novel method for the production of core-shell microparticles by inverse gelation optimized with artificial intelligent tools.

PubMed

Rodríguez-Dorado, Rosalia; Landín, Mariana; Altai, Ayça; Russo, Paola; Aquino, Rita P; Del Gaudio, Pasquale

2018-03-01

Numerous studies have been focused on hydrophobic compounds encapsulation as oils. In fact, oils can provide numerous health benefits as synergic ingredient combined with other hydrophobic active ingredients. However, stable microparticles for pharmaceutical purposes are difficult to achieve when commonly techniques are used. In this work, sunflower oil was encapsulated in calcium-alginate capsules by prilling technique in co-axial configuration. Core-shell beads were produced by inverse gelation directly at the nozzle using a w/o emulsion containing aqueous calcium chloride solution in sunflower oil pumped through the inner nozzle while an aqueous alginate solution, coming out from the annular nozzle, produced the beads shell. To optimize process parameters artificial intelligence tools were proposed to optimize the numerous prilling process variables. Homogeneous and spherical microcapsules with narrow size distribution and a thin alginate shell were obtained when the parameters as w/o constituents, polymer concentrations, flow rates and frequency of vibration were optimized by two commercial software, FormRules® and INForm®, which implement neurofuzzy logic and Artificial Neural Networks together with genetic algorithms, respectively. This technique constitutes an innovative approach for hydrophobic compounds microencapsulation. Copyright © 2018 Elsevier B.V. All rights reserved.

Low back pain: conservative treatment with artificial shock absorbers.

PubMed

Wosk, J; Voloshin, A S

1985-03-01

A new method of conservative treatment for low back pain (LBP) was studied by follow-up investigation of 382 patients during the last five years. The attempt to reduce repetitive impulsive intervertebral impact in the troublesome S1-L5-4 area by significant improvement of the foot's attenuational capacity through artificial viscoelastic shock absorbing was prompted by the authors' work on decreased capability of LBP spines to attenuate axially propagated walking stresses. Viscoelastic shoe inserts were used in addition to light flexible shoes as artificial shock absorbing devices. Maximal amplitudes of bone oscillation during walking were reduced by about 40% by the viscoelastic inserts. Rapid and surprisingly significant improvement of pain syndrome and patient mobility occurred in about 80% of the patients. The accelerographic patterns recorded on a sacrum of patient with LBP were unusual for a healthy subject; they usually disappeared after treatment in LBP cases. Results suggested that poor walking impact attenuation was a true cause for prolonging intervertebral structures overstrain and consequent degeneration. It seemed logical that as spine damage could be explained primarily by prolonged impulsive overstrain, treatment must include viscoelastic inserts which increase foot shock absorbing capacity and help cushion the spine.

Linking the Tao, biomathics and information through the logic of energy.

PubMed

Brenner, Joseph E

2017-12-01

The knowledge accumulated in West and East is incomplete in different ways. The mainstream Western approach has contributed the basis for modern science, but indications have appeared in the Western literature that something has been missing in it that Eastern thought could offer. This paper explores the similarities and differences between Eastern and Western approaches to knowledge and whether a trend exists toward their conjunction or convergence. I suggest that a process of conjunction of these different modes of exploration of what the concepts of 'Life and Mind' really entail, at the interface of philosophy and science, is taking place in the areas of information and biomathics. These conjunctions in China and in the West are characterized by scientific and philosophical systems which are holistic rather than reductionist. I argue that a non-standard, non-truth-functional logic of energy, based on the work of Stéphane Lupasco (1900-1988), provides a thread linking these approaches. Grounded in modern physics, it can describe the qualitative changes which are the focus of Chinese thought. In biology, Lupasco showed how the principles of this logic of dynamic relations operate in intra- and inter-cellular processes and at higher levels of organization. This paper supports key, primarily Chinese concepts and critiques the logical and categorial distinctions underlying and restricting the Western world-view. The paper also supports the implicit openness of Integral Biomathics to qualitative Eastern perspectives. Its finality is to find, from the conjunction, "better ideas for better exploration" of the nature of mind and life. This is not an academic exercise but a moral imperative for both Eastern and Western society. Copyright © 2017 Elsevier Ltd. All rights reserved.

Knowledge-Based Aircraft Automation: Managers Guide on the use of Artificial Intelligence for Aircraft Automation and Verification and Validation Approach for a Neural-Based Flight Controller

NASA Technical Reports Server (NTRS)

Broderick, Ron

1997-01-01

The ultimate goal of this report was to integrate the powerful tools of artificial intelligence into the traditional process of software development. To maintain the US aerospace competitive advantage, traditional aerospace and software engineers need to more easily incorporate the technology of artificial intelligence into the advanced aerospace systems being designed today. The future goal was to transition artificial intelligence from an emerging technology to a standard technology that is considered early in the life cycle process to develop state-of-the-art aircraft automation systems. This report addressed the future goal in two ways. First, it provided a matrix that identified typical aircraft automation applications conducive to various artificial intelligence methods. The purpose of this matrix was to provide top-level guidance to managers contemplating the possible use of artificial intelligence in the development of aircraft automation. Second, the report provided a methodology to formally evaluate neural networks as part of the traditional process of software development. The matrix was developed by organizing the discipline of artificial intelligence into the following six methods: logical, object representation-based, distributed, uncertainty management, temporal and neurocomputing. Next, a study of existing aircraft automation applications that have been conducive to artificial intelligence implementation resulted in the following five categories: pilot-vehicle interface, system status and diagnosis, situation assessment, automatic flight planning, and aircraft flight control. The resulting matrix provided management guidance to understand artificial intelligence as it applied to aircraft automation. The approach taken to develop a methodology to formally evaluate neural networks as part of the software engineering life cycle was to start with the existing software quality assurance standards and to change these standards to include neural network development. The changes were to include evaluation tools that can be applied to neural networks at each phase of the software engineering life cycle. The result was a formal evaluation approach to increase the product quality of systems that use neural networks for their implementation.

Seeing by touch: evaluation of a soft biologically-inspired artificial fingertip in real-time active touch.

PubMed

Assaf, Tareq; Roke, Calum; Rossiter, Jonathan; Pipe, Tony; Melhuish, Chris

2014-02-07

Effective tactile sensing for artificial platforms remains an open issue in robotics. This study investigates the performance of a soft biologically-inspired artificial fingertip in active exploration tasks. The fingertip sensor replicates the mechanisms within human skin and offers a robust solution that can be used both for tactile sensing and gripping/manipulating objects. The softness of the optical sensor's contact surface also allows safer interactions with objects. High-level tactile features such as edges are extrapolated from the sensor's output and the information is used to generate a tactile image. The work presented in this paper aims to investigate and evaluate this artificial fingertip for 2D shape reconstruction. The sensor was mounted on a robot arm to allow autonomous exploration of different objects. The sensor and a number of human participants were then tested for their abilities to track the raised perimeters of different planar objects and compared. By observing the technique and accuracy of the human subjects, simple but effective parameters were determined in order to evaluate the artificial system's performance. The results prove the capability of the sensor in such active exploration tasks, with a comparable performance to the human subjects despite it using tactile data alone whereas the human participants were also able to use proprioceptive cues.

Apple Fool! An Introduction to Artificial Flavors.

ERIC Educational Resources Information Center

Journal of Chemical Education, 2003

2003-01-01

Presents a science activity on consumer chemistry in which students explore artificial flavors that are commonly used in foods, such as isoamyl acetate and methyl salicylate. Includes instructor information and a student worksheet. (YDS)

SCB Quantum Computers Using iSWAP and 1-Qubit Rotations

NASA Technical Reports Server (NTRS)

Williams, Colin; Echtemach, Pierre

2005-01-01

Units of superconducting circuitry that exploit the concept of the single- Cooper-pair box (SCB) have been built and are undergoing testing as prototypes of logic gates that could, in principle, constitute building blocks of clocked quantum computers. These units utilize quantized charge states as the quantum information-bearing degrees of freedom. An SCB is an artificial two-level quantum system that comprises a nanoscale superconducting electrode connected to a reservoir of Cooper-pair charges via a Josephson junction. The logical quantum states of the device, .0. and .1., are implemented physically as a pair of charge-number states that differ by 2e (where e is the charge of an electron). Typically, some 109 Cooper pairs are involved. Transitions between the logical states are accomplished by tunneling of Cooper pairs through the Josephson junction. Although the two-level system contains a macroscopic number of charges, in the superconducting regime, they behave collectively, as a Bose-Einstein condensate, making possible a coherent superposition of the two logical states. This possibility makes the SCB a candidate for the physical implementation of a qubit. A set of quantum logic operations and the gates that implement them is characterized as universal if, in principle, one can form combinations of the operations in the set to implement any desired quantum computation. To be able to design a practical quantum computer, one must first specify how to decompose any valid quantum computation into a sequence of elementary 1- and 2-qubit quantum gates that are universal and that can be realized in hardware that is feasible to fabricate. Traditionally, the set of universal gates has been taken to be the set of all 1-qubit quantum gates in conjunction with the controlled-NOT (CNOT) gate, which is a 2-qubit gate. Also, it has been known for some time that the SWAP gate, which implements square root of the simple 2-qubit exchange interaction, is as computationally universal as is the CNOT operation.

The logic of relations and the logic of management.

PubMed

Buntinx, W

2008-07-01

Increasing emphasis on financial and administrative control processes is affecting service culture in support organisations for persons with intellectual disability. This phenomenon is currently obvious in Dutch service organisations that find themselves in transition towards more community care and at the same time under pressure from new administrative and funding managerial bureaucracy. As a result, the logic of management is becoming more dominant in direct support settings and risk to overshadow the logic of relationships between staff and clients. The article presents a reflection on this phenomenon, starting from a description of service team characteristics as found in the literature. Next, findings about direct support staff (DSS) continuity are summarised from four Dutch studies. Following up these findings, the concept of 'microsystems' is explored as a possible answer to the organisational challenges demonstrated in the studies. Team characteristics, especially team size and membership continuity for DSS, appear relevant factors for assuring supportive relationships and service quality in direct support teams. The structure of the primary support team shows to be of special interest. The organisational concept of 'microsystems' is explored with respect to transcending the present conflict between bureaucratic managerial pressure and the need for supportive relationships. Service organisations need to create structural conditions for the efficacy of direct support teams in terms of client relationships and relevant client outcomes. At the same time, the need for administrative and control processes can not be denied. The concept of 'microsystems', application of a Quality of Life framework and the use of new instruments, such as the Supports Intensity Scale, can contribute to an organisational solution for the present conflicting logic of relations and management.

Protein Logic: A Statistical Mechanical Study of Signal Integration at the Single-Molecule Level

PubMed Central

de Ronde, Wiet; Rein ten Wolde, Pieter; Mugler, Andrew

2012-01-01

Information processing and decision-making is based upon logic operations, which in cellular networks has been well characterized at the level of transcription. In recent years, however, both experimentalists and theorists have begun to appreciate that cellular decision-making can also be performed at the level of a single protein, giving rise to the notion of protein logic. Here we systematically explore protein logic using a well-known statistical mechanical model. As an example system, we focus on receptors that bind either one or two ligands, and their associated dimers. Notably, we find that a single heterodimer can realize any of the 16 possible logic gates, including the XOR gate, by variation of biochemical parameters. We then introduce what to our knowledge is a novel idea: that a set of receptors with fixed parameters can encode functionally unique logic gates simply by forming different dimeric combinations. An exhaustive search reveals that the simplest set of receptors (two single-ligand receptors and one double-ligand receptor) can realize several different groups of three unique gates, a result for which the parametric analysis of single receptors and dimers provides a clear interpretation. Both results underscore the surprising functional freedom readily available to cells at the single-protein level. PMID:23009860

Distinguishing between evidence and its explanations in the steering of atomic clocks

NASA Astrophysics Data System (ADS)

Myers, John M.; Hadi Madjid, F.

2014-11-01

Quantum theory reflects within itself a separation of evidence from explanations. This separation leads to a known proof that: (1) no wave function can be determined uniquely by evidence, and (2) any chosen wave function requires a guess reaching beyond logic to things unforeseeable. Chosen wave functions are encoded into computer-mediated feedback essential to atomic clocks, including clocks that step computers through their phases of computation and clocks in space vehicles that supply evidence of signal propagation explained by hypotheses of spacetimes with metric tensor fields. The propagation of logical symbols from one computer to another requires a shared rhythm-like a bucket brigade. Here we show how hypothesized metric tensors, dependent on guesswork, take part in the logical synchronization by which clocks are steered in rate and position toward aiming points that satisfy phase constraints, thereby linking the physics of signal propagation with the sharing of logical symbols among computers. Recognizing the dependence of the phasing of symbol arrivals on guesses about signal propagation transports logical synchronization from the engineering of digital communications to a discipline essential to physics. Within this discipline we begin to explore questions invisible under any concept of time that fails to acknowledge unforeseeable events. In particular, variation of spacetime curvature is shown to limit the bit rate of logical communication.

Spin wave nonreciprocity for logic device applications

NASA Astrophysics Data System (ADS)

Jamali, Mahdi; Kwon, Jae Hyun; Seo, Soo-Man; Lee, Kyung-Jin; Yang, Hyunsoo

2013-11-01

The utilization of spin waves as eigenmodes of the magnetization dynamics for information processing and communication has been widely explored recently due to its high operational speed with low power consumption and possible applications for quantum computations. Previous proposals of spin wave Mach-Zehnder devices were based on the spin wave phase, a delicate entity which can be easily disrupted. Here, we propose a complete logic system based on the spin wave amplitude utilizing the nonreciprocal spin wave behavior excited by microstrip antennas. The experimental data reveal that the nonreciprocity of magnetostatic surface spin wave can be tuned by the bias magnetic field. Furthermore, engineering of the device structure could result in a high nonreciprocity factor for spin wave logic applications.

Exploration of picture grammars, grammar learning, and inductive logic programming for image understanding

NASA Astrophysics Data System (ADS)

Ducksbury, P. G.; Kennedy, C.; Lock, Z.

2003-09-01

Grammars have been used for the formal specification of programming languages, and there are a number of commercial products which now use grammars. However, these have tended to be focused mainly on flow control type applications. In this paper, we consider the potential use of picture grammars and inductive logic programming in generic image understanding applications, such as object recognition. A number of issues are considered, such as what type of grammar needs to be used, how to construct the grammar with its associated attributes, difficulties encountered with parsing grammars followed by issues of automatically learning grammars using a genetic algorithm. The concept of inductive logic programming is then introduced as a method that can overcome some of the earlier difficulties.

Spin wave nonreciprocity for logic device applications

PubMed Central

Jamali, Mahdi; Kwon, Jae Hyun; Seo, Soo-Man; Lee, Kyung-Jin; Yang, Hyunsoo

2013-01-01

The utilization of spin waves as eigenmodes of the magnetization dynamics for information processing and communication has been widely explored recently due to its high operational speed with low power consumption and possible applications for quantum computations. Previous proposals of spin wave Mach-Zehnder devices were based on the spin wave phase, a delicate entity which can be easily disrupted. Here, we propose a complete logic system based on the spin wave amplitude utilizing the nonreciprocal spin wave behavior excited by microstrip antennas. The experimental data reveal that the nonreciprocity of magnetostatic surface spin wave can be tuned by the bias magnetic field. Furthermore, engineering of the device structure could result in a high nonreciprocity factor for spin wave logic applications. PMID:24196318

Organisational Structure and Information Technology (IT): Exploring the Implications of IT for Future Military Structures

DTIC Science & Technology

2006-07-01

4 Abbreviations AI Artificial Intelligence AM Artificial Memory CAD Computer Aided...memory (AM), artificial intelligence (AI), and embedded knowledge systems it is possible to expand the “effective span of competence” of...Technology J Joint J2 Joint Intelligence J3 Joint Operations NATO North Atlantic Treaty Organisation NCW Network Centric Warfare NHS National Health

Methodology for the specification of communication activities within the framework of a multi-layered architecture: Toward the definition of a knowledge base

NASA Astrophysics Data System (ADS)

Amyay, Omar

A method defined in terms of synthesis and verification steps is presented. The specification of the services and protocols of communication within a multilayered architecture of the Open Systems Interconnection (OSI) type is an essential issue for the design of computer networks. The aim is to obtain an operational specification of the protocol service couple of a given layer. Planning synthesis and verification steps constitute a specification trajectory. The latter is based on the progressive integration of the 'initial data' constraints and verification of the specification originating from each synthesis step, through validity constraints that characterize an admissible solution. Two types of trajectories are proposed according to the style of the initial specification of the service protocol couple: operational type and service supplier viewpoint; knowledge property oriented type and service viewpoint. Synthesis and verification activities were developed and formalized in terms of labeled transition systems, temporal logic and epistemic logic. The originality of the second specification trajectory and the use of the epistemic logic are shown. An 'artificial intelligence' approach enables a conceptual model to be defined for a knowledge base system for implementing the method proposed. It is structured in three levels of representation of the knowledge relating to the domain, the reasoning characterizing synthesis and verification activities and the planning of the steps of a specification trajectory.

Exploring the Use of a Facebook Page in Anatomy Education

ERIC Educational Resources Information Center

Jaffar, Akram Abood

2014-01-01

Facebook is the most popular social media site visited by university students on a daily basis. Consequently, Facebook is the logical place to start with for integrating social media technologies into education. This study explores how a faculty-administered Facebook Page can be used to supplement anatomy education beyond the traditional…

Belief, Doubt and Reason: C. S. Peirce on Education

ERIC Educational Resources Information Center

Cunningham, Donald J.; Schreiber, James B.; Moss, Connie M.

2005-01-01

In this paper, we explore Peirce's work for insights into a theory of learning and cognition for education. Our focus for this exploration is Peirce's paper The "Fixation of Belief" (FOB), originally published in 1877 in "Popular Science Monthly". We begin by examining Peirce's assertion that the study of logic is essential for understanding…

Unsayable Somethings: Modern American Poetry, Language, and the Logic of Experience

ERIC Educational Resources Information Center

McWhorter, Ellen

2009-01-01

By exploring the categorical similarities between popular models of science, political economy, psychology, and sexuality, this dissertation addresses modern U.S. poetry's obsession with conjuring the unsayable. Chapters 1 and 2 explore the social and conceptual landscape that came to align the sayable with the cognitive and credible, while…

Qualitative Research in Career Development: Exploring the Center and Margins of Discourse About Careers and Working

ERIC Educational Resources Information Center

Blustein, David L.; Kenna, Alexandra C.; Murphy, Kerri A.; DeVoy, Julia E.; DeWine, David B.

2005-01-01

This article explores the contributions of qualitative research to the study of career development and the psychology of working. Epistemological perspectives (logical positivism, postpositivism, and social constructionism) are discussed as they relate to historical context, career theories, and the various methods used within qualitative…

Propulsion Health Management System Development for Affordable and Reliable Operation of Space Exploration Systems

NASA Technical Reports Server (NTRS)

Melcher, Kevin J.; Maul, William A.; Garg, Sanjay

2007-01-01

The constraints of future Exploration Missions will require unique integrated system health management capabilities throughout the mission. An ambitious launch schedule, human-rating requirements, long quiescent periods, limited human access for repair or replacement, and long communication delays, all require an integrated approach to health management that can span distinct, yet interdependent vehicle subsystems, anticipate failure states, provide autonomous remediation and support the Exploration Mission from beginning to end. Propulsion is a critical part of any space exploration mission, and monitoring the health of the propulsion system is an integral part of assuring mission safety and success. Health management is a somewhat ubiquitous technology that encompasses a large spectrum of physical components and logical processes. For this reason, it is essential to develop a systematic plan for propulsion health management system development. This paper provides a high-level perspective of propulsion health management systems, and describes a logical approach for the future planning and early development that are crucial to planned space exploration programs. It also presents an overall approach, or roadmap, for propulsion health management system development and a discussion of the associated roadblocks and challenges.

The Use of CK-LOG Formalism for Knowledge Representation and Problem Solving in OPPLAN-CONSULTANT: An Expert System for Naval Operational Planning.

DTIC Science & Technology

1985-09-30

further discussed in Sections 4 and 5. "=:.’. 1 ":210 NRL REPORT 8902 Notice that I have used the plural form, OBJECTS, in Fig. 2.1 to indicate that there...Washington, DC. Artificial Intelligence Center, SRI International , Menlo Park, CA, 1978. i 8. G. Gentzen, "Investigations into Logical Deduction," The...one of the form ( relatio -sm term-i term-Z) or (tuple-name term-I ... term-a) with or without the negation operator oT, and atm-exp denotes a timed

Developing a multimodal biometric authentication system using soft computing methods.

PubMed

Malcangi, Mario

2015-01-01

Robust personal authentication is becoming ever more important in computer-based applications. Among a variety of methods, biometric offers several advantages, mainly in embedded system applications. Hard and soft multi-biometric, combined with hard and soft computing methods, can be applied to improve the personal authentication process and to generalize the applicability. This chapter describes the embedded implementation of a multi-biometric (voiceprint and fingerprint) multimodal identification system based on hard computing methods (DSP) for feature extraction and matching, an artificial neural network (ANN) for soft feature pattern matching, and a fuzzy logic engine (FLE) for data fusion and decision.

Knowledge engineering in volcanology: Practical claims and general approach

NASA Astrophysics Data System (ADS)

Pshenichny, Cyril A.

2014-10-01

Knowledge engineering, being a branch of artificial intelligence, offers a variety of methods for elicitation and structuring of knowledge in a given domain. Only a few of them (ontologies and semantic nets, event/probability trees, Bayesian belief networks and event bushes) are known to volcanologists. Meanwhile, the tasks faced by volcanology and the solutions found so far favor a much wider application of knowledge engineering, especially tools for handling dynamic knowledge. This raises some fundamental logical and mathematical problems and requires an organizational effort, but may strongly improve panel discussions, enhance decision support, optimize physical modeling and support scientific collaboration.

Inorganic proton conducting electrolyte coupled oxide-based dendritic transistors for synaptic electronics.

PubMed

Wan, Chang Jin; Zhu, Li Qiang; Zhou, Ju Mei; Shi, Yi; Wan, Qing

2014-05-07

Ionic/electronic hybrid devices with synaptic functions are considered to be the essential building blocks for neuromorphic systems and brain-inspired computing. Here, artificial synapses based on indium-zinc-oxide (IZO) transistors gated by nanogranular SiO2 proton-conducting electrolyte films are fabricated on glass substrates. Spike-timing dependent plasticity and paired-pulse facilitation are successfully mimicked in an individual bottom-gate transistor. Most importantly, dynamic logic and dendritic integration established by spatiotemporally correlated spikes are also mimicked in dendritic transistors with two in-plane gates as the presynaptic input terminals.

Real coded genetic algorithm for fuzzy time series prediction

NASA Astrophysics Data System (ADS)

Jain, Shilpa; Bisht, Dinesh C. S.; Singh, Phool; Mathpal, Prakash C.

2017-10-01

Genetic Algorithm (GA) forms a subset of evolutionary computing, rapidly growing area of Artificial Intelligence (A.I.). Some variants of GA are binary GA, real GA, messy GA, micro GA, saw tooth GA, differential evolution GA. This research article presents a real coded GA for predicting enrollments of University of Alabama. Data of Alabama University is a fuzzy time series. Here, fuzzy logic is used to predict enrollments of Alabama University and genetic algorithm optimizes fuzzy intervals. Results are compared to other eminent author works and found satisfactory, and states that real coded GA are fast and accurate.

Testing the applicability of artificial intelligence techniques to the subject of erythemal ultraviolet solar radiation part one: the applicability of a fuzzy rule based approach.

PubMed

Riad, A M; Elminir, Hamdy K; Own, Hala S; Azzam, Yosry A

2008-02-27

This work presents the applicability of applying a fuzzy logic approach to the calculation of noontime erythemal UV irradiance for the plain areas of Egypt. When different combinations of data sets were examined from the test performance point of view, it was found that 91% of the whole series was estimated within a deviation of less than +/-10 mW/m(2), and 9% of these deviations lay within the range of +/-15 mW/m(2) to +/-25 mW/m(2).

