An Adaptive Sensor Mining Framework for Pervasive Computing Applications

Science.gov (United States)

Rashidi, Parisa; Cook, Diane J.

Analyzing sensor data in pervasive computing applications brings unique challenges to the KDD community. The challenge is heightened when the underlying data source is dynamic and the patterns change. We introduce a new adaptive mining framework that detects patterns in sensor data, and more importantly, adapts to the changes in the underlying model. In our framework, the frequent and periodic patterns of data are first discovered by the Frequent and Periodic Pattern Miner (FPPM) algorithm; and then any changes in the discovered patterns over the lifetime of the system are discovered by the Pattern Adaptation Miner (PAM) algorithm, in order to adapt to the changing environment. This framework also captures vital context information present in pervasive computing applications, such as the startup triggers and temporal information. In this paper, we present a description of our mining framework and validate the approach using data collected in the CASAS smart home testbed.

Adaptive, dynamic, and resilient systems

CERN Document Server

Suri, Niranjan

2015-01-01

As the complexity of today's networked computer systems grows, they become increasingly difficult to understand, predict, and control. Addressing these challenges requires new approaches to building these systems. Adaptive, Dynamic, and Resilient Systems supplies readers with various perspectives of the critical infrastructure that systems of networked computers rely on. It introduces the key issues, describes their interrelationships, and presents new research in support of these areas.The book presents the insights of a different group of international experts in each chapter. Reporting on r

Processing Optimization of Typed Resources with Synchronized Storage and Computation Adaptation in Fog Computing

Directory of Open Access Journals (Sweden)

Zhengyang Song

2018-01-01

Full Text Available Wide application of the Internet of Things (IoT system has been increasingly demanding more hardware facilities for processing various resources including data, information, and knowledge. With the rapid growth of generated resource quantity, it is difficult to adapt to this situation by using traditional cloud computing models. Fog computing enables storage and computing services to perform at the edge of the network to extend cloud computing. However, there are some problems such as restricted computation, limited storage, and expensive network bandwidth in Fog computing applications. It is a challenge to balance the distribution of network resources. We propose a processing optimization mechanism of typed resources with synchronized storage and computation adaptation in Fog computing. In this mechanism, we process typed resources in a wireless-network-based three-tier architecture consisting of Data Graph, Information Graph, and Knowledge Graph. The proposed mechanism aims to minimize processing cost over network, computation, and storage while maximizing the performance of processing in a business value driven manner. Simulation results show that the proposed approach improves the ratio of performance over user investment. Meanwhile, conversions between resource types deliver support for dynamically allocating network resources.

An Adaptive Middleware for Improved Computational Performance

DEFF Research Database (Denmark)

Bonnichsen, Lars Frydendal

, we are improving computational performance by exploiting modern hardware features, such as dynamic voltage-frequency scaling and transactional memory. Adapting software is an iterative process, requiring that we continually revisit it to meet new requirements or realities; a time consuming process......The performance improvements in computer systems over the past 60 years have been fueled by an exponential increase in energy efficiency. In recent years, the phenomenon known as the end of Dennard’s scaling has slowed energy efficiency improvements — but improving computer energy efficiency...... is more important now than ever. Traditionally, most improvements in computer energy efficiency have come from improvements in lithography — the ability to produce smaller transistors — and computer architecture - the ability to apply those transistors efficiently. Since the end of scaling, we have seen...

Water System Adaptation To Hydrological Changes: Module 14, Life Cycle Analysis (LCA) and Prioritization Tools in Water System Adaptation

Science.gov (United States)

This course will introduce students to the fundamental principles of water system adaptation to hydrological changes, with emphasis on data analysis and interpretation, technical planning, and computational modeling. Starting with real-world scenarios and adaptation needs, the co...

Computational Strategies for Dissecting the High-Dimensional Complexity of Adaptive Immune Repertoires

Directory of Open Access Journals (Sweden)

Enkelejda Miho

2018-02-01

Full Text Available The adaptive immune system recognizes antigens via an immense array of antigen-binding antibodies and T-cell receptors, the immune repertoire. The interrogation of immune repertoires is of high relevance for understanding the adaptive immune response in disease and infection (e.g., autoimmunity, cancer, HIV. Adaptive immune receptor repertoire sequencing (AIRR-seq has driven the quantitative and molecular-level profiling of immune repertoires, thereby revealing the high-dimensional complexity of the immune receptor sequence landscape. Several methods for the computational and statistical analysis of large-scale AIRR-seq data have been developed to resolve immune repertoire complexity and to understand the dynamics of adaptive immunity. Here, we review the current research on (i diversity, (ii clustering and network, (iii phylogenetic, and (iv machine learning methods applied to dissect, quantify, and compare the architecture, evolution, and specificity of immune repertoires. We summarize outstanding questions in computational immunology and propose future directions for systems immunology toward coupling AIRR-seq with the computational discovery of immunotherapeutics, vaccines, and immunodiagnostics.

CMAC-based adaptive backstepping synchronization of uncertain chaotic systems

International Nuclear Information System (INIS)

Lin, C.-M.; Peng, Y.-F.; Lin, M.-H.

2009-01-01

This study proposes an adaptive backstepping control system for synchronizing uncertain chaotic system by using cerebellar model articulation controller (CMAC). CMAC is a nonlinear network with simple computation, good generalization capability and fast learning property. The proposed CMAC-based adaptive backstepping control (CABC) system uses backstepping method and adaptive cerebellar model articulation controller (ACMAC) for synchronizing uncertain chaotic system. Finally, simulation results for the Genesio system are presented to illustrate the effectiveness of the proposed control system.

Secure computing on reconfigurable systems

OpenAIRE

Fernandes Chaves, R.J.

2007-01-01

This thesis proposes a Secure Computing Module (SCM) for reconfigurable computing systems. SC provides a protected and reliable computational environment, where data security and protection against malicious attacks to the system is assured. SC is strongly based on encryption algorithms and on the attestation of the executed functions. The use of SC on reconfigurable devices has the advantage of being highly adaptable to the application and the user requirements, while providing high performa...

Adaptively detecting changes in Autonomic Grid Computing

KAUST Repository

Zhang, Xiangliang

2010-10-01

Detecting the changes is the common issue in many application fields due to the non-stationary distribution of the applicative data, e.g., sensor network signals, web logs and gridrunning logs. Toward Autonomic Grid Computing, adaptively detecting the changes in a grid system can help to alarm the anomalies, clean the noises, and report the new patterns. In this paper, we proposed an approach of self-adaptive change detection based on the Page-Hinkley statistic test. It handles the non-stationary distribution without the assumption of data distribution and the empirical setting of parameters. We validate the approach on the EGEE streaming jobs, and report its better performance on achieving higher accuracy comparing to the other change detection methods. Meanwhile this change detection process could help to discover the device fault which was not claimed in the system logs. © 2010 IEEE.

Goal-recognition-based adaptive brain-computer interface for navigating immersive robotic systems

Science.gov (United States)

Abu-Alqumsan, Mohammad; Ebert, Felix; Peer, Angelika

2017-06-01

Objective. This work proposes principled strategies for self-adaptations in EEG-based Brain-computer interfaces (BCIs) as a way out of the bandwidth bottleneck resulting from the considerable mismatch between the low-bandwidth interface and the bandwidth-hungry application, and a way to enable fluent and intuitive interaction in embodiment systems. The main focus is laid upon inferring the hidden target goals of users while navigating in a remote environment as a basis for possible adaptations. Approach. To reason about possible user goals, a general user-agnostic Bayesian update rule is devised to be recursively applied upon the arrival of evidences, i.e. user input and user gaze. Experiments were conducted with healthy subjects within robotic embodiment settings to evaluate the proposed method. These experiments varied along three factors: the type of the robot/environment (simulated and physical), the type of the interface (keyboard or BCI), and the way goal recognition (GR) is used to guide a simple shared control (SC) driving scheme. Main results. Our results show that the proposed GR algorithm is able to track and infer the hidden user goals with relatively high precision and recall. Further, the realized SC driving scheme benefits from the output of the GR system and is able to reduce the user effort needed to accomplish the assigned tasks. Despite the fact that the BCI requires higher effort compared to the keyboard conditions, most subjects were able to complete the assigned tasks, and the proposed GR system is additionally shown able to handle the uncertainty in user input during SSVEP-based interaction. The SC application of the belief vector indicates that the benefits of the GR module are more pronounced for BCIs, compared to the keyboard interface. Significance. Being based on intuitive heuristics that model the behavior of the general population during the execution of navigation tasks, the proposed GR method can be used without prior tuning for the

A stereotactic adapter compatible with computed tomography

International Nuclear Information System (INIS)

Cacak, R.K.; Law, J.D.

1982-01-01

One application of computed-tomographic (CT) scanners is the localization of intracranial targets for stereotactic surgery. Unfortunately, conventional stereotactic devices affixed to the patient cause artifacts which obscure anatomic features in CT images. The authors describe the initial phase of a project to eliminate this problem by using an adapter that is free of metallic objects. Localization of the target point relative to the coordinate system of a Leksell stereotactic frame is achieved from CT image measurements

Unified Computational Intelligence for Complex Systems

CERN Document Server

Seiffertt, John

2010-01-01

Computational intelligence encompasses a wide variety of techniques that allow computation to learn, to adapt, and to seek. That is, they may be designed to learn information without explicit programming regarding the nature of the content to be retained, they may be imbued with the functionality to adapt to maintain their course within a complex and unpredictably changing environment, and they may help us seek out truths about our own dynamics and lives through their inclusion in complex system modeling. These capabilities place our ability to compute in a category apart from our ability to e

Adaptive intrusion data system

International Nuclear Information System (INIS)

Johnson, C.S.

1976-01-01

An Adaptive Intrusion Data System (AIDS) was developed to collect data from intrusion alarm sensors as part of an evaluation system to improve sensor performance. AIDS is a unique digital data compression, storage, and formatting system. It also incorporates capability for video selection and recording for assessment of the sensors monitored by the system. The system is software reprogrammable to numerous configurations that may be utilized for the collection of environmental, bi-level, analog and video data. The output of the system is digital tapes formatted for direct data reduction on a CDC 6400 computer, and video tapes containing timed tagged information that can be correlated with the digital data

Human Adaptation to the Computer.

Science.gov (United States)

1986-09-01

8217"’ TECHNOSTRESS " 5 5’..,:. VI I. CONCLUSIONS-------------------------59 -- LIST OF REFERENCES-------------------------61 BI BLI OGRAPHY...computer has not developed. Instead, what has developed is a "modern disease of adaptation" called " technostress ," a phrase coined by Brod. Craig...34 technostress ." Managers (according to Brod) have been implementing computers in ways that contribute directly to this stress: [Ref. 3:p. 38) 1. They

A Framework for the Development of Context-Adaptable User Interfaces for Ubiquitous Computing Systems

Science.gov (United States)

Varela, Gervasio; Paz-Lopez, Alejandro; Becerra, Jose A.; Duro, Richard

2016-01-01

This paper addresses the problem of developing user interfaces for Ubiquitous Computing (UC) and Ambient Intelligence (AmI) systems. These kind of systems are expected to provide a natural user experience, considering interaction modalities adapted to the user abilities and preferences and using whatever interaction devices are present in the environment. These interaction devices are not necessarily known at design time. The task is quite complicated due to the variety of devices and technologies, and the diversity of scenarios, and it usually burdens the developer with the need to create many different UIs in order to consider the foreseeable user-environment combinations. Here, we propose an UI abstraction framework for UC and AmI systems that effectively improves the portability of those systems between different environments and for different users. It allows developers to design and implement a single UI capable of being deployed with different devices and modalities regardless the physical location. PMID:27399711

A Framework for the Development of Context-Adaptable User Interfaces for Ubiquitous Computing Systems

Directory of Open Access Journals (Sweden)

Gervasio Varela

2016-07-01

Full Text Available This paper addresses the problem of developing user interfaces for Ubiquitous Computing (UC and Ambient Intelligence (AmI systems. These kind of systems are expected to provide a natural user experience, considering interaction modalities adapted to the user abilities and preferences and using whatever interaction devices are present in the environment. These interaction devices are not necessarily known at design time. The task is quite complicated due to the variety of devices and technologies, and the diversity of scenarios, and it usually burdens the developer with the need to create many different UIs in order to consider the foreseeable user-environment combinations. Here, we propose an UI abstraction framework for UC and AmI systems that effectively improves the portability of those systems between different environments and for different users. It allows developers to design and implement a single UI capable of being deployed with different devices and modalities regardless the physical location.

A Framework for the Development of Context-Adaptable User Interfaces for Ubiquitous Computing Systems.

Science.gov (United States)

Varela, Gervasio; Paz-Lopez, Alejandro; Becerra, Jose A; Duro, Richard

2016-07-07

This paper addresses the problem of developing user interfaces for Ubiquitous Computing (UC) and Ambient Intelligence (AmI) systems. These kind of systems are expected to provide a natural user experience, considering interaction modalities adapted to the user abilities and preferences and using whatever interaction devices are present in the environment. These interaction devices are not necessarily known at design time. The task is quite complicated due to the variety of devices and technologies, and the diversity of scenarios, and it usually burdens the developer with the need to create many different UIs in order to consider the foreseeable user-environment combinations. Here, we propose an UI abstraction framework for UC and AmI systems that effectively improves the portability of those systems between different environments and for different users. It allows developers to design and implement a single UI capable of being deployed with different devices and modalities regardless the physical location.

Distributed computer systems theory and practice

CERN Document Server

Zedan, H S M

2014-01-01

Distributed Computer Systems: Theory and Practice is a collection of papers dealing with the design and implementation of operating systems, including distributed systems, such as the amoeba system, argus, Andrew, and grapevine. One paper discusses the concepts and notations for concurrent programming, particularly language notation used in computer programming, synchronization methods, and also compares three classes of languages. Another paper explains load balancing or load redistribution to improve system performance, namely, static balancing and adaptive load balancing. For program effici

Wavefront measurement using computational adaptive optics.

Science.gov (United States)

South, Fredrick A; Liu, Yuan-Zhi; Bower, Andrew J; Xu, Yang; Carney, P Scott; Boppart, Stephen A

2018-03-01

In many optical imaging applications, it is necessary to correct for aberrations to obtain high quality images. Optical coherence tomography (OCT) provides access to the amplitude and phase of the backscattered optical field for three-dimensional (3D) imaging samples. Computational adaptive optics (CAO) modifies the phase of the OCT data in the spatial frequency domain to correct optical aberrations without using a deformable mirror, as is commonly done in hardware-based adaptive optics (AO). This provides improvement of image quality throughout the 3D volume, enabling imaging across greater depth ranges and in highly aberrated samples. However, the CAO aberration correction has a complicated relation to the imaging pupil and is not a direct measurement of the pupil aberrations. Here we present new methods for recovering the wavefront aberrations directly from the OCT data without the use of hardware adaptive optics. This enables both computational measurement and correction of optical aberrations.

Unauthorised adaptation of computer programmes - is criminalisation a solution?

Directory of Open Access Journals (Sweden)

L Muswaka

2011-12-01

Full Text Available In Haupt t/a Softcopy v Brewers Marketing Intelligence (Pty Ltd 2006 4 SA 458 (SCA Haupt sought to enforce a copyright claim in the Data Explorer computer programme against Brewers Marketing Intelligence (Pty Ltd. His claim was dismissed in the High Court and he appealed to the Supreme Court of Appeal. The Court held that copyright in the Data Explorer programme vested in Haupt. Haupt acquired copyright in the Data Explorer programme regardless of the fact that the programme was as a result of an unauthorised adaptation of the Project AMPS programme which belonged to Brewers Marketing Intelligence (Pty Ltd.This case note inter alia analyses the possibility of an author being sued for infringement even though he has acquired copyright in a work that he created by making unauthorised adaptations to another's copyright material. Furthermore, it examines whether or not the law adequately protects copyright owners in situations where infringement takes the form of unauthorised adaptations of computer programmes. It is argued that the protection afforded by the Copyright Act 98 of 1978 (Copyright Act in terms of section 27(1 to copyright owners of computer programmes is narrowly defined. It excludes from its ambit of criminal liability the act of making unauthorised adaptation of computer programmes. The issue that is considered is therefore whether or not the unauthorised adaptation of computer programmes should attract a criminal sanction. In addressing this issue and with the aim of making recommendations, the legal position in the United Kingdom (UK is analysed. From the analysis it is recommended that the Copyright Act be amended by the insertion of a new section, section 27(1(A, which will make the act of making an unauthorised adaptation of a computer programme an offence. This recommended section will close the gap that currently exists in our law with regard to unauthorised adaptations of computer programmes.

Complex adaptative systems and computational simulation in Archaeology

Directory of Open Access Journals (Sweden)

Salvador Pardo-Gordó

2017-07-01

Full Text Available Traditionally the concept of ‘complexity’ is used as a synonym for ‘complex society’, i.e., human groups with characteristics such as urbanism, inequalities, and hierarchy. The introduction of Nonlinear Systems and Complex Adaptive Systems to the discipline of archaeology has nuanced this concept. This theoretical turn has led to the rise of modelling as a method of analysis of historical processes. This work has a twofold objective: to present the theoretical current characterized by generative thinking in archaeology and to present a concrete application of agent-based modelling to an archaeological problem: the dispersal of the first ceramic production in the western Mediterranean.

PERSO: Towards an Adaptive e-Learning System

Science.gov (United States)

Chorfi, Henda; Jemni, Mohamed

2004-01-01

In today's information technology society, members are increasingly required to be up to date on new technologies, particularly for computers, regardless of their background social situation. In this context, our aim is to design and develop an adaptive hypermedia e-learning system, called PERSO (PERSOnalizing e-learning system), where learners…

Test Anxiety, Computer-Adaptive Testing and the Common Core

Science.gov (United States)

Colwell, Nicole Makas

2013-01-01

This paper highlights the current findings and issues regarding the role of computer-adaptive testing in test anxiety. The computer-adaptive test (CAT) proposed by one of the Common Core consortia brings these issues to the forefront. Research has long indicated that test anxiety impairs student performance. More recent research indicates that…

Simple adaptive sparse representation based classification schemes for EEG based brain-computer interface applications.

