EAGLE Monitors by Collecting Facts and Generating Obligations

NASA Technical Reports Server (NTRS)

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

2003-01-01

We present a rule-based framework, called EAGLE, that has been shown to be capable of defining and implementing a range of finite trace monitoring logics, including future and past time temporal logic, extended regular expressions, real-time and metric temporal logics, interval logics, forms of quantified temporal logics, and so on. A monitor for an EAGLE formula checks if a finite trace of states satisfies the given formula. We present, in details, an algorithm for the synthesis of monitors for EAGLE. The algorithm is implemented as a Java application and involves novel techniques for rule definition, manipulation and execution. Monitoring is achieved on a state-by-state basis avoiding any need to store the input trace of states. Our initial experiments have been successful as EAGLE detected a previously unknown bug while testing a planetary rover controller.

Fuzzy forecasting based on fuzzy-trend logical relationship groups.

PubMed

Chen, Shyi-Ming; Wang, Nai-Yi

2010-10-01

In this paper, we present a new method to predict the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) based on fuzzy-trend logical relationship groups (FTLRGs). The proposed method divides fuzzy logical relationships into FTLRGs based on the trend of adjacent fuzzy sets appearing in the antecedents of fuzzy logical relationships. First, we apply an automatic clustering algorithm to cluster the historical data into intervals of different lengths. Then, we define fuzzy sets based on these intervals of different lengths. Then, the historical data are fuzzified into fuzzy sets to derive fuzzy logical relationships. Then, we divide the fuzzy logical relationships into FTLRGs for forecasting the TAIEX. Moreover, we also apply the proposed method to forecast the enrollments and the inventory demand, respectively. The experimental results show that the proposed method gets higher average forecasting accuracy rates than the existing methods.

Fuzzy Logic-based Intelligent Scheme for Enhancing QoS of Vertical Handover Decision in Vehicular Ad-hoc Networks

NASA Astrophysics Data System (ADS)

Azzali, F.; Ghazali, O.; Omar, M. H.

2017-08-01

The design of next generation networks in various technologies under the “Anywhere, Anytime” paradigm offers seamless connectivity across different coverage. A conventional algorithm such as RSSThreshold algorithm, that only uses the received strength signal (RSS) as a metric, will decrease handover performance regarding handover latency, delay, packet loss, and handover failure probability. Moreover, the RSS-based algorithm is only suitable for horizontal handover decision to examine the quality of service (QoS) compared to the vertical handover decision in advanced technologies. In the next generation network, vertical handover can be started based on the user’s convenience or choice rather than connectivity reasons. This study proposes a vertical handover decision algorithm that uses a Fuzzy Logic (FL) algorithm, to increase QoS performance in heterogeneous vehicular ad-hoc networks (VANET). The study uses network simulator 2.29 (NS 2.29) along with the mobility traffic network and generator to implement simulation scenarios and topologies. This helps the simulation to achieve a realistic VANET mobility scenario. The required analysis on the performance of QoS in the vertical handover can thus be conducted. The proposed Fuzzy Logic algorithm shows improvement over the conventional algorithm (RSSThreshold) in the average percentage of handover QoS whereby it achieves 20%, 21% and 13% improvement on handover latency, delay, and packet loss respectively. This is achieved through triggering a process in layer two and three that enhances the handover performance.

Evaluation of a fuzzy logic ramp metering algorithm : a comparative study among three ramp metering algorithms used in the greater Seattle area

DOT National Transportation Integrated Search

2000-02-01

A Fuzzy Logic Ramp Metering Algorithm was implemented on 126 ramps in the greater Seattle area. Two multiple-ramp study sites were evaluted by comparing the fuzzy logic controller (FLC) to the other two ramp metering algorithms in operation at those ...

Fuzzy Logic Based Anomaly Detection for Embedded Network Security Cyber Sensor

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

Ondrej Linda; Todd Vollmer; Jason Wright

Resiliency and security in critical infrastructure control systems in the modern world of cyber terrorism constitute a relevant concern. Developing a network security system specifically tailored to the requirements of such critical assets is of a primary importance. This paper proposes a novel learning algorithm for anomaly based network security cyber sensor together with its hardware implementation. The presented learning algorithm constructs a fuzzy logic rule based model of normal network behavior. Individual fuzzy rules are extracted directly from the stream of incoming packets using an online clustering algorithm. This learning algorithm was specifically developed to comply with the constrainedmore » computational requirements of low-cost embedded network security cyber sensors. The performance of the system was evaluated on a set of network data recorded from an experimental test-bed mimicking the environment of a critical infrastructure control system.« less

Fluorescence intensity positivity classification of Hep-2 cells images using fuzzy logic

NASA Astrophysics Data System (ADS)

Sazali, Dayang Farzana Abang; Janier, Josefina Barnachea; May, Zazilah Bt.

2014-10-01

Indirect Immunofluorescence (IIF) is a good standard used for antinuclear autoantibody (ANA) test using Hep-2 cells to determine specific diseases. Different classifier algorithm methods have been proposed in previous works however, there still no valid set as a standard to classify the fluorescence intensity. This paper presents the use of fuzzy logic to classify the fluorescence intensity and to determine the positivity of the Hep-2 cell serum samples. The fuzzy algorithm involves the image pre-processing by filtering the noises and smoothen the image, converting the red, green and blue (RGB) color space of images to luminosity layer, chromaticity layer "a" and "b" (LAB) color space where the mean value of the lightness and chromaticity layer "a" was extracted and classified by using fuzzy logic algorithm based on the standard score ranges of antinuclear autoantibody (ANA) fluorescence intensity. Using 100 data sets of positive and intermediate fluorescence intensity for testing the performance measurements, the fuzzy logic obtained an accuracy of intermediate and positive class as 85% and 87% respectively.

Applications of fuzzy logic to control and decision making

NASA Technical Reports Server (NTRS)

Lea, Robert N.; Jani, Yashvant

1991-01-01

Long range space missions will require high operational efficiency as well as autonomy to enhance the effectivity of performance. Fuzzy logic technology has been shown to be powerful and robust in interpreting imprecise measurements and generating appropriate control decisions for many space operations. Several applications are underway, studying the fuzzy logic approach to solving control and decision making problems. Fuzzy logic algorithms for relative motion and attitude control have been developed and demonstrated for proximity operations. Based on this experience, motion control algorithms that include obstacle avoidance were developed for a Mars Rover prototype for maneuvering during the sample collection process. A concept of an intelligent sensor system that can identify objects and track them continuously and learn from its environment is under development to support traffic management and proximity operations around the Space Station Freedom. For safe and reliable operation of Lunar/Mars based crew quarters, high speed controllers with ability to combine imprecise measurements from several sensors is required. A fuzzy logic approach that uses high speed fuzzy hardware chips is being studied.

CONCAM's Fuzzy-Logic All-Sky Star Recognition Algorithm

NASA Astrophysics Data System (ADS)

Shamir, L.; Nemiroff, R. J.

2004-05-01

One of the purposes of the global Night Sky Live (NSL) network of fisheye CONtinuous CAMeras (CONCAMs) is to monitor and archive the entire bright night sky, track stellar variability, and search for transients. The high quality of raw CONCAM data allows automation of stellar object recognition, although distortions of the fisheye lens and frequent slight shifts in CONCAM orientations can make even this seemingly simple task formidable. To meet this challenge, a fuzzy logic based algorithm has been developed that transforms (x,y) image coordinates in the CCD frame into fuzzy right ascension and declination coordinates for use in matching with star catalogs. Using a training set of reference stars, the algorithm statically builds the fuzzy logic model. At runtime, the algorithm searches for peaks, and then applies the fuzzy logic model to perform the coordinate transformation before choosing the optimal star catalog match. The present fuzzy-logic algorithm works much better than our first generation, straightforward coordinate transformation formula. Following this essential step, algorithms dealing with the higher level data products can then provide a stream of photometry for a few hundred stellar objects visible in the night sky. Accurate photometry further enables the computation of all-sky maps of skyglow and opacity, as well as a search for uncataloged transients. All information is stored in XML-like tagged ASCII files that are instantly copied to the public domain and available at http://NightSkyLive.net. Currently, the NSL software detects stars and creates all-sky image files from eight different locations around the globe every 3 minutes and 56 seconds.

The Type-2 Fuzzy Logic Controller-Based Maximum Power Point Tracking Algorithm and the Quadratic Boost Converter for Pv System

NASA Astrophysics Data System (ADS)

Altin, Necmi

2018-05-01

An interval type-2 fuzzy logic controller-based maximum power point tracking algorithm and direct current-direct current (DC-DC) converter topology are proposed for photovoltaic (PV) systems. The proposed maximum power point tracking algorithm is designed based on an interval type-2 fuzzy logic controller that has an ability to handle uncertainties. The change in PV power and the change in PV voltage are determined as inputs of the proposed controller, while the change in duty cycle is determined as the output of the controller. Seven interval type-2 fuzzy sets are determined and used as membership functions for input and output variables. The quadratic boost converter provides high voltage step-up ability without any reduction in performance and stability of the system. The performance of the proposed system is validated through MATLAB/Simulink simulations. It is seen that the proposed system provides high maximum power point tracking speed and accuracy even for fast changing atmospheric conditions and high voltage step-up requirements.

Programmer's guide to the fuzzy logic ramp metering algorithm : software design, integration, testing, and evaluation

DOT National Transportation Integrated Search

2000-02-01

A Fuzzy Logic Ramp Metering Algorithm was implemented on 126 ramps in the greater Seattle area. This report documents the implementation of the Fuzzy Logic Ramp Metering Algorithm at the Northwest District of the Washington State Department of Transp...

Design Genetic Algorithm Optimization Education Software Based Fuzzy Controller for a Tricopter Fly Path Planning

ERIC Educational Resources Information Center

Tran, Huu-Khoa; Chiou, Juing -Shian; Peng, Shou-Tao

2016-01-01

In this paper, the feasibility of a Genetic Algorithm Optimization (GAO) education software based Fuzzy Logic Controller (GAO-FLC) for simulating the flight motion control of Unmanned Aerial Vehicles (UAVs) is designed. The generated flight trajectories integrate the optimized Scaling Factors (SF) fuzzy controller gains by using GAO algorithm. The…

Machine Learning-based Intelligent Formal Reasoning and Proving System

NASA Astrophysics Data System (ADS)

Chen, Shengqing; Huang, Xiaojian; Fang, Jiaze; Liang, Jia

2018-03-01

The reasoning system can be used in many fields. How to improve reasoning efficiency is the core of the design of system. Through the formal description of formal proof and the regular matching algorithm, after introducing the machine learning algorithm, the system of intelligent formal reasoning and verification has high efficiency. The experimental results show that the system can verify the correctness of propositional logic reasoning and reuse the propositional logical reasoning results, so as to obtain the implicit knowledge in the knowledge base and provide the basic reasoning model for the construction of intelligent system.

Electrically reconfigurable logic array

NASA Technical Reports Server (NTRS)

Agarwal, R. K.

1982-01-01

To compose the complicated systems using algorithmically specialized logic circuits or processors, one solution is to perform relational computations such as union, division and intersection directly on hardware. These relations can be pipelined efficiently on a network of processors having an array configuration. These processors can be designed and implemented with a few simple cells. In order to determine the state-of-the-art in Electrically Reconfigurable Logic Array (ERLA), a survey of the available programmable logic array (PLA) and the logic circuit elements used in such arrays was conducted. Based on this survey some recommendations are made for ERLA devices.

Principles of logic and the use of digital geographic information systems

USGS Publications Warehouse

Robinove, Charles Joseph

1986-01-01

Digital geographic information systems allow many different types of data to be spatially and statistically analyzed. Logical operations can be performed on individual or multiple data planes by algorithms that can be implemented in computer systems. Users and creators of the systems should fully understand these operations. This paper describes the relationships of layers and features in geographic data bases and the principles of logic that can be applied by geographic information systems and suggests that a thorough knowledge of the data that are entered into a geographic data base and of the logical operations will produce results that are most satisfactory to the user. Methods of spatial analysis are reduced to their primitive logical operations and explained to further such understanding.

Directional passability and quadratic steering logic for pyramid-type single gimbal control moment gyros

NASA Astrophysics Data System (ADS)

Yamada, Katsuhiko; Jikuya, Ichiro

2014-09-01

Singularity analysis and the steering logic of pyramid-type single gimbal control moment gyros are studied. First, a new concept of directional passability in a specified direction is introduced to investigate the structure of an elliptic singular surface. The differences between passability and directional passability are discussed in detail and are visualized for 0H, 2H, and 4H singular surfaces. Second, quadratic steering logic (QSL), a new steering logic for passing the singular surface, is investigated. The algorithm is based on the quadratic constrained quadratic optimization problem and is reduced to the Newton method by using Gröbner bases. The proposed steering logic is demonstrated through numerical simulations for both constant torque maneuvering examples and attitude control examples.

Logical NAND and NOR Operations Using Algorithmic Self-assembly of DNA Molecules

NASA Astrophysics Data System (ADS)

Wang, Yanfeng; Cui, Guangzhao; Zhang, Xuncai; Zheng, Yan

DNA self-assembly is the most advanced and versatile system that has been experimentally demonstrated for programmable construction of patterned systems on the molecular scale. It has been demonstrated that the simple binary arithmetic and logical operations can be computed by the process of self assembly of DNA tiles. Here we report a one-dimensional algorithmic self-assembly of DNA triple-crossover molecules that can be used to execute five steps of a logical NAND and NOR operations on a string of binary bits. To achieve this, abstract tiles were translated into DNA tiles based on triple-crossover motifs. Serving as input for the computation, long single stranded DNA molecules were used to nucleate growth of tiles into algorithmic crystals. Our method shows that engineered DNA self-assembly can be treated as a bottom-up design techniques, and can be capable of designing DNA computer organization and architecture.

Satisfiability of logic programming based on radial basis function neural networks

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

Hamadneh, Nawaf; Sathasivam, Saratha; Tilahun, Surafel Luleseged

2014-07-10

In this paper, we propose a new technique to test the Satisfiability of propositional logic programming and quantified Boolean formula problem in radial basis function neural networks. For this purpose, we built radial basis function neural networks to represent the proportional logic which has exactly three variables in each clause. We used the Prey-predator algorithm to calculate the output weights of the neural networks, while the K-means clustering algorithm is used to determine the hidden parameters (the centers and the widths). Mean of the sum squared error function is used to measure the activity of the two algorithms. We appliedmore » the developed technique with the recurrent radial basis function neural networks to represent the quantified Boolean formulas. The new technique can be applied to solve many applications such as electronic circuits and NP-complete problems.« less

SAT Encoding of Unification in EL

NASA Astrophysics Data System (ADS)

Baader, Franz; Morawska, Barbara

Unification in Description Logics has been proposed as a novel inference service that can, for example, be used to detect redundancies in ontologies. In a recent paper, we have shown that unification in EL is NP-complete, and thus of a complexity that is considerably lower than in other Description Logics of comparably restricted expressive power. In this paper, we introduce a new NP-algorithm for solving unification problems in EL, which is based on a reduction to satisfiability in propositional logic (SAT). The advantage of this new algorithm is, on the one hand, that it allows us to employ highly optimized state-of-the-art SAT solvers when implementing an EL-unification algorithm. On the other hand, this reduction provides us with a proof of the fact that EL-unification is in NP that is much simpler than the one given in our previous paper on EL-unification.

Quantum logic gates based on ballistic transport in graphene

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

Dragoman, Daniela; Academy of Romanian Scientists, Splaiul Independentei 54, 050094 Bucharest; Dragoman, Mircea, E-mail: mircea.dragoman@imt.ro

2016-03-07

The paper presents various configurations for the implementation of graphene-based Hadamard, C-phase, controlled-NOT, and Toffoli gates working at room temperature. These logic gates, essential for any quantum computing algorithm, involve ballistic graphene devices for qubit generation and processing and can be fabricated using existing nanolithographical techniques. All quantum gate configurations are based on the very large mean-free-paths of carriers in graphene at room temperature.

Relay Protection and Automation Systems Based on Programmable Logic Integrated Circuits

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

Lashin, A. V., E-mail: LashinAV@lhp.ru; Kozyrev, A. V.

One of the most promising forms of developing the apparatus part of relay protection and automation devices is considered. The advantages of choosing programmable logic integrated circuits to obtain adaptive technological algorithms in power system protection and control systems are pointed out. The technical difficulties in the problems which today stand in the way of using relay protection and automation systems are indicated and a new technology for solving these problems is presented. Particular attention is devoted to the possibility of reconfiguring the logic of these devices, using programmable logic integrated circuits.

An Adaptive Fuzzy-Logic Traffic Control System in Conditions of Saturated Transport Stream

PubMed Central

Marakhimov, A. R.; Igamberdiev, H. Z.; Umarov, Sh. X.

2016-01-01

This paper considers the problem of building adaptive fuzzy-logic traffic control systems (AFLTCS) to deal with information fuzziness and uncertainty in case of heavy traffic streams. Methods of formal description of traffic control on the crossroads based on fuzzy sets and fuzzy logic are proposed. This paper also provides efficient algorithms for implementing AFLTCS and develops the appropriate simulation models to test the efficiency of suggested approach. PMID:27517081

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.

Fuzzy logic in autonomous orbital operations

NASA Technical Reports Server (NTRS)

Lea, Robert N.; Jani, Yashvant

1991-01-01

Fuzzy logic can be used advantageously in autonomous orbital operations that require the capability of handling imprecise measurements from sensors. Several applications are underway to investigate fuzzy logic approaches and develop guidance and control algorithms for autonomous orbital operations. Translational as well as rotational control of a spacecraft have been demonstrated using space shuttle simulations. An approach to a camera tracking system has been developed to support proximity operations and traffic management around the Space Station Freedom. Pattern recognition and object identification algorithms currently under development will become part of this camera system at an appropriate level in the future. A concept to control environment and life support systems for large Lunar based crew quarters is also under development. Investigations in the area of reinforcement learning, utilizing neural networks, combined with a fuzzy logic controller, are planned as a joint project with the Ames Research Center.

Logic circuits based on molecular spider systems.

PubMed

Mo, Dandan; Lakin, Matthew R; Stefanovic, Darko

2016-08-01

Spatial locality brings the advantages of computation speed-up and sequence reuse to molecular computing. In particular, molecular walkers that undergo localized reactions are of interest for implementing logic computations at the nanoscale. We use molecular spider walkers to implement logic circuits. We develop an extended multi-spider model with a dynamic environment wherein signal transmission is triggered via localized reactions, and use this model to implement three basic gates (AND, OR, NOT) and a cascading mechanism. We develop an algorithm to automatically generate the layout of the circuit. We use a kinetic Monte Carlo algorithm to simulate circuit computations, and we analyze circuit complexity: our design scales linearly with formula size and has a logarithmic time complexity. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Distributed autonomous systems: resource management, planning, and control algorithms

NASA Astrophysics Data System (ADS)

Smith, James F., III; Nguyen, ThanhVu H.

2005-05-01

Distributed autonomous systems, i.e., systems that have separated distributed components, each of which, exhibit some degree of autonomy are increasingly providing solutions to naval and other DoD problems. Recently developed control, planning and resource allocation algorithms for two types of distributed autonomous systems will be discussed. The first distributed autonomous system (DAS) to be discussed consists of a collection of unmanned aerial vehicles (UAVs) that are under fuzzy logic control. The UAVs fly and conduct meteorological sampling in a coordinated fashion determined by their fuzzy logic controllers to determine the atmospheric index of refraction. Once in flight no human intervention is required. A fuzzy planning algorithm determines the optimal trajectory, sampling rate and pattern for the UAVs and an interferometer platform while taking into account risk, reliability, priority for sampling in certain regions, fuel limitations, mission cost, and related uncertainties. The real-time fuzzy control algorithm running on each UAV will give the UAV limited autonomy allowing it to change course immediately without consulting with any commander, request other UAVs to help it, alter its sampling pattern and rate when observing interesting phenomena, or to terminate the mission and return to base. The algorithms developed will be compared to a resource manager (RM) developed for another DAS problem related to electronic attack (EA). This RM is based on fuzzy logic and optimized by evolutionary algorithms. It allows a group of dissimilar platforms to use EA resources distributed throughout the group. For both DAS types significant theoretical and simulation results will be presented.

Weighted Description Logics Preference Formulas for Multiattribute Negotiation

NASA Astrophysics Data System (ADS)

Ragone, Azzurra; di Noia, Tommaso; Donini, Francesco M.; di Sciascio, Eugenio; Wellman, Michael P.

We propose a framework to compute the utility of an agreement w.r.t a preference set in a negotiation process. In particular, we refer to preferences expressed as weighted formulas in a decidable fragment of First-order Logic and agreements expressed as a formula. We ground our framework in Description Logics (DL) endowed with disjunction, to be compliant with Semantic Web technologies. A logic based approach to preference representation allows, when a background knowledge base is exploited, to relax the often unrealistic assumption of additive independence among attributes. We provide suitable definitions of the problem and present algorithms to compute utility in our setting. We also validate our approach through an experimental evaluation.

Reusable rocket engine turbopump health monitoring system, part 3

NASA Technical Reports Server (NTRS)

Perry, John G.

1989-01-01

Degradation mechanisms and sensor identification/selection resulted in a list of degradation modes and a list of sensors that are utilized in the diagnosis of these degradation modes. The sensor list is divided into primary and secondary indicators of the corresponding degradation modes. The signal conditioning requirements are discussed, describing the methods of producing the Space Shuttle Main Engine (SSME) post-hot-fire test data to be utilized by the Health Monitoring System. Development of the diagnostic logic and algorithms is also presented. The knowledge engineering approach, as utilized, includes the knowledge acquisition effort, characterization of the expert's problem solving strategy, conceptually defining the form of the applicable knowledge base, and rule base, and identifying an appropriate inferencing mechanism for the problem domain. The resulting logic flow graphs detail the diagnosis/prognosis procedure as followed by the experts. The nature and content of required support data and databases is also presented. The distinction between deep and shallow types of knowledge is identified. Computer coding of the Health Monitoring System is shown to follow the logical inferencing of the logic flow graphs/algorithms.

Minimally inconsistent reasoning in Semantic Web.

PubMed

Zhang, Xiaowang

2017-01-01

Reasoning with inconsistencies is an important issue for Semantic Web as imperfect information is unavoidable in real applications. For this, different paraconsistent approaches, due to their capacity to draw as nontrivial conclusions by tolerating inconsistencies, have been proposed to reason with inconsistent description logic knowledge bases. However, existing paraconsistent approaches are often criticized for being too skeptical. To this end, this paper presents a non-monotonic paraconsistent version of description logic reasoning, called minimally inconsistent reasoning, where inconsistencies tolerated in the reasoning are minimized so that more reasonable conclusions can be inferred. Some desirable properties are studied, which shows that the new semantics inherits advantages of both non-monotonic reasoning and paraconsistent reasoning. A complete and sound tableau-based algorithm, called multi-valued tableaux, is developed to capture the minimally inconsistent reasoning. In fact, the tableaux algorithm is designed, as a framework for multi-valued DL, to allow for different underlying paraconsistent semantics, with the mere difference in the clash conditions. Finally, the complexity of minimally inconsistent description logic reasoning is shown on the same level as the (classical) description logic reasoning.

Minimally inconsistent reasoning in Semantic Web

PubMed Central

Zhang, Xiaowang

2017-01-01

Reasoning with inconsistencies is an important issue for Semantic Web as imperfect information is unavoidable in real applications. For this, different paraconsistent approaches, due to their capacity to draw as nontrivial conclusions by tolerating inconsistencies, have been proposed to reason with inconsistent description logic knowledge bases. However, existing paraconsistent approaches are often criticized for being too skeptical. To this end, this paper presents a non-monotonic paraconsistent version of description logic reasoning, called minimally inconsistent reasoning, where inconsistencies tolerated in the reasoning are minimized so that more reasonable conclusions can be inferred. Some desirable properties are studied, which shows that the new semantics inherits advantages of both non-monotonic reasoning and paraconsistent reasoning. A complete and sound tableau-based algorithm, called multi-valued tableaux, is developed to capture the minimally inconsistent reasoning. In fact, the tableaux algorithm is designed, as a framework for multi-valued DL, to allow for different underlying paraconsistent semantics, with the mere difference in the clash conditions. Finally, the complexity of minimally inconsistent description logic reasoning is shown on the same level as the (classical) description logic reasoning. PMID:28750030

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.

Fuzzy Logic-Based Audio Pattern Recognition

NASA Astrophysics Data System (ADS)

Malcangi, M.

2008-11-01

Audio and audio-pattern recognition is becoming one of the most important technologies to automatically control embedded systems. Fuzzy logic may be the most important enabling methodology due to its ability to rapidly and economically model such application. An audio and audio-pattern recognition engine based on fuzzy logic has been developed for use in very low-cost and deeply embedded systems to automate human-to-machine and machine-to-machine interaction. This engine consists of simple digital signal-processing algorithms for feature extraction and normalization, and a set of pattern-recognition rules manually tuned or automatically tuned by a self-learning process.

Hybrid genetic algorithm in the Hopfield network for maximum 2-satisfiability problem

NASA Astrophysics Data System (ADS)

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

2017-08-01

Heuristic method was designed for finding optimal solution more quickly compared to classical methods which are too complex to comprehend. In this study, a hybrid approach that utilizes Hopfield network and genetic algorithm in doing maximum 2-Satisfiability problem (MAX-2SAT) was proposed. Hopfield neural network was used to minimize logical inconsistency in interpretations of logic clauses or program. Genetic algorithm (GA) has pioneered the implementation of methods that exploit the idea of combination and reproduce a better solution. The simulation incorporated with and without genetic algorithm will be examined by using Microsoft Visual 2013 C++ Express software. The performance of both searching techniques in doing MAX-2SAT was evaluate based on global minima ratio, ratio of satisfied clause and computation time. The result obtained form the computer simulation demonstrates the effectiveness and acceleration features of genetic algorithm in doing MAX-2SAT in Hopfield network.

An acceleration framework for synthetic aperture radar algorithms

NASA Astrophysics Data System (ADS)

Kim, Youngsoo; Gloster, Clay S.; Alexander, Winser E.

2017-04-01

Algorithms for radar signal processing, such as Synthetic Aperture Radar (SAR) are computationally intensive and require considerable execution time on a general purpose processor. Reconfigurable logic can be used to off-load the primary computational kernel onto a custom computing machine in order to reduce execution time by an order of magnitude as compared to kernel execution on a general purpose processor. Specifically, Field Programmable Gate Arrays (FPGAs) can be used to accelerate these kernels using hardware-based custom logic implementations. In this paper, we demonstrate a framework for algorithm acceleration. We used SAR as a case study to illustrate the potential for algorithm acceleration offered by FPGAs. Initially, we profiled the SAR algorithm and implemented a homomorphic filter using a hardware implementation of the natural logarithm. Experimental results show a linear speedup by adding reasonably small processing elements in Field Programmable Gate Array (FPGA) as opposed to using a software implementation running on a typical general purpose processor.

Architecture and data processing alternatives for Tse computer. Volume 1: Tse logic design concepts and the development of image processing machine architectures

NASA Technical Reports Server (NTRS)

Rickard, D. A.; Bodenheimer, R. E.

1976-01-01

Digital computer components which perform two dimensional array logic operations (Tse logic) on binary data arrays are described. The properties of Golay transforms which make them useful in image processing are reviewed, and several architectures for Golay transform processors are presented with emphasis on the skeletonizing algorithm. Conventional logic control units developed for the Golay transform processors are described. One is a unique microprogrammable control unit that uses a microprocessor to control the Tse computer. The remaining control units are based on programmable logic arrays. Performance criteria are established and utilized to compare the various Golay transform machines developed. A critique of Tse logic is presented, and recommendations for additional research are included.

Quantum Algorithmic Readout in Multi-Ion Clocks.

PubMed

Schulte, M; Lörch, N; Leroux, I D; Schmidt, P O; Hammerer, K

2016-01-08

Optical clocks based on ensembles of trapped ions promise record frequency accuracy with good short-term stability. Most suitable ion species lack closed transitions, so the clock signal must be read out indirectly by transferring the quantum state of the clock ions to cotrapped logic ions of a different species. Existing methods of quantum logic readout require a linear overhead in either time or the number of logic ions. Here we describe a quantum algorithmic readout whose overhead scales logarithmically with the number of clock ions in both of these respects. The scheme allows a quantum nondemolition readout of the number of excited clock ions using a single multispecies gate operation which can also be used in other areas of ion trap technology such as quantum information processing, quantum simulations, metrology, and precision spectroscopy.

New mode switching algorithm for the JPL 70-meter antenna servo controller

NASA Technical Reports Server (NTRS)

Nickerson, J. A.

1988-01-01

The design of control mode switching algorithms and logic for JPL's 70 m antenna servo controller are described. The old control mode switching logic was reviewed and perturbation problems were identified. Design approaches for mode switching are presented and the final design is described. Simulations used to compare old and new mode switching algorithms and logic show that the new mode switching techniques will significantly reduce perturbation problems.

Algorithm design, user interface, and optimization procedure for a fuzzy logic ramp metering algorithm : a training manual for freeway operations engineers

DOT National Transportation Integrated Search

2000-02-01

This training manual describes the fuzzy logic ramp metering algorithm in detail, as implemented system-wide in the greater Seattle area. The method of defining the inputs to the controller and optimizing the performance of the algorithm is explained...

Automata-Based Verification of Temporal Properties on Running Programs

NASA Technical Reports Server (NTRS)

Giannakopoulou, Dimitra; Havelund, Klaus; Lan, Sonie (Technical Monitor)

2001-01-01

This paper presents an approach to checking a running program against its Linear Temporal Logic (LTL) specifications. LTL is a widely used logic for expressing properties of programs viewed as sets of executions. Our approach consists of translating LTL formulae to finite-state automata, which are used as observers of the program behavior. The translation algorithm we propose modifies standard LTL to Buchi automata conversion techniques to generate automata that check finite program traces. The algorithm has been implemented in a tool, which has been integrated with the generic JPaX framework for runtime analysis of Java programs.

Adaptive process control using fuzzy logic and genetic algorithms

NASA Technical Reports Server (NTRS)

Karr, C. L.

1993-01-01

Researchers at the U.S. Bureau of Mines have developed adaptive process control systems in which genetic algorithms (GA's) are used to augment fuzzy logic controllers (FLC's). GA's are search algorithms that rapidly locate near-optimum solutions to a wide spectrum of problems by modeling the search procedures of natural genetics. FLC's are rule based systems that efficiently manipulate a problem environment by modeling the 'rule-of-thumb' strategy used in human decision making. Together, GA's and FLC's possess the capabilities necessary to produce powerful, efficient, and robust adaptive control systems. To perform efficiently, such control systems require a control element to manipulate the problem environment, and a learning element to adjust to the changes in the problem environment. Details of an overall adaptive control system are discussed. A specific laboratory acid-base pH system is used to demonstrate the ideas presented.

Adaptive Process Control with Fuzzy Logic and Genetic Algorithms

NASA Technical Reports Server (NTRS)

Karr, C. L.

1993-01-01

Researchers at the U.S. Bureau of Mines have developed adaptive process control systems in which genetic algorithms (GA's) are used to augment fuzzy logic controllers (FLC's). GA's are search algorithms that rapidly locate near-optimum solutions to a wide spectrum of problems by modeling the search procedures of natural genetics. FLC's are rule based systems that efficiently manipulate a problem environment by modeling the 'rule-of-thumb' strategy used in human decision-making. Together, GA's and FLC's possess the capabilities necessary to produce powerful, efficient, and robust adaptive control systems. To perform efficiently, such control systems require a control element to manipulate the problem environment, an analysis element to recognize changes in the problem environment, and a learning element to adjust to the changes in the problem environment. Details of an overall adaptive control system are discussed. A specific laboratory acid-base pH system is used to demonstrate the ideas presented.

HWDA: A coherence recognition and resolution algorithm for hybrid web data aggregation

NASA Astrophysics Data System (ADS)

Guo, Shuhang; Wang, Jian; Wang, Tong

2017-09-01

Aiming at the object confliction recognition and resolution problem for hybrid distributed data stream aggregation, a distributed data stream object coherence solution technology is proposed. Firstly, the framework was defined for the object coherence conflict recognition and resolution, named HWDA. Secondly, an object coherence recognition technology was proposed based on formal language description logic and hierarchical dependency relationship between logic rules. Thirdly, a conflict traversal recognition algorithm was proposed based on the defined dependency graph. Next, the conflict resolution technology was prompted based on resolution pattern matching including the definition of the three types of conflict, conflict resolution matching pattern and arbitration resolution method. At last, the experiment use two kinds of web test data sets to validate the effect of application utilizing the conflict recognition and resolution technology of HWDA.

Coordination Logic for Repulsive Resolution Maneuvers

NASA Technical Reports Server (NTRS)

Narkawicz, Anthony J.; Munoz, Cesar A.; Dutle, Aaron M.

2016-01-01

This paper presents an algorithm for determining the direction an aircraft should maneuver in the event of a potential conflict with another aircraft. The algorithm is implicitly coordinated, meaning that with perfectly reliable computations and information, it will in- dependently provide directional information that is guaranteed to be coordinated without any additional information exchange or direct communication. The logic is inspired by the logic of TCAS II, the airborne system designed to reduce the risk of mid-air collisions between aircraft. TCAS II provides pilots with only vertical resolution advice, while the proposed algorithm, using a similar logic, provides implicitly coordinated vertical and horizontal directional advice.

Lithium-ion battery state of function estimation based on fuzzy logic algorithm with associated variables

NASA Astrophysics Data System (ADS)

Gan, L.; Yang, F.; Shi, Y. F.; He, H. L.

2017-11-01

Many occasions related to batteries demand to know how much continuous and instantaneous power can batteries provide such as the rapidly developing electric vehicles. As the large-scale applications of lithium-ion batteries, lithium-ion batteries are used to be our research object. Many experiments are designed to get the lithium-ion battery parameters to ensure the relevance and reliability of the estimation. To evaluate the continuous and instantaneous load capability of a battery called state-of-function (SOF), this paper proposes a fuzzy logic algorithm based on battery state-of-charge(SOC), state-of-health(SOH) and C-rate parameters. Simulation and experimental results indicate that the proposed approach is suitable for battery SOF estimation.

Fuzzy logic applications to expert systems and control

NASA Technical Reports Server (NTRS)

Lea, Robert N.; Jani, Yashvant

1991-01-01

A considerable amount of work on the development of fuzzy logic algorithms and application to space related control problems has been done at the Johnson Space Center (JSC) over the past few years. Particularly, guidance control systems for space vehicles during proximity operations, learning systems utilizing neural networks, control of data processing during rendezvous navigation, collision avoidance algorithms, camera tracking controllers, and tether controllers have been developed utilizing fuzzy logic technology. Several other areas in which fuzzy sets and related concepts are being considered at JSC are diagnostic systems, control of robot arms, pattern recognition, and image processing. It has become evident, based on the commercial applications of fuzzy technology in Japan and China during the last few years, that this technology should be exploited by the government as well as private industry for energy savings.

Acoustic logic gates and Boolean operation based on self-collimating acoustic beams

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

Zhang, Ting; Xu, Jian-yi; Cheng, Ying, E-mail: chengying@nju.edu.cn

2015-03-16

The reveal of self-collimation effect in two-dimensional (2D) photonic or acoustic crystals has opened up possibilities for signal manipulation. In this paper, we have proposed acoustic logic gates based on the linear interference of self-collimated beams in 2D sonic crystals (SCs) with line-defects. The line defects on the diagonal of the 2D square SCs are actually functioning as a 3 dB splitter. By adjusting the phase difference between two input signals, the basic Boolean logic functions such as XOR, OR, AND, and NOT are achieved both theoretically and experimentally. Due to the non-diffracting property of self-collimation beams, more complex Boolean logicmore » and algorithms such as NAND, NOR, and XNOR can be realized by cascading the basic logic gates. The achievement of acoustic logic gates and Boolean operation provides a promising approach for acoustic signal computing and manipulations.« less

Optimization of topological quantum algorithms using Lattice Surgery is hard

NASA Astrophysics Data System (ADS)

Herr, Daniel; Nori, Franco; Devitt, Simon

The traditional method for computation in the surface code or the Raussendorf model is the creation of holes or ''defects'' within the encoded lattice of qubits which are manipulated via topological braiding to enact logic gates. However, this is not the only way to achieve universal, fault-tolerant computation. In this work we turn attention to the Lattice Surgery representation, which realizes encoded logic operations without destroying the intrinsic 2D nearest-neighbor interactions sufficient for braided based logic and achieves universality without using defects for encoding information. In both braided and lattice surgery logic there are open questions regarding the compilation and resource optimization of quantum circuits. Optimization in braid-based logic is proving to be difficult to define and the classical complexity associated with this problem has yet to be determined. In the context of lattice surgery based logic, we can introduce an optimality condition, which corresponds to a circuit with lowest amount of physical qubit requirements, and prove that the complexity of optimizing the geometric (lattice surgery) representation of a quantum circuit is NP-hard.

Hand-Held Calculator Algorithms for Coastal Engineering.

DTIC Science & Technology

1982-01-01

and water depth at the structure toe, ds. The development of the equation is derived on the solution sheet included with program 104R. Algorithm uses...Limited Design Breaking Wave Height at Structure (AOS logic)... .... ....... ......... .54 6. 105R Wave Transmission - Fuchs’ Equation (RPN logic...58 105A Wave Transmission - Fuchs’ Equation (AOS logic). . . . 61 APPENDIX BLANK PROGRAM FORMS ........ ....................... ... 67 4

Incident detection on an arterial roadway

DOT National Transportation Integrated Search

1997-01-01

Presented here is the development of an automatic incident detection algorithm for use on Lakeshore Boulevard, Toronto, Canada, based on volume or occupancy data recorded from fixed-loop detectors. Four prospective logics were based on 20-sec interva...

Path planning of decentralized multi-quadrotor based on fuzzy-cell decomposition algorithm

NASA Astrophysics Data System (ADS)

Iswanto, Wahyunggoro, Oyas; Cahyadi, Adha Imam

2017-04-01

The paper aims to present a design algorithm for multi quadrotor lanes in order to move towards the goal quickly and avoid obstacles in an area with obstacles. There are several problems in path planning including how to get to the goal position quickly and avoid static and dynamic obstacles. To overcome the problem, therefore, the paper presents fuzzy logic algorithm and fuzzy cell decomposition algorithm. Fuzzy logic algorithm is one of the artificial intelligence algorithms which can be applied to robot path planning that is able to detect static and dynamic obstacles. Cell decomposition algorithm is an algorithm of graph theory used to make a robot path map. By using the two algorithms the robot is able to get to the goal position and avoid obstacles but it takes a considerable time because they are able to find the shortest path. Therefore, this paper describes a modification of the algorithms by adding a potential field algorithm used to provide weight values on the map applied for each quadrotor by using decentralized controlled, so that the quadrotor is able to move to the goal position quickly by finding the shortest path. The simulations conducted have shown that multi-quadrotor can avoid various obstacles and find the shortest path by using the proposed algorithms.

The knowledge instinct, cognitive algorithms, modeling of language and cultural evolution

NASA Astrophysics Data System (ADS)

Perlovsky, Leonid I.

2008-04-01

The talk discusses mechanisms of the mind and their engineering applications. The past attempts at designing "intelligent systems" encountered mathematical difficulties related to algorithmic complexity. The culprit turned out to be logic, which in one way or another was used not only in logic rule systems, but also in statistical, neural, and fuzzy systems. Algorithmic complexity is related to Godel's theory, a most fundamental mathematical result. These difficulties were overcome by replacing logic with a dynamic process "from vague to crisp," dynamic logic. It leads to algorithms overcoming combinatorial complexity, and resulting in orders of magnitude improvement in classical problems of detection, tracking, fusion, and prediction in noise. I present engineering applications to pattern recognition, detection, tracking, fusion, financial predictions, and Internet search engines. Mathematical and engineering efficiency of dynamic logic can also be understood as cognitive algorithm, which describes fundamental property of the mind, the knowledge instinct responsible for all our higher cognitive functions: concepts, perception, cognition, instincts, imaginations, intuitions, emotions, including emotions of the beautiful. I present our latest results in modeling evolution of languages and cultures, their interactions in these processes, and role of music in cultural evolution. Experimental data is presented that support the theory. Future directions are outlined.

Fuzzy Logic Module of Convolutional Neural Network for Handwritten Digits Recognition

NASA Astrophysics Data System (ADS)

Popko, E. A.; Weinstein, I. A.

2016-08-01

Optical character recognition is one of the important issues in the field of pattern recognition. This paper presents a method for recognizing handwritten digits based on the modeling of convolutional neural network. The integrated fuzzy logic module based on a structural approach was developed. Used system architecture adjusted the output of the neural network to improve quality of symbol identification. It was shown that proposed algorithm was flexible and high recognition rate of 99.23% was achieved.

Playing Tic-Tac-Toe with a Sugar-Based Molecular Computer.

PubMed

Elstner, M; Schiller, A

2015-08-24

Today, molecules can perform Boolean operations and circuits at a level of higher complexity. However, concatenation of logic gates and inhomogeneous inputs and outputs are still challenging tasks. Novel approaches for logic gate integration are possible when chemical programming and software programming are combined. Here it is shown that a molecular finite automaton based on the concatenated implication function (IMP) of a fluorescent two-component sugar probe via a wiring algorithm is able to play tic-tac-toe.

Simulation of Automatic Incidents Detection Algorithm on the Transport Network

ERIC Educational Resources Information Center

Nikolaev, Andrey B.; Sapego, Yuliya S.; Jakubovich, Anatolij N.; Berner, Leonid I.; Ivakhnenko, Andrey M.

2016-01-01

Management of traffic incident is a functional part of the whole approach to solving traffic problems in the framework of intelligent transport systems. Development of an effective process of traffic incident management is an important part of the transport system. In this research, it's suggested algorithm based on fuzzy logic to detect traffic…

Fuzzy-logic based Q-Learning interference management algorithms in two-tier networks

NASA Astrophysics Data System (ADS)

Xu, Qiang; Xu, Zezhong; Li, Li; Zheng, Yan

2017-10-01

Unloading from macrocell network and enhancing coverage can be realized by deploying femtocells in the indoor scenario. However, the system performance of the two-tier network could be impaired by the co-tier and cross-tier interference. In this paper, a distributed resource allocation scheme is studied when each femtocell base station is self-governed and the resource cannot be assigned centrally through the gateway. A novel Q-Learning interference management scheme is proposed, that is divided into cooperative and independent part. In the cooperative algorithm, the interference information is exchanged between the cell-edge users which are classified by the fuzzy logic in the same cell. Meanwhile, we allocate the orthogonal subchannels to the high-rate cell-edge users to disperse the interference power when the data rate requirement is satisfied. The resource is assigned directly according to the minimum power principle in the independent algorithm. Simulation results are provided to demonstrate the significant performance improvements in terms of the average data rate, interference power and energy efficiency over the cutting-edge resource allocation algorithms.

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

PubMed

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

2012-01-01

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

Monkey search algorithm for ECE components partitioning

NASA Astrophysics Data System (ADS)

Kuliev, Elmar; Kureichik, Vladimir; Kureichik, Vladimir, Jr.

2018-05-01

The paper considers one of the important design problems – a partitioning of electronic computer equipment (ECE) components (blocks). It belongs to the NP-hard class of problems and has a combinatorial and logic nature. In the paper, a partitioning problem formulation can be found as a partition of graph into parts. To solve the given problem, the authors suggest using a bioinspired approach based on a monkey search algorithm. Based on the developed software, computational experiments were carried out that show the algorithm efficiency, as well as its recommended settings for obtaining more effective solutions in comparison with a genetic algorithm.

Time-space modal logic for verification of bit-slice circuits

NASA Astrophysics Data System (ADS)

Hiraishi, Hiromi

1996-03-01

The major goal of this paper is to propose a new modal logic aiming at formal verification of bit-slice circuits. The new logic is called as time-space modal logic and its major feature is that it can handle two transition relations: one for time transition and the other for space transition. As for a verification algorithm, a symbolic model checking algorithm of the new logic is shown. This could be applicable to verification of bit-slice microprocessor of infinite bit width and 1D systolic array of infinite length. A simple benchmark result shows the effectiveness of the proposed approach.

Agent Based Modeling and Simulation Framework for Supply Chain Risk Management

DTIC Science & Technology

2012-03-01

Christopher and Peck 2004) macroeconomic , policy, competition, and resource (Ghoshal 1987) value chain, operational, event, and recurring (Shi 2004...clustering algorithms in agent logic to protect company privacy ( da Silva et al. 2006), aggregation of domain context in agent data analysis logic (Xiang...Operational Availability ( OA ) for FMC and PMC. 75 Mission Capable (MICAP) Hours is the measure of total time (in a month) consumable or reparable

Fuzzy-Based Hybrid Control Algorithm for the Stabilization of a Tri-Rotor UAV.

PubMed

Ali, Zain Anwar; Wang, Daobo; Aamir, Muhammad

2016-05-09

In this paper, a new and novel mathematical fuzzy hybrid scheme is proposed for the stabilization of a tri-rotor unmanned aerial vehicle (UAV). The fuzzy hybrid scheme consists of a fuzzy logic controller, regulation pole-placement tracking (RST) controller with model reference adaptive control (MRAC), in which adaptive gains of the RST controller are being fine-tuned by a fuzzy logic controller. Brushless direct current (BLDC) motors are installed in the triangular frame of the tri-rotor UAV, which helps maintain control on its motion and different altitude and attitude changes, similar to rotorcrafts. MRAC-based MIT rule is proposed for system stability. Moreover, the proposed hybrid controller with nonlinear flight dynamics is shown in the presence of translational and rotational velocity components. The performance of the proposed algorithm is demonstrated via MATLAB simulations, in which the proposed fuzzy hybrid controller is compared with the existing adaptive RST controller. It shows that our proposed algorithm has better transient performance with zero steady-state error, and fast convergence towards stability.

Generalized look-ahead number conversion from signed digit to complement representation with optical logic operations

NASA Astrophysics Data System (ADS)

Qian, Feng; Li, Guoqiang

2001-12-01

In this paper a generalized look-ahead logic algorithm for number conversion from signed-digit to its complement representation is developed. By properly encoding the signed digits, all the operations are performed by binary logic, and unified logical expressions can be obtained for conversion from modified-signed-digit (MSD) to 2's complement, trinary signed-digit (TSD) to 3's complement, and quaternary signed-digit (QSD) to 4's complement. For optical implementation, a parallel logical array module using electron-trapping device is employed, which is suitable for realizing complex logic functions in the form of sum-of-product. The proposed algorithm and architecture are compatible with a general-purpose optoelectronic computing system.

Genetic Algorithm Tuned Fuzzy Logic for Gliding Return Trajectories

NASA Technical Reports Server (NTRS)

Burchett, Bradley T.

2003-01-01

The problem of designing and flying a trajectory for successful recovery of a reusable launch vehicle is tackled using fuzzy logic control with genetic algorithm optimization. The plant is approximated by a simplified three degree of freedom non-linear model. A baseline trajectory design and guidance algorithm consisting of several Mamdani type fuzzy controllers is tuned using a simple genetic algorithm. Preliminary results show that the performance of the overall system is shown to improve with genetic algorithm tuning.

Quality Improvement of Liver Ultrasound Images Using Fuzzy Techniques.

PubMed

Bayani, Azadeh; Langarizadeh, Mostafa; Radmard, Amir Reza; Nejad, Ahmadreza Farzaneh

2016-12-01

Liver ultrasound images are so common and are applied so often to diagnose diffuse liver diseases like fatty liver. However, the low quality of such images makes it difficult to analyze them and diagnose diseases. The purpose of this study, therefore, is to improve the contrast and quality of liver ultrasound images. In this study, a number of image contrast enhancement algorithms which are based on fuzzy logic were applied to liver ultrasound images - in which the view of kidney is observable - using Matlab2013b to improve the image contrast and quality which has a fuzzy definition; just like image contrast improvement algorithms using a fuzzy intensification operator, contrast improvement algorithms applying fuzzy image histogram hyperbolization, and contrast improvement algorithms by fuzzy IF-THEN rules. With the measurement of Mean Squared Error and Peak Signal to Noise Ratio obtained from different images, fuzzy methods provided better results, and their implementation - compared with histogram equalization method - led both to the improvement of contrast and visual quality of images and to the improvement of liver segmentation algorithms results in images. Comparison of the four algorithms revealed the power of fuzzy logic in improving image contrast compared with traditional image processing algorithms. Moreover, contrast improvement algorithm based on a fuzzy intensification operator was selected as the strongest algorithm considering the measured indicators. This method can also be used in future studies on other ultrasound images for quality improvement and other image processing and analysis applications.

Quality Improvement of Liver Ultrasound Images Using Fuzzy Techniques

PubMed Central

Bayani, Azadeh; Langarizadeh, Mostafa; Radmard, Amir Reza; Nejad, Ahmadreza Farzaneh

2016-01-01

Background: Liver ultrasound images are so common and are applied so often to diagnose diffuse liver diseases like fatty liver. However, the low quality of such images makes it difficult to analyze them and diagnose diseases. The purpose of this study, therefore, is to improve the contrast and quality of liver ultrasound images. Methods: In this study, a number of image contrast enhancement algorithms which are based on fuzzy logic were applied to liver ultrasound images - in which the view of kidney is observable - using Matlab2013b to improve the image contrast and quality which has a fuzzy definition; just like image contrast improvement algorithms using a fuzzy intensification operator, contrast improvement algorithms applying fuzzy image histogram hyperbolization, and contrast improvement algorithms by fuzzy IF-THEN rules. Results: With the measurement of Mean Squared Error and Peak Signal to Noise Ratio obtained from different images, fuzzy methods provided better results, and their implementation - compared with histogram equalization method - led both to the improvement of contrast and visual quality of images and to the improvement of liver segmentation algorithms results in images. Conclusion: Comparison of the four algorithms revealed the power of fuzzy logic in improving image contrast compared with traditional image processing algorithms. Moreover, contrast improvement algorithm based on a fuzzy intensification operator was selected as the strongest algorithm considering the measured indicators. This method can also be used in future studies on other ultrasound images for quality improvement and other image processing and analysis applications. PMID:28077898

Therapeutic target discovery using Boolean network attractors: improvements of kali

PubMed Central

Guziolowski, Carito

2018-01-01

In a previous article, an algorithm for identifying therapeutic targets in Boolean networks modelling pathological mechanisms was introduced. In the present article, the improvements made on this algorithm, named kali, are described. These improvements are (i) the possibility to work on asynchronous Boolean networks, (ii) a finer assessment of therapeutic targets and (iii) the possibility to use multivalued logic. kali assumes that the attractors of a dynamical system, such as a Boolean network, are associated with the phenotypes of the modelled biological system. Given a logic-based model of pathological mechanisms, kali searches for therapeutic targets able to reduce the reachability of the attractors associated with pathological phenotypes, thus reducing their likeliness. kali is illustrated on an example network and used on a biological case study. The case study is a published logic-based model of bladder tumorigenesis from which kali returns consistent results. However, like any computational tool, kali can predict but cannot replace human expertise: it is a supporting tool for coping with the complexity of biological systems in the field of drug discovery. PMID:29515890

Coloured Logic Petri Nets and analysis of their reachable trees

NASA Astrophysics Data System (ADS)

Wang, Jing; Du, YuYue; Yu, ShuXia

2015-11-01

Logic Petri nets (LPNs) can describe and analyse the batch processing function and passing value indeterminacy in cooperative systems, and alleviate the state space explosion problem. However, the indeterminate data of logical output transitions cannot be described explicitly in LPNs. Therefore, Coloured Logic Petri nets (CLPNs) are defined in this paper. It can determine the indeterminate data of logic output transitions in LPNs, i.e., the indeterminate data can be represented definitely in CLPNs. A vector matching method is proposed to judge the enabling transitions and analyse CLPNs. From the marking equation and the proposed reachable tree generation algorithm of CLPNs, a reachable tree can be built, and reachable markings are calculated. The advantage of CLPNs can be shown based on the number of leaf nodes of the reachability tree, and CLPNs can solve the indeterminate data of logical output transitions. Finally, an example shows that CLPNs can further reduce the dimensionality of reachable markings.

Design of automata theory of cubical complexes with applications to diagnosis and algorithmic description

NASA Technical Reports Server (NTRS)

Roth, J. P.

1972-01-01

Methods for development of logic design together with algorithms for failure testing, a method for design of logic for ultra-large-scale integration, extension of quantum calculus to describe the functional behavior of a mechanism component-by-component and to computer tests for failures in the mechanism using the diagnosis algorithm, and the development of an algorithm for the multi-output 2-level minimization problem are discussed.

Design of automata theory of cubical complexes with applications to diagnosis and algorithmic description

NASA Technical Reports Server (NTRS)

Roth, J. P.

1972-01-01

The following problems are considered: (1) methods for development of logic design together with algorithms, so that it is possible to compute a test for any failure in the logic design, if such a test exists, and developing algorithms and heuristics for the purpose of minimizing the computation for tests; and (2) a method of design of logic for ultra LSI (large scale integration). It was discovered that the so-called quantum calculus can be extended to render it possible: (1) to describe the functional behavior of a mechanism component by component, and (2) to compute tests for failures, in the mechanism, using the diagnosis algorithm. The development of an algorithm for the multioutput two-level minimization problem is presented and the program MIN 360 was written for this algorithm. The program has options of mode (exact minimum or various approximations), cost function, cost bound, etc., providing flexibility.

Logic Programming as an Inference Engine for Non-Monotonic Reasoning

DTIC Science & Technology

1991-11-11

Mathematical Sciences . ... University of Texas at El Paso AdI!ar, El Pazo , TX 79968-0514 [ A , (teodor math.ep.utexas.edu) Dist November 11, 1991 Title...Przymusinska, L. Pereira and D.S. Warren. Significant progress has been made towards both theoretical and algorithmic foundations of a non-monotonic...reasoning system based on logic programming. An implementation of such a system, limited to circumscrip- tive thoories, has been also completed. 14

Telerobotic control of a mobile coordinated robotic server. M.S. Thesis Annual Technical Report

NASA Technical Reports Server (NTRS)

Lee, Gordon

1993-01-01

The annual report on telerobotic control of a mobile coordinated robotic server is presented. The goal of this effort is to develop advanced control methods for flexible space manipulator systems. As such, an adaptive fuzzy logic controller was developed in which model structure as well as parameter constraints are not required for compensation. The work builds upon previous work on fuzzy logic controllers. Fuzzy logic controllers have been growing in importance in the field of automatic feedback control. Hardware controllers using fuzzy logic have become available as an alternative to the traditional PID controllers. Software has also been introduced to aid in the development of fuzzy logic rule-bases. The advantages of using fuzzy logic controllers include the ability to merge the experience and intuition of expert operators into the rule-base and that a model of the system is not required to construct the controller. A drawback of the classical fuzzy logic controller, however, is the many parameters needed to be turned off-line prior to application in the closed-loop. In this report, an adaptive fuzzy logic controller is developed requiring no system model or model structure. The rule-base is defined to approximate a state-feedback controller while a second fuzzy logic algorithm varies, on-line, parameters of the defining controller. Results indicate the approach is viable for on-line adaptive control of systems when the model is too complex or uncertain for application of other more classical control techniques.