A brief history and technical review of the expert system research

NASA Astrophysics Data System (ADS)

Tan, Haocheng

2017-09-01

The expert system is a computer system that emulates the decision-making ability of a human expert, which aims to solve complex problems by reasoning knowledge. It is an important branch of artificial intelligence. In this paper, firstly, we briefly introduce the development and basic structure of the expert system. Then, from the perspective of the enabling technology, we classify the current expert systems and elaborate four expert systems: The Rule-Based Expert System, the Framework-Based Expert System, the Fuzzy Logic-Based Expert System and the Expert System Based on Neural Network.

Evaluation of automated decisionmaking methodologies and development of an integrated robotic system simulation. Volume 1: Study results

NASA Technical Reports Server (NTRS)

Lowrie, J. W.; Fermelia, A. J.; Haley, D. C.; Gremban, K. D.; Vanbaalen, J.; Walsh, R. W.

1982-01-01

A variety of artificial intelligence techniques which could be used with regard to NASA space applications and robotics were evaluated. The techniques studied were decision tree manipulators, problem solvers, rule based systems, logic programming languages, representation language languages, and expert systems. The overall structure of a robotic simulation tool was defined and a framework for that tool developed. Nonlinear and linearized dynamics equations were formulated for n link manipulator configurations. A framework for the robotic simulation was established which uses validated manipulator component models connected according to a user defined configuration.

Challenges And Results of the Applications of Fuzzy Logic in the Classification of Rich Galaxy Clusters

NASA Astrophysics Data System (ADS)

Santiago Girola Schneider, Rafael

2015-08-01

The fuzzy logic is a branch of the artificial intelligence founded on the concept that 'everything is a matter of degree.' It intends to create mathematical approximations on the resolution of certain types of problems. In addition, it aims to produce exact results obtained from imprecise data, for which it is particularly useful for electronic and computer applications. This enables it to handle vague or unspecific information when certain parts of a system are unknown or ambiguous and, therefore, they cannot be measured in a reliable manner. Also, when the variation of a variable can produce an alteration on the others.The main focus of this paper is to prove the importance of these techniques formulated from a theoretical analysis on its application on ambiguous situations in the field of the rich clusters of galaxies. The purpose is to show its applicability in the several classification systems proposed for the rich clusters, which are based on criteria such as the level of richness of the cluster, the distribution of the brightest galaxies, whether there are signs of type-cD galaxies or not or the existence of sub-clusters.Fuzzy logic enables the researcher to work with “imprecise” information implementing fuzzy sets and combining rules to define actions. The control systems based on fuzzy logic join input variables that are defined in terms of fuzzy sets through rule groups that produce one or several output values of the system under study. From this context, the application of the fuzzy logic’s techniques approximates the solution of the mathematical models in abstractions about the rich galaxy cluster classification of physical properties in order to solve the obscurities that must be confronted by an investigation group in order to make a decision.

SOM guided fuzzy logic prospectivity model for gold in the Häme Belt, southwestern Finland

NASA Astrophysics Data System (ADS)

Leväniemi, Hanna; Hulkki, Helena; Tiainen, Markku

2017-04-01

This study investigated gold prospectivity in the Paleoproterozoic Häme Belt, located in southwestern Finland. The Häme Belt comprises calc-alkaline and tholeitic volcanic rocks, migmatites, granitoids, and mafic to ultramafic intrusions. Mineral exploration in the region has resulted in the discovery of several gold occurrences during recent decades; however, no prospectivity modeling for gold has yet been conducted. This study integrated till geochemical and geophysical data to examine and extract data characteristics critical for gold occurrences. Modeling was guided by self-organizing map (SOM) analysis to define essential data associations and to aid in model input data selection and generation. The final fuzzy logic prospectivity model map yielded high predictability values for most known Au or Cu-Au occurrences, but also highlighted new targets for exploration.

On the Need for Artificial Intelligence and Advanced Test and Evaluation Methods for Space Exploration

NASA Astrophysics Data System (ADS)

Scheidt, D. H.; Hibbitts, C. A.; Chen, M. H.; Paxton, L. J.; Bekker, D. L.

2017-02-01

Implementing mature artificial intelligence would create the ability to significantly increase the science return from a mission, while potentially saving costs in mission and instrument operations, and solving currently intractable problems.

Exploring Agricultural Drainage's Influence on Wetland and Watershed Connectivity

EPA Science Inventory

Artificial agricultural drainage (i.e. surface ditches or subsurface tile) is an important agricultural management tool. Artificial drainage allows for timely fieldwork and adequate root aeration, resulting in greater crop yields for farmers. This practice is widespread throughou...

A fuzzy classifier system for process control

NASA Technical Reports Server (NTRS)

Karr, C. L.; Phillips, J. C.

1994-01-01

A fuzzy classifier system that discovers rules for controlling a mathematical model of a pH titration system was developed by researchers at the U.S. Bureau of Mines (USBM). Fuzzy classifier systems successfully combine the strengths of learning classifier systems and fuzzy logic controllers. Learning classifier systems resemble familiar production rule-based systems, but they represent their IF-THEN rules by strings of characters rather than in the traditional linguistic terms. Fuzzy logic is a tool that allows for the incorporation of abstract concepts into rule based-systems, thereby allowing the rules to resemble the familiar 'rules-of-thumb' commonly used by humans when solving difficult process control and reasoning problems. Like learning classifier systems, fuzzy classifier systems employ a genetic algorithm to explore and sample new rules for manipulating the problem environment. Like fuzzy logic controllers, fuzzy classifier systems encapsulate knowledge in the form of production rules. The results presented in this paper demonstrate the ability of fuzzy classifier systems to generate a fuzzy logic-based process control system.

Phosphorene/rhenium disulfide heterojunction-based negative differential resistance device for multi-valued logic

NASA Astrophysics Data System (ADS)

Shim, Jaewoo; Oh, Seyong; Kang, Dong-Ho; Jo, Seo-Hyeon; Ali, Muhammad Hasnain; Choi, Woo-Young; Heo, Keun; Jeon, Jaeho; Lee, Sungjoo; Kim, Minwoo; Song, Young Jae; Park, Jin-Hong

2016-11-01

Recently, negative differential resistance devices have attracted considerable attention due to their folded current-voltage characteristic, which presents multiple threshold voltage values. Because of this remarkable property, studies associated with the negative differential resistance devices have been explored for realizing multi-valued logic applications. Here we demonstrate a negative differential resistance device based on a phosphorene/rhenium disulfide (BP/ReS2) heterojunction that is formed by type-III broken-gap band alignment, showing high peak-to-valley current ratio values of 4.2 and 6.9 at room temperature and 180 K, respectively. Also, the carrier transport mechanism of the BP/ReS2 negative differential resistance device is investigated in detail by analysing the tunnelling and diffusion currents at various temperatures with the proposed analytic negative differential resistance device model. Finally, we demonstrate a ternary inverter as a multi-valued logic application. This study of a two-dimensional material heterojunction is a step forward toward future multi-valued logic device research.

Phosphorene/rhenium disulfide heterojunction-based negative differential resistance device for multi-valued logic

PubMed Central

Shim, Jaewoo; Oh, Seyong; Kang, Dong-Ho; Jo, Seo-Hyeon; Ali, Muhammad Hasnain; Choi, Woo-Young; Heo, Keun; Jeon, Jaeho; Lee, Sungjoo; Kim, Minwoo; Song, Young Jae; Park, Jin-Hong

2016-01-01

Recently, negative differential resistance devices have attracted considerable attention due to their folded current–voltage characteristic, which presents multiple threshold voltage values. Because of this remarkable property, studies associated with the negative differential resistance devices have been explored for realizing multi-valued logic applications. Here we demonstrate a negative differential resistance device based on a phosphorene/rhenium disulfide (BP/ReS2) heterojunction that is formed by type-III broken-gap band alignment, showing high peak-to-valley current ratio values of 4.2 and 6.9 at room temperature and 180 K, respectively. Also, the carrier transport mechanism of the BP/ReS2 negative differential resistance device is investigated in detail by analysing the tunnelling and diffusion currents at various temperatures with the proposed analytic negative differential resistance device model. Finally, we demonstrate a ternary inverter as a multi-valued logic application. This study of a two-dimensional material heterojunction is a step forward toward future multi-valued logic device research. PMID:27819264

Bayesian Model Averaging of Artificial Intelligence Models for Hydraulic Conductivity Estimation

NASA Astrophysics Data System (ADS)

Nadiri, A.; Chitsazan, N.; Tsai, F. T.; Asghari Moghaddam, A.

2012-12-01

This research presents a Bayesian artificial intelligence model averaging (BAIMA) method that incorporates multiple artificial intelligence (AI) models to estimate hydraulic conductivity and evaluate estimation uncertainties. Uncertainty in the AI model outputs stems from error in model input as well as non-uniqueness in selecting different AI methods. Using one single AI model tends to bias the estimation and underestimate uncertainty. BAIMA employs Bayesian model averaging (BMA) technique to address the issue of using one single AI model for estimation. BAIMA estimates hydraulic conductivity by averaging the outputs of AI models according to their model weights. In this study, the model weights were determined using the Bayesian information criterion (BIC) that follows the parsimony principle. BAIMA calculates the within-model variances to account for uncertainty propagation from input data to AI model output. Between-model variances are evaluated to account for uncertainty due to model non-uniqueness. We employed Takagi-Sugeno fuzzy logic (TS-FL), artificial neural network (ANN) and neurofuzzy (NF) to estimate hydraulic conductivity for the Tasuj plain aquifer, Iran. BAIMA combined three AI models and produced better fitting than individual models. While NF was expected to be the best AI model owing to its utilization of both TS-FL and ANN models, the NF model is nearly discarded by the parsimony principle. The TS-FL model and the ANN model showed equal importance although their hydraulic conductivity estimates were quite different. This resulted in significant between-model variances that are normally ignored by using one AI model.

Log-linear model based behavior selection method for artificial fish swarm algorithm.

PubMed

Huang, Zhehuang; Chen, Yidong

2015-01-01

Artificial fish swarm algorithm (AFSA) is a population based optimization technique inspired by social behavior of fishes. In past several years, AFSA has been successfully applied in many research and application areas. The behavior of fishes has a crucial impact on the performance of AFSA, such as global exploration ability and convergence speed. How to construct and select behaviors of fishes are an important task. To solve these problems, an improved artificial fish swarm algorithm based on log-linear model is proposed and implemented in this paper. There are three main works. Firstly, we proposed a new behavior selection algorithm based on log-linear model which can enhance decision making ability of behavior selection. Secondly, adaptive movement behavior based on adaptive weight is presented, which can dynamically adjust according to the diversity of fishes. Finally, some new behaviors are defined and introduced into artificial fish swarm algorithm at the first time to improve global optimization capability. The experiments on high dimensional function optimization showed that the improved algorithm has more powerful global exploration ability and reasonable convergence speed compared with the standard artificial fish swarm algorithm.

Rewritable ferroelectric vortex pairs in BiFeO3

NASA Astrophysics Data System (ADS)

Li, Yang; Jin, Yaming; Lu, Xiaomei; Yang, Jan-Chi; Chu, Ying-Hao; Huang, Fengzhen; Zhu, Jinsong; Cheong, Sang-Wook

2017-08-01

Ferroelectric vortex in multiferroic materials has been considered as a promising alternative to current memory cells for the merit of high storage density. However, the formation of regular natural ferroelectric vortex is difficult, restricting the achievement of vortex memory device. Here, we demonstrated the creation of ferroelectric vortex-antivortex pairs in BiFeO3 thin films by using local electric field. The evolution of the polar vortex structure is studied by piezoresponse force microscopy at nanoscale. The results reveal that the patterns and stability of vortex structures are sensitive to the poling position. Consecutive writing and erasing processes cause no influence on the original domain configuration. The Z4 proper coloring vortex-antivortex network is then analyzed by graph theory, which verifies the rationality of artificial vortex-antivortex pairs. This study paves a foundation for artificial regulation of vortex, which provides a possible pathway for the design and realization of non-volatile vortex memory devices and logical devices.

Relationship between isoseismal area and magnitude of historical earthquakes in Greece by a hybrid fuzzy neural network method

NASA Astrophysics Data System (ADS)

Tselentis, G.-A.; Sokos, E.

2012-01-01

In this paper we suggest the use of diffusion-neural-networks, (neural networks with intrinsic fuzzy logic abilities) to assess the relationship between isoseismal area and earthquake magnitude for the region of Greece. It is of particular importance to study historical earthquakes for which we often have macroseismic information in the form of isoseisms but it is statistically incomplete to assess magnitudes from an isoseismal area or to train conventional artificial neural networks for magnitude estimation. Fuzzy relationships are developed and used to train a feed forward neural network with a back propagation algorithm to obtain the final relationships. Seismic intensity data from 24 earthquakes in Greece have been used. Special attention is being paid to the incompleteness and contradictory patterns in scanty historical earthquake records. The results show that the proposed processing model is very effective, better than applying classical artificial neural networks since the magnitude macroseismic intensity target function has a strong nonlinearity and in most cases the macroseismic datasets are very small.

Size exclusion chromatography for analyses of fibroin in silk: optimization of sampling and separation conditions

NASA Astrophysics Data System (ADS)

Pawcenis, Dominika; Koperska, Monika A.; Milczarek, Jakub M.; Łojewski, Tomasz; Łojewska, Joanna

2014-02-01

A direct goal of this paper was to improve the methods of sample preparation and separation for analyses of fibroin polypeptide with the use of size exclusion chromatography (SEC). The motivation for the study arises from our interest in natural polymers included in historic textile and paper artifacts, and is a logical response to the urgent need for developing rationale-based methods for materials conservation. The first step is to develop a reliable analytical tool which would give insight into fibroin structure and its changes caused by both natural and artificial ageing. To investigate the influence of preparation conditions, two sets of artificially aged samples were prepared (with and without NaCl in sample solution) and measured by the means of SEC with multi angle laser light scattering detector. It was shown that dialysis of fibroin dissolved in LiBr solution allows removal of the salt which destroys stacks chromatographic columns and prevents reproducible analyses. Salt rich (NaCl) water solutions of fibroin improved the quality of chromatograms.

The Bright, Artificial Intelligence-Augmented Future of Neuroimaging Reading.

PubMed

Hainc, Nicolin; Federau, Christian; Stieltjes, Bram; Blatow, Maria; Bink, Andrea; Stippich, Christoph

2017-01-01

Radiologists are among the first physicians to be directly affected by advances in computer technology. Computers are already capable of analyzing medical imaging data, and with decades worth of digital information available for training, will an artificial intelligence (AI) one day signal the end of the human radiologist? With the ever increasing work load combined with the looming doctor shortage, radiologists will be pushed far beyond their current estimated 3 s allotted time-of-analysis per image; an AI with super-human capabilities might seem like a logical replacement. We feel, however, that AI will lead to an augmentation rather than a replacement of the radiologist. The AI will be relied upon to handle the tedious, time-consuming tasks of detecting and segmenting outliers while possibly generating new, unanticipated results that can then be used as sources of medical discovery. This will affect not only radiologists but all physicians and also researchers dealing with medical imaging. Therefore, we must embrace future technology and collaborate interdisciplinary to spearhead the next revolution in medicine.

Artificial Intelligence Tools for Scaling Up of High Shear Wet Granulation Process.

PubMed

Landin, Mariana

2017-01-01

The results presented in this article demonstrate the potential of artificial intelligence tools for predicting the endpoint of the granulation process in high-speed mixer granulators of different scales from 25L to 600L. The combination of neurofuzzy logic and gene expression programing technologies allowed the modeling of the impeller power as a function of operation conditions and wet granule properties, establishing the critical variables that affect the response and obtaining a unique experimental polynomial equation (transparent model) of high predictability (R 2 > 86.78%) for all size equipment. Gene expression programing allowed the modeling of the granulation process for granulators of similar and dissimilar geometries and can be improved by implementing additional characteristics of the process, as composition variables or operation parameters (e.g., batch size, chopper speed). The principles and the methodology proposed here can be applied to understand and control manufacturing process, using any other granulation equipment, including continuous granulation processes. Copyright © 2016 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

Application of Artificial Neuro-Fuzzy Logic Inference System for Predicting the Microbiological Pollution in Fresh Water

NASA Astrophysics Data System (ADS)

Bouharati, S.; Benmahammed, K.; Harzallah, D.; El-Assaf, Y. M.

The classical methods for detecting the micro biological pollution in water are based on the detection of the coliform bacteria which indicators of contamination. But to check each water supply for these contaminants would be a time-consuming job and a qualify operators. In this study, we propose a novel intelligent system which provides a detection of microbiological pollution in fresh water. The proposed system is a hierarchical integration of an Artificial Neuro-Fuzzy Inference System (ANFIS). This method is based on the variations of the physical and chemical parameters occurred during bacteria growth. The instantaneous result obtained by the measurements of the variations of the physical and chemical parameters occurred during bacteria growth-temperature, pH, electrical potential and electrical conductivity of many varieties of water (surface water, well water, drinking water and used water) on the number Escherichia coli in water. The instantaneous result obtained by measurements of the inputs parameters of water from sensors.

Designing Hysteresis with Dipolar Chains

NASA Astrophysics Data System (ADS)

Concha, Andrés; Aguayo, David; Mellado, Paula

2018-04-01

Materials that have hysteretic response to an external field are essential in modern information storage and processing technologies. A myriad of magnetization curves of several natural and artificial materials have previously been measured and each has found a particular mechanism that accounts for it. However, a phenomenological model that captures all the hysteresis loops and at the same time provides a simple way to design the magnetic response of a material while remaining minimal is missing. Here, we propose and experimentally demonstrate an elementary method to engineer hysteresis loops in metamaterials built out of dipolar chains. We show that by tuning the interactions of the system and its geometry we can shape the hysteresis loop which allows for the design of the softness of a magnetic material at will. Additionally, this mechanism allows for the control of the number of loops aimed to realize multiple-valued logic technologies. Our findings pave the way for the rational design of hysteretical responses in a variety of physical systems such as dipolar cold atoms, ferroelectrics, or artificial magnetic lattices, among others.

Design of Power System Architectures for Small Spacecraft Systems

NASA Technical Reports Server (NTRS)

Momoh, James A.; Subramonian, Rama; Dias, Lakshman G.

1996-01-01

The objective of this research is to perform a trade study on several candidate power system architectures for small spacecrafts to be used in NASA's new millennium program. Three initial candidate architectures have been proposed by NASA and two other candidate architectures have been proposed by Howard University. Howard University is currently conducting the necessary analysis, synthesis, and simulation needed to perform the trade studies and arrive at the optimal power system architecture. Statistical, sensitivity and tolerant studies has been performed on the systems. It is concluded from present studies that certain components such as the series regulators, buck-boost converters and power converters can be minimized while retaining the desired functionality of the overall architecture. This in conjunction with battery scalability studies and system efficiency studies have enabled us to develop more economic architectures. Future studies will include artificial neural networks and fuzzy logic to analyze the performance of the systems. Fault simulation studies and fault diagnosis studies using EMTP and artificial neural networks will also be conducted.

Designing Hysteresis with Dipolar Chains.

PubMed

Concha, Andrés; Aguayo, David; Mellado, Paula

2018-04-13

Materials that have hysteretic response to an external field are essential in modern information storage and processing technologies. A myriad of magnetization curves of several natural and artificial materials have previously been measured and each has found a particular mechanism that accounts for it. However, a phenomenological model that captures all the hysteresis loops and at the same time provides a simple way to design the magnetic response of a material while remaining minimal is missing. Here, we propose and experimentally demonstrate an elementary method to engineer hysteresis loops in metamaterials built out of dipolar chains. We show that by tuning the interactions of the system and its geometry we can shape the hysteresis loop which allows for the design of the softness of a magnetic material at will. Additionally, this mechanism allows for the control of the number of loops aimed to realize multiple-valued logic technologies. Our findings pave the way for the rational design of hysteretical responses in a variety of physical systems such as dipolar cold atoms, ferroelectrics, or artificial magnetic lattices, among others.

Application of Artificial Intelligence (AI) Programming Techniques to Tactical Guidance for Fighter Aircraft

NASA Technical Reports Server (NTRS)

McManus, John W.; Goodrich, Kenneth H.

1989-01-01

A research program investigating the use of Artificial Intelligence (AI) techniques to aid in the development of a Tactical Decision Generator (TDG) for Within-Visual-Range (WVR) air combat engagements is discussed. The application of AI methods for development and implementation of the TDG is presented. The history of the Adaptive Maneuvering Logic (AML) program is traced and current versions of the AML program are compared and contrasted with the TDG system. The Knowledge-Based Systems (KBS) used by the TDG to aid in the decision-making process are outlined in detail and example rules are presented. The results of tests to evaluate the performance of the TDG versus a version of AML and versus human pilots in the Langley Differential Maneuvering Simulator (DMS) are presented. To date, these results have shown significant performance gains in one-versus-one air combat engagements, and the AI-based TDG software has proven to be much easier to modify than the updated FORTRAN AML programs.

Adaptive control of artificial pancreas systems - a review.

PubMed

Turksoy, Kamuran; Cinar, Ali

2014-01-01

Artificial pancreas (AP) systems offer an important improvement in regulating blood glucose concentration for patients with type 1 diabetes, compared to current approaches. AP consists of sensors, control algorithms and an insulin pump. Different AP control algorithms such as proportional-integral-derivative, model-predictive control, adaptive control, and fuzzy logic control have been investigated in simulation and clinical studies in the past three decades. The variability over time and complexity of the dynamics of blood glucose concentration, unsteady disturbances such as meals, time-varying delays on measurements and insulin infusion, and noisy data from sensors create a challenging system to AP. Adaptive control is a powerful control technique that can deal with such challenges. In this paper, a review of adaptive control techniques for blood glucose regulation with an AP system is presented. The investigations and advances in technology produced impressive results, but there is still a need for a reliable AP system that is both commercially viable and appealing to patients with type 1 diabetes.

Some practical approaches to a course on paraconsistent logic for engineers

NASA Astrophysics Data System (ADS)

Lambert-Torres, Germano; de Moraes, Carlos Henrique Valerio; Coutinho, Maurilio Pereira; Martins, Helga Gonzaga; Borges da Silva, Luiz Eduardo

2017-11-01

This paper describes a non-classical logic course primarily indicated for graduate students in electrical engineering and energy engineering. The content of this course is based on the vision that it is not enough for a student to indefinitely accumulate knowledge; it is necessary to explore all the occasions to update, deepen, and enrich that knowledge, adapting it to a complex world. Therefore, this course is not tied to theoretical formalities and tries at each moment to provide a practical view of the non-classical logic. In the real world, the inconsistencies are important and cannot be ignored because contradictory information brings relevant facts, sometimes modifying the entire result of the analysis. As consequence, the non-classical logics, such as annotated paraconsistent logic - APL, are efficiently framed in the approach of complex situations of the real world. In APL, the concepts of unknown, partial, ambiguous, and inconsistent knowledge are referred not to trivialise any system in analysis. This course presents theoretical and applicable aspects of APL, which are successfully used in decision-making structures. The course is divided into modules: Basic, 2vAPL, 3vAPL, 4vAPL, and Final Project.

Exploring creative activity: a software environment for multimedia systems

NASA Astrophysics Data System (ADS)

Farrett, Peter W.; Jardine, David A.

1992-03-01

This paper examines various issues related to the theory, design, and implementation of a system that supports creative activity for a multimedia environment. The system incorporates artificial intelligence notions to acquire concepts of the problem domain. This paper investigates this environment by considering a model that is a basis for a system, which supports a history of user interaction. A multimedia system that supports creative activity is problematic. It must function as a tool allowing users to experiment dynamically with their own creative reasoning process--a very nebulous task environment. It should also support the acquisition of domain knowledge so that empirical observation can be further evaluated. This paper aims to illustrate that via the reuse of domain-specific knowledge, closely related ideas can be quickly developed. This approach is useful in the following sense: Multimedia navigational systems hardcode referential links with respect to a web or network. Although users can access or control navigation in a nonlinear (static) manner, these referential links are 'frozen' and can not capture their creative actions, which are essential in tutoring or learning applications. This paper describes a multimedia assistant based on the notion of knowledge- links, which allows users to navigate through creative information in a nonlinear (dynamic) fashion. A selection of prototype code based on object-oriented techniques and logic programming partially demonstrates this.