Science.gov (United States)

Shin, Younghak; Lee, Seungchan; Ahn, Minkyu; Cho, Hohyun; Jun, Sung Chan; Lee, Heung-No

2015-11-01

One of the main problems related to electroencephalogram (EEG) based brain-computer interface (BCI) systems is the non-stationarity of the underlying EEG signals. This results in the deterioration of the classification performance during experimental sessions. Therefore, adaptive classification techniques are required for EEG based BCI applications. In this paper, we propose simple adaptive sparse representation based classification (SRC) schemes. Supervised and unsupervised dictionary update techniques for new test data and a dictionary modification method by using the incoherence measure of the training data are investigated. The proposed methods are very simple and additional computation for the re-training of the classifier is not needed. The proposed adaptive SRC schemes are evaluated using two BCI experimental datasets. The proposed methods are assessed by comparing classification results with the conventional SRC and other adaptive classification methods. On the basis of the results, we find that the proposed adaptive schemes show relatively improved classification accuracy as compared to conventional methods without requiring additional computation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Adaptation and hybridization in computational intelligence

CERN Document Server

Jr, Iztok

2015-01-01

  This carefully edited book takes a walk through recent advances in adaptation and hybridization in the Computational Intelligence (CI) domain. It consists of ten chapters that are divided into three parts. The first part illustrates background information and provides some theoretical foundation tackling the CI domain, the second part deals with the adaptation in CI algorithms, while the third part focuses on the hybridization in CI. This book can serve as an ideal reference for researchers and students of computer science, electrical and civil engineering, economy, and natural sciences that are confronted with solving the optimization, modeling and simulation problems. It covers the recent advances in CI that encompass Nature-inspired algorithms, like Artificial Neural networks, Evolutionary Algorithms and Swarm Intelligence –based algorithms.  

Simple and Effective Algorithms: Computer-Adaptive Testing.

Science.gov (United States)

Linacre, John Michael

Computer-adaptive testing (CAT) allows improved security, greater scoring accuracy, shorter testing periods, quicker availability of results, and reduced guessing and other undesirable test behavior. Simple approaches can be applied by the classroom teacher, or other content specialist, who possesses simple computer equipment and elementary…

Indirect adaptive control of discrete chaotic systems

International Nuclear Information System (INIS)

Salarieh, Hassan; Shahrokhi, Mohammad

2007-01-01

In this paper an indirect adaptive control algorithm is proposed to stabilize the fixed points of discrete chaotic systems. It is assumed that the functionality of the chaotic dynamics is known but the system parameters are unknown. This assumption is usually applicable to many chaotic systems, such as the Henon map, logistic and many other nonlinear maps. Using the recursive-least squares technique, the system parameters are identified and based on the feedback linearization method an adaptive controller is designed for stabilizing the fixed points, or unstable periodic orbits of the chaotic maps. The stability of the proposed scheme has been shown and the effectiveness of the control algorithm has been demonstrated through computer simulations

'Micro-8' micro-computer system

International Nuclear Information System (INIS)

Yagi, Hideyuki; Nakahara, Yoshinori; Yamada, Takayuki; Takeuchi, Norio; Koyama, Kinji

1978-08-01

The micro-computer Micro-8 system has been developed to organize a data exchange network between various instruments and a computer group including a large computer system. Used for packet exchangers and terminal controllers, the system consists of ten kinds of standard boards including a CPU board with INTEL-8080 one-chip-processor. CPU architecture, BUS architecture, interrupt control, and standard-boards function are explained in circuit block diagrams. Operations of the basic I/O device, digital I/O board and communication adapter are described with definitions of the interrupt ramp status, I/O command, I/O mask, data register, etc. In the appendixes are circuit drawings, INTEL-8080 micro-processor specifications, BUS connections, I/O address mappings, jumper connections of address selection, and interface connections. (author)

Systems analysis and the computer

Energy Technology Data Exchange (ETDEWEB)

Douglas, A S

1983-08-01

The words systems analysis are used in at least two senses. Whilst the general nature of the topic is well understood in the or community, the nature of the term as used by computer scientists is less familiar. In this paper, the nature of systems analysis as it relates to computer-based systems is examined from the point of view that the computer system is an automaton embedded in a human system, and some facets of this are explored. It is concluded that or analysts and computer analysts have things to learn from each other and that this ought to be reflected in their education. The important role played by change in the design of systems is also highlighted, and it is concluded that, whilst the application of techniques developed in the artificial intelligence field have considerable relevance to constructing automata able to adapt to change in the environment, study of the human factors affecting the overall systems within which the automata are embedded has an even more important role. 19 references.

Computationally Efficient Blind Code Synchronization for Asynchronous DS-CDMA Systems with Adaptive Antenna Arrays

Directory of Open Access Journals (Sweden)

Chia-Chang Hu

2005-04-01

Full Text Available A novel space-time adaptive near-far robust code-synchronization array detector for asynchronous DS-CDMA systems is developed in this paper. There are the same basic requirements that are needed by the conventional matched filter of an asynchronous DS-CDMA system. For the real-time applicability, a computationally efficient architecture of the proposed detector is developed that is based on the concept of the multistage Wiener filter (MWF of Goldstein and Reed. This multistage technique results in a self-synchronizing detection criterion that requires no inversion or eigendecomposition of a covariance matrix. As a consequence, this detector achieves a complexity that is only a linear function of the size of antenna array (J, the rank of the MWF (M, the system processing gain (N, and the number of samples in a chip interval (S, that is, 𝒪(JMNS. The complexity of the equivalent detector based on the minimum mean-squared error (MMSE or the subspace-based eigenstructure analysis is a function of 𝒪((JNS3. Moreover, this multistage scheme provides a rapid adaptive convergence under limited observation-data support. Simulations are conducted to evaluate the performance and convergence behavior of the proposed detector with the size of the J-element antenna array, the amount of the L-sample support, and the rank of the M-stage MWF. The performance advantage of the proposed detector over other DS-CDMA detectors is investigated as well.

Water System Adaptation to Hydrological Changes: Module 10, Basic Principles of Incorporating Adaptation Science into Hydrologic Planning and Design

Science.gov (United States)

This course will introduce students to the fundamental principles of water system adaptation to hydrological changes, with emphasis on data analysis and interpretation, technical planning, and computational modeling. Starting with real-world scenarios and adaptation needs, the co...

Method and system for rendering and interacting with an adaptable computing environment

Science.gov (United States)

Osbourn, Gordon Cecil [Albuquerque, NM; Bouchard, Ann Marie [Albuquerque, NM

2012-06-12

An adaptable computing environment is implemented with software entities termed "s-machines", which self-assemble into hierarchical data structures capable of rendering and interacting with the computing environment. A hierarchical data structure includes a first hierarchical s-machine bound to a second hierarchical s-machine. The first hierarchical s-machine is associated with a first layer of a rendering region on a display screen and the second hierarchical s-machine is associated with a second layer of the rendering region overlaying at least a portion of the first layer. A screen element s-machine is linked to the first hierarchical s-machine. The screen element s-machine manages data associated with a screen element rendered to the display screen within the rendering region at the first layer.

Building fast, reliable, and adaptive software for computational science

International Nuclear Information System (INIS)

Rendell, A P; Antony, J; Armstrong, W; Janes, P; Yang, R

2008-01-01

Building fast, reliable, and adaptive software is a constant challenge for computational science, especially given recent developments in computer architecture. This paper outlines some of our efforts to address these three issues in the context of computational chemistry. First, a simple linear performance that can be used to model and predict the performance of Hartree-Fock calculations is discussed. Second, the use of interval arithmetic to assess the numerical reliability of the sort of integrals used in electronic structure methods is presented. Third, use of dynamic code modification as part of a framework to support adaptive software is outlined

Efficient computation of smoothing splines via adaptive basis sampling

KAUST Repository

Ma, Ping

2015-06-24

© 2015 Biometrika Trust. Smoothing splines provide flexible nonparametric regression estimators. However, the high computational cost of smoothing splines for large datasets has hindered their wide application. In this article, we develop a new method, named adaptive basis sampling, for efficient computation of smoothing splines in super-large samples. Except for the univariate case where the Reinsch algorithm is applicable, a smoothing spline for a regression problem with sample size n can be expressed as a linear combination of n basis functions and its computational complexity is generally O(n³). We achieve a more scalable computation in the multivariate case by evaluating the smoothing spline using a smaller set of basis functions, obtained by an adaptive sampling scheme that uses values of the response variable. Our asymptotic analysis shows that smoothing splines computed via adaptive basis sampling converge to the true function at the same rate as full basis smoothing splines. Using simulation studies and a large-scale deep earth core-mantle boundary imaging study, we show that the proposed method outperforms a sampling method that does not use the values of response variables.

Efficient computation of smoothing splines via adaptive basis sampling

KAUST Repository

Ma, Ping; Huang, Jianhua Z.; Zhang, Nan

2015-01-01

© 2015 Biometrika Trust. Smoothing splines provide flexible nonparametric regression estimators. However, the high computational cost of smoothing splines for large datasets has hindered their wide application. In this article, we develop a new method, named adaptive basis sampling, for efficient computation of smoothing splines in super-large samples. Except for the univariate case where the Reinsch algorithm is applicable, a smoothing spline for a regression problem with sample size n can be expressed as a linear combination of n basis functions and its computational complexity is generally O(n³). We achieve a more scalable computation in the multivariate case by evaluating the smoothing spline using a smaller set of basis functions, obtained by an adaptive sampling scheme that uses values of the response variable. Our asymptotic analysis shows that smoothing splines computed via adaptive basis sampling converge to the true function at the same rate as full basis smoothing splines. Using simulation studies and a large-scale deep earth core-mantle boundary imaging study, we show that the proposed method outperforms a sampling method that does not use the values of response variables.

Overview of adaptive finite element analysis in computational geodynamics

Science.gov (United States)

May, D. A.; Schellart, W. P.; Moresi, L.

2013-10-01

The use of numerical models to develop insight and intuition into the dynamics of the Earth over geological time scales is a firmly established practice in the geodynamics community. As our depth of understanding grows, and hand-in-hand with improvements in analytical techniques and higher resolution remote sensing of the physical structure and state of the Earth, there is a continual need to develop more efficient, accurate and reliable numerical techniques. This is necessary to ensure that we can meet the challenge of generating robust conclusions, interpretations and predictions from improved observations. In adaptive numerical methods, the desire is generally to maximise the quality of the numerical solution for a given amount of computational effort. Neither of these terms has a unique, universal definition, but typically there is a trade off between the number of unknowns we can calculate to obtain a more accurate representation of the Earth, and the resources (time and computational memory) required to compute them. In the engineering community, this topic has been extensively examined using the adaptive finite element (AFE) method. Recently, the applicability of this technique to geodynamic processes has started to be explored. In this review we report on the current status and usage of spatially adaptive finite element analysis in the field of geodynamics. The objective of this review is to provide a brief introduction to the area of spatially adaptive finite analysis, including a summary of different techniques to define spatial adaptation and of different approaches to guide the adaptive process in order to control the discretisation error inherent within the numerical solution. An overview of the current state of the art in adaptive modelling in geodynamics is provided, together with a discussion pertaining to the issues related to using adaptive analysis techniques and perspectives for future research in this area. Additionally, we also provide a

Intelligent computational systems for space applications

Science.gov (United States)

Lum, Henry; Lau, Sonie

Intelligent computational systems can be described as an adaptive computational system integrating both traditional computational approaches and artificial intelligence (AI) methodologies to meet the science and engineering data processing requirements imposed by specific mission objectives. These systems will be capable of integrating, interpreting, and understanding sensor input information; correlating that information to the "world model" stored within its data base and understanding the differences, if any; defining, verifying, and validating a command sequence to merge the "external world" with the "internal world model"; and, controlling the vehicle and/or platform to meet the scientific and engineering mission objectives. Performance and simulation data obtained to date indicate that the current flight processors baselined for many missions such as Space Station Freedom do not have the computational power to meet the challenges of advanced automation and robotics systems envisioned for the year 2000 era. Research issues which must be addressed to achieve greater than giga-flop performance for on-board intelligent computational systems have been identified, and a technology development program has been initiated to achieve the desired long-term system performance objectives.

Scalable space-time adaptive simulation tools for computational electrocardiology

OpenAIRE

Krause, Dorian; Krause, Rolf

2013-01-01

This work is concerned with the development of computational tools for the solution of reaction-diffusion equations from the field of computational electrocardiology. We designed lightweight spatially and space-time adaptive schemes for large-scale parallel simulations. We propose two different adaptive schemes based on locally structured meshes, managed either via a conforming coarse tessellation or a forest of shallow trees. A crucial ingredient of our approach is a non-conforming morta...

Adaptive Intrusion Data System (AIDS)

International Nuclear Information System (INIS)

Corlis, N.E.

1980-05-01

The adaptive intrusion data system (AIDS) was developed to collect data from intrusion alarm sensors as part of an evaluation system to improve sensor performance. AIDS is a unique data system which uses computer controlled data systems, video cameras and recorders, analog-to-digital conversion, environmental sensors, and digital recorders to collect sensor data. The data can be viewed either manually or with a special computerized data-reduction system which adds new data to a data base stored on a magnetic disc recorder. This report provides a synoptic account of the AIDS as it presently exists. Modifications to the purchased subsystems are described, and references are made to publications which describe the Sandia-designed subsystems

Runtime adaptive multi-processor system-on-chip: RAMPSoC

OpenAIRE

Göhringer, D.; Hübner, M.; Schatz, V.; Becker, J.

2008-01-01

Current trends in high performance computing show, that the usage of multiprocessor systems on chip are one approach for the requirements of computing intensive applications. The multiprocessor system on chip (MPSoC) approaches often provide a static and homogeneous infrastructure of networked microprocessor on the chip die. A novel idea in this research area is to introduce the dynamic adaptivity of reconfigurable hardware in order to provide a flexible heterogeneous set of processing elemen...

Advanced intelligent computational technologies and decision support systems

CERN Document Server

Kountchev, Roumen

2014-01-01

This book offers a state of the art collection covering themes related to Advanced Intelligent Computational Technologies and Decision Support Systems which can be applied to fields like healthcare assisting the humans in solving problems. The book brings forward a wealth of ideas, algorithms and case studies in themes like: intelligent predictive diagnosis; intelligent analyzing of medical images; new format for coding of single and sequences of medical images; Medical Decision Support Systems; diagnosis of Down’s syndrome; computational perspectives for electronic fetal monitoring; efficient compression of CT Images; adaptive interpolation and halftoning for medical images; applications of artificial neural networks for real-life problems solving; present and perspectives for Electronic Healthcare Record Systems; adaptive approaches for noise reduction in sequences of CT images etc.

Water System Adaptation To Hydrological Changes: Module 5, Water Quality and Infrastructure Response to Rapid Urbanization: Adaptation Case Study in China

Science.gov (United States)

This course will introduce students to the fundamental principles of water system adaptation to hydrological changes, with emphasis on data analysis and interpretation, technical planning, and computational modeling. Starting with real-world scenarios and adaptation needs, the co...

Application of stable adaptive schemes to nuclear reactor systems, (1)

International Nuclear Information System (INIS)

Fukuda, Toshio

1978-01-01

Parameter identification and adaptive control schemes are presented for a point reactor with internal feedbacks which lead to the nonlinearity of the overall system. Both are shown stable with new representation of the system, which corresponds to the nonminimal system representation, in the vein of the Model Reference Adaptive System (MRAS) via the Lyapunov's method. For the sake of the parameter identification, model parameters can be adjusted adaptively as soon as measurements start, while plant parameters can also adaptively be compensated through control input to reduce the output error between the model and the plant for the case of the adaptive control. In the case of the adaptive control, control schemes are presented for two cases, the case of the unknown decay constant of the delayed neutron and the case of the known constant. The adaptive control scheme for the latter case is shown extremely simpler than that for the former. Furthermore, when plant parameters vary slowly with time, computer simulations show that the proposed adaptive control scheme works satisfactorily enough to stabilize an unstable reactor and that it does even in the noise with small variance. (auth.)

Identification of chaotic memristor systems based on piecewise adaptive Legendre filters

International Nuclear Information System (INIS)

Zhao, Yibo; Zhang, Xiuzai; Xu, Jin; Guo, Yecai

2015-01-01

Memristor is a nonlinear device, which plays an important role in the design and implementation of chaotic systems. In order to be able to understand in-depth the complex nonlinear dynamic behaviors in chaotic memristor systems, modeling or identification of its nonlinear model is very important premise. This paper presents a chaotic memristor system identification method based on piecewise adaptive Legendre filters. The threshold decomposition is carried out for the input vector, and also the input signal subintervals via decomposition satisfy the convergence condition of the adaptive Legendre filters. Then the adaptive Legendre filter structure and adaptive weight update algorithm are derived. Final computer simulation results show the effectiveness as well as fast convergence characteristics.

Adaptive Wavelet Coding Applied in a Wireless Control System.

Science.gov (United States)

Gama, Felipe O S; Silveira, Luiz F Q; Salazar, Andrés O

2017-12-13

Wireless control systems can sense, control and act on the information exchanged between the wireless sensor nodes in a control loop. However, the exchanged information becomes susceptible to the degenerative effects produced by the multipath propagation. In order to minimize the destructive effects characteristic of wireless channels, several techniques have been investigated recently. Among them, wavelet coding is a good alternative for wireless communications for its robustness to the effects of multipath and its low computational complexity. This work proposes an adaptive wavelet coding whose parameters of code rate and signal constellation can vary according to the fading level and evaluates the use of this transmission system in a control loop implemented by wireless sensor nodes. The performance of the adaptive system was evaluated in terms of bit error rate (BER) versus E b / N 0 and spectral efficiency, considering a time-varying channel with flat Rayleigh fading, and in terms of processing overhead on a control system with wireless communication. The results obtained through computational simulations and experimental tests show performance gains obtained by insertion of the adaptive wavelet coding in a control loop with nodes interconnected by wireless link. These results enable the use of this technique in a wireless link control loop.

Adaptive Wavelet Coding Applied in a Wireless Control System

Directory of Open Access Journals (Sweden)

Felipe O. S. Gama

2017-12-01

Full Text Available Wireless control systems can sense, control and act on the information exchanged between the wireless sensor nodes in a control loop. However, the exchanged information becomes susceptible to the degenerative effects produced by the multipath propagation. In order to minimize the destructive effects characteristic of wireless channels, several techniques have been investigated recently. Among them, wavelet coding is a good alternative for wireless communications for its robustness to the effects of multipath and its low computational complexity. This work proposes an adaptive wavelet coding whose parameters of code rate and signal constellation can vary according to the fading level and evaluates the use of this transmission system in a control loop implemented by wireless sensor nodes. The performance of the adaptive system was evaluated in terms of bit error rate (BER versus E b / N 0 and spectral efficiency, considering a time-varying channel with flat Rayleigh fading, and in terms of processing overhead on a control system with wireless communication. The results obtained through computational simulations and experimental tests show performance gains obtained by insertion of the adaptive wavelet coding in a control loop with nodes interconnected by wireless link. These results enable the use of this technique in a wireless link control loop.