Discriminating between intentional and unintentional gaze fixation using multimodal-based fuzzy logic algorithm for gaze tracking system with NIR camera sensor

NASA Astrophysics Data System (ADS)

Naqvi, Rizwan Ali; Park, Kang Ryoung

2016-06-01

Gaze tracking systems are widely used in human-computer interfaces, interfaces for the disabled, game interfaces, and for controlling home appliances. Most studies on gaze detection have focused on enhancing its accuracy, whereas few have considered the discrimination of intentional gaze fixation (looking at a target to activate or select it) from unintentional fixation while using gaze detection systems. Previous research methods based on the use of a keyboard or mouse button, eye blinking, and the dwell time of gaze position have various limitations. Therefore, we propose a method for discriminating between intentional and unintentional gaze fixation using a multimodal fuzzy logic algorithm applied to a gaze tracking system with a near-infrared camera sensor. Experimental results show that the proposed method outperforms the conventional method for determining gaze fixation.

Full autonomous microline trace robot

NASA Astrophysics Data System (ADS)

Yi, Deer; Lu, Si; Yan, Yingbai; Jin, Guofan

2000-10-01

Optoelectric inspection may find applications in robotic system. In micro robotic system, smaller optoelectric inspection system is preferred. However, as miniaturizing the size of the robot, the number of the optoelectric detector becomes lack. And lack of the information makes the micro robot difficult to acquire its status. In our lab, a micro line trace robot has been designed, which autonomous acts based on its optoelectric detection. It has been programmed to follow a black line printed on the white colored ground. Besides the optoelectric inspection, logical algorithm in the microprocessor is also important. In this paper, we propose a simply logical algorithm to realize robot's intelligence. The robot's intelligence is based on a AT89C2051 microcontroller which controls its movement. The technical details of the micro robot are as follow: dimension: 30mm*25mm*35*mm; velocity: 60mm/s.

Active control of flexible structures using a fuzzy logic algorithm

NASA Astrophysics Data System (ADS)

Cohen, Kelly; Weller, Tanchum; Ben-Asher, Joseph Z.

2002-08-01

This study deals with the development and application of an active control law for the vibration suppression of beam-like flexible structures experiencing transient disturbances. Collocated pairs of sensors/actuators provide active control of the structure. A design methodology for the closed-loop control algorithm based on fuzzy logic is proposed. First, the behavior of the open-loop system is observed. Then, the number and locations of collocated actuator/sensor pairs are selected. The proposed control law, which is based on the principles of passivity, commands the actuator to emulate the behavior of a dynamic vibration absorber. The absorber is tuned to a targeted frequency, whereas the damping coefficient of the dashpot is varied in a closed loop using a fuzzy logic based algorithm. This approach not only ensures inherent stability associated with passive absorbers, but also circumvents the phenomenon of modal spillover. The developed controller is applied to the AFWAL/FIB 10 bar truss. Simulated results using MATLAB© show that the closed-loop system exhibits fairly quick settling times and desirable performance, as well as robustness characteristics. To demonstrate the robustness of the control system to changes in the temporal dynamics of the flexible structure, the transient response to a considerably perturbed plant is simulated. The modal frequencies of the 10 bar truss were raised as well as lowered substantially, thereby significantly perturbing the natural frequencies of vibration. For these cases, too, the developed control law provides adequate settling times and rates of vibrational energy dissipation.

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

Intelligent neural network and fuzzy logic control of industrial and power systems

NASA Astrophysics Data System (ADS)

Kuljaca, Ognjen

The main role played by neural network and fuzzy logic intelligent control algorithms today is to identify and compensate unknown nonlinear system dynamics. There are a number of methods developed, but often the stability analysis of neural network and fuzzy control systems was not provided. This work will meet those problems for the several algorithms. Some more complicated control algorithms included backstepping and adaptive critics will be designed. Nonlinear fuzzy control with nonadaptive fuzzy controllers is also analyzed. An experimental method for determining describing function of SISO fuzzy controller is given. The adaptive neural network tracking controller for an autonomous underwater vehicle is analyzed. A novel stability proof is provided. The implementation of the backstepping neural network controller for the coupled motor drives is described. Analysis and synthesis of adaptive critic neural network control is also provided in the work. Novel tuning laws for the system with action generating neural network and adaptive fuzzy critic are given. Stability proofs are derived for all those control methods. It is shown how these control algorithms and approaches can be used in practical engineering control. Stability proofs are given. Adaptive fuzzy logic control is analyzed. Simulation study is conducted to analyze the behavior of the adaptive fuzzy system on the different environment changes. A novel stability proof for adaptive fuzzy logic systems is given. Also, adaptive elastic fuzzy logic control architecture is described and analyzed. A novel membership function is used for elastic fuzzy logic system. The stability proof is proffered. Adaptive elastic fuzzy logic control is compared with the adaptive nonelastic fuzzy logic control. The work described in this dissertation serves as foundation on which analysis of particular representative industrial systems will be conducted. Also, it gives a good starting point for analysis of learning abilities of adaptive and neural network control systems, as well as for the analysis of the different algorithms such as elastic fuzzy systems.

Synthesizing Dynamic Programming Algorithms from Linear Temporal Logic Formulae

NASA Technical Reports Server (NTRS)

Rosu, Grigore; Havelund, Klaus

2001-01-01

The problem of testing a linear temporal logic (LTL) formula on a finite execution trace of events, generated by an executing program, occurs naturally in runtime analysis of software. We present an algorithm which takes an LTL formula and generates an efficient dynamic programming algorithm. The generated algorithm tests whether the LTL formula is satisfied by a finite trace of events given as input. The generated algorithm runs in linear time, its constant depending on the size of the LTL formula. The memory needed is constant, also depending on the size of the formula.

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.

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

Blansett, Ethan L.; Schroeppel, Richard Crabtree; Tang, Jason D.

With the build-out of large transport networks utilizing optical technologies, more and more capacity is being made available. Innovations in Dense Wave Division Multiplexing (DWDM) and the elimination of optical-electrical-optical conversions have brought on advances in communication speeds as we move into 10 Gigabit Ethernet and above. Of course, there is a need to encrypt data on these optical links as the data traverses public and private network backbones. Unfortunately, as the communications infrastructure becomes increasingly optical, advances in encryption (done electronically) have failed to keep up. This project examines the use of optical logic for implementing encryption in themore » photonic domain to achieve the requisite encryption rates. In order to realize photonic encryption designs, technology developed for electrical logic circuits must be translated to the photonic regime. This paper examines two classes of all optical logic (SEED, gain competition) and how each discrete logic element can be interconnected and cascaded to form an optical circuit. Because there is no known software that can model these devices at a circuit level, the functionality of the SEED and gain competition devices in an optical circuit were modeled in PSpice. PSpice allows modeling of the macro characteristics of the devices in context of a logic element as opposed to device level computational modeling. By representing light intensity as voltage, 'black box' models are generated that accurately represent the intensity response and logic levels in both technologies. By modeling the behavior at the systems level, one can incorporate systems design tools and a simulation environment to aid in the overall functional design. Each black box model of the SEED or gain competition device takes certain parameters (reflectance, intensity, input response), and models the optical ripple and time delay characteristics. These 'black box' models are interconnected and cascaded in an encrypting/scrambling algorithm based on a study of candidate encryption algorithms. We found that a low gate count, cascadable encryption algorithm is most feasible given device and processing constraints. The modeling and simulation of optical designs using these components is proceeding in parallel with efforts to perfect the physical devices and their interconnect. We have applied these techniques to the development of a 'toy' algorithm that may pave the way for more robust optical algorithms. These design/modeling/simulation techniques are now ready to be applied to larger optical designs in advance of our ability to implement such systems in hardware.« less

Feedback error learning control of magnetic satellites using type-2 fuzzy neural networks with elliptic membership functions.

PubMed

Khanesar, Mojtaba Ahmadieh; Kayacan, Erdal; Reyhanoglu, Mahmut; Kaynak, Okyay

2015-04-01

A novel type-2 fuzzy membership function (MF) in the form of an ellipse has recently been proposed in literature, the parameters of which that represent uncertainties are de-coupled from its parameters that determine the center and the support. This property has enabled the proposers to make an analytical comparison of the noise rejection capabilities of type-1 fuzzy logic systems with its type-2 counterparts. In this paper, a sliding mode control theory-based learning algorithm is proposed for an interval type-2 fuzzy logic system which benefits from elliptic type-2 fuzzy MFs. The learning is based on the feedback error learning method and not only the stability of the learning is proved but also the stability of the overall system is shown by adding an additional component to the control scheme to ensure robustness. In order to test the efficiency and efficacy of the proposed learning and the control algorithm, the trajectory tracking problem of a magnetic rigid spacecraft is studied. The simulations results show that the proposed control algorithm gives better performance results in terms of a smaller steady state error and a faster transient response as compared to conventional control algorithms.

A Rewriting-Based Approach to Trace Analysis

NASA Technical Reports Server (NTRS)

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

2002-01-01

We present a rewriting-based algorithm for efficiently evaluating future time Linear Temporal Logic (LTL) formulae on finite execution traces online. While the standard models of LTL are infinite traces, finite traces appear naturally when testing and/or monitoring red applications that only run for limited time periods. The presented algorithm is implemented in the Maude executable specification language and essentially consists of a set of equations establishing an executable semantics of LTL using a simple formula transforming approach. The algorithm is further improved to build automata on-the-fly from formulae, using memoization. The result is a very efficient and small Maude program that can be used to monitor program executions. We furthermore present an alternative algorithm for synthesizing probably minimal observer finite state machines (or automata) from LTL formulae, which can be used to analyze execution traces without the need for a rewriting system, and can hence be used by observers written in conventional programming languages. The presented work is part of an ambitious runtime verification and monitoring project at NASA Ames, called PATHEXPLORER, and demonstrates that rewriting can be a tractable and attractive means for experimenting and implementing program monitoring logics.

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.

High-efficiency induction motor drives using type-2 fuzzy logic

NASA Astrophysics Data System (ADS)

Khemis, A.; Benlaloui, I.; Drid, S.; Chrifi-Alaoui, L.; Khamari, D.; Menacer, A.

2018-03-01

In this work we propose to develop an algorithm for improving the efficiency of an induction motor using type-2 fuzzy logic. Vector control is used to control this motor due to the high performances of this strategy. The type-2 fuzzy logic regulators are developed to obtain the optimal rotor flux for each torque load by minimizing the copper losses. We have compared the performances of our fuzzy type-2 algorithm with the type-1 fuzzy one proposed in the literature. The proposed algorithm is tested with success on the dSPACE DS1104 system even if there is parameters variance.

Cybernetic systems based on inductive logic

NASA Astrophysics Data System (ADS)

Fry, Robert L.

2001-05-01

Recent work in the area of inductive logic suggests that cybernetics might be quantified and reduced to engineering practice. If so, then there are considerable implications for engineering, science, and other fields. This paper attempts to capture the essential ideas of cybernetics cast in the light of inductive logic. The described inductive logic extends conventional logic by adding a conjugate logical domain of questions to the logical domain of assertions intrinsic to Boolean Algebra with which most are familiar. This was first posited and developed by Richard Cox. Interestingly enough, these two logical domains, one of questions and the other of assertions, only exist relative to one another with each possessing natural measures of entropy and probability, respectively. Examples are given that highlight the utility of cybernetic approaches to neuroscience, algorithm design, system engineering, and the design and understanding of defensive and offensive systems. For example, the application of cybernetic approaches to defense systems suggests that these systems possess a wavefunction which like quantum mechanics, collapses when we ``look'' through the eyes of the system sensors such as radars and optical sensors. .

Short-term prediction of solar energy in Saudi Arabia using automated-design fuzzy logic systems

PubMed Central

2017-01-01

Solar energy is considered as one of the main sources for renewable energy in the near future. However, solar energy and other renewable energy sources have a drawback related to the difficulty in predicting their availability in the near future. This problem affects optimal exploitation of solar energy, especially in connection with other resources. Therefore, reliable solar energy prediction models are essential to solar energy management and economics. This paper presents work aimed at designing reliable models to predict the global horizontal irradiance (GHI) for the next day in 8 stations in Saudi Arabia. The designed models are based on computational intelligence methods of automated-design fuzzy logic systems. The fuzzy logic systems are designed and optimized with two models using fuzzy c-means clustering (FCM) and simulated annealing (SA) algorithms. The first model uses FCM based on the subtractive clustering algorithm to automatically design the predictor fuzzy rules from data. The second model is using FCM followed by simulated annealing algorithm to enhance the prediction accuracy of the fuzzy logic system. The objective of the predictor is to accurately predict next-day global horizontal irradiance (GHI) using previous-day meteorological and solar radiation observations. The proposed models use observations of 10 variables of measured meteorological and solar radiation data to build the model. The experimentation and results of the prediction are detailed where the root mean square error of the prediction was approximately 88% for the second model tuned by simulated annealing compared to 79.75% accuracy using the first model. This results demonstrate a good modeling accuracy of the second model despite that the training and testing of the proposed models were carried out using spatially and temporally independent data. PMID:28806754

Short-term prediction of solar energy in Saudi Arabia using automated-design fuzzy logic systems.

PubMed

Almaraashi, Majid

2017-01-01

Solar energy is considered as one of the main sources for renewable energy in the near future. However, solar energy and other renewable energy sources have a drawback related to the difficulty in predicting their availability in the near future. This problem affects optimal exploitation of solar energy, especially in connection with other resources. Therefore, reliable solar energy prediction models are essential to solar energy management and economics. This paper presents work aimed at designing reliable models to predict the global horizontal irradiance (GHI) for the next day in 8 stations in Saudi Arabia. The designed models are based on computational intelligence methods of automated-design fuzzy logic systems. The fuzzy logic systems are designed and optimized with two models using fuzzy c-means clustering (FCM) and simulated annealing (SA) algorithms. The first model uses FCM based on the subtractive clustering algorithm to automatically design the predictor fuzzy rules from data. The second model is using FCM followed by simulated annealing algorithm to enhance the prediction accuracy of the fuzzy logic system. The objective of the predictor is to accurately predict next-day global horizontal irradiance (GHI) using previous-day meteorological and solar radiation observations. The proposed models use observations of 10 variables of measured meteorological and solar radiation data to build the model. The experimentation and results of the prediction are detailed where the root mean square error of the prediction was approximately 88% for the second model tuned by simulated annealing compared to 79.75% accuracy using the first model. This results demonstrate a good modeling accuracy of the second model despite that the training and testing of the proposed models were carried out using spatially and temporally independent data.

Self-Tuning of Design Variables for Generalized Predictive Control

NASA Technical Reports Server (NTRS)

Lin, Chaung; Juang, Jer-Nan

2000-01-01

Three techniques are introduced to determine the order and control weighting for the design of a generalized predictive controller. These techniques are based on the application of fuzzy logic, genetic algorithms, and simulated annealing to conduct an optimal search on specific performance indexes or objective functions. Fuzzy logic is found to be feasible for real-time and on-line implementation due to its smooth and quick convergence. On the other hand, genetic algorithms and simulated annealing are applicable for initial estimation of the model order and control weighting, and final fine-tuning within a small region of the solution space, Several numerical simulations for a multiple-input and multiple-output system are given to illustrate the techniques developed in this paper.

Programmable logic controller implementation of an auto-tuned predictive control based on minimal plant information.

PubMed

Valencia-Palomo, G; Rossiter, J A

2011-01-01

This paper makes two key contributions. First, it tackles the issue of the availability of constrained predictive control for low-level control loops. Hence, it describes how the constrained control algorithm is embedded in an industrial programmable logic controller (PLC) using the IEC 61131-3 programming standard. Second, there is a definition and implementation of a novel auto-tuned predictive controller; the key novelty is that the modelling is based on relatively crude but pragmatic plant information. Laboratory experiment tests were carried out in two bench-scale laboratory systems to prove the effectiveness of the combined algorithm and hardware solution. For completeness, the results are compared with a commercial proportional-integral-derivative (PID) controller (also embedded in the PLC) using the most up to date auto-tuning rules. Copyright © 2010 ISA. Published by Elsevier Ltd. All rights reserved.

Integration of Genetic Algorithms and Fuzzy Logic for Urban Growth Modeling

NASA Astrophysics Data System (ADS)

Foroutan, E.; Delavar, M. R.; Araabi, B. N.

2012-07-01

Urban growth phenomenon as a spatio-temporal continuous process is subject to spatial uncertainty. This inherent uncertainty cannot be fully addressed by the conventional methods based on the Boolean algebra. Fuzzy logic can be employed to overcome this limitation. Fuzzy logic preserves the continuity of dynamic urban growth spatially by choosing fuzzy membership functions, fuzzy rules and the fuzzification-defuzzification process. Fuzzy membership functions and fuzzy rule sets as the heart of fuzzy logic are rather subjective and dependent on the expert. However, due to lack of a definite method for determining the membership function parameters, certain optimization is needed to tune the parameters and improve the performance of the model. This paper integrates genetic algorithms and fuzzy logic as a genetic fuzzy system (GFS) for modeling dynamic urban growth. The proposed approach is applied for modeling urban growth in Tehran Metropolitan Area in Iran. Historical land use/cover data of Tehran Metropolitan Area extracted from the 1988 and 1999 Landsat ETM+ images are employed in order to simulate the urban growth. The extracted land use classes of the year 1988 include urban areas, street, vegetation areas, slope and elevation used as urban growth physical driving forces. Relative Operating Characteristic (ROC) curve as an fitness function has been used to evaluate the performance of the GFS algorithm. The optimum membership function parameter is applied for generating a suitability map for the urban growth. Comparing the suitability map and real land use map of 1999 gives the threshold value for the best suitability map which can simulate the land use map of 1999. The simulation outcomes in terms of kappa of 89.13% and overall map accuracy of 95.58% demonstrated the efficiency and reliability of the proposed model.

Complete all-optical processing polarization-based binary logic gates and optical processors.

PubMed

Zaghloul, Y A; Zaghloul, A R M

2006-10-16

We present a complete all-optical-processing polarization-based binary-logic system, by which any logic gate or processor can be implemented. Following the new polarization-based logic presented in [Opt. Express 14, 7253 (2006)], we develop a new parallel processing technique that allows for the creation of all-optical-processing gates that produce a unique output either logic 1 or 0 only once in a truth table, and those that do not. This representation allows for the implementation of simple unforced OR, AND, XOR, XNOR, inverter, and more importantly NAND and NOR gates that can be used independently to represent any Boolean expression or function. In addition, the concept of a generalized gate is presented which opens the door for reconfigurable optical processors and programmable optical logic gates. Furthermore, the new design is completely compatible with the old one presented in [Opt. Express 14, 7253 (2006)], and with current semiconductor based devices. The gates can be cascaded, where the information is always on the laser beam. The polarization of the beam, and not its intensity, carries the information. The new methodology allows for the creation of multiple-input-multiple-output processors that implement, by itself, any Boolean function, such as specialized or non-specialized microprocessors. Three all-optical architectures are presented: orthoparallel optical logic architecture for all known and unknown binary gates, singlebranch architecture for only XOR and XNOR gates, and the railroad (RR) architecture for polarization optical processors (POP). All the control inputs are applied simultaneously leading to a single time lag which leads to a very-fast and glitch-immune POP. A simple and easy-to-follow step-by-step algorithm is provided for the POP, and design reduction methodologies are briefly discussed. The algorithm lends itself systematically to software programming and computer-assisted design. As examples, designs of all binary gates, multiple-input gates, and sequential and non-sequential Boolean expressions are presented and discussed. The operation of each design is simply understood by a bullet train traveling at the speed of light on a railroad system preconditioned by the crossover states predetermined by the control inputs. The presented designs allow for optical processing of the information eliminating the need to convert it, back and forth, to an electronic signal for processing purposes. All gates with a truth table, including for example Fredkin, Toffoli, testable reversible logic, and threshold logic gates, can be designed and implemented using the railroad architecture. That includes any future gates not known today. Those designs and the quantum gates are not discussed in this paper.

Fuzzy-Based Hybrid Control Algorithm for the Stabilization of a Tri-Rotor UAV

PubMed Central

Ali, Zain Anwar; Wang, Daobo; Aamir, Muhammad

2016-01-01

In this paper, a new and novel mathematical fuzzy hybrid scheme is proposed for the stabilization of a tri-rotor unmanned aerial vehicle (UAV). The fuzzy hybrid scheme consists of a fuzzy logic controller, regulation pole-placement tracking (RST) controller with model reference adaptive control (MRAC), in which adaptive gains of the RST controller are being fine-tuned by a fuzzy logic controller. Brushless direct current (BLDC) motors are installed in the triangular frame of the tri-rotor UAV, which helps maintain control on its motion and different altitude and attitude changes, similar to rotorcrafts. MRAC-based MIT rule is proposed for system stability. Moreover, the proposed hybrid controller with nonlinear flight dynamics is shown in the presence of translational and rotational velocity components. The performance of the proposed algorithm is demonstrated via MATLAB simulations, in which the proposed fuzzy hybrid controller is compared with the existing adaptive RST controller. It shows that our proposed algorithm has better transient performance with zero steady-state error, and fast convergence towards stability. PMID:27171084

Linear-time general decoding algorithm for the surface code

NASA Astrophysics Data System (ADS)

Darmawan, Andrew S.; Poulin, David

2018-05-01

A quantum error correcting protocol can be substantially improved by taking into account features of the physical noise process. We present an efficient decoder for the surface code which can account for general noise features, including coherences and correlations. We demonstrate that the decoder significantly outperforms the conventional matching algorithm on a variety of noise models, including non-Pauli noise and spatially correlated noise. The algorithm is based on an approximate calculation of the logical channel using a tensor-network description of the noisy state.

Knowledge discovery through games and game theory

NASA Astrophysics Data System (ADS)

Smith, James F., III; Rhyne, Robert D.

2001-03-01

A fuzzy logic based expert system has been developed that automatically allocates electronic attack (EA) resources in real-time over many dissimilar platforms. The platforms can be very general, e.g., ships, planes, robots, land based facilities, etc. Potential foes the platforms deal with can also be general. The initial version of the algorithm was optimized using a genetic algorithm employing fitness functions constructed based on expertise. A new approach is being explored that involves embedding the resource manager in a electronic game environment. The game allows a human expert to play against the resource manager in a simulated battlespace with each of the defending platforms being exclusively directed by the fuzzy resource manager and the attacking platforms being controlled by the human expert or operating autonomously under their own logic. This approach automates the data mining problem. The game automatically creates a database reflecting the domain expert's knowledge, it calls a data mining function, a genetic algorithm, for data mining of the database as required. The game allows easy evaluation of the information mined in the second step. The measure of effectiveness (MOE) for re-optimization is discussed. The mined information is extremely valuable as shown through demanding scenarios.

Design of an iterative auto-tuning algorithm for a fuzzy PID controller

NASA Astrophysics Data System (ADS)

Saeed, Bakhtiar I.; Mehrdadi, B.

2012-05-01

Since the first application of fuzzy logic in the field of control engineering, it has been extensively employed in controlling a wide range of applications. The human knowledge on controlling complex and non-linear processes can be incorporated into a controller in the form of linguistic terms. However, with the lack of analytical design study it is becoming more difficult to auto-tune controller parameters. Fuzzy logic controller has several parameters that can be adjusted, such as: membership functions, rule-base and scaling gains. Furthermore, it is not always easy to find the relation between the type of membership functions or rule-base and the controller performance. This study proposes a new systematic auto-tuning algorithm to fine tune fuzzy logic controller gains. A fuzzy PID controller is proposed and applied to several second order systems. The relationship between the closed-loop response and the controller parameters is analysed to devise an auto-tuning method. The results show that the proposed method is highly effective and produces zero overshoot with enhanced transient response. In addition, the robustness of the controller is investigated in the case of parameter changes and the results show a satisfactory performance.

An adaptive optimal control for smart structures based on the subspace tracking identification technique

NASA Astrophysics Data System (ADS)

Ripamonti, Francesco; Resta, Ferruccio; Borroni, Massimo; Cazzulani, Gabriele

2014-04-01

A new method for the real-time identification of mechanical system modal parameters is used in order to design different adaptive control logics aiming to reduce the vibrations in a carbon fiber plate smart structure. It is instrumented with three piezoelectric actuators, three accelerometers and three strain gauges. The real-time identification is based on a recursive subspace tracking algorithm whose outputs are elaborated by an ARMA model. A statistical approach is finally applied to choose the modal parameter correct values. These are given in input to model-based control logics such as a gain scheduling and an adaptive LQR control.

PLQP & Company: Decidable Logics for Quantum Algorithms

NASA Astrophysics Data System (ADS)

Baltag, Alexandru; Bergfeld, Jort; Kishida, Kohei; Sack, Joshua; Smets, Sonja; Zhong, Shengyang

2014-10-01

We introduce a probabilistic modal (dynamic-epistemic) quantum logic PLQP for reasoning about quantum algorithms. We illustrate its expressivity by using it to encode the correctness of the well-known quantum search algorithm, as well as of a quantum protocol known to solve one of the paradigmatic tasks from classical distributed computing (the leader election problem). We also provide a general method (extending an idea employed in the decidability proof in Dunn et al. (J. Symb. Log. 70:353-359, 2005)) for proving the decidability of a range of quantum logics, interpreted on finite-dimensional Hilbert spaces. We give general conditions for the applicability of this method, and in particular we apply it to prove the decidability of PLQP.

Quantified moving average strategy of crude oil futures market based on fuzzy logic rules and genetic algorithms

NASA Astrophysics Data System (ADS)

Liu, Xiaojia; An, Haizhong; Wang, Lijun; Guan, Qing

2017-09-01

The moving average strategy is a technical indicator that can generate trading signals to assist investment. While the trading signals tell the traders timing to buy or sell, the moving average cannot tell the trading volume, which is a crucial factor for investment. This paper proposes a fuzzy moving average strategy, in which the fuzzy logic rule is used to determine the strength of trading signals, i.e., the trading volume. To compose one fuzzy logic rule, we use four types of moving averages, the length of the moving average period, the fuzzy extent, and the recommend value. Ten fuzzy logic rules form a fuzzy set, which generates a rating level that decides the trading volume. In this process, we apply genetic algorithms to identify an optimal fuzzy logic rule set and utilize crude oil futures prices from the New York Mercantile Exchange (NYMEX) as the experiment data. Each experiment is repeated for 20 times. The results show that firstly the fuzzy moving average strategy can obtain a more stable rate of return than the moving average strategies. Secondly, holding amounts series is highly sensitive to price series. Thirdly, simple moving average methods are more efficient. Lastly, the fuzzy extents of extremely low, high, and very high are more popular. These results are helpful in investment decisions.

Systematic methods for the design of a class of fuzzy logic controllers

NASA Astrophysics Data System (ADS)

Yasin, Saad Yaser

2002-09-01

Fuzzy logic control, a relatively new branch of control, can be used effectively whenever conventional control techniques become inapplicable or impractical. Various attempts have been made to create a generalized fuzzy control system and to formulate an analytically based fuzzy control law. In this study, two methods, the left and right parameterization method and the normalized spline-base membership function method, were utilized for formulating analytical fuzzy control laws in important practical control applications. The first model was used to design an idle speed controller, while the second was used to control an inverted control problem. The results of both showed that a fuzzy logic control system based on the developed models could be used effectively to control highly nonlinear and complex systems. This study also investigated the application of fuzzy control in areas not fully utilizing fuzzy logic control. Three important practical applications pertaining to the automotive industries were studied. The first automotive-related application was the idle speed of spark ignition engines, using two fuzzy control methods: (1) left and right parameterization, and (2) fuzzy clustering techniques and experimental data. The simulation and experimental results showed that a conventional controller-like performance fuzzy controller could be designed based only on experimental data and intuitive knowledge of the system. In the second application, the automotive cruise control problem, a fuzzy control model was developed using parameters adaptive Proportional plus Integral plus Derivative (PID)-type fuzzy logic controller. Results were comparable to those using linearized conventional PID and linear quadratic regulator (LQR) controllers and, in certain cases and conditions, the developed controller outperformed the conventional PID and LQR controllers. The third application involved the air/fuel ratio control problem, using fuzzy clustering techniques, experimental data, and a conversion algorithm, to develop a fuzzy-based control algorithm. Results were similar to those obtained by recently published conventional control based studies. The influence of the fuzzy inference operators and parameters on performance and stability of the fuzzy logic controller was studied Results indicated that, the selections of certain parameters or combinations of parameters, affect greatly the performance and stability of the fuzzy controller. Diagnostic guidelines used to tune or change certain factors or parameters to improve controller performance were developed based on knowledge gained from conventional control methods and knowledge gained from the experimental and the simulation results of this study.

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

Tang, Jason D.; Schroeppel, Richard Crabtree; Robertson, Perry J.

With the build-out of large transport networks utilizing optical technologies, more and more capacity is being made available. Innovations in Dense Wave Division Multiplexing (DWDM) and the elimination of optical-electrical-optical conversions have brought on advances in communication speeds as we move into 10 Gigabit Ethernet and above. Of course, there is a need to encrypt data on these optical links as the data traverses public and private network backbones. Unfortunately, as the communications infrastructure becomes increasingly optical, advances in encryption (done electronically) have failed to keep up. This project examines the use of optical logic for implementing encryption in themore » photonic domain to achieve the requisite encryption rates. This paper documents the innovations and advances of work first detailed in 'Photonic Encryption using All Optical Logic,' [1]. A discussion of underlying concepts can be found in SAND2003-4474. In order to realize photonic encryption designs, technology developed for electrical logic circuits must be translated to the photonic regime. This paper examines S-SEED devices and how discrete logic elements can be interconnected and cascaded to form an optical circuit. Because there is no known software that can model these devices at a circuit level, the functionality of S-SEED devices in an optical circuit was modeled in PSpice. PSpice allows modeling of the macro characteristics of the devices in context of a logic element as opposed to device level computational modeling. By representing light intensity as voltage, 'black box' models are generated that accurately represent the intensity response and logic levels in both technologies. By modeling the behavior at the systems level, one can incorporate systems design tools and a simulation environment to aid in the overall functional design. Each black box model takes certain parameters (reflectance, intensity, input response), and models the optical ripple and time delay characteristics. These 'black box' models are interconnected and cascaded in an encrypting/scrambling algorithm based on a study of candidate encryption algorithms. Demonstration circuits show how these logic elements can be used to form NAND, NOR, and XOR functions. This paper also presents functional analysis of a serial, low gate count demonstration algorithm suitable for scrambling/encryption using S-SEED devices.« less

Multiagent data warehousing and multiagent data mining for cerebrum/cerebellum modeling

NASA Astrophysics Data System (ADS)

Zhang, Wen-Ran

2002-03-01

An algorithm named Neighbor-Miner is outlined for multiagent data warehousing and multiagent data mining. The algorithm is defined in an evolving dynamic environment with autonomous or semiautonomous agents. Instead of mining frequent itemsets from customer transactions, the new algorithm discovers new agents and mining agent associations in first-order logic from agent attributes and actions. While the Apriori algorithm uses frequency as a priory threshold, the new algorithm uses agent similarity as priory knowledge. The concept of agent similarity leads to the notions of agent cuboid, orthogonal multiagent data warehousing (MADWH), and multiagent data mining (MADM). Based on agent similarities and action similarities, Neighbor-Miner is proposed and illustrated in a MADWH/MADM approach to cerebrum/cerebellum modeling. It is shown that (1) semiautonomous neurofuzzy agents can be identified for uniped locomotion and gymnastic training based on attribute relevance analysis; (2) new agents can be discovered and agent cuboids can be dynamically constructed in an orthogonal MADWH, which resembles an evolving cerebrum/cerebellum system; and (3) dynamic motion laws can be discovered as association rules in first order logic. Although examples in legged robot gymnastics are used to illustrate the basic ideas, the new approach is generally suitable for a broad category of data mining tasks where knowledge can be discovered collectively by a set of agents from a geographically or geometrically distributed but relevant environment, especially in scientific and engineering data environments.

Analytical learning and term-rewriting systems

NASA Technical Reports Server (NTRS)

Laird, Philip; Gamble, Evan

1990-01-01

Analytical learning is a set of machine learning techniques for revising the representation of a theory based on a small set of examples of that theory. When the representation of the theory is correct and complete but perhaps inefficient, an important objective of such analysis is to improve the computational efficiency of the representation. Several algorithms with this purpose have been suggested, most of which are closely tied to a first order logical language and are variants of goal regression, such as the familiar explanation based generalization (EBG) procedure. But because predicate calculus is a poor representation for some domains, these learning algorithms are extended to apply to other computational models. It is shown that the goal regression technique applies to a large family of programming languages, all based on a kind of term rewriting system. Included in this family are three language families of importance to artificial intelligence: logic programming, such as Prolog; lambda calculus, such as LISP; and combinatorial based languages, such as FP. A new analytical learning algorithm, AL-2, is exhibited that learns from success but is otherwise quite different from EBG. These results suggest that term rewriting systems are a good framework for analytical learning research in general, and that further research should be directed toward developing new techniques.

Ant colony optimisation-direct cover: a hybrid ant colony direct cover technique for multi-level synthesis of multiple-valued logic functions

NASA Astrophysics Data System (ADS)

Abd-El-Barr, Mostafa

2010-12-01

The use of non-binary (multiple-valued) logic in the synthesis of digital systems can lead to savings in chip area. Advances in very large scale integration (VLSI) technology have enabled the successful implementation of multiple-valued logic (MVL) circuits. A number of heuristic algorithms for the synthesis of (near) minimal sum-of products (two-level) realisation of MVL functions have been reported in the literature. The direct cover (DC) technique is one such algorithm. The ant colony optimisation (ACO) algorithm is a meta-heuristic that uses constructive greediness to explore a large solution space in finding (near) optimal solutions. The ACO algorithm mimics the ant's behaviour in the real world in using the shortest path to reach food sources. We have previously introduced an ACO-based heuristic for the synthesis of two-level MVL functions. In this article, we introduce the ACO-DC hybrid technique for the synthesis of multi-level MVL functions. The basic idea is to use an ant to decompose a given MVL function into a number of levels and then synthesise each sub-function using a DC-based technique. The results obtained using the proposed approach are compared to those obtained using existing techniques reported in the literature. A benchmark set consisting of 50,000 randomly generated 2-variable 4-valued functions is used in the comparison. The results obtained using the proposed ACO-DC technique are shown to produce efficient realisation in terms of the average number of gates (as a measure of chip area) needed for the synthesis of a given MVL function.

Families of Graph Algorithms: SSSP Case Study

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

Kanewala Appuhamilage, Thejaka Amila Jay; Zalewski, Marcin J.; Lumsdaine, Andrew

2017-08-28

Single-Source Shortest Paths (SSSP) is a well-studied graph problem. Examples of SSSP algorithms include the original Dijkstra’s algorithm and the parallel Δ-stepping and KLA-SSSP algorithms. In this paper, we use a novel Abstract Graph Machine (AGM) model to show that all these algorithms share a common logic and differ from one another by the order in which they perform work. We use the AGM model to thoroughly analyze the family of algorithms that arises from the common logic. We start with the basic algorithm without any ordering (Chaotic), and then we derive the existing and new algorithms by methodically exploringmore » semantic and spatial ordering of work. Our experimental results show that new derived algorithms show better performance than the existing distributed memory parallel algorithms, especially at higher scales.« less

Data mining for multiagent rules, strategies, and fuzzy decision tree structure

NASA Astrophysics Data System (ADS)

Smith, James F., III; Rhyne, Robert D., II; Fisher, Kristin

2002-03-01

A fuzzy logic based resource manager (RM) has been developed that automatically allocates electronic attack resources in real-time over many dissimilar platforms. Two different data mining algorithms have been developed to determine rules, strategies, and fuzzy decision tree structure. The first data mining algorithm uses a genetic algorithm as a data mining function and is called from an electronic game. The game allows a human expert to play against the resource manager in a simulated battlespace with each of the defending platforms being exclusively directed by the fuzzy resource manager and the attacking platforms being controlled by the human expert or operating autonomously under their own logic. This approach automates the data mining problem. The game automatically creates a database reflecting the domain expert's knowledge. It calls a data mining function, a genetic algorithm, for data mining of the database as required and allows easy evaluation of the information mined in the second step. The criterion for re- optimization is discussed as well as experimental results. Then a second data mining algorithm that uses a genetic program as a data mining function is introduced to automatically discover fuzzy decision tree structures. Finally, a fuzzy decision tree generated through this process is discussed.

Design Time Optimization for Hardware Watermarking Protection of HDL Designs

PubMed Central

Castillo, E.; Morales, D. P.; García, A.; Parrilla, L.; Todorovich, E.; Meyer-Baese, U.

2015-01-01

HDL-level design offers important advantages for the application of watermarking to IP cores, but its complexity also requires tools automating these watermarking algorithms. A new tool for signature distribution through combinational logic is proposed in this work. IPP@HDL, a previously proposed high-level watermarking technique, has been employed for evaluating the tool. IPP@HDL relies on spreading the bits of a digital signature at the HDL design level using combinational logic included within the original system. The development of this new tool for the signature distribution has not only extended and eased the applicability of this IPP technique, but it has also improved the signature hosting process itself. Three algorithms were studied in order to develop this automated tool. The selection of a cost function determines the best hosting solutions in terms of area and performance penalties on the IP core to protect. An 1D-DWT core and MD5 and SHA1 digital signatures were used in order to illustrate the benefits of the new tool and its optimization related to the extraction logic resources. Among the proposed algorithms, the alternative based on simulated annealing reduces the additional resources while maintaining an acceptable computation time and also saving designer effort and time. PMID:25861681

Fuzzy Logic, Neural Networks, Genetic Algorithms: Views of Three Artificial Intelligence Concepts Used in Modeling Scientific Systems

ERIC Educational Resources Information Center

Sunal, Cynthia Szymanski; Karr, Charles L.; Sunal, Dennis W.

2003-01-01

Students' conceptions of three major artificial intelligence concepts used in the modeling of systems in science, fuzzy logic, neural networks, and genetic algorithms were investigated before and after a higher education science course. Students initially explored their prior ideas related to the three concepts through active tasks. Then,…

Teaching Semantic Tableaux Method for Propositional Classical Logic with a CAS

ERIC Educational Resources Information Center

Aguilera-Venegas, Gabriel; Galán-García, José Luis; Galán-García, María Ángeles; Rodríguez-Cielos, Pedro

2015-01-01

Automated theorem proving (ATP) for Propositional Classical Logic is an algorithm to check the validity of a formula. It is a very well-known problem which is decidable but co-NP-complete. There are many algorithms for this problem. In this paper, an educationally oriented implementation of Semantic Tableaux method is described. The program has…

A generalized algorithm to design finite field normal basis multipliers

NASA Technical Reports Server (NTRS)

Wang, C. C.

1986-01-01

Finite field arithmetic logic is central in the implementation of some error-correcting coders and some cryptographic devices. There is a need for good multiplication algorithms which can be easily realized. Massey and Omura recently developed a new multiplication algorithm for finite fields based on a normal basis representation. Using the normal basis representation, the design of the finite field multiplier is simple and regular. The fundamental design of the Massey-Omura multiplier is based on a design of a product function. In this article, a generalized algorithm to locate a normal basis in a field is first presented. Using this normal basis, an algorithm to construct the product function is then developed. This design does not depend on particular characteristics of the generator polynomial of the field.

Development of Real Time Implementation of 5/5 Rule based Fuzzy Logic Controller Shunt Active Power Filter for Power Quality Improvement

NASA Astrophysics Data System (ADS)

Puhan, Pratap Sekhar; Ray, Pravat Kumar; Panda, Gayadhar

2016-12-01

This paper presents the effectiveness of 5/5 Fuzzy rule implementation in Fuzzy Logic Controller conjunction with indirect control technique to enhance the power quality in single phase system, An indirect current controller in conjunction with Fuzzy Logic Controller is applied to the proposed shunt active power filter to estimate the peak reference current and capacitor voltage. Current Controller based pulse width modulation (CCPWM) is used to generate the switching signals of voltage source inverter. Various simulation results are presented to verify the good behaviour of the Shunt active Power Filter (SAPF) with proposed two levels Hysteresis Current Controller (HCC). For verification of Shunt Active Power Filter in real time, the proposed control algorithm has been implemented in laboratory developed setup in dSPACE platform.

Enhancing the Selection of Backoff Interval Using Fuzzy Logic over Wireless Ad Hoc Networks

PubMed Central

Ranganathan, Radha; Kannan, Kathiravan

2015-01-01

IEEE 802.11 is the de facto standard for medium access over wireless ad hoc network. The collision avoidance mechanism (i.e., random binary exponential backoff—BEB) of IEEE 802.11 DCF (distributed coordination function) is inefficient and unfair especially under heavy load. In the literature, many algorithms have been proposed to tune the contention window (CW) size. However, these algorithms make every node select its backoff interval between [0, CW] in a random and uniform manner. This randomness is incorporated to avoid collisions among the nodes. But this random backoff interval can change the optimal order and frequency of channel access among competing nodes which results in unfairness and increased delay. In this paper, we propose an algorithm that schedules the medium access in a fair and effective manner. This algorithm enhances IEEE 802.11 DCF with additional level of contention resolution that prioritizes the contending nodes according to its queue length and waiting time. Each node computes its unique backoff interval using fuzzy logic based on the input parameters collected from contending nodes through overhearing. We evaluate our algorithm against IEEE 802.11, GDCF (gentle distributed coordination function) protocols using ns-2.35 simulator and show that our algorithm achieves good performance. PMID:25879066

Fuzzy logic and optical correlation-based face recognition method for patient monitoring application in home video surveillance

NASA Astrophysics Data System (ADS)

Elbouz, Marwa; Alfalou, Ayman; Brosseau, Christian

2011-06-01

Home automation is being implemented into more and more domiciles of the elderly and disabled in order to maintain their independence and safety. For that purpose, we propose and validate a surveillance video system, which detects various posture-based events. One of the novel points of this system is to use adapted Vander-Lugt correlator (VLC) and joint-transfer correlator (JTC) techniques to make decisions on the identity of a patient and his three-dimensional (3-D) positions in order to overcome the problem of crowd environment. We propose a fuzzy logic technique to get decisions on the subject's behavior. Our system is focused on the goals of accuracy, convenience, and cost, which in addition does not require any devices attached to the subject. The system permits one to study and model subject responses to behavioral change intervention because several levels of alarm can be incorporated according different situations considered. Our algorithm performs a fast 3-D recovery of the subject's head position by locating eyes within the face image and involves a model-based prediction and optical correlation techniques to guide the tracking procedure. The object detection is based on (hue, saturation, value) color space. The system also involves an adapted fuzzy logic control algorithm to make a decision based on information given to the system. Furthermore, the principles described here are applicable to a very wide range of situations and robust enough to be implementable in ongoing experiments.

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.

Automated Software Acceleration in Programmable Logic for an Efficient NFFT Algorithm Implementation: A Case Study.

PubMed

Rodríguez, Manuel; Magdaleno, Eduardo; Pérez, Fernando; García, Cristhian

2017-03-28

Non-equispaced Fast Fourier transform (NFFT) is a very important algorithm in several technological and scientific areas such as synthetic aperture radar, computational photography, medical imaging, telecommunications, seismic analysis and so on. However, its computation complexity is high. In this paper, we describe an efficient NFFT implementation with a hardware coprocessor using an All-Programmable System-on-Chip (APSoC). This is a hybrid device that employs an Advanced RISC Machine (ARM) as Processing System with Programmable Logic for high-performance digital signal processing through parallelism and pipeline techniques. The algorithm has been coded in C language with pragma directives to optimize the architecture of the system. We have used the very novel Software Develop System-on-Chip (SDSoC) evelopment tool that simplifies the interface and partitioning between hardware and software. This provides shorter development cycles and iterative improvements by exploring several architectures of the global system. The computational results shows that hardware acceleration significantly outperformed the software based implementation.

Automated Software Acceleration in Programmable Logic for an Efficient NFFT Algorithm Implementation: A Case Study

PubMed Central

Rodríguez, Manuel; Magdaleno, Eduardo; Pérez, Fernando; García, Cristhian

2017-01-01

Non-equispaced Fast Fourier transform (NFFT) is a very important algorithm in several technological and scientific areas such as synthetic aperture radar, computational photography, medical imaging, telecommunications, seismic analysis and so on. However, its computation complexity is high. In this paper, we describe an efficient NFFT implementation with a hardware coprocessor using an All-Programmable System-on-Chip (APSoC). This is a hybrid device that employs an Advanced RISC Machine (ARM) as Processing System with Programmable Logic for high-performance digital signal processing through parallelism and pipeline techniques. The algorithm has been coded in C language with pragma directives to optimize the architecture of the system. We have used the very novel Software Develop System-on-Chip (SDSoC) evelopment tool that simplifies the interface and partitioning between hardware and software. This provides shorter development cycles and iterative improvements by exploring several architectures of the global system. The computational results shows that hardware acceleration significantly outperformed the software based implementation. PMID:28350358

Exact Synthesis of Reversible Circuits Using A* Algorithm

NASA Astrophysics Data System (ADS)

Datta, K.; Rathi, G. K.; Sengupta, I.; Rahaman, H.

2015-06-01

With the growing emphasis on low-power design methodologies, and the result that theoretical zero power dissipation is possible only if computations are information lossless, design and synthesis of reversible logic circuits have become very important in recent years. Reversible logic circuits are also important in the context of quantum computing, where the basic operations are reversible in nature. Several synthesis methodologies for reversible circuits have been reported. Some of these methods are termed as exact, where the motivation is to get the minimum-gate realization for a given reversible function. These methods are computationally very intensive, and are able to synthesize only very small functions. There are other methods based on function transformations or higher-level representation of functions like binary decision diagrams or exclusive-or sum-of-products, that are able to handle much larger circuits without any guarantee of optimality or near-optimality. Design of exact synthesis algorithms is interesting in this context, because they set some kind of benchmarks against which other methods can be compared. This paper proposes an exact synthesis approach based on an iterative deepening version of the A* algorithm using the multiple-control Toffoli gate library. Experimental results are presented with comparisons with other exact and some heuristic based synthesis approaches.

Image denoising based on noise detection

NASA Astrophysics Data System (ADS)

Jiang, Yuanxiang; Yuan, Rui; Sun, Yuqiu; Tian, Jinwen

2018-03-01

Because of the noise points in the images, any operation of denoising would change the original information of non-noise pixel. A noise detection algorithm based on fractional calculus was proposed to denoise in this paper. Convolution of the image was made to gain direction gradient masks firstly. Then, the mean gray was calculated to obtain the gradient detection maps. Logical product was made to acquire noise position image next. Comparisons in the visual effect and evaluation parameters after processing, the results of experiment showed that the denoising algorithms based on noise were better than that of traditional methods in both subjective and objective aspects.

The Priority Inversion Problem and Real-Time Symbolic Model Checking

DTIC Science & Technology

1993-04-23

real time systems unpredictable in subtle ways. This makes it more difficult to implement and debug such systems. Our work discusses this problem and presents one possible solution. The solution is formalized and verified using temporal logic model checking techniques. In order to perform the verification, the BDD-based symbolic model checking algorithm given in previous works was extended to handle real-time properties using the bounded until operator. We believe that this algorithm, which is based on discrete time, is able to handle many real-time properties

Type-2 fuzzy logic control of a 2-DOF helicopter (TRMS system)

NASA Astrophysics Data System (ADS)

Zeghlache, Samir; Kara, Kamel; Saigaa, Djamel

2014-09-01

The helicopter dynamic includes nonlinearities, parametric uncertainties and is subject to unknown external disturbances. Such complicated dynamics involve designing sophisticated control algorithms that can deal with these difficulties. In this paper, a type 2 fuzzy logic PID controller is proposed for TRMS (twin rotor mimo system) control problem. Using triangular membership functions and based on a human operator experience, two controllers are designed to control the position of the yaw and the pitch angles of the TRMS. Simulation results are given to illustrate the effectiveness of the proposed control scheme.

Logic via Computer Programming.

ERIC Educational Resources Information Center

Wieschenberg, Agnes A.

This paper proposed the question "How do we teach logical thinking and sophisticated mathematics to unsophisticated college students?" One answer among many is through the writing of computer programs. The writing of computer algorithms is mathematical problem solving and logic in disguise and it may attract students who would otherwise stop…

Runtime Analysis of Linear Temporal Logic Specifications

NASA Technical Reports Server (NTRS)

Giannakopoulou, Dimitra; Havelund, Klaus

2001-01-01

This report presents an approach to checking a running program against its Linear Temporal Logic (LTL) specifications. LTL is a widely used logic for expressing properties of programs viewed as sets of executions. Our approach consists of translating LTL formulae to finite-state automata, which are used as observers of the program behavior. The translation algorithm we propose modifies standard LTL to B chi automata conversion techniques to generate automata that check finite program traces. The algorithm has been implemented in a tool, which has been integrated with the generic JPaX framework for runtime analysis of Java programs.

Brain Computation Is Organized via Power-of-Two-Based Permutation Logic.

PubMed

Xie, Kun; Fox, Grace E; Liu, Jun; Lyu, Cheng; Lee, Jason C; Kuang, Hui; Jacobs, Stephanie; Li, Meng; Liu, Tianming; Song, Sen; Tsien, Joe Z

2016-01-01

There is considerable scientific interest in understanding how cell assemblies-the long-presumed computational motif-are organized so that the brain can generate intelligent cognition and flexible behavior. The Theory of Connectivity proposes that the origin of intelligence is rooted in a power-of-two-based permutation logic ( N = 2 i -1), producing specific-to-general cell-assembly architecture capable of generating specific perceptions and memories, as well as generalized knowledge and flexible actions. We show that this power-of-two-based permutation logic is widely used in cortical and subcortical circuits across animal species and is conserved for the processing of a variety of cognitive modalities including appetitive, emotional and social information. However, modulatory neurons, such as dopaminergic (DA) neurons, use a simpler logic despite their distinct subtypes. Interestingly, this specific-to-general permutation logic remained largely intact although NMDA receptors-the synaptic switch for learning and memory-were deleted throughout adulthood, suggesting that the logic is developmentally pre-configured. Moreover, this computational logic is implemented in the cortex via combining a random-connectivity strategy in superficial layers 2/3 with nonrandom organizations in deep layers 5/6. This randomness of layers 2/3 cliques-which preferentially encode specific and low-combinatorial features and project inter-cortically-is ideal for maximizing cross-modality novel pattern-extraction, pattern-discrimination and pattern-categorization using sparse code, consequently explaining why it requires hippocampal offline-consolidation. In contrast, the nonrandomness in layers 5/6-which consists of few specific cliques but a higher portion of more general cliques projecting mostly to subcortical systems-is ideal for feedback-control of motivation, emotion, consciousness and behaviors. These observations suggest that the brain's basic computational algorithm is indeed organized by the power-of-two-based permutation logic. This simple mathematical logic can account for brain computation across the entire evolutionary spectrum, ranging from the simplest neural networks to the most complex.

Brain Computation Is Organized via Power-of-Two-Based Permutation Logic

PubMed Central

Xie, Kun; Fox, Grace E.; Liu, Jun; Lyu, Cheng; Lee, Jason C.; Kuang, Hui; Jacobs, Stephanie; Li, Meng; Liu, Tianming; Song, Sen; Tsien, Joe Z.

2016-01-01

There is considerable scientific interest in understanding how cell assemblies—the long-presumed computational motif—are organized so that the brain can generate intelligent cognition and flexible behavior. The Theory of Connectivity proposes that the origin of intelligence is rooted in a power-of-two-based permutation logic (N = 2i–1), producing specific-to-general cell-assembly architecture capable of generating specific perceptions and memories, as well as generalized knowledge and flexible actions. We show that this power-of-two-based permutation logic is widely used in cortical and subcortical circuits across animal species and is conserved for the processing of a variety of cognitive modalities including appetitive, emotional and social information. However, modulatory neurons, such as dopaminergic (DA) neurons, use a simpler logic despite their distinct subtypes. Interestingly, this specific-to-general permutation logic remained largely intact although NMDA receptors—the synaptic switch for learning and memory—were deleted throughout adulthood, suggesting that the logic is developmentally pre-configured. Moreover, this computational logic is implemented in the cortex via combining a random-connectivity strategy in superficial layers 2/3 with nonrandom organizations in deep layers 5/6. This randomness of layers 2/3 cliques—which preferentially encode specific and low-combinatorial features and project inter-cortically—is ideal for maximizing cross-modality novel pattern-extraction, pattern-discrimination and pattern-categorization using sparse code, consequently explaining why it requires hippocampal offline-consolidation. In contrast, the nonrandomness in layers 5/6—which consists of few specific cliques but a higher portion of more general cliques projecting mostly to subcortical systems—is ideal for feedback-control of motivation, emotion, consciousness and behaviors. These observations suggest that the brain’s basic computational algorithm is indeed organized by the power-of-two-based permutation logic. This simple mathematical logic can account for brain computation across the entire evolutionary spectrum, ranging from the simplest neural networks to the most complex. PMID:27895562

Fuzzy Logic Based Control for Autonomous Mobile Robot Navigation

PubMed Central

Masmoudi, Mohamed Slim; Masmoudi, Mohamed

2016-01-01

This paper describes the design and the implementation of a trajectory tracking controller using fuzzy logic for mobile robot to navigate in indoor environments. Most of the previous works used two independent controllers for navigation and avoiding obstacles. The main contribution of the paper can be summarized in the fact that we use only one fuzzy controller for navigation and obstacle avoidance. The used mobile robot is equipped with DC motor, nine infrared range (IR) sensors to measure the distance to obstacles, and two optical encoders to provide the actual position and speeds. To evaluate the performances of the intelligent navigation algorithms, different trajectories are used and simulated using MATLAB software and SIMIAM navigation platform. Simulation results show the performances of the intelligent navigation algorithms in terms of simulation times and travelled path. PMID:27688748

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.

Realworld maximum power point tracking simulation of PV system based on Fuzzy Logic control

NASA Astrophysics Data System (ADS)

Othman, Ahmed M.; El-arini, Mahdi M. M.; Ghitas, Ahmed; Fathy, Ahmed

2012-12-01

In the recent years, the solar energy becomes one of the most important alternative sources of electric energy, so it is important to improve the efficiency and reliability of the photovoltaic (PV) systems. Maximum power point tracking (MPPT) plays an important role in photovoltaic power systems because it maximize the power output from a PV system for a given set of conditions, and therefore maximize their array efficiency. This paper presents a maximum power point tracker (MPPT) using Fuzzy Logic theory for a PV system. The work is focused on the well known Perturb and Observe (P&O) algorithm and is compared to a designed fuzzy logic controller (FLC). The simulation work dealing with MPPT controller; a DC/DC Ćuk converter feeding a load is achieved. The results showed that the proposed Fuzzy Logic MPPT in the PV system is valid.

DNA strand displacement system running logic programs.

PubMed

Rodríguez-Patón, Alfonso; Sainz de Murieta, Iñaki; Sosík, Petr

2014-01-01

The paper presents a DNA-based computing model which is enzyme-free and autonomous, not requiring a human intervention during the computation. The model is able to perform iterated resolution steps with logical formulae in conjunctive normal form. The implementation is based on the technique of DNA strand displacement, with each clause encoded in a separate DNA molecule. Propositions are encoded assigning a strand to each proposition p, and its complementary strand to the proposition ¬p; clauses are encoded comprising different propositions in the same strand. The model allows to run logic programs composed of Horn clauses by cascading resolution steps. The potential of the model is demonstrated also by its theoretical capability of solving SAT. The resulting SAT algorithm has a linear time complexity in the number of resolution steps, whereas its spatial complexity is exponential in the number of variables of the formula. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Embedding Term Similarity and Inverse Document Frequency into a Logical Model of Information Retrieval.

ERIC Educational Resources Information Center

Losada, David E.; Barreiro, Alvaro

2003-01-01

Proposes an approach to incorporate term similarity and inverse document frequency into a logical model of information retrieval. Highlights include document representation and matching; incorporating term similarity into the measure of distance; new algorithms for implementation; inverse document frequency; and logical versus classical models of…

Architecture and data processing alternatives for the TSE computer. Volume 3: Execution of a parallel counting algorithm using array logic (Tse) devices

NASA Technical Reports Server (NTRS)

Metcalfe, A. G.; Bodenheimer, R. E.