Argumentation and evidence.

PubMed

Upshur, R E G; Colak, Errol

2003-01-01

This essay explores the role of informal logic and its application in the context of current debates regarding evidence-based medicine. This aim is achieved through a discussion of the goals and objectives of evidence-based medicine and a review of the criticisms raised against evidence-based medicine. The contributions to informal logic by Stephen Toulmin and Douglas Walton are explicated and their relevance for evidence-based medicine is discussed in relation to a common clinical scenario: hypertension management. This essay concludes with a discussion on the relationship between clinical reasoning, rationality, and evidence. It is argued that informal logic has the virtue of bringing explicitness to the role of evidence in clinical reasoning, and brings sensitivity to understanding the role of dialogical context in the need for evidence in clinical decision making.

An improved non-uniformity correction algorithm and its hardware implementation on FPGA

NASA Astrophysics Data System (ADS)

Rong, Shenghui; Zhou, Huixin; Wen, Zhigang; Qin, Hanlin; Qian, Kun; Cheng, Kuanhong

2017-09-01

The Non-uniformity of Infrared Focal Plane Arrays (IRFPA) severely degrades the infrared image quality. An effective non-uniformity correction (NUC) algorithm is necessary for an IRFPA imaging and application system. However traditional scene-based NUC algorithm suffers the image blurring and artificial ghosting. In addition, few effective hardware platforms have been proposed to implement corresponding NUC algorithms. Thus, this paper proposed an improved neural-network based NUC algorithm by the guided image filter and the projection-based motion detection algorithm. First, the guided image filter is utilized to achieve the accurate desired image to decrease the artificial ghosting. Then a projection-based moving detection algorithm is utilized to determine whether the correction coefficients should be updated or not. In this way the problem of image blurring can be overcome. At last, an FPGA-based hardware design is introduced to realize the proposed NUC algorithm. A real and a simulated infrared image sequences are utilized to verify the performance of the proposed algorithm. Experimental results indicated that the proposed NUC algorithm can effectively eliminate the fix pattern noise with less image blurring and artificial ghosting. The proposed hardware design takes less logic elements in FPGA and spends less clock cycles to process one frame of image.

Protein logic: a statistical mechanical study of signal integration at the single-molecule level.

PubMed

de Ronde, Wiet; Rein ten Wolde, Pieter; Mugler, Andrew

2012-09-05

Information processing and decision-making is based upon logic operations, which in cellular networks has been well characterized at the level of transcription. In recent years, however, both experimentalists and theorists have begun to appreciate that cellular decision-making can also be performed at the level of a single protein, giving rise to the notion of protein logic. Here we systematically explore protein logic using a well-known statistical mechanical model. As an example system, we focus on receptors that bind either one or two ligands, and their associated dimers. Notably, we find that a single heterodimer can realize any of the 16 possible logic gates, including the XOR gate, by variation of biochemical parameters. We then introduce what to our knowledge is a novel idea: that a set of receptors with fixed parameters can encode functionally unique logic gates simply by forming different dimeric combinations. An exhaustive search reveals that the simplest set of receptors (two single-ligand receptors and one double-ligand receptor) can realize several different groups of three unique gates, a result for which the parametric analysis of single receptors and dimers provides a clear interpretation. Both results underscore the surprising functional freedom readily available to cells at the single-protein level. Copyright © 2012 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Critical Development Exploration Based on the Islamic Education in Iranian Higher Education

ERIC Educational Resources Information Center

Taheri, Mohammad Reza; Keshtiaray, Narges; Yousefy, Ali Reza

2015-01-01

The aim of this research is to do a critical development exploration based on the Islamic education in Iranian higher education. In this paper, logical analysis qualitative method was used. Through library studies, information was collected and analysis of the results was done. The information collecting tool was note taking and information was…

The Role of Policy in Constructing the Peripheral Scientist in the Era of Globalization

ERIC Educational Resources Information Center

Englander, Karen; Uzuner-Smith, Sedef

2013-01-01

This study explores how the logic and values of globalization are manifested in international discourses of higher education in relation to scientific knowledge production and how those values are appropriated in national and institutional policies. This study also explores how this confluence of discourses and policies construct scientists in two…

Stress Testing of an Artificial Pancreas System With Pizza and Exercise Leads to Improvements in the System's Fuzzy Logic Controller.

PubMed

Mauseth, Richard; Lord, Sandra M; Hirsch, Irl B; Kircher, Robert C; Matheson, Don P; Greenbaum, Carla J

2015-09-14

Under controlled conditions, the Dose Safety artificial pancreas (AP) system controller, which utilizes "fuzzy logic" (FL) methodology to calculate and deliver appropriate insulin dosages based on changes in blood glucose, successfully managed glycemic excursions. The aim of this study was to show whether stressing the system with pizza (high carbohydrate/high fat) meals and exercise would reveal deficits in the performance of the Dose Safety FL controller (FLC) and lead to improvements in the dosing matrix. Ten subjects with type 1 diabetes (T1D) were enrolled and participated in 30 studies (17 meal, 13 exercise) using 2 versions of the FLC. After conducting 13 studies with the first version (FLC v2.0), interim results were evaluated and the FLC insulin-dosing matrix was modified to create a new controller version (FLC v2.1) that was validated through regression testing using v2.0 CGM datasets prior to its use in clinical studies. The subsequent 17 studies were performed using FLC v2.1. Use of FLC v2.1 vs FLC v2.0 in the pizza meal tests showed improvements in mean blood glucose (205 mg/dL vs 232 mg/dL, P = .04). FLC v2.1 versus FLC v2.0 in exercise tests showed improvements in mean blood glucose (146 mg/dL vs 201 mg/dL, P = .004), percentage time spent >180 mg/dL (19.3% vs 46.7%, P = .001), and percentage time spent 70-180 mg/dL (80.0% vs 53.3%, P = .002). Stress testing the AP system revealed deficits in the FLC performance, which led to adjustments to the dosing matrix followed by improved FLC performance when retested. © 2015 Diabetes Technology Society.

Breast tumor malignancy modelling using evolutionary neural logic networks.

PubMed

Tsakonas, Athanasios; Dounias, Georgios; Panagi, Georgia; Panourgias, Evangelia

2006-01-01

The present work proposes a computer assisted methodology for the effective modelling of the diagnostic decision for breast tumor malignancy. The suggested approach is based on innovative hybrid computational intelligence algorithms properly applied in related cytological data contained in past medical records. The experimental data used in this study were gathered in the early 1990s in the University of Wisconsin, based in post diagnostic cytological observations performed by expert medical staff. Data were properly encoded in a computer database and accordingly, various alternative modelling techniques were applied on them, in an attempt to form diagnostic models. Previous methods included standard optimisation techniques, as well as artificial intelligence approaches, in a way that a variety of related publications exists in modern literature on the subject. In this report, a hybrid computational intelligence approach is suggested, which effectively combines modern mathematical logic principles, neural computation and genetic programming in an effective manner. The approach proves promising either in terms of diagnostic accuracy and generalization capabilities, or in terms of comprehensibility and practical importance for the related medical staff.

A solution to the biodiversity paradox by logical deterministic cellular automata.

PubMed

Kalmykov, Lev V; Kalmykov, Vyacheslav L

2015-06-01

The paradox of biological diversity is the key problem of theoretical ecology. The paradox consists in the contradiction between the competitive exclusion principle and the observed biodiversity. The principle is important as the basis for ecological theory. On a relatively simple model we show a mechanism of indefinite coexistence of complete competitors which violates the known formulations of the competitive exclusion principle. This mechanism is based on timely recovery of limiting resources and their spatio-temporal allocation between competitors. Because of limitations of the black-box modeling there was a problem to formulate the exclusion principle correctly. Our white-box multiscale model of two-species competition is based on logical deterministic individual-based cellular automata. This approach provides an automatic deductive inference on the basis of a system of axioms, and gives a direct insight into mechanisms of the studied system. It is one of the most promising methods of artificial intelligence. We reformulate and generalize the competitive exclusion principle and explain why this formulation provides a solution of the biodiversity paradox. In addition, we propose a principle of competitive coexistence.

Development of cyberblog-based intelligent tutorial system to improve students learning ability algorithm

NASA Astrophysics Data System (ADS)

Wahyudin; Riza, L. S.; Putro, B. L.

2018-05-01

E-learning as a learning activity conducted online by the students with the usual tools is favoured by students. The use of computer media in learning provides benefits that are not owned by other learning media that is the ability of computers to interact individually with students. But the weakness of many learning media is to assume that all students have a uniform ability, when in reality this is not the case. The concept of Intelligent Tutorial System (ITS) combined with cyberblog application can overcome the weaknesses in neglecting diversity. An Intelligent Tutorial System-based Cyberblog application (ITS) is a web-based interactive application program that implements artificial intelligence which can be used as a learning and evaluation media in the learning process. The use of ITS-based Cyberblog in learning is one of the alternative learning media that is interesting and able to help students in measuring ability in understanding the material. This research will be associated with the improvement of logical thinking ability (logical thinking) of students, especially in algorithm subjects.

Approach of automatic 3D geological mapping: the case of the Kovdor phoscorite-carbonatite complex, NW Russia.

PubMed

Kalashnikov, A O; Ivanyuk, G Yu; Mikhailova, J A; Sokharev, V A

2017-07-31

We have developed an approach for automatic 3D geological mapping based on conversion of chemical composition of rocks to mineral composition by logical computation. It allows to calculate mineral composition based on bulk rock chemistry, interpolate the mineral composition in the same way as chemical composition, and, finally, build a 3D geological model. The approach was developed for the Kovdor phoscorite-carbonatite complex containing the Kovdor baddeleyite-apatite-magnetite deposit. We used 4 bulk rock chemistry analyses - Fe magn , P 2 O 5 , CO 2 and SiO 2 . We used four techniques for prediction of rock types - calculation of normative mineral compositions (norms), multiple regression, artificial neural network and developed by logical evaluation. The two latter became the best. As a result, we distinguished 14 types of phoscorites (forsterite-apatite-magnetite-carbonate rock), carbonatite and host rocks. The results show good convergence with our petrographical studies of the deposit, and recent manually built maps. The proposed approach can be used as a tool of a deposit genesis reconstruction and preliminary geometallurgical modelling.

Counseling, Artificial Intelligence, and Expert Systems.

ERIC Educational Resources Information Center

Illovsky, Michael E.

1994-01-01

Considers the use of artificial intelligence and expert systems in counseling. Limitations are explored; candidates for counseling versus those for expert systems are discussed; programming considerations are reviewed; and techniques for dealing with rational, nonrational, and irrational thoughts and feelings are described. (Contains 46…

Artificial Gravity Research Plan

NASA Technical Reports Server (NTRS)

Cromwell, Ronita

2014-01-01

This document describes the forward working plan to identify what countermeasure resources are needed for a vehicle with an artificial gravity module (intermittent centrifugation) and what Countermeasure Resources are needed for a rotating transit vehicle (continuous centrifugation) to minimize the effects of microgravity to Mars Exploration crewmembers.

NOVA: A new multi-level logic simulator

NASA Technical Reports Server (NTRS)

Miles, L.; Prins, P.; Cameron, K.; Shovic, J.

1990-01-01

A new logic simulator that was developed at the NASA Space Engineering Research Center for VLSI Design was described. The simulator is multi-level, being able to simulate from the switch level through the functional model level. NOVA is currently in the Beta test phase and was used to simulate chips designed for the NASA Space Station and the Explorer missions. A new algorithm was devised to simulate bi-directional pass transistors and a preliminary version of the algorithm is presented. The usage of functional models in NOVA is also described and performance figures are presented.

Formal Verification Toolkit for Requirements and Early Design Stages

NASA Technical Reports Server (NTRS)

Badger, Julia M.; Miller, Sheena Judson

2011-01-01

Efficient flight software development from natural language requirements needs an effective way to test designs earlier in the software design cycle. A method to automatically derive logical safety constraints and the design state space from natural language requirements is described. The constraints can then be checked using a logical consistency checker and also be used in a symbolic model checker to verify the early design of the system. This method was used to verify a hybrid control design for the suit ports on NASA Johnson Space Center's Space Exploration Vehicle against safety requirements.

The Design of Fault Tolerant Quantum Dot Cellular Automata Based Logic

NASA Technical Reports Server (NTRS)

Armstrong, C. Duane; Humphreys, William M.; Fijany, Amir

2002-01-01

As transistor geometries are reduced, quantum effects begin to dominate device performance. At some point, transistors cease to have the properties that make them useful computational components. New computing elements must be developed in order to keep pace with Moore s Law. Quantum dot cellular automata (QCA) represent an alternative paradigm to transistor-based logic. QCA architectures that are robust to manufacturing tolerances and defects must be developed. We are developing software that allows the exploration of fault tolerant QCA gate architectures by automating the specification, simulation, analysis and documentation processes.

Artificial Gravity: Will it Preserve Bone Health on Long-Duration Missions?

NASA Technical Reports Server (NTRS)

Davis-Street, Janis; Paloski, William H.

2005-01-01

Prolonged microgravity exposure disrupts bone, muscle, and cardiovascular homeostasis, sensory-motor coordination, immune function, and behavioral performance. Bone loss, in particular, remains a serious impediment to the success of exploration-class missions by increasing the risks of bone fracture and renal stone formation for crew members. Current countermeasures, consisting primarily of resistive and aerobic exercise, have not yet proven fully successful for preventing bone loss during long-duration spaceflight. While other bone-specific countermeasures, such as pharmacological therapy and dietary modifications, are under consideration, countermeasure approaches that simultaneously address multiple physiologic systems may be more desirable for exploration-class missions, particularly if they can provide effective protection at reduced mission resource requirements (up-mass, power, crew time, etc). The most robust of the multi-system approaches under consideration, artificial gravity (AG), could prevent all of the microgravity-related physiological changes from occurring. The potential methods for realizing an artificial gravity countermeasure are reviewed, as well as selected animal and human studies evaluating the effects of artificial gravity on bone function. Future plans for the study of the multi-system effects of artificial gravity include a joint, cooperative international effort that will systematically seek an optimal prescription for intermittent AG to preserve bone, muscle, and cardiovascular function in human subjects deconditioned by 6 degree head-down-tilt-bed rest. It is concluded that AG has great promise as a multi-system countermeasure, but that further research is required to determine the appropriate parameters for implementation of such a countermeasure for exploration-class missions.

Laying date, incubation and egg breakage as determinants of bacterial load on bird eggshells: experimental evidence.

PubMed

Soler, Juan José; Ruiz-Rodríguez, Magdalena; Martín-Vivaldi, Manuel; Peralta-Sánchez, Juan Manuel; Ruiz-Castellano, Cristina; Tomás, Gustavo

2015-09-01

Exploring factors guiding interactions of bacterial communities with animals has become of primary importance for ecologists and evolutionary biologists during the last years because of their likely central role in the evolution of animal life history traits. We explored the association between laying date and eggshell bacterial load (mesophilic bacteria, Enterobacteriaceae, Staphylococci, and Enterococci) in natural and artificial magpie (Pica pica) nests containing fresh commercial quail (Coturnix coturnix) eggs. We manipulated hygiene conditions by spilling egg contents on magpie and artificial nests and explored experimental effects during the breeding season. Egg breakage is a common outcome of brood parasitism by great spotted cuckoos (Clamator glandarius) on the nests of magpie, one of its main hosts. We found that the treatment increased eggshell bacterial load in artificial nests, but not in magpie nests with incubating females, which suggests that parental activity prevents the proliferation of bacteria on the eggshells in relation to egg breakage. Moreover, laying date was positively related to eggshell bacterial load in active magpie nests, but negatively in artificial nests. The results suggest that variation in parental characteristics of magpies rather than climatic variation during the breeding season explained the detected positive association. Because the eggshell bacterial load is a proxy of hatching success, the detected positive association between eggshell bacterial loads and laying date in natural, but not in artificial nests, suggests that the generalized negative association between laying date and avian breeding success can be, at least partially, explained by differential bacterial effects.

Artificial Intelligence and CALL.

ERIC Educational Resources Information Center

Underwood, John H.

The potential application of artificial intelligence (AI) to computer-assisted language learning (CALL) is explored. Two areas of AI that hold particular interest to those who deal with language meaning--knowledge representation and expert systems, and natural-language processing--are described and examples of each are presented. AI contribution…

Artificial Intelligence Support for Landing Site Selection on Mars

NASA Astrophysics Data System (ADS)

Rongier, G.; Pankratius, V.

2017-12-01

Mars is a key target for planetary exploration; a better understanding of its evolution and habitability requires roving in situ. Landing site selection is becoming more challenging for scientists as new instruments generate higher data volumes. The involved engineering and scientific constraints make site selection and the anticipation of possible onsite actions into a complex optimization problem: there may be multiple acceptable solutions depending on various goals and assumptions. Solutions must also account for missing data, errors, and potential biases. To address these problems, we propose an AI-informed decision support system that allows scientists, mission designers, engineers, and committees to explore alternative site selection choices based on data. In particular, we demonstrate first results of an exploratory case study using fuzzy logic and a simulation of a rover's mobility map based on the fast marching algorithm. Our system computes favorability maps of the entire planet to facilitate landing site selection and allows a definition of different configurations for rovers, science target priorities, landing ellipses, and other constraints. For a rover similar to NASA's Mars 2020 rover, we present results in form of a site favorability map as well as four derived exploration scenarios that depend on different prioritized scientific targets, all visualizing inherent tradeoffs. Our method uses the NASA PDS Geosciences Node and the NASA/ICA Integrated Database of Planetary Features. Under common assumptions, the data products reveal Eastern Margaritifer Terra and Meridiani Planum to be the most favorable sites due to a high concentration of scientific targets and a flat, easily navigable surface. Our method also allows mission designers to investigate which constraints have the highest impact on the mission exploration potential and to change parameter ranges. Increasing the elevation limit for landing, for example, provides access to many additional, more interesting sites on the southern terrains of Mars. The speed of current rovers is another limit to exploration capabilities: our system helps quantify how speed increases can improve the number of reachable targets in the search space. We acknowledge support from NASA AISTNNX15AG84G (PI Pankratius) and NSF ACI1442997 (PI Pankratius).

High Stakes Policy and Mandated Curriculum: A Rhetorical Argumentation Analysis to Explore the Social Processes That Shape School Leaders' and Teachers' Strategic Responses

ERIC Educational Resources Information Center

Dulude, Eliane; Spillane, James P.; Dumay, Xavier

2017-01-01

Several social processes guide and shape how school actors engage with high stakes state and district policies relative to mandated curriculum and instruction. In this article, we use rhetorical argumentation analysis to explore how stakeholders mobilize resources through argumentation and rhetorical appeals (logical, emotional, and…

Log-Linear Model Based Behavior Selection Method for Artificial Fish Swarm Algorithm

PubMed Central

Huang, Zhehuang; Chen, Yidong

2015-01-01

Artificial fish swarm algorithm (AFSA) is a population based optimization technique inspired by social behavior of fishes. In past several years, AFSA has been successfully applied in many research and application areas. The behavior of fishes has a crucial impact on the performance of AFSA, such as global exploration ability and convergence speed. How to construct and select behaviors of fishes are an important task. To solve these problems, an improved artificial fish swarm algorithm based on log-linear model is proposed and implemented in this paper. There are three main works. Firstly, we proposed a new behavior selection algorithm based on log-linear model which can enhance decision making ability of behavior selection. Secondly, adaptive movement behavior based on adaptive weight is presented, which can dynamically adjust according to the diversity of fishes. Finally, some new behaviors are defined and introduced into artificial fish swarm algorithm at the first time to improve global optimization capability. The experiments on high dimensional function optimization showed that the improved algorithm has more powerful global exploration ability and reasonable convergence speed compared with the standard artificial fish swarm algorithm. PMID:25691895

Programmable hardware for reconfigurable computing systems

NASA Astrophysics Data System (ADS)

Smith, Stephen

1996-10-01

In 1945 the work of J. von Neumann and H. Goldstein created the principal architecture for electronic computation that has now lasted fifty years. Nevertheless alternative architectures have been created that have computational capability, for special tasks, far beyond that feasible with von Neumann machines. The emergence of high capacity programmable logic devices has made the realization of these architectures practical. The original ENIAC and EDVAC machines were conceived to solve special mathematical problems that were far from today's concept of 'killer applications.' In a similar vein programmable hardware computation is being used today to solve unique mathematical problems. Our programmable hardware activity is focused on the research and development of novel computational systems based upon the reconfigurability of our programmable logic devices. We explore our programmable logic architectures and their implications for programmable hardware. One programmable hardware board implementation is detailed.

Fuzzy Logic Path Planning System for Collision Avoidance by an Autonomous Rover Vehicle

NASA Technical Reports Server (NTRS)

Murphy, Michael G.

1991-01-01

Systems already developed at JSC have shown the benefits of applying fuzzy logic control theory to space related operations. Four major issues are addressed that are associated with developing an autonomous collision avoidance subsystem within a path planning system designed for application in a remote, hostile environment that does not lend itself well to remote manipulation of the vehicle involved through Earth-based telecommunication. A good focus for this is unmanned exploration of the surface of Mars. The uncertainties involved indicate that robust approaches such as fuzzy logic control are particularly appropriate. The four major issues addressed are: (1) avoidance of a single fuzzy moving obstacle; (2) back off from a dead end in a static obstacle environment; (3) fusion of sensor data to detect obstacles; and (4) options for adaptive learning in a path planning system.

Globalization, Educational Targeting, and Stable Inequalities: A Comparative Analysis of Argentina, Brazil, and Chile

NASA Astrophysics Data System (ADS)

Rambla, Xavier

2006-05-01

The present study analyzes educational targeting in Argentina, Brazil and Chile from a sociological point of view. It shows that a `logic of induction' has become the vehicle for anti-poverty education strategies meant to help targeted groups improve on their own. The analysis explores the influence of the global educational agenda, the empirical connection between the logic of induction and the mechanism of emulation, and the territorial aspects of educational inequalities. Emulation plays a main role inasmuch as the logic of induction leads targeted groups to compare their adverse situation with more privileged groups, which actually legitimizes inequalities. A brief statistical summary completes the study, showing that educational inequality has remained unchanged as far as urban-rural ratios (in Brazil and Chile) and regional disparities (in all three countries) are concerned.

A white-box model of S-shaped and double S-shaped single-species population growth

PubMed Central

Kalmykov, Lev V.

2015-01-01

Complex systems may be mechanistically modelled by white-box modeling with using logical deterministic individual-based cellular automata. Mathematical models of complex systems are of three types: black-box (phenomenological), white-box (mechanistic, based on the first principles) and grey-box (mixtures of phenomenological and mechanistic models). Most basic ecological models are of black-box type, including Malthusian, Verhulst, Lotka–Volterra models. In black-box models, the individual-based (mechanistic) mechanisms of population dynamics remain hidden. Here we mechanistically model the S-shaped and double S-shaped population growth of vegetatively propagated rhizomatous lawn grasses. Using purely logical deterministic individual-based cellular automata we create a white-box model. From a general physical standpoint, the vegetative propagation of plants is an analogue of excitation propagation in excitable media. Using the Monte Carlo method, we investigate a role of different initial positioning of an individual in the habitat. We have investigated mechanisms of the single-species population growth limited by habitat size, intraspecific competition, regeneration time and fecundity of individuals in two types of boundary conditions and at two types of fecundity. Besides that, we have compared the S-shaped and J-shaped population growth. We consider this white-box modeling approach as a method of artificial intelligence which works as automatic hyper-logical inference from the first principles of the studied subject. This approach is perspective for direct mechanistic insights into nature of any complex systems. PMID:26038717

Natural and engineered biosynthesis of nucleoside antibiotics in Actinomycetes.