The adaptation method in the Monte Carlo simulation for computed tomography

Energy Technology Data Exchange (ETDEWEB)

Lee, Hyoung Gun; Yoon, Chang Yeon; Lee, Won Ho [Dept. of Bio-convergence Engineering, Korea University, Seoul (Korea, Republic of); Cho, Seung Ryong [Dept. of Nuclear and Quantum Engineering, Korea Advanced Institute of Science and Technology, Daejeon (Korea, Republic of); Park, Sung Ho [Dept. of Neurosurgery, Ulsan University Hospital, Ulsan (Korea, Republic of)

2015-06-15

The patient dose incurred from diagnostic procedures during advanced radiotherapy has become an important issue. Many researchers in medical physics are using computational simulations to calculate complex parameters in experiments. However, extended computation times make it difficult for personal computers to run the conventional Monte Carlo method to simulate radiological images with high-flux photons such as images produced by computed tomography (CT). To minimize the computation time without degrading imaging quality, we applied a deterministic adaptation to the Monte Carlo calculation and verified its effectiveness by simulating CT image reconstruction for an image evaluation phantom (Catphan; Phantom Laboratory, New York NY, USA) and a human-like voxel phantom (KTMAN-2) (Los Alamos National Laboratory, Los Alamos, NM, USA). For the deterministic adaptation, the relationship between iteration numbers and the simulations was estimated and the option to simulate scattered radiation was evaluated. The processing times of simulations using the adaptive method were at least 500 times faster than those using a conventional statistical process. In addition, compared with the conventional statistical method, the adaptive method provided images that were more similar to the experimental images, which proved that the adaptive method was highly effective for a simulation that requires a large number of iterations-assuming no radiation scattering in the vicinity of detectors minimized artifacts in the reconstructed image.

Adaptively detecting changes in Autonomic Grid Computing

KAUST Repository

Zhang, Xiangliang; Germain, Cé cile; Sebag, Michè le

2010-01-01

Detecting the changes is the common issue in many application fields due to the non-stationary distribution of the applicative data, e.g., sensor network signals, web logs and gridrunning logs. Toward Autonomic Grid Computing, adaptively detecting

Adaptive Dynamic Process Scheduling on Distributed Memory Parallel Computers

Directory of Open Access Journals (Sweden)

Wei Shu

1994-01-01

Full Text Available One of the challenges in programming distributed memory parallel machines is deciding how to allocate work to processors. This problem is particularly important for computations with unpredictable dynamic behaviors or irregular structures. We present a scheme for dynamic scheduling of medium-grained processes that is useful in this context. The adaptive contracting within neighborhood (ACWN is a dynamic, distributed, load-dependent, and scalable scheme. It deals with dynamic and unpredictable creation of processes and adapts to different systems. The scheme is described and contrasted with two other schemes that have been proposed in this context, namely the randomized allocation and the gradient model. The performance of the three schemes on an Intel iPSC/2 hypercube is presented and analyzed. The experimental results show that even though the ACWN algorithm incurs somewhat larger overhead than the randomized allocation, it achieves better performance in most cases due to its adaptiveness. Its feature of quickly spreading the work helps it outperform the gradient model in performance and scalability.

Pipelining Computational Stages of the Tomographic Reconstructor for Multi-Object Adaptive Optics on a Multi-GPU System

KAUST Repository

Charara, Ali

2014-11-01

The European Extremely Large Telescope project (E-ELT) is one of Europe\\'s highest priorities in ground-based astronomy. ELTs are built on top of a variety of highly sensitive and critical astronomical instruments. In particular, a new instrument called MOSAIC has been proposed to perform multi-object spectroscopy using the Multi-Object Adaptive Optics (MOAO) technique. The core implementation of the simulation lies in the intensive computation of a tomographic reconstruct or (TR), which is used to drive the deformable mirror in real time from the measurements. A new numerical algorithm is proposed (1) to capture the actual experimental noise and (2) to substantially speed up previous implementations by exposing more concurrency, while reducing the number of floating-point operations. Based on the Matrices Over Runtime System at Exascale numerical library (MORSE), a dynamic scheduler drives all computational stages of the tomographic reconstruct or simulation and allows to pipeline and to run tasks out-of order across different stages on heterogeneous systems, while ensuring data coherency and dependencies. The proposed TR simulation outperforms asymptotically previous state-of-the-art implementations up to 13-fold speedup. At more than 50000 unknowns, this appears to be the largest-scale AO problem submitted to computation, to date, and opens new research directions for extreme scale AO simulations. © 2014 IEEE.

Water System Adaptation To Hydrological Changes: Module 9, Water System Resilience and Security under Hydrologic Variability and Uncertainty

Science.gov (United States)

This course will introduce students to the fundamental principles of water system adaptation to hydrological changes, with emphasis on data analysis and interpretation, technical planning, and computational modeling. Starting with real-world scenarios and adaptation needs, the co...

Adaptive tight frame based medical image reconstruction: a proof-of-concept study for computed tomography

International Nuclear Information System (INIS)

Zhou, Weifeng; Cai, Jian-Feng; Gao, Hao

2013-01-01

A popular approach for medical image reconstruction has been through the sparsity regularization, assuming the targeted image can be well approximated by sparse coefficients under some properly designed system. The wavelet tight frame is such a widely used system due to its capability for sparsely approximating piecewise-smooth functions, such as medical images. However, using a fixed system may not always be optimal for reconstructing a variety of diversified images. Recently, the method based on the adaptive over-complete dictionary that is specific to structures of the targeted images has demonstrated its superiority for image processing. This work is to develop the adaptive wavelet tight frame method image reconstruction. The proposed scheme first constructs the adaptive wavelet tight frame that is task specific, and then reconstructs the image of interest by solving an l 1 -regularized minimization problem using the constructed adaptive tight frame system. The proof-of-concept study is performed for computed tomography (CT), and the simulation results suggest that the adaptive tight frame method improves the reconstructed CT image quality from the traditional tight frame method. (paper)

Sequential decision making in computational sustainability via adaptive submodularity

Science.gov (United States)

Krause, Andreas; Golovin, Daniel; Converse, Sarah J.

2015-01-01

Many problems in computational sustainability require making a sequence of decisions in complex, uncertain environments. Such problems are generally notoriously difficult. In this article, we review the recently discovered notion of adaptive submodularity, an intuitive diminishing returns condition that generalizes the classical notion of submodular set functions to sequential decision problems. Problems exhibiting the adaptive submodularity property can be efficiently and provably near-optimally solved using simple myopic policies. We illustrate this concept in several case studies of interest in computational sustainability: First, we demonstrate how it can be used to efficiently plan for resolving uncertainty in adaptive management scenarios. Secondly, we show how it applies to dynamic conservation planning for protecting endangered species, a case study carried out in collaboration with the US Geological Survey and the US Fish and Wildlife Service.

Features of the adaptive control and measuring the effectiveness of distant teaching to computer science

Directory of Open Access Journals (Sweden)

Евгений Игоревич Горюшкин

2009-06-01

Full Text Available In title approaches to construction of effective monitoring systems of productivity of training to computer science in high schools are described. It is offered to put adaptive testing at which in development of tests artificial neural networks are applied in a basis of such systems.

Quinoa - Adaptive Computational Fluid Dynamics, 0.2

Energy Technology Data Exchange (ETDEWEB)

2017-09-22

Quinoa is a set of computational tools that enables research and numerical analysis in fluid dynamics. At this time it remains a test-bed to experiment with various algorithms using fully asynchronous runtime systems. Currently, Quinoa consists of the following tools: (1) Walker, a numerical integrator for systems of stochastic differential equations in time. It is a mathematical tool to analyze and design the behavior of stochastic differential equations. It allows the estimation of arbitrary coupled statistics and probability density functions and is currently used for the design of statistical moment approximations for multiple mixing materials in variable-density turbulence. (2) Inciter, an overdecomposition-aware finite element field solver for partial differential equations using 3D unstructured grids. Inciter is used to research asynchronous mesh-based algorithms and to experiment with coupling asynchronous to bulk-synchronous parallel code. Two planned new features of Inciter, compared to the previous release (LA-CC-16-015), to be implemented in 2017, are (a) a simple Navier-Stokes solver for ideal single-material compressible gases, and (b) solution-adaptive mesh refinement (AMR), which enables dynamically concentrating compute resources to regions with interesting physics. Using the NS-AMR problem we plan to explore how to scale such high-load-imbalance simulations, representative of large production multiphysics codes, to very large problems on very large computers using an asynchronous runtime system. (3) RNGTest, a test harness to subject random number generators to stringent statistical tests enabling quantitative ranking with respect to their quality and computational cost. (4) UnitTest, a unit test harness, running hundreds of tests per second, capable of testing serial, synchronous, and asynchronous functions. (5) MeshConv, a mesh file converter that can be used to convert 3D tetrahedron meshes from and to either of the following formats: Gmsh

IAE-adaptive Kalman filter for INS/GPS integrated navigation system

Institute of Scientific and Technical Information of China (English)

Bian Hongwei; Jin Zhihua; Tian Weifeng

2006-01-01

A marine INS/GPS adaptive navigation system is presented in this paper. GPS with two antenna providing vessel's altitude is selected as the auxiliary system fusing with INS to improve the performance of the hybrid system. The Kalman filter is the most frequently used algorithm in the integrated navigation system, which is capable of estimating INS errors online based on the measured errors between INS and GPS. The standard Kalman filter (SKF) assumes that the statistics of the noise on each sensor are given. As long as the noise distributions do not change, the Kalman filter will give the optimal estimation. However GPS receiver will be disturbed easily and thus temporally changing measurement noise will join into the outputs of GPS, which will lead to performance degradation of the Kalman filter. Many researchers introduce fuzzy logic control method into innovation-based adaptive estimation adaptive Kalman filtering (IAE-AKF) algorithm, and accordingly propose various adaptive Kalman filters. However how to design the fuzzy logic controller is a very complicated problem still without a convincing solution. A novel IAE-AKF is proposed herein, which is based on the maximum likelihood criterion for the proper computation of the filter innovation covariance and hence of the filter gain. The approach is direct and simple without having to establish fuzzy inference rules. After having deduced the proposed IAE-AKF algorithm theoretically in detail, the approach is tested by the simulation based on the system error model of the developed INS/GPS integrated marine navigation system. Simulation results show that the adaptive Kalman filter outperforms the SKF with higher accuracy, robustness and less computation. It is demonstrated that this proposed approach is a valid solution for the unknown changing measurement noise exited in the Kalman filter.

Adaptation in Living Systems

Science.gov (United States)

Tu, Yuhai; Rappel, Wouter-Jan

2018-03-01

Adaptation refers to the biological phenomenon where living systems change their internal states in response to changes in their environments in order to maintain certain key functions critical for their survival and fitness. Adaptation is one of the most ubiquitous and arguably one of the most fundamental properties of living systems. It occurs throughout all biological scales, from adaptation of populations of species over evolutionary time to adaptation of a single cell to different environmental stresses during its life span. In this article, we review some of the recent progress made in understanding molecular mechanisms of cellular-level adaptation. We take the minimalist (or the physicist) approach and study the simplest systems that exhibit generic adaptive behaviors, namely chemotaxis in bacterium cells (Escherichia coli) and eukaryotic cells (Dictyostelium). We focus on understanding the basic biochemical interaction networks that are responsible for adaptation dynamics. By combining theoretical modeling with quantitative experimentation, we demonstrate universal features in adaptation as well as important differences in different cellular systems. Future work in extending the modeling framework to study adaptation in more complex systems such as sensory neurons is also discussed.

Accuracy requirements of optical linear algebra processors in adaptive optics imaging systems

Science.gov (United States)

Downie, John D.; Goodman, Joseph W.

1989-10-01

The accuracy requirements of optical processors in adaptive optics systems are determined by estimating the required accuracy in a general optical linear algebra processor (OLAP) that results in a smaller average residual aberration than that achieved with a conventional electronic digital processor with some specific computation speed. Special attention is given to an error analysis of a general OLAP with regard to the residual aberration that is created in an adaptive mirror system by the inaccuracies of the processor, and to the effect of computational speed of an electronic processor on the correction. Results are presented on the ability of an OLAP to compete with a digital processor in various situations.

An adaptive multi-spline refinement algorithm in simulation based sailboat trajectory optimization using onboard multi-core computer systems

Directory of Open Access Journals (Sweden)

Dębski Roman

2016-06-01

Full Text Available A new dynamic programming based parallel algorithm adapted to on-board heterogeneous computers for simulation based trajectory optimization is studied in the context of “high-performance sailing”. The algorithm uses a new discrete space of continuously differentiable functions called the multi-splines as its search space representation. A basic version of the algorithm is presented in detail (pseudo-code, time and space complexity, search space auto-adaptation properties. Possible extensions of the basic algorithm are also described. The presented experimental results show that contemporary heterogeneous on-board computers can be effectively used for solving simulation based trajectory optimization problems. These computers can be considered micro high performance computing (HPC platforms-they offer high performance while remaining energy and cost efficient. The simulation based approach can potentially give highly accurate results since the mathematical model that the simulator is built upon may be as complex as required. The approach described is applicable to many trajectory optimization problems due to its black-box represented performance measure and use of OpenCL.

A Framework for Adaptive Information Security Systems : A Holistic Investigation

OpenAIRE

Mwakalinga, Jeffy

2011-01-01

This research proposes a framework for adaptive information security systems that considers both the technical and social aspects of information systems security. Initial development of information systems security focused on computer technology and communication protocols. Researchers and designers did not consider culture, traditions, ethics, and other social issues of the people using the systems when designing and developing information security systems. They also seemed to ignore environ...

Adaptive Integral Sliding Mode Stabilization of Nonholonomic Drift-Free Systems

Directory of Open Access Journals (Sweden)

Waseem Abbasi

2016-01-01

Full Text Available This article presents adaptive integral sliding mode control algorithm for the stabilization of nonholonomic drift-free systems. First the system is transformed, by using input transform, into a special structure containing a nominal part and some unknown terms which are computed adaptively. The transformed system is then stabilized using adaptive integral sliding mode control. The stabilizing controller for the transformed system is constructed that consists of the nominal control plus a compensator control. The compensator control and the adaptive laws are derived on the basis of Lyapunov stability theory. The proposed control algorithm is applied to three different nonholonomic drift-free systems: the unicycle model, the front wheel car model, and the mobile robot with trailer model. The controllability Lie algebra of the unicycle model contains Lie brackets of depth one, the model of a front wheel car contains Lie brackets of depths one and two, and the model of a mobile robot with trailer contains Lie brackets of depths one, two, and three. The effectiveness of the proposed control algorithm is verified through numerical simulations.

The self-adaptation to dynamic failures for efficient virtual organization formations in grid computing context

International Nuclear Information System (INIS)

Han Liangxiu

2009-01-01

Grid computing aims to enable 'resource sharing and coordinated problem solving in dynamic, multi-institutional virtual organizations (VOs)'. However, due to the nature of heterogeneous and dynamic resources, dynamic failures in the distributed grid environment usually occur more than in traditional computation platforms, which cause failed VO formations. In this paper, we develop a novel self-adaptive mechanism to dynamic failures during VO formations. Such a self-adaptive scheme allows an individual and member of VOs to automatically find other available or replaceable one once a failure happens and therefore makes systems automatically recover from dynamic failures. We define dynamic failure situations of a system by using two standard indicators: mean time between failures (MTBF) and mean time to recover (MTTR). We model both MTBF and MTTR as Poisson distributions. We investigate and analyze the efficiency of the proposed self-adaptation mechanism to dynamic failures by comparing the success probability of VO formations before and after adopting it in three different cases: (1) different failure situations; (2) different organizational structures and scales; (3) different task complexities. The experimental results show that the proposed scheme can automatically adapt to dynamic failures and effectively improve the dynamic VO formation performance in the event of node failures, which provide a valuable addition to the field.

Distributed computing environments for future space control systems

Science.gov (United States)

Viallefont, Pierre

1993-01-01

The aim of this paper is to present the results of a CNES research project on distributed computing systems. The purpose of this research was to study the impact of the use of new computer technologies in the design and development of future space applications. The first part of this study was a state-of-the-art review of distributed computing systems. One of the interesting ideas arising from this review is the concept of a 'virtual computer' allowing the distributed hardware architecture to be hidden from a software application. The 'virtual computer' can improve system performance by adapting the best architecture (addition of computers) to the software application without having to modify its source code. This concept can also decrease the cost and obsolescence of the hardware architecture. In order to verify the feasibility of the 'virtual computer' concept, a prototype representative of a distributed space application is being developed independently of the hardware architecture.

A computational framework for modeling targets as complex adaptive systems

Science.gov (United States)

Santos, Eugene; Santos, Eunice E.; Korah, John; Murugappan, Vairavan; Subramanian, Suresh

2017-05-01

Modeling large military targets is a challenge as they can be complex systems encompassing myriad combinations of human, technological, and social elements that interact, leading to complex behaviors. Moreover, such targets have multiple components and structures, extending across multiple spatial and temporal scales, and are in a state of change, either in response to events in the environment or changes within the system. Complex adaptive system (CAS) theory can help in capturing the dynamism, interactions, and more importantly various emergent behaviors, displayed by the targets. However, a key stumbling block is incorporating information from various intelligence, surveillance and reconnaissance (ISR) sources, while dealing with the inherent uncertainty, incompleteness and time criticality of real world information. To overcome these challenges, we present a probabilistic reasoning network based framework called complex adaptive Bayesian Knowledge Base (caBKB). caBKB is a rigorous, overarching and axiomatic framework that models two key processes, namely information aggregation and information composition. While information aggregation deals with the union, merger and concatenation of information and takes into account issues such as source reliability and information inconsistencies, information composition focuses on combining information components where such components may have well defined operations. Since caBKBs can explicitly model the relationships between information pieces at various scales, it provides unique capabilities such as the ability to de-aggregate and de-compose information for detailed analysis. Using a scenario from the Network Centric Operations (NCO) domain, we will describe how our framework can be used for modeling targets with a focus on methodologies for quantifying NCO performance metrics.

Models, methods and software tools for building complex adaptive traffic systems

International Nuclear Information System (INIS)

Alyushin, S.A.