1976-01-01

A parallel algorithm for counting the number of logic-l elements in a binary array or image developed during preliminary investigation of the Tse concept is described. The counting algorithm is implemented using a basic combinational structure. Modifications which improve the efficiency of the basic structure are also presented. A programmable Tse computer structure is proposed, along with a hardware control unit, Tse instruction set, and software program for execution of the counting algorithm. Finally, a comparison is made between the different structures in terms of their more important characteristics.

A Feature Mining Based Approach for the Classification of Text Documents into Disjoint Classes.

ERIC Educational Resources Information Center

Nieto Sanchez, Salvador; Triantaphyllou, Evangelos; Kraft, Donald

2002-01-01

Proposes a new approach for classifying text documents into two disjoint classes. Highlights include a brief overview of document clustering; a data mining approach called the One Clause at a Time (OCAT) algorithm which is based on mathematical logic; vector space model (VSM); and comparing the OCAT to the VSM. (Author/LRW)

An analytical fuzzy-based approach to ?-gain optimal control of input-affine nonlinear systems using Newton-type algorithm

NASA Astrophysics Data System (ADS)

Milic, Vladimir; Kasac, Josip; Novakovic, Branko

2015-10-01

This paper is concerned with ?-gain optimisation of input-affine nonlinear systems controlled by analytic fuzzy logic system. Unlike the conventional fuzzy-based strategies, the non-conventional analytic fuzzy control method does not require an explicit fuzzy rule base. As the first contribution of this paper, we prove, by using the Stone-Weierstrass theorem, that the proposed fuzzy system without rule base is universal approximator. The second contribution of this paper is an algorithm for solving a finite-horizon minimax problem for ?-gain optimisation. The proposed algorithm consists of recursive chain rule for first- and second-order derivatives, Newton's method, multi-step Adams method and automatic differentiation. Finally, the results of this paper are evaluated on a second-order nonlinear system.

An optimal adder-based hardware architecture for the DCT/SA-DCT

NASA Astrophysics Data System (ADS)

Kinane, Andrew; Muresan, Valentin; O'Connor, Noel

2005-07-01

The explosive growth of the mobile multimedia industry has accentuated the need for ecient VLSI implemen- tations of the associated computationally demanding signal processing algorithms. This need becomes greater as end-users demand increasingly enhanced features and more advanced underpinning video analysis. One such feature is object-based video processing as supported by MPEG-4 core profile, which allows content-based in- teractivity. MPEG-4 has many computationally demanding underlying algorithms, an example of which is the Shape Adaptive Discrete Cosine Transform (SA-DCT). The dynamic nature of the SA-DCT processing steps pose significant VLSI implementation challenges and many of the previously proposed approaches use area and power consumptive multipliers. Most also ignore the subtleties of the packing steps and manipulation of the shape information. We propose a new multiplier-less serial datapath based solely on adders and multiplexers to improve area and power. The adder cost is minimised by employing resource re-use methods. The number of (physical) adders used has been derived using a common sub-expression elimination algorithm. Additional energy eciency is factored into the design by employing guarded evaluation and local clock gating. Our design implements the SA-DCT packing with minimal switching using ecient addressing logic with a transpose mem- ory RAM. The entire design has been synthesized using TSMC 0.09µm TCBN90LP technology yielding a gate count of 12028 for the datapath and its control logic.

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

Kumar, Dinesh; Thapliyal, Himanshu; Mohammad, Azhar

Differential Power Analysis (DPA) attack is considered to be a main threat while designing cryptographic processors. In cryptographic algorithms like DES and AES, S-Box is used to indeterminate the relationship between the keys and the cipher texts. However, S-box is prone to DPA attack due to its high power consumption. In this paper, we are implementing an energy-efficient 8-bit S-Box circuit using our proposed Symmetric Pass Gate Adiabatic Logic (SPGAL). SPGAL is energy-efficient as compared to the existing DPAresistant adiabatic and non-adiabatic logic families. SPGAL is energy-efficient due to reduction of non-adiabatic loss during the evaluate phase of the outputs.more » Further, the S-Box circuit implemented using SPGAL is resistant to DPA attacks. The results are verified through SPICE simulations in 180nm technology. SPICE simulations show that the SPGAL based S-Box circuit saves upto 92% and 67% of energy as compared to the conventional CMOS and Secured Quasi-Adiabatic Logic (SQAL) based S-Box circuit. From the simulation results, it is evident that the SPGAL based circuits are energy-efficient as compared to the existing DPAresistant adiabatic and non-adiabatic logic families. In nutshell, SPGAL based gates can be used to build secure hardware for lowpower portable electronic devices and Internet-of-Things (IoT) based electronic devices.« less

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.

A genetic algorithms approach for altering the membership functions in fuzzy logic controllers

NASA Technical Reports Server (NTRS)

Shehadeh, Hana; Lea, Robert N.

1992-01-01

Through previous work, a fuzzy control system was developed to perform translational and rotational control of a space vehicle. This problem was then re-examined to determine the effectiveness of genetic algorithms on fine tuning the controller. This paper explains the problems associated with the design of this fuzzy controller and offers a technique for tuning fuzzy logic controllers. A fuzzy logic controller is a rule-based system that uses fuzzy linguistic variables to model human rule-of-thumb approaches to control actions within a given system. This 'fuzzy expert system' features rules that direct the decision process and membership functions that convert the linguistic variables into the precise numeric values used for system control. Defining the fuzzy membership functions is the most time consuming aspect of the controller design. One single change in the membership functions could significantly alter the performance of the controller. This membership function definition can be accomplished by using a trial and error technique to alter the membership functions creating a highly tuned controller. This approach can be time consuming and requires a great deal of knowledge from human experts. In order to shorten development time, an iterative procedure for altering the membership functions to create a tuned set that used a minimal amount of fuel for velocity vector approach and station-keep maneuvers was developed. Genetic algorithms, search techniques used for optimization, were utilized to solve this problem.

A Novel Strain-Based Method to Estimate Tire Conditions Using Fuzzy Logic for Intelligent Tires.

PubMed

Garcia-Pozuelo, Daniel; Olatunbosun, Oluremi; Yunta, Jorge; Yang, Xiaoguang; Diaz, Vicente

2017-02-10

The so-called intelligent tires are one of the most promising research fields for automotive engineers. These tires are equipped with sensors which provide information about vehicle dynamics. Up to now, the commercial intelligent tires only provide information about inflation pressure and their contribution to stability control systems is currently very limited. Nowadays one of the major problems for intelligent tire development is how to embed feasible and low cost sensors to obtain reliable information such as inflation pressure, vertical load or rolling speed. These parameters provide key information for vehicle dynamics characterization. In this paper, we propose a novel algorithm based on fuzzy logic to estimate the mentioned parameters by means of a single strain-based system. Experimental tests have been carried out in order to prove the suitability and durability of the proposed on-board strain sensor system, as well as its low cost advantages, and the accuracy of the obtained estimations by means of fuzzy logic.

A new robust control scheme using second order sliding mode and fuzzy logic of a DFIM supplied by two five-level SVPWM inverters

NASA Astrophysics Data System (ADS)

Boudjema, Zinelaabidine; Taleb, Rachid; Bounadja, Elhadj

2017-02-01

Traditional filed oriented control strategy including proportional-integral (PI) regulator for the speed drive of the doubly fed induction motor (DFIM) have some drawbacks such as parameter tuning complications, mediocre dynamic performances and reduced robustness. Therefore, based on the analysis of the mathematical model of a DFIM supplied by two five-level SVPWM inverters, this paper proposes a new robust control scheme based on super twisting sliding mode and fuzzy logic. The conventional sliding mode control (SMC) has vast chattering effect on the electromagnetic torque developed by the DFIM. In order to resolve this problem, a second order sliding mode technique based on super twisting algorithm and fuzzy logic functions is employed. The validity of the employed approach was tested by using Matlab/Simulink software. Interesting simulation results were obtained and remarkable advantages of the proposed control scheme were exposed including simple design of the control system, reduced chattering as well as the other advantages.

A Novel Strain-Based Method to Estimate Tire Conditions Using Fuzzy Logic for Intelligent Tires

PubMed Central

Garcia-Pozuelo, Daniel; Olatunbosun, Oluremi; Yunta, Jorge; Yang, Xiaoguang; Diaz, Vicente

2017-01-01

The so-called intelligent tires are one of the most promising research fields for automotive engineers. These tires are equipped with sensors which provide information about vehicle dynamics. Up to now, the commercial intelligent tires only provide information about inflation pressure and their contribution to stability control systems is currently very limited. Nowadays one of the major problems for intelligent tire development is how to embed feasible and low cost sensors to obtain reliable information such as inflation pressure, vertical load or rolling speed. These parameters provide key information for vehicle dynamics characterization. In this paper, we propose a novel algorithm based on fuzzy logic to estimate the mentioned parameters by means of a single strain-based system. Experimental tests have been carried out in order to prove the suitability and durability of the proposed on-board strain sensor system, as well as its low cost advantages, and the accuracy of the obtained estimations by means of fuzzy logic. PMID:28208631

Identifying Interacting Genetic Variations by Fish-Swarm Logic Regression

PubMed Central

Yang, Aiyuan; Yan, Chunxia; Zhu, Feng; Zhao, Zhongmeng; Cao, Zhi

2013-01-01

Understanding associations between genotypes and complex traits is a fundamental problem in human genetics. A major open problem in mapping phenotypes is that of identifying a set of interacting genetic variants, which might contribute to complex traits. Logic regression (LR) is a powerful multivariant association tool. Several LR-based approaches have been successfully applied to different datasets. However, these approaches are not adequate with regard to accuracy and efficiency. In this paper, we propose a new LR-based approach, called fish-swarm logic regression (FSLR), which improves the logic regression process by incorporating swarm optimization. In our approach, a school of fish agents are conducted in parallel. Each fish agent holds a regression model, while the school searches for better models through various preset behaviors. A swarm algorithm improves the accuracy and the efficiency by speeding up the convergence and preventing it from dropping into local optimums. We apply our approach on a real screening dataset and a series of simulation scenarios. Compared to three existing LR-based approaches, our approach outperforms them by having lower type I and type II error rates, being able to identify more preset causal sites, and performing at faster speeds. PMID:23984382

Teaching Proofs and Algorithms in Discrete Mathematics with Online Visual Logic Puzzles

ERIC Educational Resources Information Center

Cigas, John; Hsin, Wen-Jung

2005-01-01

Visual logic puzzles provide a fertile environment for teaching multiple topics in discrete mathematics. Many puzzles can be solved by the repeated application of a small, finite set of strategies. Explicitly reasoning from a strategy to a new puzzle state illustrates theorems, proofs, and logic principles. These provide valuable, concrete…

Calculator Logic Systems and Mathematical Understandings.

ERIC Educational Resources Information Center

Burrows, Enid R.

This monograph is aimed at helping the reader understand the built-in logic of various calculator operating systems. It is an outgrowth of workshop contacts with in-service and pre-service teachers of mathematics and is in response to their request for a book on the subject of calculator logic systems and calculator algorithms. The mathematical…

Evidence-based algorithm for heparin dosing before cardiopulmonary bypass. Part 1: Development of the algorithm.

PubMed

McKinney, Mark C; Riley, Jeffrey B

2007-12-01

The incidence of heparin resistance during adult cardiac surgery with cardiopulmonary bypass has been reported at 15%-20%. The consistent use of a clinical decision-making algorithm may increase the consistency of patient care and likely reduce the total required heparin dose and other problems associated with heparin dosing. After a directed survey of practicing perfusionists regarding treatment of heparin resistance and a literature search for high-level evidence regarding the diagnosis and treatment of heparin resistance, an evidence-based decision-making algorithm was constructed. The face validity of the algorithm decisive steps and logic was confirmed by a second survey of practicing perfusionists. The algorithm begins with review of the patient history to identify predictors for heparin resistance. The definition for heparin resistance contained in the algorithm is an activated clotting time < 450 seconds with > 450 IU/kg heparin loading dose. Based on the literature, the treatment for heparin resistance used in the algorithm is anti-thrombin III supplement. The algorithm seems to be valid and is supported by high-level evidence and clinician opinion. The next step is a human randomized clinical trial to test the clinical procedure guideline algorithm vs. current standard clinical practice.

Acceleration of block-matching algorithms using a custom instruction-based paradigm on a Nios II microprocessor

NASA Astrophysics Data System (ADS)

González, Diego; Botella, Guillermo; García, Carlos; Prieto, Manuel; Tirado, Francisco

2013-12-01

This contribution focuses on the optimization of matching-based motion estimation algorithms widely used for video coding standards using an Altera custom instruction-based paradigm and a combination of synchronous dynamic random access memory (SDRAM) with on-chip memory in Nios II processors. A complete profile of the algorithms is achieved before the optimization, which locates code leaks, and afterward, creates a custom instruction set, which is then added to the specific design, enhancing the original system. As well, every possible memory combination between on-chip memory and SDRAM has been tested to achieve the best performance. The final throughput of the complete designs are shown. This manuscript outlines a low-cost system, mapped using very large scale integration technology, which accelerates software algorithms by converting them into custom hardware logic blocks and showing the best combination between on-chip memory and SDRAM for the Nios II processor.

Generalizing Atoms in Constraint Logic

NASA Technical Reports Server (NTRS)

Page, C. David, Jr.; Frisch, Alan M.

1991-01-01

This paper studies the generalization of atomic formulas, or atoms, that are augmented with constraints on or among their terms. The atoms may also be viewed as definite clauses whose antecedents express the constraints. Atoms are generalized relative to a body of background information about the constraints. This paper first examines generalization of atoms with only monadic constraints. The paper develops an algorithm for the generalization task and discusses algorithm complexity. It then extends the algorithm to apply to atoms with constraints of arbitrary arity. The paper also presents semantic properties of the generalizations computed by the algorithms, making the algorithms applicable to such problems as abduction, induction, and knowledge base verification. The paper emphasizes the application to induction and presents a pac-learning result for constrained atoms.

Bio-Inspired Genetic Algorithms with Formalized Crossover Operators for Robotic Applications.

PubMed

Zhang, Jie; Kang, Man; Li, Xiaojuan; Liu, Geng-Yang

2017-01-01

Genetic algorithms are widely adopted to solve optimization problems in robotic applications. In such safety-critical systems, it is vitally important to formally prove the correctness when genetic algorithms are applied. This paper focuses on formal modeling of crossover operations that are one of most important operations in genetic algorithms. Specially, we for the first time formalize crossover operations with higher-order logic based on HOL4 that is easy to be deployed with its user-friendly programing environment. With correctness-guaranteed formalized crossover operations, we can safely apply them in robotic applications. We implement our technique to solve a path planning problem using a genetic algorithm with our formalized crossover operations, and the results show the effectiveness of our technique.

Efficient Boundary Extraction of BSP Solids Based on Clipping Operations.

PubMed

Wang, Charlie C L; Manocha, Dinesh

2013-01-01

We present an efficient algorithm to extract the manifold surface that approximates the boundary of a solid represented by a Binary Space Partition (BSP) tree. Our polygonization algorithm repeatedly performs clipping operations on volumetric cells that correspond to a spatial convex partition and computes the boundary by traversing the connected cells. We use point-based representations along with finite-precision arithmetic to improve the efficiency and generate the B-rep approximation of a BSP solid. The core of our polygonization method is a novel clipping algorithm that uses a set of logical operations to make it resistant to degeneracies resulting from limited precision of floating-point arithmetic. The overall BSP to B-rep conversion algorithm can accurately generate boundaries with sharp and small features, and is faster than prior methods. At the end of this paper, we use this algorithm for a few geometric processing applications including Boolean operations, model repair, and mesh reconstruction.

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.

Testing Linear Temporal Logic Formulae on Finite Execution Traces

NASA Technical Reports Server (NTRS)

Havelund, Klaus; Rosu, Grigore; Norvig, Peter (Technical Monitor)

2001-01-01

We present an algorithm for efficiently testing Linear Temporal Logic (LTL) formulae on finite execution traces. The standard models of LTL are infinite traces, reflecting the behavior of reactive and concurrent systems which conceptually may be continuously alive. In most past applications of LTL. theorem provers and model checkers have been used to formally prove that down-scaled models satisfy such LTL specifications. Our goal is instead to use LTL for up-scaled testing of real software applications. Such tests correspond to analyzing the conformance of finite traces against LTL formulae. We first describe what it means for a finite trace to satisfy an LTL property. We then suggest an optimized algorithm based on transforming LTL formulae. The work is done using the Maude rewriting system. which turns out to provide a perfect notation and an efficient rewriting engine for performing these experiments.

Controllability of switched singular mix-valued logical control networks with constraints

NASA Astrophysics Data System (ADS)

Deng, Lei; Gong, Mengmeng; Zhu, Peiyong

2018-03-01

The present paper investigates the controllability problem of switched singular mix-valued logical control networks (SSMLCNs) with constraints on states and controls. First, using the semi-tenser product (STP) of matrices, the SSMLCN is expressed in an algebraic form, based on which a necessary and sufficient condition is given for the uniqueness of solution of SSMLCNs. Second, a necessary and sufficient criteria is derived for the controllability of constrained SSMLCNs, by converting a constrained SSMLCN into a parallel constrained switched mix-valued logical control network. Third, an algorithm is presented to design a proper switching sequence and a control scheme which force a state to a reachable state. Finally, a numerical example is given to demonstrate the efficiency of the results obtained in this paper.

Computational Intelligence Based Data Fusion Algorithm for Dynamic sEMG and Skeletal Muscle Force Modelling

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

Chandrasekhar Potluri,; Madhavi Anugolu; Marco P. Schoen

2013-08-01

In this work, an array of three surface Electrography (sEMG) sensors are used to acquired muscle extension and contraction signals for 18 healthy test subjects. The skeletal muscle force is estimated using the acquired sEMG signals and a Non-linear Wiener Hammerstein model, relating the two signals in a dynamic fashion. The model is obtained from using System Identification (SI) algorithm. The obtained force models for each sensor are fused using a proposed fuzzy logic concept with the intent to improve the force estimation accuracy and resilience to sensor failure or misalignment. For the fuzzy logic inference system, the sEMG entropy,more » the relative error, and the correlation of the force signals are considered for defining the membership functions. The proposed fusion algorithm yields an average of 92.49% correlation between the actual force and the overall estimated force output. In addition, the proposed fusionbased approach is implemented on a test platform. Experiments indicate an improvement in finger/hand force estimation.« less

The design and performance characteristics of a cellular logic 3-D image classification processor

NASA Astrophysics Data System (ADS)

Ankeney, L. A.

1981-04-01

The introduction of high resolution scanning laser radar systems which are capable of collecting range and reflectivity images, is predicted to significantly influence the development of processors capable of performing autonomous target classification tasks. Actively sensed range images are shown to be superior to passively collected infrared images in both image stability and information content. An illustrated tutorial introduces cellular logic (neighborhood) transformations and two and three dimensional erosion and dilation operations which are used for noise filters and geometric shape measurement. A unique 'cookbook' approach to selecting a sequence of neighborhood transformations suitable for object measurement is developed and related to false alarm rate and algorithm effectiveness measures. The cookbook design approach is used to develop an algorithm to classify objects based upon their 3-D geometrical features. A Monte Carlo performance analysis is used to demonstrate the utility of the design approach by characterizing the ability of the algorithm to classify randomly positioned three dimensional objects in the presence of additive noise, scale variations, and other forms of image distortion.

Multi-Objectives Optimization of Ventilation Controllers for Passive Cooling in Residential Buildings

PubMed Central

Grygierek, Krzysztof; Ferdyn-Grygierek, Joanna

2018-01-01

An inappropriate indoor climate, mostly indoor temperature, may cause occupants’ discomfort. There are a great number of air conditioning systems that make it possible to maintain the required thermal comfort. Their installation, however, involves high investment costs and high energy demand. The study analyses the possibilities of limiting too high a temperature in residential buildings using passive cooling by means of ventilation with ambient cool air. A fuzzy logic controller whose aim is to control mechanical ventilation has been proposed and optimized. In order to optimize the controller, the modified Multiobjective Evolutionary Algorithm, based on the Strength Pareto Evolutionary Algorithm, has been adopted. The optimization algorithm has been implemented in MATLAB®, which is coupled by MLE+ with EnergyPlus for performing dynamic co-simulation between the programs. The example of a single detached building shows that the occupants’ thermal comfort in a transitional climate may improve significantly owing to mechanical ventilation controlled by the suggested fuzzy logic controller. When the system is connected to the traditional cooling system, it may further bring about a decrease in cooling demand. PMID:29642525

Logic Model Checking of Time-Periodic Real-Time Systems

NASA Technical Reports Server (NTRS)

Florian, Mihai; Gamble, Ed; Holzmann, Gerard

2012-01-01

In this paper we report on the work we performed to extend the logic model checker SPIN with built-in support for the verification of periodic, real-time embedded software systems, as commonly used in aircraft, automobiles, and spacecraft. We first extended the SPIN verification algorithms to model priority based scheduling policies. Next, we added a library to support the modeling of periodic tasks. This library was used in a recent application of the SPIN model checker to verify the engine control software of an automobile, to study the feasibility of software triggers for unintended acceleration events.

A Genetic Algorithm and Fuzzy Logic Approach for Video Shot Boundary Detection

PubMed Central

Thounaojam, Dalton Meitei; Khelchandra, Thongam; Singh, Kh. Manglem; Roy, Sudipta

2016-01-01

This paper proposed a shot boundary detection approach using Genetic Algorithm and Fuzzy Logic. In this, the membership functions of the fuzzy system are calculated using Genetic Algorithm by taking preobserved actual values for shot boundaries. The classification of the types of shot transitions is done by the fuzzy system. Experimental results show that the accuracy of the shot boundary detection increases with the increase in iterations or generations of the GA optimization process. The proposed system is compared to latest techniques and yields better result in terms of F1score parameter. PMID:27127500

Model-based approach for cyber-physical attack detection in water distribution systems.

PubMed

Housh, Mashor; Ohar, Ziv

2018-08-01

Modern Water Distribution Systems (WDSs) are often controlled by Supervisory Control and Data Acquisition (SCADA) systems and Programmable Logic Controllers (PLCs) which manage their operation and maintain a reliable water supply. As such, and with the cyber layer becoming a central component of WDS operations, these systems are at a greater risk of being subjected to cyberattacks. This paper offers a model-based methodology based on a detailed hydraulic understanding of WDSs combined with an anomaly detection algorithm for the identification of complex cyberattacks that cannot be fully identified by hydraulically based rules alone. The results show that the proposed algorithm is capable of achieving the best-known performance when tested on the data published in the BATtle of the Attack Detection ALgorithms (BATADAL) competition (http://www.batadal.net). Copyright © 2018. Published by Elsevier Ltd.

Multitarget mixture reduction algorithm with incorporated target existence recursions

NASA Astrophysics Data System (ADS)

Ristic, Branko; Arulampalam, Sanjeev

2000-07-01

The paper derives a deferred logic data association algorithm based on the mixture reduction approach originally due to Salmond [SPIE vol.1305, 1990]. The novelty of the proposed algorithm provides the recursive formulae for both data association and target existence (confidence) estimation, thus allowing automatic track initiation and termination. T he track initiation performance of the proposed filter is investigated by computer simulations. It is observed that at moderately high levels of clutter density the proposed filter initiates tracks more reliably than its corresponding PDA filter. An extension of the proposed filter to the multi-target case is also presented. In addition, the paper compares the track maintenance performance of the MR algorithm with an MHT implementation.

The Forensic Potential of Flash Memory

DTIC Science & Technology

2009-09-01

limit range of 10 to 100 years before data is lost [12]. 5. Flash Memory Logical Structure The logical structure of flash memory from least to...area is not standardized and is manufacturer specific. This information will be used by the wear leveling algorithms and as such will be proprietary...memory cells, the manufacturers of the flash implement a wear leveling algorithm . In contrast, a magnetic disk in an overwrite operation will reuse the

Encoding Schemes For A Digital Optical Multiplier Using The Modified Signed-Digit Number Representation

NASA Astrophysics Data System (ADS)

Lasher, Mark E.; Henderson, Thomas B.; Drake, Barry L.; Bocker, Richard P.

1986-09-01

The modified signed-digit (MSD) number representation offers full parallel, carry-free addition. A MSD adder has been described by the authors. This paper describes how the adder can be used in a tree structure to implement an optical multiply algorithm. Three different optical schemes, involving position, polarization, and intensity encoding, are proposed for realizing the trinary logic system. When configured in the generic multiplier architecture, these schemes yield the combinatorial logic necessary to carry out the multiplication algorithm. The optical systems are essentially three dimensional arrangements composed of modular units. Of course, this modularity is important for design considerations, while the parallelism and noninterfering communication channels of optical systems are important from the standpoint of reduced complexity. The authors have also designed electronic hardware to demonstrate and model the combinatorial logic required to carry out the algorithm. The electronic and proposed optical systems will be compared in terms of complexity and speed.

A Fuzzy-Decision Based Approach for Composite Event Detection in Wireless Sensor Networks

PubMed Central

Zhang, Shukui; Chen, Hao; Zhu, Qiaoming

2014-01-01

The event detection is one of the fundamental researches in wireless sensor networks (WSNs). Due to the consideration of various properties that reflect events status, the Composite event is more consistent with the objective world. Thus, the research of the Composite event becomes more realistic. In this paper, we analyze the characteristics of the Composite event; then we propose a criterion to determine the area of the Composite event and put forward a dominating set based network topology construction algorithm under random deployment. For the unreliability of partial data in detection process and fuzziness of the event definitions in nature, we propose a cluster-based two-dimensional τ-GAS algorithm and fuzzy-decision based composite event decision mechanism. In the case that the sensory data of most nodes are normal, the two-dimensional τ-GAS algorithm can filter the fault node data effectively and reduce the influence of erroneous data on the event determination. The Composite event judgment mechanism which is based on fuzzy-decision holds the superiority of the fuzzy-logic based algorithm; moreover, it does not need the support of a huge rule base and its computational complexity is small. Compared to CollECT algorithm and CDS algorithm, this algorithm improves the detection accuracy and reduces the traffic. PMID:25136690

Efficient Web Services Policy Combination

NASA Technical Reports Server (NTRS)

Vatan, Farrokh; Harman, Joseph G.

2010-01-01

Large-scale Web security systems usually involve cooperation between domains with non-identical policies. The network management and Web communication software used by the different organizations presents a stumbling block. Many of the tools used by the various divisions do not have the ability to communicate network management data with each other. At best, this means that manual human intervention into the communication protocols used at various network routers and endpoints is required. Developing practical, sound, and automated ways to compose policies to bridge these differences is a long-standing problem. One of the key subtleties is the need to deal with inconsistencies and defaults where one organization proposes a rule on a particular feature, and another has a different rule or expresses no rule. A general approach is to assign priorities to rules and observe the rules with the highest priorities when there are conflicts. The present methods have inherent inefficiency, which heavily restrict their practical applications. A new, efficient algorithm combines policies utilized for Web services. The method is based on an algorithm that allows an automatic and scalable composition of security policies between multiple organizations. It is based on defeasible policy composition, a promising approach for finding conflicts and resolving priorities between rules. In the general case, policy negotiation is an intractable problem. A promising method, suggested in the literature, is when policies are represented in defeasible logic, and composition is based on rules for non-monotonic inference. In this system, policy writers construct metapolicies describing both the policy that they wish to enforce and annotations describing their composition preferences. These annotations can indicate whether certain policy assertions are required by the policy writer or, if not, under what circumstances the policy writer is willing to compromise and allow other assertions to take precedence. Meta-policies are specified in defeasible logic, a computationally efficient non-monotonic logic developed to model human reasoning. One drawback of this method is that at one point the algorithm starts an exhaustive search of all subsets of the set of conclusions of a defeasible theory. Although the propositional defeasible logic has linear complexity, the set of conclusions here may be large, especially in real-life practical cases. This phenomenon leads to an inefficient exponential explosion of complexity. The current process of getting a Web security policy from combination of two meta-policies consists of two steps. The first is generating a new meta-policy that is a composition of the input meta-policies, and the second is mapping the meta-policy onto a security policy. The new algorithm avoids the exhaustive search in the current algorithm, and provides a security policy that matches all requirements of the involved metapolicies.

Strategic Control Algorithm Development : Volume 4A. Computer Program Report.

DOT National Transportation Integrated Search

1974-08-01

A description of the strategic algorithm evaluation model is presented, both at the user and programmer levels. The model representation of an airport configuration, environmental considerations, the strategic control algorithm logic, and the airplan...

Strategic Control Algorithm Development : Volume 4B. Computer Program Report (Concluded)

DOT National Transportation Integrated Search

1974-08-01

A description of the strategic algorithm evaluation model is presented, both at the user and programmer levels. The model representation of an airport configuration, environmental considerations, the strategic control algorithm logic, and the airplan...

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.

Evolutionary Fuzzy Block-Matching-Based Camera Raw Image Denoising.

PubMed

Yang, Chin-Chang; Guo, Shu-Mei; Tsai, Jason Sheng-Hong

2017-09-01

An evolutionary fuzzy block-matching-based image denoising algorithm is proposed to remove noise from a camera raw image. Recently, a variance stabilization transform is widely used to stabilize the noise variance, so that a Gaussian denoising algorithm can be used to remove the signal-dependent noise in camera sensors. However, in the stabilized domain, the existed denoising algorithm may blur too much detail. To provide a better estimate of the noise-free signal, a new block-matching approach is proposed to find similar blocks by the use of a type-2 fuzzy logic system (FLS). Then, these similar blocks are averaged with the weightings which are determined by the FLS. Finally, an efficient differential evolution is used to further improve the performance of the proposed denoising algorithm. The experimental results show that the proposed denoising algorithm effectively improves the performance of image denoising. Furthermore, the average performance of the proposed method is better than those of two state-of-the-art image denoising algorithms in subjective and objective measures.

Research on NC motion controller based on SOPC technology

NASA Astrophysics Data System (ADS)

Jiang, Tingbiao; Meng, Biao

2006-11-01

With the rapid development of the digitization and informationization, the application of numerical control technology in the manufacturing industry becomes more and more important. However, the conventional numerical control system usually has some shortcomings such as the poor in system openness, character of real-time, cutability and reconfiguration. In order to solve these problems, this paper investigates the development prospect and advantage of the application in numerical control area with system-on-a-Programmable-Chip (SOPC) technology, and puts forward to a research program approach to the NC controller based on SOPC technology. Utilizing the characteristic of SOPC technology, we integrate high density logic device FPGA, memory SRAM, and embedded processor ARM into a single programmable logic device. We also combine the 32-bit RISC processor with high computing capability of the complicated algorithm with the FPGA device with strong motivable reconfiguration logic control ability. With these steps, we can greatly resolve the defect described in above existing numerical control systems. For the concrete implementation method, we use FPGA chip embedded with ARM hard nuclear processor to construct the control core of the motion controller. We also design the peripheral circuit of the controller according to the requirements of actual control functions, transplant real-time operating system into ARM, design the driver of the peripheral assisted chip, develop the application program to control and configuration of FPGA, design IP core of logic algorithm for various NC motion control to configured it into FPGA. The whole control system uses the concept of modular and structured design to develop hardware and software system. Thus the NC motion controller with the advantage of easily tailoring, highly opening, reconfigurable, and expandable can be implemented.

Logic gates based all-optical binary half adder using triple core photonic crystal fiber

NASA Astrophysics Data System (ADS)

Uthayakumar, T.; Vasantha Jayakantha Raja, R.

2018-06-01

This study presents the implementation of an all-optical binary logic half adder by employing a triple core photonic crystal fiber (TPCF). The noteworthy feature of the present investigation is that an identical set of TPCF schemes, which demonstrated all-optical logic functions in our previous report, has revealed the ability to demonstrate the successful half adder operation. The control signal (CS) power defining the extinction ratios of the output ports for the considered symmetric planar and triangular TPCFs is evaluated through a numerical algorithm. Through suitable CS power and input combinations, the logic outputs are generated from extinction ratios to demonstrate the half adder operation. The results obtained display the significant influence of the input conditions on the delivery of half adder operation for different TPCF schemes considered. Furthermore, chloroform filled TPCF structures demonstrated the efficient low power half adder operation with a significant figure of merit, compared to that of the silica counterpart.

Towards Resilient Critical Infrastructures: Application of Type-2 Fuzzy Logic in Embedded Network Security Cyber Sensor

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

Ondrej Linda; Todd Vollmer; Jim Alves-Foss

2011-08-01

Resiliency and cyber security of modern critical infrastructures is becoming increasingly important with the growing number of threats in the cyber-environment. This paper proposes an extension to a previously developed fuzzy logic based anomaly detection network security cyber sensor via incorporating Type-2 Fuzzy Logic (T2 FL). In general, fuzzy logic provides a framework for system modeling in linguistic form capable of coping with imprecise and vague meanings of words. T2 FL is an extension of Type-1 FL which proved to be successful in modeling and minimizing the effects of various kinds of dynamic uncertainties. In this paper, T2 FL providesmore » a basis for robust anomaly detection and cyber security state awareness. In addition, the proposed algorithm was specifically developed to comply with the constrained computational requirements of low-cost embedded network security cyber sensors. The performance of the system was evaluated on a set of network data recorded from an experimental cyber-security test-bed.« less

Simulation of the Predictive Control Algorithm for Container Crane Operation using Matlab Fuzzy Logic Tool Box

NASA Technical Reports Server (NTRS)

Richardson, Albert O.

1997-01-01

This research has investigated the use of fuzzy logic, via the Matlab Fuzzy Logic Tool Box, to design optimized controller systems. The engineering system for which the controller was designed and simulate was the container crane. The fuzzy logic algorithm that was investigated was the 'predictive control' algorithm. The plant dynamics of the container crane is representative of many important systems including robotic arm movements. The container crane that was investigated had a trolley motor and hoist motor. Total distance to be traveled by the trolley was 15 meters. The obstruction height was 5 meters. Crane height was 17.8 meters. Trolley mass was 7500 kilograms. Load mass was 6450 kilograms. Maximum trolley and rope velocities were 1.25 meters per sec. and 0.3 meters per sec., respectively. The fuzzy logic approach allowed the inclusion, in the controller model, of performance indices that are more effectively defined in linguistic terms. These include 'safety' and 'cargo swaying'. Two fuzzy inference systems were implemented using the Matlab simulation package, namely the Mamdani system (which relates fuzzy input variables to fuzzy output variables), and the Sugeno system (which relates fuzzy input variables to crisp output variable). It is found that the Sugeno FIS is better suited to including aspects of those plant dynamics whose mathematical relationships can be determined.

Formal logic rewrite system bachelor in teaching mathematical informatics

NASA Astrophysics Data System (ADS)

Habiballa, Hashim; Jendryscik, Radek

2017-07-01

The article presents capabilities of the formal rewrite logic system - Bachelor - for teaching theoretical computer science (mathematical informatics). The system Bachelor enables constructivist approach to teaching and therefore it may enhance the learning process in hard informatics essential disciplines. It brings not only detailed description of formal rewrite process but also it can demonstrate algorithmical principles for logic formulae manipulations.

Real-Time Algebraic Derivative Estimations Using a Novel Low-Cost Architecture Based on Reconfigurable Logic

PubMed Central

Morales, Rafael; Rincón, Fernando; Gazzano, Julio Dondo; López, Juan Carlos

2014-01-01

Time derivative estimation of signals plays a very important role in several fields, such as signal processing and control engineering, just to name a few of them. For that purpose, a non-asymptotic algebraic procedure for the approximate estimation of the system states is used in this work. The method is based on results from differential algebra and furnishes some general formulae for the time derivatives of a measurable signal in which two algebraic derivative estimators run simultaneously, but in an overlapping fashion. The algebraic derivative algorithm presented in this paper is computed online and in real-time, offering high robustness properties with regard to corrupting noises, versatility and ease of implementation. Besides, in this work, we introduce a novel architecture to accelerate this algebraic derivative estimator using reconfigurable logic. The core of the algorithm is implemented in an FPGA, improving the speed of the system and achieving real-time performance. Finally, this work proposes a low-cost platform for the integration of hardware in the loop in MATLAB. PMID:24859033

Automated Robot Movement in the Mapped Area Using Fuzzy Logic for Wheel Chair Application

NASA Astrophysics Data System (ADS)

Siregar, B.; Efendi, S.; Ramadhana, H.; Andayani, U.; Fahmi, F.

2018-03-01

The difficulties of the disabled to move make them unable to live independently. People with disabilities need supporting device to move from place to place. For that, we proposed a solution that can help people with disabilities to move from one room to another automatically. This study aims to create a wheelchair prototype in the form of a wheeled robot as a means to learn the automatic mobilization. The fuzzy logic algorithm was used to determine motion direction based on initial position, ultrasonic sensors reading in avoiding obstacles, infrared sensors reading as a black line reader for the wheeled robot to move smooth and smartphone as a mobile controller. As a result, smartphones with the Android operating system can control the robot using Bluetooth. Here Bluetooth technology can be used to control the robot from a maximum distance of 15 meters. The proposed algorithm was able to work stable for automatic motion determination based on initial position, and also able to modernize the wheelchair movement from one room to another automatically.

Learning and tuning fuzzy logic controllers through reinforcements

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.; Khedkar, Pratap

1992-01-01

A new method for learning and tuning a fuzzy logic controller based on reinforcements from a dynamic system is presented. In particular, our Generalized Approximate Reasoning-based Intelligent Control (GARIC) architecture: (1) learns and tunes a fuzzy logic controller even when only weak reinforcements, such as a binary failure signal, is available; (2) introduces a new conjunction operator in computing the rule strengths of fuzzy control rules; (3) introduces a new localized mean of maximum (LMOM) method in combining the conclusions of several firing control rules; and (4) learns to produce real-valued control actions. Learning is achieved by integrating fuzzy inference into a feedforward network, which can then adaptively improve performance by using gradient descent methods. We extend the AHC algorithm of Barto, Sutton, and Anderson to include the prior control knowledge of human operators. The GARIC architecture is applied to a cart-pole balancing system and has demonstrated significant improvements in terms of the speed of learning and robustness to changes in the dynamic system's parameters over previous schemes for cart-pole balancing.

Adaptive Control Strategies for Flexible Robotic Arm

NASA Technical Reports Server (NTRS)

Bialasiewicz, Jan T.

1996-01-01

The control problem of a flexible robotic arm has been investigated. The control strategies that have been developed have a wide application in approaching the general control problem of flexible space structures. The following control strategies have been developed and evaluated: neural self-tuning control algorithm, neural-network-based fuzzy logic control algorithm, and adaptive pole assignment algorithm. All of the above algorithms have been tested through computer simulation. In addition, the hardware implementation of a computer control system that controls the tip position of a flexible arm clamped on a rigid hub mounted directly on the vertical shaft of a dc motor, has been developed. An adaptive pole assignment algorithm has been applied to suppress vibrations of the described physical model of flexible robotic arm and has been successfully tested using this testbed.

Co-evolutionary data mining for fuzzy rules: automatic fitness function creation phase space, and experiments

NASA Astrophysics Data System (ADS)

Smith, James F., III; Blank, Joseph A.

2003-03-01

An approach is being explored that involves embedding a fuzzy logic based resource manager in an electronic game environment. Game agents can function under their own autonomous logic or human control. This approach automates the data mining problem. The game automatically creates a cleansed database reflecting the domain expert's knowledge, it calls a data mining function, a genetic algorithm, for data mining of the data base as required and allows easy evaluation of the information extracted. The co-evolutionary fitness functions, chromosomes and stopping criteria for ending the game are discussed. Genetic algorithm and genetic program based data mining procedures are discussed that automatically discover new fuzzy rules and strategies. The strategy tree concept and its relationship to co-evolutionary data mining are examined as well as the associated phase space representation of fuzzy concepts. The overlap of fuzzy concepts in phase space reduces the effective strategies available to adversaries. Co-evolutionary data mining alters the geometric properties of the overlap region known as the admissible region of phase space significantly enhancing the performance of the resource manager. Procedures for validation of the information data mined are discussed and significant experimental results provided.

Appendix F. Developmental enforcement algorithm definition document : predictive braking enforcement algorithm definition document.

DOT National Transportation Integrated Search

2012-05-01

The purpose of this document is to fully define and describe the logic flow and mathematical equations for a predictive braking enforcement algorithm intended for implementation in a Positive Train Control (PTC) system.

Algorithme et enseignement de la grammaire (Algorithm and the Teaching of Grammar)

ERIC Educational Resources Information Center

Michiels, A.

1975-01-01

Binary algorithmic logic may prove useful for teaching grammar, especially in the case of 'closed-system items.' (Text is in French.) Available from Instituut voor Toegepaste Linguistiek, Vesaliusstraat 2, B. 3000 Leuven, Belgium. (TL)

Implementation of trinary logic in a polarization encoded optical shadow-casting scheme.

PubMed

Rizvi, R A; Zaheer, K; Zubairy, M S

1991-03-10

The design of various multioutput trinary combinational logic units by a polarization encoded optical shadow-casting (POSC) technique is presented. The POSC modified algorithm is employed to design and implement these logic elements in a trinary number system with separate and simultaneous generation of outputs. A detailed solution of the POSC logic equations for a fixed source plane and a fixed decoding mask is given to obtain input pixel coding for a trinary half-adder, full adder, and subtractor.

Knowledge-Based Scheduling of Arrival Aircraft in the Terminal Area

NASA Technical Reports Server (NTRS)

Krzeczowski, K. J.; Davis, T.; Erzberger, H.; Lev-Ram, Israel; Bergh, Christopher P.

1995-01-01

A knowledge based method for scheduling arrival aircraft in the terminal area has been implemented and tested in real time simulation. The scheduling system automatically sequences, assigns landing times, and assign runways to arrival aircraft by utilizing continuous updates of aircraft radar data and controller inputs. The scheduling algorithm is driven by a knowledge base which was obtained in over two thousand hours of controller-in-the-loop real time simulation. The knowledge base contains a series of hierarchical 'rules' and decision logic that examines both performance criteria, such as delay reductions, as well as workload reduction criteria, such as conflict avoidance. The objective of the algorithm is to devise an efficient plan to land the aircraft in a manner acceptable to the air traffic controllers. This paper describes the scheduling algorithms, gives examples of their use, and presents data regarding their potential benefits to the air traffic system.

Knowledge-based scheduling of arrival aircraft

NASA Technical Reports Server (NTRS)

Krzeczowski, K.; Davis, T.; Erzberger, H.; Lev-Ram, I.; Bergh, C.

1995-01-01

A knowledge-based method for scheduling arrival aircraft in the terminal area has been implemented and tested in real-time simulation. The scheduling system automatically sequences, assigns landing times, and assigns runways to arrival aircraft by utilizing continuous updates of aircraft radar data and controller inputs. The scheduling algorithms is driven by a knowledge base which was obtained in over two thousand hours of controller-in-the-loop real-time simulation. The knowledge base contains a series of hierarchical 'rules' and decision logic that examines both performance criteria, such as delay reduction, as well as workload reduction criteria, such as conflict avoidance. The objective of the algorithms is to devise an efficient plan to land the aircraft in a manner acceptable to the air traffic controllers. This paper will describe the scheduling algorithms, give examples of their use, and present data regarding their potential benefits to the air traffic system.

Mitigation of adverse interactions in pairs of clinical practice guidelines using constraint logic programming.

PubMed

Wilk, Szymon; Michalowski, Wojtek; Michalowski, Martin; Farion, Ken; Hing, Marisela Mainegra; Mohapatra, Subhra

2013-04-01

We propose a new method to mitigate (identify and address) adverse interactions (drug-drug or drug-disease) that occur when a patient with comorbid diseases is managed according to two concurrently applied clinical practice guidelines (CPGs). A lack of methods to facilitate the concurrent application of CPGs severely limits their use in clinical practice and the development of such methods is one of the grand challenges for clinical decision support. The proposed method responds to this challenge. We introduce and formally define logical models of CPGs and other related concepts, and develop the mitigation algorithm that operates on these concepts. In the algorithm we combine domain knowledge encoded as interaction and revision operators using the constraint logic programming (CLP) paradigm. The operators characterize adverse interactions and describe revisions to logical models required to address these interactions, while CLP allows us to efficiently solve the logical models - a solution represents a feasible therapy that may be safely applied to a patient. The mitigation algorithm accepts two CPGs and available (likely incomplete) patient information. It reports whether mitigation has been successful or not, and on success it gives a feasible therapy and points at identified interactions (if any) together with the revisions that address them. Thus, we consider the mitigation algorithm as an alerting tool to support a physician in the concurrent application of CPGs that can be implemented as a component of a clinical decision support system. We illustrate our method in the context of two clinical scenarios involving a patient with duodenal ulcer who experiences an episode of transient ischemic attack. Copyright © 2013 Elsevier Inc. All rights reserved.

Toward Developing an Unbiased Scoring Algorithm for "NASA" and Similar Ranking Tasks.

ERIC Educational Resources Information Center

Lane, Irving M.; And Others

1981-01-01

Presents both logical and empirical evidence to illustrate that the conventional scoring algorithm for ranking tasks significantly underestimates the initial level of group ability and that Slevin's alternative scoring algorithm significantly overestimates the initial level of ability. Presents a modification of Slevin's algorithm which authors…

Logic-based assessment of the compatibility of UMLS ontology sources

PubMed Central

2011-01-01

Background The UMLS Metathesaurus (UMLS-Meta) is currently the most comprehensive effort for integrating independently-developed medical thesauri and ontologies. UMLS-Meta is being used in many applications, including PubMed and ClinicalTrials.gov. The integration of new sources combines automatic techniques, expert assessment, and auditing protocols. The automatic techniques currently in use, however, are mostly based on lexical algorithms and often disregard the semantics of the sources being integrated. Results In this paper, we argue that UMLS-Meta’s current design and auditing methodologies could be significantly enhanced by taking into account the logic-based semantics of the ontology sources. We provide empirical evidence suggesting that UMLS-Meta in its 2009AA version contains a significant number of errors; these errors become immediately apparent if the rich semantics of the ontology sources is taken into account, manifesting themselves as unintended logical consequences that follow from the ontology sources together with the information in UMLS-Meta. We then propose general principles and specific logic-based techniques to effectively detect and repair such errors. Conclusions Our results suggest that the methodologies employed in the design of UMLS-Meta are not only very costly in terms of human effort, but also error-prone. The techniques presented here can be useful for both reducing human effort in the design and maintenance of UMLS-Meta and improving the quality of its contents. PMID:21388571

Reasoning by analogy as an aid to heuristic theorem proving.

NASA Technical Reports Server (NTRS)

Kling, R. E.

1972-01-01

When heuristic problem-solving programs are faced with large data bases that contain numbers of facts far in excess of those needed to solve any particular problem, their performance rapidly deteriorates. In this paper, the correspondence between a new unsolved problem and a previously solved analogous problem is computed and invoked to tailor large data bases to manageable sizes. This paper outlines the design of an algorithm for generating and exploiting analogies between theorems posed to a resolution-logic system. These algorithms are believed to be the first computationally feasible development of reasoning by analogy to be applied to heuristic theorem proving.

The continuum fusion theory of signal detection applied to a bi-modal fusion problem

NASA Astrophysics Data System (ADS)

Schaum, A.

2011-05-01

A new formalism has been developed that produces detection algorithms for model-based problems, in which one or more parameter values is unknown. Continuum Fusion can be used to generate different flavors of algorithm for any composite hypothesis testing problem. The methodology is defined by a fusion logic that can be translated into max/min conditions. Here it is applied to a simple sensor fusion model, but one for which the generalized likelihood ratio test is intractable. By contrast, a fusion-based response to the same problem can be devised that is solvable in closed form and represents a good approximation to the GLR test.

FPGA implementation of bit controller in double-tick architecture

NASA Astrophysics Data System (ADS)

Kobylecki, Michał; Kania, Dariusz

2017-11-01

This paper presents a comparison of the two original architectures of programmable bit controllers built on FPGAs. Programmable Logic Controllers (which include, among other things programmable bit controllers) built on FPGAs provide a efficient alternative to the controllers based on microprocessors which are expensive and often too slow. The presented and compared methods allow for the efficient implementation of any bit control algorithm written in Ladder Diagram language into the programmable logic system in accordance with IEC61131-3. In both cases, we have compared the effect of the applied architecture on the performance of executing the same bit control program in relation to its own size.

Industrial Control System Process-Oriented Intrusion Detection (iPoid) Algorithm

DTIC Science & Technology

2016-08-01

inspection rules using an intrusion-detection system (IDS) sensor, a simulated Programmable Logic Controller (PLC), and a Modbus client operating...operating system PLC Programmable Logic Controller SCADA supervisory control and data acquisition SIGHUP signal hangup SPAN Switched Port Analyzer

Design of optical axis jitter control system for multi beam lasers based on FPGA

NASA Astrophysics Data System (ADS)

Ou, Long; Li, Guohui; Xie, Chuanlin; Zhou, Zhiqiang

2018-02-01

A design of optical axis closed-loop control system for multi beam lasers coherent combining based on FPGA was introduced. The system uses piezoelectric ceramics Fast Steering Mirrors (FSM) as actuator, the Fairfield spot detection of multi beam lasers by the high speed CMOS camera for optical detecting, a control system based on FPGA for real-time optical axis jitter suppression. The algorithm for optical axis centroid detecting and PID of anti-Integral saturation were realized by FPGA. Optimize the structure of logic circuit by reuse resource and pipeline, as a result of reducing logic resource but reduced the delay time, and the closed-loop bandwidth increases to 100Hz. The jitter of laser less than 40Hz was reduced 40dB. The cost of the system is low but it works stably.

Robust Deep Semantics for Language Understanding

DTIC Science & Technology

focus on five areas: deep learning, textual inferential relations, relation and event extraction by distant supervision , semantic parsing and...ontology expansion, and coreference resolution. As time went by, the program focus converged towards emphasizing technologies for knowledge base...natural logic methods for text understanding, improved mention coreference algorithms, and the further development of multilingual tools in CoreNLP.

Non Linear Programming (NLP) Formulation for Quantitative Modeling of Protein Signal Transduction Pathways

PubMed Central

Morris, Melody K.; Saez-Rodriguez, Julio; Lauffenburger, Douglas A.; Alexopoulos, Leonidas G.

2012-01-01

Modeling of signal transduction pathways plays a major role in understanding cells' function and predicting cellular response. Mathematical formalisms based on a logic formalism are relatively simple but can describe how signals propagate from one protein to the next and have led to the construction of models that simulate the cells response to environmental or other perturbations. Constrained fuzzy logic was recently introduced to train models to cell specific data to result in quantitative pathway models of the specific cellular behavior. There are two major issues in this pathway optimization: i) excessive CPU time requirements and ii) loosely constrained optimization problem due to lack of data with respect to large signaling pathways. Herein, we address both issues: the former by reformulating the pathway optimization as a regular nonlinear optimization problem; and the latter by enhanced algorithms to pre/post-process the signaling network to remove parts that cannot be identified given the experimental conditions. As a case study, we tackle the construction of cell type specific pathways in normal and transformed hepatocytes using medium and large-scale functional phosphoproteomic datasets. The proposed Non Linear Programming (NLP) formulation allows for fast optimization of signaling topologies by combining the versatile nature of logic modeling with state of the art optimization algorithms. PMID:23226239

Moving code - Sharing geoprocessing logic on the Web

NASA Astrophysics Data System (ADS)

Müller, Matthias; Bernard, Lars; Kadner, Daniel

2013-09-01

Efficient data processing is a long-standing challenge in remote sensing. Effective and efficient algorithms are required for product generation in ground processing systems, event-based or on-demand analysis, environmental monitoring, and data mining. Furthermore, the increasing number of survey missions and the exponentially growing data volume in recent years have created demand for better software reuse as well as an efficient use of scalable processing infrastructures. Solutions that address both demands simultaneously have begun to slowly appear, but they seldom consider the possibility to coordinate development and maintenance efforts across different institutions, community projects, and software vendors. This paper presents a new approach to share, reuse, and possibly standardise geoprocessing logic in the field of remote sensing. Drawing from the principles of service-oriented design and distributed processing, this paper introduces moving-code packages as self-describing software components that contain algorithmic code and machine-readable descriptions of the provided functionality, platform, and infrastructure, as well as basic information about exploitation rights. Furthermore, the paper presents a lean publishing mechanism by which to distribute these packages on the Web and to integrate them in different processing environments ranging from monolithic workstations to elastic computational environments or "clouds". The paper concludes with an outlook toward community repositories for reusable geoprocessing logic and their possible impact on data-driven science in general.

Toshiba General Hospital PACS for routine in- and outpatient clinics

NASA Astrophysics Data System (ADS)

Toshimitsu, Akihiro; Okazaki, Nobuo; Kura, Hiroyuki; Nishihara, Eitaro; Tsubura, Shinichi

1996-05-01

The Toshiba General Hospital introduced a departmental RIS/PACS (Radiology Information System/Picture Archiving and Communication System) in the radiology department in May, 1993. It has been used routinely since that time. In order to provide efficient means for clinicians to find and read many images, the system has been expanded to the neurosurgery and urology clinics and wards since May, 1995, and five image referring workstations now provide digital images to clinicians. In this paper we discuss an algorithm for image migration, one of the key issues to accomplish the expansion to outpatient clinics successfully, and propose the WYWIWYG (what you want is what you get) image transfer logic. This is the logic used to transfer images that physicians require refer without increasing the traffic between the image server and referring workstations. We accomplish the WYWIWYG logic by prioritizing exams the physicians have not yet viewed and by finding historical exams according to the modality, anatomy, and marking. Clinicians gave us comments from their first use of the system and suggested that the PACS enables clinicians to review images more efficiently compared to a film-based system. Our experience suggests that it is a key to the effective application of PACS in outpatient clinics to incorporate consideration patterns of clinicians on the migration algorithm.

Non Linear Programming (NLP) formulation for quantitative modeling of protein signal transduction pathways.

PubMed

Mitsos, Alexander; Melas, Ioannis N; Morris, Melody K; Saez-Rodriguez, Julio; Lauffenburger, Douglas A; Alexopoulos, Leonidas G

2012-01-01

Modeling of signal transduction pathways plays a major role in understanding cells' function and predicting cellular response. Mathematical formalisms based on a logic formalism are relatively simple but can describe how signals propagate from one protein to the next and have led to the construction of models that simulate the cells response to environmental or other perturbations. Constrained fuzzy logic was recently introduced to train models to cell specific data to result in quantitative pathway models of the specific cellular behavior. There are two major issues in this pathway optimization: i) excessive CPU time requirements and ii) loosely constrained optimization problem due to lack of data with respect to large signaling pathways. Herein, we address both issues: the former by reformulating the pathway optimization as a regular nonlinear optimization problem; and the latter by enhanced algorithms to pre/post-process the signaling network to remove parts that cannot be identified given the experimental conditions. As a case study, we tackle the construction of cell type specific pathways in normal and transformed hepatocytes using medium and large-scale functional phosphoproteomic datasets. The proposed Non Linear Programming (NLP) formulation allows for fast optimization of signaling topologies by combining the versatile nature of logic modeling with state of the art optimization algorithms.