PubMed

Chen, Wenqing; Qi, Jianzhao; Wu, Pan; Wan, Dan; Liu, Jin; Feng, Xuan; Deng, Zixin

2016-03-01

Nucleoside antibiotics constitute an important family of microbial natural products bearing diverse bioactivities and unusual structural features. Their biosynthetic logics are unique with involvement of complex multi-enzymatic reactions leading to the intricate molecules from simple building blocks. Understanding how nature builds this family of antibiotics in post-genomic era sets the stage for rational enhancement of their production, and also paves the way for targeted persuasion of the cell factories to make artificial designer nucleoside drugs and leads via synthetic biology approaches. In this review, we discuss the recent progress and perspectives on the natural and engineered biosynthesis of nucleoside antibiotics.

Using machine learning for improving knowledge on antibacterial effect of bioactive glass.

PubMed

Echezarreta-López, M M; Landin, M

2013-09-10

The aim of this work was to find relationships between critical bioactive glass characteristics and their antibacterial behaviour using an artificial intelligence tool. A large dataset including ingredients and process variables of the bioactive glasses production, bacterial characteristics and microbiological experimental conditions was generated from literature and analyzed by neurofuzzy logic technology. Our findings allow an explanation on the variability in antibacterial behaviour found by different authors and to obtain general conclusions about critical parameters of bioactive glasses to be considered in order to achieve activity against some of the most common skin and implant surgery pathogens. Copyright © 2013 Elsevier B.V. All rights reserved.

Innovative intelligent technology of distance learning for visually impaired people

NASA Astrophysics Data System (ADS)

Samigulina, Galina; Shayakhmetova, Assem; Nuysuppov, Adlet

2017-12-01

The aim of the study is to develop innovative intelligent technology and information systems of distance education for people with impaired vision (PIV). To solve this problem a comprehensive approach has been proposed, which consists in the aggregate of the application of artificial intelligence methods and statistical analysis. Creating an accessible learning environment, identifying the intellectual, physiological, psychophysiological characteristics of perception and information awareness by this category of people is based on cognitive approach. On the basis of fuzzy logic the individually-oriented learning path of PIV is con- structed with the aim of obtaining high-quality engineering education with modern equipment in the joint use laboratories.

Robotics, Artificial Intelligence, Computer Simulation: Future Applications in Special Education.

ERIC Educational Resources Information Center

Moore, Gwendolyn B.; And Others

1986-01-01

Describes possible applications of new technologies to special education. Discusses results of a study designed to explore the use of robotics, artificial intelligence, and computer simulations to aid people with handicapping conditions. Presents several scenarios in which specific technological advances may contribute to special education…

Implementing biological logic gates using gold nanoparticles conjugated to fluorophores

NASA Astrophysics Data System (ADS)

Barnoy, Eran A.; Popovtzer, Rachela; Fixler, Dror

2018-02-01

We describe recent research in which we explored biologically relevant logic gates using gold nanoparticles (GNPs) conjugated to fluorophores and tracing the results remotely by time-domain fluorescence lifetime imaging microscopy (FLIM). GNPs have a well-known effect on nearby fluorophores in terms of their fluorescence intensity (FI - increase or decrease) as well as fluorescence lifetime (FLT). We have designed a few bio-switch systems in which the FLIMdetected fluorescence varies after biologically relevant stimulation. Some of our tools include fluorescein diacetate (FDA) which can be activated by either esterases or pH, peptide chains cleavable by caspase 3, and the polymer polyacrylic acid which varies in size based on surrounding pH. After conjugating GNPs to chosen fluorophores, we have successfully demonstrated the logic gates of NOT, AND, OR, NAND, NOR, and XOR by imaging different stages of activation. These logic gates have been demonstrated both in solutions as well as within cultured cells, thereby possibly opening the door for nanoparticulate in vivo smart detection. While these initial probes are mainly tools for intelligent detection systems, they lay the foundation for logic gates functioning in conjunction so as to lead to a form of in vivo biological computing, where the system would be able to release proper treatment options in specific situations without external influence.

Logical synchronization: how evidence and hypotheses steer atomic clocks

NASA Astrophysics Data System (ADS)

Myers, John M.; Madjid, F. Hadi

2014-05-01

A clock steps a computer through a cycle of phases. For the propagation of logical symbols from one computer to another, each computer must mesh its phases with arrivals of symbols from other computers. Even the best atomic clocks drift unforeseeably in frequency and phase; feedback steers them toward aiming points that depend on a chosen wave function and on hypotheses about signal propagation. A wave function, always under-determined by evidence, requires a guess. Guessed wave functions are coded into computers that steer atomic clocks in frequency and position—clocks that step computers through their phases of computations, as well as clocks, some on space vehicles, that supply evidence of the propagation of signals. Recognizing the dependence of the phasing of symbol arrivals on guesses about signal propagation elevates `logical synchronization.' from its practice in computer engineering to a dicipline essential to physics. Within this discipline we begin to explore questions invisible under any concept of time that fails to acknowledge the unforeseeable. In particular, variation of spacetime curvature is shown to limit the bit rate of logical communication.

Fuzzy logic control system to provide autonomous collision avoidance for Mars rover vehicle

NASA Technical Reports Server (NTRS)

Murphy, Michael G.

1990-01-01

NASA is currently involved with planning unmanned missions to Mars to investigate the terrain and process soil samples in advance of a manned mission. A key issue involved in unmanned surface exploration on Mars is that of supporting autonomous maneuvering since radio communication involves lengthy delays. It is anticipated that specific target locations will be designated for sample gathering. In maneuvering autonomously from a starting position to a target position, the rover will need to avoid a variety of obstacles such as boulders or troughs that may block the shortest path to the target. The physical integrity of the rover needs to be maintained while minimizing the time and distance required to attain the target position. Fuzzy logic lends itself well to building reliable control systems that function in the presence of uncertainty or ambiguity. The following major issues are discussed: (1) the nature of fuzzy logic control systems and software tools to implement them; (2) collision avoidance in the presence of fuzzy parameters; and (3) techniques for adaptation in fuzzy logic control systems.

Values beyond value? Is anything beyond the logic of capital?

PubMed

Skeggs, Bev

2014-03-01

We are living in a time when it is frequently assumed that the logic of capital has subsumed every single aspect of our lives, intervening in the organization of our intimate relations as well as the control of our time, including investments in the future (e.g. via debt). The theories that document the incursion of this logic (often through the terms of neoliberalism and/or governmentality) assume that this logic is internalized, works and organizes everything including our subjectivity. These theories performatively reproduce the very conditions they describe, shrinking the domain of values and making it subject to capital's logic. All values are reduced to value. Yet values and value are always dialogic, dependent and co-constituting. In this paper I chart the history by which value eclipses values and how this shrinks our sociological imagination. By outlining the historical processes that institutionalized different organizations of the population through political economy and the social contract, producing ideas of proper personhood premised on propriety, I detail how forms of raced, gendered and classed personhood was formed. The gaps between the proper and improper generate significant contradictions that offer both opportunities to and limits on capitals' lines of flight. It is the lacks, the residues, and the excess that cannot be captured by capital's mechanisms of valuation that will be explored in order to think beyond the logic of capital and show how values will always haunt value. © London School of Economics and Political Science 2014.

Artificial intelligence in medicine.

PubMed Central

Ramesh, A. N.; Kambhampati, C.; Monson, J. R. T.; Drew, P. J.

2004-01-01

INTRODUCTION: Artificial intelligence is a branch of computer science capable of analysing complex medical data. Their potential to exploit meaningful relationship with in a data set can be used in the diagnosis, treatment and predicting outcome in many clinical scenarios. METHODS: Medline and internet searches were carried out using the keywords 'artificial intelligence' and 'neural networks (computer)'. Further references were obtained by cross-referencing from key articles. An overview of different artificial intelligent techniques is presented in this paper along with the review of important clinical applications. RESULTS: The proficiency of artificial intelligent techniques has been explored in almost every field of medicine. Artificial neural network was the most commonly used analytical tool whilst other artificial intelligent techniques such as fuzzy expert systems, evolutionary computation and hybrid intelligent systems have all been used in different clinical settings. DISCUSSION: Artificial intelligence techniques have the potential to be applied in almost every field of medicine. There is need for further clinical trials which are appropriately designed before these emergent techniques find application in the real clinical setting. PMID:15333167

Artificial intelligence in medicine.

PubMed

Ramesh, A N; Kambhampati, C; Monson, J R T; Drew, P J

2004-09-01

Artificial intelligence is a branch of computer science capable of analysing complex medical data. Their potential to exploit meaningful relationship with in a data set can be used in the diagnosis, treatment and predicting outcome in many clinical scenarios. Medline and internet searches were carried out using the keywords 'artificial intelligence' and 'neural networks (computer)'. Further references were obtained by cross-referencing from key articles. An overview of different artificial intelligent techniques is presented in this paper along with the review of important clinical applications. The proficiency of artificial intelligent techniques has been explored in almost every field of medicine. Artificial neural network was the most commonly used analytical tool whilst other artificial intelligent techniques such as fuzzy expert systems, evolutionary computation and hybrid intelligent systems have all been used in different clinical settings. Artificial intelligence techniques have the potential to be applied in almost every field of medicine. There is need for further clinical trials which are appropriately designed before these emergent techniques find application in the real clinical setting.

Artificial Exo-Society Modeling: a New Tool for SETI Research

NASA Astrophysics Data System (ADS)

Gardner, James N.

2002-01-01

One of the newest fields of complexity research is artificial society modeling. Methodologically related to artificial life research, artificial society modeling utilizes agent-based computer simulation tools like SWARM and SUGARSCAPE developed by the Santa Fe Institute, Los Alamos National Laboratory and the Bookings Institution in an effort to introduce an unprecedented degree of rigor and quantitative sophistication into social science research. The broad aim of artificial society modeling is to begin the development of a more unified social science that embeds cultural evolutionary processes in a computational environment that simulates demographics, the transmission of culture, conflict, economics, disease, the emergence of groups and coadaptation with an environment in a bottom-up fashion. When an artificial society computer model is run, artificial societal patterns emerge from the interaction of autonomous software agents (the "inhabitants" of the artificial society). Artificial society modeling invites the interpretation of society as a distributed computational system and the interpretation of social dynamics as a specialized category of computation. Artificial society modeling techniques offer the potential of computational simulation of hypothetical alien societies in much the same way that artificial life modeling techniques offer the potential to model hypothetical exobiological phenomena. NASA recently announced its intention to begin exploring the possibility of including artificial life research within the broad portfolio of scientific fields comprised by the interdisciplinary astrobiology research endeavor. It may be appropriate for SETI researchers to likewise commence an exploration of the possible inclusion of artificial exo-society modeling within the SETI research endeavor. Artificial exo-society modeling might be particularly useful in a post-detection environment by (1) coherently organizing the set of data points derived from a detected ETI signal, (2) mapping trends in the data points over time (assuming receipt of an extended ETI signal), and (3) projecting such trends forward to derive alternative cultural evolutionary scenarios for the exo-society under analysis. The latter exercise might be particularly useful to compensate for the inevitable time lag between generation of an ETI signal and receipt of an ETI signal on Earth. For this reason, such an exercise might be a helpful adjunct to the decisional process contemplated by Paragraph 9 of the Declaration of Principles Concerning Activities Following the Detection of Extraterrestrial Intelligence.

Using Artificial Neural Networks in Educational Research: Some Comparisons with Linear Statistical Models.

ERIC Educational Resources Information Center

Everson, Howard T.; And Others

This paper explores the feasibility of neural computing methods such as artificial neural networks (ANNs) and abductory induction mechanisms (AIM) for use in educational measurement. ANNs and AIMS methods are contrasted with more traditional statistical techniques, such as multiple regression and discriminant function analyses, for making…

The Relationship between Artificial and Second Language Learning

ERIC Educational Resources Information Center

Ettlinger, Marc; Morgan-Short, Kara; Faretta-Stutenberg, Mandy; Wong, Patrick C. M.

2016-01-01

Artificial language learning (ALL) experiments have become an important tool in exploring principles of language and language learning. A persistent question in all of this work, however, is whether ALL engages the linguistic system and whether ALL studies are ecologically valid assessments of natural language ability. In the present study, we…

15 CFR 970.301 - Requirements for applications based on pre-enactment exploration.

Code of Federal Regulations, 2012 CFR

2012-01-01

... COMMERCE GENERAL REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR.... (f) The coordinates and any chart of the logical mining unit applied for in an application based on a...

15 CFR 970.301 - Requirements for applications based on pre-enactment exploration.

Code of Federal Regulations, 2014 CFR

2014-01-01

... COMMERCE GENERAL REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR.... (f) The coordinates and any chart of the logical mining unit applied for in an application based on a...

15 CFR 970.301 - Requirements for applications based on pre-enactment exploration.

Code of Federal Regulations, 2013 CFR

2013-01-01

... COMMERCE GENERAL REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR.... (f) The coordinates and any chart of the logical mining unit applied for in an application based on a...

15 CFR 970.301 - Requirements for applications based on pre-enactment exploration.

Code of Federal Regulations, 2011 CFR

2011-01-01

... COMMERCE GENERAL REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR.... (f) The coordinates and any chart of the logical mining unit applied for in an application based on a...

15 CFR 970.301 - Requirements for applications based on pre-enactment exploration.

Code of Federal Regulations, 2010 CFR

2010-01-01

... COMMERCE GENERAL REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR.... (f) The coordinates and any chart of the logical mining unit applied for in an application based on a...

IDEAS.

ERIC Educational Resources Information Center

Young, Sharon L.

1991-01-01

Presented are activities that focus on gathering, using, and interpreting data about fingerprints as a basis for integrating mathematics and science. Patterns, classification, logical reasoning, and mathematical relationships are explored by making graphs, classifying fingerprints, and matching identical fingerprints. A parent-involvement activity…

A framework to find the logic backbone of a biological network.

PubMed

Maheshwari, Parul; Albert, Réka

2017-12-06

Cellular behaviors are governed by interaction networks among biomolecules, for example gene regulatory and signal transduction networks. An often used dynamic modeling framework for these networks, Boolean modeling, can obtain their attractors (which correspond to cell types and behaviors) and their trajectories from an initial state (e.g. a resting state) to the attractors, for example in response to an external signal. The existing methods however do not elucidate the causal relationships between distant nodes in the network. In this work, we propose a simple logic framework, based on categorizing causal relationships as sufficient or necessary, as a complement to Boolean networks. We identify and explore the properties of complex subnetworks that are distillable into a single logic relationship. We also identify cyclic subnetworks that ensure the stabilization of the state of participating nodes regardless of the rest of the network. We identify the logic backbone of biomolecular networks, consisting of external signals, self-sustaining cyclic subnetworks (stable motifs), and output nodes. Furthermore, we use the logic framework to identify crucial nodes whose override can drive the system from one steady state to another. We apply these techniques to two biological networks: the epithelial-to-mesenchymal transition network corresponding to a developmental process exploited in tumor invasion, and the network of abscisic acid induced stomatal closure in plants. We find interesting subnetworks with logical implications in these networks. Using these subgraphs and motifs, we efficiently reduce both networks to succinct backbone structures. The logic representation identifies the causal relationships between distant nodes and subnetworks. This knowledge can form the basis of network control or used in the reverse engineering of networks.

Health literacy and logical inconsistencies in valuations of hypothetical health states: results from the Canadian EQ-5D-5L valuation study.

PubMed

Al Sayah, Fatima; Johnson, Jeffrey A; Ohinmaa, Arto; Xie, Feng; Bansback, Nick

2017-06-01

To examine the association of health literacy with logical inconsistencies in time trade-off valuations of hypothetical health states described by the EQ-5D-5L classification system. Data from the EQ-5D-5L Canadian Valuation study were used. Health literacy was assessed using the Brief Health Literacy Screen. A health state valuation was considered logically inconsistent if a respondent gave the same or lower value for a very mild health state compared to the value given to 55555, or gave the same or lower value for a very mild health state compared to value assigned to the majority of the health states that are dominated by the very mild health state. Average age of respondents (N = 1209) was 48 (SD = 17) years, 45% were male, 7% reported inadequate health literacy, and 11% had a logical inconsistency. In adjusted analysis, participants with inadequate health literacy were 2.2 (95%CI: 1.2, 4.0; p = 0.014) times more likely to provide an inconsistent valuation compared to those with adequate health literacy. More specifically, those who had problems in "understanding written information" and "reading health information" were more likely to have a logical inconsistency compared to those who did not. However, lacking "confidence in completing medical forms" was not associated with logical inconsistencies. Health literacy was associated with logical inconsistencies in valuations of hypothetical health states described by the EQ-5D-5L classification system. Valuations studies should consider assessing health literacy, and explore better ways to introduce the valuation tasks or use simpler approaches of health preferences elicitation for individuals with inadequate health literacy.

Evaluating data distribution and drift vulnerabilities of machine learning algorithms in secure and adversarial environments

NASA Astrophysics Data System (ADS)

Nelson, Kevin; Corbin, George; Blowers, Misty

2014-05-01

Machine learning is continuing to gain popularity due to its ability to solve problems that are difficult to model using conventional computer programming logic. Much of the current and past work has focused on algorithm development, data processing, and optimization. Lately, a subset of research has emerged which explores issues related to security. This research is gaining traction as systems employing these methods are being applied to both secure and adversarial environments. One of machine learning's biggest benefits, its data-driven versus logic-driven approach, is also a weakness if the data on which the models rely are corrupted. Adversaries could maliciously influence systems which address drift and data distribution changes using re-training and online learning. Our work is focused on exploring the resilience of various machine learning algorithms to these data-driven attacks. In this paper, we present our initial findings using Monte Carlo simulations, and statistical analysis, to explore the maximal achievable shift to a classification model, as well as the required amount of control over the data.

Intelligent control based on fuzzy logic and neural net theory

NASA Technical Reports Server (NTRS)

Lee, Chuen-Chien

1991-01-01

In the conception and design of intelligent systems, one promising direction involves the use of fuzzy logic and neural network theory to enhance such systems' capability to learn from experience and adapt to changes in an environment of uncertainty and imprecision. Here, an intelligent control scheme is explored by integrating these multidisciplinary techniques. A self-learning system is proposed as an intelligent controller for dynamical processes, employing a control policy which evolves and improves automatically. One key component of the intelligent system is a fuzzy logic-based system which emulates human decision making behavior. It is shown that the system can solve a fairly difficult control learning problem. Simulation results demonstrate that improved learning performance can be achieved in relation to previously described systems employing bang-bang control. The proposed system is relatively insensitive to variations in the parameters of the system environment.

International Conference on Integrated Optical Circuit Engineering, 1st, Cambridge, MA, October 23-25, 1984, Proceedings

NASA Astrophysics Data System (ADS)

Ostrowsky, D. B.; Sriram, S.

Aspects of waveguide technology are explored, taking into account waveguide fabrication techniques in GaAs/GaAlAs, the design and fabrication of AlGaAs/GaAs phase couplers for optical integrated circuit applications, ion implanted GaAs integrated optics fabrication technology, a direct writing electron beam lithography based process for the realization of optoelectronic integrated circuits, and advances in the development of semiconductor integrated optical circuits for telecommunications. Other subjects examined are related to optical signal processing, optical switching, and questions of optical bistability and logic. Attention is given to acousto-optic techniques in integrated optics, acousto-optic Bragg diffraction in proton exchanged waveguides, optical threshold logic architectures for hybrid binary/residue processors, integrated optical modulation and switching, all-optic logic devices for waveguide optics, optoelectronic switching, high-speed photodetector switching, and a mechanical optical switch.

Fuzzy set methods for object recognition in space applications

NASA Technical Reports Server (NTRS)

Keller, James M.

1991-01-01

During the reporting period, the development of the theory and application of methodologies for decision making under uncertainty was addressed. Two subreports are included; the first on properties of general hybrid operators, while the second considers some new research on generalized threshold logic units. In the first part, the properties of the additive gamma-model, where the intersection part is first considered to be the product of the input values and the union part is obtained by an extension of De Morgan's law to fuzzy sets, is explored. Then the Yager's class of union and intersection is used in the additive gamma-model. The inputs are weighted to some power that represents their importance and thus their contribution to the compensation process. In the second part, the extension of binary logic synthesis methods to multiple valued logic synthesis methods to enable the synthesis of decision networks when the input/output variables are not binary is discussed.

Active matter logic for autonomous microfluidics

NASA Astrophysics Data System (ADS)

Woodhouse, Francis G.; Dunkel, Jörn

2017-04-01

Chemically or optically powered active matter plays an increasingly important role in materials design, but its computational potential has yet to be explored systematically. The competition between energy consumption and dissipation imposes stringent physical constraints on the information transport in active flow networks, facilitating global optimization strategies that are not well understood. Here, we combine insights from recent microbial experiments with concepts from lattice-field theory and non-equilibrium statistical mechanics to introduce a generic theoretical framework for active matter logic. Highlighting conceptual differences with classical and quantum computation, we demonstrate how the inherent non-locality of incompressible active flow networks can be utilized to construct universal logical operations, Fredkin gates and memory storage in set-reset latches through the synchronized self-organization of many individual network components. Our work lays the conceptual foundation for developing autonomous microfluidic transport devices driven by bacterial fluids, active liquid crystals or chemically engineered motile colloids.

A Fuzzy Description Logic with Automatic Object Membership Measurement

NASA Astrophysics Data System (ADS)

Cai, Yi; Leung, Ho-Fung

In this paper, we propose a fuzzy description logic named f om -DL by combining the classical view in cognitive psychology and fuzzy set theory. A formal mechanism used to determine object memberships automatically in concepts is also proposed, which is lacked in previous work fuzzy description logics. In this mechanism, object membership is based on the defining properties of concept definition and properties in object description. Moreover, while previous works cannot express the qualitative measurements of an object possessing a property, we introduce two kinds of properties named N-property and L-property, which are quantitative measurements and qualitative measurements of an object possessing a property respectively. The subsumption and implication of concepts and properties are also explored in our work. We believe that it is useful to the Semantic Web community for reasoning the fuzzy membership of objects for concepts in fuzzy ontologies.

Informing health? Negotiating the logics of choice and care in everyday practices of 'healthy living'.

PubMed

Henwood, Flis; Harris, Roma; Spoel, Philippa

2011-06-01

This paper reports on a qualitative study examining everyday practices of healthy living (HL). Forty-four semi-structured interviews were undertaken with Canadian and UK citizens, aged 45 - 70, in April-May 2010. The research sits within the now substantial literature concerned with how health information is mediated, both by people and technologies, and employed in the context of 'good' health citizenship. Throughout this work, notions of 'choice' and 'empowerment' have been interrogated, theoretically and empirically, to reveal both the knowledge/power relationships integral to 'informing' processes and the shifting relationship between information and care in contemporary health encounters. In this paper, we analyse how people make sense of what it means to live healthily and how they know if they are doing so by focussing on three ways in which study participants become informed about healthy living: through their engagement with universal HL messages, through their own information searches, and through their attempts to measure their 'healthiness'. Following Mol's (2008) critique of the "logic of choice" in contemporary healthcare, we understand healthy living as a "situation of choice" where complex problems are framed as simple matters of choice and where information and technologies are understood as neutral aids to decision-making in support of 'correct' choices. Our analysis builds on and extends Mol's work by exploring how participants negotiate between this "logic of choice" and her alternative "logic of care" in their accounts of everyday HL informing practices and how the two logics "interfere" with one another. These accounts show resistance to the logic of choice through 'calls for care' but they also show clearly how the disciplining logic of choice works to (re)present such calls for care as failed attempts at healthy living, undermining the very practices the logic of choice seeks to encourage. Copyright © 2011 Elsevier Ltd. All rights reserved.

Quality by design approach: application of artificial intelligence techniques of tablets manufactured by direct compression.