2011-01-01

The paper studies the modern methods and tools to simulate the behavior of complex adaptive systems (CAS), the existing systems of traffic modeling in simulators and their characteristics; proposes requirements for assessing the suitability of the system to simulate the CAS behavior in simulators. The author has developed a model of adaptive agent representation and its functioning environment to meet certain requirements set above, and has presented methods of agents' interactions and methods of conflict resolution in simulated traffic situations. A simulation system realizing computer modeling for simulating the behavior of CAS in traffic situations has been created [ru

Personal computer based home automation system

OpenAIRE

Hellmuth, George F.

1993-01-01

The systems engineering process is applied in the development of the preliminary design of a home automation communication protocol. The objective of the communication protocol is to provide a means for a personal computer to communicate with adapted appliances in the home. A needs analysis is used to ascertain that a need exist for a home automation system. Numerous design alternatives are suggested and evaluated to determine the best possible protocol design. Coaxial cable...

Genre-adaptive Semantic Computing and Audio-based Modelling for Music Mood Annotation

DEFF Research Database (Denmark)

Saari, Pasi; Fazekas, György; Eerola, Tuomas

2016-01-01

This study investigates whether taking genre into account is beneficial for automatic music mood annotation in terms of core affects valence, arousal, and tension, as well as several other mood scales. Novel techniques employing genre-adaptive semantic computing and audio-based modelling are prop......This study investigates whether taking genre into account is beneficial for automatic music mood annotation in terms of core affects valence, arousal, and tension, as well as several other mood scales. Novel techniques employing genre-adaptive semantic computing and audio-based modelling...... related to a set of 600 popular music tracks spanning multiple genres. The results show that ACTwg outperforms a semantic computing technique that does not exploit genre information, and ACTwg-SLPwg outperforms conventional techniques and other genre-adaptive alternatives. In particular, improvements......-based genre representation for genre-adaptive music mood analysis....

Distributed Problem Solving: Adaptive Networks with a Computer Intermediary Resource. Intelligent Executive Computer Communication

Science.gov (United States)

1991-06-01

Proceedings of The National Conference on Artificial Intelligence , pages 181-184, The American Association for Aritificial Intelligence , Pittsburgh...Intermediary Resource: Intelligent Executive Computer Communication John Lyman and Carla J. Conaway University of California at Los Angeles for Contracting...Include Security Classification) Interim Report: Distributed Problem Solving: Adaptive Networks With a Computer Intermediary Resource: Intelligent

Pipelining Computational Stages of the Tomographic Reconstructor for Multi-Object Adaptive Optics on a Multi-GPU System

KAUST Repository

Charara, Ali; Ltaief, Hatem; Gratadour, Damien; Keyes, David E.; Sevin, Arnaud; Abdelfattah, Ahmad; Gendron, Eric; Morel, Carine; Vidal, Fabrice

2014-01-01

called MOSAIC has been proposed to perform multi-object spectroscopy using the Multi-Object Adaptive Optics (MOAO) technique. The core implementation of the simulation lies in the intensive computation of a tomographic reconstruct or (TR), which is used

Computer-Adaptive Testing in Second Language Contexts.

Science.gov (United States)

Chalhoub-Deville, Micheline; Deville, Craig

1999-01-01

Provides a broad overview of computerized testing issues with an emphasis on computer-adaptive testing (CAT). A survey of the potential benefits and drawbacks of CAT are given, the process of CAT development is described; and some L2 instruments developed to assess various language skills are summarized. (Author/VWL)

Computerized adaptive testing in computer assisted learning?

NARCIS (Netherlands)

Veldkamp, Bernard P.; Matteucci, Mariagiulia; Eggen, Theodorus Johannes Hendrikus Maria; De Wannemacker, Stefan; Clarebout, Geraldine; De Causmaecker, Patrick

2011-01-01

A major goal in computerized learning systems is to optimize learning, while in computerized adaptive tests (CAT) efficient measurement of the proficiency of students is the main focus. There seems to be a common interest to integrate computerized adaptive item selection in learning systems and

Self-adaptation in Software-intensive Cyber-physical Systems: From System Goals to Architecture Configurations

Czech Academy of Sciences Publication Activity Database

Gerostathopoulos, I.; Bureš, Tomáš; Hnětynka, P.; Keznikl, Jaroslav; Kit, M.; Plášil, F.; Plouzeau, N.

2016-01-01

Roč. 122, December (2016), s. 378-397 ISSN 0164-1212 Grant - others:GA MŠk(CZ) LD15051 Institutional support: RVO:67985807 Keywords : cyber–physical systems * self-adaptivity * dependability Subject RIV: JC - Computer Hardware ; Software Impact factor: 2.444, year: 2016

Algebraic and adaptive learning in neural control systems

Science.gov (United States)

Ferrari, Silvia

A systematic approach is developed for designing adaptive and reconfigurable nonlinear control systems that are applicable to plants modeled by ordinary differential equations. The nonlinear controller comprising a network of neural networks is taught using a two-phase learning procedure realized through novel techniques for initialization, on-line training, and adaptive critic design. A critical observation is that the gradients of the functions defined by the neural networks must equal corresponding linear gain matrices at chosen operating points. On-line training is based on a dual heuristic adaptive critic architecture that improves control for large, coupled motions by accounting for actual plant dynamics and nonlinear effects. An action network computes the optimal control law; a critic network predicts the derivative of the cost-to-go with respect to the state. Both networks are algebraically initialized based on prior knowledge of satisfactory pointwise linear controllers and continue to adapt on line during full-scale simulations of the plant. On-line training takes place sequentially over discrete periods of time and involves several numerical procedures. A backpropagating algorithm called Resilient Backpropagation is modified and successfully implemented to meet these objectives, without excessive computational expense. This adaptive controller is as conservative as the linear designs and as effective as a global nonlinear controller. The method is successfully implemented for the full-envelope control of a six-degree-of-freedom aircraft simulation. The results show that the on-line adaptation brings about improved performance with respect to the initialization phase during aircraft maneuvers that involve large-angle and coupled dynamics, and parameter variations.

Experience with a distributed computing system for magnetic field analysis

International Nuclear Information System (INIS)

Newman, M.J.

1978-08-01

The development of a general purpose computer system, THESEUS, is described the initial use for which has been magnetic field analysis. The system involves several computers connected by data links. Some are small computers with interactive graphics facilities and limited analysis capabilities, and others are large computers for batch execution of analysis programs with heavy processor demands. The system is highly modular for easy extension and highly portable for transfer to different computers. It can easily be adapted for a completely different application. It provides a highly efficient and flexible interface between magnet designers and specialised analysis programs. Both the advantages and problems experienced are highlighted, together with a mention of possible future developments. (U.K.)

Introducing Enabling Computational Tools to the Climate Sciences: Multi-Resolution Climate Modeling with Adaptive Cubed-Sphere Grids

Energy Technology Data Exchange (ETDEWEB)

Jablonowski, Christiane [Univ. of Michigan, Ann Arbor, MI (United States)

2015-07-14

The research investigates and advances strategies how to bridge the scale discrepancies between local, regional and global phenomena in climate models without the prohibitive computational costs of global cloud-resolving simulations. In particular, the research explores new frontiers in computational geoscience by introducing high-order Adaptive Mesh Refinement (AMR) techniques into climate research. AMR and statically-adapted variable-resolution approaches represent an emerging trend for atmospheric models and are likely to become the new norm in future-generation weather and climate models. The research advances the understanding of multi-scale interactions in the climate system and showcases a pathway how to model these interactions effectively with advanced computational tools, like the Chombo AMR library developed at the Lawrence Berkeley National Laboratory. The research is interdisciplinary and combines applied mathematics, scientific computing and the atmospheric sciences. In this research project, a hierarchy of high-order atmospheric models on cubed-sphere computational grids have been developed that serve as an algorithmic prototype for the finite-volume solution-adaptive Chombo-AMR approach. The foci of the investigations have lied on the characteristics of both static mesh adaptations and dynamically-adaptive grids that can capture flow fields of interest like tropical cyclones. Six research themes have been chosen. These are (1) the introduction of adaptive mesh refinement techniques into the climate sciences, (2) advanced algorithms for nonhydrostatic atmospheric dynamical cores, (3) an assessment of the interplay between resolved-scale dynamical motions and subgrid-scale physical parameterizations, (4) evaluation techniques for atmospheric model hierarchies, (5) the comparison of AMR refinement strategies and (6) tropical cyclone studies with a focus on multi-scale interactions and variable-resolution modeling. The results of this research project

Learning-Based Adaptive Optimal Tracking Control of Strict-Feedback Nonlinear Systems.

Science.gov (United States)

Gao, Weinan; Jiang, Zhong-Ping; Weinan Gao; Zhong-Ping Jiang; Gao, Weinan; Jiang, Zhong-Ping

2018-06-01

This paper proposes a novel data-driven control approach to address the problem of adaptive optimal tracking for a class of nonlinear systems taking the strict-feedback form. Adaptive dynamic programming (ADP) and nonlinear output regulation theories are integrated for the first time to compute an adaptive near-optimal tracker without any a priori knowledge of the system dynamics. Fundamentally different from adaptive optimal stabilization problems, the solution to a Hamilton-Jacobi-Bellman (HJB) equation, not necessarily a positive definite function, cannot be approximated through the existing iterative methods. This paper proposes a novel policy iteration technique for solving positive semidefinite HJB equations with rigorous convergence analysis. A two-phase data-driven learning method is developed and implemented online by ADP. The efficacy of the proposed adaptive optimal tracking control methodology is demonstrated via a Van der Pol oscillator with time-varying exogenous signals.

Non-adaptive measurement-based quantum computation and multi-party Bell inequalities

International Nuclear Information System (INIS)

Hoban, Matty J; Campbell, Earl T; Browne, Dan E; Loukopoulos, Klearchos

2011-01-01

Quantum correlations exhibit behaviour that cannot be resolved with a local hidden variable picture of the world. In quantum information, they are also used as resources for information processing tasks, such as measurement-based quantum computation (MQC). In MQC, universal quantum computation can be achieved via adaptive measurements on a suitable entangled resource state. In this paper, we look at a version of MQC in which we remove the adaptivity of measurements and aim to understand what computational abilities remain in the resource. We show that there are explicit connections between this model of computation and the question of non-classicality in quantum correlations. We demonstrate this by focusing on deterministic computation of Boolean functions, in which natural generalizations of the Greenberger-Horne-Zeilinger paradox emerge; we then explore probabilistic computation via, which multipartite Bell inequalities can be defined. We use this correspondence to define families of multi-party Bell inequalities, which we show to have a number of interesting contrasting properties.

Non-adaptive measurement-based quantum computation and multi-party Bell inequalities

Energy Technology Data Exchange (ETDEWEB)

Hoban, Matty J; Campbell, Earl T; Browne, Dan E [Department of Physics and Astronomy, University College London, Gower Street, London WC1E 6BT (United Kingdom); Loukopoulos, Klearchos, E-mail: m.hoban@ucl.ac.uk [Department of Materials, Oxford University, Parks Road, Oxford OX1 4PH (United Kingdom)

2011-02-15

Quantum correlations exhibit behaviour that cannot be resolved with a local hidden variable picture of the world. In quantum information, they are also used as resources for information processing tasks, such as measurement-based quantum computation (MQC). In MQC, universal quantum computation can be achieved via adaptive measurements on a suitable entangled resource state. In this paper, we look at a version of MQC in which we remove the adaptivity of measurements and aim to understand what computational abilities remain in the resource. We show that there are explicit connections between this model of computation and the question of non-classicality in quantum correlations. We demonstrate this by focusing on deterministic computation of Boolean functions, in which natural generalizations of the Greenberger-Horne-Zeilinger paradox emerge; we then explore probabilistic computation via, which multipartite Bell inequalities can be defined. We use this correspondence to define families of multi-party Bell inequalities, which we show to have a number of interesting contrasting properties.

System and method for controlling power consumption in a computer system based on user satisfaction

Science.gov (United States)

Yang, Lei; Dick, Robert P; Chen, Xi; Memik, Gokhan; Dinda, Peter A; Shy, Alex; Ozisikyilmaz, Berkin; Mallik, Arindam; Choudhary, Alok

2014-04-22

Systems and methods for controlling power consumption in a computer system. For each of a plurality of interactive applications, the method changes a frequency at which a processor of the computer system runs, receives an indication of user satisfaction, determines a relationship between the changed frequency and the user satisfaction of the interactive application, and stores the determined relationship information. The determined relationship can distinguish between different users and different interactive applications. A frequency may be selected from the discrete frequencies at which the processor of the computer system runs based on the determined relationship information for a particular user and a particular interactive application running on the processor of the computer system. The processor may be adapted to run at the selected frequency.

Accuracy requirements of optical linear algebra processors in adaptive optics imaging systems

Science.gov (United States)

Downie, John D.

1990-01-01

A ground-based adaptive optics imaging telescope system attempts to improve image quality by detecting and correcting for atmospherically induced wavefront aberrations. The required control computations during each cycle will take a finite amount of time. Longer time delays result in larger values of residual wavefront error variance since the atmosphere continues to change during that time. Thus an optical processor may be well-suited for this task. This paper presents a study of the accuracy requirements in a general optical processor that will make it competitive with, or superior to, a conventional digital computer for the adaptive optics application. An optimization of the adaptive optics correction algorithm with respect to an optical processor's degree of accuracy is also briefly discussed.

A Complexity-Aware Video Adaptation Mechanism for Live Streaming Systems

Directory of Open Access Journals (Sweden)

Chen Homer H

2007-01-01

Full Text Available The paradigm shift of network design from performance-centric to constraint-centric has called for new signal processing techniques to deal with various aspects of resource-constrained communication and networking. In this paper, we consider the computational constraints of a multimedia communication system and propose a video adaptation mechanism for live video streaming of multiple channels. The video adaptation mechanism includes three salient features. First, it adjusts the computational resource of the streaming server block by block to provide a fine control of the encoding complexity. Second, as far as we know, it is the first mechanism to allocate the computational resource to multiple channels. Third, it utilizes a complexity-distortion model to determine the optimal coding parameter values to achieve global optimization. These techniques constitute the basic building blocks for a successful application of wireless and Internet video to digital home, surveillance, IPTV, and online games.

A Complexity-Aware Video Adaptation Mechanism for Live Streaming Systems

Science.gov (United States)

Lu, Meng-Ting; Yao, Jason J.; Chen, Homer H.

2007-12-01

The paradigm shift of network design from performance-centric to constraint-centric has called for new signal processing techniques to deal with various aspects of resource-constrained communication and networking. In this paper, we consider the computational constraints of a multimedia communication system and propose a video adaptation mechanism for live video streaming of multiple channels. The video adaptation mechanism includes three salient features. First, it adjusts the computational resource of the streaming server block by block to provide a fine control of the encoding complexity. Second, as far as we know, it is the first mechanism to allocate the computational resource to multiple channels. Third, it utilizes a complexity-distortion model to determine the optimal coding parameter values to achieve global optimization. These techniques constitute the basic building blocks for a successful application of wireless and Internet video to digital home, surveillance, IPTV, and online games.

Real time computer system with distributed microprocessors

International Nuclear Information System (INIS)

Heger, D.; Steusloff, H.; Syrbe, M.

1979-01-01

The usual centralized structure of computer systems, especially of process computer systems, cannot sufficiently use the progress of very large-scale integrated semiconductor technology with respect to increasing the reliability and performance and to decreasing the expenses especially of the external periphery. This and the increasing demands on process control systems has led the authors to generally examine the structure of such systems and to adapt it to the new surroundings. Computer systems with distributed, optical fibre-coupled microprocessors allow a very favourable problem-solving with decentralized controlled buslines and functional redundancy with automatic fault diagnosis and reconfiguration. A fit programming system supports these hardware properties: PEARL for multicomputer systems, dynamic loader, processor and network operating system. The necessary design principles for this are proved mainly theoretically and by value analysis. An optimal overall system of this new generation of process control systems was established, supported by results of 2 PDV projects (modular operating systems, input/output colour screen system as control panel), for the purpose of testing by apllying the system for the control of 28 pit furnaces of a steel work. (orig.) [de

Treatment of human-computer interface in a decision support system

International Nuclear Information System (INIS)

Heger, A.S.; Duran, F.A.; Cox, R.G.

1992-01-01

One of the most challenging applications facing the computer community is development of effective adaptive human-computer interface. This challenge stems from the complex nature of the human part of this symbiosis. The application of this discipline to the environmental restoration and waste management is further complicated due to the nature of environmental data. The information that is required to manage environmental impacts of human activity is fundamentally complex. This paper will discuss the efforts at Sandia National Laboratories in developing the adaptive conceptual model manager within the constraint of the environmental decision-making. A computer workstation, that hosts the Conceptual Model Manager and the Sandia Environmental Decision Support System will also be discussed

Wireless Adaptive Therapeutic TeleGaming in a Pervasive Computing Environment

Science.gov (United States)

Peters, James F.; Szturm, Tony; Borkowski, Maciej; Lockery, Dan; Ramanna, Sheela; Shay, Barbara

This chapter introduces a wireless, pervasive computing approach to adaptive therapeutic telegaming considered in the context of near set theory. Near set theory provides a formal basis for observation, comparison and classification of perceptual granules. A perceptual granule is defined by a collection of objects that are graspable by the senses or by the mind. In the proposed pervasive computing approach to telegaming, a handicapped person (e.g., stroke patient with limited hand, finger, arm function) plays a video game by interacting with familiar instrumented objects such as cups, cutlery, soccer balls, nozzles, screw top-lids, spoons, so that the technology that makes therapeutic exercise game-playing possible is largely invisible (Archives of Physical Medicine and Rehabilitation 89:2213-2217, 2008). The basic approach to adaptive learning (AL) in the proposed telegaming environment is ethology-inspired and is quite different from the traditional approach to reinforcement learning. In biologically-inspired learning, organisms learn to achieve some goal by durable modification of behaviours in response to signals from the environment resulting from specific experiences (Animal Behavior, 1995). The term adaptive is used here in an ethological sense, where learning by an organism results from modifying behaviour in response to perceived changes in the environment. To instill adaptivity in a video game, it is assumed that learning by a video game is episodic. During an episode, the behaviour of a player is measured indirectly by tracking the occurrence of gaming events such as a hit or a miss of a target (e.g., hitting a moving ball with a game paddle). An ethogram provides a record of behaviour feature values that provide a basis a functional registry for handicapped players for gaming adaptivity. An important practical application of adaptive gaming is therapeutic rehabilitation exercise carried out in parallel with playing action video games. Enjoyable and

Computer Adaptive Testing, Big Data and Algorithmic Approaches to Education

Science.gov (United States)

Thompson, Greg

2017-01-01

This article critically considers the promise of computer adaptive testing (CAT) and digital data to provide better and quicker data that will improve the quality, efficiency and effectiveness of schooling. In particular, it uses the case of the Australian NAPLAN test that will become an online, adaptive test from 2016. The article argues that…

Computational adaptive optics for broadband optical interferometric tomography of biological tissue.