Stream-based Hebbian eigenfilter for real-time neuronal spike discrimination

PubMed Central

2012-01-01

Background Principal component analysis (PCA) has been widely employed for automatic neuronal spike sorting. Calculating principal components (PCs) is computationally expensive, and requires complex numerical operations and large memory resources. Substantial hardware resources are therefore needed for hardware implementations of PCA. General Hebbian algorithm (GHA) has been proposed for calculating PCs of neuronal spikes in our previous work, which eliminates the needs of computationally expensive covariance analysis and eigenvalue decomposition in conventional PCA algorithms. However, large memory resources are still inherently required for storing a large volume of aligned spikes for training PCs. The large size memory will consume large hardware resources and contribute significant power dissipation, which make GHA difficult to be implemented in portable or implantable multi-channel recording micro-systems. Method In this paper, we present a new algorithm for PCA-based spike sorting based on GHA, namely stream-based Hebbian eigenfilter, which eliminates the inherent memory requirements of GHA while keeping the accuracy of spike sorting by utilizing the pseudo-stationarity of neuronal spikes. Because of the reduction of large hardware storage requirements, the proposed algorithm can lead to ultra-low hardware resources and power consumption of hardware implementations, which is critical for the future multi-channel micro-systems. Both clinical and synthetic neural recording data sets were employed for evaluating the accuracy of the stream-based Hebbian eigenfilter. The performance of spike sorting using stream-based eigenfilter and the computational complexity of the eigenfilter were rigorously evaluated and compared with conventional PCA algorithms. Field programmable logic arrays (FPGAs) were employed to implement the proposed algorithm, evaluate the hardware implementations and demonstrate the reduction in both power consumption and hardware memories achieved by the streaming computing Results and discussion Results demonstrate that the stream-based eigenfilter can achieve the same accuracy and is 10 times more computationally efficient when compared with conventional PCA algorithms. Hardware evaluations show that 90.3% logic resources, 95.1% power consumption and 86.8% computing latency can be reduced by the stream-based eigenfilter when compared with PCA hardware. By utilizing the streaming method, 92% memory resources and 67% power consumption can be saved when compared with the direct implementation of GHA. Conclusion Stream-based Hebbian eigenfilter presents a novel approach to enable real-time spike sorting with reduced computational complexity and hardware costs. This new design can be further utilized for multi-channel neuro-physiological experiments or chronic implants. PMID:22490725

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

NASA Technical Reports Server (NTRS)

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

1997-01-01

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

Proceedings of the Second Joint Technology Workshop on Neural Networks and Fuzzy Logic, volume 2

NASA Technical Reports Server (NTRS)

Lea, Robert N. (Editor); Villarreal, James A. (Editor)

1991-01-01

Documented here are papers presented at the Neural Networks and Fuzzy Logic Workshop sponsored by NASA and the University of Texas, Houston. Topics addressed included adaptive systems, learning algorithms, network architectures, vision, robotics, neurobiological connections, speech recognition and synthesis, fuzzy set theory and application, control and dynamics processing, space applications, fuzzy logic and neural network computers, approximate reasoning, and multiobject decision making.

Super-Encryption Implementation Using Monoalphabetic Algorithm and XOR Algorithm for Data Security

NASA Astrophysics Data System (ADS)

Rachmawati, Dian; Andri Budiman, Mohammad; Aulia, Indra

2018-03-01

The exchange of data that occurs offline and online is very vulnerable to the threat of data theft. In general, cryptography is a science and art to maintain data secrecy. An encryption is a cryptography algorithm in which data is transformed into cipher text, which is something that is unreadable and meaningless so it cannot be read or understood by other parties. In super-encryption, two or more encryption algorithms are combined to make it more secure. In this work, Monoalphabetic algorithm and XOR algorithm are combined to form a super- encryption. Monoalphabetic algorithm works by changing a particular letter into a new letter based on existing keywords while the XOR algorithm works by using logic operation XOR Since Monoalphabetic algorithm is a classical cryptographic algorithm and XOR algorithm is a modern cryptographic algorithm, this scheme is expected to be both easy-to-implement and more secure. The combination of the two algorithms is capable of securing the data and restoring it back to its original form (plaintext), so the data integrity is still ensured.

Monitoring Programs Using Rewriting

NASA Technical Reports Server (NTRS)

Havelund, Klaus; Rosu, Grigore; Lan, Sonie (Technical Monitor)

2001-01-01

We present a rewriting algorithm for efficiently testing future time Linear Temporal Logic (LTL) formulae on finite execution traces, The standard models of LTL are infinite traces, reflecting the behavior of reactive and concurrent systems which conceptually may be continuously alive in most past applications of LTL, theorem provers and model checkers have been used to formally prove that down-scaled models satisfy such LTL specifications. Our goal is instead to use LTL for up-scaled testing of real software applications, corresponding to analyzing the conformance of finite traces against LTL formulae. We first describe what it means for a finite trace to satisfy an LTL property end then suggest an optimized algorithm based on transforming LTL formulae. We use the Maude rewriting logic, which turns out to be a good notation and being supported by an efficient rewriting engine for performing these experiments. The work constitutes part of the Java PathExplorer (JPAX) project, the purpose of which is to develop a flexible tool for monitoring Java program executions.

Demonstration of an optoelectronic interconnect architecture for a parallel modified signed-digit adder and subtracter

NASA Astrophysics Data System (ADS)

Sun, Degui; Wang, Na-Xin; He, Li-Ming; Weng, Zhao-Heng; Wang, Daheng; Chen, Ray T.

1996-06-01

A space-position-logic-encoding scheme is proposed and demonstrated. This encoding scheme not only makes the best use of the convenience of binary logic operation, but is also suitable for the trinary property of modified signed- digit (MSD) numbers. Based on the space-position-logic-encoding scheme, a fully parallel modified signed-digit adder and subtractor is built using optoelectronic switch technologies in conjunction with fiber-multistage 3D optoelectronic interconnects. Thus an effective combination of a parallel algorithm and a parallel architecture is implemented. In addition, the performance of the optoelectronic switches used in this system is experimentally studied and verified. Both the 3-bit experimental model and the experimental results of a parallel addition and a parallel subtraction are provided and discussed. Finally, the speed ratio between the MSD adder and binary adders is discussed and the advantage of the MSD in operating speed is demonstrated.

A high performance hardware implementation image encryption with AES algorithm

NASA Astrophysics Data System (ADS)

Farmani, Ali; Jafari, Mohamad; Miremadi, Seyed Sohrab

2011-06-01

This paper describes implementation of a high-speed encryption algorithm with high throughput for encrypting the image. Therefore, we select a highly secured symmetric key encryption algorithm AES(Advanced Encryption Standard), in order to increase the speed and throughput using pipeline technique in four stages, control unit based on logic gates, optimal design of multiplier blocks in mixcolumn phase and simultaneous production keys and rounds. Such procedure makes AES suitable for fast image encryption. Implementation of a 128-bit AES on FPGA of Altra company has been done and the results are as follow: throughput, 6 Gbps in 471MHz. The time of encrypting in tested image with 32*32 size is 1.15ms.

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.

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

PubMed

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

2010-09-17

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

Modelling of Robotized Manufacturing Systems Using MultiAgent Formalism

NASA Astrophysics Data System (ADS)

Foit, K.; Gwiazda, A.; Banaś, W.

2016-08-01

The evolution of manufacturing systems has greatly accelerated due to development of sophisticated control systems. On top of determined, one way production flow the need of decision making has arisen as a result of growing product range that are manufactured simultaneously, using the same resources. On the other hand, the intelligent flow control could address the “bottleneck” problem caused by the machine failure. This sort of manufacturing systems uses advanced control algorithms that are introduced by the use of logic controllers. The complex algorithms used in the control systems requires to employ appropriate methods during the modelling process, like the agent-based one, which is the subject of this paper. The concept of an agent is derived from the object-based methodology of modelling, so it meets the requirements of representing the physical properties of the machines as well as the logical form of control systems. Each agent has a high level of autonomy and could be considered separately. The multi-agent system consists of minimum two agents that can interact and modify the environment, where they act. This may lead to the creation of self-organizing structure, what could be interesting feature during design and test of manufacturing system.

Forest fire autonomous decision system based on fuzzy logic

NASA Astrophysics Data System (ADS)

Lei, Z.; Lu, Jianhua

2010-11-01

The proposed system integrates GPS / pseudolite / IMU and thermal camera in order to autonomously process the graphs by identification, extraction, tracking of forest fire or hot spots. The airborne detection platform, the graph-based algorithms and the signal processing frame are analyzed detailed; especially the rules of the decision function are expressed in terms of fuzzy logic, which is an appropriate method to express imprecise knowledge. The membership function and weights of the rules are fixed through a supervised learning process. The perception system in this paper is based on a network of sensorial stations and central stations. The sensorial stations collect data including infrared and visual images and meteorological information. The central stations exchange data to perform distributed analysis. The experiment results show that working procedure of detection system is reasonable and can accurately output the detection alarm and the computation of infrared oscillations.

Algorithms and architecture for multiprocessor based circuit simulation

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

Deutsch, J.T.

Accurate electrical simulation is critical to the design of high performance integrated circuits. Logic simulators can verify function and give first-order timing information. Switch level simulators are more effective at dealing with charge sharing than standard logic simulators, but cannot provide accurate timing information or discover DC problems. Delay estimation techniques and cell level simulation can be used in constrained design methods, but must be tuned for each application, and circuit simulation must still be used to generate the cell models. None of these methods has the guaranteed accuracy that many circuit designers desire, and none can provide detailed waveformmore » information. Detailed electrical-level simulation can predict circuit performance if devices and parasitics are modeled accurately. However, the computational requirements of conventional circuit simulators make it impractical to simulate current large circuits. In this dissertation, the implementation of Iterated Timing Analysis (ITA), a relaxation-based technique for accurate circuit simulation, on a special-purpose multiprocessor is presented. The ITA method is an SOR-Newton, relaxation-based method which uses event-driven analysis and selective trace to exploit the temporal sparsity of the electrical network. Because event-driven selective trace techniques are employed, this algorithm lends itself to implementation on a data-driven computer.« less

Programmable computing with a single magnetoresistive element

NASA Astrophysics Data System (ADS)

Ney, A.; Pampuch, C.; Koch, R.; Ploog, K. H.

2003-10-01

The development of transistor-based integrated circuits for modern computing is a story of great success. However, the proved concept for enhancing computational power by continuous miniaturization is approaching its fundamental limits. Alternative approaches consider logic elements that are reconfigurable at run-time to overcome the rigid architecture of the present hardware systems. Implementation of parallel algorithms on such `chameleon' processors has the potential to yield a dramatic increase of computational speed, competitive with that of supercomputers. Owing to their functional flexibility, `chameleon' processors can be readily optimized with respect to any computer application. In conventional microprocessors, information must be transferred to a memory to prevent it from getting lost, because electrically processed information is volatile. Therefore the computational performance can be improved if the logic gate is additionally capable of storing the output. Here we describe a simple hardware concept for a programmable logic element that is based on a single magnetic random access memory (MRAM) cell. It combines the inherent advantage of a non-volatile output with flexible functionality which can be selected at run-time to operate as an AND, OR, NAND or NOR gate.

Learning and tuning fuzzy logic controllers through reinforcements

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.; Khedkar, Pratap

1992-01-01

This paper presents a new method for learning and tuning a fuzzy logic controller based on reinforcements from a dynamic system. In particular, our generalized approximate reasoning-based intelligent control (GARIC) architecture (1) learns and tunes a fuzzy logic controller even when only weak reinforcement, such as a binary failure signal, is available; (2) introduces a new conjunction operator in computing the rule strengths of fuzzy control rules; (3) introduces a new localized mean of maximum (LMOM) method in combining the conclusions of several firing control rules; and (4) learns to produce real-valued control actions. Learning is achieved by integrating fuzzy inference into a feedforward neural network, which can then adaptively improve performance by using gradient descent methods. We extend the AHC algorithm of Barto et al. (1983) to include the prior control knowledge of human operators. The GARIC architecture is applied to a cart-pole balancing system and demonstrates significant improvements in terms of the speed of learning and robustness to changes in the dynamic system's parameters over previous schemes for cart-pole balancing.

Temporal Specification and Verification of Real-Time Systems.

DTIC Science & Technology

1991-08-30

of concrete real - time systems can be modeled adequately. Specification: We present two conservative extensions of temporal logic that allow for the...logic. We present both model-checking algorithms for the automatic verification of finite-state real - time systems and proof methods for the deductive verification of real - time systems .

Fuzzy logic techniques for rendezvous and docking of two geostationary satellites

NASA Technical Reports Server (NTRS)

Ortega, Guillermo

1995-01-01

Large assemblings in space require the ability to manage rendezvous and docking operations. In future these techniques will be required for the gradual build up of big telecommunication platforms in the geostationary orbit. The paper discusses the use of fuzzy logic to model and implement a control system for the docking/berthing of two satellites in geostationary orbit. The system mounted in a chaser vehicle determines the actual state of both satellites and generates torques to execute maneuvers to establish the structural latching. The paper describes the proximity operations to collocate the two satellites in the same orbital window, the fuzzy guidance and navigation of the chaser approaching the target and the final Fuzzy berthing. The fuzzy logic system represents a knowledge based controller that realizes the close loop operations autonomously replacing the conventional control algorithms. The goal is to produce smooth control actions in the proximity of the target and during the docking to avoid disturbance torques in the final assembly orbit. The knowledge of the fuzzy controller consists of a data base of rules and the definitions of the fuzzy sets. The knowledge of an experienced spacecraft controller is captured into a set of rules forming the Rules Data Base.

Boolean network identification from perturbation time series data combining dynamics abstraction and logic programming.

PubMed

Ostrowski, M; Paulevé, L; Schaub, T; Siegel, A; Guziolowski, C

2016-11-01

Boolean networks (and more general logic models) are useful frameworks to study signal transduction across multiple pathways. Logic models can be learned from a prior knowledge network structure and multiplex phosphoproteomics data. However, most efficient and scalable training methods focus on the comparison of two time-points and assume that the system has reached an early steady state. In this paper, we generalize such a learning procedure to take into account the time series traces of phosphoproteomics data in order to discriminate Boolean networks according to their transient dynamics. To that end, we identify a necessary condition that must be satisfied by the dynamics of a Boolean network to be consistent with a discretized time series trace. Based on this condition, we use Answer Set Programming to compute an over-approximation of the set of Boolean networks which fit best with experimental data and provide the corresponding encodings. Combined with model-checking approaches, we end up with a global learning algorithm. Our approach is able to learn logic models with a true positive rate higher than 78% in two case studies of mammalian signaling networks; for a larger case study, our method provides optimal answers after 7min of computation. We quantified the gain in our method predictions precision compared to learning approaches based on static data. Finally, as an application, our method proposes erroneous time-points in the time series data with respect to the optimal learned logic models. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Application of ANN and fuzzy logic algorithms for streamflow modelling of Savitri catchment

NASA Astrophysics Data System (ADS)

Kothari, Mahesh; Gharde, K. D.

2015-07-01

The streamflow prediction is an essentially important aspect of any watershed modelling. The black box models (soft computing techniques) have proven to be an efficient alternative to physical (traditional) methods for simulating streamflow and sediment yield of the catchments. The present study focusses on development of models using ANN and fuzzy logic (FL) algorithm for predicting the streamflow for catchment of Savitri River Basin. The input vector to these models were daily rainfall, mean daily evaporation, mean daily temperature and lag streamflow used. In the present study, 20 years (1992-2011) rainfall and other hydrological data were considered, of which 13 years (1992-2004) was for training and rest 7 years (2005-2011) for validation of the models. The mode performance was evaluated by R, RMSE, EV, CE, and MAD statistical parameters. It was found that, ANN model performance improved with increasing input vectors. The results with fuzzy logic models predict the streamflow with single input as rainfall better in comparison to multiple input vectors. While comparing both ANN and FL algorithms for prediction of streamflow, ANN model performance is quite superior.

A critical analysis of the internal logic in the Life-Space Assessment (LSA) composite score and suggested solutions.

PubMed

Siordia, Carlos

2016-06-01

An individual's ability to live independently is commonly measured in health research interested in identifying risk factors associated with disablement processes. In order to inform clinical practice, population research has attempted to identify the contraction of "lived-space" by using various survey instruments. Studies assessing habitual movements over the environment with the Life-Space Assessment (LSA) survey instrument should carefully consider how the LSA Composite Score (LSA-CS) is computed. Until now, no publication has carefully delineated the assumptions guiding the internal logic used in the computation of the LSA-CS. Because the internal logic of the LSA may need further justification, a non-data-editing scoring algorithm should be considered. Compute LSA-CS by only using non-edited data. Paper first delineates the logic guiding the algorithm used in the formation of the LSA-CS and explains how the scoring creates and changes participant responses when they conflict with its internal logic. An easy-to-use SAS® 9.3 program for estimating a Non-Data-Edited LSA-CS (NDE-LSA-CS) is also presented. Researchers interested in assessing lived-space should carefully consider if the internal logic of the LSA-CS is warranted. Clinicians should know it is important to understand the strengths and weaknesses of outcome measures used when deciding on whether to apply the results of research to direct clinical practice. © The Author(s) 2015.

Measure Landscape Diversity with Logical Scout Agents

NASA Astrophysics Data System (ADS)

Wirth, E.; Szabó, G.; Czinkóczky, A.

2016-06-01

The Common Agricultural Policy reform of the EU focuses on three long-term objectives: viable food production, sustainable management of natural resources and climate action with balanced territorial development. To achieve these goals, the EU farming and subsidizing policies (EEA, 2014) support landscape heterogeneity and diversity. Current paper introduces an agent-based method to calculate the potential of landscape diversity. The method tries to catch the nature of heterogeneity using logic and modelling as opposed to the traditional statistical reasoning. The outlined Random Walk Scouting algorithm registers the land cover crossings of the scout agents to a Monte Carlo integral. The potential is proportional with the composition and the configuration (spatial character) of the landscape. Based on the measured points a potential map is derived to give an objective and quantitative basis to the stakeholders (policy makers, farmers).

Exploring the Feasibility of a DNA Computer: Design of an ALU Using Sticker-Based DNA Model.

PubMed

Sarkar, Mayukh; Ghosal, Prasun; Mohanty, Saraju P

2017-09-01

Since its inception, DNA computing has advanced to offer an extremely powerful, energy-efficient emerging technology for solving hard computational problems with its inherent massive parallelism and extremely high data density. This would be much more powerful and general purpose when combined with other existing well-known algorithmic solutions that exist for conventional computing architectures using a suitable ALU. Thus, a specifically designed DNA Arithmetic and Logic Unit (ALU) that can address operations suitable for both domains can mitigate the gap between these two. An ALU must be able to perform all possible logic operations, including NOT, OR, AND, XOR, NOR, NAND, and XNOR; compare, shift etc., integer and floating point arithmetic operations (addition, subtraction, multiplication, and division). In this paper, design of an ALU has been proposed using sticker-based DNA model with experimental feasibility analysis. Novelties of this paper may be in manifold. First, the integer arithmetic operations performed here are 2s complement arithmetic, and the floating point operations follow the IEEE 754 floating point format, resembling closely to a conventional ALU. Also, the output of each operation can be reused for any next operation. So any algorithm or program logic that users can think of can be implemented directly on the DNA computer without any modification. Second, once the basic operations of sticker model can be automated, the implementations proposed in this paper become highly suitable to design a fully automated ALU. Third, proposed approaches are easy to implement. Finally, these approaches can work on sufficiently large binary numbers.

A technology mapping based on graph of excitations and outputs for finite state machines

NASA Astrophysics Data System (ADS)

Kania, Dariusz; Kulisz, Józef

2017-11-01

A new, efficient technology mapping method of FSMs, dedicated for PAL-based PLDs is proposed. The essence of the method consists in searching for the minimal set of PAL-based logic blocks that cover a set of multiple-output implicants describing the transition and output functions of an FSM. The method is based on a new concept of graph: the Graph of Excitations and Outputs. The proposed algorithm was tested using the FSM benchmarks. The obtained results were compared with the classical technology mapping of FSM.

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

PubMed Central

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

2015-01-01

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

Design of physical and logical topologies with fault-tolerant ability in wavelength-routed optical network

NASA Astrophysics Data System (ADS)

Chen, Chunfeng; Liu, Hua; Fan, Ge

2005-02-01

In this paper we consider the problem of designing a network of optical cross-connects(OXCs) to provide end-to-end lightpath services to label switched routers (LSRs). Like some previous work, we select the number of OXCs as our objective. Compared with the previous studies, we take into account the fault-tolerant characteristic of logical topology. First of all, using a Prufer number randomly generated, we generate a tree. By adding some edges to the tree, we can obtain a physical topology which consists of a certain number of OXCs and fiber links connecting OXCs. It is notable that we for the first time limit the number of layers of the tree produced according to the method mentioned above. Then we design the logical topologies based on the physical topologies mentioned above. In principle, we will select the shortest path in addition to some consideration on the load balancing of links and the limitation owing to the SRLG. Notably, we implement the routing algorithm for the nodes in increasing order of the degree of the nodes. With regarding to the problem of the wavelength assignment, we adopt the heuristic algorithm of the graph coloring commonly used. It is clear our problem is computationally intractable especially when the scale of the network is large. We adopt the taboo search algorithm to find the near optimal solution to our objective. We present numerical results for up to 1000 LSRs and for a wide range of system parameters such as the number of wavelengths supported by each fiber link and traffic. The results indicate that it is possible to build large-scale optical networks with rich connectivity in a cost-effective manner, using relatively few but properly dimensioned OXCs.

Monitoring and control of the biogas process based on propionate concentration using online VFA measurement.

PubMed

Boe, Kanokwan; Steyer, Jean-Philippe; Angelidaki, Irini

2008-01-01

Simple logic control algorithms were tested for automatic control of a lab-scale CSTR manure digester. Using an online VFA monitoring system, propionate concentration in the reactor was used as parameter for control of the biogas process. The propionate concentration was kept below a threshold of 10 mM by manipulating the feed flow. Other online parameters such as pH, biogas production, total VFA, and other individual VFA were also measured to examine process performance. The experimental results showed that a simple logic control can successfully prevent the reactor from overload, but with fluctuations of the propionate level due to the nature of control approach. The fluctuation of propionate concentration could be reduced, by adding a lower feed flow limit into the control algorithm to prevent undershooting of propionate response. It was found that use of the biogas production as a main control parameter, rather than propionate can give a more stable process, since propionate was very persistent and only responded very slowly to the decrease of the feed flow which lead to high fluctuation of biogas production. Propionate, however, was still an excellent parameter to indicate process stress under gradual overload and thus recommended as an alarm in the control algorithm. Copyright IWA Publishing 2008.

Study on some useful Operators for Graph-theoretic Image Processing

NASA Astrophysics Data System (ADS)

Moghani, Ali; Nasiri, Parviz

2010-11-01

In this paper we describe a human perception based approach to pixel color segmentation which applied in color reconstruction by numerical method associated with graph-theoretic image processing algorithm typically in grayscale. Fuzzy sets defined on the Hue, Saturation and Value components of the HSV color space, provide a fuzzy logic model that aims to follow the human intuition of color classification.

Evidence for an inhibitory-control theory of the reasoning brain.

PubMed

Houdé, Olivier; Borst, Grégoire

2015-01-01

In this article, we first describe our general inhibitory-control theory and, then, we describe how we have tested its specific hypotheses on reasoning with brain imaging techniques in adults and children. The innovative part of this perspective lies in its attempt to come up with a brain-based synthesis of Jean Piaget's theory on logical algorithms and Daniel Kahneman's theory on intuitive heuristics.

Development of an integrated spacecraft Guidance, Navigation, & Control subsystem for automated proximity operations

NASA Astrophysics Data System (ADS)

Schulte, Peter Z.; Spencer, David A.

2016-01-01

This paper describes the development and validation process of a highly automated Guidance, Navigation, & Control subsystem for a small satellite on-orbit inspection application, enabling proximity operations without human-in-the-loop interaction. The paper focuses on the integration and testing of Guidance, Navigation, & Control software and the development of decision logic to address the question of how such a system can be effectively implemented for full automation. This process is unique because a multitude of operational scenarios must be considered and a set of complex interactions between subsystem algorithms must be defined to achieve the automation goal. The Prox-1 mission is currently under development within the Space Systems Design Laboratory at the Georgia Institute of Technology. The mission involves the characterization of new small satellite component technologies, deployment of the LightSail 3U CubeSat, entering into a trailing orbit relative to LightSail using ground-in-the-loop commands, and demonstration of automated proximity operations through formation flight and natural motion circumnavigation maneuvers. Operations such as these may be utilized for many scenarios including on-orbit inspection, refueling, repair, construction, reconnaissance, docking, and debris mitigation activities. Prox-1 uses onboard sensors and imaging instruments to perform Guidance, Navigation, & Control operations during on-orbit inspection of LightSail. Navigation filters perform relative orbit determination based on images of the target spacecraft, and guidance algorithms conduct automated maneuver planning. A slew and tracking controller sends attitude actuation commands to a set of control moment gyroscopes, and other controllers manage desaturation, detumble, thruster firing, and target acquisition/recovery. All Guidance, Navigation, & Control algorithms are developed in a MATLAB/Simulink six degree-of-freedom simulation environment and are integrated using decision logic to autonomously determine when actions should be performed. The complexity of this decision logic is the primary challenge of the automated process, and the Stateflow tool in Simulink is used to establish logical relationships and manage data flow between each of the individual hardware and software components. Once the integrated simulation is fully developed in MATLAB/Simulink, the algorithms are autocoded to C/C++ and integrated into flight software. Hardware-in-the-loop testing provides validation of the Guidance, Navigation, & Control subsystem performance.

Lattice surgery on the Raussendorf lattice

NASA Astrophysics Data System (ADS)

Herr, Daniel; Paler, Alexandru; Devitt, Simon J.; Nori, Franco

2018-07-01

Lattice surgery is a method to perform quantum computation fault-tolerantly by using operations on boundary qubits between different patches of the planar code. This technique allows for universal planar code computation without eliminating the intrinsic two-dimensional nearest-neighbor properties of the surface code that eases physical hardware implementations. Lattice surgery approaches to algorithmic compilation and optimization have been demonstrated to be more resource efficient for resource-intensive components of a fault-tolerant algorithm, and consequently may be preferable over braid-based logic. Lattice surgery can be extended to the Raussendorf lattice, providing a measurement-based approach to the surface code. In this paper we describe how lattice surgery can be performed on the Raussendorf lattice and therefore give a viable alternative to computation using braiding in measurement-based implementations of topological codes.

Multi-variants synthesis of Petri nets for FPGA devices

NASA Astrophysics Data System (ADS)

Bukowiec, Arkadiusz; Doligalski, Michał

2015-09-01

There is presented new method of synthesis of application specific logic controllers for FPGA devices. The specification of control algorithm is made with use of control interpreted Petri net (PT type). It allows specifying parallel processes in easy way. The Petri net is decomposed into state-machine type subnets. In this case, each subnet represents one parallel process. For this purpose there are applied algorithms of coloring of Petri nets. There are presented two approaches of such decomposition: with doublers of macroplaces or with one global wait place. Next, subnets are implemented into two-level logic circuit of the controller. The levels of logic circuit are obtained as a result of its architectural decomposition. The first level combinational circuit is responsible for generation of next places and second level decoder is responsible for generation output symbols. There are worked out two variants of such circuits: with one shared operational memory or with many flexible distributed memories as a decoder. Variants of Petri net decomposition and structures of logic circuits can be combined together without any restrictions. It leads to existence of four variants of multi-variants synthesis.

Proceedings of the Second Joint Technology Workshop on Neural Networks and Fuzzy Logic, volume 1

NASA Technical Reports Server (NTRS)

Lea, Robert N. (Editor); Villarreal, James (Editor)

1991-01-01

Documented here are papers presented at the Neural Networks and Fuzzy Logic Workshop sponsored by NASA and the University of Houston, Clear Lake. The workshop was held April 11 to 13 at the Johnson Space Flight Center. Technical topics addressed included adaptive systems, learning algorithms, network architectures, vision, robotics, neurobiological connections, speech recognition and synthesis, fuzzy set theory and application, control and dynamics processing, space applications, fuzzy logic and neural network computers, approximate reasoning, and multiobject decision making.

Complex scenes and situations visualization in hierarchical learning algorithm with dynamic 3D NeoAxis engine

NASA Astrophysics Data System (ADS)

Graham, James; Ternovskiy, Igor V.

2013-06-01

We applied a two stage unsupervised hierarchical learning system to model complex dynamic surveillance and cyber space monitoring systems using a non-commercial version of the NeoAxis visualization software. The hierarchical scene learning and recognition approach is based on hierarchical expectation maximization, and was linked to a 3D graphics engine for validation of learning and classification results and understanding the human - autonomous system relationship. Scene recognition is performed by taking synthetically generated data and feeding it to a dynamic logic algorithm. The algorithm performs hierarchical recognition of the scene by first examining the features of the objects to determine which objects are present, and then determines the scene based on the objects present. This paper presents a framework within which low level data linked to higher-level visualization can provide support to a human operator and be evaluated in a detailed and systematic way.

A TCAS-II Resolution Advisory Detection Algorithm

NASA Technical Reports Server (NTRS)

Munoz, Cesar; Narkawicz, Anthony; Chamberlain, James

2013-01-01

The Traffic Alert and Collision Avoidance System (TCAS) is a family of airborne systems designed to reduce the risk of mid-air collisions between aircraft. TCASII, the current generation of TCAS devices, provides resolution advisories that direct pilots to maintain or increase vertical separation when aircraft distance and time parameters are beyond designed system thresholds. This paper presents a mathematical model of the TCASII Resolution Advisory (RA) logic that assumes accurate aircraft state information. Based on this model, an algorithm for RA detection is also presented. This algorithm is analogous to a conflict detection algorithm, but instead of predicting loss of separation, it predicts resolution advisories. It has been formally verified that for a kinematic model of aircraft trajectories, this algorithm completely and correctly characterizes all encounter geometries between two aircraft that lead to a resolution advisory within a given lookahead time interval. The RA detection algorithm proposed in this paper is a fundamental component of a NASA sense and avoid concept for the integration of Unmanned Aircraft Systems in civil airspace.

A Reversible Logical Circuit Synthesis Algorithm Based on Decomposition of Cycle Representations of Permutations

NASA Astrophysics Data System (ADS)

Zhu, Wei; Li, Zhiqiang; Zhang, Gaoman; Pan, Suhan; Zhang, Wei

2018-05-01

A reversible function is isomorphic to a permutation and an arbitrary permutation can be represented by a series of cycles. A new synthesis algorithm for 3-qubit reversible circuits was presented. It consists of two parts, the first part used the Number of reversible function's Different Bits (NDBs) to decide whether the NOT gate should be added to decrease the Hamming distance of the input and output vectors; the second part was based on the idea of exploring properties of the cycle representation of permutations, decomposed the cycles to make the permutation closer to the identity permutation and finally turn into the identity permutation, it was realized by using totally controlled Toffoli gates with positive and negative controls.

Maximum power point tracking algorithm based on sliding mode and fuzzy logic for photovoltaic sources under variable environmental conditions

NASA Astrophysics Data System (ADS)

Atik, L.; Petit, P.; Sawicki, J. P.; Ternifi, Z. T.; Bachir, G.; Della, M.; Aillerie, M.

2017-02-01

Solar panels have a nonlinear voltage-current characteristic, with a distinct maximum power point (MPP), which depends on the environmental factors, such as temperature and irradiation. In order to continuously harvest maximum power from the solar panels, they have to operate at their MPP despite the inevitable changes in the environment. Various methods for maximum power point tracking (MPPT) were developed and finally implemented in solar power electronic controllers to increase the efficiency in the electricity production originate from renewables. In this paper we compare using Matlab tools Simulink, two different MPP tracking methods, which are, fuzzy logic control (FL) and sliding mode control (SMC), considering their efficiency in solar energy production.

Modal Logics with Counting

NASA Astrophysics Data System (ADS)

Areces, Carlos; Hoffmann, Guillaume; Denis, Alexandre

We present a modal language that includes explicit operators to count the number of elements that a model might include in the extension of a formula, and we discuss how this logic has been previously investigated under different guises. We show that the language is related to graded modalities and to hybrid logics. We illustrate a possible application of the language to the treatment of plural objects and queries in natural language. We investigate the expressive power of this logic via bisimulations, discuss the complexity of its satisfiability problem, define a new reasoning task that retrieves the cardinality bound of the extension of a given input formula, and provide an algorithm to solve it.

Data Mining and Privacy of Social Network Sites' Users: Implications of the Data Mining Problem.

PubMed

Al-Saggaf, Yeslam; Islam, Md Zahidul

2015-08-01

This paper explores the potential of data mining as a technique that could be used by malicious data miners to threaten the privacy of social network sites (SNS) users. It applies a data mining algorithm to a real dataset to provide empirically-based evidence of the ease with which characteristics about the SNS users can be discovered and used in a way that could invade their privacy. One major contribution of this article is the use of the decision forest data mining algorithm (SysFor) to the context of SNS, which does not only build a decision tree but rather a forest allowing the exploration of more logic rules from a dataset. One logic rule that SysFor built in this study, for example, revealed that anyone having a profile picture showing just the face or a picture showing a family is less likely to be lonely. Another contribution of this article is the discussion of the implications of the data mining problem for governments, businesses, developers and the SNS users themselves.

A Mechanism of Modeling and Verification for SaaS Customization Based on TLA

NASA Astrophysics Data System (ADS)

Luan, Shuai; Shi, Yuliang; Wang, Haiyang

With the gradually mature of SOA and the rapid development of Internet, SaaS has become a popular software service mode. The customized action of SaaS is usually subject to internal and external dependency relationships. This paper first introduces a method for modeling customization process based on Temporal Logic of Actions, and then proposes a verification algorithm to assure that each step in customization will not cause unpredictable influence on system and follow the related rules defined by SaaS provider.

Prosthetic joint infection development of an evidence-based diagnostic algorithm.

PubMed

Mühlhofer, Heinrich M L; Pohlig, Florian; Kanz, Karl-Georg; Lenze, Ulrich; Lenze, Florian; Toepfer, Andreas; Kelch, Sarah; Harrasser, Norbert; von Eisenhart-Rothe, Rüdiger; Schauwecker, Johannes

2017-03-09

Increasing rates of prosthetic joint infection (PJI) have presented challenges for general practitioners, orthopedic surgeons and the health care system in the recent years. The diagnosis of PJI is complex; multiple diagnostic tools are used in the attempt to correctly diagnose PJI. Evidence-based algorithms can help to identify PJI using standardized diagnostic steps. We reviewed relevant publications between 1990 and 2015 using a systematic literature search in MEDLINE and PUBMED. The selected search results were then classified into levels of evidence. The keywords were prosthetic joint infection, biofilm, diagnosis, sonication, antibiotic treatment, implant-associated infection, Staph. aureus, rifampicin, implant retention, pcr, maldi-tof, serology, synovial fluid, c-reactive protein level, total hip arthroplasty (THA), total knee arthroplasty (TKA) and combinations of these terms. From an initial 768 publications, 156 publications were stringently reviewed. Publications with class I-III recommendations (EAST) were considered. We developed an algorithm for the diagnostic approach to display the complex diagnosis of PJI in a clear and logically structured process according to ISO 5807. The evidence-based standardized algorithm combines modern clinical requirements and evidence-based treatment principles. The algorithm provides a detailed transparent standard operating procedure (SOP) for diagnosing PJI. Thus, consistently high, examiner-independent process quality is assured to meet the demands of modern quality management in PJI diagnosis.

Crystal Identification in Dual-Layer-Offset DOI-PET Detectors Using Stratified Peak Tracking Based on SVD and Mean-Shift Algorithm

NASA Astrophysics Data System (ADS)

Wei, Qingyang; Dai, Tiantian; Ma, Tianyu; Liu, Yaqiang; Gu, Yu

2016-10-01

An Anger-logic based pixelated PET detector block requires a crystal position map (CPM) to assign the position of each detected event to a most probable crystal index. Accurate assignments are crucial to PET imaging performance. In this paper, we present a novel automatic approach to generate the CPMs for dual-layer offset (DLO) PET detectors using a stratified peak tracking method. In which, the top and bottom layers are distinguished by their intensity difference and the peaks of the top and bottom layers are tracked based on a singular value decomposition (SVD) and mean-shift algorithm in succession. The CPM is created by classifying each pixel to its nearest peak and assigning the pixel with the crystal index of that peak. A Matlab-based graphical user interface program was developed including the automatic algorithm and a manual interaction procedure. The algorithm was tested for three DLO PET detector blocks. Results show that the proposed method exhibits good performance as well as robustness for all the three blocks. Compared to the existing methods, our approach can directly distinguish the layer and crystal indices using the information of intensity and offset grid pattern.

On the fusion of tuning parameters of fuzzy rules and neural network

NASA Astrophysics Data System (ADS)

Mamuda, Mamman; Sathasivam, Saratha

2017-08-01

Learning fuzzy rule-based system with neural network can lead to a precise valuable empathy of several problems. Fuzzy logic offers a simple way to reach at a definite conclusion based upon its vague, ambiguous, imprecise, noisy or missing input information. Conventional learning algorithm for tuning parameters of fuzzy rules using training input-output data usually end in a weak firing state, this certainly powers the fuzzy rule and makes it insecure for a multiple-input fuzzy system. In this paper, we introduce a new learning algorithm for tuning the parameters of the fuzzy rules alongside with radial basis function neural network (RBFNN) in training input-output data based on the gradient descent method. By the new learning algorithm, the problem of weak firing using the conventional method was addressed. We illustrated the efficiency of our new learning algorithm by means of numerical examples. MATLAB R2014(a) software was used in simulating our result The result shows that the new learning method has the best advantage of training the fuzzy rules without tempering with the fuzzy rule table which allowed a membership function of the rule to be used more than one time in the fuzzy rule base.

Obtaining ABET Student Outcome Satisfaction from Course Learning Outcome Data Using Fuzzy Logic

ERIC Educational Resources Information Center

Imam, Muhammad Hasan; Tasadduq, Imran Ali; Ahmad, Abdul-Rahim; Aldosari, Fahd

2017-01-01

One of the approaches for obtaining the satisfaction data for ABET "Student Outcomes" (SOs) is to transform Course Learning Outcomes (CLOs) satisfaction data obtained through assessment of CLOs to SO satisfaction data. Considering the fuzzy nature of metrics of CLOs and SOs, a Fuzzy Logic algorithm has been proposed to extract SO…

A low power, area efficient fpga based beamforming technique for 1-D CMUT arrays.

PubMed

Joseph, Bastin; Joseph, Jose; Vanjari, Siva Rama Krishna

2015-08-01

A low power area efficient digital beamformer targeting low frequency (2MHz) 1-D linear Capacitive Micromachined Ultrasonic Transducer (CMUT) array is developed. While designing the beamforming logic, the symmetry of the CMUT array is well exploited to reduce the area and power consumption. The proposed method is verified in Matlab by clocking an Arbitrary Waveform Generator(AWG). The architecture is successfully implemented in Xilinx Spartan 3E FPGA kit to check its functionality. The beamforming logic is implemented for 8, 16, 32, and 64 element CMUTs targeting Application Specific Integrated Circuit (ASIC) platform at Vdd 1.62V for UMC 90nm technology. It is observed that the proposed architecture consumes significantly lesser power and area (1.2895 mW power and 47134.4 μm(2) area for a 64 element digital beamforming circuit) compared to the conventional square root based algorithm.

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%.

Electric Motors Maintenance Planning From Its Operating Variables

NASA Astrophysics Data System (ADS)

Rodrigues, Francisco; Fonseca, Inácio; Farinha, José Torres; Ferreira, Luís; Galar, Diego

2017-09-01

The maintenance planning corresponds to an approach that seeks to maximize the availability of equipment and, consequently, increase the levels of competitiveness of companies by increasing production times. This paper presents a maintenance planning based on operating variables (number of hours worked, duty cycles, number of revolutions) to maximizing the availability of operation of electrical motors. The reading of the operating variables and its sampling is done based on predetermined sampling cycles and subsequently is made the data analysis through time series algorithms aiming to launch work orders before reaching the variables limit values. This approach is supported by tools and technologies such as logical applications that enable a graphical user interface for access to relevant information about their Physical Asset HMI (Human Machine Interface), including the control and supervision by acquisition through SCADA (Supervisory Control And data acquisition) data, also including the communication protocols among different logical applications.

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.

Evidence for an inhibitory-control theory of the reasoning brain

PubMed Central

Houdé, Olivier; Borst, Grégoire

2015-01-01

In this article, we first describe our general inhibitory-control theory and, then, we describe how we have tested its specific hypotheses on reasoning with brain imaging techniques in adults and children. The innovative part of this perspective lies in its attempt to come up with a brain-based synthesis of Jean Piaget’s theory on logical algorithms and Daniel Kahneman’s theory on intuitive heuristics. PMID:25852528

Investigation, Development, and Evaluation of Performance Proving for Fault-tolerant Computers

NASA Technical Reports Server (NTRS)

Levitt, K. N.; Schwartz, R.; Hare, D.; Moore, J. S.; Melliar-Smith, P. M.; Shostak, R. E.; Boyer, R. S.; Green, M. W.; Elliott, W. D.

1983-01-01

A number of methodologies for verifying systems and computer based tools that assist users in verifying their systems were developed. These tools were applied to verify in part the SIFT ultrareliable aircraft computer. Topics covered included: STP theorem prover; design verification of SIFT; high level language code verification; assembly language level verification; numerical algorithm verification; verification of flight control programs; and verification of hardware logic.

Prediction system of hydroponic plant growth and development using algorithm Fuzzy Mamdani method

NASA Astrophysics Data System (ADS)

Sudana, I. Made; Purnawirawan, Okta; Arief, Ulfa Mediaty

2017-03-01

Hydroponics is a method of farming without soil. One of the Hydroponic plants is Watercress (Nasturtium Officinale). The development and growth process of hydroponic Watercress was influenced by levels of nutrients, acidity and temperature. The independent variables can be used as input variable system to predict the value level of plants growth and development. The prediction system is using Fuzzy Algorithm Mamdani method. This system was built to implement the function of Fuzzy Inference System (Fuzzy Inference System/FIS) as a part of the Fuzzy Logic Toolbox (FLT) by using MATLAB R2007b. FIS is a computing system that works on the principle of fuzzy reasoning which is similar to humans' reasoning. Basically FIS consists of four units which are fuzzification unit, fuzzy logic reasoning unit, base knowledge unit and defuzzification unit. In addition to know the effect of independent variables on the plants growth and development that can be visualized with the function diagram of FIS output surface that is shaped three-dimensional, and statistical tests based on the data from the prediction system using multiple linear regression method, which includes multiple linear regression analysis, T test, F test, the coefficient of determination and donations predictor that are calculated using SPSS (Statistical Product and Service Solutions) software applications.

Maximum power point tracking techniques for wind energy systems using three levels boost converter

NASA Astrophysics Data System (ADS)

Tran, Cuong Hung; Nollet, Frédéric; Essounbouli, Najib; Hamzaoui, Abdelaziz

2018-05-01

This paper presents modeling and simulation of three level Boost DC-DC converter in Wind Energy Conversion System (WECS). Three-level Boost converter has significant advantage compared to conventional Boost. A maximum power point tracking (MPPT) method for a variable speed wind turbine using permanent magnet synchronous generator (PMSG) is also presented. Simulation of three-level Boost converter topology with Perturb and Observe algorithm and Fuzzy Logic Control is implemented in MATLAB/SIMULINK. Results of this simulation show that the system with MPPT using fuzzy logic controller has better performance to the Perturb and Observe algorithm: fast response under changing conditions and small oscillation.

Logical account of a terminological tool

NASA Astrophysics Data System (ADS)

Bresciani, Paolo

1991-03-01

YAK (Yet Another Krapfen) is a hybrid knowledge representation environment following the tradition of KL-ONE and KRYPTON. In its terminological box (TBOX) concepts and roles are described by means of a language called KFL that, even if inspired to FL-, captures a different set of descriptions, especially allowing the formulation of structured roles, that are aimed to be more adequate for the representational goal. KFL results to have a valid and complete calculus for the notion of subsumption, and a tractable algorithm that realize it is available. In the present paper it is shown how the semantics of a sufficiently significative subset of KFL can be described in terms of standard first order logic semantics. It is so possible to develop a notion of 'relation' between KFL and a full first order logic language formulated ad hoc and usable as formalization of an assertional box (ABOX). We then use this notion to justify the use of the terminological classification algorithm of the TBOX of YAK as part of the deduction machinery of the ABOX. In this way, the whole hybrid environment can take real and consistent advantages both from the TBOX and its tractable classification algorithm, and from the ABOX, and its wider expressive capability.

Eigensolution of finite element problems in a completely connected parallel architecture

NASA Technical Reports Server (NTRS)

Akl, F.; Morel, M.

1989-01-01

A parallel algorithm is presented for the solution of the generalized eigenproblem in linear elastic finite element analysis. The algorithm is based on a completely connected parallel architecture in which each processor is allowed to communicate with all other processors. The algorithm is successfully implemented on a tightly coupled MIMD parallel processor. A finite element model is divided into m domains each of which is assumed to process n elements. Each domain is then assigned to a processor or to a logical processor (task) if the number of domains exceeds the number of physical processors. The effect of the number of domains, the number of degrees-of-freedom located along the global fronts, and the dimension of the subspace on the performance of the algorithm is investigated. For a 64-element rectangular plate, speed-ups of 1.86, 3.13, 3.18, and 3.61 are achieved on two, four, six, and eight processors, respectively.

Experimental realization of a one-way quantum computer algorithm solving Simon's problem.

PubMed

Tame, M S; Bell, B A; Di Franco, C; Wadsworth, W J; Rarity, J G

2014-11-14

We report an experimental demonstration of a one-way implementation of a quantum algorithm solving Simon's problem-a black-box period-finding problem that has an exponential gap between the classical and quantum runtime. Using an all-optical setup and modifying the bases of single-qubit measurements on a five-qubit cluster state, key representative functions of the logical two-qubit version's black box can be queried and solved. To the best of our knowledge, this work represents the first experimental realization of the quantum algorithm solving Simon's problem. The experimental results are in excellent agreement with the theoretical model, demonstrating the successful performance of the algorithm. With a view to scaling up to larger numbers of qubits, we analyze the resource requirements for an n-qubit version. This work helps highlight how one-way quantum computing provides a practical route to experimentally investigating the quantum-classical gap in the query complexity model.

VLSI architectures for computing multiplications and inverses in GF(2m)

NASA Technical Reports Server (NTRS)

Wang, C. C.; Truong, T. K.; Shao, H. M.; Deutsch, L. J.; Omura, J. K.

1985-01-01

Finite field arithmetic logic is central in the implementation of Reed-Solomon coders and in some cryptographic algorithms. There is a need for good multiplication and inversion algorithms that are easily realized on VLSI chips. Massey and Omura recently developed a new multiplication algorithm for Galois fields based on a normal basis representation. A pipeline structure is developed to realize the Massey-Omura multiplier in the finite field GF(2m). With the simple squaring property of the normal-basis representation used together with this multiplier, a pipeline architecture is also developed for computing inverse elements in GF(2m). The designs developed for the Massey-Omura multiplier and the computation of inverse elements are regular, simple, expandable and, therefore, naturally suitable for VLSI implementation.

VLSI architectures for computing multiplications and inverses in GF(2-m)

NASA Technical Reports Server (NTRS)

Wang, C. C.; Truong, T. K.; Shao, H. M.; Deutsch, L. J.; Omura, J. K.; Reed, I. S.

1983-01-01

Finite field arithmetic logic is central in the implementation of Reed-Solomon coders and in some cryptographic algorithms. There is a need for good multiplication and inversion algorithms that are easily realized on VLSI chips. Massey and Omura recently developed a new multiplication algorithm for Galois fields based on a normal basis representation. A pipeline structure is developed to realize the Massey-Omura multiplier in the finite field GF(2m). With the simple squaring property of the normal-basis representation used together with this multiplier, a pipeline architecture is also developed for computing inverse elements in GF(2m). The designs developed for the Massey-Omura multiplier and the computation of inverse elements are regular, simple, expandable and, therefore, naturally suitable for VLSI implementation.

Predictive Lateral Logic for Numerical Entry Guidance Algorithms

NASA Technical Reports Server (NTRS)

Smith, Kelly M.

2016-01-01

Recent entry guidance algorithm development123 has tended to focus on numerical integration of trajectories onboard in order to evaluate candidate bank profiles. Such methods enjoy benefits such as flexibility to varying mission profiles and improved robustness to large dispersions. A common element across many of these modern entry guidance algorithms is a reliance upon the concept of Apollo heritage lateral error (or azimuth error) deadbands in which the number of bank reversals to be performed is non-deterministic. This paper presents a closed-loop bank reversal method that operates with a fixed number of bank reversals defined prior to flight. However, this number of bank reversals can be modified at any point, including in flight, based on contingencies such as fuel leaks where propellant usage must be minimized.

VLSI architectures for computing multiplications and inverses in GF(2m).

PubMed

Wang, C C; Truong, T K; Shao, H M; Deutsch, L J; Omura, J K; Reed, I S

1985-08-01

Finite field arithmetic logic is central in the implementation of Reed-Solomon coders and in some cryptographic algorithms. There is a need for good multiplication and inversion algorithms that can be easily realized on VLSI chips. Massey and Omura recently developed a new multiplication algorithm for Galois fields based on a normal basis representation. In this paper, a pipeline structure is developed to realize the Massey-Omura multiplier in the finite field GF(2m). With the simple squaring property of the normal basis representation used together with this multiplier, a pipeline architecture is developed for computing inverse elements in GF(2m). The designs developed for the Massey-Omura multiplier and the computation of inverse elements are regular, simple, expandable, and therefore, naturally suitable for VLSI implementation.

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.

Nonlinear Aerodynamic Modeling From Flight Data Using Advanced Piloted Maneuvers and Fuzzy Logic

NASA Technical Reports Server (NTRS)

Brandon, Jay M.; Morelli, Eugene A.

2012-01-01

Results of the Aeronautics Research Mission Directorate Seedling Project Phase I research project entitled "Nonlinear Aerodynamics Modeling using Fuzzy Logic" are presented. Efficient and rapid flight test capabilities were developed for estimating highly nonlinear models of airplane aerodynamics over a large flight envelope. Results showed that the flight maneuvers developed, used in conjunction with the fuzzy-logic system identification algorithms, produced very good model fits of the data, with no model structure inputs required, for flight conditions ranging from cruise to departure and spin conditions.

Automatic Parking of Self-Driving CAR Based on LIDAR

NASA Astrophysics Data System (ADS)

Lee, B.; Wei, Y.; Guo, I. Y.

2017-09-01

To overcome the deficiency of ultrasonic sensor and camera, this paper proposed a method of autonomous parking based on the self-driving car, using HDL-32E LiDAR. First the 3-D point cloud data was preprocessed. Then we calculated the minimum size of parking space according to the dynamic theories of vehicle. Second the rapidly-exploring random tree algorithm (RRT) algorithm was improved in two aspects based on the moving characteristic of autonomous car. And we calculated the parking path on the basis of the vehicle's dynamics and collision constraints. Besides, we used the fuzzy logic controller to control the brake and accelerator in order to realize the stably of speed. At last the experiments were conducted in an autonomous car, and the results show that the proposed automatic parking system is feasible and effective.

An Algorithm for the Hierarchical Organization of Path Diagrams and Calculation of Components of Expected Covariance.

ERIC Educational Resources Information Center

Boker, Steven M.; McArdle, J. J.; Neale, Michael

2002-01-01

Presents an algorithm for the production of a graphical diagram from a matrix formula in such a way that its components are logically and hierarchically arranged. The algorithm, which relies on the matrix equations of J. McArdle and R. McDonald (1984), calculates the individual path components of expected covariance between variables and…

Spacecube: A Family of Reconfigurable Hybrid On-Board Science Data Processors

NASA Technical Reports Server (NTRS)

Flatley, Thomas P.

2015-01-01

SpaceCube is a family of Field Programmable Gate Array (FPGA) based on-board science data processing systems developed at the NASA Goddard Space Flight Center (GSFC). The goal of the SpaceCube program is to provide 10x to 100x improvements in on-board computing power while lowering relative power consumption and cost. SpaceCube is based on the Xilinx Virtex family of FPGAs, which include processor, FPGA logic and digital signal processing (DSP) resources. These processing elements are leveraged to produce a hybrid science data processing platform that accelerates the execution of algorithms by distributing computational functions to the most suitable elements. This approach enables the implementation of complex on-board functions that were previously limited to ground based systems, such as on-board product generation, data reduction, calibration, classification, eventfeature detection, data mining and real-time autonomous operations. The system is fully reconfigurable in flight, including data parameters, software and FPGA logic, through either ground commanding or autonomously in response to detected eventsfeatures in the instrument data stream.

A method exploiting direct communication between phasor measurement units for power system wide-area protection and control algorithms.

PubMed

Almas, Muhammad Shoaib; Vanfretti, Luigi

2017-01-01

Synchrophasor measurements from Phasor Measurement Units (PMUs) are the primary sensors used to deploy Wide-Area Monitoring, Protection and Control (WAMPAC) systems. PMUs stream out synchrophasor measurements through the IEEE C37.118.2 protocol using TCP/IP or UDP/IP. The proposed method establishes a direct communication between two PMUs, thus eliminating the requirement of an intermediate phasor data concentrator, data mediator and/or protocol parser and thereby ensuring minimum communication latency without considering communication link delays. This method allows utilizing synchrophasor measurements internally in a PMU to deploy custom protection and control algorithms. These algorithms are deployed using protection logic equations which are supported by all the PMU vendors. Moreover, this method reduces overall equipment cost as the algorithms execute internally in a PMU and therefore does not require any additional controller for their deployment. The proposed method can be utilized for fast prototyping of wide-area measurements based protection and control applications. The proposed method is tested by coupling commercial PMUs as Hardware-in-the-Loop (HIL) with Opal-RT's eMEGAsim Real-Time Simulator (RTS). As illustrative example, anti-islanding protection application is deployed using proposed method and its performance is assessed. The essential points in the method are: •Bypassing intermediate phasor data concentrator or protocol parsers as the synchrophasors are communicated directly between the PMUs (minimizes communication delays).•Wide Area Protection and Control Algorithm is deployed using logic equations in the client PMU, therefore eliminating the requirement for an external hardware controller (cost curtailment)•Effortless means to exploit PMU measurements in an environment familiar to protection engineers.

Compact, high-speed algorithm for laying out printed circuit board runs

NASA Astrophysics Data System (ADS)

Zapolotskiy, D. Y.

1985-09-01

A high speed printed circuit connection layout algorithm is described which was developed within the framework of an interactive system for designing two-sided printed circuit broads. For this reason, algorithm speed was considered, a priori, as a requirement equally as important as the inherent demand for minimizing circuit run lengths and the number of junction openings. This resulted from the fact that, in order to provide psychological man/machine compatibility in the design process, real-time dialog during the layout phase is possible only within limited time frames (on the order of several seconds) for each circuit run. The work was carried out for use on an ARM-R automated work site complex based on an SM-4 minicomputer with a 32K-word memory. This limited memory capacity heightened the demand for algorithm speed and also tightened data file structure and size requirements. The layout algorithm's design logic is analyzed. The structure and organization of the data files are described.

System for corrosion monitoring in pipeline applying fuzzy logic mathematics

NASA Astrophysics Data System (ADS)

Kuzyakov, O. N.; Kolosova, A. L.; Andreeva, M. A.

2018-05-01

A list of factors influencing corrosion rate on the external side of underground pipeline is determined. Principles of constructing a corrosion monitoring system are described; the system performance algorithm and program are elaborated. A comparative analysis of methods for calculating corrosion rate is undertaken. Fuzzy logic mathematics is applied to reduce calculations while considering a wider range of corrosion factors.