PubMed

Aksu, Buket; Paradkar, Anant; de Matas, Marcel; Ozer, Ozgen; Güneri, Tamer; York, Peter

2012-12-01

The publication of the International Conference of Harmonization (ICH) Q8, Q9, and Q10 guidelines paved the way for the standardization of quality after the Food and Drug Administration issued current Good Manufacturing Practices guidelines in 2003. "Quality by Design", mentioned in the ICH Q8 guideline, offers a better scientific understanding of critical process and product qualities using knowledge obtained during the life cycle of a product. In this scope, the "knowledge space" is a summary of all process knowledge obtained during product development, and the "design space" is the area in which a product can be manufactured within acceptable limits. To create the spaces, artificial neural networks (ANNs) can be used to emphasize the multidimensional interactions of input variables and to closely bind these variables to a design space. This helps guide the experimental design process to include interactions among the input variables, along with modeling and optimization of pharmaceutical formulations. The objective of this study was to develop an integrated multivariate approach to obtain a quality product based on an understanding of the cause-effect relationships between formulation ingredients and product properties with ANNs and genetic programming on the ramipril tablets prepared by the direct compression method. In this study, the data are generated through the systematic application of the design of experiments (DoE) principles and optimization studies using artificial neural networks and neurofuzzy logic programs.

Nest Material Shapes Eggs Bacterial Environment.

PubMed

Ruiz-Castellano, Cristina; Tomás, Gustavo; Ruiz-Rodríguez, Magdalena; Martín-Gálvez, David; Soler, Juan José

2016-01-01

Selective pressures imposed by pathogenic microorganisms to embryos have selected in hosts for a battery of antimicrobial lines of defenses that includes physical and chemical barriers. Due to the antimicrobial properties of volatile compounds of green plants and of chemicals of feather degrading bacteria, the use of aromatic plants and feathers for nest building has been suggested as one of these barriers. However, experimental evidence suggesting such effects is scarce in the literature. During two consecutive years, we explored experimentally the effects of these nest materials on loads of different groups of bacteria (mesophilic bacteria, Enterobacteriaceae, Staphylococcus and Enterococcus) of eggshells in nests of spotless starlings (Sturnus unicolor) at the beginning and at the end of the incubation period. This was also explored in artificial nests without incubation activity. We also experimentally increased bacterial density of eggs in natural and artificial nests and explored the effects of nest lining treatments on eggshell bacterial load. Support for the hypothetical antimicrobial function of nest materials was mainly detected for the year and location with larger average values of eggshell bacterial density. The beneficial effects of feathers and plants were more easily detected in artificial nests with no incubation activity, suggesting an active role of incubation against bacterial colonization of eggshells. Pigmented and unpigmented feathers reduced eggshell bacterial load in starling nests and artificial nest boxes. Results from artificial nests allowed us to discuss and discard alternative scenarios explaining the detected association, particularly those related to the possible sexual role of feathers and aromatic plants in starling nests. All these results considered together confirm the antimicrobial functionality mainly of feathers but also of plants used as nest materials, and highlight the importance of temporally and geographically environmental variation associated with risk of bacterial proliferation determining the strength of such effects. Because of costs associated to nest building, birds should adjust nest building effort to expected bacterial environments during incubation, a prediction that should be further explored.

Nest Material Shapes Eggs Bacterial Environment

PubMed Central

Ruiz-Castellano, Cristina; Tomás, Gustavo; Ruiz-Rodríguez, Magdalena; Martín-Gálvez, David; Soler, Juan José

2016-01-01

Selective pressures imposed by pathogenic microorganisms to embryos have selected in hosts for a battery of antimicrobial lines of defenses that includes physical and chemical barriers. Due to the antimicrobial properties of volatile compounds of green plants and of chemicals of feather degrading bacteria, the use of aromatic plants and feathers for nest building has been suggested as one of these barriers. However, experimental evidence suggesting such effects is scarce in the literature. During two consecutive years, we explored experimentally the effects of these nest materials on loads of different groups of bacteria (mesophilic bacteria, Enterobacteriaceae, Staphylococcus and Enterococcus) of eggshells in nests of spotless starlings (Sturnus unicolor) at the beginning and at the end of the incubation period. This was also explored in artificial nests without incubation activity. We also experimentally increased bacterial density of eggs in natural and artificial nests and explored the effects of nest lining treatments on eggshell bacterial load. Support for the hypothetical antimicrobial function of nest materials was mainly detected for the year and location with larger average values of eggshell bacterial density. The beneficial effects of feathers and plants were more easily detected in artificial nests with no incubation activity, suggesting an active role of incubation against bacterial colonization of eggshells. Pigmented and unpigmented feathers reduced eggshell bacterial load in starling nests and artificial nest boxes. Results from artificial nests allowed us to discuss and discard alternative scenarios explaining the detected association, particularly those related to the possible sexual role of feathers and aromatic plants in starling nests. All these results considered together confirm the antimicrobial functionality mainly of feathers but also of plants used as nest materials, and highlight the importance of temporally and geographically environmental variation associated with risk of bacterial proliferation determining the strength of such effects. Because of costs associated to nest building, birds should adjust nest building effort to expected bacterial environments during incubation, a prediction that should be further explored. PMID:26871451

The Bright, Artificial Intelligence-Augmented Future of Neuroimaging Reading

PubMed Central

Hainc, Nicolin; Federau, Christian; Stieltjes, Bram; Blatow, Maria; Bink, Andrea; Stippich, Christoph

2017-01-01

Radiologists are among the first physicians to be directly affected by advances in computer technology. Computers are already capable of analyzing medical imaging data, and with decades worth of digital information available for training, will an artificial intelligence (AI) one day signal the end of the human radiologist? With the ever increasing work load combined with the looming doctor shortage, radiologists will be pushed far beyond their current estimated 3 s allotted time-of-analysis per image; an AI with super-human capabilities might seem like a logical replacement. We feel, however, that AI will lead to an augmentation rather than a replacement of the radiologist. The AI will be relied upon to handle the tedious, time-consuming tasks of detecting and segmenting outliers while possibly generating new, unanticipated results that can then be used as sources of medical discovery. This will affect not only radiologists but all physicians and also researchers dealing with medical imaging. Therefore, we must embrace future technology and collaborate interdisciplinary to spearhead the next revolution in medicine. PMID:28983278

High-dimensional Controlled-phase Gate Between a 2 N -dimensional Photon and N Three-level Artificial Atoms

NASA Astrophysics Data System (ADS)

Ma, Yun-Ming; Wang, Tie-Jun

2017-10-01

Higher-dimensional quantum system is of great interest owing to the outstanding features exhibited in the implementation of novel fundamental tests of nature and application in various quantum information tasks. High-dimensional quantum logic gate is a key element in scalable quantum computation and quantum communication. In this paper, we propose a scheme to implement a controlled-phase gate between a 2 N -dimensional photon and N three-level artificial atoms. This high-dimensional controlled-phase gate can serve as crucial components of the high-capacity, long-distance quantum communication. We use the high-dimensional Bell state analysis as an example to show the application of this device. Estimates on the system requirements indicate that our protocol is realizable with existing or near-further technologies. This scheme is ideally suited to solid-state integrated optical approaches to quantum information processing, and it can be applied to various system, such as superconducting qubits coupled to a resonator or nitrogen-vacancy centers coupled to a photonic-band-gap structures.

Artificial Intelligence (AI) Based Tactical Guidance for Fighter Aircraft

NASA Technical Reports Server (NTRS)

McManus, John W.; Goodrich, Kenneth H.

1990-01-01

A research program investigating the use of Artificial Intelligence (AI) techniques to aid in the development of a Tactical Decision Generator (TDG) for Within Visual Range (WVR) air combat engagements is discussed. The application of AI programming and problem solving methods in the development and implementation of the Computerized Logic For Air-to-Air Warfare Simulations (CLAWS), a second generation TDG, is presented. The Knowledge-Based Systems used by CLAWS to aid in the tactical decision-making process are outlined in detail, and the results of tests to evaluate the performance of CLAWS versus a baseline TDG developed in FORTRAN to run in real-time in the Langley Differential Maneuvering Simulator (DMS), are presented. To date, these test results have shown significant performance gains with respect to the TDG baseline in one-versus-one air combat engagements, and the AI-based TDG software has proven to be much easier to modify and maintain than the baseline FORTRAN TDG programs. Alternate computing environments and programming approaches, including the use of parallel algorithms and heterogeneous computer networks are discussed, and the design and performance of a prototype concurrent TDG system are presented.

Production of radionuclides in artificial meteorites irradiated isotropically with 600 MeV protons

NASA Technical Reports Server (NTRS)

Michel, R.; Dragovitsch, P.; Englert, P.; Herpers, U.

1986-01-01

The understanding of the production of cosmogenic nuclides in small meteorites (R is less than 40 cm) still is not satisfactory. The existing models for the calculation of depth dependent production rates do not distinguish between the different types of nucleons reacting in a meteorite. They rather use general depth dependent particle fluxes to which cross sections have to be adjusted to fit the measured radionuclide concentrations. Some of these models can not even be extended to zero meteorite sizes without logical contradictions. Therefore, a series of three thick target irradiations was started at the 600 MeV proton beam of the CERN isochronuous cyclotron in order to study the interactions of small stony meteorites with galactic protons. The homogeneous 4 pi irradiation technique used provides a realistic meteorite model which allows a direct comparison of the measured depth profiles with those in real meteorites. Moreover, by the simultaneous measurement of thin target production cross sections one can differentiate between the contributions of primary and secondary nucleons over the entire volume of the artificial meteorite.

Sleep and wake phase of heart beat dynamics by artificial insymmetrised patterns

NASA Astrophysics Data System (ADS)

Dudkowska, A.; Makowiec, D.

2004-05-01

In order to determine differences between healthy patients and patients with congestive heart failure we apply the artificial insymmetrised pattern (AIP) method. The AIP method by exploring a human eye ability to extract regularities and read symmetries in a dot pattern, serves a tool for qualitative discrimination of heart rate states.

The Influence of Consistency, Frequency, and Semantics on Learning to Read: An Artificial Orthography Paradigm

ERIC Educational Resources Information Center

Taylor, J. S. H.; Plunkett, Kim; Nation, Kate

2011-01-01

Two experiments explored learning, generalization, and the influence of semantics on orthographic processing in an artificial language. In Experiment 1, 16 adults learned to read 36 novel words written in novel characters. Posttraining, participants discriminated trained from untrained items and generalized to novel items, demonstrating extraction…

Nanomaterials with enzyme-like characteristics (nanozymes): next-generation artificial enzymes.

PubMed

Wei, Hui; Wang, Erkang

2013-07-21

Over the past few decades, researchers have established artificial enzymes as highly stable and low-cost alternatives to natural enzymes in a wide range of applications. A variety of materials including cyclodextrins, metal complexes, porphyrins, polymers, dendrimers and biomolecules have been extensively explored to mimic the structures and functions of naturally occurring enzymes. Recently, some nanomaterials have been found to exhibit unexpected enzyme-like activities, and great advances have been made in this area due to the tremendous progress in nano-research and the unique characteristics of nanomaterials. To highlight the progress in the field of nanomaterial-based artificial enzymes (nanozymes), this review discusses various nanomaterials that have been explored to mimic different kinds of enzymes. We cover their kinetics, mechanisms and applications in numerous fields, from biosensing and immunoassays, to stem cell growth and pollutant removal. We also summarize several approaches to tune the activities of nanozymes. Finally, we make comparisons between nanozymes and other catalytic materials (other artificial enzymes, natural enzymes, organic catalysts and nanomaterial-based catalysts) and address the current challenges and future directions (302 references).

Characterizing precipitate evolution of an Al–Zn–Mg–Cu-based commercial alloy during artificial aging and non-isothermal heat treatments by in situ electrical resistivity monitoring

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

Jiang, Fulin; Department of Materials Science and Engineering, McMaster University, 1280 Main Street West, Hamilton, Ontario L8S 4L7; Zurob, Hatem S., E-mail: zurobh@mcmaster.ca

In situ electrical resistivity monitoring technique was employed to continuously evaluate the precipitate evolution of an Al–Zn–Mg–Cu-based commercial alloy during typical artificial aging treatments. The effects of artificial aging on the precipitates stability during non-isothermal heat treatments were also explored. Conventional hardness test, transmission electron microscopy and differential scanning calorimetry were also adopted to verify the electrical resistivity results. The results indicated that both the precipitation process and its timely rate could be followed by the monitored electrical resistivity during artificial aging treatments. The electrical resistivity results gave overall information on continuous precipitation and dissolution processes, especially under high heatingmore » rates. Samples artificial aging heat treated at 120 °C for 24 h followed by aging at 150 °C for 24 h presented more stable state and coarser precipitates than the samples only artificial aging heat treated at 120 °C for 24 h or triple artificial aging heat treated at 120 °C/24 h + 195 °C/15 min + 120 °/24 h. While the incoherent η precipitates in the samples artificial aging heat treated at 120 °C for 24 h followed by aging at 150 °C for 24 h were more easiness to coarsening and dissolve during non-isothermal heat treatments as well. - Highlights: • In situ electrical resistivity monitoring technique was employed on an Al-Zn-Mg-Cu alloy. • The precipitate evolution during typical artificial aging treatments was studied. • The precipitate stability during non-isothermal heat treatments was explored. • The electrical resistivity wonderfully monitored continuous precipitation and dissolution. • The alloy submitted to a T7 treatment presents a more stable state during heating due to incoherent η precipitates.« less

Modelling Of Anticipated Damage Ratio On Breakwaters Using Fuzzy Logic

NASA Astrophysics Data System (ADS)

Mercan, D. E.; Yagci, O.; Kabdasli, S.

2003-04-01

In breakwater design the determination of armour unit weight is especially important in terms of the structure's life. In a typical experimental breakwater stability study, different wave series composed of different wave heights; wave period and wave steepness characteristics are applied in order to investigate performance the structure. Using a classical approach, a regression equation is generated for damage ratio as a function of characteristic wave height. The parameters wave period and wave steepness are not considered. In this study, differing from the classical approach using a fuzzy logic, a relationship between damage ratio as a function of mean wave period (T_m), wave steepness (H_s/L_m) and significant wave height (H_s) was further generated. The system's inputs were mean wave period (T_m), wave steepness (H_s/L_m) and significant wave height (H_s). For fuzzification all input variables were divided into three fuzzy subsets, their membership functions were defined using method developed by Mandani (Mandani, 1974) and the rules were written. While for defuzzification the centroid method was used. In order to calibrate and test the generated models an experimental study was conducted. The experiments were performed in a wave flume (24 m long, 1.0 m wide and 1.0 m high) using 20 different irregular wave series (P-M spectrum). Throughout the study, the water depth was 0.6 m and the breakwater cross-sectional slope was 1V/2H. In the armour layer, a type of artificial armour unit known as antifer cubes were used. The results of the established fuzzy logic model and regression equation model was compared with experimental data and it was determined that the established fuzzy logic model gave a more accurate prediction of the damage ratio on this type of breakwater. References Mandani, E.H., "Application of Fuzzy Algorithms for Control of Simple Dynamic Plant", Proc. IEE, vol. 121, no. 12, December 1974.

[Artificial organs].

PubMed

Raguin, Thibaut; Dupret-Bories, Agnès; Debry, Christian

2017-01-01

Research has been fighting against organ failure and shortage of donations by supplying artificial organs for many years. With the raise of new technologies, tissue engineering and regenerative medicine, many organs can benefit of an artificial equivalent: thanks to retinal implants some blind people can visualize stimuli, an artificial heart can be proposed in case of cardiac failure while awaiting for a heart transplant, artificial larynx enables laryngectomy patients to an almost normal life, while the diabetic can get a glycemic self-regulation controlled by smartphones with an artificial device. Dialysis devices become portable, as well as the oxygenation systems for terminal respiratory failure. Bright prospects are being explored or might emerge in a near future. However, the retrospective assessment of putative side effects is not yet sufficient. Finally, the cost of these new devices is significant even if the advent of three dimensional printers may reduce it. © 2017 médecine/sciences – Inserm.

Constraint Logic Programming approach to protein structure prediction.

PubMed

Dal Palù, Alessandro; Dovier, Agostino; Fogolari, Federico

2004-11-30

The protein structure prediction problem is one of the most challenging problems in biological sciences. Many approaches have been proposed using database information and/or simplified protein models. The protein structure prediction problem can be cast in the form of an optimization problem. Notwithstanding its importance, the problem has very seldom been tackled by Constraint Logic Programming, a declarative programming paradigm suitable for solving combinatorial optimization problems. Constraint Logic Programming techniques have been applied to the protein structure prediction problem on the face-centered cube lattice model. Molecular dynamics techniques, endowed with the notion of constraint, have been also exploited. Even using a very simplified model, Constraint Logic Programming on the face-centered cube lattice model allowed us to obtain acceptable results for a few small proteins. As a test implementation their (known) secondary structure and the presence of disulfide bridges are used as constraints. Simplified structures obtained in this way have been converted to all atom models with plausible structure. Results have been compared with a similar approach using a well-established technique as molecular dynamics. The results obtained on small proteins show that Constraint Logic Programming techniques can be employed for studying protein simplified models, which can be converted into realistic all atom models. The advantage of Constraint Logic Programming over other, much more explored, methodologies, resides in the rapid software prototyping, in the easy way of encoding heuristics, and in exploiting all the advances made in this research area, e.g. in constraint propagation and its use for pruning the huge search space.

Quantum cellular automata

NASA Astrophysics Data System (ADS)

Porod, Wolfgang; Lent, Craig S.; Bernstein, Gary H.

1994-06-01

The Notre Dame group has developed a new paradigm for ultra-dense and ultra-fast information processing in nanoelectronic systems. These Quantum Cellular Automata (QCA's) are the first concrete proposal for a technology based on arrays of coupled quantum dots. The basic building block of these cellular arrays is the Notre Dame Logic Cell, as it has been called in the literature. The phenomenon of Coulomb exclusion, which is a synergistic interplay of quantum confinement and Coulomb interaction, leads to a bistable behavior of each cell which makes possible their use in large-scale cellular arrays. The physical interaction between neighboring cells has been exploited to implement logic functions. New functionality may be achieved in this fashion, and the Notre Dame group invented a versatile majority logic gate. In a series of papers, the feasibility of QCA wires, wire crossing, inverters, and Boolean logic gates was demonstrated. A major finding is that all logic functions may be integrated in a hierarchial fashion which allows the design of complicated QCA structures. The most complicated system which was simulated to date is a one-bit full adder consisting of some 200 cells. In addition to exploring these new concepts, efforts are under way to physically realize such structures both in semiconductor and metal systems. Extensive modeling work of semiconductor quantum dot structures has helped identify optimum design parameters for QCA experimental implementations.

Internet advertising of artificial tanning in Australia.

PubMed

Team, Victoria; Markovic, Milica

2006-08-01

Artificial tanning, defined as deliberate exposure to ultraviolet rays produced by artificial tanning devices, is a new and emerging public health issue in Australia and globally. Epidemiological research suggests that artificial tanning may contribute to the incidence of melanoma, nonmelanoma skin cancer as well as other health problems. Given that Australia has a high incidence of skin cancer, we have undertaken a study to explore how artificial tanning has been promoted to its users. The aim was to analyze the completeness and accuracy of information about artificial tanning. A content analysis of web sites of tanning salons and distributors of tanning equipment in Australia was conducted. A total of 22 web sites were analyzed. None of the solarium operators or distributors of equipment provided full information about the risks of artificial tanning. Fifty-nine percent of web advertisements had no information and 41% provided only partial information regarding the risks of artificial tanning. Pictures with the image of bronze-tanned bodies, predominantly women, were used by all web advertisers. In light of the success of sun-safety campaigns in Australia, the findings of future epidemiological research on the prevalence of artificial tanning and sociological and anthropological research on why people utilize artificial tanning should be a basis for developing effective targeted health promotion on the elimination of artificial tanning in the country.

Temporal abstraction and inductive logic programming for arrhythmia recognition from electrocardiograms.

PubMed

Carrault, G; Cordier, M-O; Quiniou, R; Wang, F

2003-07-01

This paper proposes a novel approach to cardiac arrhythmia recognition from electrocardiograms (ECGs). ECGs record the electrical activity of the heart and are used to diagnose many heart disorders. The numerical ECG is first temporally abstracted into series of time-stamped events. Temporal abstraction makes use of artificial neural networks to extract interesting waves and their features from the input signals. A temporal reasoner called a chronicle recogniser processes such series in order to discover temporal patterns called chronicles which can be related to cardiac arrhythmias. Generally, it is difficult to elicit an accurate set of chronicles from a doctor. Thus, we propose to learn automatically from symbolic ECG examples the chronicles discriminating the arrhythmias belonging to some specific subset. Since temporal relationships are of major importance, inductive logic programming (ILP) is the tool of choice as it enables first-order relational learning. The approach has been evaluated on real ECGs taken from the MIT-BIH database. The performance of the different modules as well as the efficiency of the whole system is presented. The results are rather good and demonstrate that integrating numerical techniques for low level perception and symbolic techniques for high level classification is very valuable.

On the discrimination between nucleation and propagation in nanomagnetic logic devices

NASA Astrophysics Data System (ADS)

Ziemys, Grazvydas; Csaba, Gyorgy; Becherer, Markus

2018-05-01

In this paper we present the extensive nucleation and propagation characterization of fabricated nanomagnets by applying ns-range magnetic field pulses. For that, an artificial nucleation center (ANC) is created by focused ion beam irradiation (FIB) of a 50 x 50 nm area at the side of a Co/Pt island as typically used in Nanomagnetic Logic with perpendicular anisotropy (pNML). Laser-Kerr Microscope is applied for statistical evaluation of the switching probability of the whole magnet, while the wide-field-Kerr microscopy is employed to discriminate between the nucleation process (which takes place at the irradiated ANC area) and the domain wall propagation process along the magnet. We show that the nanomagnet can be treated as a single Stoner-Wolfhart particle above 100 ns field-pulse width, as the whole magnetization is switched during the field-pulse. By contrary, for field-pulse width below 100 ns, the domain wall (DW) motion is the limiting process hindering full magnetization reversal on that time-scale. However, the nucleation still follows the Arrhenius law. The results allow precise understanding of the reversal process and highlight the need for faster DW speed in pNML materials.

Using Sorting Networks for Skill Building and Reasoning

ERIC Educational Resources Information Center

Andre, Robert; Wiest, Lynda R.

2007-01-01

Sorting networks, used in graph theory, have instructional value as a skill- building tool as well as an interesting exploration in discrete mathematics. Students can practice mathematics facts and develop reasoning and logic skills with this topic. (Contains 4 figures.)

A reconfigurable on-line learning spiking neuromorphic processor comprising 256 neurons and 128K synapses.

PubMed

Qiao, Ning; Mostafa, Hesham; Corradi, Federico; Osswald, Marc; Stefanini, Fabio; Sumislawska, Dora; Indiveri, Giacomo

2015-01-01

Implementing compact, low-power artificial neural processing systems with real-time on-line learning abilities is still an open challenge. In this paper we present a full-custom mixed-signal VLSI device with neuromorphic learning circuits that emulate the biophysics of real spiking neurons and dynamic synapses for exploring the properties of computational neuroscience models and for building brain-inspired computing systems. The proposed architecture allows the on-chip configuration of a wide range of network connectivities, including recurrent and deep networks, with short-term and long-term plasticity. The device comprises 128 K analog synapse and 256 neuron circuits with biologically plausible dynamics and bi-stable spike-based plasticity mechanisms that endow it with on-line learning abilities. In addition to the analog circuits, the device comprises also asynchronous digital logic circuits for setting different synapse and neuron properties as well as different network configurations. This prototype device, fabricated using a 180 nm 1P6M CMOS process, occupies an area of 51.4 mm(2), and consumes approximately 4 mW for typical experiments, for example involving attractor networks. Here we describe the details of the overall architecture and of the individual circuits and present experimental results that showcase its potential. By supporting a wide range of cortical-like computational modules comprising plasticity mechanisms, this device will enable the realization of intelligent autonomous systems with on-line learning capabilities.