Science.gov (United States)

Adie, Steven G; Graf, Benedikt W; Ahmad, Adeel; Carney, P Scott; Boppart, Stephen A

2012-05-08

Aberrations in optical microscopy reduce image resolution and contrast, and can limit imaging depth when focusing into biological samples. Static correction of aberrations may be achieved through appropriate lens design, but this approach does not offer the flexibility of simultaneously correcting aberrations for all imaging depths, nor the adaptability to correct for sample-specific aberrations for high-quality tomographic optical imaging. Incorporation of adaptive optics (AO) methods have demonstrated considerable improvement in optical image contrast and resolution in noninterferometric microscopy techniques, as well as in optical coherence tomography. Here we present a method to correct aberrations in a tomogram rather than the beam of a broadband optical interferometry system. Based on Fourier optics principles, we correct aberrations of a virtual pupil using Zernike polynomials. When used in conjunction with the computed imaging method interferometric synthetic aperture microscopy, this computational AO enables object reconstruction (within the single scattering limit) with ideal focal-plane resolution at all depths. Tomographic reconstructions of tissue phantoms containing subresolution titanium-dioxide particles and of ex vivo rat lung tissue demonstrate aberration correction in datasets acquired with a highly astigmatic illumination beam. These results also demonstrate that imaging with an aberrated astigmatic beam provides the advantage of a more uniform depth-dependent signal compared to imaging with a standard gaussian beam. With further work, computational AO could enable the replacement of complicated and expensive optical hardware components with algorithms implemented on a standard desktop computer, making high-resolution 3D interferometric tomography accessible to a wider group of users and nonspecialists.

Water System Adaptation To Hydrological Changes: Module 8, Regulatory Framework Intersections: Past, Present, and Future

Science.gov (United States)

This course will introduce students to the fundamental principles of water system adaptation to hydrological changes, with emphasis on data analysis and interpretation, technical planning, and computational modeling. Starting with real-world scenarios and adaptation needs, the co...

Adaptive Modeling of the International Space Station Electrical Power System

Science.gov (United States)

Thomas, Justin Ray

2007-01-01

Software simulations provide NASA engineers the ability to experiment with spacecraft systems in a computer-imitated environment. Engineers currently develop software models that encapsulate spacecraft system behavior. These models can be inaccurate due to invalid assumptions, erroneous operation, or system evolution. Increasing accuracy requires manual calibration and domain-specific knowledge. This thesis presents a method for automatically learning system models without any assumptions regarding system behavior. Data stream mining techniques are applied to learn models for critical portions of the International Space Station (ISS) Electrical Power System (EPS). We also explore a knowledge fusion approach that uses traditional engineered EPS models to supplement the learned models. We observed that these engineered EPS models provide useful background knowledge to reduce predictive error spikes when confronted with making predictions in situations that are quite different from the training scenarios used when learning the model. Evaluations using ISS sensor data and existing EPS models demonstrate the success of the adaptive approach. Our experimental results show that adaptive modeling provides reductions in model error anywhere from 80% to 96% over these existing models. Final discussions include impending use of adaptive modeling technology for ISS mission operations and the need for adaptive modeling in future NASA lunar and Martian exploration.

An Overview of Recent Developments in Cognitive Diagnostic Computer Adaptive Assessments

Directory of Open Access Journals (Sweden)

Alan Huebner

2010-01-01

Full Text Available Cognitive diagnostic modeling has become an exciting new field of psychometric research. These models aim to diagnose examinees' mastery status of a group of discretely defined skills, or attributes, thereby providing them with detailed information regarding their specific strengths and weaknesses. Combining cognitive diagnosis with computer adaptive assessments has emerged as an important part of this new field. This article aims to provide practitioners and researchers with an introduction to and overview of recent developments in cognitive diagnostic computer adaptive assessments.

Comparative study of adaptive-noise-cancellation algorithms for intrusion detection systems

International Nuclear Information System (INIS)

Claassen, J.P.; Patterson, M.M.

1981-01-01

Some intrusion detection systems are susceptible to nonstationary noise resulting in frequent nuisance alarms and poor detection when the noise is present. Adaptive inverse filtering for single channel systems and adaptive noise cancellation for two channel systems have both demonstrated good potential in removing correlated noise components prior detection. For such noise susceptible systems the suitability of a noise reduction algorithm must be established in a trade-off study weighing algorithm complexity against performance. The performance characteristics of several distinct classes of algorithms are established through comparative computer studies using real signals. The relative merits of the different algorithms are discussed in the light of the nature of intruder and noise signals

Intelligent adaptive systems an interaction-centered design perspective

CERN Document Server

Hou, Ming; Burns, Catherine

2014-01-01

A synthesis of recent research and developments on intelligent adaptive systems from the HF (human factors) and HCI (human-computer interaction) domains, this book provides integrated design guidance and recommendations for researchers and system developers. It addresses a recognized lack of integration between the HF and HCI research communities, which has led to inconsistencies between the research approaches adopted, and a lack of exploitation of research from one field by the other. The book establishes design guidance through the review of conceptual frameworks, analytical methodologies,

Indirect versus direct feedback in computer-based Prism Adaptation Therapy

DEFF Research Database (Denmark)

Wilms, Inge Linda; Rytter, Hana Malá

2010-01-01

Prism Adaptation Therapy (PAT) is an intervention method in the treatment of the attention disorder neglect (Frassinetti, Angeli, Meneghello, Avanzi, & Ladavas, 2002; Rossetti, et al., 1998). The aim of this study was to investigate whether one session of PAT using a computer-attached touchscreen...... in the aftereffect. The findings have direct implications for future implementations of computer-based methods of treatment of visuospatial disorders and computer-assisted rehabilitation in general....

Computer-Adaptive Testing: Implications for Students' Achievement, Motivation, Engagement, and Subjective Test Experience

Science.gov (United States)

Martin, Andrew J.; Lazendic, Goran

2018-01-01

The present study investigated the implications of computer-adaptive testing (operationalized by way of multistage adaptive testing; MAT) and "conventional" fixed order computer testing for various test-relevant outcomes in numeracy, including achievement, test-relevant motivation and engagement, and subjective test experience. It did so…

Detection of User Independent Single Trial ERPs in Brain Computer Interfaces: An Adaptive Spatial Filtering Approach

DEFF Research Database (Denmark)

Leza, Cristina; Puthusserypady, Sadasivan

2017-01-01

Brain Computer Interfaces (BCIs) use brain signals to communicate with the external world. The main challenges to address are speed, accuracy and adaptability. Here, a novel algorithm for P300 based BCI spelling system is presented, specifically suited for single-trial detection of Event...

Computational 3-D Model of the Human Respiratory System

Science.gov (United States)

We are developing a comprehensive, morphologically-realistic computational model of the human respiratory system that can be used to study the inhalation, deposition, and clearance of contaminants, while being adaptable for age, race, gender, and health/disease status. The model ...

Slice image pretreatment for cone-beam computed tomography based on adaptive filter

International Nuclear Information System (INIS)

Huang Kuidong; Zhang Dinghua; Jin Yanfang

2009-01-01

According to the noise properties and the serial slice image characteristics in Cone-Beam Computed Tomography (CBCT) system, a slice image pretreatment for CBCT based on adaptive filter was proposed. The judging criterion for the noise is established firstly. All pixels are classified into two classes: adaptive center weighted modified trimmed mean (ACWMTM) filter is used for the pixels corrupted by Gauss noise and adaptive median (AM) filter is used for the pixels corrupted by impulse noise. In ACWMTM filtering algorithm, the estimated Gauss noise standard deviation in the current slice image with offset window is replaced by the estimated standard deviation in the adjacent slice image to the current with the corresponding window, so the filtering accuracy of the serial images is improved. The pretreatment experiment on CBCT slice images of wax model of hollow turbine blade shows that the method makes a good performance both on eliminating noises and on protecting details. (authors)

Towards a global monitoring system for CMS computing operations

CERN Multimedia

CERN. Geneva; Bauerdick, Lothar A.T.

2012-01-01

The operation of the CMS computing system requires a complex monitoring system to cover all its aspects: central services, databases, the distributed computing infrastructure, production and analysis workflows, the global overview of the CMS computing activities and the related historical information. Several tools are available to provide this information, developed both inside and outside of the collaboration and often used in common with other experiments. Despite the fact that the current monitoring allowed CMS to successfully perform its computing operations, an evolution of the system is clearly required, to adapt to the recent changes in the data and workload management tools and models and to address some shortcomings that make its usage less than optimal. Therefore, a recent and ongoing coordinated effort was started in CMS, aiming at improving the entire monitoring system by identifying its weaknesses and the new requirements from the stakeholders, rationalise and streamline existing components and ...

Towards psychologically adaptive brain-computer interfaces

Science.gov (United States)

Myrden, A.; Chau, T.

2016-12-01

Objective. Brain-computer interface (BCI) performance is sensitive to short-term changes in psychological states such as fatigue, frustration, and attention. This paper explores the design of a BCI that can adapt to these short-term changes. Approach. Eleven able-bodied individuals participated in a study during which they used a mental task-based EEG-BCI to play a simple maze navigation game while self-reporting their perceived levels of fatigue, frustration, and attention. In an offline analysis, a regression algorithm was trained to predict changes in these states, yielding Pearson correlation coefficients in excess of 0.45 between the self-reported and predicted states. Two means of fusing the resultant mental state predictions with mental task classification were investigated. First, single-trial mental state predictions were used to predict correct classification by the BCI during each trial. Second, an adaptive BCI was designed that retrained a new classifier for each testing sample using only those training samples for which predicted mental state was similar to that predicted for the current testing sample. Main results. Mental state-based prediction of BCI reliability exceeded chance levels. The adaptive BCI exhibited significant, but practically modest, increases in classification accuracy for five of 11 participants and no significant difference for the remaining six despite a smaller average training set size. Significance. Collectively, these findings indicate that adaptation to psychological state may allow the design of more accurate BCIs.

Self-Adaptive Event-Driven Simulation of Multi-Scale Plasma Systems

Science.gov (United States)

Omelchenko, Yuri; Karimabadi, Homayoun

2005-10-01

Multi-scale plasmas pose a formidable computational challenge. The explicit time-stepping models suffer from the global CFL restriction. Efficient application of adaptive mesh refinement (AMR) to systems with irregular dynamics (e.g. turbulence, diffusion-convection-reaction, particle acceleration etc.) may be problematic. To address these issues, we developed an alternative approach to time stepping: self-adaptive discrete-event simulation (DES). DES has origin in operations research, war games and telecommunications. We combine finite-difference and particle-in-cell techniques with this methodology by assuming two caveats: (1) a local time increment, dt for a discrete quantity f can be expressed in terms of a physically meaningful quantum value, df; (2) f is considered to be modified only when its change exceeds df. Event-driven time integration is self-adaptive as it makes use of causality rules rather than parametric time dependencies. This technique enables asynchronous flux-conservative update of solution in accordance with local temporal scales, removes the curse of the global CFL condition, eliminates unnecessary computation in inactive spatial regions and results in robust and fast parallelizable codes. It can be naturally combined with various mesh refinement techniques. We discuss applications of this novel technology to diffusion-convection-reaction systems and hybrid simulations of magnetosonic shocks.

Active Hearing Mechanisms Inspire Adaptive Amplification in an Acoustic Sensor System.

Science.gov (United States)

Guerreiro, Jose; Reid, Andrew; Jackson, Joseph C; Windmill, James F C

2018-06-01

Over many millions of years of evolution, nature has developed some of the most adaptable sensors and sensory systems possible, capable of sensing, conditioning and processing signals in a very power- and size-effective manner. By looking into biological sensors and systems as a source of inspiration, this paper presents the study of a bioinspired concept of signal processing at the sensor level. By exploiting a feedback control mechanism between a front-end acoustic receiver and back-end neuronal based computation, a nonlinear amplification with hysteretic behavior is created. Moreover, the transient response of the front-end acoustic receiver can also be controlled and enhanced. A theoretical model is proposed and the concept is prototyped experimentally through an embedded system setup that can provide dynamic adaptations of a sensory system comprising a MEMS microphone placed in a closed-loop feedback system. It faithfully mimics the mosquito's active hearing response as a function of the input sound intensity. This is an adaptive acoustic sensor system concept that can be exploited by sensor and system designers within acoustics and ultrasonic engineering fields.

Performance Comparison of Adaptive Estimation Techniques for Power System Small-Signal Stability Assessment

Directory of Open Access Journals (Sweden)

E. A. Feilat

2010-12-01

Full Text Available This paper demonstrates the assessment of the small-signal stability of a single-machine infinite- bus power system under widely varying loading conditions using the concept of synchronizing and damping torques coefficients. The coefficients are calculated from the time responses of the rotor angle, speed, and torque of the synchronous generator. Three adaptive computation algorithms including Kalman filtering, Adaline, and recursive least squares have been compared to estimate the synchronizing and damping torque coefficients. The steady-state performance of the three adaptive techniques is compared with the conventional static least squares technique by conducting computer simulations at different loading conditions. The algorithms are compared to each other in terms of speed of convergence and accuracy. The recursive least squares estimation offers several advantages including significant reduction in computing time and computational complexity. The tendency of an unsupplemented static exciter to degrade the system damping for medium and heavy loading is verified. Consequently, a power system stabilizer whose parameters are adjusted to compensate for variations in the system loading is designed using phase compensation method. The effectiveness of the stabilizer in enhancing the dynamic stability over wide range of operating conditions is verified through the calculation of the synchronizing and damping torque coefficients using recursive least square technique.

Online adaptation of a c-VEP Brain-computer Interface(BCI) based on error-related potentials and unsupervised learning.

Science.gov (United States)

Spüler, Martin; Rosenstiel, Wolfgang; Bogdan, Martin

2012-01-01

The goal of a Brain-Computer Interface (BCI) is to control a computer by pure brain activity. Recently, BCIs based on code-modulated visual evoked potentials (c-VEPs) have shown great potential to establish high-performance communication. In this paper we present a c-VEP BCI that uses online adaptation of the classifier to reduce calibration time and increase performance. We compare two different approaches for online adaptation of the system: an unsupervised method and a method that uses the detection of error-related potentials. Both approaches were tested in an online study, in which an average accuracy of 96% was achieved with adaptation based on error-related potentials. This accuracy corresponds to an average information transfer rate of 144 bit/min, which is the highest bitrate reported so far for a non-invasive BCI. In a free-spelling mode, the subjects were able to write with an average of 21.3 error-free letters per minute, which shows the feasibility of the BCI system in a normal-use scenario. In addition we show that a calibration of the BCI system solely based on the detection of error-related potentials is possible, without knowing the true class labels.

Modeling of memristor-based chaotic systems using nonlinear Wiener adaptive filters based on backslash operator

International Nuclear Information System (INIS)

Zhao, Yibo; Jiang, Yi; Feng, Jiuchao; Wu, Lifu

2016-01-01

Highlights: • A novel nonlinear Wiener adaptive filters based on the backslash operator are proposed. • The identification approach to the memristor-based chaotic systems using the proposed adaptive filters. • The weight update algorithm and convergence characteristics for the proposed adaptive filters are derived. - Abstract: Memristor-based chaotic systems have complex dynamical behaviors, which are characterized as nonlinear and hysteresis characteristics. Modeling and identification of their nonlinear model is an important premise for analyzing the dynamical behavior of the memristor-based chaotic systems. This paper presents a novel nonlinear Wiener adaptive filtering identification approach to the memristor-based chaotic systems. The linear part of Wiener model consists of the linear transversal adaptive filters, the nonlinear part consists of nonlinear adaptive filters based on the backslash operator for the hysteresis characteristics of the memristor. The weight update algorithms for the linear and nonlinear adaptive filters are derived. Final computer simulation results show the effectiveness as well as fast convergence characteristics. Comparing with the adaptive nonlinear polynomial filters, the proposed nonlinear adaptive filters have less identification error.

Complex systems relationships between control, communications and computing

CERN Document Server

2016-01-01

This book gives a wide-ranging description of the many facets of complex dynamic networks and systems within an infrastructure provided by integrated control and supervision: envisioning, design, experimental exploration, and implementation. The theoretical contributions and the case studies presented can reach control goals beyond those of stabilization and output regulation or even of adaptive control. Reporting on work of the Control of Complex Systems (COSY) research program, Complex Systems follows from and expands upon an earlier collection: Control of Complex Systems by introducing novel theoretical techniques for hard-to-control networks and systems. The major common feature of all the superficially diverse contributions encompassed by this book is that of spotting and exploiting possible areas of mutual reinforcement between control, computing and communications. These help readers to achieve not only robust stable plant system operation but also properties such as collective adaptivity, integrity an...

Evolutionary Computation and Its Applications in Neural and Fuzzy Systems

Directory of Open Access Journals (Sweden)

Biaobiao Zhang

2011-01-01

Full Text Available Neural networks and fuzzy systems are two soft-computing paradigms for system modelling. Adapting a neural or fuzzy system requires to solve two optimization problems: structural optimization and parametric optimization. Structural optimization is a discrete optimization problem which is very hard to solve using conventional optimization techniques. Parametric optimization can be solved using conventional optimization techniques, but the solution may be easily trapped at a bad local optimum. Evolutionary computation is a general-purpose stochastic global optimization approach under the universally accepted neo-Darwinian paradigm, which is a combination of the classical Darwinian evolutionary theory, the selectionism of Weismann, and the genetics of Mendel. Evolutionary algorithms are a major approach to adaptation and optimization. In this paper, we first introduce evolutionary algorithms with emphasis on genetic algorithms and evolutionary strategies. Other evolutionary algorithms such as genetic programming, evolutionary programming, particle swarm optimization, immune algorithm, and ant colony optimization are also described. Some topics pertaining to evolutionary algorithms are also discussed, and a comparison between evolutionary algorithms and simulated annealing is made. Finally, the application of EAs to the learning of neural networks as well as to the structural and parametric adaptations of fuzzy systems is also detailed.