Fuzzy Sets in Dynamic Adaptation of Parameters of a Bee Colony Optimization for Controlling the Trajectory of an Autonomous Mobile Robot

PubMed Central

Amador-Angulo, Leticia; Mendoza, Olivia; Castro, Juan R.; Rodríguez-Díaz, Antonio; Melin, Patricia; Castillo, Oscar

2016-01-01

A hybrid approach composed by different types of fuzzy systems, such as the Type-1 Fuzzy Logic System (T1FLS), Interval Type-2 Fuzzy Logic System (IT2FLS) and Generalized Type-2 Fuzzy Logic System (GT2FLS) for the dynamic adaptation of the alpha and beta parameters of a Bee Colony Optimization (BCO) algorithm is presented. The objective of the work is to focus on the BCO technique to find the optimal distribution of the membership functions in the design of fuzzy controllers. We use BCO specifically for tuning membership functions of the fuzzy controller for trajectory stability in an autonomous mobile robot. We add two types of perturbations in the model for the Generalized Type-2 Fuzzy Logic System to better analyze its behavior under uncertainty and this shows better results when compared to the original BCO. We implemented various performance indices; ITAE, IAE, ISE, ITSE, RMSE and MSE to measure the performance of the controller. The experimental results show better performances using GT2FLS then by IT2FLS and T1FLS in the dynamic adaptation the parameters for the BCO algorithm. PMID:27618062

Efficient Graph Based Assembly of Short-Read Sequences on Hybrid Core Architecture

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

Sczyrba, Alex; Pratap, Abhishek; Canon, Shane

2011-03-22

Advanced architectures can deliver dramatically increased throughput for genomics and proteomics applications, reducing time-to-completion in some cases from days to minutes. One such architecture, hybrid-core computing, marries a traditional x86 environment with a reconfigurable coprocessor, based on field programmable gate array (FPGA) technology. In addition to higher throughput, increased performance can fundamentally improve research quality by allowing more accurate, previously impractical approaches. We will discuss the approach used by Convey?s de Bruijn graph constructor for short-read, de-novo assembly. Bioinformatics applications that have random access patterns to large memory spaces, such as graph-based algorithms, experience memory performance limitations on cache-based x86more » servers. Convey?s highly parallel memory subsystem allows application-specific logic to simultaneously access 8192 individual words in memory, significantly increasing effective memory bandwidth over cache-based memory systems. Many algorithms, such as Velvet and other de Bruijn graph based, short-read, de-novo assemblers, can greatly benefit from this type of memory architecture. Furthermore, small data type operations (four nucleotides can be represented in two bits) make more efficient use of logic gates than the data types dictated by conventional programming models.JGI is comparing the performance of Convey?s graph constructor and Velvet on both synthetic and real data. We will present preliminary results on memory usage and run time metrics for various data sets with different sizes, from small microbial and fungal genomes to very large cow rumen metagenome. For genomes with references we will also present assembly quality comparisons between the two assemblers.« less

Computer-aided bone age assessment for ethnically diverse older children using integrated fuzzy logic system

NASA Astrophysics Data System (ADS)

Ma, Kevin; Moin, Paymann; Zhang, Aifeng; Liu, Brent

2010-03-01

Bone Age Assessment (BAA) of children is a clinical procedure frequently performed in pediatric radiology to evaluate the stage of skeletal maturation based on the left hand x-ray radiograph. The current BAA standard in the US is using the Greulich & Pyle (G&P) Hand Atlas, which was developed fifty years ago and was only based on Caucasian population from the Midwest US. To bring the BAA procedure up-to-date with today's population, a Digital Hand Atlas (DHA) consisting of 1400 hand images of normal children of different ethnicities, age, and gender. Based on the DHA and to solve inter- and intra-observer reading discrepancies, an automatic computer-aided bone age assessment system has been developed and tested in clinical environments. The algorithm utilizes features extracted from three regions of interests: phalanges, carpal, and radius. The features are aggregated into a fuzzy logic system, which outputs the calculated bone age. The previous BAA system only uses features from phalanges and carpal, thus BAA result for children over age of 15 is less accurate. In this project, the new radius features are incorporated into the overall BAA system. The bone age results, calculated from the new fuzzy logic system, are compared against radiologists' readings based on G&P atlas, and exhibits an improvement in reading accuracy for older children.

Evolutionary Data Mining Approach to Creating Digital Logic

DTIC Science & Technology

2010-01-01

To deal with this problem a genetic program (GP) based data mining ( DM ) procedure has been invented (Smith 2005). A genetic program is an algorithm...that can operate on the variables. When a GP was used as a DM function in the past to automatically create fuzzy decision trees, the Report...rules represents an approach to the determining the effect of linguistic imprecision, i.e., the inability of experts to provide crisp rules. The

Formal modeling of a system of chemical reactions under uncertainty.

PubMed

Ghosh, Krishnendu; Schlipf, John

2014-10-01

We describe a novel formalism representing a system of chemical reactions, with imprecise rates of reactions and concentrations of chemicals, and describe a model reduction method, pruning, based on the chemical properties. We present two algorithms, midpoint approximation and interval approximation, for construction of efficient model abstractions with uncertainty in data. We evaluate computational feasibility by posing queries in computation tree logic (CTL) on a prototype of extracellular-signal-regulated kinase (ERK) pathway.

An Energy-Efficient Spectrum-Aware Reinforcement Learning-Based Clustering Algorithm for Cognitive Radio Sensor Networks

PubMed Central

Mustapha, Ibrahim; Ali, Borhanuddin Mohd; Rasid, Mohd Fadlee A.; Sali, Aduwati; Mohamad, Hafizal

2015-01-01

It is well-known that clustering partitions network into logical groups of nodes in order to achieve energy efficiency and to enhance dynamic channel access in cognitive radio through cooperative sensing. While the topic of energy efficiency has been well investigated in conventional wireless sensor networks, the latter has not been extensively explored. In this paper, we propose a reinforcement learning-based spectrum-aware clustering algorithm that allows a member node to learn the energy and cooperative sensing costs for neighboring clusters to achieve an optimal solution. Each member node selects an optimal cluster that satisfies pairwise constraints, minimizes network energy consumption and enhances channel sensing performance through an exploration technique. We first model the network energy consumption and then determine the optimal number of clusters for the network. The problem of selecting an optimal cluster is formulated as a Markov Decision Process (MDP) in the algorithm and the obtained simulation results show convergence, learning and adaptability of the algorithm to dynamic environment towards achieving an optimal solution. Performance comparisons of our algorithm with the Groupwise Spectrum Aware (GWSA)-based algorithm in terms of Sum of Square Error (SSE), complexity, network energy consumption and probability of detection indicate improved performance from the proposed approach. The results further reveal that an energy savings of 9% and a significant Primary User (PU) detection improvement can be achieved with the proposed approach. PMID:26287191

An Energy-Efficient Spectrum-Aware Reinforcement Learning-Based Clustering Algorithm for Cognitive Radio Sensor Networks.

PubMed

Mustapha, Ibrahim; Mohd Ali, Borhanuddin; Rasid, Mohd Fadlee A; Sali, Aduwati; Mohamad, Hafizal

2015-08-13

It is well-known that clustering partitions network into logical groups of nodes in order to achieve energy efficiency and to enhance dynamic channel access in cognitive radio through cooperative sensing. While the topic of energy efficiency has been well investigated in conventional wireless sensor networks, the latter has not been extensively explored. In this paper, we propose a reinforcement learning-based spectrum-aware clustering algorithm that allows a member node to learn the energy and cooperative sensing costs for neighboring clusters to achieve an optimal solution. Each member node selects an optimal cluster that satisfies pairwise constraints, minimizes network energy consumption and enhances channel sensing performance through an exploration technique. We first model the network energy consumption and then determine the optimal number of clusters for the network. The problem of selecting an optimal cluster is formulated as a Markov Decision Process (MDP) in the algorithm and the obtained simulation results show convergence, learning and adaptability of the algorithm to dynamic environment towards achieving an optimal solution. Performance comparisons of our algorithm with the Groupwise Spectrum Aware (GWSA)-based algorithm in terms of Sum of Square Error (SSE), complexity, network energy consumption and probability of detection indicate improved performance from the proposed approach. The results further reveal that an energy savings of 9% and a significant Primary User (PU) detection improvement can be achieved with the proposed approach.

DNA Cryptography and Deep Learning using Genetic Algorithm with NW algorithm for Key Generation.

PubMed

Kalsi, Shruti; Kaur, Harleen; Chang, Victor

2017-12-05

Cryptography is not only a science of applying complex mathematics and logic to design strong methods to hide data called as encryption, but also to retrieve the original data back, called decryption. The purpose of cryptography is to transmit a message between a sender and receiver such that an eavesdropper is unable to comprehend it. To accomplish this, not only we need a strong algorithm, but a strong key and a strong concept for encryption and decryption process. We have introduced a concept of DNA Deep Learning Cryptography which is defined as a technique of concealing data in terms of DNA sequence and deep learning. In the cryptographic technique, each alphabet of a letter is converted into a different combination of the four bases, namely; Adenine (A), Cytosine (C), Guanine (G) and Thymine (T), which make up the human deoxyribonucleic acid (DNA). Actual implementations with the DNA don't exceed laboratory level and are expensive. To bring DNA computing on a digital level, easy and effective algorithms are proposed in this paper. In proposed work we have introduced firstly, a method and its implementation for key generation based on the theory of natural selection using Genetic Algorithm with Needleman-Wunsch (NW) algorithm and Secondly, a method for implementation of encryption and decryption based on DNA computing using biological operations Transcription, Translation, DNA Sequencing and Deep Learning.

Two-step digit-set-restricted modified signed-digit addition-subtraction algorithm and its optoelectronic implementation.

PubMed

Qian, F; Li, G; Ruan, H; Jing, H; Liu, L

1999-09-10

A novel, to our knowledge, two-step digit-set-restricted modified signed-digit (MSD) addition-subtraction algorithm is proposed. With the introduction of the reference digits, the operand words are mapped into an intermediate carry word with all digits restricted to the set {1, 0} and an intermediate sum word with all digits restricted to the set {0, 1}, which can be summed to form the final result without carry generation. The operation can be performed in parallel by use of binary logic. An optical system that utilizes an electron-trapping device is suggested for accomplishing the required binary logic operations. By programming of the illumination of data arrays, any complex logic operations of multiple variables can be realized without additional temporal latency of the intermediate results. This technique has a high space-bandwidth product and signal-to-noise ratio. The main structure can be stacked to construct a compact optoelectronic MSD adder-subtracter.

Groundspeed filtering for CTAS

NASA Technical Reports Server (NTRS)

Slater, Gary L.

1994-01-01

Ground speed is one of the radar observables which is obtained along with position and heading from NASA Ames Center radar. Within the Center TRACON Automation System (CTAS), groundspeed is converted into airspeed using the wind speeds which CTAS obtains from the NOAA weather grid. This airspeed is then used in the trajectory synthesis logic which computes the trajectory for each individual aircraft. The time history of the typical radar groundspeed data is generally quite noisy, with high frequency variations on the order of five knots, and occasional 'outliers' which can be significantly different from the probable true speed. To try to smooth out these speeds and make the ETA estimate less erratic, filtering of the ground speed is done within CTAS. In its base form, the CTAS filter is a 'moving average' filter which averages the last ten radar values. In addition, there is separate logic to detect and correct for 'outliers', and acceleration logic which limits the groundspeed change in adjacent time samples. As will be shown, these additional modifications do cause significant changes in the actual groundspeed filter output. The conclusion is that the current ground speed filter logic is unable to track accurately the speed variations observed on many aircraft. The Kalman filter logic however, appears to be an improvement to the current algorithm used to smooth ground speed variations, while being simpler and more efficient to implement. Additional logic which can test for true 'outliers' can easily be added by looking at the difference in the a priori and post priori Kalman estimates, and not updating if the difference in these quantities is too large.

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

THRESHOLD LOGIC.

DTIC Science & Technology

synthesis procedures; a ’best’ method is definitely established. (2) ’Symmetry Types for Threshold Logic’ is a tutorial expositon including a careful...development of the Goto-Takahasi self-dual type ideas. (3) ’Best Threshold Gate Decisions’ reports a comparison, on the 2470 7-argument threshold ...interpretation is shown best. (4) ’ Threshold Gate Networks’ reviews the previously discussed 2-algorithm in geometric terms, describes our FORTRAN

Relevancies of multiple-interaction events and signal-to-noise ratio for Anger-logic based PET detector designs

NASA Astrophysics Data System (ADS)

Peng, Hao

2015-10-01

A fundamental challenge for PET block detector designs is to deploy finer crystal elements while limiting the number of readout channels. The standard Anger-logic scheme including light sharing (an 8 by 8 crystal array coupled to a 2×2 photodetector array with an optical diffuser, multiplexing ratio: 16:1) has been widely used to address such a challenge. Our work proposes a generalized model to study the impacts of two critical parameters on spatial resolution performance of a PET block detector: multiple interaction events and signal-to-noise ratio (SNR). The study consists of the following three parts: (1) studying light output profile and multiple interactions of 511 keV photons within crystal arrays of different crystal widths (from 4 mm down to 1 mm, constant height: 20 mm); (2) applying the Anger-logic positioning algorithm to investigate positioning/decoding uncertainties (i.e., "block effect") in terms of peak-to-valley ratio (PVR), with light sharing, multiple interactions and photodetector SNR taken into account; and (3) studying the dependency of spatial resolution on SNR in the context of modulation transfer function (MTF). The proposed model can be used to guide the development and evaluation of a standard Anger-logic based PET block detector including: (1) selecting/optimizing the configuration of crystal elements for a given photodetector SNR; and (2) predicting to what extent additional electronic multiplexing may be implemented to further reduce the number of readout channels.

Computer sciences

NASA Technical Reports Server (NTRS)

Smith, Paul H.

1988-01-01

The Computer Science Program provides advanced concepts, techniques, system architectures, algorithms, and software for both space and aeronautics information sciences and computer systems. The overall goal is to provide the technical foundation within NASA for the advancement of computing technology in aerospace applications. The research program is improving the state of knowledge of fundamental aerospace computing principles and advancing computing technology in space applications such as software engineering and information extraction from data collected by scientific instruments in space. The program includes the development of special algorithms and techniques to exploit the computing power provided by high performance parallel processors and special purpose architectures. Research is being conducted in the fundamentals of data base logic and improvement techniques for producing reliable computing systems.

Process Materialization Using Templates and Rules to Design Flexible Process Models

NASA Astrophysics Data System (ADS)

Kumar, Akhil; Yao, Wen

The main idea in this paper is to show how flexible processes can be designed by combining generic process templates and business rules. We instantiate a process by applying rules to specific case data, and running a materialization algorithm. The customized process instance is then executed in an existing workflow engine. We present an architecture and also give an algorithm for process materialization. The rules are written in a logic-based language like Prolog. Our focus is on capturing deeper process knowledge and achieving a holistic approach to robust process design that encompasses control flow, resources and data, as well as makes it easier to accommodate changes to business policy.

Nocardial scleritis: A case report and a suggested algorithm for disease management based on a literature review.

PubMed

Cunha, Laura Pires da; Juncal, Verena; Carvalhaes, Cecília Godoy; Leão, Sylvia Cardoso; Chimara, Erica; Freitas, Denise

2018-06-01

To report a case of nocardial scleritis and to propose a logical treatment algorithm based on a literature review. It is important to suspect a nocardial infection when evaluating anterior unilateral scleritis accompanied by multiple purulent or necrotic abscesses, especially in male patients with a history of chronic ocular pain and redness, trauma inflicted by organic materials, or recent ophthalmic surgery. A microbiological investigation is essential. In positive cases, a direct smear reveals weakly acid-fast organisms or Gram-positive, thin, beading and branching filaments. Also, the organism (usually) grows on blood agar and Lowenstein-Jensen plates. An infection can generally be fully resolved by debridement of necrotic areas and application of topical amikacin drops accompanied by systemic sulfamethoxazole-trimethoprim. Together with the case report described, we review data on a total of 43 eyes with nocardial scleritis. Our proposed algorithm may afford a useful understanding of this sight-threatening disease, facilitating easier and faster diagnosis and management.

Logic integer programming models for signaling networks.

PubMed

Haus, Utz-Uwe; Niermann, Kathrin; Truemper, Klaus; Weismantel, Robert

2009-05-01

We propose a static and a dynamic approach to model biological signaling networks, and show how each can be used to answer relevant biological questions. For this, we use the two different mathematical tools of Propositional Logic and Integer Programming. The power of discrete mathematics for handling qualitative as well as quantitative data has so far not been exploited in molecular biology, which is mostly driven by experimental research, relying on first-order or statistical models. The arising logic statements and integer programs are analyzed and can be solved with standard software. For a restricted class of problems the logic models reduce to a polynomial-time solvable satisfiability algorithm. Additionally, a more dynamic model enables enumeration of possible time resolutions in poly-logarithmic time. Computational experiments are included.

PLL Based Energy Efficient PV System with Fuzzy Logic Based Power Tracker for Smart Grid Applications.

PubMed

Rohini, G; Jamuna, V

This work aims at improving the dynamic performance of the available photovoltaic (PV) system and maximizing the power obtained from it by the use of cascaded converters with intelligent control techniques. Fuzzy logic based maximum power point technique is embedded on the first conversion stage to obtain the maximum power from the available PV array. The cascading of second converter is needed to maintain the terminal voltage at grid potential. The soft-switching region of three-stage converter is increased with the proposed phase-locked loop based control strategy. The proposed strategy leads to reduction in the ripple content, rating of components, and switching losses. The PV array is mathematically modeled and the system is simulated and the results are analyzed. The performance of the system is compared with the existing maximum power point tracking algorithms. The authors have endeavored to accomplish maximum power and improved reliability for the same insolation of the PV system. Hardware results of the system are also discussed to prove the validity of the simulation results.

PLL Based Energy Efficient PV System with Fuzzy Logic Based Power Tracker for Smart Grid Applications

PubMed Central

Rohini, G.; Jamuna, V.

2016-01-01

This work aims at improving the dynamic performance of the available photovoltaic (PV) system and maximizing the power obtained from it by the use of cascaded converters with intelligent control techniques. Fuzzy logic based maximum power point technique is embedded on the first conversion stage to obtain the maximum power from the available PV array. The cascading of second converter is needed to maintain the terminal voltage at grid potential. The soft-switching region of three-stage converter is increased with the proposed phase-locked loop based control strategy. The proposed strategy leads to reduction in the ripple content, rating of components, and switching losses. The PV array is mathematically modeled and the system is simulated and the results are analyzed. The performance of the system is compared with the existing maximum power point tracking algorithms. The authors have endeavored to accomplish maximum power and improved reliability for the same insolation of the PV system. Hardware results of the system are also discussed to prove the validity of the simulation results. PMID:27294189

A Linguistic Truth-Valued Temporal Reasoning Formalism and Its Implementation

NASA Astrophysics Data System (ADS)

Lu, Zhirui; Liu, Jun; Augusto, Juan C.; Wang, Hui

Temporality and uncertainty are important features of many real world systems. Solving problems in such systems requires the use of formal mechanism such as logic systems, statistical methods or other reasoning and decision-making methods. In this paper, we propose a linguistic truth-valued temporal reasoning formalism to enable the management of both features concurrently using a linguistic truth valued logic and a temporal logic. We also provide a backward reasoning algorithm which allows the answering of user queries. A simple but realistic scenario in a smart home application is used to illustrate our work.

The CSM testbed matrix processors internal logic and dataflow descriptions

NASA Technical Reports Server (NTRS)

Regelbrugge, Marc E.; Wright, Mary A.

1988-01-01

This report constitutes the final report for subtask 1 of Task 5 of NASA Contract NAS1-18444, Computational Structural Mechanics (CSM) Research. This report contains a detailed description of the coded workings of selected CSM Testbed matrix processors (i.e., TOPO, K, INV, SSOL) and of the arithmetic utility processor AUS. These processors and the current sparse matrix data structures are studied and documented. Items examined include: details of the data structures, interdependence of data structures, data-blocking logic in the data structures, processor data flow and architecture, and processor algorithmic logic flow.

Proceedings of the Third International Workshop on Neural Networks and Fuzzy Logic, volume 2

NASA Technical Reports Server (NTRS)

Culbert, Christopher J. (Editor)

1993-01-01

Papers presented at the Neural Networks and Fuzzy Logic Workshop sponsored by the National Aeronautics and Space Administration and cosponsored by the University of Houston, Clear Lake, held 1-3 Jun. 1992 at the Lyndon B. Johnson Space Center in Houston, Texas are included. During the three days approximately 50 papers were presented. Technical topics addressed included adaptive systems; learning algorithms; network architectures; vision; robotics; neurobiological connections; speech recognition and synthesis; fuzzy set theory and application, control and dynamics processing; space applications; fuzzy logic and neural network computers; approximate reasoning; and multiobject decision making.

Analysis of atomic force microscopy data for surface characterization using fuzzy logic

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

Al-Mousa, Amjed, E-mail: aalmousa@vt.edu; Niemann, Darrell L.; Niemann, Devin J.

2011-07-15

In this paper we present a methodology to characterize surface nanostructures of thin films. The methodology identifies and isolates nanostructures using Atomic Force Microscopy (AFM) data and extracts quantitative information, such as their size and shape. The fuzzy logic based methodology relies on a Fuzzy Inference Engine (FIE) to classify the data points as being top, bottom, uphill, or downhill. The resulting data sets are then further processed to extract quantitative information about the nanostructures. In the present work we introduce a mechanism which can consistently distinguish crowded surfaces from those with sparsely distributed structures and present an omni-directional searchmore » technique to improve the structural recognition accuracy. In order to demonstrate the effectiveness of our approach we present a case study which uses our approach to quantitatively identify particle sizes of two specimens each with a unique gold nanoparticle size distribution. - Research Highlights: {yields} A Fuzzy logic analysis technique capable of characterizing AFM images of thin films. {yields} The technique is applicable to different surfaces regardless of their densities. {yields} Fuzzy logic technique does not require manual adjustment of the algorithm parameters. {yields} The technique can quantitatively capture differences between surfaces. {yields} This technique yields more realistic structure boundaries compared to other methods.« less

Automatic casting surface defect recognition and classification

NASA Astrophysics Data System (ADS)

Wong, Boon K.; Elliot, M. P.; Rapley, C. W.

1995-03-01

High integrity castings require surfaces free from defects to reduce, if not eliminate, vulnerability to component failure from such as physical or thermal fatigue or corrosion attack. Previous studies have shown that defects on casting surfaces can be optically enhanced from the surrounding randomly textured surface by liquid penetrants, magnetic particle and other methods. However, very little has been reported on recognition and classification of the defects. The basic problem is one of shape recognition and classification, where the shape can vary in size and orientation as well as in actual shape generally within an envelope that classifies it as a particular defect. The initial work done towards this has focused on recognizing and classifying standard shapes such as the circle, square, rectangle and triangle. Various approaches were tried and this led eventually to a series of fuzzy logic based algorithms from which very good results were obtained. From this work fuzzy logic memberships were generated for the detection of defects found on casting surfaces. Simulated model shapes of such as the quench crack, mechanical crack and hole have been used to test the generated algorithm and the results for recognition and classification are very encouraging.

Automated cloud classification with a fuzzy logic expert system

NASA Technical Reports Server (NTRS)

Tovinkere, Vasanth; Baum, Bryan A.

1993-01-01

An unresolved problem in current cloud retrieval algorithms concerns the analysis of scenes containing overlapping cloud layers. Cloud parameterizations are very important both in global climate models and in studies of the Earth's radiation budget. Most cloud retrieval schemes, such as the bispectral method used by the International Satellite Cloud Climatology Project (ISCCP), have no way of determining whether overlapping cloud layers exist in any group of satellite pixels. One promising method uses fuzzy logic to determine whether mixed cloud and/or surface types exist within a group of pixels, such as cirrus, land, and water, or cirrus and stratus. When two or more class types are present, fuzzy logic uses membership values to assign the group of pixels partially to the different class types. The strength of fuzzy logic lies in its ability to work with patterns that may include more than one class, facilitating greater information extraction from satellite radiometric data. The development of the fuzzy logic rule-based expert system involves training the fuzzy classifier with spectral and textural features calculated from accurately labeled 32x32 regions of Advanced Very High Resolution Radiometer (AVHRR) 1.1-km data. The spectral data consists of AVHRR channels 1 (0.55-0.68 mu m), 2 (0.725-1.1 mu m), 3 (3.55-3.93 mu m), 4 (10.5-11.5 mu m), and 5 (11.5-12.5 mu m), which include visible, near-infrared, and infrared window regions. The textural features are based on the gray level difference vector (GLDV) method. A sophisticated new interactive visual image Classification System (IVICS) is used to label samples chosen from scenes collected during the FIRE IFO II. The training samples are chosen from predefined classes, chosen to be ocean, land, unbroken stratiform, broken stratiform, and cirrus. The November 28, 1991 NOAA overpasses contain complex multilevel cloud situations ideal for training and validating the fuzzy logic expert system.

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

Development of a solar-powered electric bicycle in bike sharing transportation system

NASA Astrophysics Data System (ADS)

Adhisuwignjo, S.; Siradjuddin, I.; Rifa'i, M.; Putri, R. I.

2017-06-01

The increasing mobility has directly led to deteriorating traffic conditions, extra fuel consumption, increasing automobile exhaust emissions, air pollution and lowering quality of life. Apart from being clean, cheap and equitable mode of transport for short-distance journeys, cycling can potentially offer solutions to the problem of urban mobility. Many cities have tried promoting cycling particularly through the implementation of bike-sharing. Apparently the fourth generation bikesharing system has been promoted utilizing electric bicycles which considered as a clean technology implementation. Utilization of solar power is probably the development keys in the fourth generation bikesharing system and will become the standard in bikesharing system in the future. Electric bikes use batteries as a source of energy, thus they require a battery charger system which powered from the solar cells energy. This research aims to design and implement electric bicycle battery charging system with solar energy sources using fuzzy logic algorithm. It is necessary to develop an electric bicycle battery charging system with solar energy sources using fuzzy logic algorithm. The study was conducted by means of experimental method which includes the design, manufacture and testing controller systems. The designed fuzzy algorithm have been planted in EEPROM microcontroller ATmega8535. The charging current was set at 1.2 Amperes and the full charged battery voltage was observed to be 40 Volts. The results showed a fuzzy logic controller was able to maintain the charging current of 1.2 Ampere with an error rate of less than 5% around the set point. The process of charging electric bike lead acid batteries from empty to fully charged was 5 hours. In conclusion, the development of solar-powered electric bicycle controlled using fuzzy logic controller can keep the battery charging current in solar-powered electric bicycle to remain stable. This shows that the fuzzy algorithm can be used as a controller in the process of charging for a solar electric bicycle.

Engineering integrated digital circuits with allosteric ribozymes for scaling up molecular computation and diagnostics.

PubMed

Penchovsky, Robert

2012-10-19

Here we describe molecular implementations of integrated digital circuits, including a three-input AND logic gate, a two-input multiplexer, and 1-to-2 decoder using allosteric ribozymes. Furthermore, we demonstrate a multiplexer-decoder circuit. The ribozymes are designed to seek-and-destroy specific RNAs with a certain length by a fully computerized procedure. The algorithm can accurately predict one base substitution that alters the ribozyme's logic function. The ability to sense the length of RNA molecules enables single ribozymes to be used as platforms for multiple interactions. These ribozymes can work as integrated circuits with the functionality of up to five logic gates. The ribozyme design is universal since the allosteric and substrate domains can be altered to sense different RNAs. In addition, the ribozymes can specifically cleave RNA molecules with triplet-repeat expansions observed in genetic disorders such as oculopharyngeal muscular dystrophy. Therefore, the designer ribozymes can be employed for scaling up computing and diagnostic networks in the fields of molecular computing and diagnostics and RNA synthetic biology.

A new approach for investigating protein flexibility based on Constraint Logic Programming. The first application in the case of the estrogen receptor.

PubMed

Dal Palú, Alessandro; Spyrakis, Francesca; Cozzini, Pietro

2012-03-01

We describe the potential of a novel method, based on Constraint Logic Programming (CLP), developed for an exhaustive sampling of protein conformational space. The CLP framework proposed here has been tested and applied to the estrogen receptor, whose activity and function is strictly related to its intrinsic, and well known, dynamics. We have investigated in particular the flexibility of H12, focusing on the pathways followed by the helix when moving from one stable crystallographic conformation to the others. Millions of geometrically feasible conformations were generated, selected and the traces connecting the different forms were determined by using a shortest path algorithm. The preliminary analyses showed a marked agreement between the crystallographic agonist-like, antagonist-like and hypothetical apo forms, and the corresponding conformations identified by the CLP framework. These promising results, together with the short computational time required to perform the analyses, make this constraint-based approach a valuable tool for the study of protein folding prediction. The CLP framework enables one to consider various structural and energetic scenarious, without changing the core algorithm. To show the feasibility of the method, we intentionally choose a pure geometric setting, neglecting the energetic evaluation of the poses, in order to be independent from a specific force field and to provide the possibility of comparing different behaviours associated with various energy models. Copyright © 2012 Elsevier Masson SAS. All rights reserved.

Rocketdyne Safety Algorithm: Space Shuttle Main Engine Fault Detection

NASA Technical Reports Server (NTRS)

Norman, Arnold M., Jr.

1994-01-01

The Rocketdyne Safety Algorithm (RSA) has been developed to the point of use on the TTBE at MSFC on Task 4 of LeRC contract NAS3-25884. This document contains a description of the work performed, the results of the nominal test of the major anomaly test cases and a table of the resulting cutoff times, a plot of the RSA value vs. time for each anomaly case, a logic flow description of the algorithm, the algorithm code, and a development plan for future efforts.

LOGICAL REASONING ABILITY AND STUDENT PERFORMANCE IN GENERAL CHEMISTRY.

PubMed

Bird, Lillian

2010-03-01

Logical reasoning skills of students enrolled in General Chemistry at the University of Puerto Rico in Río Piedras were measured using the Group Assessment of Logical Thinking (GALT) test. The results were used to determine the students' cognitive level (concrete, transitional, formal) as well as their level of performance by logical reasoning mode (mass/volume conservation, proportional reasoning, correlational reasoning, experimental variable control, probabilistic reasoning and combinatorial reasoning). This information was used to identify particular deficiencies and gender effects, and to determine which logical reasoning modes were the best predictors of student performance in the general chemistry course. Statistical tests to analyze the relation between (a) operational level and final grade in both semesters of the course; (b) GALT test results and performance in the ACS General Chemistry Examination; and (c) operational level and student approach (algorithmic or conceptual) towards a test question that may be answered correctly using either strategy, were also performed.

LOGICAL REASONING ABILITY AND STUDENT PERFORMANCE IN GENERAL CHEMISTRY

PubMed Central

Bird, Lillian

2010-01-01

Logical reasoning skills of students enrolled in General Chemistry at the University of Puerto Rico in Río Piedras were measured using the Group Assessment of Logical Thinking (GALT) test. The results were used to determine the students’ cognitive level (concrete, transitional, formal) as well as their level of performance by logical reasoning mode (mass/volume conservation, proportional reasoning, correlational reasoning, experimental variable control, probabilistic reasoning and combinatorial reasoning). This information was used to identify particular deficiencies and gender effects, and to determine which logical reasoning modes were the best predictors of student performance in the general chemistry course. Statistical tests to analyze the relation between (a) operational level and final grade in both semesters of the course; (b) GALT test results and performance in the ACS General Chemistry Examination; and (c) operational level and student approach (algorithmic or conceptual) towards a test question that may be answered correctly using either strategy, were also performed. PMID:21373364

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.

Cognitive foundations for model-based sensor fusion

NASA Astrophysics Data System (ADS)

Perlovsky, Leonid I.; Weijers, Bertus; Mutz, Chris W.

2003-08-01

Target detection, tracking, and sensor fusion are complicated problems, which usually are performed sequentially. First detecting targets, then tracking, then fusing multiple sensors reduces computations. This procedure however is inapplicable to difficult targets which cannot be reliably detected using individual sensors, on individual scans or frames. In such more complicated cases one has to perform functions of fusing, tracking, and detecting concurrently. This often has led to prohibitive combinatorial complexity and, as a consequence, to sub-optimal performance as compared to the information-theoretic content of all the available data. It is well appreciated that in this task the human mind is by far superior qualitatively to existing mathematical methods of sensor fusion, however, the human mind is limited in the amount of information and speed of computation it can cope with. Therefore, research efforts have been devoted toward incorporating "biological lessons" into smart algorithms, yet success has been limited. Why is this so, and how to overcome existing limitations? The fundamental reasons for current limitations are analyzed and a potentially breakthrough research and development effort is outlined. We utilize the way our mind combines emotions and concepts in the thinking process and present the mathematical approach to accomplishing this in the current technology computers. The presentation will summarize the difficulties encountered by intelligent systems over the last 50 years related to combinatorial complexity, analyze the fundamental limitations of existing algorithms and neural networks, and relate it to the type of logic underlying the computational structure: formal, multivalued, and fuzzy logic. A new concept of dynamic logic will be introduced along with algorithms capable of pulling together all the available information from multiple sources. This new mathematical technique, like our brain, combines conceptual understanding with emotional evaluation and overcomes the combinatorial complexity of concurrent fusion, tracking, and detection. The presentation will discuss examples of performance, where computational speedups of many orders of magnitude were attained leading to performance improvements of up to 10 dB (and better).

Extended Mixed-Efects Item Response Models with the MH-RM Algorithm

ERIC Educational Resources Information Center

Chalmers, R. Philip

2015-01-01

A mixed-effects item response theory (IRT) model is presented as a logical extension of the generalized linear mixed-effects modeling approach to formulating explanatory IRT models. Fixed and random coefficients in the extended model are estimated using a Metropolis-Hastings Robbins-Monro (MH-RM) stochastic imputation algorithm to accommodate for…

Genetic algorithm optimized rainfall-runoff fuzzy inference system for row crop watersheds with claypan soils

USDA-ARS?s Scientific Manuscript database

The fuzzy logic algorithm has the ability to describe knowledge in a descriptive human-like manner in the form of simple rules using linguistic variables, and provides a new way of modeling uncertain or naturally fuzzy hydrological processes like non-linear rainfall-runoff relationships. Fuzzy infe...

Improving the Accuracy and Scalability of Discriminative Learning Methods for Markov Logic Networks

DTIC Science & Technology

2011-05-01

9 2.2 Inductive Logic Programming and Aleph . . . . . . . . . . . . 10 2.3 MLNs and Alchemy ...positive examples. Aleph allows users to customize each of 10 these steps, and thereby supports a variety of specific algorithms. 2.3 MLNs and Alchemy An...tural motifs. By limiting the search to each unique motif, LSM is able to find good clauses in an efficient manner. Alchemy (Kok, Singla, Richardson

A fuzzy logic approach to control anaerobic digestion.

PubMed

Domnanovich, A M; Strik, D P; Zani, L; Pfeiffer, B; Karlovits, M; Braun, R; Holubar, P

2003-01-01

One of the goals of the EU-Project AMONCO (Advanced Prediction, Monitoring and Controlling of Anaerobic Digestion Process Behaviour towards Biogas Usage in Fuel Cells) is to create a control tool for the anaerobic digestion process, which predicts the volumetric organic loading rate (Bv) for the next day, to obtain a high biogas quality and production. The biogas should contain a high methane concentration (over 50%) and a low concentration of components toxic for fuel cells, e.g. hydrogen sulphide, siloxanes, ammonia and mercaptanes. For producing data to test the control tool, four 20 l anaerobic Continuously Stirred Tank Reactors (CSTR) are operated. For controlling two systems were investigated: a pure fuzzy logic system and a hybrid-system which contains a fuzzy based reactor condition calculation and a hierachial neural net in a cascade of optimisation algorithms.

Centralized and distributed control architectures under Foundation Fieldbus network.

PubMed

Persechini, Maria Auxiliadora Muanis; Jota, Fábio Gonçalves

2013-01-01

This paper aims at discussing possible automation and control system architectures based on fieldbus networks in which the controllers can be implemented either in a centralized or in a distributed form. An experimental setup is used to demonstrate some of the addressed issues. The control and automation architecture is composed of a supervisory system, a programmable logic controller and various other devices connected to a Foundation Fieldbus H1 network. The procedures used in the network configuration, in the process modelling and in the design and implementation of controllers are described. The specificities of each one of the considered logical organizations are also discussed. Finally, experimental results are analysed using an algorithm for the assessment of control loops to compare the performances between the centralized and the distributed implementations. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

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.

A Scala DSL for RETE-Based Runtime Verification

NASA Technical Reports Server (NTRS)

Havelund, Klaus

2013-01-01

Runtime verification (RV) consists in part of checking execution traces against formalized specifications. Several systems have emerged, most of which support specification notations based on state machines, regular expressions, temporal logic, or grammars. The field of Artificial Intelligence (AI) has for an even longer period of time studied rule-based production systems, which at a closer look appear to be relevant for RV, although seemingly focused on slightly different application domains, such as for example business processes and expert systems. The core algorithm in many of these systems is the Rete algorithm. We have implemented a Rete-based runtime verification system, named LogFire (originally intended for offline log analysis but also applicable to online analysis), as an internal DSL in the Scala programming language, using Scala's support for defining DSLs. This combination appears attractive from a practical point of view. Our contribution is in part conceptual in arguing that such rule-based frameworks originating from AI may be suited for RV.

Design of a Ferroelectric Programmable Logic Gate Array

NASA Technical Reports Server (NTRS)

MacLeod, Todd C.; Ho, Fat Duen

2003-01-01

A programmable logic gate array has been designed utilizing ferroelectric field effect transistors. The design has only a small number of gates, but this could be scaled up to a more useful size. Using FFET's in a logic array gives several advantages. First, it allows real-time programmability to the array to give high speed reconfiguration. It also allows the array to be configured nearly an unlimited number of times, unlike a FLASH FPGA. Finally, the Ferroelectric Programmable Logic Gate Array (FPLGA) can be implemented using a smaller number of transistors because of the inherent logic characteristics of an FFET. The device was only designed and modeled using Spice models of the circuit, including the FFET. The actual device was not produced. The design consists of a small array of NAND and NOR logic gates. Other gates could easily be produced. They are linked by FFET's that control the logic flow. Timing and logic tables have been produced showing the array can produce a variety of logic combinations at a real time usable speed. This device could be a prototype for a device that could be put into imbedded systems that need the high speed of hardware implementation of logic and the complexity to need to change the logic algorithm. Because of the non-volatile nature of the FFET, it would also be useful in situations that needed to program a logic array once and use it repeatedly after the power has been shut off.

Scaffold hopping in drug discovery using inductive logic programming.

PubMed

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

2008-05-01

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

A fuzzy Petri-net-based mode identification algorithm for fault diagnosis of complex systems

NASA Astrophysics Data System (ADS)

Propes, Nicholas C.; Vachtsevanos, George

2003-08-01

Complex dynamical systems such as aircraft, manufacturing systems, chillers, motor vehicles, submarines, etc. exhibit continuous and event-driven dynamics. These systems undergo several discrete operating modes from startup to shutdown. For example, a certain shipboard system may be operating at half load or full load or may be at start-up or shutdown. Of particular interest are extreme or "shock" operating conditions, which tend to severely impact fault diagnosis or the progression of a fault leading to a failure. Fault conditions are strongly dependent on the operating mode. Therefore, it is essential that in any diagnostic/prognostic architecture, the operating mode be identified as accurately as possible so that such functions as feature extraction, diagnostics, prognostics, etc. can be correlated with the predominant operating conditions. This paper introduces a mode identification methodology that incorporates both time- and event-driven information about the process. A fuzzy Petri net is used to represent the possible successive mode transitions and to detect events from processed sensor signals signifying a mode change. The operating mode is initialized and verified by analysis of the time-driven dynamics through a fuzzy logic classifier. An evidence combiner module is used to combine the results from both the fuzzy Petri net and the fuzzy logic classifier to determine the mode. Unlike most event-driven mode identifiers, this architecture will provide automatic mode initialization through the fuzzy logic classifier and robustness through the combining of evidence of the two algorithms. The mode identification methodology is applied to an AC Plant typically found as a component of a shipboard system.

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.

Adaptive Gaussian mixture models for pre-screening in GPR data

NASA Astrophysics Data System (ADS)

Torrione, Peter; Morton, Kenneth, Jr.; Besaw, Lance E.

2011-06-01

Due to the large amount of data generated by vehicle-mounted ground penetrating radar (GPR) antennae arrays, advanced feature extraction and classification can only be performed on a small subset of data during real-time operation. As a result, most GPR based landmine detection systems implement "pre-screening" algorithms to processes all of the data generated by the antennae array and identify locations with anomalous signatures for more advanced processing. These pre-screening algorithms must be computationally efficient and obtain high probability of detection, but can permit a false alarm rate which might be higher than the total system requirements. Many approaches to prescreening have previously been proposed, including linear prediction coefficients, the LMS algorithm, and CFAR-based approaches. Similar pre-screening techniques have also been developed in the field of video processing to identify anomalous behavior or anomalous objects. One such algorithm, an online k-means approximation to an adaptive Gaussian mixture model (GMM), is particularly well-suited to application for pre-screening in GPR data due to its computational efficiency, non-linear nature, and relevance of the logic underlying the algorithm to GPR processing. In this work we explore the application of an adaptive GMM-based approach for anomaly detection from the video processing literature to pre-screening in GPR data. Results with the ARA Nemesis landmine detection system demonstrate significant pre-screening performance improvements compared to alternative approaches, and indicate that the proposed algorithm is a complimentary technique to existing methods.

Security Data Warehouse Application

NASA Technical Reports Server (NTRS)

Vernon, Lynn R.; Hennan, Robert; Ortiz, Chris; Gonzalez, Steve; Roane, John

2012-01-01

The Security Data Warehouse (SDW) is used to aggregate and correlate all JSC IT security data. This includes IT asset inventory such as operating systems and patch levels, users, user logins, remote access dial-in and VPN, and vulnerability tracking and reporting. The correlation of this data allows for an integrated understanding of current security issues and systems by providing this data in a format that associates it to an individual host. The cornerstone of the SDW is its unique host-mapping algorithm that has undergone extensive field tests, and provides a high degree of accuracy. The algorithm comprises two parts. The first part employs fuzzy logic to derive a best-guess host assignment using incomplete sensor data. The second part is logic to identify and correct errors in the database, based on subsequent, more complete data. Host records are automatically split or merged, as appropriate. The process had to be refined and thoroughly tested before the SDW deployment was feasible. Complexity was increased by adding the dimension of time. The SDW correlates all data with its relationship to time. This lends support to forensic investigations, audits, and overall situational awareness. Another important feature of the SDW architecture is that all of the underlying complexities of the data model and host-mapping algorithm are encapsulated in an easy-to-use and understandable Perl language Application Programming Interface (API). This allows the SDW to be quickly augmented with additional sensors using minimal coding and testing. It also supports rapid generation of ad hoc reports and integration with other information systems.

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.

Proceedings of the Third International Workshop on Neural Networks and Fuzzy Logic, volume 1

NASA Technical Reports Server (NTRS)

Culbert, Christopher J. (Editor)

1993-01-01

Documented here are papers presented at the Neural Networks and Fuzzy Logic Workshop sponsored by the National Aeronautics and Space Administration and cosponsored by the University of Houston, Clear Lake. The workshop was held June 1-3, 1992 at the Lyndon B. Johnson Space Center in Houston, Texas. During the three days approximately 50 papers were presented. Technical topics addressed included adaptive systems; learning algorithms; network architectures; vision; robotics; neurobiological connections; speech recognition and synthesis; fuzzy set theory and application, control, and dynamics processing; space applications; fuzzy logic and neural network computers; approximate reasoning; and multiobject decision making.

Mixed-initiative control of intelligent systems

NASA Technical Reports Server (NTRS)

Borchardt, G. C.

1987-01-01

Mixed-initiative user interfaces provide a means by which a human operator and an intelligent system may collectively share the task of deciding what to do next. Such interfaces are important to the effective utilization of real-time expert systems as assistants in the execution of critical tasks. Presented here is the Incremental Inference algorithm, a symbolic reasoning mechanism based on propositional logic and suited to the construction of mixed-initiative interfaces. The algorithm is similar in some respects to the Truth Maintenance System, but replaces the notion of 'justifications' with a notion of recency, allowing newer values to override older values yet permitting various interested parties to refresh these values as they become older and thus more vulnerable to change. A simple example is given of the use of the Incremental Inference algorithm plus an overview of the integration of this mechanism within the SPECTRUM expert system for geological interpretation of imaging spectrometer data.

A Family of Well-Clear Boundary Models for the Integration of UAS in the NAS

NASA Technical Reports Server (NTRS)

Munoz, Cesar A.; Narkawicz, Anthony; Chamberlain, James; Consiglio, Maria; Upchurch, Jason

2014-01-01

The FAA-sponsored Sense and Avoid Workshop for Unmanned Aircraft Systems (UAS) defines the concept of sense and avoid for remote pilots as "the capability of a UAS to remain well clear from and avoid collisions with other airborne traffic." Hence, a rigorous definition of well clear is fundamental to any separation assurance concept for the integration of UAS into civil airspace. This paper presents a family of well-clear boundary models based on the TCAS II Resolution Advisory logic. For these models, algorithms that predict well-clear violations along aircraft current trajectories are provided. These algorithms are analogous to conflict detection algorithms but instead of predicting loss of separation, they predict whether well-clear violations will occur during a given lookahead time interval. Analytical techniques are used to study the properties and relationships satisfied by the models.

Genetic algorithms in adaptive fuzzy control

NASA Technical Reports Server (NTRS)

Karr, C. Lucas; Harper, Tony R.

1992-01-01

Researchers at the U.S. Bureau of Mines have developed adaptive process control systems in which genetic algorithms (GA's) are used to augment fuzzy logic controllers (FLC's). GA's are search algorithms that rapidly locate near-optimum solutions to a wide spectrum of problems by modeling the search procedures of natural genetics. FLC's are rule based systems that efficiently manipulate a problem environment by modeling the 'rule-of-thumb' strategy used in human decision making. Together, GA's and FLC's possess the capabilities necessary to produce powerful, efficient, and robust adaptive control systems. To perform efficiently, such control systems require a control element to manipulate the problem environment, an analysis element to recognize changes in the problem environment, and a learning element to adjust fuzzy membership functions in response to the changes in the problem environment. Details of an overall adaptive control system are discussed. A specific computer-simulated chemical system is used to demonstrate the ideas presented.

Temporal Precedence Checking for Switched Models and its Application to a Parallel Landing Protocol

NASA Technical Reports Server (NTRS)

Duggirala, Parasara Sridhar; Wang, Le; Mitra, Sayan; Viswanathan, Mahesh; Munoz, Cesar A.

2014-01-01

This paper presents an algorithm for checking temporal precedence properties of nonlinear switched systems. This class of properties subsume bounded safety and capture requirements about visiting a sequence of predicates within given time intervals. The algorithm handles nonlinear predicates that arise from dynamics-based predictions used in alerting protocols for state-of-the-art transportation systems. It is sound and complete for nonlinear switch systems that robustly satisfy the given property. The algorithm is implemented in the Compare Execute Check Engine (C2E2) using validated simulations. As a case study, a simplified model of an alerting system for closely spaced parallel runways is considered. The proposed approach is applied to this model to check safety properties of the alerting logic for different operating conditions such as initial velocities, bank angles, aircraft longitudinal separation, and runway separation.

Evaluation and Application of Satellite-Based Latent Heating Profile Estimation Methods

NASA Technical Reports Server (NTRS)

Olson, William S.; Grecu, Mircea; Yang, Song; Tao, Wei-Kuo

2004-01-01

In recent years, methods for estimating atmospheric latent heating vertical structure from both passive and active microwave remote sensing have matured to the point where quantitative evaluation of these methods is the next logical step. Two approaches for heating algorithm evaluation are proposed: First, application of heating algorithms to synthetic data, based upon cloud-resolving model simulations, can be used to test the internal consistency of heating estimates in the absence of systematic errors in physical assumptions. Second, comparisons of satellite-retrieved vertical heating structures to independent ground-based estimates, such as rawinsonde-derived analyses of heating, provide an additional test. The two approaches are complementary, since systematic errors in heating indicated by the second approach may be confirmed by the first. A passive microwave and combined passive/active microwave heating retrieval algorithm are evaluated using the described approaches. In general, the passive microwave algorithm heating profile estimates are subject to biases due to the limited vertical heating structure information contained in the passive microwave observations. These biases may be partly overcome by including more environment-specific a priori information into the algorithm s database of candidate solution profiles. The combined passive/active microwave algorithm utilizes the much higher-resolution vertical structure information provided by spaceborne radar data to produce less biased estimates; however, the global spatio-temporal sampling by spaceborne radar is limited. In the present study, the passive/active microwave algorithm is used to construct a more physically-consistent and environment-specific set of candidate solution profiles for the passive microwave algorithm and to help evaluate errors in the passive algorithm s heating estimates. Although satellite estimates of latent heating are based upon instantaneous, footprint- scale data, suppression of random errors requires averaging to at least half-degree resolution. Analysis of mesoscale and larger space-time scale phenomena based upon passive and passive/active microwave heating estimates from TRMM, SSMI, and AMSR data will be presented at the conference.

ARPANET Routing Algorithm Improvements. Volume 1

DTIC Science & Technology

1980-08-01

the currently active PROCESS (at the head of the scheduling list). TIME returns the time. PASSIVATE puts the CURRENT PROCESS to sleep , and wakes uD...Ccntract. Network buffer managemenL issues are discussed and a new buffer managemet scheme for f the ARPANET is designed. Logical addressing is discussed...and a design is given for a logical addressing scheme suitable for ARPANET or DIN II. The applicability of ARPANET Routing to DIN II is evaluaced. The

Hetero-association for pattern translation

NASA Astrophysics Data System (ADS)

Yu, Francis T. S.; Lu, Thomas T.; Yang, Xiangyang

1991-09-01

A hetero-association neural network using an interpattern association algorithm is presented. By using simple logical rules, hetero-association memory can be constructed based on the association between the input-output reference patterns. For optical implementation, a compact size liquid crystal television neural network is used. Translations between the English letters and the Chinese characters as well as Arabic and Chinese numerics are demonstrated. The authors have shown that the hetero-association model can perform more effectively in comparison to the Hopfield model in retrieving large numbers of similar patterns.

Parallel algorithms for simulating continuous time Markov chains

NASA Technical Reports Server (NTRS)

Nicol, David M.; Heidelberger, Philip

1992-01-01

We have previously shown that the mathematical technique of uniformization can serve as the basis of synchronization for the parallel simulation of continuous-time Markov chains. This paper reviews the basic method and compares five different methods based on uniformization, evaluating their strengths and weaknesses as a function of problem characteristics. The methods vary in their use of optimism, logical aggregation, communication management, and adaptivity. Performance evaluation is conducted on the Intel Touchstone Delta multiprocessor, using up to 256 processors.

Self-tuning control algorithm design for vehicle adaptive cruise control system through real-time estimation of vehicle parameters and road grade

NASA Astrophysics Data System (ADS)

Marzbanrad, Javad; Tahbaz-zadeh Moghaddam, Iman

2016-09-01

The main purpose of this paper is to design a self-tuning control algorithm for an adaptive cruise control (ACC) system that can adapt its behaviour to variations of vehicle dynamics and uncertain road grade. To this aim, short-time linear quadratic form (STLQF) estimation technique is developed so as to track simultaneously the trend of the time-varying parameters of vehicle longitudinal dynamics with a small delay. These parameters are vehicle mass, road grade and aerodynamic drag-area coefficient. Next, the values of estimated parameters are used to tune the throttle and brake control inputs and to regulate the throttle/brake switching logic that governs the throttle and brake switching. The performance of the designed STLQF-based self-tuning control (STLQF-STC) algorithm for ACC system is compared with the conventional method based on fixed control structure regarding the speed/distance tracking control modes. Simulation results show that the proposed control algorithm improves the performance of throttle and brake controllers, providing more comfort while travelling, enhancing driving safety and giving a satisfactory performance in the presence of different payloads and road grade variations.

Concrete resource analysis of the quantum linear-system algorithm used to compute the electromagnetic scattering cross section of a 2D target

NASA Astrophysics Data System (ADS)

Scherer, Artur; Valiron, Benoît; Mau, Siun-Chuon; Alexander, Scott; van den Berg, Eric; Chapuran, Thomas E.

2017-03-01

We provide a detailed estimate for the logical resource requirements of the quantum linear-system algorithm (Harrow et al. in Phys Rev Lett 103:150502, 2009) including the recently described elaborations and application to computing the electromagnetic scattering cross section of a metallic target (Clader et al. in Phys Rev Lett 110:250504, 2013). Our resource estimates are based on the standard quantum-circuit model of quantum computation; they comprise circuit width (related to parallelism), circuit depth (total number of steps), the number of qubits and ancilla qubits employed, and the overall number of elementary quantum gate operations as well as more specific gate counts for each elementary fault-tolerant gate from the standard set { X, Y, Z, H, S, T, { CNOT } }. In order to perform these estimates, we used an approach that combines manual analysis with automated estimates generated via the Quipper quantum programming language and compiler. Our estimates pertain to the explicit example problem size N=332{,}020{,}680 beyond which, according to a crude big-O complexity comparison, the quantum linear-system algorithm is expected to run faster than the best known classical linear-system solving algorithm. For this problem size, a desired calculation accuracy ɛ =0.01 requires an approximate circuit width 340 and circuit depth of order 10^{25} if oracle costs are excluded, and a circuit width and circuit depth of order 10^8 and 10^{29}, respectively, if the resource requirements of oracles are included, indicating that the commonly ignored oracle resources are considerable. In addition to providing detailed logical resource estimates, it is also the purpose of this paper to demonstrate explicitly (using a fine-grained approach rather than relying on coarse big-O asymptotic approximations) how these impressively large numbers arise with an actual circuit implementation of a quantum algorithm. While our estimates may prove to be conservative as more efficient advanced quantum-computation techniques are developed, they nevertheless provide a valid baseline for research targeting a reduction of the algorithmic-level resource requirements, implying that a reduction by many orders of magnitude is necessary for the algorithm to become practical.

Effective algorithm for solving complex problems of production control and of material flows control of industrial enterprise

NASA Astrophysics Data System (ADS)

Mezentsev, Yu A.; Baranova, N. V.

2018-05-01

A universal economical and mathematical model designed for determination of optimal strategies for managing subsystems (components of subsystems) of production and logistics of enterprises is considered. Declared universality allows taking into account on the system level both production components, including limitations on the ways of converting raw materials and components into sold goods, as well as resource and logical restrictions on input and output material flows. The presented model and generated control problems are developed within the framework of the unified approach that allows one to implement logical conditions of any complexity and to define corresponding formal optimization tasks. Conceptual meaning of used criteria and limitations are explained. The belonging of the generated tasks of the mixed programming with the class of NP is shown. An approximate polynomial algorithm for solving the posed optimization tasks for mixed programming of real dimension with high computational complexity is proposed. Results of testing the algorithm on the tasks in a wide range of dimensions are presented.

Reducing false-positive detections by combining two stage-1 computer-aided mass detection algorithms

NASA Astrophysics Data System (ADS)

Bedard, Noah D.; Sampat, Mehul P.; Stokes, Patrick A.; Markey, Mia K.

2006-03-01

In this paper we present a strategy for reducing the number of false-positives in computer-aided mass detection. Our approach is to only mark "consensus" detections from among the suspicious sites identified by different "stage-1" detection algorithms. By "stage-1" we mean that each of the Computer-aided Detection (CADe) algorithms is designed to operate with high sensitivity, allowing for a large number of false positives. In this study, two mass detection methods were used: (1) Heath and Bowyer's algorithm based on the average fraction under the minimum filter (AFUM) and (2) a low-threshold bi-lateral subtraction algorithm. The two methods were applied separately to a set of images from the Digital Database for Screening Mammography (DDSM) to obtain paired sets of mass candidates. The consensus mass candidates for each image were identified by a logical "and" operation of the two CADe algorithms so as to eliminate regions of suspicion that were not independently identified by both techniques. It was shown that by combining the evidence from the AFUM filter method with that obtained from bi-lateral subtraction, the same sensitivity could be reached with fewer false-positives per image relative to using the AFUM filter alone.