A seasonal forecast scheme for the Inner Mongolia spring drought part-II: a logical reasoning evidence-based method for spring predictions

NASA Astrophysics Data System (ADS)

Gao, Tao; Wulan, Wulan; Yu, Xiao; Yang, Zelong; Gao, Jing; Hua, Weiqi; Yang, Peng; Si, Yaobing

2018-05-01

Spring precipitation is the predominant factor that controls meteorological drought in Inner Mongolia (IM), China. This study used the anomaly percentage of spring precipitation (PAP) as a drought index to measure spring drought. A scheme for forecasting seasonal drought was designed based on evidence of spring drought occurrence and speculative reasoning methods introduced in computer artificial intelligence theory. Forecast signals with sufficient lead-time for predictions of spring drought were extracted from eight crucial areas of oceans and 500-hPa geopotential height. Using standardized values, these signals were synthesized into three examples of spring drought evidence (SDE) depending on their primary effects on three major atmospheric circulation components of spring precipitation in IM: the western Pacific subtropical high, North Polar vortex, and East Asian trough. Thresholds for the SDE were determined following numerical analyses of the influential factors. Furthermore, five logical reasoning rules for distinguishing the occurrence of SDE were designed after examining all possible combined cases. The degree of confidence in the rules was determined based on estimations of their prior probabilities. Then, an optimized logical reasoning scheme was identified for judging the possibility of spring drought. The scheme was successful in hindcast predictions of 11 of the 16 (accuracy: 68.8%) spring droughts that have occurred during 1960-2009. Moreover, the accuracy ratio for the same period was 82.0% for drought (PAP ≤ -20%) or not (PAP > -20%). Predictions for the recent 6-year period (2010-2015) demonstrated successful outcomes.

Toward a generalized and high-throughput enzyme screening system based on artificial genetic circuits.

PubMed

Choi, Su-Lim; Rha, Eugene; Lee, Sang Jun; Kim, Haseong; Kwon, Kilkoang; Jeong, Young-Su; Rhee, Young Ha; Song, Jae Jun; Kim, Hak-Sung; Lee, Seung-Goo

2014-03-21

Large-scale screening of enzyme libraries is essential for the development of cost-effective biological processes, which will be indispensable for the production of sustainable biobased chemicals. Here, we introduce a genetic circuit termed the Genetic Enzyme Screening System that is highly useful for high-throughput enzyme screening from diverse microbial metagenomes. The circuit consists of two AND logics. The first AND logic, the two inputs of which are the target enzyme and its substrate, is responsible for the accumulation of a phenol compound in cell. Then, the phenol compound and its inducible transcription factor, whose activation turns on the expression of a reporter gene, interact in the other logic gate. We confirmed that an individual cell harboring this genetic circuit can present approximately a 100-fold higher cellular fluorescence than the negative control and can be easily quantified by flow cytometry depending on the amounts of phenolic derivatives. The high sensitivity of the genetic circuit enables the rapid discovery of novel enzymes from metagenomic libraries, even for genes that show marginal activities in a host system. The crucial feature of this approach is that this single system can be used to screen a variety of enzymes that produce a phenol compound from respective synthetic phenyl-substrates, including cellulase, lipase, alkaline phosphatase, tyrosine phenol-lyase, and methyl parathion hydrolase. Consequently, the highly sensitive and quantitative nature of this genetic circuit along with flow cytometry techniques could provide a widely applicable toolkit for discovering and engineering novel enzymes at a single cell level.

Experimental Verification of Electric Drive Technologies Based on Artificial Intelligence Tools

NASA Technical Reports Server (NTRS)

Rubaai, Ahmed; Kankam, David (Technical Monitor)

2003-01-01

A laboratory implementation of a fuzzy logic-tracking controller using a low cost Motorola MC68HC11E9 microprocessor is described in this report. The objective is to design the most optimal yet practical controller that can be implemented and marketed, and which gives respectable performance, even when the system loads, inertia and parameters are varying. A distinguishing feature of this work is the by-product goal of developing a marketable, simple, functional and low cost controller. Additionally, real-time nonlinearities are not ignored, and a mathematical model is not required. A number of components have been designed, built and tested individually, and in various combinations of hardware and software segments. These components have been integrated with a brushless motor to constitute the drive system. A microprocessor-based FLC is incorporated to provide robust speed and position control. Design objectives that are difficult to express mathematically can be easily incorporated in a fuzzy logic-based controller by linguistic information (in the form of fuzzy IF-THEN rules). The theory and design are tested in the laboratory using a hardware setup. Several test cases have been conducted to confirm the effectiveness of the proposed controller. The results indicate excellent tracking performance for both speed and position trajectories. For the purpose of comparison, a bang-bang controller has been tested. The fuzzy logic controller performs significantly better than the traditional bang-bang controller. The bang-bang controller has been shown to be relatively inaccurate and lacking in robustness. Description of the implementation hardware system is also given.

Expert system for surveillance and diagnosis of breach fuel elements

DOEpatents

Gross, K.C.

1988-01-21

An apparatus and method are disclosed for surveillance and diagnosis of breached fuel elements in a nuclear reactor. A delayed neutron monitoring system provides output signals indicating the delayed neutron activity and age and the equivalent recoil area of a breached fuel element. Sensors are used to provide outputs indicating the status of each component of the delayed neutron monitoring system. Detectors also generate output signals indicating the reactor power level and the primary coolant flow rate of the reactor. The outputs from the detectors and sensors are interfaced with an artificial intelligence-based knowledge system which implements predetermined logic and generates output signals indicating the operability of the reactor. 2 figs.

Expert system for surveillance and diagnosis of breach fuel elements

DOEpatents

Gross, Kenny C.

1989-01-01

An apparatus and method are disclosed for surveillance and diagnosis of breached fuel elements in a nuclear reactor. A delayed neutron monitoring system provides output signals indicating the delayed neutron activity and age and the equivalent recoil areas of a breached fuel element. Sensors are used to provide outputs indicating the status of each component of the delayed neutron monitoring system. Detectors also generate output signals indicating the reactor power level and the primary coolant flow rate of the reactor. The outputs from the detectors and sensors are interfaced with an artificial intelligence-based knowledge system which implements predetermined logic and generates output signals indicating the operability of the reactor.

Smart sensorless prediction diagnosis of electric drives

NASA Astrophysics Data System (ADS)

Kruglova, TN; Glebov, NA; Shoshiashvili, ME

2017-10-01

In this paper, the discuss diagnostic method and prediction of the technical condition of an electrical motor using artificial intelligent method, based on the combination of fuzzy logic and neural networks, are discussed. The fuzzy sub-model determines the degree of development of each fault. The neural network determines the state of the object as a whole and the number of serviceable work periods for motors actuator. The combination of advanced techniques reduces the learning time and increases the forecasting accuracy. The experimental implementation of the method for electric drive diagnosis and associated equipment is carried out at different speeds. As a result, it was found that this method allows troubleshooting the drive at any given speed.

A proto-architecture for innate directionally selective visual maps.

PubMed

Adams, Samantha V; Harris, Chris M

2014-01-01

Self-organizing artificial neural networks are a popular tool for studying visual system development, in particular the cortical feature maps present in real systems that represent properties such as ocular dominance (OD), orientation-selectivity (OR) and direction selectivity (DS). They are also potentially useful in artificial systems, for example robotics, where the ability to extract and learn features from the environment in an unsupervised way is important. In this computational study we explore a DS map that is already latent in a simple artificial network. This latent selectivity arises purely from the cortical architecture without any explicit coding for DS and prior to any self-organising process facilitated by spontaneous activity or training. We find DS maps with local patchy regions that exhibit features similar to maps derived experimentally and from previous modeling studies. We explore the consequences of changes to the afferent and lateral connectivity to establish the key features of this proto-architecture that support DS.

[Suitable investigation method of exploration and suggestions for investigating Chinese materia medica resources from wetland and artificial water of Hongze Lake region].

PubMed

Liu, Rui; Yan, Hui; Duan, Jin-Ao; Liu, Xing-Jian; Ren, Quan-Jin; Li, Hui-Wei; Bao, Bei-Hua; Zhang, Zhao-Hui

2016-08-01

According to the technology requirements of the fourth national survey of Chinese Materia Medica resources (pilot), suitable investigation method of exploration and suggestions for investigating Chinese Materia Medica resources was proposed based on the type of wetland and artificial water of Hongze Lake region. Environment of Hongze Lake and overview of wetland, present situation of ecology and vegetation and vegetation distribution were analyzed. Establishment of survey plan, selection of sample area and sample square and confirmation of representative water area survey plan were all suggested. The present study provide references for improving Chinese materia medica resources survey around Hongze Lake, and improving the technical specifications. It also provide references for investigating Chinese Materia Medica resources survey on similar ecological environment under the condition of artificial intervention. Copyright© by the Chinese Pharmaceutical Association.

An organic jelly made fractal logic gate with an infinite truth table

PubMed Central

Ghosh, Subrata; Fujita, Daisuke; Bandyopadhyay, Anirban

2015-01-01

Widely varying logic gates invented over a century are all finite. As data deluge problem looms large on the information processing and communication industry, the thrust to explore radical concepts is increasing rapidly. Here, we design and synthesis a molecule, wherein, the input energy transmits in a cycle inside the molecular system, just like an oscillator, then, we use the molecule to make a jelly that acts as chain of oscillators with a fractal like resonance band. Hence, with the increasing detection resolution, in the vacant space between two energy levels of a given resonance band, a new band appears, due to fractal nature, generation of newer energy levels never stops. This is natural property of a linear chain oscillator. As we correlate each energy level of the resonance band of organic jelly, as a function of pH and density of the jelly, we realize a logic gate, whose truth table is finite, but if we zoom any small part, a new truth table appears. In principle, zooming of truth table would continue forever. Thus, we invent a new class of infinite logic gate for the first time. PMID:26086417

LEGO-MM: LEarning structured model by probabilistic loGic Ontology tree for MultiMedia.

PubMed

Tang, Jinhui; Chang, Shiyu; Qi, Guo-Jun; Tian, Qi; Rui, Yong; Huang, Thomas S

2016-09-22

Recent advances in Multimedia ontology have resulted in a number of concept models, e.g., LSCOM and Mediamill 101, which are accessible and public to other researchers. However, most current research effort still focuses on building new concepts from scratch, very few work explores the appropriate method to construct new concepts upon the existing models already in the warehouse. To address this issue, we propose a new framework in this paper, termed LEGO1-MM, which can seamlessly integrate both the new target training examples and the existing primitive concept models to infer the more complex concept models. LEGOMM treats the primitive concept models as the lego toy to potentially construct an unlimited vocabulary of new concepts. Specifically, we first formulate the logic operations to be the lego connectors to combine existing concept models hierarchically in probabilistic logic ontology trees. Then, we incorporate new target training information simultaneously to efficiently disambiguate the underlying logic tree and correct the error propagation. Extensive experiments are conducted on a large vehicle domain data set from ImageNet. The results demonstrate that LEGO-MM has significantly superior performance over existing state-of-the-art methods, which build new concept models from scratch.

Artificial ferroic systems: novel functionality from structure, interactions and dynamics.

PubMed

Heyderman, L J; Stamps, R L

2013-09-11

Lithographic processing and film growth technologies are continuing to advance, so that it is now possible to create patterned ferroic materials consisting of arrays of sub-1 μm elements with high definition. Some of the most fascinating behaviour of these arrays can be realised by exploiting interactions between the individual elements to create new functionality. The properties of these artificial ferroic systems differ strikingly from those of their constituent components, with novel emergent behaviour arising from the collective dynamics of the interacting elements, which are arranged in specific designs and can be activated by applying magnetic or electric fields. We first focus on artificial spin systems consisting of arrays of dipolar-coupled nanomagnets and, in particular, review the field of artificial spin ice, which demonstrates a wide range of fascinating phenomena arising from the frustration inherent in particular arrangements of nanomagnets, including emergent magnetic monopoles, domains of ordered macrospins, and novel avalanche behaviour. We outline how demagnetisation protocols have been employed as an effective thermal anneal in an attempt to reach the ground state, comment on phenomena that arise in thermally activated systems and discuss strategies for selectively generating specific configurations using applied magnetic fields. We then move on from slow field and temperature driven dynamics to high frequency phenomena, discussing spinwave excitations in the context of magnonic crystals constructed from arrays of patterned magnetic elements. At high frequencies, these arrays are studied in terms of potential applications including magnetic logic, linear and non-linear microwave optics, and fast, efficient switching, and we consider the possibility to create tunable magnonic crystals with artificial spin ice. Finally, we discuss how functional ferroic composites can be incorporated to realise magnetoelectric effects. Specifically, we discuss artificial multiferroics (or multiferroic composites), which hold promise for new applications that involve electric field control of magnetism, or electric and magnetic field responsive devices for high frequency integrated circuit design in microwave and terahertz signal processing. We close with comments on how enhanced functionality can be realised through engineering of nanostructures with interacting ferroic components, creating opportunities for novel spin electronic devices that, for example, make use of the transport of magnetic charges, thermally activated elements, and reprogrammable nanomagnet systems.

Use of an Artificial Neural Network to Construct a Model of Predicting Deep Fungal Infection in Lung Cancer Patients.

PubMed

Chen, Jian; Chen, Jie; Ding, Hong-Yan; Pan, Qin-Shi; Hong, Wan-Dong; Xu, Gang; Yu, Fang-You; Wang, Yu-Min

2015-01-01

The statistical methods to analyze and predict the related dangerous factors of deep fungal infection in lung cancer patients were several, such as logic regression analysis, meta-analysis, multivariate Cox proportional hazards model analysis, retrospective analysis, and so on, but the results are inconsistent. A total of 696 patients with lung cancer were enrolled. The factors were compared employing Student's t-test or the Mann-Whitney test or the Chi-square test and variables that were significantly related to the presence of deep fungal infection selected as candidates for input into the final artificial neural network analysis (ANN) model. The receiver operating characteristic (ROC) and area under curve (AUC) were used to evaluate the performance of the artificial neural network (ANN) model and logistic regression (LR) model. The prevalence of deep fungal infection from lung cancer in this entire study population was 32.04%(223/696), deep fungal infections occur in sputum specimens 44.05% (200/454). The ratio of candida albicans was 86.99% (194/223) in the total fungi. It was demonstrated that older (≥65 years), use of antibiotics, low serum albumin concentrations (≤37.18 g /L), radiotherapy, surgery, low hemoglobin hyperlipidemia (≤93.67 g /L), long time of hospitalization (≥14 days) were apt to deep fungal infection and the ANN model consisted of the seven factors. The AUC of ANN model (0.829±0.019) was higher than that of LR model (0.756±0.021). The artificial neural network model with variables consisting of age, use of antibiotics, serum albumin concentrations, received radiotherapy, received surgery, hemoglobin, time of hospitalization should be useful for predicting the deep fungal infection in lung cancer.

Using Dual-Task Methodology to Dissociate Automatic from Nonautomatic Processes Involved in Artificial Grammar Learning

ERIC Educational Resources Information Center

Hendricks, Michelle A.; Conway, Christopher M.; Kellogg, Ronald T.

2013-01-01

Previous studies have suggested that both automatic and intentional processes contribute to the learning of grammar and fragment knowledge in artificial grammar learning (AGL) tasks. To explore the relative contribution of automatic and intentional processes to knowledge gained in AGL, we utilized dual-task methodology to dissociate automatic and…

Elective Inactivation of Total Artificial Heart Technology in Non-Futile Situations: Inpatients, Outpatients and Research Participants

ERIC Educational Resources Information Center

Bramstedt, Katrina A.

2004-01-01

Total artificial heart technology as a potential clinical therapy raises the issue of elective device inactivation in both futile and non-futile situations. This article explores elective device inactivation in non-futile situations. In reply to such requests for inactivation, the medical team should reflect on the individual's decision-making…

The four antinomies of the death instinct.

PubMed

Blanco, Ignacio Matte

2005-10-01

Matte Blanco examines four paradoxical positions that arise out of Freud's writings on the death instinct. He notes that death is not a content known to the unconscious. Furthermore, the absence of time and space in the unconscious means that the conditions necessary for any process such as instinct are similarly absent. Matte Blanco demonstrates the way in which the antinomies that he explores can be explained in terms of the logics that obtain in the unconscious, and he suggests that the concept of the death instinct is one of the most profound expressions of the relationship between the modes that underlie conscious and unconscious logic.

Generalized Rainich conditions, generalized stress-energy conditions, and the Hawking-Ellis classification

NASA Astrophysics Data System (ADS)

Martín–Moruno, Prado; Visser, Matt

2017-11-01

The (generalized) Rainich conditions are algebraic conditions which are polynomial in the (mixed-component) stress-energy tensor. As such they are logically distinct from the usual classical energy conditions (NEC, WEC, SEC, DEC), and logically distinct from the usual Hawking-Ellis (Segré-Plebański) classification of stress-energy tensors (type I, type II, type III, type IV). There will of course be significant inter-connections between these classification schemes, which we explore in the current article. Overall, we shall argue that it is best to view the (generalized) Rainich conditions as a refinement of the classical energy conditions and the usual Hawking-Ellis classification.

Programmable Logic Application Notes

NASA Technical Reports Server (NTRS)

Katz, Richard

1999-01-01

This column will be provided each quarter as a source for reliability, radiation results, NASA capabilities, and other information on programmable logic devices and related applications. This quarter the focus is on some experimental data on low voltage drop out regulators to support mixed 5 and 3.3 volt systems. A discussion of the Small Explorer WIRE spacecraft will also be given. Lastly, we show take a first look at robust state machines in Hardware Description Languages (VHDL) and their use in critical systems. If you have information that you would like to submit or an area you would like discussed or researched, please give me a call or e-mail.

On the Equivalence of Formal Grammars and Machines.

ERIC Educational Resources Information Center

Lund, Bruce

1991-01-01

Explores concepts of formal language and automata theory underlying computational linguistics. A computational formalism is described known as a "logic grammar," with which computational systems process linguistic data, with examples in declarative and procedural semantics and definite clause grammars. (13 references) (CB)

Math is Functional! A Math Fair for Kids.

ERIC Educational Resources Information Center

Reys, Barbara J.; Wasman, Deanna G.

1998-01-01

Describes a mathematics fair prepared by the University of Missouri Mathematics Teachers Organization (UM2TO) which includes games involving numbers and computation, logic puzzles, geometry and spatial-visualization exploration, and probability and statistics activities. Presents tips for developing a mathematics fair. (ASK)

Computational Analysis of Artificial Gravity as a Possible Countermeasure to Spaceflight Induced Bone Loss

NASA Technical Reports Server (NTRS)

Mulugeta, L.; Werner, C. R.; Pennline, J. A.

2015-01-01

During exploration class missions, such as to asteroids and Mars, astronauts will be exposed to reduced gravity for extended periods. Data has shown that astronauts lose bone mass at a rate of 1% to 2% a month in microgravity, particularly in lower extremities such as the proximal femur. Exercise countermeasures have not completely eliminated bone loss from long duration spaceflight missions, which leaves astronauts susceptible to early onset osteoporosis and greater risk of fracture. Introduction of the Advanced Resistive Exercise Device and other large exercise devices on the International Space Station (ISS), coupled with improved nutrition, has further minimized bone loss. However, unlike the ISS, exploration vehicles will have very limited volume and power available to accommodate such capabilities. Therefore, novel concepts like artificial gravity systems are being explored as a means to provide sufficient load stimulus to the musculoskeletal system to mitigate bone changes that may lead to early onset osteoporosis and increased risk of fracture. Currently, there is minimal data available to drive further research and development efforts to appropriately explore such options. Computational modeling can be leveraged to gain insight on the level of osteoprotection that may be achieved using artificial gravity produced by a spinning spacecraft or centrifuge. With this in mind, NASA's Digital Astronaut Project (DAP) has developed a bone remodeling model that has been validated for predicting volumetric bone mineral density (vBMD) changes of trabecular and cortical bone both for gravitational unloading condition and the equivalent of 1g daily load stimulus. Using this model, it is possible to simulate vBMD changes in trabecular and cortical bone under different gravity conditions. In this presentation, we will discuss our preliminary findings regarding if and how artificial gravity may be used to mitigate spaceflight induced bone loss.

Strategy for outer planets exploration

NASA Technical Reports Server (NTRS)

1975-01-01

NASA's Planetary Programs Office formed a number of scientific working groups to study in depth the potential scientific return from the various candidate missions to the outer solar system. The results of these working group studies were brought together in a series of symposia to evaluate the potential outer planet missions and to discuss strategies for exploration of the outer solar system that were consistent with fiscal constraints and with anticipated spacecraft and launch vehicle capabilities. A logical, scientifically sound, and cost effective approach to exploration of the outer solar system is presented.

Microbial ecology of the closed artificial ecosystem MELiSSA (Micro-Ecological Life Support System Alternative): reinventing and compartmentalizing the Earth's food and oxygen regeneration system for long-haul space exploration missions.

PubMed

Hendrickx, Larissa; De Wever, Heleen; Hermans, Veronik; Mastroleo, Felice; Morin, Nicolas; Wilmotte, Annick; Janssen, Paul; Mergeay, Max

2006-01-01

MELiSSA is a bioregenerative life support system designed by the European Space Agency (ESA) for the complete recycling of gas, liquid and solid wastes during long distance space exploration. The system uses the combined activity of different living organisms: microbial cultures in bioreactors, a plant compartment and a human crew. In this minireview, the development of a short-cut ecological system for the biotransformation of organic waste is discussed from a microorganism's perspective. The artificial ecological model--still in full development--that is inspired by Earth's own geomicrobiological ecosystem serves as an ideal study object on microbial ecology and will become an indispensable travel companion in manned space exploration.

The effect of artificial bulk viscosity in simulations of forced compressible turbulence

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

Campos, A.; Morgan, B.

The use of an artificial bulk viscosity for shock stabilization is a common approach employed in turbulence simulations with high-order numerics. The effect of the artificial bulk viscosity is analyzed in the context of large eddy simulations by using as a test case simulations of linearly-forced compressible homogeneous turbulence (Petersen and Livescu, 2010 [12]). This case is unique in that it allows for the specification of a priori target values for total dissipation and ratio of solenoidal to dilatational dissipation. A comparison between these target values and the true predicted levels of dissipation is thus used to investigate the performancemore » of the artificial bulk viscosity. Results show that the artificial bulk viscosity is effective at achieving stable solutions, but also leads to large values of artificial dissipation that outweigh the physical dissipation caused by fluid viscosity. An alternate approach, which employs the artificial thermal conductivity only, shows that the dissipation of dilatational modes is entirely due to the fluid viscosity. However, this method leads to unwanted Gibbs oscillations around the shocklets. The use of shock sensors that further localize the artificial bulk viscosity did not reduce the amount of artificial dissipation introduced by the artificial bulk viscosity. Finally, an improved forcing function that explicitly accounts for the role of the artificial bulk viscosity in the budget of turbulent kinetic energy was explored.« less

The effect of artificial bulk viscosity in simulations of forced compressible turbulence

DOE PAGES

Campos, A.; Morgan, B.

2018-05-17

The use of an artificial bulk viscosity for shock stabilization is a common approach employed in turbulence simulations with high-order numerics. The effect of the artificial bulk viscosity is analyzed in the context of large eddy simulations by using as a test case simulations of linearly-forced compressible homogeneous turbulence (Petersen and Livescu, 2010 [12]). This case is unique in that it allows for the specification of a priori target values for total dissipation and ratio of solenoidal to dilatational dissipation. A comparison between these target values and the true predicted levels of dissipation is thus used to investigate the performancemore » of the artificial bulk viscosity. Results show that the artificial bulk viscosity is effective at achieving stable solutions, but also leads to large values of artificial dissipation that outweigh the physical dissipation caused by fluid viscosity. An alternate approach, which employs the artificial thermal conductivity only, shows that the dissipation of dilatational modes is entirely due to the fluid viscosity. However, this method leads to unwanted Gibbs oscillations around the shocklets. The use of shock sensors that further localize the artificial bulk viscosity did not reduce the amount of artificial dissipation introduced by the artificial bulk viscosity. Finally, an improved forcing function that explicitly accounts for the role of the artificial bulk viscosity in the budget of turbulent kinetic energy was explored.« less

DRINKING WATER AND CANCER INCIDENCE IN IOWA. 2. RADIOACTIVITY IN DRINKING WATER

EPA Science Inventory

This paper presents a logical epidemiologic exploration into possible associations between exposures to radium-226 in drinking water and incidence rates for cancers of the bladder, breast, colon, lung, prostate, and rectum. The most striking finding is the increasing gradient of ...