Computer intervention impact on psychosocial adaptation of rural women with chronic conditions.

Science.gov (United States)

Weinert, Clarann; Cudney, Shirley; Comstock, Bryan; Bansal, Aasthaa

2011-01-01

Adapting to living with chronic conditions is a life-long psychosocial challenge. The purpose of this study was to report the effect of a computer intervention on the psychosocial adaptation of rural women with chronic conditions. A two-group study design was used with 309 middle-aged, rural women who had chronic conditions, randomized into either a computer-based intervention or a control group. Data were collected at baseline, at the end of the intervention, and 6 months later on the psychosocial indicators of social support, self-esteem, acceptance of illness, stress, depression, and loneliness. The impact of the computer-based intervention was statistically significant for five of six of the psychosocial outcomes measured, with a modest impact on social support. The largest benefits were seen in depression, stress, and acceptance. The women-to-women intervention resulted in positive psychosocial responses that have the potential to contribute to successful management of illness and adaptation. Other components of adaptation to be examined are the impact of the intervention on illness management and quality of life and the interrelationships among environmental stimuli, psychosocial response, and illness management.

Identifying Students at Risk: An Examination of Computer-Adaptive Measures and Latent Class Growth Analysis

Science.gov (United States)

Keller-Margulis, Milena; McQuillin, Samuel D.; Castañeda, Juan Javier; Ochs, Sarah; Jones, John H.

2018-01-01

Multitiered systems of support depend on screening technology to identify students at risk. The purpose of this study was to examine the use of a computer-adaptive test and latent class growth analysis (LCGA) to identify students at risk in reading with focus on the use of this methodology to characterize student performance in screening.…

Towards a Global Monitoring System for CMS Computing Operations

Energy Technology Data Exchange (ETDEWEB)

Bauerdick, L. A.T. [Fermilab; Sciaba, Andrea [CERN

2012-01-01

The operation of the CMS computing system requires a complex monitoring system to cover all its aspects: central services, databases, the distributed computing infrastructure, production and analysis workflows, the global overview of the CMS computing activities and the related historical information. Several tools are available to provide this information, developed both inside and outside of the collaboration and often used in common with other experiments. Despite the fact that the current monitoring allowed CMS to successfully perform its computing operations, an evolution of the system is clearly required, to adapt to the recent changes in the data and workload management tools and models and to address some shortcomings that make its usage less than optimal. Therefore, a recent and ongoing coordinated effort was started in CMS, aiming at improving the entire monitoring system by identifying its weaknesses and the new requirements from the stakeholders, rationalise and streamline existing components and drive future software development. This contribution gives a complete overview of the CMS monitoring system and a description of all the recent activities that have been started with the goal of providing a more integrated, modern and functional global monitoring system for computing operations.

Estimation of functional failure probability of passive systems based on adaptive importance sampling method

International Nuclear Information System (INIS)

Wang Baosheng; Wang Dongqing; Zhang Jianmin; Jiang Jing

2012-01-01

In order to estimate the functional failure probability of passive systems, an innovative adaptive importance sampling methodology is presented. In the proposed methodology, information of variables is extracted with some pre-sampling of points in the failure region. An important sampling density is then constructed from the sample distribution in the failure region. Taking the AP1000 passive residual heat removal system as an example, the uncertainties related to the model of a passive system and the numerical values of its input parameters are considered in this paper. And then the probability of functional failure is estimated with the combination of the response surface method and adaptive importance sampling method. The numerical results demonstrate the high computed efficiency and excellent computed accuracy of the methodology compared with traditional probability analysis methods. (authors)

The modelling of adaptive posture advisory system for decubitus prevention during air travel

NARCIS (Netherlands)

Tan, C.F.; Chen, W.; Verbunt, M.N.C.; Rauterberg, G.W.M.

2009-01-01

The design process of any technical system is based on well elaborated procedures, which leads step by step, from concept to the final product. For industrial product, such as adaptive advisory systems, a combination of multiple technology such as electronic and computer science is involved. There

Improving personality facet scores with multidimensional computer adaptive testing

DEFF Research Database (Denmark)

Makransky, Guido; Mortensen, Erik Lykke; Glas, Cees A W

2013-01-01

personality tests contain many highly correlated facets. This article investigates the possibility of increasing the precision of the NEO PI-R facet scores by scoring items with multidimensional item response theory and by efficiently administering and scoring items with multidimensional computer adaptive...

Using an adaptive expertise lens to understand the quality of teachers' classroom implementation of computer-supported complex systems curricula in high school science

Science.gov (United States)

Yoon, Susan A.; Koehler-Yom, Jessica; Anderson, Emma; Lin, Joyce; Klopfer, Eric

2015-05-01

Background: This exploratory study is part of a larger-scale research project aimed at building theoretical and practical knowledge of complex systems in students and teachers with the goal of improving high school biology learning through professional development and a classroom intervention. Purpose: We propose a model of adaptive expertise to better understand teachers' classroom practices as they attempt to navigate myriad variables in the implementation of biology units that include working with computer simulations, and learning about and teaching through complex systems ideas. Sample: Research participants were three high school biology teachers, two females and one male, ranging in teaching experience from six to 16 years. Their teaching contexts also ranged in student achievement from 14-47% advanced science proficiency. Design and methods: We used a holistic multiple case study methodology and collected data during the 2011-2012 school year. Data sources include classroom observations, teacher and student surveys, and interviews. Data analyses and trustworthiness measures were conducted through qualitative mining of data sources and triangulation of findings. Results: We illustrate the characteristics of adaptive expertise of more or less successful teaching and learning when implementing complex systems curricula. We also demonstrate differences between case study teachers in terms of particular variables associated with adaptive expertise. Conclusions: This research contributes to scholarship on practices and professional development needed to better support teachers to teach through a complex systems pedagogical and curricular approach.

  Indirect versus direct feedback in computer-based Prism Adaptation Therapy

DEFF Research Database (Denmark)

Wilms, Inge Linda; Rytter, Hana Malá

2010-01-01

  Prism Adaptation Therapy (PAT) is an intervention method in the treatment of the attention disorder neglect (Frassinetti, Angeli, Meneghello, Avanzi, & Ladavas, 2002; Rossetti, et al., 1998). The aim of this study was to investigate whether one session of PAT using a computer-attached touchscreen...... have direct implications for future implementations of computer-based methods of treatment of visuospatial disorders and computer-assisted rehabilitation in general....

DualTrust: A Trust Management Model for Swarm-Based Autonomic Computing Systems

Energy Technology Data Exchange (ETDEWEB)

Maiden, Wendy M. [Washington State Univ., Pullman, WA (United States)

2010-05-01

Trust management techniques must be adapted to the unique needs of the application architectures and problem domains to which they are applied. For autonomic computing systems that utilize mobile agents and ant colony algorithms for their sensor layer, certain characteristics of the mobile agent ant swarm -- their lightweight, ephemeral nature and indirect communication -- make this adaptation especially challenging. This thesis looks at the trust issues and opportunities in swarm-based autonomic computing systems and finds that by monitoring the trustworthiness of the autonomic managers rather than the swarming sensors, the trust management problem becomes much more scalable and still serves to protect the swarm. After analyzing the applicability of trust management research as it has been applied to architectures with similar characteristics, this thesis specifies the required characteristics for trust management mechanisms used to monitor the trustworthiness of entities in a swarm-based autonomic computing system and describes a trust model that meets these requirements.

FRIEND: a brain-monitoring agent for adaptive and assistive systems.

Science.gov (United States)

Morris, Alexis; Ulieru, Mihaela

2012-01-01

This paper presents an architectural design for adaptive-systems agents (FRIEND) that use brain state information to make more effective decisions on behalf of a user; measuring brain context versus situational demands. These systems could be useful for alerting users to cognitive workload levels or fatigue, and could attempt to compensate for higher cognitive activity by filtering noise information. In some cases such systems could also share control of devices, such as pulling over in an automated vehicle. These aim to assist people in everyday systems to perform tasks better and be more aware of internal states. Achieving a functioning system of this sort is a challenge, involving a unification of brain- computer-interfaces, human-computer-interaction, soft-computin deliberative multi-agent systems disciplines. Until recently, these were not able to be combined into a usable platform due largely to technological limitations (e.g., size, cost, and processing speed), insufficient research on extracting behavioral states from EEG signals, and lack of low-cost wireless sensing headsets. We aim to surpass these limitations and develop control architectures for making sense of brain state in applications by realizing an agent architecture for adaptive (human-aware) technology. In this paper we present an early, high-level design towards implementing a multi-purpose brain-monitoring agent system to improve user quality of life through the assistive applications of psycho-physiological monitoring, noise-filtering, and shared system control.

Adaptive automatic generation control with superconducting magnetic energy storage in power systems

International Nuclear Information System (INIS)

Tripathy, S.C.; Balasubramanian, R.; Nair, P.S.C.

1992-01-01

An improved automatic generation control (AGC) employing self-tuning adaptive control for both main AGC loop and superconducting magnetic energy storage (SMES) is presented in this paper. Computer simulations on a two-area interconnected power system show that the proposed adaptive control scheme is very effective in damping out oscillations caused by load disturbances and its performance is quite insensitive to controller gain parameter changes of SMES. A comprehensive comparative performance evaluation of control schemes using adaptive and non-adaptive controllers in the main AGC and in the SMES control loops is presented. The improvement in performance brought in by the adaptive scheme is particularly pronounced for load changes of random magnitude and duration. The proposed controller can be easily implemented using microprocessors

Techniques for grid manipulation and adaptation. [computational fluid dynamics

Science.gov (United States)

Choo, Yung K.; Eisemann, Peter R.; Lee, Ki D.

1992-01-01

Two approaches have been taken to provide systematic grid manipulation for improved grid quality. One is the control point form (CPF) of algebraic grid generation. It provides explicit control of the physical grid shape and grid spacing through the movement of the control points. It works well in the interactive computer graphics environment and hence can be a good candidate for integration with other emerging technologies. The other approach is grid adaptation using a numerical mapping between the physical space and a parametric space. Grid adaptation is achieved by modifying the mapping functions through the effects of grid control sources. The adaptation process can be repeated in a cyclic manner if satisfactory results are not achieved after a single application.

Adaptivity in Professional Printing Systems

NARCIS (Netherlands)

Verriet, J.H.; Basten, T; Hamberg, R.; Reckers, F.J.; Somers, L.

2013-01-01

There is a constant pressure on developers of embedded systems to simultaneously increase system functionality and to decrease development costs. Aviable way to obtain a better system performance with the same physical hardware is adaptivity: a system should be able to adapt itself to dynamically

Adaptive cyber-attack modeling system

Science.gov (United States)

Gonsalves, Paul G.; Dougherty, Edward T.

2006-05-01

The pervasiveness of software and networked information systems is evident across a broad spectrum of business and government sectors. Such reliance provides an ample opportunity not only for the nefarious exploits of lone wolf computer hackers, but for more systematic software attacks from organized entities. Much effort and focus has been placed on preventing and ameliorating network and OS attacks, a concomitant emphasis is required to address protection of mission critical software. Typical software protection technique and methodology evaluation and verification and validation (V&V) involves the use of a team of subject matter experts (SMEs) to mimic potential attackers or hackers. This manpower intensive, time-consuming, and potentially cost-prohibitive approach is not amenable to performing the necessary multiple non-subjective analyses required to support quantifying software protection levels. To facilitate the evaluation and V&V of software protection solutions, we have designed and developed a prototype adaptive cyber attack modeling system. Our approach integrates an off-line mechanism for rapid construction of Bayesian belief network (BN) attack models with an on-line model instantiation, adaptation and knowledge acquisition scheme. Off-line model construction is supported via a knowledge elicitation approach for identifying key domain requirements and a process for translating these requirements into a library of BN-based cyber-attack models. On-line attack modeling and knowledge acquisition is supported via BN evidence propagation and model parameter learning.

Farming System Evolution and Adaptive Capacity: Insights for Adaptation Support

Directory of Open Access Journals (Sweden)

Jami L. Dixon

2014-02-01

Full Text Available Studies of climate impacts on agriculture and adaptation often provide current or future assessments, ignoring the historical contexts farming systems are situated within. We investigate how historical trends have influenced farming system adaptive capacity in Uganda using data from household surveys, semi-structured interviews, focus-group discussions and observations. By comparing two farming systems, we note three major findings: (1 similar trends in farming system evolution have had differential impacts on the diversity of farming systems; (2 trends have contributed to the erosion of informal social and cultural institutions and an increasing dependence on formal institutions; and (3 trade-offs between components of adaptive capacity are made at the farm-scale, thus influencing farming system adaptive capacity. To identify the actual impacts of future climate change and variability, it is important to recognize the dynamic nature of adaptation. In practice, areas identified for further adaptation support include: shift away from one-size-fits-all approach the identification and integration of appropriate modern farming method; a greater focus on building inclusive formal and informal institutions; and a more nuanced understanding regarding the roles and decision-making processes of influential, but external, actors. More research is needed to understand farm-scale trade-offs and the resulting impacts across spatial and temporal scales.

ACCESS TO A COMPUTER SYSTEM. BETWEEN LEGAL PROVISIONS AND TECHNICAL REALITY

Directory of Open Access Journals (Sweden)

Maxim DOBRINOIU

2016-05-01

Full Text Available Nowadays, on a rise of cybersecurity incidents and a very complex IT&C environment, the national legal systems must adapt in order to properly address the new and modern forms of criminality in cyberspace. The illegal access to a computer system remains one of the most important cyber-related crimes due to its popularity but also from the perspective as being a door opened to computer data and sometimes a vehicle for other tech crimes. In the same time, the information society services slightly changed the IT paradigm and represent the new interface between users and systems. Is true that services rely on computer systems, but accessing services goes now beyond the simple accessing computer systems as commonly understood by most of the legislations. The article intends to explain other sides of the access related to computer systems and services, with the purpose to advance possible legal solutions to certain case scenarios.

Turbine system and adapter

Science.gov (United States)

Hogberg, Nicholas Alvin; Garcia-Crespo, Andres Jose

2017-05-30

A turbine system and adapter are disclosed. The adapter includes a turbine attachment portion having a first geometry arranged to receive a corresponding geometry of a wheelpost of a turbine rotor, and a bucket attachment portion having a second geometry arranged to receive a corresponding geometry of a root portion of a non-metallic turbine bucket. Another adapter includes a turbine attachment portion arranged to receive a plurality of wheelposts of a turbine rotor, and a bucket attachment portion arranged to receive a plurality of non-metallic turbine buckets having single dovetail configuration root portions. The turbine system includes a turbine rotor wheel configured to receive metal buckets, at least one adapter secured to at least one wheelpost on the turbine rotor wheel, and at least one non-metallic bucket secured to the at least one adapter.

Intelligent Adaptation and Personalization Techniques in Computer-Supported Collaborative Learning

CERN Document Server

Demetriadis, Stavros; Xhafa, Fatos

2012-01-01

Adaptation and personalization have been extensively studied in CSCL research community aiming to design intelligent systems that adaptively support eLearning processes and collaboration. Yet, with the fast development in Internet technologies, especially with the emergence of new data technologies and the mobile technologies, new opportunities and perspectives are opened for advanced adaptive and personalized systems. Adaptation and personalization are posing new research and development challenges to nowadays CSCL systems. In particular, adaptation should be focused in a multi-dimensional way (cognitive, technological, context-aware and personal). Moreover, it should address the particularities of both individual learners and group collaboration. As a consequence, the aim of this book is twofold. On the one hand, it discusses the latest advances and findings in the area of intelligent adaptive and personalized learning systems. On the other hand it analyzes the new implementation perspectives for intelligen...

Generic adaptation framework for unifying adaptive web-based systems

NARCIS (Netherlands)

Knutov, E.

2012-01-01

The Generic Adaptation Framework (GAF) research project first and foremost creates a common formal framework for describing current and future adaptive hypermedia (AHS) and adaptive webbased systems in general. It provides a commonly agreed upon taxonomy and a reference model that encompasses the

Comparison between iterative wavefront control algorithm and direct gradient wavefront control algorithm for adaptive optics system

International Nuclear Information System (INIS)

Cheng Sheng-Yi; Liu Wen-Jin; Chen Shan-Qiu; Dong Li-Zhi; Yang Ping; Xu Bing

2015-01-01

Among all kinds of wavefront control algorithms in adaptive optics systems, the direct gradient wavefront control algorithm is the most widespread and common method. This control algorithm obtains the actuator voltages directly from wavefront slopes through pre-measuring the relational matrix between deformable mirror actuators and Hartmann wavefront sensor with perfect real-time characteristic and stability. However, with increasing the number of sub-apertures in wavefront sensor and deformable mirror actuators of adaptive optics systems, the matrix operation in direct gradient algorithm takes too much time, which becomes a major factor influencing control effect of adaptive optics systems. In this paper we apply an iterative wavefront control algorithm to high-resolution adaptive optics systems, in which the voltages of each actuator are obtained through iteration arithmetic, which gains great advantage in calculation and storage. For AO system with thousands of actuators, the computational complexity estimate is about O(n 2 ) ∼ O(n 3 ) in direct gradient wavefront control algorithm, while the computational complexity estimate in iterative wavefront control algorithm is about O(n) ∼ (O(n) 3/2 ), in which n is the number of actuators of AO system. And the more the numbers of sub-apertures and deformable mirror actuators, the more significant advantage the iterative wavefront control algorithm exhibits. (paper)

“Future Directions”: m-government computer systems accessed via cloud computing – advantages and possible implementations

OpenAIRE

Daniela LIŢAN

2015-01-01

In recent years, the activities of companies and Public Administration had been automated and adapted to the current information system. Therefore, in this paper, I will present and exemplify the benefits of m-government computer systems development and implementation (which can be accessed from mobile devices and which are specific to the workflow of Public Administrations) starting from the “experience” of e-government systems implementation in the context of their access and usage through ...

Self-* and Adaptive Mechanisms for Large Scale Distributed Systems

Science.gov (United States)

Fragopoulou, P.; Mastroianni, C.; Montero, R.; Andrjezak, A.; Kondo, D.

Large-scale distributed computing systems and infrastructure, such as Grids, P2P systems and desktop Grid platforms, are decentralized, pervasive, and composed of a large number of autonomous entities. The complexity of these systems is such that human administration is nearly impossible and centralized or hierarchical control is highly inefficient. These systems need to run on highly dynamic environments, where content, network topologies and workloads are continuously changing. Moreover, they are characterized by the high degree of volatility of their components and the need to provide efficient service management and to handle efficiently large amounts of data. This paper describes some of the areas for which adaptation emerges as a key feature, namely, the management of computational Grids, the self-management of desktop Grid platforms and the monitoring and healing of complex applications. It also elaborates on the use of bio-inspired algorithms to achieve self-management. Related future trends and challenges are described.