The development of a novel knowledge-based weaning algorithm using pulmonary parameters: a simulation study.

PubMed

Guler, Hasan; Kilic, Ugur

2018-03-01

Weaning is important for patients and clinicians who have to determine correct weaning time so that patients do not become addicted to the ventilator. There are already some predictors developed, such as the rapid shallow breathing index (RSBI), the pressure time index (PTI), and Jabour weaning index. Many important dimensions of weaning are sometimes ignored by these predictors. This is an attempt to develop a knowledge-based weaning process via fuzzy logic that eliminates the disadvantages of the present predictors. Sixteen vital parameters listed in published literature have been used to determine the weaning decisions in the developed system. Since there are considered to be too many individual parameters in it, related parameters were grouped together to determine acid-base balance, adequate oxygenation, adequate pulmonary function, hemodynamic stability, and the psychological status of the patients. To test the performance of the developed algorithm, 20 clinical scenarios were generated using Monte Carlo simulations and the Gaussian distribution method. The developed knowledge-based algorithm and RSBI predictor were applied to the generated scenarios. Finally, a clinician evaluated each clinical scenario independently. The Student's t test was used to show the statistical differences between the developed weaning algorithm, RSBI, and the clinician's evaluation. According to the results obtained, there were no statistical differences between the proposed methods and the clinician evaluations.

DAIDALUS: Detect and Avoid Alerting Logic for Unmanned Systems

NASA Technical Reports Server (NTRS)

Munoz, Cesar; Narkawicz, Anthony; Hagen, George; Upchurch, Jason; Dutle, Aaron; Consiglio, Maria; Chamberlain, James

2015-01-01

This paper presents DAIDALUS (Detect and Avoid Alerting Logic for Unmanned Systems), a reference implementation of a detect and avoid concept intended to support the integration of Unmanned Aircraft Systems into civil airspace. DAIDALUS consists of self-separation and alerting algorithms that provide situational awareness to UAS remote pilots. These algorithms have been formally specified in a mathematical notation and verified for correctness in an interactive theorem prover. The software implementation has been verified against the formal models and validated against multiple stressing cases jointly developed by the US Air Force Research Laboratory, MIT Lincoln Laboratory, and NASA. The DAIDALUS reference implementation is currently under consideration for inclusion in the appendices to the Minimum Operational Performance Standards for Unmanned Aircraft Systems presently being developed by RTCA Special Committee 228.

Method and apparatus for digitally based high speed x-ray spectrometer

DOEpatents

Warburton, W.K.; Hubbard, B.

1997-11-04

A high speed, digitally based, signal processing system which accepts input data from a detector-preamplifier and produces a spectral analysis of the x-rays illuminating the detector. The system achieves high throughputs at low cost by dividing the required digital processing steps between a ``hardwired`` processor implemented in combinatorial digital logic, which detects the presence of the x-ray signals in the digitized data stream and extracts filtered estimates of their amplitudes, and a programmable digital signal processing computer, which refines the filtered amplitude estimates and bins them to produce the desired spectral analysis. One set of algorithms allow this hybrid system to match the resolution of analog systems while operating at much higher data rates. A second set of algorithms implemented in the processor allow the system to be self calibrating as well. The same processor also handles the interface to an external control computer. 19 figs.

Method and apparatus for digitally based high speed x-ray spectrometer

DOEpatents

Warburton, William K.; Hubbard, Bradley

1997-01-01

A high speed, digitally based, signal processing system which accepts input data from a detector-preamplifier and produces a spectral analysis of the x-rays illuminating the detector. The system achieves high throughputs at low cost by dividing the required digital processing steps between a "hardwired" processor implemented in combinatorial digital logic, which detects the presence of the x-ray signals in the digitized data stream and extracts filtered estimates of their amplitudes, and a programmable digital signal processing computer, which refines the filtered amplitude estimates and bins them to produce the desired spectral analysis. One set of algorithms allow this hybrid system to match the resolution of analog systems while operating at much higher data rates. A second set of algorithms implemented in the processor allow the system to be self calibrating as well. The same processor also handles the interface to an external control computer.

A hybrid fuzzy logic and extreme learning machine for improving efficiency of circulating water systems in power generation plant

NASA Astrophysics Data System (ADS)

Aziz, Nur Liyana Afiqah Abdul; Siah Yap, Keem; Afif Bunyamin, Muhammad

2013-06-01

This paper presents a new approach of the fault detection for improving efficiency of circulating water system (CWS) in a power generation plant using a hybrid Fuzzy Logic System (FLS) and Extreme Learning Machine (ELM) neural network. The FLS is a mathematical tool for calculating the uncertainties where precision and significance are applied in the real world. It is based on natural language which has the ability of "computing the word". The ELM is an extremely fast learning algorithm for neural network that can completed the training cycle in a very short time. By combining the FLS and ELM, new hybrid model, i.e., FLS-ELM is developed. The applicability of this proposed hybrid model is validated in fault detection in CWS which may help to improve overall efficiency of power generation plant, hence, consuming less natural recourses and producing less pollutions.

FPGA implementation of predictive degradation model for engine oil lifetime

NASA Astrophysics Data System (ADS)

Idros, M. F. M.; Razak, A. H. A.; Junid, S. A. M. Al; Suliman, S. I.; Halim, A. K.

2018-03-01

This paper presents the implementation of linear regression model for degradation prediction on Register Transfer Logic (RTL) using QuartusII. A stationary model had been identified in the degradation trend for the engine oil in a vehicle in time series method. As for RTL implementation, the degradation model is written in Verilog HDL and the data input are taken at a certain time. Clock divider had been designed to support the timing sequence of input data. At every five data, a regression analysis is adapted for slope variation determination and prediction calculation. Here, only the negative value are taken as the consideration for the prediction purposes for less number of logic gate. Least Square Method is adapted to get the best linear model based on the mean values of time series data. The coded algorithm has been implemented on FPGA for validation purposes. The result shows the prediction time to change the engine oil.

WNN 92; Proceedings of the 3rd Workshop on Neural Networks: Academic/Industrial/NASA/Defense, Auburn Univ., AL, Feb. 10-12, 1992 and South Shore Harbour, TX, Nov. 4-6, 1992

NASA Technical Reports Server (NTRS)

Padgett, Mary L. (Editor)

1993-01-01

The present conference discusses such neural networks (NN) related topics as their current development status, NN architectures, NN learning rules, NN optimization methods, NN temporal models, NN control methods, NN pattern recognition systems and applications, biological and biomedical applications of NNs, VLSI design techniques for NNs, NN systems simulation, fuzzy logic, and genetic algorithms. Attention is given to missileborne integrated NNs, adaptive-mixture NNs, implementable learning rules, an NN simulator for travelling salesman problem solutions, similarity-based forecasting, NN control of hypersonic aircraft takeoff, NN control of the Space Shuttle Arm, an adaptive NN robot manipulator controller, a synthetic approach to digital filtering, NNs for speech analysis, adaptive spline networks, an anticipatory fuzzy logic controller, and encoding operations for fuzzy associative memories.

Stego on FPGA: An IWT Approach

PubMed Central

Ramalingam, Balakrishnan

2014-01-01

A reconfigurable hardware architecture for the implementation of integer wavelet transform (IWT) based adaptive random image steganography algorithm is proposed. The Haar-IWT was used to separate the subbands namely, LL, LH, HL, and HH, from 8 × 8 pixel blocks and the encrypted secret data is hidden in the LH, HL, and HH blocks using Moore and Hilbert space filling curve (SFC) scan patterns. Either Moore or Hilbert SFC was chosen for hiding the encrypted data in LH, HL, and HH coefficients, whichever produces the lowest mean square error (MSE) and the highest peak signal-to-noise ratio (PSNR). The fixated random walk's verdict of all blocks is registered which is nothing but the furtive key. Our system took 1.6 µs for embedding the data in coefficient blocks and consumed 34% of the logic elements, 22% of the dedicated logic register, and 2% of the embedded multiplier on Cyclone II field programmable gate array (FPGA). PMID:24723794

Evolutionary fuzzy modeling human diagnostic decisions.

PubMed

Peña-Reyes, Carlos Andrés

2004-05-01

Fuzzy CoCo is a methodology, combining fuzzy logic and evolutionary computation, for constructing systems able to accurately predict the outcome of a human decision-making process, while providing an understandable explanation of the underlying reasoning. Fuzzy logic provides a formal framework for constructing systems exhibiting both good numeric performance (accuracy) and linguistic representation (interpretability). However, fuzzy modeling--meaning the construction of fuzzy systems--is an arduous task, demanding the identification of many parameters. To solve it, we use evolutionary computation techniques (specifically cooperative coevolution), which are widely used to search for adequate solutions in complex spaces. We have successfully applied the algorithm to model the decision processes involved in two breast cancer diagnostic problems, the WBCD problem and the Catalonia mammography interpretation problem, obtaining systems both of high performance and high interpretability. For the Catalonia problem, an evolved system was embedded within a Web-based tool-called COBRA-for aiding radiologists in mammography interpretation.

Automated ILA design for synchronous sequential circuits

NASA Technical Reports Server (NTRS)

Liu, M. N.; Liu, K. Z.; Maki, G. K.; Whitaker, S. R.

1991-01-01

An iterative logic array (ILA) architecture for synchronous sequential circuits is presented. This technique utilizes linear algebra to produce the design equations. The ILA realization of synchronous sequential logic can be fully automated with a computer program. A programmable design procedure is proposed to fullfill the design task and layout generation. A software algorithm in the C language has been developed and tested to generate 1 micron CMOS layouts using the Hewlett-Packard FUNGEN module generator shell.

Fractal dimension and fuzzy logic systems for broken rotor bar detection in induction motors at start-up and steady-state regimes

NASA Astrophysics Data System (ADS)

Amezquita-Sanchez, Juan P.; Valtierra-Rodriguez, Martin; Perez-Ramirez, Carlos A.; Camarena-Martinez, David; Garcia-Perez, Arturo; Romero-Troncoso, Rene J.

2017-07-01

Squirrel-cage induction motors (SCIMs) are key machines in many industrial applications. In this regard, the monitoring of their operating condition aiming at avoiding damage and reducing economical losses has become a demanding task for industry. In the literature, several techniques and methodologies to detect faults that affect the integrity and performance of SCIMs have been proposed. However, they have only been focused on analyzing either the start-up transient or the steady-state operation regimes, two common operating scenarios in real practice. In this work, a novel methodology for broken rotor bar (BRB) detection in SCIMs during both start-up and steady-state operation regimes is proposed. It consists of two main steps. In the first one, the analysis of three-axis vibration signals using fractal dimension (FD) theory is carried out. Since different FD-based algorithms can give different results, three algorithms named Katz’ FD, Higuchi’s FD, and box dimension, are tested. In the second step, a fuzzy logic system for each regime is presented for automatic diagnosis. To validate the proposal, a motor with different damage levels has been tested: one with a partially BRB, a second with one fully BRB, and the third with two BRBs. The obtained results demonstrate the proposed effectiveness.

First-order logic theory for manipulating clinical practice guidelines applied to comorbid patients: a case study.

PubMed

Michalowski, Martin; Wilk, Szymon; Tan, Xing; Michalowski, Wojtek

2014-01-01

Clinical practice guidelines (CPGs) implement evidence-based medicine designed to help generate a therapy for a patient suffering from a single disease. When applied to a comorbid patient, the concurrent combination of treatment steps from multiple CPGs is susceptible to adverse interactions in the resulting combined therapy (i.e., a therapy established according to all considered CPGs). This inability to concurrently apply CPGs has been shown to be one of the key shortcomings of CPG uptake in a clinical setting1. Several research efforts are underway to address this issue such as the K4CARE2 and GuideLine INteraction Detection Assistant (GLINDA)3 projects and our previous research on applying constraint logic programming to developing a consistent combined therapy for a comorbid patient4. However, there is no generalized framework for mitigation that effectively captures general characteristics of the problem while handling nuances such as time and ordering requirements imposed by specific CPGs. In this paper we propose a first-order logic-based (FOL) approach for developing a generalized framework of mitigation. This approach uses a meta-algorithm and entailment properties to mitigate (i.e., identify and address) adverse interactions introduced by concurrently applied CPGs. We use an illustrative case study of a patient suffering from type 2 diabetes being treated for an onset of severe rheumatoid arthritis to show the expressiveness and robustness of our proposed FOL-based approach, and we discuss its appropriateness as the basis for the generalized theory.

Cb-LIKE - Thunderstorm forecasts up to six hours with fuzzy logic

NASA Astrophysics Data System (ADS)

Köhler, Martin; Tafferner, Arnold

2016-04-01

Thunderstorms with their accompanying effects like heavy rain, hail, or downdrafts cause delays and flight cancellations and therefore high additional cost for airlines and airport operators. A reliable thunderstorm forecast up to several hours could provide more time for decision makers in air traffic for an appropriate reaction on possible storm cells and initiation of adequate counteractions. To provide the required forecasts Cb-LIKE (Cumulonimbus-LIKElihood) has been developed at the DLR (Deutsches Zentrum für Luft- und Raumfahrt) Institute of Atmospheric Physics. The new algorithm is an automated system which designates areas with possible thunderstorm development by using model data of the COSMO-DE weather model, which is driven by the German Meteorological Service (DWD). A newly developed "Best-Member- Selection" method allows the automatic selection of that particular model run of a time-lagged COSMO- DE model ensemble, which matches best the current thunderstorm situation. Thereby the application of the best available data basis for the calculation of the thunderstorm forecasts by Cb-LIKE is ensured. Altogether there are four different modes for the selection of the best member. Four atmospheric parameters (CAPE, vertical wind velocity, radar reflectivity and cloud top temperature) of the model output are used within the algorithm. A newly developed fuzzy logic system enables the subsequent combination of the model parameters and the calculation of a thunderstorm indicator within a value range of 12 up to 88 for each grid point of the model domain for the following six hours in one hour intervals. The higher the indicator value the more the model parameters imply the development of thunderstorms. The quality of the Cb-LIKE thunderstorm forecasts was evaluated by a substantial verification using a neighborhood verification approach and multi-event contingency tables. The verification was performed for the whole summer period of 2012. On the basis of a deterministic object comparison with heavy precipitation cells observed by the radar-based thunderstorm tracking algorithm Rad-TRAM, several verification scores like BIAS, POD, FAR and CSI were calculated to identify possible advantages of the new algorithm. The presentation illustrates in detail the concept of the Cb-LIKE algorithm with regard to the fuzzy logic system and the Best-Member-Selection. Additionally some case studies and the most important results of the verification will be shown. The implementation of the forecasts into the DLR WxFUSION system, an user oriented forecasting system for air traffic, will also be included.

A computer method of finding valuations forcing validity of LC formulae

NASA Astrophysics Data System (ADS)

Godlewski, Łukasz; Świetorzecka, Kordula; Mulawka, Jan

2014-11-01

The purpose of this paper is to present the computer implementation of a system known as LC temporal logic [1]. Firstly, to become familiar with some theoretical issues, a short introduction to this logic is discussed. The algorithms allowing a deep analysis of the formulae of LC logic are considered. In particular we discuss how to determine if a formula is a tautology, contrtautology or it is satisfable. Next, we show how to find all valuations to satisfy the formula. Finally, we consider finding histories generated by the formula and transforming these histories into the state machine. Moreover, a description of the experiments that verify the implementation are briefly presented.

Switching Logic for Converting Off-grid PV Customers to On-grid by Utilizing Off-grid Inverter and Battery

NASA Astrophysics Data System (ADS)

Anishkumar, A. R.; Sreejaya, P.

2016-12-01

Kerala is a state in India having a very good potential for solar PV energy production. The domestic customers in Kerala using PV system are approximately 15 % and almost all of them are using the off-grid PV system. When these off grid customers move to on-grid system, off grid system accessories such as inverter and batteries become redundant. In this paper, a switching logic has been developed for the effective utilization of off grid accessories and reducing islanding power loss for on grid customers. An algorithm is proposed for the switching logic and it is verified using simulation results and hardware implementation.

LDPC decoder with a limited-precision FPGA-based floating-point multiplication coprocessor

NASA Astrophysics Data System (ADS)

Moberly, Raymond; O'Sullivan, Michael; Waheed, Khurram

2007-09-01

Implementing the sum-product algorithm, in an FPGA with an embedded processor, invites us to consider a tradeoff between computational precision and computational speed. The algorithm, known outside of the signal processing community as Pearl's belief propagation, is used for iterative soft-decision decoding of LDPC codes. We determined the feasibility of a coprocessor that will perform product computations. Our FPGA-based coprocessor (design) performs computer algebra with significantly less precision than the standard (e.g. integer, floating-point) operations of general purpose processors. Using synthesis, targeting a 3,168 LUT Xilinx FPGA, we show that key components of a decoder are feasible and that the full single-precision decoder could be constructed using a larger part. Soft-decision decoding by the iterative belief propagation algorithm is impacted both positively and negatively by a reduction in the precision of the computation. Reducing precision reduces the coding gain, but the limited-precision computation can operate faster. A proposed solution offers custom logic to perform computations with less precision, yet uses the floating-point format to interface with the software. Simulation results show the achievable coding gain. Synthesis results help theorize the the full capacity and performance of an FPGA-based coprocessor.

The myocardial microangiopathy in human and experimental diabetes mellitus. (A microscopic, ultrastructural, morphometric and computer-assisted symbolic-logic analysis).

PubMed

Taşcă, C; Stefăneanu, L; Vasilescu, C

1986-01-01

The following microscopical aspects were found in the small intramural arteries in the myocardium of 30 diabetic patients: endothelial proliferations with focal protuberances leading to partial narrowing of the lumen, increased thickness of the arterial wall due to fibrosis and accumulations of neutral mucopolysaccharides: alteration of elastic fibres. Morphometrically, the arterial wall thickness and the arterial diameter were increased whereas the arterial density decreased in the diabetic heart. In 25 rats with streptozotocin-induced diabetes the small intramyocardial arteries were investigated at 11 to 40 weeks of diabetic state. Using morphometrical analysis a constant increase of arterial wall thickness paralleling the diabetes duration was found. Microscopically, the lesions consist in endothelial proliferation with bridging across the vascular lumen and slight perivascular and diffuse fibrosis. Ultrastructurally, the capillary basal lamina was thickened in the diabetic myocardium. In order to investigate the morphometrical data we used symbolic-logic as a decision method, by applying an original computer program based on the Quine-McCluskey algorithm. All our results together with the final symbolic-logic expression suggest that damage of the small intramyocardial arteries plays an important role in the pathogenesis of diabetic cardiomyopathy.

Design Considerations for a Computationally-Lightweight Authentication Mechanism for Passive RFID Tags

DTIC Science & Technology

2009-09-01

suffer the power and complexity requirements of a public key system. 28 In [18], a simulation of the SHA –1 algorithm is performed on a Xilinx FPGA ... 256 bits. Thus, the construction of a hash table would need 2512 independent comparisons. It is known that hash collisions of the SHA –1 algorithm... SHA –1 algorithm for small-core FPGA design. Small-core FPGA design is the process by which a circuit is adapted to use the minimal amount of logic

Plasmid mapping computer program.

PubMed Central

Nolan, G P; Maina, C V; Szalay, A A

1984-01-01

Three new computer algorithms are described which rapidly order the restriction fragments of a plasmid DNA which has been cleaved with two restriction endonucleases in single and double digestions. Two of the algorithms are contained within a single computer program (called MPCIRC). The Rule-Oriented algorithm, constructs all logical circular map solutions within sixty seconds (14 double-digestion fragments) when used in conjunction with the Permutation method. The program is written in Apple Pascal and runs on an Apple II Plus Microcomputer with 64K of memory. A third algorithm is described which rapidly maps double digests and uses the above two algorithms as adducts. Modifications of the algorithms for linear mapping are also presented. PMID:6320105

Decision support system for triage management: A hybrid approach using rule-based reasoning and fuzzy logic.

PubMed

Dehghani Soufi, Mahsa; Samad-Soltani, Taha; Shams Vahdati, Samad; Rezaei-Hachesu, Peyman

2018-06-01

Fast and accurate patient triage for the response process is a critical first step in emergency situations. This process is often performed using a paper-based mode, which intensifies workload and difficulty, wastes time, and is at risk of human errors. This study aims to design and evaluate a decision support system (DSS) to determine the triage level. A combination of the Rule-Based Reasoning (RBR) and Fuzzy Logic Classifier (FLC) approaches were used to predict the triage level of patients according to the triage specialist's opinions and Emergency Severity Index (ESI) guidelines. RBR was applied for modeling the first to fourth decision points of the ESI algorithm. The data relating to vital signs were used as input variables and modeled using fuzzy logic. Narrative knowledge was converted to If-Then rules using XML. The extracted rules were then used to create the rule-based engine and predict the triage levels. Fourteen RBR and 27 fuzzy rules were extracted and used in the rule-based engine. The performance of the system was evaluated using three methods with real triage data. The accuracy of the clinical decision support systems (CDSSs; in the test data) was 99.44%. The evaluation of the error rate revealed that, when using the traditional method, 13.4% of the patients were miss-triaged, which is statically significant. The completeness of the documentation also improved from 76.72% to 98.5%. Designed system was effective in determining the triage level of patients and it proved helpful for nurses as they made decisions, generated nursing diagnoses based on triage guidelines. The hybrid approach can reduce triage misdiagnosis in a highly accurate manner and improve the triage outcomes. Copyright © 2018 Elsevier B.V. All rights reserved.

Mamdani Fuzzy System for Indoor Autonomous Mobile Robot

NASA Astrophysics Data System (ADS)

Khan, M. K. A. Ahamed; Rashid, Razif; Elamvazuthi, I.

2011-06-01

Several control algorithms for autonomous mobile robot navigation have been proposed in the literature. Recently, the employment of non-analytical methods of computing such as fuzzy logic, evolutionary computation, and neural networks has demonstrated the utility and potential of these paradigms for intelligent control of mobile robot navigation. In this paper, Mamdani fuzzy system for an autonomous mobile robot is developed. The paper begins with the discussion on the conventional controller and then followed by the description of fuzzy logic controller in detail.

Efficient dynamic optimization of logic programs

NASA Technical Reports Server (NTRS)

Laird, Phil

1992-01-01

A summary is given of the dynamic optimization approach to speed up learning for logic programs. The problem is to restructure a recursive program into an equivalent program whose expected performance is optimal for an unknown but fixed population of problem instances. We define the term 'optimal' relative to the source of input instances and sketch an algorithm that can come within a logarithmic factor of optimal with high probability. Finally, we show that finding high-utility unfolding operations (such as EBG) can be reduced to clause reordering.

Motivation for DOC III: 64-bit digital optical computer

NASA Astrophysics Data System (ADS)

Guilfoyle, Peter S.

1991-09-01

This paper suggests a new class of digital logic. OptiComp has focused on a digital optical logic family in order to capitalize on the inherent benefits of optical computing, which include (1) high FAN-IN and FAN-OUT, (2) low power consumption, (3) high noise margin, (4) high algorithmic efficiency using 'smart' interconnects, (5) free space leverage of GIBP (gate interconnect bandwidth product). Other well-known secondary advantages of optical logic include (but are not limited to) zero capacitive loading of signals at a detector, zero cross-talk between signals, zero signal dispersion, minimal clock skew (a few picoseconds or less in an imaging system). The primary focus of this paper is to demonstrate how each of the five advantages can be used to leverage other logic family performance such as GaAs; the secondary attributes will be discussed only in the context of introducing the DOC III architecture.

Motivation for DOC III: 64-bit digital optical computer

NASA Astrophysics Data System (ADS)

Guilfoyle, Peter S.

1991-09-01

The objective of this paper is to motivate a new class of digital logic. OptiComp has focused on a digital optical logic family in order to capitalize on the inherent benefits of optical computing, which include: (1) high FAN-IN and FAN-OUT, (2) low power consumption, (3) high noise margin, (4) high algorithmic efficiency using 'smart' interconnects, (5) free space leverage of GIBP (gate interconnect bandwidth product). Other well-known secondary advantages of optical logic include (but are not limited to): zero capacitive loading of signals at a detector, zero cross-talk between signals, zero signal dispersion, and minimal clock skew (a few picoseconds or less in an imaging system). The primary focus of this paper is on demonstrating how each of the five advantages can be used to leverage other logic family performance such as GaAs; the secondary attributes will be discussed only in the context of introducing the DOC III architecture.

Molecular system identification for enzyme directed evolution and design

NASA Astrophysics Data System (ADS)

Guan, Xiangying; Chakrabarti, Raj

2017-09-01

The rational design of chemical catalysts requires methods for the measurement of free energy differences in the catalytic mechanism for any given catalyst Hamiltonian. The scope of experimental learning algorithms that can be applied to catalyst design would also be expanded by the availability of such methods. Methods for catalyst characterization typically either estimate apparent kinetic parameters that do not necessarily correspond to free energy differences in the catalytic mechanism or measure individual free energy differences that are not sufficient for establishing the relationship between the potential energy surface and catalytic activity. Moreover, in order to enhance the duty cycle of catalyst design, statistically efficient methods for the estimation of the complete set of free energy differences relevant to the catalytic activity based on high-throughput measurements are preferred. In this paper, we present a theoretical and algorithmic system identification framework for the optimal estimation of free energy differences in solution phase catalysts, with a focus on one- and two-substrate enzymes. This framework, which can be automated using programmable logic, prescribes a choice of feasible experimental measurements and manipulated input variables that identify the complete set of free energy differences relevant to the catalytic activity and minimize the uncertainty in these free energy estimates for each successive Hamiltonian design. The framework also employs decision-theoretic logic to determine when model reduction can be applied to improve the duty cycle of high-throughput catalyst design. Automation of the algorithm using fluidic control systems is proposed, and applications of the framework to the problem of enzyme design are discussed.

‘Toning’ up hypotonia assessment: A proposal and critique

PubMed Central

Joubert, Robin W.E.

2016-01-01

Background Clinical assessment of hypotonia is challenging due to the subjective nature of the initial clinical evaluation. This poses dilemmas for practitioners in gaining accuracy, given that the presentation of hypotonia can be either a non-threatening or malevolent sign. The research question posed was how clinical assessment can be improved, given the current contentions expressed in the scientific literature. Objectives This paper describes the development and critique of a clinical algorithm to aid the assessment of hypotonia. Methods An initial exploratory sequential phase, consisting of a systematic review, a survey amongst clinicians and a Delphi process, assisted in the development of the algorithm, which is presented within the framework of the International Classification of Functioning, Disability and Health. The ensuing critique followed a qualitative emergent–systematic focus group design with a purposive sample of 59 clinicians. Data were analysed using semantical content analysis and are presented thematically with analytical considerations. Results This study culminated in the development of an evidence-based clinical algorithm for practice. The qualitative critique of the algorithm considered aspects such as inadequacies, misconceptions and omissions; strengths; clinical use; resource implications; and recommendations. Conclusions The first prototype and critique of a clinical algorithm to assist the clinical assessment of hypotonia in children has been described. Barriers highlighted include aspects related to knowledge gaps of clinicians, issues around user-friendliness and formatting concerns. Strengths identified by the critique included aspects related to the evidence-based nature of the criteria within the algorithm, the suitability of the algorithm in being merged or extending current practice, the potential of the algorithm in aiding more accurate decision-making, the suitability of the algorithm across age groups and the logical flow. These findings provide a starting point towards ascertaining the clinical utility of the algorithm as an essential step towards evidence-based praxis. PMID:28730054

Parallel image logical operations using cross correlation

NASA Technical Reports Server (NTRS)

Strong, J. P., III

1972-01-01

Methods are presented for counting areas in an image in a parallel manner using noncoherent optical techniques. The techniques presented include the Levialdi algorithm for counting, optical techniques for binary operations, and cross-correlation.

Multi-strategy coevolving aging particle optimization.

PubMed

Iacca, Giovanni; Caraffini, Fabio; Neri, Ferrante

2014-02-01

We propose Multi-Strategy Coevolving Aging Particles (MS-CAP), a novel population-based algorithm for black-box optimization. In a memetic fashion, MS-CAP combines two components with complementary algorithm logics. In the first stage, each particle is perturbed independently along each dimension with a progressively shrinking (decaying) radius, and attracted towards the current best solution with an increasing force. In the second phase, the particles are mutated and recombined according to a multi-strategy approach in the fashion of the ensemble of mutation strategies in Differential Evolution. The proposed algorithm is tested, at different dimensionalities, on two complete black-box optimization benchmarks proposed at the Congress on Evolutionary Computation 2010 and 2013. To demonstrate the applicability of the approach, we also test MS-CAP to train a Feedforward Neural Network modeling the kinematics of an 8-link robot manipulator. The numerical results show that MS-CAP, for the setting considered in this study, tends to outperform the state-of-the-art optimization algorithms on a large set of problems, thus resulting in a robust and versatile optimizer.

A vector-based failure detection and isolation algorithm for a dual fail-operational redundant strapdown inertial measurement unit

NASA Technical Reports Server (NTRS)

Morrell, Frederick R.; Bailey, Melvin L.

1987-01-01

A vector-based failure detection and isolation technique for a skewed array of two degree-of-freedom inertial sensors is developed. Failure detection is based on comparison of parity equations with a threshold, and isolation is based on comparison of logic variables which are keyed to pass/fail results of the parity test. A multi-level approach to failure detection is used to ensure adequate coverage for the flight control, display, and navigation avionics functions. Sensor error models are introduced to expose the susceptibility of the parity equations to sensor errors and physical separation effects. The algorithm is evaluated in a simulation of a commercial transport operating in a range of light to severe turbulence environments. A bias-jump failure level of 0.2 deg/hr was detected and isolated properly in the light and moderate turbulence environments, but not detected in the extreme turbulence environment. An accelerometer bias-jump failure level of 1.5 milli-g was detected over all turbulence environments. For both types of inertial sensor, hard-over, and null type failures were detected in all environments without incident. The algorithm functioned without false alarm or isolation over all turbulence environments for the runs tested.

Integrating fuzzy object based image analysis and ant colony optimization for road extraction from remotely sensed images

NASA Astrophysics Data System (ADS)

Maboudi, Mehdi; Amini, Jalal; Malihi, Shirin; Hahn, Michael

2018-04-01

Updated road network as a crucial part of the transportation database plays an important role in various applications. Thus, increasing the automation of the road extraction approaches from remote sensing images has been the subject of extensive research. In this paper, we propose an object based road extraction approach from very high resolution satellite images. Based on the object based image analysis, our approach incorporates various spatial, spectral, and textural objects' descriptors, the capabilities of the fuzzy logic system for handling the uncertainties in road modelling, and the effectiveness and suitability of ant colony algorithm for optimization of network related problems. Four VHR optical satellite images which are acquired by Worldview-2 and IKONOS satellites are used in order to evaluate the proposed approach. Evaluation of the extracted road networks shows that the average completeness, correctness, and quality of the results can reach 89%, 93% and 83% respectively, indicating that the proposed approach is applicable for urban road extraction. We also analyzed the sensitivity of our algorithm to different ant colony optimization parameter values. Comparison of the achieved results with the results of four state-of-the-art algorithms and quantifying the robustness of the fuzzy rule set demonstrate that the proposed approach is both efficient and transferable to other comparable images.

Real-time plasma control based on the ISTTOK tomography diagnostica)

NASA Astrophysics Data System (ADS)

Carvalho, P. J.; Carvalho, B. B.; Neto, A.; Coelho, R.; Fernandes, H.; Sousa, J.; Varandas, C.; Chávez-Alarcón, E.; Herrera-Velázquez, J. J. E.

2008-10-01

The presently available processing power in generic processing units (GPUs) combined with state-of-the-art programmable logic devices benefits the implementation of complex, real-time driven, data processing algorithms for plasma diagnostics. A tomographic reconstruction diagnostic has been developed for the ISTTOK tokamak, based on three linear pinhole cameras each with ten lines of sight. The plasma emissivity in a poloidal cross section is computed locally on a submillisecond time scale, using a Fourier-Bessel algorithm, allowing the use of the output signals for active plasma position control. The data acquisition and reconstruction (DAR) system is based on ATCA technology and consists of one acquisition board with integrated field programmable gate array (FPGA) capabilities and a dual-core Pentium module running real-time application interface (RTAI) Linux. In this paper, the DAR real-time firmware/software implementation is presented, based on (i) front-end digital processing in the FPGA; (ii) a device driver specially developed for the board which enables streaming data acquisition to the host GPU; and (iii) a fast reconstruction algorithm running in Linux RTAI. This system behaves as a module of the central ISTTOK control and data acquisition system (FIRESIGNAL). Preliminary results of the above experimental setup are presented and a performance benchmarking against the magnetic coil diagnostic is shown.

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.

Memory-Intensive Benchmarks: IRAM vs. Cache-Based Machines

NASA Technical Reports Server (NTRS)

Biswas, Rupak; Gaeke, Brian R.; Husbands, Parry; Li, Xiaoye S.; Oliker, Leonid; Yelick, Katherine A.; Biegel, Bryan (Technical Monitor)

2002-01-01

The increasing gap between processor and memory performance has lead to new architectural models for memory-intensive applications. In this paper, we explore the performance of a set of memory-intensive benchmarks and use them to compare the performance of conventional cache-based microprocessors to a mixed logic and DRAM processor called VIRAM. The benchmarks are based on problem statements, rather than specific implementations, and in each case we explore the fundamental hardware requirements of the problem, as well as alternative algorithms and data structures that can help expose fine-grained parallelism or simplify memory access patterns. The benchmarks are characterized by their memory access patterns, their basic control structures, and the ratio of computation to memory operation.

Circuit for high resolution decoding of multi-anode microchannel array detectors

NASA Technical Reports Server (NTRS)

Kasle, David B. (Inventor)

1995-01-01

A circuit for high resolution decoding of multi-anode microchannel array detectors consisting of input registers accepting transient inputs from the anode array; anode encoding logic circuits connected to the input registers; midpoint pipeline registers connected to the anode encoding logic circuits; and pixel decoding logic circuits connected to the midpoint pipeline registers is described. A high resolution algorithm circuit operates in parallel with the pixel decoding logic circuit and computes a high resolution least significant bit to enhance the multianode microchannel array detector's spatial resolution by halving the pixel size and doubling the number of pixels in each axis of the anode array. A multiplexer is connected to the pixel decoding logic circuit and allows a user selectable pixel address output according to the actual multi-anode microchannel array detector anode array size. An output register concatenates the high resolution least significant bit onto the standard ten bit pixel address location to provide an eleven bit pixel address, and also stores the full eleven bit pixel address. A timing and control state machine is connected to the input registers, the anode encoding logic circuits, and the output register for managing the overall operation of the circuit.

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.

Recent advances in nonlinear implicit, electrostatic particle-in-cell (PIC) algorithms

NASA Astrophysics Data System (ADS)

Chen, Guangye; Chacón, Luis; Barnes, Daniel

2012-10-01

An implicit 1D electrostatic PIC algorithmfootnotetextChen, Chac'on, Barnes, J. Comput. Phys. 230 (2011) has been developed that satisfies exact energy and charge conservation. The algorithm employs a kinetic-enslaved Jacobian-free Newton-Krylov methodfootnotetextIbid. that ensures nonlinear convergence while taking timesteps comparable to the dynamical timescale of interest. Here we present two main improvements of the algorithm. The first is the formulation of a preconditioner based on linearized fluid equations, which are closed using available particle information. The computational benefit is that solving the fluid system is much cheaper than the kinetic one. The effectiveness of the preconditioner in accelerating nonlinear iterations on challenging problems will be demonstrated. A second improvement is the generalization of Ref. 1 to curvilinear meshes,footnotetextChac'on, Chen, Barnes, J. Comput. Phys. submitted (2012) with a hybrid particle update of positions and velocities in logical and physical space respectively.footnotetextSwift, J. Comp. Phys., 126 (1996) The curvilinear algorithm remains exactly charge and energy-conserving, and can be extended to multiple dimensions. We demonstrate the accuracy and efficiency of the algorithm with a 1D ion-acoustic shock wave simulation.

Optimized design of embedded DSP system hardware supporting complex algorithms

NASA Astrophysics Data System (ADS)

Li, Yanhua; Wang, Xiangjun; Zhou, Xinling

2003-09-01

The paper presents an optimized design method for a flexible and economical embedded DSP system that can implement complex processing algorithms as biometric recognition, real-time image processing, etc. It consists of a floating-point DSP, 512 Kbytes data RAM, 1 Mbytes FLASH program memory, a CPLD for achieving flexible logic control of input channel and a RS-485 transceiver for local network communication. Because of employing a high performance-price ratio DSP TMS320C6712 and a large FLASH in the design, this system permits loading and performing complex algorithms with little algorithm optimization and code reduction. The CPLD provides flexible logic control for the whole DSP board, especially in input channel, and allows convenient interface between different sensors and DSP system. The transceiver circuit can transfer data between DSP and host computer. In the paper, some key technologies are also introduced which make the whole system work efficiently. Because of the characters referred above, the hardware is a perfect flat for multi-channel data collection, image processing, and other signal processing with high performance and adaptability. The application section of this paper presents how this hardware is adapted for the biometric identification system with high identification precision. The result reveals that this hardware is easy to interface with a CMOS imager and is capable of carrying out complex biometric identification algorithms, which require real-time process.

An adaptive neuro fuzzy inference system controlled space cector pulse width modulation based HVDC light transmission system under AC fault conditions

NASA Astrophysics Data System (ADS)

Ajay Kumar, M.; Srikanth, N. V.

2014-03-01

In HVDC Light transmission systems, converter control is one of the major fields of present day research works. In this paper, fuzzy logic controller is utilized for controlling both the converters of the space vector pulse width modulation (SVPWM) based HVDC Light transmission systems. Due to its complexity in the rule base formation, an intelligent controller known as adaptive neuro fuzzy inference system (ANFIS) controller is also introduced in this paper. The proposed ANFIS controller changes the PI gains automatically for different operating conditions. A hybrid learning method which combines and exploits the best features of both the back propagation algorithm and least square estimation method is used to train the 5-layer ANFIS controller. The performance of the proposed ANFIS controller is compared and validated with the fuzzy logic controller and also with the fixed gain conventional PI controller. The simulations are carried out in the MATLAB/SIMULINK environment. The results reveal that the proposed ANFIS controller is reducing power fluctuations at both the converters. It also improves the dynamic performance of the test power system effectively when tested for various ac fault conditions.

Fuzzy-Logic Based Distributed Energy-Efficient Clustering Algorithm for Wireless Sensor Networks.

PubMed

Zhang, Ying; Wang, Jun; Han, Dezhi; Wu, Huafeng; Zhou, Rundong

2017-07-03

Due to the high-energy efficiency and scalability, the clustering routing algorithm has been widely used in wireless sensor networks (WSNs). In order to gather information more efficiently, each sensor node transmits data to its Cluster Head (CH) to which it belongs, by multi-hop communication. However, the multi-hop communication in the cluster brings the problem of excessive energy consumption of the relay nodes which are closer to the CH. These nodes' energy will be consumed more quickly than the farther nodes, which brings the negative influence on load balance for the whole networks. Therefore, we propose an energy-efficient distributed clustering algorithm based on fuzzy approach with non-uniform distribution (EEDCF). During CHs' election, we take nodes' energies, nodes' degree and neighbor nodes' residual energies into consideration as the input parameters. In addition, we take advantage of Takagi, Sugeno and Kang (TSK) fuzzy model instead of traditional method as our inference system to guarantee the quantitative analysis more reasonable. In our scheme, each sensor node calculates the probability of being as CH with the help of fuzzy inference system in a distributed way. The experimental results indicate EEDCF algorithm is better than some current representative methods in aspects of data transmission, energy consumption and lifetime of networks.

AutoBayes Program Synthesis System System Internals

NASA Technical Reports Server (NTRS)

Schumann, Johann Martin

2011-01-01

This lecture combines the theoretical background of schema based program synthesis with the hands-on study of a powerful, open-source program synthesis system (Auto-Bayes). Schema-based program synthesis is a popular approach toward program synthesis. The lecture will provide an introduction into this topic and discuss how this technology can be used to generate customized algorithms. The synthesis of advanced numerical algorithms requires the availability of a powerful symbolic (algebra) system. Its task is to symbolically solve equations, simplify expressions, or to symbolically calculate derivatives (among others) such that the synthesized algorithms become as efficient as possible. We will discuss the use and importance of the symbolic system for synthesis. Any synthesis system is a large and complex piece of code. In this lecture, we will study Autobayes in detail. AutoBayes has been developed at NASA Ames and has been made open source. It takes a compact statistical specification and generates a customized data analysis algorithm (in C/C++) from it. AutoBayes is written in SWI Prolog and many concepts from rewriting, logic, functional, and symbolic programming. We will discuss the system architecture, the schema libary and the extensive support infra-structure. Practical hands-on experiments and exercises will enable the student to get insight into a realistic program synthesis system and provides knowledge to use, modify, and extend Autobayes.

LibKiSAO: a Java library for Querying KiSAO.

PubMed

Zhukova, Anna; Adams, Richard; Laibe, Camille; Le Novère, Nicolas

2012-09-24

The Kinetic Simulation Algorithm Ontology (KiSAO) supplies information about existing algorithms available for the simulation of Systems Biology models, their characteristics, parameters and inter-relationships. KiSAO enables the unambiguous identification of algorithms from simulation descriptions. Information about analogous methods having similar characteristics and about algorithm parameters incorporated into KiSAO is desirable for simulation tools. To retrieve this information programmatically an application programming interface (API) for KiSAO is needed. We developed libKiSAO, a Java library to enable querying of the KiSA Ontology. It implements methods to retrieve information about simulation algorithms stored in KiSAO, their characteristics and parameters, and methods to query the algorithm hierarchy and search for similar algorithms providing comparable results for the same simulation set-up. Using libKiSAO, simulation tools can make logical inferences based on this knowledge and choose the most appropriate algorithm to perform a simulation. LibKiSAO also enables simulation tools to handle a wider range of simulation descriptions by determining which of the available methods are similar and can be used instead of the one indicated in the simulation description if that one is not implemented. LibKiSAO enables Java applications to easily access information about simulation algorithms, their characteristics and parameters stored in the OWL-encoded Kinetic Simulation Algorithm Ontology. LibKiSAO can be used by simulation description editors and simulation tools to improve reproducibility of computational simulation tasks and facilitate model re-use.

Optical pattern recognition algorithms on neural-logic equivalent models and demonstration of their prospects and possible implementations

NASA Astrophysics Data System (ADS)

Krasilenko, Vladimir G.; Nikolsky, Alexander I.; Zaitsev, Alexandr V.; Voloshin, Victor M.

2001-03-01

Historic information regarding the appearance and creation of fundamentals of algebra-logical apparatus-`equivalental algebra' for description of neuro-nets paradigms and algorithms is considered which is unification of theory of neuron nets (NN), linear algebra and the most generalized neuro-biology extended for matrix case. A survey is given of `equivalental models' of neuron nets and associative memory is suggested new, modified matrix-tenzor neurological equivalental models (MTNLEMS) are offered with double adaptive-equivalental weighing (DAEW) for spatial-non- invariant recognition (SNIR) and space-invariant recognition (SIR) of 2D images (patterns). It is shown, that MTNLEMS DAEW are the most generalized, they can describe the processes in NN both within the frames of known paradigms and within new `equivalental' paradigm of non-interaction type, and the computing process in NN under using the offered MTNLEMs DAEW is reduced to two-step and multi-step algorithms and step-by-step matrix-tenzor procedures (for SNIR) and procedures of defining of space-dependent equivalental functions from two images (for SIR).

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.

HYTESS 2: A Hypothetical Turbofan Engine Simplified Simulation with multivariable control and sensor analytical redundancy

NASA Technical Reports Server (NTRS)

Merrill, W. C.

1986-01-01

A hypothetical turbofan engine simplified simulation with a multivariable control and sensor failure detection, isolation, and accommodation logic (HYTESS II) is presented. The digital program, written in FORTRAN, is self-contained, efficient, realistic and easily used. Simulated engine dynamics were developed from linearized operating point models. However, essential nonlinear effects are retained. The simulation is representative of the hypothetical, low bypass ratio turbofan engine with an advanced control and failure detection logic. Included is a description of the engine dynamics, the control algorithm, and the sensor failure detection logic. Details of the simulation including block diagrams, variable descriptions, common block definitions, subroutine descriptions, and input requirements are given. Example simulation results are also presented.

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.

Simulation and Verification of Synchronous Set Relations in Rewriting Logic

NASA Technical Reports Server (NTRS)

Rocha, Camilo; Munoz, Cesar A.

2011-01-01

This paper presents a mathematical foundation and a rewriting logic infrastructure for the execution and property veri cation of synchronous set relations. The mathematical foundation is given in the language of abstract set relations. The infrastructure consists of an ordersorted rewrite theory in Maude, a rewriting logic system, that enables the synchronous execution of a set relation provided by the user. By using the infrastructure, existing algorithm veri cation techniques already available in Maude for traditional asynchronous rewriting, such as reachability analysis and model checking, are automatically available to synchronous set rewriting. The use of the infrastructure is illustrated with an executable operational semantics of a simple synchronous language and the veri cation of temporal properties of a synchronous system.

Mission Analysis Program for Solar Electric Propulsion (MAPSEP). Volume 3: Program manual

NASA Technical Reports Server (NTRS)

Huling, K. R.; Boain, R. J.; Wilson, T.; Hong, P. E.; Shults, G. L.

1974-01-01

The internal structure of MAPSEP is described. Topics discussed include: macrologic, variable definition, subroutines, and logical flow. Information is given to facilitate modifications to the models and algorithms of MAPSEP.

Development of a meta-algorithm for guiding primary care encounters for patients with multimorbidity using evidence-based and case-based guideline development methodology.

PubMed

Muche-Borowski, Cathleen; Lühmann, Dagmar; Schäfer, Ingmar; Mundt, Rebekka; Wagner, Hans-Otto; Scherer, Martin

2017-06-22

The study aimed to develop a comprehensive algorithm (meta-algorithm) for primary care encounters of patients with multimorbidity. We used a novel, case-based and evidence-based procedure to overcome methodological difficulties in guideline development for patients with complex care needs. Systematic guideline development methodology including systematic evidence retrieval (guideline synopses), expert opinions and informal and formal consensus procedures. Primary care. The meta-algorithm was developed in six steps:1. Designing 10 case vignettes of patients with multimorbidity (common, epidemiologically confirmed disease patterns and/or particularly challenging health care needs) in a multidisciplinary workshop.2. Based on the main diagnoses, a systematic guideline synopsis of evidence-based and consensus-based clinical practice guidelines was prepared. The recommendations were prioritised according to the clinical and psychosocial characteristics of the case vignettes.3. Case vignettes along with the respective guideline recommendations were validated and specifically commented on by an external panel of practicing general practitioners (GPs).4. Guideline recommendations and experts' opinions were summarised as case specific management recommendations (N-of-one guidelines).5. Healthcare preferences of patients with multimorbidity were elicited from a systematic literature review and supplemented with information from qualitative interviews.6. All N-of-one guidelines were analysed using pattern recognition to identify common decision nodes and care elements. These elements were put together to form a generic meta-algorithm. The resulting meta-algorithm reflects the logic of a GP's encounter of a patient with multimorbidity regarding decision-making situations, communication needs and priorities. It can be filled with the complex problems of individual patients and hereby offer guidance to the practitioner. Contrary to simple, symptom-oriented algorithms, the meta-algorithm illustrates a superordinate process that permanently keeps the entire patient in view. The meta-algorithm represents the back bone of the multimorbidity guideline of the German College of General Practitioners and Family Physicians. This article presents solely the development phase; the meta-algorithm needs to be piloted before it can be implemented. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Performance comparison of attitude determination, attitude estimation, and nonlinear observers algorithms

NASA Astrophysics Data System (ADS)

MOHAMMED, M. A. SI; BOUSSADIA, H.; BELLAR, A.; ADNANE, A.

2017-01-01

This paper presents a brief synthesis and useful performance analysis of different attitude filtering algorithms (attitude determination algorithms, attitude estimation algorithms, and nonlinear observers) applied to Low Earth Orbit Satellite in terms of accuracy, convergence time, amount of memory, and computation time. This latter is calculated in two ways, using a personal computer and also using On-board computer 750 (OBC 750) that is being used in many SSTL Earth observation missions. The use of this comparative study could be an aided design tool to the designer to choose from an attitude determination or attitude estimation or attitude observer algorithms. The simulation results clearly indicate that the nonlinear Observer is the more logical choice.

I-Ching, dyadic groups of binary numbers and the geno-logic coding in living bodies.

PubMed

Hu, Zhengbing; Petoukhov, Sergey V; Petukhova, Elena S

2017-12-01

The ancient Chinese book I-Ching was written a few thousand years ago. It introduces the system of symbols Yin and Yang (equivalents of 0 and 1). It had a powerful impact on culture, medicine and science of ancient China and several other countries. From the modern standpoint, I-Ching declares the importance of dyadic groups of binary numbers for the Nature. The system of I-Ching is represented by the tables with dyadic groups of 4 bigrams, 8 trigrams and 64 hexagrams, which were declared as fundamental archetypes of the Nature. The ancient Chinese did not know about the genetic code of protein sequences of amino acids but this code is organized in accordance with the I-Ching: in particularly, the genetic code is constructed on DNA molecules using 4 nitrogenous bases, 16 doublets, and 64 triplets. The article also describes the usage of dyadic groups as a foundation of the bio-mathematical doctrine of the geno-logic code, which exists in parallel with the known genetic code of amino acids but serves for a different goal: to code the inherited algorithmic processes using the logical holography and the spectral logic of systems of genetic Boolean functions. Some relations of this doctrine with the I-Ching are discussed. In addition, the ratios of musical harmony that can be revealed in the parameters of DNA structure are also represented in the I-Ching book. Copyright © 2017 Elsevier Ltd. All rights reserved.

Uncertain decision tree inductive inference

NASA Astrophysics Data System (ADS)

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

2011-10-01

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

A Hybrid alldifferent-Tabu Search Algorithm for Solving Sudoku Puzzles

PubMed Central

Crawford, Broderick; Paredes, Fernando; Norero, Enrique

2015-01-01

The Sudoku problem is a well-known logic-based puzzle of combinatorial number-placement. It consists in filling a n 2 × n 2 grid, composed of n columns, n rows, and n subgrids, each one containing distinct integers from 1 to n 2. Such a puzzle belongs to the NP-complete collection of problems, to which there exist diverse exact and approximate methods able to solve it. In this paper, we propose a new hybrid algorithm that smartly combines a classic tabu search procedure with the alldifferent global constraint from the constraint programming world. The alldifferent constraint is known to be efficient for domain filtering in the presence of constraints that must be pairwise different, which are exactly the kind of constraints that Sudokus own. This ability clearly alleviates the work of the tabu search, resulting in a faster and more robust approach for solving Sudokus. We illustrate interesting experimental results where our proposed algorithm outperforms the best results previously reported by hybrids and approximate methods. PMID:26078751

A Hybrid alldifferent-Tabu Search Algorithm for Solving Sudoku Puzzles.

PubMed

Soto, Ricardo; Crawford, Broderick; Galleguillos, Cristian; Paredes, Fernando; Norero, Enrique

2015-01-01

The Sudoku problem is a well-known logic-based puzzle of combinatorial number-placement. It consists in filling a n(2) × n(2) grid, composed of n columns, n rows, and n subgrids, each one containing distinct integers from 1 to n(2). Such a puzzle belongs to the NP-complete collection of problems, to which there exist diverse exact and approximate methods able to solve it. In this paper, we propose a new hybrid algorithm that smartly combines a classic tabu search procedure with the alldifferent global constraint from the constraint programming world. The alldifferent constraint is known to be efficient for domain filtering in the presence of constraints that must be pairwise different, which are exactly the kind of constraints that Sudokus own. This ability clearly alleviates the work of the tabu search, resulting in a faster and more robust approach for solving Sudokus. We illustrate interesting experimental results where our proposed algorithm outperforms the best results previously reported by hybrids and approximate methods.

Different types of maximum power point tracking techniques for renewable energy systems: A survey

NASA Astrophysics Data System (ADS)

Khan, Mohammad Junaid; Shukla, Praveen; Mustafa, Rashid; Chatterji, S.; Mathew, Lini

2016-03-01

Global demand for electricity is increasing while production of energy from fossil fuels is declining and therefore the obvious choice of the clean energy source that is abundant and could provide security for development future is energy from the sun. In this paper, the characteristic of the supply voltage of the photovoltaic generator is nonlinear and exhibits multiple peaks, including many local peaks and a global peak in non-uniform irradiance. To keep global peak, MPPT is the important component of photovoltaic systems. Although many review articles discussed conventional techniques such as P & O, incremental conductance, the correlation ripple control and very few attempts have been made with intelligent MPPT techniques. This document also discusses different algorithms based on fuzzy logic, Ant Colony Optimization, Genetic Algorithm, artificial neural networks, Particle Swarm Optimization Algorithm Firefly, Extremum seeking control method and hybrid methods applied to the monitoring of maximum value of power at point in systems of photovoltaic under changing conditions of irradiance.

Ordering Traces Logically to Identify Lateness in Message Passing Programs

DOE PAGES

Isaacs, Katherine E.; Gamblin, Todd; Bhatele, Abhinav; ...

2015-03-30

Event traces are valuable for understanding the behavior of parallel programs. However, automatically analyzing a large parallel trace is difficult, especially without a specific objective. We aid this endeavor by extracting a trace's logical structure, an ordering of trace events derived from happened-before relationships, while taking into account developer intent. Using this structure, we can calculate an operation's delay relative to its peers on other processes. The logical structure also serves as a platform for comparing and clustering processes as well as highlighting communication patterns in a trace visualization. We present an algorithm for determining this idealized logical structure frommore » traces of message passing programs, and we develop metrics to quantify delays and differences among processes. We implement our techniques in Ravel, a parallel trace visualization tool that displays both logical and physical timelines. Rather than showing the duration of each operation, we display where delays begin and end, and how they propagate. As a result, we apply our approach to the traces of several message passing applications, demonstrating the accuracy of our extracted structure and its utility in analyzing these codes.« less

Automatic threshold selection for multi-class open set recognition

NASA Astrophysics Data System (ADS)

Scherreik, Matthew; Rigling, Brian

2017-05-01

Multi-class open set recognition is the problem of supervised classification with additional unknown classes encountered after a model has been trained. An open set classifer often has two core components. The first component is a base classifier which estimates the most likely class of a given example. The second component consists of open set logic which estimates if the example is truly a member of the candidate class. Such a system is operated in a feed-forward fashion. That is, a candidate label is first estimated by the base classifier, and the true membership of the example to the candidate class is estimated afterward. Previous works have developed an iterative threshold selection algorithm for rejecting examples from classes which were not present at training time. In those studies, a Platt-calibrated SVM was used as the base classifier, and the thresholds were applied to class posterior probabilities for rejection. In this work, we investigate the effectiveness of other base classifiers when paired with the threshold selection algorithm and compare their performance with the original SVM solution.

Evolvable Hardware for Space Applications

NASA Technical Reports Server (NTRS)

Lohn, Jason; Globus, Al; Hornby, Gregory; Larchev, Gregory; Kraus, William

2004-01-01

This article surveys the research of the Evolvable Systems Group at NASA Ames Research Center. Over the past few years, our group has developed the ability to use evolutionary algorithms in a variety of NASA applications ranging from spacecraft antenna design, fault tolerance for programmable logic chips, atomic force field parameter fitting, analog circuit design, and earth observing satellite scheduling. In some of these applications, evolutionary algorithms match or improve on human performance.