Critical Thinking vs. Critical Consciousness

ERIC Educational Resources Information Center

Doughty, Howard A.

2006-01-01

This article explores four kinds of critical thinking. The first is found in Socratic dialogues, which employ critical thinking mainly to reveal logical fallacies in common opinions, thus cleansing superior minds of error and leaving philosophers free to contemplate universal verities. The second is critical interpretation (hermeneutics) which…

Knowing Who Your Friends Are: Aspects of the Politics of Logical Empiricism

ERIC Educational Resources Information Center

Uebel, Thomas

2009-01-01

This paper comments on Reisch's book "How the Cold War Transformed Philosophy of Science." Overall supportive of Reisch's project and perspective, it raises certain points where the data appear inconclusive and either provides additional support or briefly explores some interpretative alternatives.

Exploring Service Logic in ESL

ERIC Educational Resources Information Center

Walker, John

2013-01-01

ESL is both a professional educational service and, particularly in post-compulsory contexts, a commercial activity. The effective management of ESL programs can secure quality outcomes for practitioners and students. Nevertheless, writings on ESL management do not figure prominently in the literature. In particular, the association between…

Deconstructing Science

ERIC Educational Resources Information Center

Trifonas, Peter Pericles

2012-01-01

In this paper I expand on the premises of Jesse Bazzul's thesis in his paper, "Neoliberal ideology, global capitalism, and science education: engaging the question of subjectivity," exploring the implications of the ideologies within the culturally emerging logic of science exposes the incommensurability of intents and purposes in its methods and…

The "Wow! signal" of the terrestrial genetic code

NASA Astrophysics Data System (ADS)

shCherbak, Vladimir I.; Makukov, Maxim A.

2013-05-01

It has been repeatedly proposed to expand the scope for SETI, and one of the suggested alternatives to radio is the biological media. Genomic DNA is already used on Earth to store non-biological information. Though smaller in capacity, but stronger in noise immunity is the genetic code. The code is a flexible mapping between codons and amino acids, and this flexibility allows modifying the code artificially. But once fixed, the code might stay unchanged over cosmological timescales; in fact, it is the most durable construct known. Therefore it represents an exceptionally reliable storage for an intelligent signature, if that conforms to biological and thermodynamic requirements. As the actual scenario for the origin of terrestrial life is far from being settled, the proposal that it might have been seeded intentionally cannot be ruled out. A statistically strong intelligent-like "signal" in the genetic code is then a testable consequence of such scenario. Here we show that the terrestrial code displays a thorough precision-type orderliness matching the criteria to be considered an informational signal. Simple arrangements of the code reveal an ensemble of arithmetical and ideographical patterns of the same symbolic language. Accurate and systematic, these underlying patterns appear as a product of precision logic and nontrivial computing rather than of stochastic processes (the null hypothesis that they are due to chance coupled with presumable evolutionary pathways is rejected with P-value < 10-13). The patterns are profound to the extent that the code mapping itself is uniquely deduced from their algebraic representation. The signal displays readily recognizable hallmarks of artificiality, among which are the symbol of zero, the privileged decimal syntax and semantical symmetries. Besides, extraction of the signal involves logically straightforward but abstract operations, making the patterns essentially irreducible to any natural origin. Plausible ways of embedding the signal into the code and possible interpretation of its content are discussed. Overall, while the code is nearly optimized biologically, its limited capacity is used extremely efficiently to pass non-biological information.

A meta-data based method for DNA microarray imputation.

PubMed

Jörnsten, Rebecka; Ouyang, Ming; Wang, Hui-Yu

2007-03-29

DNA microarray experiments are conducted in logical sets, such as time course profiling after a treatment is applied to the samples, or comparisons of the samples under two or more conditions. Due to cost and design constraints of spotted cDNA microarray experiments, each logical set commonly includes only a small number of replicates per condition. Despite the vast improvement of the microarray technology in recent years, missing values are prevalent. Intuitively, imputation of missing values is best done using many replicates within the same logical set. In practice, there are few replicates and thus reliable imputation within logical sets is difficult. However, it is in the case of few replicates that the presence of missing values, and how they are imputed, can have the most profound impact on the outcome of downstream analyses (e.g. significance analysis and clustering). This study explores the feasibility of imputation across logical sets, using the vast amount of publicly available microarray data to improve imputation reliability in the small sample size setting. We download all cDNA microarray data of Saccharomyces cerevisiae, Arabidopsis thaliana, and Caenorhabditis elegans from the Stanford Microarray Database. Through cross-validation and simulation, we find that, for all three species, our proposed imputation using data from public databases is far superior to imputation within a logical set, sometimes to an astonishing degree. Furthermore, the imputation root mean square error for significant genes is generally a lot less than that of non-significant ones. Since downstream analysis of significant genes, such as clustering and network analysis, can be very sensitive to small perturbations of estimated gene effects, it is highly recommended that researchers apply reliable data imputation prior to further analysis. Our method can also be applied to cDNA microarray experiments from other species, provided good reference data are available.

Distinguishing between evidence and its explanations in the steering of atomic clocks

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

Myers, John M., E-mail: myers@seas.harvard.edu; Hadi Madjid, F., E-mail: gmadjid@aol.com

2014-11-15

Quantum theory reflects within itself a separation of evidence from explanations. This separation leads to a known proof that: (1) no wave function can be determined uniquely by evidence, and (2) any chosen wave function requires a guess reaching beyond logic to things unforeseeable. Chosen wave functions are encoded into computer-mediated feedback essential to atomic clocks, including clocks that step computers through their phases of computation and clocks in space vehicles that supply evidence of signal propagation explained by hypotheses of spacetimes with metric tensor fields. The propagation of logical symbols from one computer to another requires a shared rhythm—likemore » a bucket brigade. Here we show how hypothesized metric tensors, dependent on guesswork, take part in the logical synchronization by which clocks are steered in rate and position toward aiming points that satisfy phase constraints, thereby linking the physics of signal propagation with the sharing of logical symbols among computers. Recognizing the dependence of the phasing of symbol arrivals on guesses about signal propagation transports logical synchronization from the engineering of digital communications to a discipline essential to physics. Within this discipline we begin to explore questions invisible under any concept of time that fails to acknowledge unforeseeable events. In particular, variation of spacetime curvature is shown to limit the bit rate of logical communication. - Highlights: • Atomic clocks are steered in frequency toward an aiming point. • The aiming point depends on a chosen wave function. • No evidence alone can determine the wave function. • The unknowability of the wave function has implications for spacetime curvature. • Variability in spacetime curvature limits the bit rate of communications.« less

Reflections on the relationship between artificial intelligence and operations research

NASA Technical Reports Server (NTRS)

Fox, Mark S.

1989-01-01

Historically, part of Artificial Intelligence's (AI's) roots lie in Operations Research (OR). How AI has extended the problem solving paradigm developed in OR is explored. In particular, by examining how scheduling problems are solved using OR and AI, it is demonstrated that AI extends OR's model of problem solving through the opportunistic use of knowledge, problem reformulation and learning.

Leading the Herd Astray: An Experimental Study of Self-Fulfilling Prophecies in an Artificial Cultural Market

ERIC Educational Resources Information Center

Salganik, Matthew J.; Watts, Duncan J.

2008-01-01

Individuals influence each others' decisions about cultural products such as songs, books, and movies; but to what extent can the perception of success become a "self-fulfilling prophecy"? We have explored this question experimentally by artificially inverting the true popularity of songs in an online "music market," in which 12,207 participants…

Using RUFDATA to guide a logic model for a quality assurance process in an undergraduate university program.

PubMed

Sherman, Paul David

2016-04-01

This article presents a framework to identify key mechanisms for developing a logic model blueprint that can be used for an impending comprehensive evaluation of an undergraduate degree program in a Canadian university. The evaluation is a requirement of a comprehensive quality assurance process mandated by the university. A modified RUFDATA (Saunders, 2000) evaluation model is applied as an initiating framework to assist in decision making to provide a guide for conceptualizing a logic model for the quality assurance process. This article will show how an educational evaluation is strengthened by employing a RUFDATA reflective process in exploring key elements of the evaluation process, and then translating this information into a logic model format that could serve to offer a more focussed pathway for the quality assurance activities. Using preliminary program evaluation data from two key stakeholders of the undergraduate program as well as an audit of the curriculum's course syllabi, a case is made for, (1) the importance of inclusivity of key stakeholders participation in the design of the evaluation process to enrich the authenticity and accuracy of program participants' feedback, and (2) the diversification of data collection methods to ensure that stakeholders' narrative feedback is given ample exposure. It is suggested that the modified RUFDATA/logic model framework be applied to all academic programs at the university undergoing the quality assurance process at the same time so that economies of scale may be realized. Copyright © 2015 Elsevier Ltd. All rights reserved.

Using logic model methods in systematic review synthesis: describing complex pathways in referral management interventions

PubMed Central

2014-01-01

Background There is increasing interest in innovative methods to carry out systematic reviews of complex interventions. Theory-based approaches, such as logic models, have been suggested as a means of providing additional insights beyond that obtained via conventional review methods. Methods This paper reports the use of an innovative method which combines systematic review processes with logic model techniques to synthesise a broad range of literature. The potential value of the model produced was explored with stakeholders. Results The review identified 295 papers that met the inclusion criteria. The papers consisted of 141 intervention studies and 154 non-intervention quantitative and qualitative articles. A logic model was systematically built from these studies. The model outlines interventions, short term outcomes, moderating and mediating factors and long term demand management outcomes and impacts. Interventions were grouped into typologies of practitioner education, process change, system change, and patient intervention. Short-term outcomes identified that may result from these interventions were changed physician or patient knowledge, beliefs or attitudes and also interventions related to changed doctor-patient interaction. A range of factors which may influence whether these outcomes lead to long term change were detailed. Demand management outcomes and intended impacts included content of referral, rate of referral, and doctor or patient satisfaction. Conclusions The logic model details evidence and assumptions underpinning the complex pathway from interventions to demand management impact. The method offers a useful addition to systematic review methodologies. Trial registration number PROSPERO registration number: CRD42013004037. PMID:24885751

Using logic model methods in systematic review synthesis: describing complex pathways in referral management interventions.

PubMed

Baxter, Susan K; Blank, Lindsay; Woods, Helen Buckley; Payne, Nick; Rimmer, Melanie; Goyder, Elizabeth

2014-05-10

There is increasing interest in innovative methods to carry out systematic reviews of complex interventions. Theory-based approaches, such as logic models, have been suggested as a means of providing additional insights beyond that obtained via conventional review methods. This paper reports the use of an innovative method which combines systematic review processes with logic model techniques to synthesise a broad range of literature. The potential value of the model produced was explored with stakeholders. The review identified 295 papers that met the inclusion criteria. The papers consisted of 141 intervention studies and 154 non-intervention quantitative and qualitative articles. A logic model was systematically built from these studies. The model outlines interventions, short term outcomes, moderating and mediating factors and long term demand management outcomes and impacts. Interventions were grouped into typologies of practitioner education, process change, system change, and patient intervention. Short-term outcomes identified that may result from these interventions were changed physician or patient knowledge, beliefs or attitudes and also interventions related to changed doctor-patient interaction. A range of factors which may influence whether these outcomes lead to long term change were detailed. Demand management outcomes and intended impacts included content of referral, rate of referral, and doctor or patient satisfaction. The logic model details evidence and assumptions underpinning the complex pathway from interventions to demand management impact. The method offers a useful addition to systematic review methodologies. PROSPERO registration number: CRD42013004037.

Artificial intelligence and synthetic biology: A tri-temporal contribution.

PubMed

Bianchini, Francesco

2016-10-01

Artificial intelligence can make numerous contributions to synthetic biology. I would like to suggest three that are related to the past, present and future of artificial intelligence. From the past, works in biology and artificial systems by Turing and von Neumann prove highly interesting to explore within the new framework of synthetic biology, especially with regard to the notions of self-modification and self-replication and their links to emergence and the bottom-up approach. The current epistemological inquiry into emergence and research on swarm intelligence, superorganisms and biologically inspired cognitive architecture may lead to new achievements on the possibilities of synthetic biology in explaining cognitive processes. Finally, the present-day discussion on the future of artificial intelligence and the rise of superintelligence may point to some research trends for the future of synthetic biology and help to better define the boundary of notions such as "life", "cognition", "artificial" and "natural", as well as their interconnections in theoretical synthetic biology. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Aeroassist Technology Planning for Exploration

NASA Technical Reports Server (NTRS)

Munk, Michelle M.; Powell, Richard W.

2000-01-01

Now that the International Space Station is undergoing assembly, NASA is strategizing about the next logical exploration strategy for robotic missions and the next destination for humans. NASA's current efforts are in developing technologies that will both aid the robotic exploration strategy and make human flight to other celestial bodies both safe and affordable. One of these enabling technologies for future robotic and human exploration missions is aeroassist. This paper will (1) define aeroassist, (2) explain the benefits and uses of aeroassist, and (3) describe a method, currently used by the NASA Aeroassist Working Group, by which widely geographically distributed teams can assemble, present, use, and archive technology information.

Environment dependent enhanced photoluminescence and Boolean logic gates like behavior of Bi2O3 and Ag:Bi2O3 nanostructures

NASA Astrophysics Data System (ADS)

Hariharan, S.; Karthikeyan, B.

2018-03-01

In the evolution of nanotechnology research for smart and precise sensor fabrication, here we report the implementation of simple logic gate operations performing by luminescent nanostructures in biomolecule environment based on photoluminescence (PL) technique. This present work deals with the luminescence property of α-Bi2O3 and Ag modified α-Bi2O3 nanostructures for D-glucose and Bovine serum albumin (BSA) sensing applications. These nanostructures are prepared by simple co-precipitation method and their morphology are examined using transmission electron microscope (TEM). We explore the PL characteristics of the prepared nanostructures and observe their change in PL intensity in the presence of D-glucose and BSA molecules. Enhancement in PL intensity is observed in the presence of D-glucose and BSA. Based on the PL response of prepared nanostructures in the biomolecule environment, we demonstrate biophotonic logic gates including YES, PASS 0, OR and INHIBIT gates.

The effect of patterning options on embedded memory cells in logic technologies at iN10 and iN7

NASA Astrophysics Data System (ADS)

Appeltans, Raf; Weckx, Pieter; Raghavan, Praveen; Kim, Ryoung-Han; Kar, Gouri Sankar; Furnémont, Arnaud; Van der Perre, Liesbet; Dehaene, Wim

2017-03-01

Static Random Access Memory (SRAM) cells are used together with logic standard cells as the benchmark to develop the process flow for new logic technologies. In order to achieve successful integration of Spin-Transfer Torque Magnetic Random Access Memory (STT-MRAM) as area efficient higher level embedded cache, it also needs to be included as a benchmark. The simple cell structure of STT-MRAM brings extra patterning challenges to achieve high density. The two memory types are compared in terms of minimum area and critical design rules in both the iN10 and iN7 node, with an extra focus on patterning options in iN7. Both the use of Self-Aligned Quadruple Patterning (SAQP) mandrel and spacer engineering, as well as multi-level via's are explored. These patterning options result in large area gains for the STT-MRAM cell and moreover determine which cell variant is the smallest.

Moral Education and the Perils of Developmentalism.

ERIC Educational Resources Information Center

Carr, David

2002-01-01

Discusses conception of moral formation. Traces progress to moral maturity through well defined stages of cognitive, conative, and/or affective growth. Explains that logical status of developmental theories are not clear. Argues that the accounts are more evaluative than descriptive. Explores the problematic moral educational implications of this…

Cross-Cultural Counseling and Cross-Cultural Meanings: An Exploration of Morita Psychotherapy.

ERIC Educational Resources Information Center

Aldous, Jane L.

1994-01-01

Describes theoretical framework and techniques of Morita psychotherapy. Western research indicates that Asian American clients prefer active-directive, logical, rational, and structured approaches. Suggests that ethnocentric counseling approaches may be imposed upon clients of Asian origin because meanings attached to terms describing counseling…

The Effects of Arts Education on Emotional Literacy.

ERIC Educational Resources Information Center

Wallace, Rebecca Rockwell

Human potential includes at least seven intelligences--only two, linguistics and mathematics/logic, typically are taught in elementary schools. Researchers in the field of multiple intelligences believe the arts represent the other intelligences, i.e.: music, spatial reasoning, kinesthetic, interpersonal, and intrapersonal. A study explored the…

Psyche/Logos: Mapping the Terrains of Mind and Rhetoric.

ERIC Educational Resources Information Center

Baumlin, James S.; Baumlin, Tita French

1989-01-01

Discusses rhetoric as mirroring psychology. Examines Aristotle's three "pisteis"--the pathetic, logical, and ethical proofs, paralleling them to Freud's id, ego, and super-ego. Explores an adequate feminine psychology and a corresponding rhetoric. Outlines two models of persuasive discourse, the rational world paradigm and the narrative…

Challenging the Logic behind Government Policies for School Completion

ERIC Educational Resources Information Center

te Riele, Kitty

2012-01-01

This paper investigates a suite of policies that comprise the "National Partnership Agreement" between federal, state and territory governments in Australia that are ostensibly aimed at improving the educational attainment levels of young Australians. It specifically explores the policy terrain of educational targets that have been…

43 CFR 3483.6 - Special logical mining unit rules.

Code of Federal Regulations, 2011 CFR

2011-10-01

... the LMU, of either Federal or non-Federal recoverable coal reserves or a combination thereof, shall be... Section 3483.6 Public Lands: Interior Regulations Relating to Public Lands (Continued) BUREAU OF LAND MANAGEMENT, DEPARTMENT OF THE INTERIOR MINERALS MANAGEMENT (3000) COAL EXPLORATION AND MINING OPERATIONS...

43 CFR 3483.6 - Special logical mining unit rules.

Code of Federal Regulations, 2013 CFR

2013-10-01

... the LMU, of either Federal or non-Federal recoverable coal reserves or a combination thereof, shall be... Section 3483.6 Public Lands: Interior Regulations Relating to Public Lands (Continued) BUREAU OF LAND MANAGEMENT, DEPARTMENT OF THE INTERIOR MINERALS MANAGEMENT (3000) COAL EXPLORATION AND MINING OPERATIONS...

43 CFR 3483.6 - Special logical mining unit rules.

Code of Federal Regulations, 2014 CFR

2014-10-01

... the LMU, of either Federal or non-Federal recoverable coal reserves or a combination thereof, shall be... Section 3483.6 Public Lands: Interior Regulations Relating to Public Lands (Continued) BUREAU OF LAND MANAGEMENT, DEPARTMENT OF THE INTERIOR MINERALS MANAGEMENT (3000) COAL EXPLORATION AND MINING OPERATIONS...

43 CFR 3483.6 - Special logical mining unit rules.

Code of Federal Regulations, 2012 CFR

2012-10-01

... the LMU, of either Federal or non-Federal recoverable coal reserves or a combination thereof, shall be... Section 3483.6 Public Lands: Interior Regulations Relating to Public Lands (Continued) BUREAU OF LAND MANAGEMENT, DEPARTMENT OF THE INTERIOR MINERALS MANAGEMENT (3000) COAL EXPLORATION AND MINING OPERATIONS...

Problems with Multivariate Normality: Can the Multivariate Bootstrap Help?

ERIC Educational Resources Information Center

Thompson, Bruce

Multivariate normality is required for some statistical tests. This paper explores the implications of violating the assumption of multivariate normality and illustrates a graphical procedure for evaluating multivariate normality. The logic for using the multivariate bootstrap is presented. The multivariate bootstrap can be used when distribution…

Herouxville's Afghanistan, or, Accumulated Violence

ERIC Educational Resources Information Center

Mookerjea, Sourayan

2009-01-01

This essay explores the cultural-pedagogical logic of what the author calls the perlocutionary effect of transcendence that the "discourse of the West" produces. This discourse provides a fortified interiority beyond history, but also a door through which racisms, imperialisms, and fascisms of the past can possibly return. The second…

Sequencing Events: Exploring Art and Art Jobs.

ERIC Educational Resources Information Center

Stephens, Pamela Geiger; Shaddix, Robin K.

2000-01-01

Presents an activity for upper-elementary students that correlates the actions of archaeologists, patrons, and artists with the sequencing of events in a logical order. Features ancient Egyptian art images. Discusses the preparation of materials, motivation, a pre-writing activity, and writing a story in sequence. (CMK)

A Parent Guide for the Misbehaving High School Student.

ERIC Educational Resources Information Center

Hall, J. Phil

1982-01-01

Explores factors that may help parents understand and correct their adolescent's misbehavior in school. Discusses the communication process and the need to delineate clear expectations. Suggests the use of logical consequences for changing behavior. Reviews principles of behaviorism and discusses the parent-school relationship. (RC)

Institutional Image: The Concept and Implications for Administrative Action.

ERIC Educational Resources Information Center

Renihan, Frederick I; Renihan, Patrick J.

1989-01-01

Explores institutional image as a key to providing a philosophy and a logical foundation for school improvement efforts. Identifies two image dimensions (cosmetic and pastoral) and classifies five school types (synergistic, candy store, disaffected, monastic, and survivor), and discusses implications for administrative action. Includes three…

Enhancing artificial bee colony algorithm with self-adaptive searching strategy and artificial immune network operators for global optimization.

PubMed

Chen, Tinggui; Xiao, Renbin

2014-01-01

Artificial bee colony (ABC) algorithm, inspired by the intelligent foraging behavior of honey bees, was proposed by Karaboga. It has been shown to be superior to some conventional intelligent algorithms such as genetic algorithm (GA), artificial colony optimization (ACO), and particle swarm optimization (PSO). However, the ABC still has some limitations. For example, ABC can easily get trapped in the local optimum when handing in functions that have a narrow curving valley, a high eccentric ellipse, or complex multimodal functions. As a result, we proposed an enhanced ABC algorithm called EABC by introducing self-adaptive searching strategy and artificial immune network operators to improve the exploitation and exploration. The simulation results tested on a suite of unimodal or multimodal benchmark functions illustrate that the EABC algorithm outperforms ACO, PSO, and the basic ABC in most of the experiments.

Enhancing Artificial Bee Colony Algorithm with Self-Adaptive Searching Strategy and Artificial Immune Network Operators for Global Optimization

PubMed Central

Chen, Tinggui; Xiao, Renbin

2014-01-01

Artificial bee colony (ABC) algorithm, inspired by the intelligent foraging behavior of honey bees, was proposed by Karaboga. It has been shown to be superior to some conventional intelligent algorithms such as genetic algorithm (GA), artificial colony optimization (ACO), and particle swarm optimization (PSO). However, the ABC still has some limitations. For example, ABC can easily get trapped in the local optimum when handing in functions that have a narrow curving valley, a high eccentric ellipse, or complex multimodal functions. As a result, we proposed an enhanced ABC algorithm called EABC by introducing self-adaptive searching strategy and artificial immune network operators to improve the exploitation and exploration. The simulation results tested on a suite of unimodal or multimodal benchmark functions illustrate that the EABC algorithm outperforms ACO, PSO, and the basic ABC in most of the experiments. PMID:24772023

Artificial gravity in space and in medical research

NASA Technical Reports Server (NTRS)

Cardus, D.