Complex Adaptive Systems of Systems (CASOS) engineering environment.

Energy Technology Data Exchange (ETDEWEB)

Detry, Richard Joseph; Linebarger, John Michael; Finley, Patrick D.; Maffitt, S. Louise; Glass, Robert John, Jr.; Beyeler, Walter Eugene; Ames, Arlo Leroy

2012-02-01

Complex Adaptive Systems of Systems, or CASoS, are vastly complex physical-socio-technical systems which we must understand to design a secure future for the nation. The Phoenix initiative implements CASoS Engineering principles combining the bottom up Complex Systems and Complex Adaptive Systems view with the top down Systems Engineering and System-of-Systems view. CASoS Engineering theory and practice must be conducted together to develop a discipline that is grounded in reality, extends our understanding of how CASoS behave and allows us to better control the outcomes. The pull of applications (real world problems) is critical to this effort, as is the articulation of a CASoS Engineering Framework that grounds an engineering approach in the theory of complex adaptive systems of systems. Successful application of the CASoS Engineering Framework requires modeling, simulation and analysis (MS and A) capabilities and the cultivation of a CASoS Engineering Community of Practice through knowledge sharing and facilitation. The CASoS Engineering Environment, itself a complex adaptive system of systems, constitutes the two platforms that provide these capabilities.

Using TinyOS Components for the Design of an Adaptive Ubiquitous System

NARCIS (Netherlands)

Kaya, O.S.; Durmaz, O.; Dulman, S.O.; Gemesi, R.; Jansen, P.G.; Havinga, Paul J.M.

2005-01-01

This work is an initiative attempt toward component-based software engineering in ubiquitous computing systems. Software components cooperate in a distributed manner to meet a demand, and adapt their software bindings during run-time depending on the context information. There are two main research

Using TinyOS Components for the Design of an Adaptive Ubiquitous System

NARCIS (Netherlands)

Kaya, O.S.; Durmaz, O.; Dulman, S.O.; Gemesi, R.; Jansen, P.G.; Havinga, Paul J.M.

This work is an initiative attempt toward component-based software engineering in ubiquitous computing systems. Software components cooperate in a distributed manner to meet a demand, and adapt their software bindings during run-time depending on the context information. There are two main research

Risk-return relationship in a complex adaptive system.

Directory of Open Access Journals (Sweden)

Kunyu Song

Full Text Available For survival and development, autonomous agents in complex adaptive systems involving the human society must compete against or collaborate with others for sharing limited resources or wealth, by using different methods. One method is to invest, in order to obtain payoffs with risk. It is a common belief that investments with a positive risk-return relationship (namely, high risk high return and vice versa are dominant over those with a negative risk-return relationship (i.e., high risk low return and vice versa in the human society; the belief has a notable impact on daily investing activities of investors. Here we investigate the risk-return relationship in a model complex adaptive system, in order to study the effect of both market efficiency and closeness that exist in the human society and play an important role in helping to establish traditional finance/economics theories. We conduct a series of computer-aided human experiments, and also perform agent-based simulations and theoretical analysis to confirm the experimental observations and reveal the underlying mechanism. We report that investments with a negative risk-return relationship have dominance over those with a positive risk-return relationship instead in such a complex adaptive systems. We formulate the dynamical process for the system's evolution, which helps to discover the different role of identical and heterogeneous preferences. This work might be valuable not only to complexity science, but also to finance and economics, to management and social science, and to physics.

Risk-return relationship in a complex adaptive system.

Science.gov (United States)

Song, Kunyu; An, Kenan; Yang, Guang; Huang, Jiping

2012-01-01

For survival and development, autonomous agents in complex adaptive systems involving the human society must compete against or collaborate with others for sharing limited resources or wealth, by using different methods. One method is to invest, in order to obtain payoffs with risk. It is a common belief that investments with a positive risk-return relationship (namely, high risk high return and vice versa) are dominant over those with a negative risk-return relationship (i.e., high risk low return and vice versa) in the human society; the belief has a notable impact on daily investing activities of investors. Here we investigate the risk-return relationship in a model complex adaptive system, in order to study the effect of both market efficiency and closeness that exist in the human society and play an important role in helping to establish traditional finance/economics theories. We conduct a series of computer-aided human experiments, and also perform agent-based simulations and theoretical analysis to confirm the experimental observations and reveal the underlying mechanism. We report that investments with a negative risk-return relationship have dominance over those with a positive risk-return relationship instead in such a complex adaptive systems. We formulate the dynamical process for the system's evolution, which helps to discover the different role of identical and heterogeneous preferences. This work might be valuable not only to complexity science, but also to finance and economics, to management and social science, and to physics.

Oral and maxillofacial surgery with computer-assisted navigation system.

Science.gov (United States)

Kawachi, Homare; Kawachi, Yasuyuki; Ikeda, Chihaya; Takagi, Ryo; Katakura, Akira; Shibahara, Takahiko

2010-01-01

Intraoperative computer-assisted navigation has gained acceptance in maxillofacial surgery with applications in an increasing number of indications. We adapted a commercially available wireless passive marker system which allows calibration and tracking of virtually every instrument in maxillofacial surgery. Virtual computer-generated anatomical structures are displayed intraoperatively in a semi-immersive head-up display. Continuous observation of the operating field facilitated by computer assistance enables surgical navigation in accordance with the physician's preoperative plans. This case report documents the potential for augmented visualization concepts in surgical resection of tumors in the oral and maxillofacial region. We report a case of T3N2bM0 carcinoma of the maxillary gingival which was surgically resected with the assistance of the Stryker Navigation Cart System. This system was found to be useful in assisting preoperative planning and intraoperative monitoring.

Computer programming and computer systems

CERN Document Server

Hassitt, Anthony

1966-01-01

Computer Programming and Computer Systems imparts a "reading knowledge? of computer systems.This book describes the aspects of machine-language programming, monitor systems, computer hardware, and advanced programming that every thorough programmer should be acquainted with. This text discusses the automatic electronic digital computers, symbolic language, Reverse Polish Notation, and Fortran into assembly language. The routine for reading blocked tapes, dimension statements in subroutines, general-purpose input routine, and efficient use of memory are also elaborated.This publication is inten

Model-based design of adaptive embedded systems

CERN Document Server

Hamberg, Roelof; Reckers, Frans; Verriet, Jacques

2013-01-01

Today’s embedded systems have to operate in a wide variety of dynamically changing environmental circumstances. Adaptivity, the ability of a system to autonomously adapt itself, is a means to optimise a system’s behaviour to accommodate changes in its environment. It involves making in-product trade-offs between system qualities at system level. The main challenge in the development of adaptive systems is keeping control of the intrinsic complexity of such systems while working with multi-disciplinary teams to create different parts of the system. Model-Based Development of Adaptive Embedded Systems focuses on the development of adaptive embedded systems both from an architectural and methodological point of view. It describes architectural solution patterns for adaptive systems and state-of-the-art model-based methods and techniques to support adaptive system development. In particular, the book describes the outcome of the Octopus project, a cooperation of a multi-disciplinary team of academic and indus...

Challenges in Quantitative Abstractions for Collective Adaptive Systems

Directory of Open Access Journals (Sweden)

Mirco Tribastone

2016-07-01

Full Text Available Like with most large-scale systems, the evaluation of quantitative properties of collective adaptive systems is an important issue that crosscuts all its development stages, from design (in the case of engineered systems to runtime monitoring and control. Unfortunately it is a difficult problem to tackle in general, due to the typically high computational cost involved in the analysis. This calls for the development of appropriate quantitative abstraction techniques that preserve most of the system's dynamical behaviour using a more compact representation. This paper focuses on models based on ordinary differential equations and reviews recent results where abstraction is achieved by aggregation of variables, reflecting on the shortcomings in the state of the art and setting out challenges for future research.

TOWARD HIGHLY SECURE AND AUTONOMIC COMPUTING SYSTEMS: A HIERARCHICAL APPROACH

Energy Technology Data Exchange (ETDEWEB)

Lee, Hsien-Hsin S

2010-05-11

The overall objective of this research project is to develop novel architectural techniques as well as system software to achieve a highly secure and intrusion-tolerant computing system. Such system will be autonomous, self-adapting, introspective, with self-healing capability under the circumstances of improper operations, abnormal workloads, and malicious attacks. The scope of this research includes: (1) System-wide, unified introspection techniques for autonomic systems, (2) Secure information-flow microarchitecture, (3) Memory-centric security architecture, (4) Authentication control and its implication to security, (5) Digital right management, (5) Microarchitectural denial-of-service attacks on shared resources. During the period of the project, we developed several architectural techniques and system software for achieving a robust, secure, and reliable computing system toward our goal.

Molecular determinants of enzyme cold adaptation: comparative structural and computational studies of cold- and warm-adapted enzymes.

Science.gov (United States)

Papaleo, Elena; Tiberti, Matteo; Invernizzi, Gaetano; Pasi, Marco; Ranzani, Valeria

2011-11-01

The identification of molecular mechanisms underlying enzyme cold adaptation is a hot-topic both for fundamental research and industrial applications. In the present contribution, we review the last decades of structural computational investigations on cold-adapted enzymes in comparison to their warm-adapted counterparts. Comparative sequence and structural studies allow the definition of a multitude of adaptation strategies. Different enzymes carried out diverse mechanisms to adapt to low temperatures, so that a general theory for enzyme cold adaptation cannot be formulated. However, some common features can be traced in dynamic and flexibility properties of these enzymes, as well as in their intra- and inter-molecular interaction networks. Interestingly, the current data suggest that a family-centered point of view is necessary in the comparative analyses of cold- and warm-adapted enzymes. In fact, enzymes belonging to the same family or superfamily, thus sharing at least the three-dimensional fold and common features of the functional sites, have evolved similar structural and dynamic patterns to overcome the detrimental effects of low temperatures.

A Gaussian mixture model based adaptive classifier for fNIRS brain-computer interfaces and its testing via simulation

Science.gov (United States)

Li, Zheng; Jiang, Yi-han; Duan, Lian; Zhu, Chao-zhe

2017-08-01

Objective. Functional near infra-red spectroscopy (fNIRS) is a promising brain imaging technology for brain-computer interfaces (BCI). Future clinical uses of fNIRS will likely require operation over long time spans, during which neural activation patterns may change. However, current decoders for fNIRS signals are not designed to handle changing activation patterns. The objective of this study is to test via simulations a new adaptive decoder for fNIRS signals, the Gaussian mixture model adaptive classifier (GMMAC). Approach. GMMAC can simultaneously classify and track activation pattern changes without the need for ground-truth labels. This adaptive classifier uses computationally efficient variational Bayesian inference to label new data points and update mixture model parameters, using the previous model parameters as priors. We test GMMAC in simulations in which neural activation patterns change over time and compare to static decoders and unsupervised adaptive linear discriminant analysis classifiers. Main results. Our simulation experiments show GMMAC can accurately decode under time-varying activation patterns: shifts of activation region, expansions of activation region, and combined contractions and shifts of activation region. Furthermore, the experiments show the proposed method can track the changing shape of the activation region. Compared to prior work, GMMAC performed significantly better than the other unsupervised adaptive classifiers on a difficult activation pattern change simulation: 99% versus  brain-computer interfaces, including neurofeedback training systems, where operation over long time spans is required.

Moving finite elements: A continuously adaptive method for computational fluid dynamics

International Nuclear Information System (INIS)

Glasser, A.H.; Miller, K.; Carlson, N.

1991-01-01

Moving Finite Elements (MFE), a recently developed method for computational fluid dynamics, promises major advances in the ability of computers to model the complex behavior of liquids, gases, and plasmas. Applications of computational fluid dynamics occur in a wide range of scientifically and technologically important fields. Examples include meteorology, oceanography, global climate modeling, magnetic and inertial fusion energy research, semiconductor fabrication, biophysics, automobile and aircraft design, industrial fluid processing, chemical engineering, and combustion research. The improvements made possible by the new method could thus have substantial economic impact. Moving Finite Elements is a moving node adaptive grid method which has a tendency to pack the grid finely in regions where it is most needed at each time and to leave it coarse elsewhere. It does so in a manner which is simple and automatic, and does not require a large amount of human ingenuity to apply it to each particular problem. At the same time, it often allows the time step to be large enough to advance a moving shock by many shock thicknesses in a single time step, moving the grid smoothly with the solution and minimizing the number of time steps required for the whole problem. For 2D problems (two spatial variables) the grid is composed of irregularly shaped and irregularly connected triangles which are very flexible in their ability to adapt to the evolving solution. While other adaptive grid methods have been developed which share some of these desirable properties, this is the only method which combines them all. In many cases, the method can save orders of magnitude of computing time, equivalent to several generations of advancing computer hardware

Fast digital zooming system using directionally adaptive image interpolation and restoration.

Science.gov (United States)

Kang, Wonseok; Jeon, Jaehwan; Yu, Soohwan; Paik, Joonki

2014-01-01

This paper presents a fast digital zooming system for mobile consumer cameras using directionally adaptive image interpolation and restoration methods. The proposed interpolation algorithm performs edge refinement along the initially estimated edge orientation using directionally steerable filters. Either the directionally weighted linear or adaptive cubic-spline interpolation filter is then selectively used according to the refined edge orientation for removing jagged artifacts in the slanted edge region. A novel image restoration algorithm is also presented for removing blurring artifacts caused by the linear or cubic-spline interpolation using the directionally adaptive truncated constrained least squares (TCLS) filter. Both proposed steerable filter-based interpolation and the TCLS-based restoration filters have a finite impulse response (FIR) structure for real time processing in an image signal processing (ISP) chain. Experimental results show that the proposed digital zooming system provides high-quality magnified images with FIR filter-based fast computational structure.

Adaptation of Hybrid FSO/RF Communication System Using Puncturing Technique

Directory of Open Access Journals (Sweden)

M. N. Khan

2016-12-01

Full Text Available Spectrum of radio frequency (RF communications is limited and expensive to install new applications. Free space optical (FSO communication is a viable technology which offers enormous bandwidth, license free installation, inexpensive deployment and error prone links. The FSO links degrade significantly due to the varying atmospheric and weather conditions (fog, cloud, snow, haze and combination of these. We propose a hybrid FSO/RF communication system which adapts the varying nature of atmosphere and weather. For the adaption of varying atmosphere and weather scenarios, we develop a novel optimization algorithm. The proposed algorithm is based on the well-known puncturing technique. We provide an extrinsic information transfer (EXIT chart for the binary and quaternary mapping scheme for the proposed communication system. We simulate the proposed algorithm for the hybrid communication system and analyze the system performance. The proposed algorithm is computationally less expensive and provide better performance gains over varying atmosphere and weather conditions. The algorithm is suitable for fast speed applications.

Adaptive stimulus optimization for sensory systems neuroscience.

Science.gov (United States)

DiMattina, Christopher; Zhang, Kechen

2013-01-01

In this paper, we review several lines of recent work aimed at developing practical methods for adaptive on-line stimulus generation for sensory neurophysiology. We consider various experimental paradigms where on-line stimulus optimization is utilized, including the classical optimal stimulus paradigm where the goal of experiments is to identify a stimulus which maximizes neural responses, the iso-response paradigm which finds sets of stimuli giving rise to constant responses, and the system identification paradigm where the experimental goal is to estimate and possibly compare sensory processing models. We discuss various theoretical and practical aspects of adaptive firing rate optimization, including optimization with stimulus space constraints, firing rate adaptation, and possible network constraints on the optimal stimulus. We consider the problem of system identification, and show how accurate estimation of non-linear models can be highly dependent on the stimulus set used to probe the network. We suggest that optimizing stimuli for accurate model estimation may make it possible to successfully identify non-linear models which are otherwise intractable, and summarize several recent studies of this type. Finally, we present a two-stage stimulus design procedure which combines the dual goals of model estimation and model comparison and may be especially useful for system identification experiments where the appropriate model is unknown beforehand. We propose that fast, on-line stimulus optimization enabled by increasing computer power can make it practical to move sensory neuroscience away from a descriptive paradigm and toward a new paradigm of real-time model estimation and comparison.

Comparing computer adaptive and curriculum-based measures of math in progress monitoring.

Science.gov (United States)

Shapiro, Edward S; Dennis, Minyi Shih; Fu, Qiong

2015-12-01

The purpose of the study was to compare the use of a Computer Adaptive Test and Curriculum-Based Measurement in the assessment of mathematics. This study also investigated the degree to which slope or rate of change predicted student outcomes on the annual state assessment of mathematics above and beyond scores of single point screening assessments (i.e., the computer adaptive test or the CBM assessment just before the administration of the state assessment). Repeated measurement of mathematics once per month across a 7-month period using a Computer Adaptive Test (STAR-Math) and Curriculum-Based Measurement (CBM, AIMSweb Math Computation, AIMSweb Math Concepts/Applications) was collected for a maximum total of 250 third, fourth, and fifth grade students. Results showed STAR-Math in all 3 grades and AIMSweb Math Concepts/Applications in the third and fifth grades had primarily linear growth patterns in mathematics. AIMSweb Math Computation in all grades and AIMSweb Math Concepts/Applications in Grade 4 had decelerating positive trends. Predictive validity evidence showed the strongest relationships were between STAR-Math and outcomes for third and fourth grade students. The blockwise multiple regression by grade revealed that slopes accounted for only a very small proportion of additional variance above and beyond what was explained by the scores obtained on a single point of assessment just prior to the administration of the state assessment. (c) 2015 APA, all rights reserved).

Definition, modeling and simulation of a grid computing system for high throughput computing

CERN Document Server

Caron, E; Tsaregorodtsev, A Yu

2006-01-01

In this paper, we study and compare grid and global computing systems and outline the benefits of having an hybrid system called dirac. To evaluate the dirac scheduling for high throughput computing, a new model is presented and a simulator was developed for many clusters of heterogeneous nodes belonging to a local network. These clusters are assumed to be connected to each other through a global network and each cluster is managed via a local scheduler which is shared by many users. We validate our simulator by comparing the experimental and analytical results of a M/M/4 queuing system. Next, we do the comparison with a real batch system and we obtain an average error of 10.5% for the response time and 12% for the makespan. We conclude that the simulator is realistic and well describes the behaviour of a large-scale system. Thus we can study the scheduling of our system called dirac in a high throughput context. We justify our decentralized, adaptive and oppor! tunistic approach in comparison to a centralize...