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.

A novel topology control approach to maintain the node degree in dynamic wireless sensor networks.

PubMed

Huang, Yuanjiang; Martínez, José-Fernán; Díaz, Vicente Hernández; Sendra, Juana

2014-03-07

Topology control is an important technique to improve the connectivity and the reliability of Wireless Sensor Networks (WSNs) by means of adjusting the communication range of wireless sensor nodes. In this paper, a novel Fuzzy-logic Topology Control (FTC) is proposed to achieve any desired average node degree by adaptively changing communication range, thus improving the network connectivity, which is the main target of FTC. FTC is a fully localized control algorithm, and does not rely on location information of neighbors. Instead of designing membership functions and if-then rules for fuzzy-logic controller, FTC is constructed from the training data set to facilitate the design process. FTC is proved to be accurate, stable and has short settling time. In order to compare it with other representative localized algorithms (NONE, FLSS, k-Neighbor and LTRT), FTC is evaluated through extensive simulations. The simulation results show that: firstly, similar to k-Neighbor algorithm, FTC is the best to achieve the desired average node degree as node density varies; secondly, FTC is comparable to FLSS and k-Neighbor in terms of energy-efficiency, but is better than LTRT and NONE; thirdly, FTC has the lowest average maximum communication range than other algorithms, which indicates that the most energy-consuming node in the network consumes the lowest power.

Stochastic p -Bits for Invertible Logic

NASA Astrophysics Data System (ADS)

Camsari, Kerem Yunus; Faria, Rafatul; Sutton, Brian M.; Datta, Supriyo

2017-07-01

Conventional semiconductor-based logic and nanomagnet-based memory devices are built out of stable, deterministic units such as standard metal-oxide semiconductor transistors, or nanomagnets with energy barriers in excess of ≈40 - 60 kT . In this paper, we show that unstable, stochastic units, which we call "p -bits," can be interconnected to create robust correlations that implement precise Boolean functions with impressive accuracy, comparable to standard digital circuits. At the same time, they are invertible, a unique property that is absent in standard digital circuits. When operated in the direct mode, the input is clamped, and the network provides the correct output. In the inverted mode, the output is clamped, and the network fluctuates among all possible inputs that are consistent with that output. First, we present a detailed implementation of an invertible gate to bring out the key role of a single three-terminal transistorlike building block to enable the construction of correlated p -bit networks. The results for this specific, CMOS-assisted nanomagnet-based hardware implementation agree well with those from a universal model for p -bits, showing that p -bits need not be magnet based: any three-terminal tunable random bit generator should be suitable. We present a general algorithm for designing a Boltzmann machine (BM) with a symmetric connection matrix [J ] (Ji j=Jj i) that implements a given truth table with p -bits. The [J ] matrices are relatively sparse with a few unique weights for convenient hardware implementation. We then show how BM full adders can be interconnected in a partially directed manner (Ji j≠Jj i) to implement large logic operations such as 32-bit binary addition. Hundreds of stochastic p -bits get precisely correlated such that the correct answer out of 233 (≈8 ×1 09) possibilities can be extracted by looking at the statistical mode or majority vote of a number of time samples. With perfect directivity (Jj i=0 ) a small number of samples is enough, while for less directed connections more samples are needed, but even in the former case logical invertibility is largely preserved. This combination of digital accuracy and logical invertibility is enabled by the hybrid design that uses bidirectional BM units to construct circuits with partially directed interunit connections. We establish this key result with extensive examples including a 4-bit multiplier which in inverted mode functions as a factorizer.

An electrically reconfigurable logic gate intrinsically enabled by spin-orbit materials.

PubMed

Kazemi, Mohammad

2017-11-10

The spin degree of freedom in magnetic devices has been discussed widely for computing, since it could significantly reduce energy dissipation, might enable beyond Von Neumann computing, and could have applications in quantum computing. For spin-based computing to become widespread, however, energy efficient logic gates comprising as few devices as possible are required. Considerable recent progress has been reported in this area. However, proposals for spin-based logic either require ancillary charge-based devices and circuits in each individual gate or adopt principals underlying charge-based computing by employing ancillary spin-based devices, which largely negates possible advantages. Here, we show that spin-orbit materials possess an intrinsic basis for the execution of logic operations. We present a spin-orbit logic gate that performs a universal logic operation utilizing the minimum possible number of devices, that is, the essential devices required for representing the logic operands. Also, whereas the previous proposals for spin-based logic require extra devices in each individual gate to provide reconfigurability, the proposed gate is 'electrically' reconfigurable at run-time simply by setting the amplitude of the clock pulse applied to the gate. We demonstrate, analytically and numerically with experimentally benchmarked models, that the gate performs logic operations and simultaneously stores the result, realizing the 'stateful' spin-based logic scalable to ultralow energy dissipation.

An optimal general type-2 fuzzy controller for Urban Traffic Network.

PubMed

Khooban, Mohammad Hassan; Vafamand, Navid; Liaghat, Alireza; Dragicevic, Tomislav

2017-01-01

Urban traffic network model is illustrated by state-charts and object-diagram. However, they have limitations to show the behavioral perspective of the Traffic Information flow. Consequently, a state space model is used to calculate the half-value waiting time of vehicles. In this study, a combination of the general type-2 fuzzy logic sets and the Modified Backtracking Search Algorithm (MBSA) techniques are used in order to control the traffic signal scheduling and phase succession so as to guarantee a smooth flow of traffic with the least wait times and average queue length. The parameters of input and output membership functions are optimized simultaneously by the novel heuristic algorithm MBSA. A comparison is made between the achieved results with those of optimal and conventional type-1 fuzzy logic controllers. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

PLA realizations for VLSI state machines

NASA Technical Reports Server (NTRS)

Gopalakrishnan, S.; Whitaker, S.; Maki, G.; Liu, K.

1990-01-01

A major problem associated with state assignment procedures for VLSI controllers is obtaining an assignment that produces minimal or near minimal logic. The key item in Programmable Logic Array (PLA) area minimization is the number of unique product terms required by the design equations. This paper presents a state assignment algorithm for minimizing the number of product terms required to implement a finite state machine using a PLA. Partition algebra with predecessor state information is used to derive a near optimal state assignment. A maximum bound on the number of product terms required can be obtained by inspecting the predecessor state information. The state assignment algorithm presented is much simpler than existing procedures and leads to the same number of product terms or less. An area-efficient PLA structure implemented in a 1.0 micron CMOS process is presented along with a summary of the performance for a controller implemented using this design procedure.

An inference engine for embedded diagnostic systems

NASA Technical Reports Server (NTRS)

Fox, Barry R.; Brewster, Larry T.

1987-01-01

The implementation of an inference engine for embedded diagnostic systems is described. The system consists of two distinct parts. The first is an off-line compiler which accepts a propositional logical statement of the relationship between facts and conclusions and produces data structures required by the on-line inference engine. The second part consists of the inference engine and interface routines which accept assertions of fact and return the conclusions which necessarily follow. Given a set of assertions, it will generate exactly the conclusions which logically follow. At the same time, it will detect any inconsistencies which may propagate from an inconsistent set of assertions or a poorly formulated set of rules. The memory requirements are fixed and the worst case execution times are bounded at compile time. The data structures and inference algorithms are very simple and well understood. The data structures and algorithms are described in detail. The system has been implemented on Lisp, Pascal, and Modula-2.

An adaptive scale factor based MPPT algorithm for changing solar irradiation levels in outer space

NASA Astrophysics Data System (ADS)

Kwan, Trevor Hocksun; Wu, Xiaofeng

2017-03-01

Maximum power point tracking (MPPT) techniques are popularly used for maximizing the output of solar panels by continuously tracking the maximum power point (MPP) of their P-V curves, which depend both on the panel temperature and the input insolation. Various MPPT algorithms have been studied in literature, including perturb and observe (P&O), hill climbing, incremental conductance, fuzzy logic control and neural networks. This paper presents an algorithm which improves the MPP tracking performance by adaptively scaling the DC-DC converter duty cycle. The principle of the proposed algorithm is to detect the oscillation by checking the sign (ie. direction) of the duty cycle perturbation between the current and previous time steps. If there is a difference in the signs then it is clear an oscillation is present and the DC-DC converter duty cycle perturbation is subsequently scaled down by a constant factor. By repeating this process, the steady state oscillations become negligibly small which subsequently allows for a smooth steady state MPP response. To verify the proposed MPPT algorithm, a simulation involving irradiances levels that are typically encountered in outer space is conducted. Simulation and experimental results prove that the proposed algorithm is fast and stable in comparison to not only the conventional fixed step counterparts, but also to previous variable step size algorithms.

Using Grey Wolf Algorithm to Solve the Capacitated Vehicle Routing Problem

NASA Astrophysics Data System (ADS)

Korayem, L.; Khorsid, M.; Kassem, S. S.

2015-05-01

The capacitated vehicle routing problem (CVRP) is a class of the vehicle routing problems (VRPs). In CVRP a set of identical vehicles having fixed capacities are required to fulfill customers' demands for a single commodity. The main objective is to minimize the total cost or distance traveled by the vehicles while satisfying a number of constraints, such as: the capacity constraint of each vehicle, logical flow constraints, etc. One of the methods employed in solving the CVRP is the cluster-first route-second method. It is a technique based on grouping of customers into a number of clusters, where each cluster is served by one vehicle. Once clusters are formed, a route determining the best sequence to visit customers is established within each cluster. The recently bio-inspired grey wolf optimizer (GWO), introduced in 2014, has proven to be efficient in solving unconstrained, as well as, constrained optimization problems. In the current research, our main contributions are: combining GWO with the traditional K-means clustering algorithm to generate the ‘K-GWO’ algorithm, deriving a capacitated version of the K-GWO algorithm by incorporating a capacity constraint into the aforementioned algorithm, and finally, developing 2 new clustering heuristics. The resulting algorithm is used in the clustering phase of the cluster-first route-second method to solve the CVR problem. The algorithm is tested on a number of benchmark problems with encouraging results.

HDL Based FPGA Interface Library for Data Acquisition and Multipurpose Real Time Algorithms

NASA Astrophysics Data System (ADS)

Fernandes, Ana M.; Pereira, R. C.; Sousa, J.; Batista, A. J. N.; Combo, A.; Carvalho, B. B.; Correia, C. M. B. A.; Varandas, C. A. F.

2011-08-01

The inherent parallelism of the logic resources, the flexibility in its configuration and the performance at high processing frequencies makes the field programmable gate array (FPGA) the most suitable device to be used both for real time algorithm processing and data transfer in instrumentation modules. Moreover, the reconfigurability of these FPGA based modules enables exploiting different applications on the same module. When using a reconfigurable module for various applications, the availability of a common interface library for easier implementation of the algorithms on the FPGA leads to more efficient development. The FPGA configuration is usually specified in a hardware description language (HDL) or other higher level descriptive language. The critical paths, such as the management of internal hardware clocks that require deep knowledge of the module behavior shall be implemented in HDL to optimize the timing constraints. The common interface library should include these critical paths, freeing the application designer from hardware complexity and able to choose any of the available high-level abstraction languages for the algorithm implementation. With this purpose a modular Verilog code was developed for the Virtex 4 FPGA of the in-house Transient Recorder and Processor (TRP) hardware module, based on the Advanced Telecommunications Computing Architecture (ATCA), with eight channels sampling at up to 400 MSamples/s (MSPS). The TRP was designed to perform real time Pulse Height Analysis (PHA), Pulse Shape Discrimination (PSD) and Pile-Up Rejection (PUR) algorithms at a high count rate (few Mevent/s). A brief description of this modular code is presented and examples of its use as an interface with end user algorithms, including a PHA with PUR, are described.

Knowledge discovery from structured mammography reports using inductive logic programming.

PubMed

Burnside, Elizabeth S; Davis, Jesse; Costa, Victor Santos; Dutra, Inês de Castro; Kahn, Charles E; Fine, Jason; Page, David

2005-01-01

The development of large mammography databases provides an opportunity for knowledge discovery and data mining techniques to recognize patterns not previously appreciated. Using a database from a breast imaging practice containing patient risk factors, imaging findings, and biopsy results, we tested whether inductive logic programming (ILP) could discover interesting hypotheses that could subsequently be tested and validated. The ILP algorithm discovered two hypotheses from the data that were 1) judged as interesting by a subspecialty trained mammographer and 2) validated by analysis of the data itself.

Generic algorithms for high performance scalable geocomputing

NASA Astrophysics Data System (ADS)

de Jong, Kor; Schmitz, Oliver; Karssenberg, Derek

2016-04-01

During the last decade, the characteristics of computing hardware have changed a lot. For example, instead of a single general purpose CPU core, personal computers nowadays contain multiple cores per CPU and often general purpose accelerators, like GPUs. Additionally, compute nodes are often grouped together to form clusters or a supercomputer, providing enormous amounts of compute power. For existing earth simulation models to be able to use modern hardware platforms, their compute intensive parts must be rewritten. This can be a major undertaking and may involve many technical challenges. Compute tasks must be distributed over CPU cores, offloaded to hardware accelerators, or distributed to different compute nodes. And ideally, all of this should be done in such a way that the compute task scales well with the hardware resources. This presents two challenges: 1) how to make good use of all the compute resources and 2) how to make these compute resources available for developers of simulation models, who may not (want to) have the required technical background for distributing compute tasks. The first challenge requires the use of specialized technology (e.g.: threads, OpenMP, MPI, OpenCL, CUDA). The second challenge requires the abstraction of the logic handling the distribution of compute tasks from the model-specific logic, hiding the technical details from the model developer. To assist the model developer, we are developing a C++ software library (called Fern) containing algorithms that can use all CPU cores available in a single compute node (distributing tasks over multiple compute nodes will be done at a later stage). The algorithms are grid-based (finite difference) and include local and spatial operations such as convolution filters. The algorithms handle distribution of the compute tasks to CPU cores internally. In the resulting model the low-level details of how this is done is separated from the model-specific logic representing the modeled system. This contrasts with practices in which code for distributing of compute tasks is mixed with model-specific code, and results in a better maintainable model. For flexibility and efficiency, the algorithms are configurable at compile-time with the respect to the following aspects: data type, value type, no-data handling, input value domain handling, and output value range handling. This makes the algorithms usable in very different contexts, without the need for making intrusive changes to existing models when using them. Applications that benefit from using the Fern library include the construction of forward simulation models in (global) hydrology (e.g. PCR-GLOBWB (Van Beek et al. 2011)), ecology, geomorphology, or land use change (e.g. PLUC (Verstegen et al. 2014)) and manipulation of hyper-resolution land surface data such as digital elevation models and remote sensing data. Using the Fern library, we have also created an add-on to the PCRaster Python Framework (Karssenberg et al. 2010) allowing its users to speed up their spatio-temporal models, sometimes by changing just a single line of Python code in their model. In our presentation we will give an overview of the design of the algorithms, providing examples of different contexts where they can be used to replace existing sequential algorithms, including the PCRaster environmental modeling software (www.pcraster.eu). We will show how the algorithms can be configured to behave differently when necessary. References Karssenberg, D., Schmitz, O., Salamon, P., De Jong, K. and Bierkens, M.F.P., 2010, A software framework for construction of process-based stochastic spatio-temporal models and data assimilation. Environmental Modelling & Software, 25, pp. 489-502, Link. Best Paper Award 2010: Software and Decision Support. Van Beek, L. P. H., Y. Wada, and M. F. P. Bierkens. 2011. Global monthly water stress: 1. Water balance and water availability. Water Resources Research. 47. Verstegen, J. A., D. Karssenberg, F. van der Hilst, and A. P. C. Faaij. 2014. Identifying a land use change cellular automaton by Bayesian data assimilation. Environmental Modelling & Software 53:121-136.

Contraceptive efficacy of the personal hormone monitoring system Persona.

PubMed

Trussell, J

1999-07-01

This is a commentary on the contraceptive effectiveness of the personal hormone-monitoring system Persona; it points out the various errors committed in computing method pregnancy rates. The modifications presented by Bonnar et al. on the incorrect procedure for computing method pregnancy rates are criticized as erroneous because the denominator includes cycles in which there is no risk of a method pregnancy according to the authors' algorithm for classifying pregnancy in an imperfect-use cycle. It is also claimed that the new exercise is a more complicated and less accurate way of computing for pregnancy rates by comparison with the simpler alternative. Since this new algorithm, used in the Persona system, is based on flawed logic, the annual risk of pregnancy is actually higher than the estimated 6% among women using Persona and having intercourse in each cycle except on red days.

Rule Systems for Runtime Verification: A Short Tutorial

NASA Astrophysics Data System (ADS)

Barringer, Howard; Havelund, Klaus; Rydeheard, David; Groce, Alex

In this tutorial, we introduce two rule-based systems for on and off-line trace analysis, RuleR and LogScope. RuleR is a conditional rule-based system, which has a simple and easily implemented algorithm for effective runtime verification, and into which one can compile a wide range of temporal logics and other specification formalisms used for runtime verification. Specifications can be parameterized with data, or even with specifications, allowing for temporal logic combinators to be defined. We outline a number of simple syntactic extensions of core RuleR that can lead to further conciseness of specification but still enabling easy and efficient implementation. RuleR is implemented in Java and we will demonstrate its ease of use in monitoring Java programs. LogScope is a derivation of RuleR adding a simple very user-friendly temporal logic. It was developed in Python, specifically for supporting testing of spacecraft flight software for NASA’s next 2011 Mars mission MSL (Mars Science Laboratory). The system has been applied by test engineers to analysis of log files generated by running the flight software. Detailed logging is already part of the system design approach, and hence there is no added instrumentation overhead caused by this approach. While post-mortem log analysis prevents the autonomous reaction to problems possible with traditional runtime verification, it provides a powerful tool for test automation. A new system is being developed that integrates features from both RuleR and LogScope.

Boolean logic tree of graphene-based chemical system for molecular computation and intelligent molecular search query.

PubMed

Huang, Wei Tao; Luo, Hong Qun; Li, Nian Bing

2014-05-06

The most serious, and yet unsolved, problem of constructing molecular computing devices consists in connecting all of these molecular events into a usable device. This report demonstrates the use of Boolean logic tree for analyzing the chemical event network based on graphene, organic dye, thrombin aptamer, and Fenton reaction, organizing and connecting these basic chemical events. And this chemical event network can be utilized to implement fluorescent combinatorial logic (including basic logic gates and complex integrated logic circuits) and fuzzy logic computing. On the basis of the Boolean logic tree analysis and logic computing, these basic chemical events can be considered as programmable "words" and chemical interactions as "syntax" logic rules to construct molecular search engine for performing intelligent molecular search query. Our approach is helpful in developing the advanced logic program based on molecules for application in biosensing, nanotechnology, and drug delivery.

Computer vision camera with embedded FPGA processing

NASA Astrophysics Data System (ADS)

Lecerf, Antoine; Ouellet, Denis; Arias-Estrada, Miguel

2000-03-01

Traditional computer vision is based on a camera-computer system in which the image understanding algorithms are embedded in the computer. To circumvent the computational load of vision algorithms, low-level processing and imaging hardware can be integrated in a single compact module where a dedicated architecture is implemented. This paper presents a Computer Vision Camera based on an open architecture implemented in an FPGA. The system is targeted to real-time computer vision tasks where low level processing and feature extraction tasks can be implemented in the FPGA device. The camera integrates a CMOS image sensor, an FPGA device, two memory banks, and an embedded PC for communication and control tasks. The FPGA device is a medium size one equivalent to 25,000 logic gates. The device is connected to two high speed memory banks, an IS interface, and an imager interface. The camera can be accessed for architecture programming, data transfer, and control through an Ethernet link from a remote computer. A hardware architecture can be defined in a Hardware Description Language (like VHDL), simulated and synthesized into digital structures that can be programmed into the FPGA and tested on the camera. The architecture of a classical multi-scale edge detection algorithm based on a Laplacian of Gaussian convolution has been developed to show the capabilities of the system.

Compton suppression and event triggering in a commercial data acquisition system

NASA Astrophysics Data System (ADS)

Tabor, Samuel; Caussyn, D. D.; Tripathi, Vandana; Vonmoss, J.; Liddick, S. N.

2012-10-01

A number of groups are starting to use flash digitizer systems to directly convert the preamplifier signals of high-resolution Ge detectors to a stream of digital data. Some digitizers are also equipped with software constant fraction discriminator algorithms capable of operating on the resulting digital data stream to provide timing information. Because of the dropping cost per channel of these systems, it should now be possible to also connect outputs of the Bismuth Germanate (BGO) scintillators used for Compton suppression to other digitizer inputs so that BGO logic signals can also be available in the same system. This provides the possibility to perform all the Compton suppression and multiplicity trigger logic within the digital system, thus eliminating the need for separate timing filter amplifiers (TFA), constant fraction discriminators (CFD), logic units, and lots of cables. This talk will describe the performance of such a system based on Pixie16 modules from XIA LLC with custom field programmable gate array (FPGA) programming for an array of Compton suppressed single Ge crystal and 4-crystal ``Clover'' detector array along with optional particle detectors. Initial tests of the system have produced results comparable with the current traditional system of individual electronics and peak sensing analog to digital converters. The advantages of the all digital system will be discussed.

Rule-Based Runtime Verification

NASA Technical Reports Server (NTRS)

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

2003-01-01

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

RNA secondary structure prediction using soft computing.

PubMed

Ray, Shubhra Sankar; Pal, Sankar K

2013-01-01

Prediction of RNA structure is invaluable in creating new drugs and understanding genetic diseases. Several deterministic algorithms and soft computing-based techniques have been developed for more than a decade to determine the structure from a known RNA sequence. Soft computing gained importance with the need to get approximate solutions for RNA sequences by considering the issues related with kinetic effects, cotranscriptional folding, and estimation of certain energy parameters. A brief description of some of the soft computing-based techniques, developed for RNA secondary structure prediction, is presented along with their relevance. The basic concepts of RNA and its different structural elements like helix, bulge, hairpin loop, internal loop, and multiloop are described. These are followed by different methodologies, employing genetic algorithms, artificial neural networks, and fuzzy logic. The role of various metaheuristics, like simulated annealing, particle swarm optimization, ant colony optimization, and tabu search is also discussed. A relative comparison among different techniques, in predicting 12 known RNA secondary structures, is presented, as an example. Future challenging issues are then mentioned.

Investigation of High-Level Synthesis tools’ applicability to data acquisition systems design based on the CMS ECAL Data Concentrator Card example

NASA Astrophysics Data System (ADS)

HUSEJKO, Michal; EVANS, John; RASTEIRO DA SILVA, Jose Carlos

2015-12-01

High-Level Synthesis (HLS) for Field-Programmable Logic Array (FPGA) programming is becoming a practical alternative to well-established VHDL and Verilog languages. This paper describes a case study in the use of HLS tools to design FPGA-based data acquisition systems (DAQ). We will present the implementation of the CERN CMS detector ECAL Data Concentrator Card (DCC) functionality in HLS and lessons learned from using HLS design flow. The DCC functionality and a definition of the initial system-level performance requirements (latency, bandwidth, and throughput) will be presented. We will describe how its packet processing control centric algorithm was implemented with VHDL and Verilog languages. We will then show how the HLS flow could speed up design-space exploration by providing loose coupling between functions interface design and functions algorithm implementation. We conclude with results of real-life hardware tests performed with the HLS flow-generated design with a DCC Tester system.

Automatic Synthetic Aperture Radar based oil spill detection and performance estimation via a semi-automatic operational service benchmark.

PubMed

Singha, Suman; Vespe, Michele; Trieschmann, Olaf

2013-08-15

Today the health of ocean is in danger as it was never before mainly due to man-made pollutions. Operational activities show regular occurrence of accidental and deliberate oil spill in European waters. Since the areas covered by oil spills are usually large, satellite remote sensing particularly Synthetic Aperture Radar represents an effective option for operational oil spill detection. This paper describes the development of a fully automated approach for oil spill detection from SAR. Total of 41 feature parameters extracted from each segmented dark spot for oil spill and 'look-alike' classification and ranked according to their importance. The classification algorithm is based on a two-stage processing that combines classification tree analysis and fuzzy logic. An initial evaluation of this methodology on a large dataset has been carried out and degree of agreement between results from proposed algorithm and human analyst was estimated between 85% and 93% respectively for ENVISAT and RADARSAT. Copyright © 2013 Elsevier Ltd. All rights reserved.

Army/NASA small turboshaft engine digital controls research program

NASA Technical Reports Server (NTRS)

Sellers, J. F.; Baez, A. N.

1981-01-01

The emphasis of a program to conduct digital controls research for small turboshaft engines is on engine test evaluation of advanced control logic using a flexible microprocessor based digital control system designed specifically for research on advanced control logic. Control software is stored in programmable memory. New control algorithms may be stored in a floppy disk and loaded directly into memory. This feature facilitates comparative evaluation of different advanced control modes. The central processor in the digital control is an Intel 8086 16 bit microprocessor. Control software is programmed in assembly language. Software checkout is accomplished prior to engine test by connecting the digital control to a real time hybrid computer simulation of the engine. The engine currently installed in the facility has a hydromechanical control modified to allow electrohydraulic fuel metering and VG actuation by the digital control. Simulation results are presented which show that the modern control reduces the transient rotor speed droop caused by unanticipated load changes such as cyclic pitch or wind gust transients.

Expanding a First-Order Logic Mitigation Framework to Handle Multimorbid Patient Preferences

PubMed Central

Michalowski, Martin; Wilk, Szymon; Rosu, Daniela; Kezadri, Mounira; Michalowski, Wojtek; Carrier, Marc

2015-01-01

The increasing prevalence of multimorbidity is a challenge for physicians who have to manage a constantly growing number of patients with simultaneous diseases. Adding to this challenge is the need to incorporate patient preferences as key components of the care process, thanks in part to the emergence of personalized and participatory medicine. In our previous work we proposed a framework employing first order logic to represent clinical practice guidelines (CPGs) and to mitigate possible adverse interactions when concurrently applying multiple CPGs to a multimorbid patient. In this paper, we describe extensions to our methodological framework that (1) broaden our definition of revision operators to support required and desired types of revisions defined in secondary knowledge sources, and (2) expand the mitigation algorithm to apply revisions based on their type. We illustrate the capabilities of the expanded framework using a clinical case study of a multimorbid patient with stable cardiac artery disease who suffers a sudden onset of deep vein thrombosis. PMID:26958226

Full-order Luenberger observer based on fuzzy-logic control for sensorless field-oriented control of a single-sided linear induction motor.

PubMed

Holakooie, Mohammad Hosein; Ojaghi, Mansour; Taheri, Asghar

2016-01-01

This paper investigates sensorless indirect field oriented control (IFOC) of SLIM with full-order Luenberger observer. The dynamic equations of SLIM are first elaborated to draw full-order Luenberger observer with some simplifying assumption. The observer gain matrix is derived from conventional procedure so that observer poles are proportional to SLIM poles to ensure the stability of system for wide range of linear speed. The operation of observer is significantly impressed by adaptive scheme. A fuzzy logic control (FLC) is proposed as adaptive scheme to estimate linear speed using speed tuning signal. The parameters of FLC are tuned using an off-line method through chaotic optimization algorithm (COA). The performance of the proposed observer is verified by both numerical simulation and real-time hardware-in-the-loop (HIL) implementation. Moreover, a detailed comparative study among proposed and other speed observers is obtained under different operation conditions. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

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.

Logic-Based Models for the Analysis of Cell Signaling Networks†

PubMed Central

2010-01-01

Computational models are increasingly used to analyze the operation of complex biochemical networks, including those involved in cell signaling networks. Here we review recent advances in applying logic-based modeling to mammalian cell biology. Logic-based models represent biomolecular networks in a simple and intuitive manner without describing the detailed biochemistry of each interaction. A brief description of several logic-based modeling methods is followed by six case studies that demonstrate biological questions recently addressed using logic-based models and point to potential advances in model formalisms and training procedures that promise to enhance the utility of logic-based methods for studying the relationship between environmental inputs and phenotypic or signaling state outputs of complex signaling networks. PMID:20225868

A motion-constraint logic for moving-base simulators based on variable filter parameters

NASA Technical Reports Server (NTRS)

Miller, G. K., Jr.

1974-01-01

A motion-constraint logic for moving-base simulators has been developed that is a modification to the linear second-order filters generally employed in conventional constraints. In the modified constraint logic, the filter parameters are not constant but vary with the instantaneous motion-base position to increase the constraint as the system approaches the positional limits. With the modified constraint logic, accelerations larger than originally expected are limited while conventional linear filters would result in automatic shutdown of the motion base. In addition, the modified washout logic has frequency-response characteristics that are an improvement over conventional linear filters with braking for low-frequency pilot inputs. During simulated landing approaches of an externally blown flap short take-off and landing (STOL) transport using decoupled longitudinal controls, the pilots were unable to detect much difference between the modified constraint logic and the logic based on linear filters with braking.

Metalevel programming in robotics: Some issues

NASA Technical Reports Server (NTRS)

Kumarn, A.; Parameswaran, N.

1987-01-01

Computing in robotics has two important requirements: efficiency and flexibility. Algorithms for robot actions are implemented usually in procedural languages such as VAL and AL. But, since their excessive bindings create inflexible structures of computation, it is proposed that Logic Programming is a more suitable language for robot programming due to its non-determinism, declarative nature, and provision for metalevel programming. Logic Programming, however, results in inefficient computations. As a solution to this problem, researchers discuss a framework in which controls can be described to improve efficiency. They have divided controls into: (1) in-code and (2) metalevel and discussed them with reference to selection of rules and dataflow. Researchers illustrated the merit of Logic Programming by modelling the motion of a robot from one point to another avoiding obstacles.

Temporal and Spatial prediction of groundwater levels using Artificial Neural Networks, Fuzzy logic and Kriging interpolation.

NASA Astrophysics Data System (ADS)

Tapoglou, Evdokia; Karatzas, George P.; Trichakis, Ioannis C.; Varouchakis, Emmanouil A.

2014-05-01

The purpose of this study is to examine the use of Artificial Neural Networks (ANN) combined with kriging interpolation method, in order to simulate the hydraulic head both spatially and temporally. Initially, ANNs are used for the temporal simulation of the hydraulic head change. The results of the most appropriate ANNs, determined through a fuzzy logic system, are used as an input for the kriging algorithm where the spatial simulation is conducted. The proposed algorithm is tested in an area located across Isar River in Bayern, Germany and covers an area of approximately 7800 km2. The available data extend to a time period from 1/11/2008 to 31/10/2012 (1460 days) and include the hydraulic head at 64 wells, temperature and rainfall at 7 weather stations and surface water elevation at 5 monitoring stations. One feedforward ANN was trained for each of the 64 wells, where hydraulic head data are available, using a backpropagation algorithm. The most appropriate input parameters for each wells' ANN are determined considering their proximity to the measuring station, as well as their statistical characteristics. For the rainfall, the data for two consecutive time lags for best correlated weather station, as well as a third and fourth input from the second best correlated weather station, are used as an input. The surface water monitoring stations with the three best correlations for each well are also used in every case. Finally, the temperature for the best correlated weather station is used. Two different architectures are considered and the one with the best results is used henceforward. The output of the ANNs corresponds to the hydraulic head change per time step. These predictions are used in the kriging interpolation algorithm. However, not all 64 simulated values should be used. The appropriate neighborhood for each prediction point is constructed based not only on the distance between known and prediction points, but also on the training and testing error of the ANN. Therefore, the neighborhood of each prediction point is the best available. Then, the appropriate variogram is determined, by fitting the experimental variogram to a theoretical variogram model. Three models are examined, the linear, the exponential and the power-law. Finally, the hydraulic head change is predicted for every grid cell and for every time step used. All the algorithms used were developed in Visual Basic .NET, while the visualization of the results was performed in MATLAB using the .NET COM Interoperability. The results are evaluated using leave one out cross-validation and various performance indicators. The best results were achieved by using ANNs with two hidden layers, consisting of 20 and 15 nodes respectively and by using power-law variogram with the fuzzy logic system.

Efficient implementation of the 3D-DDA ray traversal algorithm on GPU and its application in radiation dose calculation.

PubMed

Xiao, Kai; Chen, Danny Z; Hu, X Sharon; Zhou, Bo

2012-12-01

The three-dimensional digital differential analyzer (3D-DDA) algorithm is a widely used ray traversal method, which is also at the core of many convolution∕superposition (C∕S) dose calculation approaches. However, porting existing C∕S dose calculation methods onto graphics processing unit (GPU) has brought challenges to retaining the efficiency of this algorithm. In particular, straightforward implementation of the original 3D-DDA algorithm inflicts a lot of branch divergence which conflicts with the GPU programming model and leads to suboptimal performance. In this paper, an efficient GPU implementation of the 3D-DDA algorithm is proposed, which effectively reduces such branch divergence and improves performance of the C∕S dose calculation programs running on GPU. The main idea of the proposed method is to convert a number of conditional statements in the original 3D-DDA algorithm into a set of simple operations (e.g., arithmetic, comparison, and logic) which are better supported by the GPU architecture. To verify and demonstrate the performance improvement, this ray traversal method was integrated into a GPU-based collapsed cone convolution∕superposition (CCCS) dose calculation program. The proposed method has been tested using a water phantom and various clinical cases on an NVIDIA GTX570 GPU. The CCCS dose calculation program based on the efficient 3D-DDA ray traversal implementation runs 1.42 ∼ 2.67× faster than the one based on the original 3D-DDA implementation, without losing any accuracy. The results show that the proposed method can effectively reduce branch divergence in the original 3D-DDA ray traversal algorithm and improve the performance of the CCCS program running on GPU. Considering the wide utilization of the 3D-DDA algorithm, various applications can benefit from this implementation method.

Fuzzy logic controller optimization

DOEpatents

Sepe, Jr., Raymond B; Miller, John Michael

2004-03-23

A method is provided for optimizing a rotating induction machine system fuzzy logic controller. The fuzzy logic controller has at least one input and at least one output. Each input accepts a machine system operating parameter. Each output produces at least one machine system control parameter. The fuzzy logic controller generates each output based on at least one input and on fuzzy logic decision parameters. Optimization begins by obtaining a set of data relating each control parameter to at least one operating parameter for each machine operating region. A model is constructed for each machine operating region based on the machine operating region data obtained. The fuzzy logic controller is simulated with at least one created model in a feedback loop from a fuzzy logic output to a fuzzy logic input. Fuzzy logic decision parameters are optimized based on the simulation.

Automated turn pike using PLC and SCADA

NASA Astrophysics Data System (ADS)

Silpa Sreedhar, P.; Aiswarya, P.; Kathirvelan, J.

2017-11-01

We propose a smart turnpike based on Programmable Logic Controller (PLC) and Supervisory Control and Data Acquisition Systems (SCADA) in this paper. In this work, the basic idea is to measure the weight of the vehicles and classify them according to its weight to the respective lanes. It is difficult for the turnpike people to monitor the whole process all the time. So, this PLC based diversion system can be implemented in turnpikes to reduce the difficulties. This method will work based on weight sensors (piezo-resistive) whose output will be fed to a PLC, which will control the vehicle diversion. Using SCADA software, the whole process can be monitored from a remote area. The algorithm developed in this successfully installed in real time system.

Tyramine Hydrochloride Based Label-Free System for Operating Various DNA Logic Gates and a DNA Caliper for Base Number Measurements.

PubMed

Fan, Daoqing; Zhu, Xiaoqing; Dong, Shaojun; Wang, Erkang

2017-07-05

DNA is believed to be a promising candidate for molecular logic computation, and the fluorogenic/colorimetric substrates of G-quadruplex DNAzyme (G4zyme) are broadly used as label-free output reporters of DNA logic circuits. Herein, for the first time, tyramine-HCl (a fluorogenic substrate of G4zyme) is applied to DNA logic computation and a series of label-free DNA-input logic gates, including elementary AND, OR, and INHIBIT logic gates, as well as a two to one encoder, are constructed. Furthermore, a DNA caliper that can measure the base number of target DNA as low as three bases is also fabricated. This DNA caliper can also perform concatenated AND-AND logic computation to fulfil the requirements of sophisticated logic computing. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Smart sensing to drive real-time loads scheduling algorithm in a domotic architecture

NASA Astrophysics Data System (ADS)

Santamaria, Amilcare Francesco; Raimondo, Pierfrancesco; De Rango, Floriano; Vaccaro, Andrea

2014-05-01

Nowadays the focus on power consumption represent a very important factor regarding the reduction of power consumption with correlated costs and the environmental sustainability problems. Automatic control load based on power consumption and use cycle represents the optimal solution to costs restraint. The purpose of these systems is to modulate the power request of electricity avoiding an unorganized work of the loads, using intelligent techniques to manage them based on real time scheduling algorithms. The goal is to coordinate a set of electrical loads to optimize energy costs and consumptions based on the stipulated contract terms. The proposed algorithm use two new main notions: priority driven loads and smart scheduling loads. The priority driven loads can be turned off (stand by) according to a priority policy established by the user if the consumption exceed a defined threshold, on the contrary smart scheduling loads are scheduled in a particular way to don't stop their Life Cycle (LC) safeguarding the devices functions or allowing the user to freely use the devices without the risk of exceeding the power threshold. The algorithm, using these two kind of notions and taking into account user requirements, manages loads activation and deactivation allowing the completion their operation cycle without exceeding the consumption threshold in an off-peak time range according to the electricity fare. This kind of logic is inspired by industrial lean manufacturing which focus is to minimize any kind of power waste optimizing the available resources.

Nonvolatile “AND,” “OR,” and “NOT” Boolean logic gates based on phase-change memory

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

Li, Y.; Zhong, Y. P.; Deng, Y. F.

2013-12-21

Electronic devices or circuits that can implement both logic and memory functions are regarded as the building blocks for future massive parallel computing beyond von Neumann architecture. Here we proposed phase-change memory (PCM)-based nonvolatile logic gates capable of AND, OR, and NOT Boolean logic operations verified in SPICE simulations and circuit experiments. The logic operations are parallel computing and results can be stored directly in the states of the logic gates, facilitating the combination of computing and memory in the same circuit. These results are encouraging for ultralow-power and high-speed nonvolatile logic circuit design based on novel memory devices.

ART/Ada design project, phase 1. Task 2 report: Detailed design

NASA Technical Reports Server (NTRS)

Allen, Bradley P.

1988-01-01

Various issues are studied in the context of the design of an Ada based expert system building tool. Using an existing successful design as a starting point, the impact is analyzed of the Ada language and Ada development methodologies on that design, the Ada system is redesigned, and its performance is analyzed using both complexity-theoretic and empirical techniques. The algorithms specified in the overall design are refined, resolving and documenting any open design issues, identifying each system module, documenting the internal architecture and control logic, and describing the primary data structures involved in the module.

Computers can't listen--algorithmic logic meets patient centredness.

PubMed

Pearce, Christopher; Trumble, Steve

2006-06-01

The doctor-patient relationship is crucial to the practice of medicine and yet the rise of science in the 19th and 20th centuries shifted doctors' focus away from the patient toward another entity: the disease. Slowly, the medical profession is rediscovering the importance of the doctor-patient relationship. General practice has contributed significantly by developing the patient centred clinical method, and further models have been introduced that take into account both the doctor's and the patient's perspectives. More recent changes in medicine--particularly computerisation and the introduction of evidence based medicine--may once again threaten this emphasis on patient centredness.

Improving activity recognition using a wearable barometric pressure sensor in mobility-impaired stroke patients.

PubMed

Massé, Fabien; Gonzenbach, Roman R; Arami, Arash; Paraschiv-Ionescu, Anisoara; Luft, Andreas R; Aminian, Kamiar

2015-08-25

Stroke survivors often suffer from mobility deficits. Current clinical evaluation methods, including questionnaires and motor function tests, cannot provide an objective measure of the patients' mobility in daily life. Physical activity performance in daily-life can be assessed using unobtrusive monitoring, for example with a single sensor module fixed on the trunk. Existing approaches based on inertial sensors have limited performance, particularly in detecting transitions between different activities and postures, due to the inherent inter-patient variability of kinematic patterns. To overcome these limitations, one possibility is to use additional information from a barometric pressure (BP) sensor. Our study aims at integrating BP and inertial sensor data into an activity classifier in order to improve the activity (sitting, standing, walking, lying) recognition and the corresponding body elevation (during climbing stairs or when taking an elevator). Taking into account the trunk elevation changes during postural transitions (sit-to-stand, stand-to-sit), we devised an event-driven activity classifier based on fuzzy-logic. Data were acquired from 12 stroke patients with impaired mobility, using a trunk-worn inertial and BP sensor. Events, including walking and lying periods and potential postural transitions, were first extracted. These events were then fed into a double-stage hierarchical Fuzzy Inference System (H-FIS). The first stage processed the events to infer activities and the second stage improved activity recognition by applying behavioral constraints. Finally, the body elevation was estimated using a pattern-enhancing algorithm applied on BP. The patients were videotaped for reference. The performance of the algorithm was estimated using the Correct Classification Rate (CCR) and F-score. The BP-based classification approach was benchmarked against a previously-published fuzzy-logic classifier (FIS-IMU) and a conventional epoch-based classifier (EPOCH). The algorithm performance for posture/activity detection, in terms of CCR was 90.4 %, with 3.3 % and 5.6 % improvements against FIS-IMU and EPOCH, respectively. The proposed classifier essentially benefits from a better recognition of standing activity (70.3 % versus 61.5 % [FIS-IMU] and 42.5 % [EPOCH]) with 98.2 % CCR for body elevation estimation. The monitoring and recognition of daily activities in mobility-impaired stoke patients can be significantly improved using a trunk-fixed sensor that integrates BP, inertial sensors, and an event-based activity classifier.

Eigensolution of finite element problems in a completely connected parallel architecture

NASA Technical Reports Server (NTRS)

Akl, Fred A.; Morel, Michael R.

1989-01-01

A parallel algorithm for the solution of the generalized eigenproblem in linear elastic finite element analysis, (K)(phi)=(M)(phi)(omega), where (K) and (M) are of order N, and (omega) is of order q is presented. The parallel algorithm is based on a completely connected parallel architecture in which each processor is allowed to communicate with all other processors. The algorithm has been successfully implemented on a tightly coupled multiple-instruction-multiple-data (MIMD) parallel processing computer, Cray X-MP. A finite element model is divided into m domains each of which is assumed to process n elements. Each domain is then assigned to a processor, or to a logical processor (task) if the number of domains exceeds the number of physical processors. The macro-tasking library routines are used in mapping each domain to a user task. Computational speed-up and efficiency are used to determine the effectiveness of the algorithm. The effect of the number of domains, the number of degrees-of-freedom located along the global fronts and the dimension of the subspace on the performance of the algorithm are investigated. For a 64-element rectangular plate, speed-ups of 1.86, 3.13, 3.18 and 3.61 are achieved on two, four, six and eight processors, respectively.

Are human beings humean robots?

NASA Astrophysics Data System (ADS)

Génova, Gonzalo; Quintanilla Navarro, Ignacio

2018-01-01

David Hume, the Scottish philosopher, conceives reason as the slave of the passions, which implies that human reason has predetermined objectives it cannot question. An essential element of an algorithm running on a computational machine (or Logical Computing Machine, as Alan Turing calls it) is its having a predetermined purpose: an algorithm cannot question its purpose, because it would cease to be an algorithm. Therefore, if self-determination is essential to human intelligence, then human beings are neither Humean beings, nor computational machines. We examine also some objections to the Turing Test as a model to understand human intelligence.

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.

Efficient experimental design of high-fidelity three-qubit quantum gates via genetic programming

NASA Astrophysics Data System (ADS)

Devra, Amit; Prabhu, Prithviraj; Singh, Harpreet; Arvind; Dorai, Kavita

2018-03-01

We have designed efficient quantum circuits for the three-qubit Toffoli (controlled-controlled-NOT) and the Fredkin (controlled-SWAP) gate, optimized via genetic programming methods. The gates thus obtained were experimentally implemented on a three-qubit NMR quantum information processor, with a high fidelity. Toffoli and Fredkin gates in conjunction with the single-qubit Hadamard gates form a universal gate set for quantum computing and are an essential component of several quantum algorithms. Genetic algorithms are stochastic search algorithms based on the logic of natural selection and biological genetics and have been widely used for quantum information processing applications. We devised a new selection mechanism within the genetic algorithm framework to select individuals from a population. We call this mechanism the "Luck-Choose" mechanism and were able to achieve faster convergence to a solution using this mechanism, as compared to existing selection mechanisms. The optimization was performed under the constraint that the experimentally implemented pulses are of short duration and can be implemented with high fidelity. We demonstrate the advantage of our pulse sequences by comparing our results with existing experimental schemes and other numerical optimization methods.

Towards lung EIT image segmentation: automatic classification of lung tissue state from analysis of EIT monitored recruitment manoeuvres.

PubMed

Grychtol, Bartłomiej; Wolf, Gerhard K; Adler, Andy; Arnold, John H

2010-08-01

There is emerging evidence that the ventilation strategy used in acute lung injury (ALI) makes a significant difference in outcome and that an inappropriate ventilation strategy may produce ventilator-associated lung injury. Most harmful during mechanical ventilation are lung overdistension and lung collapse or atelectasis. Electrical impedance tomography (EIT) as a non-invasive imaging technology may be helpful to identify lung areas at risk. Currently, no automated method is routinely available to identify lung areas that are overdistended, collapsed or ventilated appropriately. We propose a fuzzy logic-based algorithm to analyse EIT images obtained during stepwise changes of mean airway pressures during mechanical ventilation. The algorithm is tested on data from two published studies of stepwise inflation-deflation manoeuvres in an animal model of ALI using conventional and high-frequency oscillatory ventilation. The timing of lung opening and collapsing on segmented images obtained using the algorithm during an inflation-deflation manoeuvre is in agreement with well-known effects of surfactant administration and changes in shunt fraction. While the performance of the algorithm has not been verified against a gold standard, we feel that it presents an important first step in tackling this challenging and important problem.

Experimental quantum computing to solve systems of linear equations.

PubMed

Cai, X-D; Weedbrook, C; Su, Z-E; Chen, M-C; Gu, Mile; Zhu, M-J; Li, Li; Liu, Nai-Le; Lu, Chao-Yang; Pan, Jian-Wei

2013-06-07

Solving linear systems of equations is ubiquitous in all areas of science and engineering. With rapidly growing data sets, such a task can be intractable for classical computers, as the best known classical algorithms require a time proportional to the number of variables N. A recently proposed quantum algorithm shows that quantum computers could solve linear systems in a time scale of order log(N), giving an exponential speedup over classical computers. Here we realize the simplest instance of this algorithm, solving 2×2 linear equations for various input vectors on a quantum computer. We use four quantum bits and four controlled logic gates to implement every subroutine required, demonstrating the working principle of this algorithm.

Runtime verification of embedded real-time systems.

PubMed

Reinbacher, Thomas; Függer, Matthias; Brauer, Jörg

We present a runtime verification framework that allows on-line monitoring of past-time Metric Temporal Logic (ptMTL) specifications in a discrete time setting. We design observer algorithms for the time-bounded modalities of ptMTL, which take advantage of the highly parallel nature of hardware designs. The algorithms can be translated into efficient hardware blocks, which are designed for reconfigurability, thus, facilitate applications of the framework in both a prototyping and a post-deployment phase of embedded real-time systems. We provide formal correctness proofs for all presented observer algorithms and analyze their time and space complexity. For example, for the most general operator considered, the time-bounded Since operator, we obtain a time complexity that is doubly logarithmic both in the point in time the operator is executed and the operator's time bounds. This result is promising with respect to a self-contained, non-interfering monitoring approach that evaluates real-time specifications in parallel to the system-under-test. We implement our framework on a Field Programmable Gate Array platform and use extensive simulation and logic synthesis runs to assess the benefits of the approach in terms of resource usage and operating frequency.

Improved HDRG decoders for qudit and non-Abelian quantum error correction

NASA Astrophysics Data System (ADS)

Hutter, Adrian; Loss, Daniel; Wootton, James R.

2015-03-01

Hard-decision renormalization group (HDRG) decoders are an important class of decoding algorithms for topological quantum error correction. Due to their versatility, they have been used to decode systems with fractal logical operators, color codes, qudit topological codes, and non-Abelian systems. In this work, we develop a method of performing HDRG decoding which combines strengths of existing decoders and further improves upon them. In particular, we increase the minimal number of errors necessary for a logical error in a system of linear size L from \\Theta ({{L}2/3}) to Ω ({{L}1-ε }) for any ε \\gt 0. We apply our algorithm to decoding D({{{Z}}d}) quantum double models and a non-Abelian anyon model with Fibonacci-like fusion rules, and show that it indeed significantly outperforms previous HDRG decoders. Furthermore, we provide the first study of continuous error correction with imperfect syndrome measurements for the D({{{Z}}d}) quantum double models. The parallelized runtime of our algorithm is poly(log L) for the perfect measurement case. In the continuous case with imperfect syndrome measurements, the averaged runtime is O(1) for Abelian systems, while continuous error correction for non-Abelian anyons stays an open problem.

Electronics for CMS Endcap Muon Level-1 Trigger System Phase-1 and HL LHC upgrades

NASA Astrophysics Data System (ADS)

Madorsky, A.

2017-07-01

To accommodate high-luminosity LHC operation at a 13 TeV collision energy, the CMS Endcap Muon Level-1 Trigger system had to be significantly modified. To provide robust track reconstruction, the trigger system must now import all available trigger primitives generated by the Cathode Strip Chambers and by certain other subsystems, such as Resistive Plate Chambers (RPC). In addition to massive input bandwidth, this also required significant increase in logic and memory resources. To satisfy these requirements, a new Sector Processor unit has been designed. It consists of three modules. The Core Logic module houses the large FPGA that contains the track-finding logic and multi-gigabit serial links for data exchange. The Optical module contains optical receivers and transmitters; it communicates with the Core Logic module via a custom backplane section. The Pt Lookup table (PTLUT) module contains 1 GB of low-latency memory that is used to assign the final Pt to reconstructed muon tracks. The μ TCA architecture (adopted by CMS) was used for this design. The talk presents the details of the hardware and firmware design of the production system based on Xilinx Virtex-7 FPGA family. The next round of LHC and CMS upgrades starts in 2019, followed by a major High-Luminosity (HL) LHC upgrade starting in 2024. In the course of these upgrades, new Gas Electron Multiplier (GEM) detectors and more RPC chambers will be added to the Endcap Muon system. In order to keep up with all these changes, a new Advanced Processor unit is being designed. This device will be based on Xilinx UltraScale+ FPGAs. It will be able to accommodate up to 100 serial links with bit rates of up to 25 Gb/s, and provide up to 2.5 times more logic resources than the device used currently. The amount of PTLUT memory will be significantly increased to provide more flexibility for the Pt assignment algorithm. The talk presents preliminary details of the hardware design program.

Multiple Imputation based Clustering Validation (MIV) for Big Longitudinal Trial Data with Missing Values in eHealth.

PubMed

Zhang, Zhaoyang; Fang, Hua; Wang, Honggang

2016-06-01

Web-delivered trials are an important component in eHealth services. These trials, mostly behavior-based, generate big heterogeneous data that are longitudinal, high dimensional with missing values. Unsupervised learning methods have been widely applied in this area, however, validating the optimal number of clusters has been challenging. Built upon our multiple imputation (MI) based fuzzy clustering, MIfuzzy, we proposed a new multiple imputation based validation (MIV) framework and corresponding MIV algorithms for clustering big longitudinal eHealth data with missing values, more generally for fuzzy-logic based clustering methods. Specifically, we detect the optimal number of clusters by auto-searching and -synthesizing a suite of MI-based validation methods and indices, including conventional (bootstrap or cross-validation based) and emerging (modularity-based) validation indices for general clustering methods as well as the specific one (Xie and Beni) for fuzzy clustering. The MIV performance was demonstrated on a big longitudinal dataset from a real web-delivered trial and using simulation. The results indicate MI-based Xie and Beni index for fuzzy-clustering are more appropriate for detecting the optimal number of clusters for such complex data. The MIV concept and algorithms could be easily adapted to different types of clustering that could process big incomplete longitudinal trial data in eHealth services.

Multiple Imputation based Clustering Validation (MIV) for Big Longitudinal Trial Data with Missing Values in eHealth

PubMed Central

Zhang, Zhaoyang; Wang, Honggang

2016-01-01

Web-delivered trials are an important component in eHealth services. These trials, mostly behavior-based, generate big heterogeneous data that are longitudinal, high dimensional with missing values. Unsupervised learning methods have been widely applied in this area, however, validating the optimal number of clusters has been challenging. Built upon our multiple imputation (MI) based fuzzy clustering, MIfuzzy, we proposed a new multiple imputation based validation (MIV) framework and corresponding MIV algorithms for clustering big longitudinal eHealth data with missing values, more generally for fuzzy-logic based clustering methods. Specifically, we detect the optimal number of clusters by auto-searching and -synthesizing a suite of MI-based validation methods and indices, including conventional (bootstrap or cross-validation based) and emerging (modularity-based) validation indices for general clustering methods as well as the specific one (Xie and Beni) for fuzzy clustering. The MIV performance was demonstrated on a big longitudinal dataset from a real web-delivered trial and using simulation. The results indicate MI-based Xie and Beni index for fuzzy-clustering is more appropriate for detecting the optimal number of clusters for such complex data. The MIV concept and algorithms could be easily adapted to different types of clustering that could process big incomplete longitudinal trial data in eHealth services. PMID:27126063

Rayleigh wave dispersion curve inversion by using particle swarm optimization and genetic algorithm

NASA Astrophysics Data System (ADS)

Buyuk, Ersin; Zor, Ekrem; Karaman, Abdullah

2017-04-01

Inversion of surface wave dispersion curves with its highly nonlinear nature has some difficulties using traditional linear inverse methods due to the need and strong dependence to the initial model, possibility of trapping in local minima and evaluation of partial derivatives. There are some modern global optimization methods to overcome of these difficulties in surface wave analysis such as Genetic algorithm (GA) and Particle Swarm Optimization (PSO). GA is based on biologic evolution consisting reproduction, crossover and mutation operations, while PSO algorithm developed after GA is inspired from the social behaviour of birds or fish of swarms. Utility of these methods require plausible convergence rate, acceptable relative error and optimum computation cost that are important for modelling studies. Even though PSO and GA processes are similar in appearence, the cross-over operation in GA is not used in PSO and the mutation operation is a stochastic process for changing the genes within chromosomes in GA. Unlike GA, the particles in PSO algorithm changes their position with logical velocities according to particle's own experience and swarm's experience. In this study, we applied PSO algorithm to estimate S wave velocities and thicknesses of the layered earth model by using Rayleigh wave dispersion curve and also compared these results with GA and we emphasize on the advantage of using PSO algorithm for geophysical modelling studies considering its rapid convergence, low misfit error and computation cost.

A novel fuzzy logic-based image steganography method to ensure medical data security.

PubMed

Karakış, R; Güler, I; Çapraz, I; Bilir, E

2015-12-01

This study aims to secure medical data by combining them into one file format using steganographic methods. The electroencephalogram (EEG) is selected as hidden data, and magnetic resonance (MR) images are also used as the cover image. In addition to the EEG, the message is composed of the doctor׳s comments and patient information in the file header of images. Two new image steganography methods that are based on fuzzy-logic and similarity are proposed to select the non-sequential least significant bits (LSB) of image pixels. The similarity values of the gray levels in the pixels are used to hide the message. The message is secured to prevent attacks by using lossless compression and symmetric encryption algorithms. The performance of stego image quality is measured by mean square of error (MSE), peak signal-to-noise ratio (PSNR), structural similarity measure (SSIM), universal quality index (UQI), and correlation coefficient (R). According to the obtained result, the proposed method ensures the confidentiality of the patient information, and increases data repository and transmission capacity of both MR images and EEG signals. Copyright © 2015 Elsevier Ltd. All rights reserved.