1994-01-01

The history of manned space flight has repeatedly documented the fact that prolonged sojourn in space causes physiological deconditioning. Physiological deterioration has raised a legitimate concern about man's ability to adequately perform in the course of long missions and even the possibility of leading to circumstances threatening survival. One of the possible countermeasures of physiological deconditioning, theoretically more complete than others presently used since it affects all bodily systems, is artificial gravity. Space stations and spacecrafts can be equipped with artificial gravity, but is artificial gravity necessary? The term "necessary" must be qualified because a meaningful answer to the question depends entirely on further defining the purpose of space travel. If man intends to stay only temporarily in space, then he must keep himself in good physical condition so as to be able to return to earth or to land on any other planetary surface without undue exposure to major physiological problems resulting from transition through variable gravitational fields. Such a situation makes artificial gravity highly desirable, although perhaps not absolutely necessary in the case of relative short exposure to microgravity, but certainly necessary in interplanetary flight and planetary landings. If the intent is to remain indefinitely in space, to colonize space, then artificial gravity may not be necessary, but in this case the consequences of long term effects of adaptation to weightlessness will have to be weighed against the biological evolutionary outcomes that are to be expected. At the moment, plans for establishing permanent colonies in space seem still remote. More likely, the initial phase of exploration of the uncharted solar system will take place through successive, scope limited, research ventures ending with return to earth. This will require man to be ready to operate in gravitational fields of variable intensity. Equipping spacecrafts or space stations with some means of artificial gravity in this initial phase is, therefore, necessary without question. In a strict sense artificial gravity is conceived as a means of replacing natural gravity in space by the centripetal acceleration generated by some sort of rotating device. Rotating devices create an inertial force which has effects on bodies similar to those caused by terrestrial gravity, but artificial gravity by a rotation device is not the same as terrestrial gravity, as we shall see. Present research in artificial gravity for space exploration is projected in two main directions: artificial gravity for whole space stations and artificial gravity produced by short arm centrifuges designed for human use in space.

Artificial gravity in space and in medical research.

PubMed

Cardús, D

1994-05-01

The history of manned space flight has repeatedly documented the fact that prolonged sojourn in space causes physiological deconditioning. Physiological deterioration has raised a legitimate concern about man's ability to adequately perform in the course of long missions and even the possibility of leading to circumstances threatening survival. One of the possible countermeasures of physiological deconditioning, theoretically more complete than others presently used since it affects all bodily systems, is artificial gravity. Space stations and spacecrafts can be equipped with artificial gravity, but is artificial gravity necessary? The term "necessary" must be qualified because a meaningful answer to the question depends entirely on further defining the purpose of space travel. If man intends to stay only temporarily in space, then he must keep himself in good physical condition so as to be able to return to earth or to land on any other planetary surface without undue exposure to major physiological problems resulting from transition through variable gravitational fields. Such a situation makes artificial gravity highly desirable, although perhaps not absolutely necessary in the case of relative short exposure to microgravity, but certainly necessary in interplanetary flight and planetary landings. If the intent is to remain indefinitely in space, to colonize space, then artificial gravity may not be necessary, but in this case the consequences of long term effects of adaptation to weightlessness will have to be weighed against the biological evolutionary outcomes that are to be expected. At the moment, plans for establishing permanent colonies in space seem still remote. More likely, the initial phase of exploration of the uncharted solar system will take place through successive, scope limited, research ventures ending with return to earth. This will require man to be ready to operate in gravitational fields of variable intensity. Equipping spacecrafts or space stations with some means of artificial gravity in this initial phase is, therefore, necessary without question. In a strict sense artificial gravity is conceived as a means of replacing natural gravity in space by the centripetal acceleration generated by some sort of rotating device. Rotating devices create an inertial force which has effects on bodies similar to those caused by terrestrial gravity, but artificial gravity by a rotation device is not the same as terrestrial gravity, as we shall see. Present research in artificial gravity for space exploration is projected in two main directions: artificial gravity for whole space stations and artificial gravity produced by short arm centrifuges designed for human use in space.

The ANMLite Language and Logic for Specifying Planning Problems

NASA Technical Reports Server (NTRS)

Butler, Ricky W.; Siminiceanu, Radu I.; Munoz, Cesar A.

2007-01-01

We present the basic concepts of the ANMLite planning language. We discuss various aspects of specifying a plan in terms of constraints and checking the existence of a solution with the help of a model checker. The constructs of the ANMLite language have been kept as simple as possible in order to reduce complexity and simplify the verification problem. We illustrate the language with a specification of the space shuttle crew activity model that was constructed under the Spacecraft Autonomy for Vehicles and Habitats (SAVH) project. The main purpose of this study was to explore the implications of choosing a robust logic behind the specification of constraints, rather than simply proposing a new planning language.

Hybrid CMOS/Molecular Integrated Circuits

NASA Astrophysics Data System (ADS)

Stan, M. R.; Rose, G. S.; Ziegler, M. M.

CMOS silicon technologies are likely to run out of steam in the next 10-15 years despite revolutionary advances in the past few decades. Molecular and other nanoscale technologies show significant promise but it is unlikely that they will completely replace CMOS, at least in the near term. This chapter explores opportunities for using CMOS and nanotechnology to enhance and complement each other in hybrid circuits. As an example of such a hybrid CMOS/nano system, a nanoscale programmable logic array (PLA) based on majority logic is described along with its supplemental CMOS circuitry. It is believed that such systems will be able to sustain the historical advances in the semiconductor industry while addressing manufacturability, yield, power, cost, and performance challenges.

Applying gene regulatory network logic to the evolution of social behavior.

PubMed

Baran, Nicole M; McGrath, Patrick T; Streelman, J Todd

2017-06-06

Animal behavior is ultimately the product of gene regulatory networks (GRNs) for brain development and neural networks for brain function. The GRN approach has advanced the fields of genomics and development, and we identify organizational similarities between networks of genes that build the brain and networks of neurons that encode brain function. In this perspective, we engage the analogy between developmental networks and neural networks, exploring the advantages of using GRN logic to study behavior. Applying the GRN approach to the brain and behavior provides a quantitative and manipulative framework for discovery. We illustrate features of this framework using the example of social behavior and the neural circuitry of aggression.

Fuzzy control of small servo motors

NASA Technical Reports Server (NTRS)

Maor, Ron; Jani, Yashvant

1993-01-01

To explore the benefits of fuzzy logic and understand the differences between the classical control methods and fuzzy control methods, the Togai InfraLogic applications engineering staff developed and implemented a motor control system for small servo motors. The motor assembly for testing the fuzzy and conventional controllers consist of servo motor RA13M and an encoder with a range of 4096 counts. An interface card was designed and fabricated to interface the motor assembly and encoder to an IBM PC. The fuzzy logic based motor controller was developed using the TILShell and Fuzzy C Development System on an IBM PC. A Proportional-Derivative (PD) type conventional controller was also developed and implemented in the IBM PC to compare the performance with the fuzzy controller. Test cases were defined to include step inputs of 90 and 180 degrees rotation, sine and square wave profiles in 5 to 20 hertz frequency range, as well as ramp inputs. In this paper we describe our approach to develop a fuzzy as well as PH controller, provide details of hardware set-up and test cases, and discuss the performance results. In comparison, the fuzzy logic based controller handles the non-linearities of the motor assembly very well and provides excellent control over a broad range of parameters. Fuzzy technology, as indicated by our results, possesses inherent adaptive features.

What would an ideal mental health service for primary care look like?

PubMed Central

2011-01-01

The creation of GP commissioning consortia offers potential opportunities for GPs to challenge a number of divisions and distinctions that are currently taken for granted in mental health services, but may be neither necessary nor logical. I examine a range of these and suggest what GPs and patients might reasonably expect if we challenged them in order to imagine and commission an ideal mental health service for primary care. Among its features, an ideal service would cross the boundaries of mental and physical care, individual and family care, and the mental, social and economic domains. It would also transcend mental health ideologies, geographical borders and the artificial distinction between making a diagnosis, offering treatment and holding a therapeutic conversation. PMID:25949648

Intelligent fault-tolerant controllers

NASA Technical Reports Server (NTRS)

Huang, Chien Y.

1987-01-01

A system with fault tolerant controls is one that can detect, isolate, and estimate failures and perform necessary control reconfiguration based on this new information. Artificial intelligence (AI) is concerned with semantic processing, and it has evolved to include the topics of expert systems and machine learning. This research represents an attempt to apply AI to fault tolerant controls, hence, the name intelligent fault tolerant control (IFTC). A generic solution to the problem is sought, providing a system based on logic in addition to analytical tools, and offering machine learning capabilities. The advantages are that redundant system specific algorithms are no longer needed, that reasonableness is used to quickly choose the correct control strategy, and that the system can adapt to new situations by learning about its effects on system dynamics.

Methods for solving reasoning problems in abstract argumentation – A survey

PubMed Central

Charwat, Günther; Dvořák, Wolfgang; Gaggl, Sarah A.; Wallner, Johannes P.; Woltran, Stefan

2015-01-01

Within the last decade, abstract argumentation has emerged as a central field in Artificial Intelligence. Besides providing a core formalism for many advanced argumentation systems, abstract argumentation has also served to capture several non-monotonic logics and other AI related principles. Although the idea of abstract argumentation is appealingly simple, several reasoning problems in this formalism exhibit high computational complexity. This calls for advanced techniques when it comes to implementation issues, a challenge which has been recently faced from different angles. In this survey, we give an overview on different methods for solving reasoning problems in abstract argumentation and compare their particular features. Moreover, we highlight available state-of-the-art systems for abstract argumentation, which put these methods to practice. PMID:25737590

Expertise and reasoning with possibility: An explanation of modal logic and expert systems

NASA Technical Reports Server (NTRS)

Rochowiak, Daniel

1988-01-01

Recently systems of modal reasoning have been brought to the foreground of artificial intelligence studies. The intuitive idea of research efforts in this area is that in addition to the actual world in which sentences have certain truth values there are other worlds in which those sentences have different truth values. Such alternative worlds can be considered as possible worlds, and an agent may or may not have access to some or all of them. This approach to reasoning can be valuable in extending the expert system paradigm. Using the scheme of reasoning proposed by Toulmin, Reike and Janick and the modal system T, a scheme is proposed for expert reasoning that mitigates some of the criticisms raised by Schank and Nickerson.

Proceedings of the Seventh International Symposium on Methodologies for Intelligent Systems (Poster Session)

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

Harber, K.S.

1993-05-01

This report contains the following papers: Implications in vivid logic; a self-learning bayesian expert system; a natural language generation system for a heterogeneous distributed database system; competence-switching'' managed by intelligent systems; strategy acquisition by an artificial neural network: Experiments in learning to play a stochastic game; viewpoints and selective inheritance in object-oriented modeling; multivariate discretization of continuous attributes for machine learning; utilization of the case-based reasoning method to resolve dynamic problems; formalization of an ontology of ceramic science in CLASSIC; linguistic tools for intelligent systems; an application of rough sets in knowledge synthesis; and a relational model for imprecise queries.more » These papers have been indexed separately.« less

Proceedings of the Seventh International Symposium on Methodologies for Intelligent Systems (Poster Session)

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

Harber, K.S.

1993-05-01

This report contains the following papers: Implications in vivid logic; a self-learning Bayesian Expert System; a natural language generation system for a heterogeneous distributed database system; ``competence-switching`` managed by intelligent systems; strategy acquisition by an artificial neural network: Experiments in learning to play a stochastic game; viewpoints and selective inheritance in object-oriented modeling; multivariate discretization of continuous attributes for machine learning; utilization of the case-based reasoning method to resolve dynamic problems; formalization of an ontology of ceramic science in CLASSIC; linguistic tools for intelligent systems; an application of rough sets in knowledge synthesis; and a relational model for imprecise queries.more » These papers have been indexed separately.« less

A secure communication using cascade chaotic computing systems on clinical decision support.

PubMed

Koksal, Ahmet Sertol; Er, Orhan; Evirgen, Hayrettin; Yumusak, Nejat

2016-06-01

Clinical decision support systems (C-DSS) provide supportive tools to the expert for the determination of the disease. Today, many of the support systems, which have been developed for a better and more accurate diagnosis, have reached a dynamic structure due to artificial intelligence techniques. However, in cases when important diagnosis studies should be performed in secret, a secure communication system is required. In this study, secure communication of a DSS is examined through a developed double layer chaotic communication system. The developed communication system consists of four main parts: random number generator, cascade chaotic calculation layer, PCM, and logical mixer layers. Thanks to this system, important patient data created by DSS will be conveyed to the center through a secure communication line.

Soft computing prediction of economic growth based in science and technology factors

NASA Astrophysics Data System (ADS)

Marković, Dušan; Petković, Dalibor; Nikolić, Vlastimir; Milovančević, Miloš; Petković, Biljana

2017-01-01

The purpose of this research is to develop and apply the Extreme Learning Machine (ELM) to forecast the gross domestic product (GDP) growth rate. In this study the GDP growth was analyzed based on ten science and technology factors. These factors were: research and development (R&D) expenditure in GDP, scientific and technical journal articles, patent applications for nonresidents, patent applications for residents, trademark applications for nonresidents, trademark applications for residents, total trademark applications, researchers in R&D, technicians in R&D and high-technology exports. The ELM results were compared with genetic programming (GP), artificial neural network (ANN) and fuzzy logic results. Based upon simulation results, it is demonstrated that ELM has better forecasting capability for the GDP growth rate.

Artificial Intelligence and Information Management

NASA Astrophysics Data System (ADS)

Fukumura, Teruo

After reviewing the recent popularization of the information transmission and processing technologies, which are supported by the progress of electronics, the authors describe that by the introduction of the opto-electronics into the information technology, the possibility of applying the artificial intelligence (AI) technique to the mechanization of the information management has emerged. It is pointed out that althuogh AI deals with problems in the mental world, its basic methodology relies upon the verification by evidence, so the experiment on computers become indispensable for the study of AI. The authors also describe that as computers operate by the program, the basic intelligence which is concerned in AI is that expressed by languages. This results in the fact that the main tool of AI is the logical proof and it involves an intrinsic limitation. To answer a question “Why do you employ AI in your problem solving”, one must have ill-structured problems and intend to conduct deep studies on the thinking and the inference, and the memory and the knowledge-representation. Finally the authors discuss the application of AI technique to the information management. The possibility of the expert-system, processing of the query, and the necessity of document knowledge-base are stated.

Fluid resuscitation: past, present, and the future.

PubMed

Santry, Heena P; Alam, Hasan B

2010-03-01

Hemorrhage remains a major cause of preventable death following both civilian and military trauma. The goals of resuscitation in the face of hemorrhagic shock are restoring end-organ perfusion and maintaining tissue oxygenation while attempting definitive control of bleeding. However, if not performed properly, resuscitation can actually exacerbate cellular injury caused by hemorrhagic shock, and the type of fluid used for resuscitation plays an important role in this injury pattern. This article reviews the historical development and scientific underpinnings of modern resuscitation techniques. We summarized data from a number of studies to illustrate the differential effects of commonly used resuscitation fluids, including isotonic crystalloids, natural and artificial colloids, hypertonic and hyperoncotic solutions, and artificial oxygen carriers, on cellular injury and how these relate to clinical practice. The data reveal that a uniformly safe, effective, and practical resuscitation fluid when blood products are unavailable and direct hemorrhage control is delayed has been elusive. Yet, it is logical to prevent this cellular injury through wiser resuscitation strategies than attempting immunomodulation after the damage has already occurred. Thus, we describe how some novel resuscitation strategies aimed at preventing or ameliorating cellular injury may become clinically available in the future.

Levels and loops: the future of artificial intelligence and neuroscience.

PubMed Central

Bell, A J

1999-01-01

In discussing artificial intelligence and neuroscience, I will focus on two themes. The first is the universality of cycles (or loops): sets of variables that affect each other in such a way that any feed-forward account of causality and control, while informative, is misleading. The second theme is based around the observation that a computer is an intrinsically dualistic entity, with its physical set-up designed so as not to interfere with its logical set-up, which executes the computation. The brain is different. When analysed empirically at several different levels (cellular, molecular), it appears that there is no satisfactory way to separate a physical brain model (or algorithm, or representation), from a physical implementational substrate. When program and implementation are inseparable and thus interfere with each other, a dualistic point-of-view is impossible. Forced by empiricism into a monistic perspective, the brain-mind appears as neither embodied by or embedded in physical reality, but rather as identical to physical reality. This perspective has implications for the future of science and society. I will approach these from a negative point-of-view, by critiquing some of our millennial culture's popular projected futures. PMID:10670021

Organic-Inorganic Hybrid Halide Perovskites for Memories, Transistors, and Artificial Synapses.

PubMed

Choi, Jaeho; Han, Ji Su; Hong, Kootak; Kim, Soo Young; Jang, Ho Won

2018-05-30

Fascinating characteristics of halide perovskites (HPs), which cannot be seen in conventional semiconductors and metal oxides, have boosted the application of HPs in electronic devices beyond optoelectronics such as solar cells, photodetectors, and light-emitting diodes. Here, recent advances in HP-based memory and logic devices such as resistive-switching memories (i.e., resistive random access memory (RRAM) or memristors), transistors, and artificial synapses are reviewed, focusing on inherently exotic properties of HPs: i) tunable bandgap, ii) facile majority carrier control, iii) fast ion migration, and iv) superflexibility. Various fabrication techniques of HP thin films from solution-based methods to vacuum processes are introduced. Up-to-date work in the field, emphasizing the compositional flexibility of HPs, suggest that HPs are promising candidates for next-generation electronic devices. Taking advantages of their unique electrical properties, low-cost and low-temperature synthesis, and compositional and mechanical flexibility, HPs have enormous potential to provide a new platform for future electronic devices and explosively intensive studies will pave the way in finding new HP materials beyond conventional silicon-based semiconductors to keep up with "More-than-Moore" times. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Computer-Assisted Recovery of Threatened Plants: Keys for Breaking Seed Dormancy of Eryngium viviparum

PubMed Central

Ayuso, Manuel; Ramil-Rego, Pablo; Landin, Mariana; Gallego, Pedro P.; Barreal, M. Esther

2017-01-01

Many endangered plants such as Eryngium viviparum (Apiaceae) present a poor germination rate. This fact could be due to intrinsic and extrinsic seed variability influencing germination and dormancy of seeds. The objective of this study is to better understand the physiological mechanism of seed latency and, through artificial intelligence models, to determine the factors that stimulate germination rates of E. viviparum seeds. This description could be essential to prevent the disappearance of endangered plants. Germination in vitro was carried out under different dormancy breaking and incubation procedures. Percentages of germination, viability and E:S ratio were calculated and seeds were dissected at the end of each assay to describe embryo development. The database obtained was modeled using neurofuzzy logic technology. We have found that the most of Eryngium seeds (62.6%) were non-viable seeds (fully empty or without embryos). Excluding those, we have established the germination conditions to break seed dormancy that allow obtaining a real germination rate of 100%. Advantageously, the best conditions pointed out by neurofuzzy logic model for embryo growth were the combination of 1 mg L−1 GA3 (Gibberellic Acid) and high incubation temperature and for germination the combination of long incubation and short warm stratification periods. Our results suggest that E. viviparum seeds present morphophysiological dormancy, which reduce the rate of germination. The knowledge provided by the neurofuzzy logic model makes possible not just break the physiological component of dormancy, but stimulate the embryo development increasing the rate of germination. Undoubtedly, the strategy developed in this work can be useful to recover other endangered plants by improving their germination rate and uniformity favoring their ex vitro conservation. PMID:29312370

Genetic programs constructed from layered logic gates in single cells

PubMed Central

Moon, Tae Seok; Lou, Chunbo; Tamsir, Alvin; Stanton, Brynne C.; Voigt, Christopher A.

2014-01-01

Genetic programs function to integrate environmental sensors, implement signal processing algorithms and control expression dynamics1. These programs consist of integrated genetic circuits that individually implement operations ranging from digital logic to dynamic circuits2–6, and they have been used in various cellular engineering applications, including the implementation of process control in metabolic networks and the coordination of spatial differentiation in artificial tissues. A key limitation is that the circuits are based on biochemical interactions occurring in the confined volume of the cell, so the size of programs has been limited to a few circuits1,7. Here we apply part mining and directed evolution to build a set of transcriptional AND gates in Escherichia coli. Each AND gate integrates two promoter inputs and controls one promoter output. This allows the gates to be layered by having the output promoter of an upstream circuit serve as the input promoter for a downstream circuit. Each gate consists of a transcription factor that requires a second chaperone protein to activate the output promoter. Multiple activator–chaperone pairs are identified from type III secretion pathways in different strains of bacteria. Directed evolution is applied to increase the dynamic range and orthogonality of the circuits. These gates are connected in different permutations to form programs, the largest of which is a 4-input AND gate that consists of 3 circuits that integrate 4 inducible systems, thus requiring 11 regulatory proteins. Measuring the performance of individual gates is sufficient to capture the behaviour of the complete program. Errors in the output due to delays (faults), a common problem for layered circuits, are not observed. This work demonstrates the successful layering of orthogonal logic gates, a design strategy that could enable the construction of large, integrated circuits in single cells. PMID:23041931

(E)pistemological Awareness, Instantiation of Methods, and Uninformed Methodological Ambiguity in Qualitative Research Projects

ERIC Educational Resources Information Center

Koro-Ljungberg, Mirka; Yendol-Hoppey, Diane; Smith, Jason Jude; Hayes, Sharon B.

2009-01-01

This article explores epistemological awareness and instantiation of methods, as well as uninformed ambiguity, in qualitative methodological decision making and research reporting. The authors argue that efforts should be made to make the research process, epistemologies, values, methodological decision points, and argumentative logic open,…

Universal Design for Learning and School Libraries: A Logical Partnership

ERIC Educational Resources Information Center

Robinson, David E.

2017-01-01

This article will explore the basic tenets of Universal Design for Learning (UDL) in relation to collaborative curriculum development and implementation; provide a case study examination of UDL principles in action; and suggest school library curricular activities that provide opportunities for multiple means of representation, action, and…

Jacques Ranciere, Education, and the Art of Citizenship

ERIC Educational Resources Information Center

Means, Alex

2011-01-01

This article is part of a broader effort recently undertaken by educational theorists to verify the implications of Jacques Ranciere's work for the field of educational studies. Rather than attempting to fashion productive linkages between Ranciere and other critical pedagogues, to render a "new logic of emancipation," or explore the political…

Intelligence: A Discriminating Circular Search for Sameness.

ERIC Educational Resources Information Center

McKerrow, Kelly

1998-01-01

Reviews relationship of IQ scores to race and gender. Explores the logic that supports the use of intelligence testing to discriminate and to exclude. Argues that default assumptions allow researchers to remain unaware of the subtle adverse impact of their research. Includes recommendations to encourage a broader understanding of intelligence.…

Academic Freedom and the Inclusive University.

ERIC Educational Resources Information Center

Kahn, Sharon E., Ed.; Pavlich, Dennis, Ed.

The chapters in this collection explore issues related to academic freedom and the inclusive university. The first section, Clarifying Concepts in Ideology, Language, and Law, contains these chapters: (1) Whats Sauce for One Goose: The Logic of Academic Freedom (Stanley Fish); (2) Academic Freedom: Rights as Immunities and Privileges (Frederick…

Naturalistic Inquiry: Politics and Implications for Special Education.

ERIC Educational Resources Information Center

Lincoln, Yvonna S.

The revolution in hard sciences is explored, from the Cartesian-Newtonian worldview to the Heisenbergian universe, and consideration is given to whether the conventional, Cartesian model is a serviceable one for research in the social/applied sciences. Five axioms comprising the existing paradigm of logical positivism are outlined (reality,…

An Analysis of the Baking Occupation.

ERIC Educational Resources Information Center

Boyadjid, Thomas A; Paoletti, Donald J.

The general purpose of the occupational analysis is to provide workable, basic information dealing with the many and varied duties performed in the baking occupation. Such tasks as choosing ingredients and the actual baking process are logical primary concerns, but also explored are the safety and sanitation factors and management problems in a…