GUI Type Fault Diagnostic Program for a Turboshaft Engine Using Fuzzy and Neural Networks

NASA Astrophysics Data System (ADS)

Kong, Changduk; Koo, Youngju

2011-04-01

The helicopter to be operated in a severe flight environmental condition must have a very reliable propulsion system. On-line condition monitoring and fault detection of the engine can promote reliability and availability of the helicopter propulsion system. A hybrid health monitoring program using Fuzzy Logic and Neural Network Algorithms can be proposed. In this hybrid method, the Fuzzy Logic identifies easily the faulted components from engine measuring parameter changes, and the Neural Networks can quantify accurately its identified faults. In order to use effectively the fault diagnostic system, a GUI (Graphical User Interface) type program is newly proposed. This program is composed of the real time monitoring part, the engine condition monitoring part and the fault diagnostic part. The real time monitoring part can display measuring parameters of the study turboshaft engine such as power turbine inlet temperature, exhaust gas temperature, fuel flow, torque and gas generator speed. The engine condition monitoring part can evaluate the engine condition through comparison between monitoring performance parameters the base performance parameters analyzed by the base performance analysis program using look-up tables. The fault diagnostic part can identify and quantify the single faults the multiple faults from the monitoring parameters using hybrid method.

Enzyme-based logic gates and circuits-analytical applications and interfacing with electronics.

PubMed

Katz, Evgeny; Poghossian, Arshak; Schöning, Michael J

2017-01-01

The paper is an overview of enzyme-based logic gates and their short circuits, with specific examples of Boolean AND and OR gates, and concatenated logic gates composed of multi-step enzyme-biocatalyzed reactions. Noise formation in the biocatalytic reactions and its decrease by adding a "filter" system, converting convex to sigmoid response function, are discussed. Despite the fact that the enzyme-based logic gates are primarily considered as components of future biomolecular computing systems, their biosensing applications are promising for immediate practical use. Analytical use of the enzyme logic systems in biomedical and forensic applications is discussed and exemplified with the logic analysis of biomarkers of various injuries, e.g., liver injury, and with analysis of biomarkers characteristic of different ethnicity found in blood samples on a crime scene. Interfacing of enzyme logic systems with modified electrodes and semiconductor devices is discussed, giving particular attention to the interfaces functionalized with signal-responsive materials. Future perspectives in the design of the biomolecular logic systems and their applications are discussed in the conclusion. Graphical Abstract Various applications and signal-transduction methods are reviewed for enzyme-based logic systems.

Examining the Return on Investment of a Security Information and Event Management Solution in a Notional Department of Defense Network Environment

DTIC Science & Technology

2013-06-01

collection are the facts that devices the lack encryption or compression methods and that the log file must be saved on the host system prior to transfer...time. Statistical correlation utilizes numerical algorithms to detect deviations from normal event levels and other routine activities (Chuvakin...can also assist in detecting low volume threats. Although easy and logical to implement, the implementation of statistical correlation algorithms

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

A Novel Topology Control Approach to Maintain the Node Degree in Dynamic Wireless Sensor Networks

PubMed Central

Huang, Yuanjiang; Martínez, José-Fernán; Díaz, Vicente Hernández; Sendra, Juana

2014-01-01

Topology control is an important technique to improve the connectivity and the reliability of Wireless Sensor Networks (WSNs) by means of adjusting the communication range of wireless sensor nodes. In this paper, a novel Fuzzy-logic Topology Control (FTC) is proposed to achieve any desired average node degree by adaptively changing communication range, thus improving the network connectivity, which is the main target of FTC. FTC is a fully localized control algorithm, and does not rely on location information of neighbors. Instead of designing membership functions and if-then rules for fuzzy-logic controller, FTC is constructed from the training data set to facilitate the design process. FTC is proved to be accurate, stable and has short settling time. In order to compare it with other representative localized algorithms (NONE, FLSS, k-Neighbor and LTRT), FTC is evaluated through extensive simulations. The simulation results show that: firstly, similar to k-Neighbor algorithm, FTC is the best to achieve the desired average node degree as node density varies; secondly, FTC is comparable to FLSS and k-Neighbor in terms of energy-efficiency, but is better than LTRT and NONE; thirdly, FTC has the lowest average maximum communication range than other algorithms, which indicates that the most energy-consuming node in the network consumes the lowest power. PMID:24608008

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.

Motivation for DOC III: 64-bit digital optical computer

NASA Astrophysics Data System (ADS)

Guilfoyle, Peter S.

1991-09-01

OptiComp has focused on a digital optical logic family in order to capitalize on the inherent benefits of optical computing, which include (1) high FAN-IN and FAN-OUT, (2) low power consumption, (3) high noise margin, (4) high algorithmic efficiency using 'smart' interconnects, and (5) free-space leverage of gate interconnect bandwidth product. Other well-known secondary advantages of optical logic include zero capacitive loading of signals at a detector, zero cross-talk between signals, zero signal dispersion, and minimal clock skew (a few picoseconds or less in an imaging system). The primary focus of this paper is to demonstrate how each of the five advantages can be used to leverage other logic family performance such as GaAs; the secondary attributes are discussed only in the context of introducing the DOC III architecture.

An Interval Type-2 Fuzzy Multiple Echelon Supply Chain Model

NASA Astrophysics Data System (ADS)

Miller, Simon; John, Robert

Planning resources for a supply chain is a major factor determining its success or failure. In this paper we build on previous work introducing an Interval Type-2 Fuzzy Logic model of a multiple echelon supply chain. It is believed that the additional degree of uncertainty provided by Interval Type-2 Fuzzy Logic will allow for better representation of the uncertainty and vagueness present in resource planning models. First, the subject of Supply Chain Management is introduced, then some background is given on related work using Type-1 Fuzzy Logic. A description of the Interval Type-2 Fuzzy model is given, and a test scenario detailed. A Genetic Algorithm uses the model to search for a near-optimal plan for the scenario. A discussion of the results follows, along with conclusions and details of intended further work.

Implementation Of Fuzzy Automated Brake Controller Using TSK Algorithm

NASA Astrophysics Data System (ADS)

Mittal, Ruchi; Kaur, Magandeep

2010-11-01

In this paper an application of Fuzzy Logic for Automatic Braking system is proposed. Anti-blocking system (ABS) brake controllers pose unique challenges to the designer: a) For optimal performance, the controller must operate at an unstable equilibrium point, b) Depending on road conditions, the maximum braking torque may vary over a wide range, c) The tire slippage measurement signal, crucial for controller performance, is both highly uncertain and noisy. A digital controller design was chosen which combines a fuzzy logic element and a decision logic network. The controller identifies the current road condition and generates a command braking pressure signal Depending upon the speed and distance of train. This paper describes design criteria, and the decision and rule structure of the control system. The simulation results present the system's performance depending upon the varying speed and distance of the train.

[Application of a mathematical algorithm for the detection of electroneuromyographic results in the pathogenesis study of facial dyskinesia].

PubMed

Gribova, N P; Iudel'son, Ia B; Golubev, V L; Abramenkova, I V

2003-01-01

To carry out a differential diagnosis of two facial dyskinesia (FD) models--facial hemispasm (FH) and facial paraspasm (FP), a combined program of electroneuromyographic (ENMG) examination has been created, using statistical analyses, including that for objects identification based on hybrid neural network with the application of adaptive fuzzy logic method and standard statistics programs (Wilcoxon, Student statistics). In FH, a lesion of peripheral facial neuromotor apparatus with augmentation of functions of inter-neurons in segmental and upper segmental stem levels predominated. In FP, primary afferent strengthening in mimic muscles was accompanied by increased motor neurons activity and reciprocal augmentation of inter-neurons, inhibiting motor portion of V pair. Mathematical algorithm for ENMG results recognition worked out in the study provides a precise differentiation of two FD models and opens possibilities for differential diagnosis of other facial motor disorders.

A Framework to Debug Diagnostic Matrices

NASA Technical Reports Server (NTRS)

Kodal, Anuradha; Robinson, Peter; Patterson-Hine, Ann

2013-01-01

Diagnostics is an important concept in system health and monitoring of space operations. Many of the existing diagnostic algorithms utilize system knowledge in the form of diagnostic matrix (D-matrix, also popularly known as diagnostic dictionary, fault signature matrix or reachability matrix) gleaned from physical models. But, sometimes, this may not be coherent to obtain high diagnostic performance. In such a case, it is important to modify this D-matrix based on knowledge obtained from other sources such as time-series data stream (simulated or maintenance data) within the context of a framework that includes the diagnostic/inference algorithm. A systematic and sequential update procedure, diagnostic modeling evaluator (DME) is proposed to modify D-matrix and wrapper logic considering least expensive solution first. This iterative procedure includes conditions ranging from modifying 0s and 1s in the matrix, or adding/removing the rows (failure sources) columns (tests). We will experiment this framework on datasets from DX challenge 2009.

Human Memory Organization for Computer Programs.

ERIC Educational Resources Information Center

Norcio, A. F.; Kerst, Stephen M.

1983-01-01

Results of study investigating human memory organization in processing of computer programming languages indicate that algorithmic logic segments form a cognitive organizational structure in memory for programs. Statement indentation and internal program documentation did not enhance organizational process of recall of statements in five Fortran…

Creating Science Simulations through Computational Thinking Patterns

ERIC Educational Resources Information Center

Basawapatna, Ashok Ram

2012-01-01

Computational thinking aims to outline fundamental skills from computer science that everyone should learn. As currently defined, with help from the National Science Foundation (NSF), these skills include problem formulation, logically organizing data, automating solutions through algorithmic thinking, and representing data through abstraction.…

Evaluation of Surface Sampling for Bacillus Spores Using ...

EPA Pesticide Factsheets

Journal Article In this study, commercially-available domestic cleaning robots were evaluated for spore surface sampling efficiency on common indoor surfaces. The current study determined the sampling efficiency of each robot, without modifying the sensors, algorithms, or logics set by the manufacturers.

Telerobotic control of a mobile coordinated robotic server, executive summary

NASA Technical Reports Server (NTRS)

Lee, Gordon

1993-01-01

This interim report continues with the research effort on advanced adaptive controls for space robotics systems. In particular, previous results developed by the principle investigator and his research team centered around fuzzy logic control (FLC) in which the lack of knowledge of the robotic system as well as the uncertainties of the environment are compensated for by a rule base structure which interacts with varying degrees of belief of control action using system measurements. An on-line adaptive algorithm was developed using a single parameter tuning scheme. In the effort presented, the methodology is further developed to include on-line scaling factor tuning and self-learning control as well as extended to the multi-input, multi-output (MIMO) case. Classical fuzzy logic control requires tuning input scale factors off-line through trial and error techniques. This is time-consuming and cannot adapt to new changes in the process. The new adaptive FLC includes a self-tuning scheme for choosing the scaling factors on-line. Further the rule base in classical FLC is usually produced by soliciting knowledge from human operators as to what is good control action for given circumstances. This usually requires full knowledge and experience of the process and operating conditions, which limits applicability. A self-learning scheme is developed which adaptively forms the rule base with very limited knowledge of the process. Finally, a MIMO method is presented employing optimization techniques. This is required for application to space robotics in which several degrees-of-freedom links are commonly used. Simulation examples are presented for terminal control - typical of robotic problems in which a desired terminal point is to be reached for each link. Future activities will be to implement the MIMO adaptive FLC on an INTEL microcontroller-based circuit and to test the algorithm on a robotic system at the Mars Mission Research Center at North Carolina State University.

SPECIAL ISSUE ON OPTICAL PROCESSING OF INFORMATION: Method of implementation of optoelectronic multiparametric signal processing systems based on multivalued-logic principles

NASA Astrophysics Data System (ADS)

Arestova, M. L.; Bykovskii, A. Yu

1995-10-01

An architecture is proposed for a specialised optoelectronic multivalued logic processor based on the Allen—Givone algebra. The processor is intended for multiparametric processing of data arriving from a large number of sensors or for tackling spectral analysis tasks. The processor architecture makes it possible to obtain an approximate general estimate of the state of an object being diagnosed on a p-level scale. Optoelectronic systems are proposed for MAXIMUM, MINIMUM, and LITERAL logic gates, based on optical-frequency encoding of logic levels. Corresponding logic gates form a complete set of logic functions in the Allen—Givone algebra.

C code generation from Petri-net-based logic controller specification

NASA Astrophysics Data System (ADS)

Grobelny, Michał; Grobelna, Iwona; Karatkevich, Andrei

2017-08-01

The article focuses on programming of logic controllers. It is important that a programming code of a logic controller is executed flawlessly according to the primary specification. In the presented approach we generate C code for an AVR microcontroller from a rule-based logical model of a control process derived from a control interpreted Petri net. The same logical model is also used for formal verification of the specification by means of the model checking technique. The proposed rule-based logical model and formal rules of transformation ensure that the obtained implementation is consistent with the already verified specification. The approach is validated by practical experiments.

Advanced Health Management Algorithms for Crew Exploration Applications

NASA Technical Reports Server (NTRS)

Davidson, Matt; Stephens, John; Jones, Judit

2005-01-01

Achieving the goals of the President's Vision for Exploration will require new and innovative ways to achieve reliability increases of key systems and sub-systems. The most prominent approach used in current systems is to maintain hardware redundancy. This imposes constraints to the system and utilizes weight that could be used for payload for extended lunar, Martian, or other deep space missions. A technique to improve reliability while reducing the system weight and constraints is through the use of an Advanced Health Management System (AHMS). This system contains diagnostic algorithms and decision logic to mitigate or minimize the impact of system anomalies on propulsion system performance throughout the powered flight regime. The purposes of the AHMS are to increase the probability of successfully placing the vehicle into the intended orbit (Earth, Lunar, or Martian escape trajectory), increase the probability of being able to safely execute an abort after it has developed anomalous performance during launch or ascent phases of the mission, and to minimize or mitigate anomalies during the cruise portion of the mission. This is accomplished by improving the knowledge of the state of the propulsion system operation at any given turbomachinery vibration protection logic and an overall system analysis algorithm that utilizes an underlying physical model and a wide array of engine system operational parameters to detect and mitigate predefined engine anomalies. These algorithms are generic enough to be utilized on any propulsion system yet can be easily tailored to each application by changing input data and engine specific parameters. The key to the advancement of such a system is the verification of the algorithms. These algorithms will be validated through the use of a database of nominal and anomalous performance from a large propulsion system where data exists for catastrophic and noncatastrophic propulsion sytem failures.

Algorithms and theory for the design and programming of industrial control systems materialized with PLC's

NASA Astrophysics Data System (ADS)

Montoya Villena, Rafael

According to its title, the general objective of the Thesis consists in developing a clear, simple and systematic methodology for programming type PLC devices. With this aim in mind, we will use the following elements: Codification of all variables types. This section is very important since it allows us working with little information. The necessary rules are given to codify all type of phrases produced in industrial processes. An algorithm that describes process evolution and that has been called process D.F. This is one of the most important contributions, since it will allow us, together with information codification, representing the process evolution in a graphic way and with any design theory used. Theory selection. Evidently, the use of some kind of design method is necessary to obtain logic equations. For this particular case, we will use binodal theory, an ideal theory for wired technologies, since it can obtain highly reduced schemas for relatively simple automatisms, which means a minimum number of components used. User program outline algorithm (D.F.P.). This is another necessary contribution and perhaps the most important one, since logic equations resulting from binodal theory are compatible with process evolution if wired technology is used, whether it is electric, electronic, pneumatic, etc. On the other hand, PLC devices performance characteristics force the program instructions order to validate or not the automatism, as we have proven in different articles and lectures at congresses both national and international. Therefore, we will codify any information concerning the automating process, graphically represent its temporal evolution and, applying binodal theory and D.F.P (previously adapted), succeed in making logic equations compatible with the process to be automated and the device in which they will be implemented (PLC in our case)

RISMA: A Rule-based Interval State Machine Algorithm for Alerts Generation, Performance Analysis and Monitoring Real-Time Data Processing

NASA Astrophysics Data System (ADS)

Laban, Shaban; El-Desouky, Aly

2013-04-01

The monitoring of real-time systems is a challenging and complicated process. So, there is a continuous need to improve the monitoring process through the use of new intelligent techniques and algorithms for detecting exceptions, anomalous behaviours and generating the necessary alerts during the workflow monitoring of such systems. The interval-based or period-based theorems have been discussed, analysed, and used by many researches in Artificial Intelligence (AI), philosophy, and linguistics. As explained by Allen, there are 13 relations between any two intervals. Also, there have also been many studies of interval-based temporal reasoning and logics over the past decades. Interval-based theorems can be used for monitoring real-time interval-based data processing. However, increasing the number of processed intervals makes the implementation of such theorems a complex and time consuming process as the relationships between such intervals are increasing exponentially. To overcome the previous problem, this paper presents a Rule-based Interval State Machine Algorithm (RISMA) for processing, monitoring, and analysing the behaviour of interval-based data, received from real-time sensors. The proposed intelligent algorithm uses the Interval State Machine (ISM) approach to model any number of interval-based data into well-defined states as well as inferring them. An interval-based state transition model and methodology are presented to identify the relationships between the different states of the proposed algorithm. By using such model, the unlimited number of relationships between similar large numbers of intervals can be reduced to only 18 direct relationships using the proposed well-defined states. For testing the proposed algorithm, necessary inference rules and code have been designed and applied to the continuous data received in near real-time from the stations of International Monitoring System (IMS) by the International Data Centre (IDC) of the Preparatory Commission for the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO). The CLIPS expert system shell has been used as the main rule engine for implementing the algorithm rules. Python programming language and the module "PyCLIPS" are used for building the necessary code for algorithm implementation. More than 1.7 million intervals constitute the Concise List of Frames (CLF) from 20 different seismic stations have been used for evaluating the proposed algorithm and evaluating stations behaviour and performance. The initial results showed that proposed algorithm can help in better understanding of the operation and performance of those stations. Different important information, such as alerts and some station performance parameters, can be derived from the proposed algorithm. For IMS interval-based data and at any period of time it is possible to analyze station behavior, determine the missing data, generate necessary alerts, and to measure some of station performance attributes. The details of the proposed algorithm, methodology, implementation, experimental results, advantages, and limitations of this research are presented. Finally, future directions and recommendations are discussed.

Spot quantification in two dimensional gel electrophoresis image analysis: comparison of different approaches and presentation of a novel compound fitting algorithm

PubMed Central

2014-01-01

Background Various computer-based methods exist for the detection and quantification of protein spots in two dimensional gel electrophoresis images. Area-based methods are commonly used for spot quantification: an area is assigned to each spot and the sum of the pixel intensities in that area, the so-called volume, is used a measure for spot signal. Other methods use the optical density, i.e. the intensity of the most intense pixel of a spot, or calculate the volume from the parameters of a fitted function. Results In this study we compare the performance of different spot quantification methods using synthetic and real data. We propose a ready-to-use algorithm for spot detection and quantification that uses fitting of two dimensional Gaussian function curves for the extraction of data from two dimensional gel electrophoresis (2-DE) images. The algorithm implements fitting using logical compounds and is computationally efficient. The applicability of the compound fitting algorithm was evaluated for various simulated data and compared with other quantification approaches. We provide evidence that even if an incorrect bell-shaped function is used, the fitting method is superior to other approaches, especially when spots overlap. Finally, we validated the method with experimental data of urea-based 2-DE of Aβ peptides andre-analyzed published data sets. Our methods showed higher precision and accuracy than other approaches when applied to exposure time series and standard gels. Conclusion Compound fitting as a quantification method for 2-DE spots shows several advantages over other approaches and could be combined with various spot detection methods. The algorithm was scripted in MATLAB (Mathworks) and is available as a supplemental file. PMID:24915860

Construction of a fuzzy and Boolean logic gates based on DNA.

PubMed

Zadegan, Reza M; Jepsen, Mette D E; Hildebrandt, Lasse L; Birkedal, Victoria; Kjems, Jørgen

2015-04-17

Logic gates are devices that can perform logical operations by transforming a set of inputs into a predictable single detectable output. The hybridization properties, structure, and function of nucleic acids can be used to make DNA-based logic gates. These devices are important modules in molecular computing and biosensing. The ideal logic gate system should provide a wide selection of logical operations, and be integrable in multiple copies into more complex structures. Here we show the successful construction of a small DNA-based logic gate complex that produces fluorescent outputs corresponding to the operation of the six Boolean logic gates AND, NAND, OR, NOR, XOR, and XNOR. The logic gate complex is shown to work also when implemented in a three-dimensional DNA origami box structure, where it controlled the position of the lid in a closed or open position. Implementation of multiple microRNA sensitive DNA locks on one DNA origami box structure enabled fuzzy logical operation that allows biosensing of complex molecular signals. Integrating logic gates with DNA origami systems opens a vast avenue to applications in the fields of nanomedicine for diagnostics and therapeutics. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Image Encryption Algorithm Based on Hyperchaotic Maps and Nucleotide Sequences Database

PubMed Central

2017-01-01

Image encryption technology is one of the main means to ensure the safety of image information. Using the characteristics of chaos, such as randomness, regularity, ergodicity, and initial value sensitiveness, combined with the unique space conformation of DNA molecules and their unique information storage and processing ability, an efficient method for image encryption based on the chaos theory and a DNA sequence database is proposed. In this paper, digital image encryption employs a process of transforming the image pixel gray value by using chaotic sequence scrambling image pixel location and establishing superchaotic mapping, which maps quaternary sequences and DNA sequences, and by combining with the logic of the transformation between DNA sequences. The bases are replaced under the displaced rules by using DNA coding in a certain number of iterations that are based on the enhanced quaternary hyperchaotic sequence; the sequence is generated by Chen chaos. The cipher feedback mode and chaos iteration are employed in the encryption process to enhance the confusion and diffusion properties of the algorithm. Theoretical analysis and experimental results show that the proposed scheme not only demonstrates excellent encryption but also effectively resists chosen-plaintext attack, statistical attack, and differential attack. PMID:28392799

Development of a constant surface pressure penetration langmuir balance based on axisymmetric drop shape analysis.

PubMed

Wege, H A; Holgado-Terriza, J A; Cabrerizo-Vílchez, M A

2002-05-15

A new constant pressure pendant-drop penetration surface balance has been developed combining a pendant-drop surface balance, a rapid-subphase-exchange technique, and a fuzzy logic control algorithm. Beside the determination of insoluble monolayer compression-expansion isotherms, it allows performance of noninvasive kinetic studies of the adsorption of surfactants added to the new subphase onto the free surface and of the adsorption/penetration/reaction of the former onto/into/with surface layers, respectively. The interfacial pressure pi is a fundamental parameter in these studies: by working at constant pi one controls the height of the energy barrier to adsorption/penetration and can select different regimes and steps of the adsorption/penetration process. In our device a solution drop is formed at the tip of a coaxial double capillary, connected to a double microinjector. Drop profiles are extracted from digital drop micrographs and fitted to the equation of capillarity, yielding pi, the drop volume V, and the interfacial area A. pi is varied changing V (and hence A) with the microinjector. Control is based on a case-adaptable modulated fuzzy-logic PID algorithm able to maintain constant pi (or A) under a wide range of experimental conditions. The drop subphase liquid can be exchanged quantitatively by the coaxial capillaries. The adsorption/penetration/reaction kinetics at constant pi are then studied monitoring A(t), i.e., determining the relative area change necessary at each instant to compensate the pressure variation due to the interaction of the surfactant in the subsurface with the surface layer. A fully Windows-integrated program manages the whole setup. Examples of experimental protein adsorption and monolayer penetration kinetics are presented.

A New Efficient Hybrid Intelligent Model for Biodegradation Process of DMP with Fuzzy Wavelet Neural Networks

NASA Astrophysics Data System (ADS)

Huang, Mingzhi; Zhang, Tao; Ruan, Jujun; Chen, Xiaohong

2017-01-01

A new efficient hybrid intelligent approach based on fuzzy wavelet neural network (FWNN) was proposed for effectively modeling and simulating biodegradation process of Dimethyl phthalate (DMP) in an anaerobic/anoxic/oxic (AAO) wastewater treatment process. With the self learning and memory abilities of neural networks (NN), handling uncertainty capacity of fuzzy logic (FL), analyzing local details superiority of wavelet transform (WT) and global search of genetic algorithm (GA), the proposed hybrid intelligent model can extract the dynamic behavior and complex interrelationships from various water quality variables. For finding the optimal values for parameters of the proposed FWNN, a hybrid learning algorithm integrating an improved genetic optimization and gradient descent algorithm is employed. The results show, compared with NN model (optimized by GA) and kinetic model, the proposed FWNN model have the quicker convergence speed, the higher prediction performance, and smaller RMSE (0.080), MSE (0.0064), MAPE (1.8158) and higher R2 (0.9851) values. which illustrates FWNN model simulates effluent DMP more accurately than the mechanism model.

A New Efficient Hybrid Intelligent Model for Biodegradation Process of DMP with Fuzzy Wavelet Neural Networks

PubMed Central

Huang, Mingzhi; Zhang, Tao; Ruan, Jujun; Chen, Xiaohong

2017-01-01

A new efficient hybrid intelligent approach based on fuzzy wavelet neural network (FWNN) was proposed for effectively modeling and simulating biodegradation process of Dimethyl phthalate (DMP) in an anaerobic/anoxic/oxic (AAO) wastewater treatment process. With the self learning and memory abilities of neural networks (NN), handling uncertainty capacity of fuzzy logic (FL), analyzing local details superiority of wavelet transform (WT) and global search of genetic algorithm (GA), the proposed hybrid intelligent model can extract the dynamic behavior and complex interrelationships from various water quality variables. For finding the optimal values for parameters of the proposed FWNN, a hybrid learning algorithm integrating an improved genetic optimization and gradient descent algorithm is employed. The results show, compared with NN model (optimized by GA) and kinetic model, the proposed FWNN model have the quicker convergence speed, the higher prediction performance, and smaller RMSE (0.080), MSE (0.0064), MAPE (1.8158) and higher R2 (0.9851) values. which illustrates FWNN model simulates effluent DMP more accurately than the mechanism model. PMID:28120889

[Development of a video image system for wireless capsule endoscopes based on DSP].

PubMed

Yang, Li; Peng, Chenglin; Wu, Huafeng; Zhao, Dechun; Zhang, Jinhua

2008-02-01

A video image recorder to record video picture for wireless capsule endoscopes was designed. TMS320C6211 DSP of Texas Instruments Inc. is the core processor of this system. Images are periodically acquired from Composite Video Broadcast Signal (CVBS) source and scaled by video decoder (SAA7114H). Video data is transported from high speed buffer First-in First-out (FIFO) to Digital Signal Processor (DSP) under the control of Complex Programmable Logic Device (CPLD). This paper adopts JPEG algorithm for image coding, and the compressed data in DSP was stored to Compact Flash (CF) card. TMS320C6211 DSP is mainly used for image compression and data transporting. Fast Discrete Cosine Transform (DCT) algorithm and fast coefficient quantization algorithm are used to accelerate operation speed of DSP and decrease the executing code. At the same time, proper address is assigned for each memory, which has different speed;the memory structure is also optimized. In addition, this system uses plenty of Extended Direct Memory Access (EDMA) to transport and process image data, which results in stable and high performance.

Urban Growth Modeling Using Anfis Algorithm: a Case Study for Sanandaj City, Iran

NASA Astrophysics Data System (ADS)

Mohammady, S.; Delavar, M. R.; Pijanowski, B. C.

2013-10-01

Global urban population has increased from 22.9% in 1985 to 47% in 2010. In spite of the tendency for urbanization worldwide, only about 2% of Earth's land surface is covered by cities. Urban population in Iran is increasing due to social and economic development. The proportion of the population living in Iran urban areas has consistently increased from about 31% in 1956 to 68.4% in 2006. Migration of the rural population to cities and population growth in cities have caused many problems, such as irregular growth of cities, improper placement of infrastructure and urban services. Air and environmental pollution, resource degradation and insufficient infrastructure, are the results of poor urban planning that have negative impact on the environment or livelihoods of people living in cities. These issues are a consequence of improper land use planning. Models have been employed to assist in our understanding of relations between land use and its subsequent effects. Different models for urban growth modeling have been developed. Methods from computational intelligence have made great contributions in all specific application domains and hybrid algorithms research as a part of them has become a big trend in computational intelligence. Artificial Neural Network (ANN) has the capability to deal with imprecise data by training, while fuzzy logic can deal with the uncertainty of human cognition. ANN learns from scratch by adjusting the interconnections between layers and Fuzzy Inference Systems (FIS) is a popular computing framework based on the concept of fuzzy set theory, fuzzy logic, and fuzzy reasoning. Fuzzy logic has many advantages such as flexibility and at the other sides, one of the biggest problems in fuzzy logic application is the location and shape and of membership function for each fuzzy variable which is generally being solved by trial and error method. In contrast, numerical computation and learning are the advantages of neural network, however, it is not easy to obtain the optimal structure. Since, in this type of fuzzy logic, neural network has been used, therefore, by using a learning algorithm the parameters have been changed until reach the optimal solution. Adaptive Neuro Fuzzy Inference System (ANFIS) computing due to ability to understand nonlinear structures is a popular framework for solving complex problems. Fusion of ANN and FIS has attracted the growing interest of researchers in various scientific and engineering areas due to the growing need of adaptive intelligent systems to solve the real world problems. In this research, an ANFIS method has been developed for modeling land use change and interpreting the relationship between the drivers of urbanization. Our study area is the city of Sanandaj located in the west of Iran. Landsat images acquired in 2000 and 2006 have been used for model development and calibration. The parameters used in this study include distance to major roads, distance to residential regions, elevation, number of urban pixels in a 3 by 3 neighborhood and distance to green space. Percent Correct Match (PCM) and Figure of Merit were used to assess model goodness of fit were 93.77% and 64.30%, respectively.

A qualitative study of participants' views on re-consent in a longitudinal biobank.

PubMed

Dixon-Woods, Mary; Kocman, David; Brewster, Liz; Willars, Janet; Laurie, Graeme; Tarrant, Carolyn

2017-03-23

Biomedical research increasingly relies on long-term studies involving use and re-use of biological samples and data stored in large repositories or "biobanks" over lengthy periods, often raising questions about whether and when a re-consenting process should be activated. We sought to investigate the views on re-consent of participants in a longitudinal biobank. We conducted a qualitative study involving interviews with 24 people who were participating in a longitudinal biobank. Their views were elicited using a semi-structured interview schedule and scenarios based on a hypothetical biobank. Data analysis was based on the constant comparative method. What participants identified as requiring new consent was not a straightforward matter predictable by algorithms about the scope of the consent, but instead was contingent. They assessed whether proposed new research implied a fundamental alteration in the underlying character of the biobank and whether specific projects were within the scope of the original consent. What mattered most to them was that the cooperative bargain into which they had entered was maintained in good faith. They saw re-consent as one important safeguard in this bargain. In determining what required re-consent, they deployed two logics. First, they used a logic of boundaries, where they sought to detect any possible rupture with their existing framework of cooperation. Second, they used a logic of risk, where they assessed proposed research for any potential threats for them personally or the research endeavour. When they judged that a need for re-consent had been activated, participants saw the process as way of re-actualising and renewing the cooperative bargain. Participants' perceptions of research as a process of mutual co-operation between volunteer and researcher were fundamental to their views on consent. Consenting arrangements for biobanks should respect the cooperative values that are important to participants, recognise the two logics used by research volunteers, and avoid rigidity. Agility may be favoured by tiered consent combined with strong oversight mechanisms; this approach requires evaluation.

The visual information system

Treesearch

Merlyn J. Paulson

1979-01-01

This paper outlines a project level process (V.I.S.) which utilizes very accurate and flexible computer algorithms in combination with contemporary site analysis and design techniques for visual evaluation, design and management. The process provides logical direction and connecting bridges through problem identification, information collection and verification, visual...

Hardware Algorithm Implementation for Mission Specific Processing

DTIC Science & Technology

2008-03-01

knowledge about the VLSI technology and understands VHDL, scripting, and intergrating the script in Cadencersoftware pro- gram or Modelsimr. The main...possible to have a trade off between parallel and serial logic design for the circuit. Power can be saved by using parallization, pipelining, or a

A Programming Environment for Parallel Vision Algorithms

DTIC Science & Technology

1990-04-11

industrial arm on the market , while the unique head was designed by Rochester’s Computer Science and Mechanical Engineering Departments. 9a 4.1 Introduction...R. Constraining-Unification and the Programming Language Unicorn . In Logic Programming, Functions, Relations, and Equations, Degroot and Lind- strom

Aircraft Engine On-Line Diagnostics Through Dual-Channel Sensor Measurements: Development of an Enhanced System

NASA Technical Reports Server (NTRS)

Kobayashi, Takahisa; Simon, Donald L.

2008-01-01

In this paper, an enhanced on-line diagnostic system which utilizes dual-channel sensor measurements is developed for the aircraft engine application. The enhanced system is composed of a nonlinear on-board engine model (NOBEM), the hybrid Kalman filter (HKF) algorithm, and fault detection and isolation (FDI) logic. The NOBEM provides the analytical third channel against which the dual-channel measurements are compared. The NOBEM is further utilized as part of the HKF algorithm which estimates measured engine parameters. Engine parameters obtained from the dual-channel measurements, the NOBEM, and the HKF are compared against each other. When the discrepancy among the signals exceeds a tolerance level, the FDI logic determines the cause of discrepancy. Through this approach, the enhanced system achieves the following objectives: 1) anomaly detection, 2) component fault detection, and 3) sensor fault detection and isolation. The performance of the enhanced system is evaluated in a simulation environment using faults in sensors and components, and it is compared to an existing baseline system.

Bird's-eye view on noise-based logic.

PubMed

Kish, Laszlo B; Granqvist, Claes G; Horvath, Tamas; Klappenecker, Andreas; Wen, He; Bezrukov, Sergey M

2014-01-01

Noise-based logic is a practically deterministic logic scheme inspired by the randomness of neural spikes and uses a system of uncorrelated stochastic processes and their superposition to represent the logic state. We briefly discuss various questions such as ( i ) What does practical determinism mean? ( ii ) Is noise-based logic a Turing machine? ( iii ) Is there hope to beat (the dreams of) quantum computation by a classical physical noise-based processor, and what are the minimum hardware requirements for that? Finally, ( iv ) we address the problem of random number generators and show that the common belief that quantum number generators are superior to classical (thermal) noise-based generators is nothing but a myth.

Bird's-eye view on noise-based logic

NASA Astrophysics Data System (ADS)

Kish, Laszlo B.; Granqvist, Claes G.; Horvath, Tamas; Klappenecker, Andreas; Wen, He; Bezrukov, Sergey M.

2014-09-01

Noise-based logic is a practically deterministic logic scheme inspired by the randomness of neural spikes and uses a system of uncorrelated stochastic processes and their superposition to represent the logic state. We briefly discuss various questions such as (i) What does practical determinism mean? (ii) Is noise-based logic a Turing machine? (iii) Is there hope to beat (the dreams of) quantum computation by a classical physical noise-based processor, and what are the minimum hardware requirements for that? Finally, (iv) we address the problem of random number generators and show that the common belief that quantum number generators are superior to classical (thermal) noise-based generators is nothing but a myth.

Hardware implementation of fuzzy Petri net as a controller.

PubMed

Gniewek, Lesław; Kluska, Jacek

2004-06-01

The paper presents a new approach to fuzzy Petri net (FPN) and its hardware implementation. The authors' motivation is as follows. Complex industrial processes can be often decomposed into many parallelly working subprocesses, which can, in turn, be modeled using Petri nets. If all the process variables (or events) are assumed to be two-valued signals, then it is possible to obtain a hardware or software control device, which works according to the algorithm described by conventional Petri net. However, the values of real signals are contained in some bounded interval and can be interpreted as events which are not only true or false, but rather true in some degree from the interval [0, 1]. Such a natural interpretation from multivalued logic (fuzzy logic) point of view, concerns sensor outputs, control signals, time expiration, etc. It leads to the idea of FPN as a controller, which one can rather simply obtain, and which would be able to process both analog, and binary signals. In the paper both graphical, and algebraic representations of the proposed FPN are given. The conditions under which transitions can be fired are described. The algebraic description of the net and a theorem which enables computation of new marking in the net, based on current marking, are formulated. Hardware implementation of the FPN, which uses fuzzy JK flip-flops and fuzzy gates, are proposed. An example illustrating usefulness of the proposed FPN for control algorithm description and its synthesis as a controller device for the concrete production process are presented.

Reprogrammable Logic Gate and Logic Circuit Based on Multistimuli-Responsive Raspberry-like Micromotors.

PubMed

Zhang, Lina; Zhang, Hui; Liu, Mei; Dong, Bin

2016-06-22

In this paper, we report a polymer-based raspberry-like micromotor. Interestingly, the resulting micromotor exhibits multistimuli-responsive motion behavior. Its on-off-on motion can be regulated by the application of stimuli such as H2O2, near-infrared light, NH3, or their combinations. Because of the versatility in motion control, the current micromotor has great potential in the application field of logic gate and logic circuit. With use of different stimuli as the inputs and the micromotor motion as the output, reprogrammable OR and INHIBIT logic gates or logic circuit consisting of OR, NOT, and AND logic gates can be achieved.

Using artificial intelligence to predict permeability from petrographic data

NASA Astrophysics Data System (ADS)

Ali, Maqsood; Chawathé, Adwait

2000-10-01

Petrographic data collected during thin section analysis can be invaluable for understanding the factors that control permeability distribution. Reliable prediction of permeability is important for reservoir characterization. The petrographic elements (mineralogy, porosity types, cements and clays, and pore morphology) interact with each other uniquely to generate a specific permeability distribution. It is difficult to quantify accurately this interaction and its consequent effect on permeability, emphasizing the non-linear nature of the process. To capture these non-linear interactions, neural networks were used to predict permeability from petrographic data. The neural net was used as a multivariate correlative tool because of its ability to learn the non-linear relationships between multiple input and output variables. The study was conducted on the upper Queen formation called the Shattuck Member (Permian age). The Shattuck Member is composed of very fine-grained arkosic sandstone. The core samples were available from the Sulimar Queen and South Lucky Lake fields located in Chaves County, New Mexico. Nineteen petrographic elements were collected for each permeability value using a combined minipermeameter-petrographic technique. In order to reduce noise and overfitting the permeability model, these petrographic elements were screened, and their control (ranking) with respect to permeability was determined using fuzzy logic. Since the fuzzy logic algorithm provides unbiased ranking, it was used to reduce the dimensionality of the input variables. Based on the fuzzy logic ranking, only the most influential petrographic elements were selected as inputs for permeability prediction. The neural net was trained and tested using data from Well 1-16 in the Sulimar Queen field. Relying on the ranking obtained from the fuzzy logic analysis, the net was trained using the most influential three, five, and ten petrographic elements. A fast algorithm (the scaled conjugate gradient method) was used to optimize the network weight matrix. The net was then successfully used to predict the permeability in the nearby South Lucky Lake field, also in the Shattuck Member. This study underscored various important aspects of using neural networks as non-linear estimators. The neural network learnt the complex relationships between petrographic control and permeability. By predicting permeability in a remotely-located, yet geologically similar field, the generalizing capability of the neural network was also demonstrated. In old fields, where conventional petrographic analysis was routine, this technique may be used to supplement core permeability estimates.

A charge- and energy-conserving implicit, electrostatic particle-in-cell algorithm on mapped computational meshes

NASA Astrophysics Data System (ADS)

Chacón, L.; Chen, G.; Barnes, D. C.

2013-01-01

We describe the extension of the recent charge- and energy-conserving one-dimensional electrostatic particle-in-cell algorithm in Ref. [G. Chen, L. Chacón, D.C. Barnes, An energy- and charge-conserving, implicit electrostatic particle-in-cell algorithm, Journal of Computational Physics 230 (2011) 7018-7036] to mapped (body-fitted) computational meshes. The approach maintains exact charge and energy conservation properties. Key to the algorithm is a hybrid push, where particle positions are updated in logical space, while velocities are updated in physical space. The effectiveness of the approach is demonstrated with a challenging numerical test case, the ion acoustic shock wave. The generalization of the approach to multiple dimensions is outlined.

A High Fuel Consumption Efficiency Management Scheme for PHEVs Using an Adaptive Genetic Algorithm

PubMed Central

Lee, Wah Ching; Tsang, Kim Fung; Chi, Hao Ran; Hung, Faan Hei; Wu, Chung Kit; Chui, Kwok Tai; Lau, Wing Hong; Leung, Yat Wah

2015-01-01

A high fuel efficiency management scheme for plug-in hybrid electric vehicles (PHEVs) has been developed. In order to achieve fuel consumption reduction, an adaptive genetic algorithm scheme has been designed to adaptively manage the energy resource usage. The objective function of the genetic algorithm is implemented by designing a fuzzy logic controller which closely monitors and resembles the driving conditions and environment of PHEVs, thus trading off between petrol versus electricity for optimal driving efficiency. Comparison between calculated results and publicized data shows that the achieved efficiency of the fuzzified genetic algorithm is better by 10% than existing schemes. The developed scheme, if fully adopted, would help reduce over 600 tons of CO2 emissions worldwide every day. PMID:25587974

On the Importance of Set-Based Meanings for Categories and Connectives in Mathematical Logic

ERIC Educational Resources Information Center

Dawkins, Paul Christian

2017-01-01

Based on data from a series of teaching experiments on standard tools of mathematical logic, this paper characterizes a range of student meanings for mathematical properties and logical connectives. Some observed meanings inhibited students' adoption of logical structure, while others greatly facilitated it. "Reasoning with predicates"…

Scheme for Quantum Computing Immune to Decoherence

NASA Technical Reports Server (NTRS)

Williams, Colin; Vatan, Farrokh

2008-01-01

A constructive scheme has been devised to enable mapping of any quantum computation into a spintronic circuit in which the computation is encoded in a basis that is, in principle, immune to quantum decoherence. The scheme is implemented by an algorithm that utilizes multiple physical spins to encode each logical bit in such a way that collective errors affecting all the physical spins do not disturb the logical bit. The scheme is expected to be of use to experimenters working on spintronic implementations of quantum logic. Spintronic computing devices use quantum-mechanical spins (typically, electron spins) to encode logical bits. Bits thus encoded (denoted qubits) are potentially susceptible to errors caused by noise and decoherence. The traditional model of quantum computation is based partly on the assumption that each qubit is implemented by use of a single two-state quantum system, such as an electron or other spin-1.2 particle. It can be surprisingly difficult to achieve certain gate operations . most notably, those of arbitrary 1-qubit gates . in spintronic hardware according to this model. However, ironically, certain 2-qubit interactions (in particular, spin-spin exchange interactions) can be achieved relatively easily in spintronic hardware. Therefore, it would be fortunate if it were possible to implement any 1-qubit gate by use of a spin-spin exchange interaction. While such a direct representation is not possible, it is possible to achieve an arbitrary 1-qubit gate indirectly by means of a sequence of four spin-spin exchange interactions, which could be implemented by use of four exchange gates. Accordingly, the present scheme provides for mapping any 1-qubit gate in the logical basis into an equivalent sequence of at most four spin-spin exchange interactions in the physical (encoded) basis. The complexity of the mathematical derivation of the scheme from basic quantum principles precludes a description within this article; it must suffice to report that the derivation provides explicit constructions for finding the exchange couplings in the physical basis needed to implement any arbitrary 1-qubit gate. These constructions lead to spintronic encodings of quantum logic that are more efficient than those of a previously published scheme that utilizes a universal but fixed set of gates.

Fuzzy knowledge base construction through belief networks based on Lukasiewicz logic

NASA Technical Reports Server (NTRS)

Lara-Rosano, Felipe

1992-01-01

In this paper, a procedure is proposed to build a fuzzy knowledge base founded on fuzzy belief networks and Lukasiewicz logic. Fuzzy procedures are developed to do the following: to assess the belief values of a consequent, in terms of the belief values of its logical antecedents and the belief value of the corresponding logical function; and to update belief values when new evidence is available.

Causal Mathematical Logic as a guiding framework for the prediction of "Intelligence Signals" in brain simulations

NASA Astrophysics Data System (ADS)

Lanzalaco, Felix; Pissanetzky, Sergio

2013-12-01

A recent theory of physical information based on the fundamental principles of causality and thermodynamics has proposed that a large number of observable life and intelligence signals can be described in terms of the Causal Mathematical Logic (CML), which is proposed to encode the natural principles of intelligence across any physical domain and substrate. We attempt to expound the current definition of CML, the "Action functional" as a theory in terms of its ability to possess a superior explanatory power for the current neuroscientific data we use to measure the mammalian brains "intelligence" processes at its most general biophysical level. Brain simulation projects define their success partly in terms of the emergence of "non-explicitly programmed" complex biophysical signals such as self-oscillation and spreading cortical waves. Here we propose to extend the causal theory to predict and guide the understanding of these more complex emergent "intelligence Signals". To achieve this we review whether causal logic is consistent with, can explain and predict the function of complete perceptual processes associated with intelligence. Primarily those are defined as the range of Event Related Potentials (ERP) which include their primary subcomponents; Event Related Desynchronization (ERD) and Event Related Synchronization (ERS). This approach is aiming for a universal and predictive logic for neurosimulation and AGi. The result of this investigation has produced a general "Information Engine" model from translation of the ERD and ERS. The CML algorithm run in terms of action cost predicts ERP signal contents and is consistent with the fundamental laws of thermodynamics. A working substrate independent natural information logic would be a major asset. An information theory consistent with fundamental physics can be an AGi. It can also operate within genetic information space and provides a roadmap to understand the live biophysical operation of the phenotype

An algorithm to compute the sequency ordered Walsh transform

NASA Technical Reports Server (NTRS)

Larsen, H.

1976-01-01

A fast sequency-ordered Walsh transform algorithm is presented; this sequency-ordered fast transform is complementary to the sequency-ordered fast Walsh transform introduced by Manz (1972) and eliminating gray code reordering through a modification of the basic fast Hadamard transform structure. The new algorithm retains the advantages of its complement (it is in place and is its own inverse), while differing in having a decimation-in time structure, accepting data in normal order, and returning the coefficients in bit-reversed sequency order. Applications include estimation of Walsh power spectra for a random process, sequency filtering and computing logical autocorrelations, and selective bit reversing.

Shaping up nucleic acid computation.

PubMed

Chen, Xi; Ellington, Andrew D

2010-08-01

Nucleic acid-based nanotechnology has always been perceived as novel, but has begun to move from theoretical demonstrations to practical applications. In particular, the large address spaces available to nucleic acids can be exploited to encode algorithms and/or act as circuits and thereby process molecular information. In this review we not only revisit several milestones in the field of nucleic acid-based computation, but also highlight how the prospects for nucleic acid computation go beyond just a large address space. Functional nucleic acid elements (aptamers, ribozymes, and deoxyribozymes) can serve as inputs and outputs to the environment, and can act as logical elements. Into the future, the chemical dynamics of nucleic acids may prove as useful as hybridization for computation. Copyright © 2010 Elsevier Ltd. All rights reserved.

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.

New-Sum: A Novel Online ABFT Scheme For General Iterative Methods

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

Tao, Dingwen; Song, Shuaiwen; Krishnamoorthy, Sriram

Emerging high-performance computing platforms, with large component counts and lower power margins, are anticipated to be more susceptible to soft errors in both logic circuits and memory subsystems. We present an online algorithm-based fault tolerance (ABFT) approach to efficiently detect and recover soft errors for general iterative methods. We design a novel checksum-based encoding scheme for matrix-vector multiplication that is resilient to both arithmetic and memory errors. Our design decouples the checksum updating process from the actual computation, and allows adaptive checksum overhead control. Building on this new encoding mechanism, we propose two online ABFT designs that can effectively recovermore » from errors when combined with a checkpoint/rollback scheme.« less

Structure-based classification and ontology in chemistry

PubMed Central

2012-01-01

Background Recent years have seen an explosion in the availability of data in the chemistry domain. With this information explosion, however, retrieving relevant results from the available information, and organising those results, become even harder problems. Computational processing is essential to filter and organise the available resources so as to better facilitate the work of scientists. Ontologies encode expert domain knowledge in a hierarchically organised machine-processable format. One such ontology for the chemical domain is ChEBI. ChEBI provides a classification of chemicals based on their structural features and a role or activity-based classification. An example of a structure-based class is 'pentacyclic compound' (compounds containing five-ring structures), while an example of a role-based class is 'analgesic', since many different chemicals can act as analgesics without sharing structural features. Structure-based classification in chemistry exploits elegant regularities and symmetries in the underlying chemical domain. As yet, there has been neither a systematic analysis of the types of structural classification in use in chemistry nor a comparison to the capabilities of available technologies. Results We analyze the different categories of structural classes in chemistry, presenting a list of patterns for features found in class definitions. We compare these patterns of class definition to tools which allow for automation of hierarchy construction within cheminformatics and within logic-based ontology technology, going into detail in the latter case with respect to the expressive capabilities of the Web Ontology Language and recent extensions for modelling structured objects. Finally we discuss the relationships and interactions between cheminformatics approaches and logic-based approaches. Conclusion Systems that perform intelligent reasoning tasks on chemistry data require a diverse set of underlying computational utilities including algorithmic, statistical and logic-based tools. For the task of automatic structure-based classification of chemical entities, essential to managing the vast swathes of chemical data being brought online, systems which are capable of hybrid reasoning combining several different approaches are crucial. We provide a thorough review of the available tools and methodologies, and identify areas of open research. PMID:22480202

Fuzzy forecasting based on two-factors second-order fuzzy-trend logical relationship groups and the probabilities of trends of fuzzy logical relationships.

PubMed

Chen, Shyi-Ming; Chen, Shen-Wen

2015-03-01

In this paper, we present a new method for fuzzy forecasting based on two-factors second-order fuzzy-trend logical relationship groups and the probabilities of trends of fuzzy-trend logical relationships. Firstly, the proposed method fuzzifies the historical training data of the main factor and the secondary factor into fuzzy sets, respectively, to form two-factors second-order fuzzy logical relationships. Then, it groups the obtained two-factors second-order fuzzy logical relationships into two-factors second-order fuzzy-trend logical relationship groups. Then, it calculates the probability of the "down-trend," the probability of the "equal-trend" and the probability of the "up-trend" of the two-factors second-order fuzzy-trend logical relationships in each two-factors second-order fuzzy-trend logical relationship group, respectively. Finally, it performs the forecasting based on the probabilities of the down-trend, the equal-trend, and the up-trend of the two-factors second-order fuzzy-trend logical relationships in each two-factors second-order fuzzy-trend logical relationship group. We also apply the proposed method to forecast the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) and the NTD/USD exchange rates. The experimental results show that the proposed method outperforms the existing methods.

Performance of Geno-Fuzzy Model on rainfall-runoff predictions in claypan watersheds

USDA-ARS?s Scientific Manuscript database

Fuzzy logic provides a relatively simple approach to simulate complex hydrological systems while accounting for the uncertainty of environmental variables. The objective of this study was to develop a fuzzy inference system (FIS) with genetic algorithm (GA) optimization for membership functions (MF...

An Amazing Algorithm

ERIC Educational Resources Information Center

Snapp, Robert R.; Neumann, Maureen D.

2015-01-01

The rapid growth of digital technology, including the worldwide adoption of mobile and embedded computers, places new demands on K-grade 12 educators and their students. Young people should have an opportunity to learn the technical knowledge of computer science (e.g., computer programming, mathematical logic, and discrete mathematics) in order to…

User's manual for the BNW-II optimization code for dry/wet-cooled power plants

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

Braun, D.J.; Bamberger, J.A.; Braun, D.J.

1978-05-01

This volume provides a listing of the BNW-II dry/wet ammonia heat rejection optimization code and is an appendix to Volume I which gives a narrative description of the code's algorithms as well as logic, input and output information.

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

DOEpatents

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

2009-07-21

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

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.

Crystal identification for a dual-layer-offset LYSO based PET system via Lu-176 background radiation and mean shift algorithm

NASA Astrophysics Data System (ADS)

Wei, Qingyang; Ma, Tianyu; Xu, Tianpeng; Zeng, Ming; Gu, Yu; Dai, Tiantian; Liu, Yaqiang

2018-01-01

Modern positron emission tomography (PET) detectors are made from pixelated scintillation crystal arrays and readout by Anger logic. The interaction position of the gamma-ray should be assigned to a crystal using a crystal position map or look-up table. Crystal identification is a critical procedure for pixelated PET systems. In this paper, we propose a novel crystal identification method for a dual-layer-offset LYSO based animal PET system via Lu-176 background radiation and mean shift algorithm. Single photon event data of the Lu-176 background radiation are acquired in list-mode for 3 h to generate a single photon flood map (SPFM). Coincidence events are obtained from the same data using time information to generate a coincidence flood map (CFM). The CFM is used to identify the peaks of the inner layer using the mean shift algorithm. The response of the inner layer is deducted from the SPFM by subtracting CFM. Then, the peaks of the outer layer are also identified using the mean shift algorithm. The automatically identified peaks are manually inspected by a graphical user interface program. Finally, a crystal position map is generated using a distance criterion based on these peaks. The proposed method is verified on the animal PET system with 48 detector blocks on a laptop with an Intel i7-5500U processor. The total runtime for whole system peak identification is 67.9 s. Results show that the automatic crystal identification has 99.98% and 99.09% accuracy for the peaks of the inner and outer layers of the whole system respectively. In conclusion, the proposed method is suitable for the dual-layer-offset lutetium based PET system to perform crystal identification instead of external radiation sources.

Realisation of all 16 Boolean logic functions in a single magnetoresistance memory cell

NASA Astrophysics Data System (ADS)

Gao, Shuang; Yang, Guang; Cui, Bin; Wang, Shouguo; Zeng, Fei; Song, Cheng; Pan, Feng

2016-06-01

Stateful logic circuits based on next-generation nonvolatile memories, such as magnetoresistance random access memory (MRAM), promise to break the long-standing von Neumann bottleneck in state-of-the-art data processing devices. For the successful commercialisation of stateful logic circuits, a critical step is realizing the best use of a single memory cell to perform logic functions. In this work, we propose a method for implementing all 16 Boolean logic functions in a single MRAM cell, namely a magnetoresistance (MR) unit. Based on our experimental results, we conclude that this method is applicable to any MR unit with a double-hump-like hysteresis loop, especially pseudo-spin-valve magnetic tunnel junctions with a high MR ratio. Moreover, after simply reversing the correspondence between voltage signals and output logic values, this method could also be applicable to any MR unit with a double-pit-like hysteresis loop. These results may provide a helpful solution for the final commercialisation of MRAM-based stateful logic circuits in the near future.Stateful logic circuits based on next-generation nonvolatile memories, such as magnetoresistance random access memory (MRAM), promise to break the long-standing von Neumann bottleneck in state-of-the-art data processing devices. For the successful commercialisation of stateful logic circuits, a critical step is realizing the best use of a single memory cell to perform logic functions. In this work, we propose a method for implementing all 16 Boolean logic functions in a single MRAM cell, namely a magnetoresistance (MR) unit. Based on our experimental results, we conclude that this method is applicable to any MR unit with a double-hump-like hysteresis loop, especially pseudo-spin-valve magnetic tunnel junctions with a high MR ratio. Moreover, after simply reversing the correspondence between voltage signals and output logic values, this method could also be applicable to any MR unit with a double-pit-like hysteresis loop. These results may provide a helpful solution for the final commercialisation of MRAM-based stateful logic circuits in the near future. Electronic supplementary information (ESI) available. See DOI: 10.1039/c6nr03169b