Adaptive Fault Tolerance for Many-Core Based Space-Borne Computing

Science.gov (United States)

James, Mark; Springer, Paul; Zima, Hans

2010-01-01

This paper describes an approach to providing software fault tolerance for future deep-space robotic NASA missions, which will require a high degree of autonomy supported by an enhanced on-board computational capability. Such systems have become possible as a result of the emerging many-core technology, which is expected to offer 1024-core chips by 2015. We discuss the challenges and opportunities of this new technology, focusing on introspection-based adaptive fault tolerance that takes into account the specific requirements of applications, guided by a fault model. Introspection supports runtime monitoring of the program execution with the goal of identifying, locating, and analyzing errors. Fault tolerance assertions for the introspection system can be provided by the user, domain-specific knowledge, or via the results of static or dynamic program analysis. This work is part of an on-going project at the Jet Propulsion Laboratory in Pasadena, California.

Hard Real-Time Task Scheduling in Cloud Computing Using an Adaptive Genetic Algorithm

Directory of Open Access Journals (Sweden)

Amjad Mahmood

2017-04-01

Full Text Available In the Infrastructure-as-a-Service cloud computing model, virtualized computing resources in the form of virtual machines are provided over the Internet. A user can rent an arbitrary number of computing resources to meet their requirements, making cloud computing an attractive choice for executing real-time tasks. Economical task allocation and scheduling on a set of leased virtual machines is an important problem in the cloud computing environment. This paper proposes a greedy and a genetic algorithm with an adaptive selection of suitable crossover and mutation operations (named as AGA to allocate and schedule real-time tasks with precedence constraint on heterogamous virtual machines. A comprehensive simulation study has been done to evaluate the performance of the proposed algorithms in terms of their solution quality and efficiency. The simulation results show that AGA outperforms the greedy algorithm and non-adaptive genetic algorithm in terms of solution quality.

Adaptive scapula bone remodeling computational simulation: Relevance to regenerative medicine

International Nuclear Information System (INIS)

Sharma, Gulshan B.; Robertson, Douglas D.

2013-01-01

Shoulder arthroplasty success has been attributed to many factors including, bone quality, soft tissue balancing, surgeon experience, and implant design. Improved long-term success is primarily limited by glenoid implant loosening. Prosthesis design examines materials and shape and determines whether the design should withstand a lifetime of use. Finite element (FE) analyses have been extensively used to study stresses and strains produced in implants and bone. However, these static analyses only measure a moment in time and not the adaptive response to the altered environment produced by the therapeutic intervention. Computational analyses that integrate remodeling rules predict how bone will respond over time. Recent work has shown that subject-specific two- and three dimensional adaptive bone remodeling models are feasible and valid. Feasibility and validation were achieved computationally, simulating bone remodeling using an intact human scapula, initially resetting the scapular bone material properties to be uniform, numerically simulating sequential loading, and comparing the bone remodeling simulation results to the actual scapula’s material properties. Three-dimensional scapula FE bone model was created using volumetric computed tomography images. Muscle and joint load and boundary conditions were applied based on values reported in the literature. Internal bone remodeling was based on element strain-energy density. Initially, all bone elements were assigned a homogeneous density. All loads were applied for 10 iterations. After every iteration, each bone element’s remodeling stimulus was compared to its corresponding reference stimulus and its material properties modified. The simulation achieved convergence. At the end of the simulation the predicted and actual specimen bone apparent density were plotted and compared. Location of high and low predicted bone density was comparable to the actual specimen. High predicted bone density was greater than

Computerized adaptive testing item selection in computerized adaptive learning systems

NARCIS (Netherlands)

Eggen, Theodorus Johannes Hendrikus Maria; Eggen, T.J.H.M.; Veldkamp, B.P.

2012-01-01

Item selection methods traditionally developed for computerized adaptive testing (CAT) are explored for their usefulness in item-based computerized adaptive learning (CAL) systems. While in CAT Fisher information-based selection is optimal, for recovering learning populations in CAL systems item

Adaptive elimination of optical fiber transmission noise in fiber ocean bottom seismic system

Science.gov (United States)

Zhong, Qiuwen; Hu, Zhengliang; Cao, Chunyan; Dong, Hongsheng

2017-10-01

In this paper, a pressure and acceleration insensitive reference Interferometer is used to obtain laser and public noise introduced by transmission fiber and laser. By using direct subtraction and adaptive filtering, this paper attempts to eliminate and estimation the transmission noise of sensing probe. This paper compares the noise suppression effect of four methods, including the direct subtraction (DS), the least mean square error adaptive elimination (LMS), the normalized least mean square error adaptive elimination (NLMS) and the least square (RLS) adaptive filtering. The experimental results show that the noise reduction effect of RLS and NLMS are almost the same, better than LMS and DS, which can reach 8dB (@100Hz). But considering the workload, RLS is not conducive to the real-time operating system. When it comes to the same treatment effect, the practicability of NLMS is higher than RLS. The noise reduction effect of LMS is slightly worse than that of RLS and NLMS, about 6dB (@100Hz), but its computational complexity is small, which is beneficial to the real time system implementation. It can also be seen that the DS method has the least amount of computational complexity, but the noise suppression effect is worse than that of the adaptive filter due to the difference of the noise amplitude between the RI and the SI, only 4dB (@100Hz) can be reached. The adaptive filter can basically eliminate the influence of the transmission noise, and the simulation signal of the sensor is kept intact.

Computational adaptive optics for broadband interferometric tomography of tissues and cells

Science.gov (United States)

Adie, Steven G.; Mulligan, Jeffrey A.

2016-03-01

Adaptive optics (AO) can shape aberrated optical wavefronts to physically restore the constructive interference needed for high-resolution imaging. With access to the complex optical field, however, many functions of optical hardware can be achieved computationally, including focusing and the compensation of optical aberrations to restore the constructive interference required for diffraction-limited imaging performance. Holography, which employs interferometric detection of the complex optical field, was developed based on this connection between hardware and computational image formation, although this link has only recently been exploited for 3D tomographic imaging in scattering biological tissues. This talk will present the underlying imaging science behind computational image formation with optical coherence tomography (OCT) -- a beam-scanned version of broadband digital holography. Analogous to hardware AO (HAO), we demonstrate computational adaptive optics (CAO) and optimization of the computed pupil correction in 'sensorless mode' (Zernike polynomial corrections with feedback from image metrics) or with the use of 'guide-stars' in the sample. We discuss the concept of an 'isotomic volume' as the volumetric extension of the 'isoplanatic patch' introduced in astronomical AO. Recent CAO results and ongoing work is highlighted to point to the potential biomedical impact of computed broadband interferometric tomography. We also discuss the advantages and disadvantages of HAO vs. CAO for the effective shaping of optical wavefronts, and highlight opportunities for hybrid approaches that synergistically combine the unique advantages of hardware and computational methods for rapid volumetric tomography with cellular resolution.

Adaptive Time Stepping for Transient Network Flow Simulation in Rocket Propulsion Systems

Science.gov (United States)

Majumdar, Alok K.; Ravindran, S. S.

2017-01-01

Fluid and thermal transients found in rocket propulsion systems such as propellant feedline system is a complex process involving fast phases followed by slow phases. Therefore their time accurate computation requires use of short time step initially followed by the use of much larger time step. Yet there are instances that involve fast-slow-fast phases. In this paper, we present a feedback control based adaptive time stepping algorithm, and discuss its use in network flow simulation of fluid and thermal transients. The time step is automatically controlled during the simulation by monitoring changes in certain key variables and by feedback. In order to demonstrate the viability of time adaptivity for engineering problems, we applied it to simulate water hammer and cryogenic chill down in pipelines. Our comparison and validation demonstrate the accuracy and efficiency of this adaptive strategy.

Adaptive Remodeling of Achilles Tendon: A Multi-scale Computational Model.

Directory of Open Access Journals (Sweden)

Stuart R Young

2016-09-01

Full Text Available While it is known that musculotendon units adapt to their load environments, there is only a limited understanding of tendon adaptation in vivo. Here we develop a computational model of tendon remodeling based on the premise that mechanical damage and tenocyte-mediated tendon damage and repair processes modify the distribution of its collagen fiber lengths. We explain how these processes enable the tendon to geometrically adapt to its load conditions. Based on known biological processes, mechanical and strain-dependent proteolytic fiber damage are incorporated into our tendon model. Using a stochastic model of fiber repair, it is assumed that mechanically damaged fibers are repaired longer, whereas proteolytically damaged fibers are repaired shorter, relative to their pre-damage length. To study adaptation of tendon properties to applied load, our model musculotendon unit is a simplified three-component Hill-type model of the human Achilles-soleus unit. Our model results demonstrate that the geometric equilibrium state of the Achilles tendon can coincide with minimization of the total metabolic cost of muscle activation. The proposed tendon model independently predicts rates of collagen fiber turnover that are in general agreement with in vivo experimental measurements. While the computational model here only represents a first step in a new approach to understanding the complex process of tendon remodeling in vivo, given these findings, it appears likely that the proposed framework may itself provide a useful theoretical foundation for developing valuable qualitative and quantitative insights into tendon physiology and pathology.

Processing-Efficient Distributed Adaptive RLS Filtering for Computationally Constrained Platforms

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Noor M. Khan

2017-01-01

Full Text Available In this paper, a novel processing-efficient architecture of a group of inexpensive and computationally incapable small platforms is proposed for a parallely distributed adaptive signal processing (PDASP operation. The proposed architecture runs computationally expensive procedures like complex adaptive recursive least square (RLS algorithm cooperatively. The proposed PDASP architecture operates properly even if perfect time alignment among the participating platforms is not available. An RLS algorithm with the application of MIMO channel estimation is deployed on the proposed architecture. Complexity and processing time of the PDASP scheme with MIMO RLS algorithm are compared with sequentially operated MIMO RLS algorithm and liner Kalman filter. It is observed that PDASP scheme exhibits much lesser computational complexity parallely than the sequential MIMO RLS algorithm as well as Kalman filter. Moreover, the proposed architecture provides an improvement of 95.83% and 82.29% decreased processing time parallely compared to the sequentially operated Kalman filter and MIMO RLS algorithm for low doppler rate, respectively. Likewise, for high doppler rate, the proposed architecture entails an improvement of 94.12% and 77.28% decreased processing time compared to the Kalman and RLS algorithms, respectively.

Adaptive control of port-Hamiltonian systems

NARCIS (Netherlands)

Dirksz, D.A.; Scherpen, J.M.A.; Edelmayer, András

2010-01-01

In this paper an adaptive control scheme is presented for general port-Hamiltonian systems. Adaptive control is used to compensate for control errors that are caused by unknown or uncertain parameter values of a system. The adaptive control is also combined with canonical transformation theory for

FEATURES OF LOGISTIC SYSTEM ADAPTIVE MANAGEMENT

Directory of Open Access Journals (Sweden)

Natalya VOZNENKO

2015-08-01

Full Text Available The study presents literature survey on enterprise logistic system adaptive management place and structure in the general enterprise management system. The theoretical basics of logistic system functioning, levels of its management and its effectiveness had been investigated. The role of adaptive management and its types had been scrutinized. The necessity of creating company’s adaptive regulator such as its economic mechanism had been proved.

Evaluating the Appropriateness of a New Computer-Administered Measure of Adaptive Function for Children and Youth with Autism Spectrum Disorders

Science.gov (United States)

Coster, Wendy J.; Kramer, Jessica M.; Tian, Feng; Dooley, Meghan; Liljenquist, Kendra; Kao, Ying-Chia; Ni, Pengsheng

2016-01-01

The Pediatric Evaluation of Disability Inventory-Computer Adaptive Test is an alternative method for describing the adaptive function of children and youth with disabilities using a computer-administered assessment. This study evaluated the performance of the Pediatric Evaluation of Disability Inventory-Computer Adaptive Test with a national…

Computing Preferred Extensions for Argumentation Systems with Sets of Attacking

DEFF Research Database (Denmark)

Nielsen, Søren Holbech; Parsons, Simon

2006-01-01

The hitherto most abstract, and hence general, argumentation system, is the one described by Dung in a paper from 1995. This framework does not allow for joint attacks on arguments, but in a recent paper we adapted it to support such attacks, and proved that this adapted framework enjoyed the same...... formal properties as that of Dung. One problem posed by Dung's original framework, which was neglected for some time, is how to compute preferred extensions of the argumentation systems. However, in 2001, in a paper by Doutre and Mengin, a procedure was given for enumerating preferred extensions...... for these systems. In this paper we propose a method for enumerating preferred extensions of the potentially more complex systems, where joint attacks are allowed. The method is inspired by the one given by Doutre and Mengin....

Adaptation in CRISPR-Cas Systems.

Science.gov (United States)

Sternberg, Samuel H; Richter, Hagen; Charpentier, Emmanuelle; Qimron, Udi

2016-03-17

Clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated (Cas) proteins constitute an adaptive immune system in prokaryotes. The system preserves memories of prior infections by integrating short segments of foreign DNA, termed spacers, into the CRISPR array in a process termed adaptation. During the past 3 years, significant progress has been made on the genetic requirements and molecular mechanisms of adaptation. Here we review these recent advances, with a focus on the experimental approaches that have been developed, the insights they generated, and a proposed mechanism for self- versus non-self-discrimination during the process of spacer selection. We further describe the regulation of adaptation and the protein players involved in this fascinating process that allows bacteria and archaea to harbor adaptive immunity. Copyright © 2016 Elsevier Inc. All rights reserved.

Resource-adaptive cognitive processes

CERN Document Server

Crocker, Matthew W

2010-01-01

This book investigates the adaptation of cognitive processes to limited resources. The central topics of this book are heuristics considered as results of the adaptation to resource limitations, through natural evolution in the case of humans, or through artificial construction in the case of computational systems; the construction and analysis of resource control in cognitive processes; and an analysis of resource-adaptivity within the paradigm of concurrent computation. The editors integrated the results of a collaborative 5-year research project that involved over 50 scientists. After a mot

Static security-based available transfer capability using adaptive neuro fuzzy inference system

Energy Technology Data Exchange (ETDEWEB)

Venkaiah, C.; Vinod Kumar, D.M.

2010-07-01

In a deregulated power system, power transactions between a seller and a buyer can only be scheduled when there is sufficient available transfer capability (ATC). Internet-based, open access same-time information systems (OASIS) provide market participants with ATC information that is continuously updated in real time. Static security-based ATC can be computed for the base case system as well as for the critical line outages of the system. Since critical line outages are based on static security analysis, the computation of static security based ATC using conventional methods is both tedious and time consuming. In this study, static security-based ATC was computed for real-time applications using 3 artificial intelligent methods notably the back propagation algorithm (BPA), the radial basis function (RBF) neural network, and the adaptive neuro fuzzy inference system (ANFIS). An IEEE 24-bus reliability test system (RTS) and 75-bus practical system were used to test these 3 different intelligent methods. The results were compared with the conventional full alternating current (AC) load flow method for different transactions.

Static security-based available transfer capability using adaptive neuro fuzzy inference system

International Nuclear Information System (INIS)

Venkaiah, C.; Vinod Kumar, D.M.

2010-01-01

In a deregulated power system, power transactions between a seller and a buyer can only be scheduled when there is sufficient available transfer capability (ATC). Internet-based, open access same-time information systems (OASIS) provide market participants with ATC information that is continuously updated in real time. Static security-based ATC can be computed for the base case system as well as for the critical line outages of the system. Since critical line outages are based on static security analysis, the computation of static security based ATC using conventional methods is both tedious and time consuming. In this study, static security-based ATC was computed for real-time applications using 3 artificial intelligent methods notably the back propagation algorithm (BPA), the radial basis function (RBF) neural network, and the adaptive neuro fuzzy inference system (ANFIS). An IEEE 24-bus reliability test system (RTS) and 75-bus practical system were used to test these 3 different intelligent methods. The results were compared with the conventional full alternating current (AC) load flow method for different transactions.

Efficient method for computing the electronic transport properties of a multiterminal system

Science.gov (United States)

Lima, Leandro R. F.; Dusko, Amintor; Lewenkopf, Caio

2018-04-01

We present a multiprobe recursive Green's function method to compute the transport properties of mesoscopic systems using the Landauer-Büttiker approach. By introducing an adaptive partition scheme, we map the multiprobe problem into the standard two-probe recursive Green's function method. We apply the method to compute the longitudinal and Hall resistances of a disordered graphene sample, a system of current interest. We show that the performance and accuracy of our method compares very well with other state-of-the-art schemes.

Genetic Algorithms for Case Adaptation

Energy Technology Data Exchange (ETDEWEB)

Salem, A M [Computer Science Dept, Faculty of Computer and Information Sciences, Ain Shams University, Cairo (Egypt); Mohamed, A H [Solid State Dept., (NCRRT), Cairo (Egypt)

2008-07-01

Case based reasoning (CBR) paradigm has been widely used to provide computer support for recalling and adapting known cases to novel situations. Case adaptation algorithms generally rely on knowledge based and heuristics in order to change the past solutions to solve new problems. However, case adaptation has always been a difficult process to engineers within (CBR) cycle. Its difficulties can be referred to its domain dependency; and computational cost. In an effort to solve this problem, this research explores a general-purpose method that applying a genetic algorithm (GA) to CBR adaptation. Therefore, it can decrease the computational complexity of the search space in the problems having a great dependency on their domain knowledge. The proposed model can be used to perform a variety of design tasks on a broad set of application domains. However, it has been implemented for the tablet formulation as a domain of application. The proposed system has improved the performance of the CBR design systems.

Genetic Algorithms for Case Adaptation

International Nuclear Information System (INIS)

Salem, A.M.; Mohamed, A.H.

2008-01-01

Case based reasoning (CBR) paradigm has been widely used to provide computer support for recalling and adapting known cases to novel situations. Case adaptation algorithms generally rely on knowledge based and heuristics in order to change the past solutions to solve new problems. However, case adaptation has always been a difficult process to engineers within (CBR) cycle. Its difficulties can be referred to its domain dependency; and computational cost. In an effort to solve this problem, this research explores a general-purpose method that applying a genetic algorithm (GA) to CBR adaptation. Therefore, it can decrease the computational complexity of the search space in the problems having a great dependency on their domain knowledge. The proposed model can be used to perform a variety of design tasks on a broad set of application domains. However, it has been implemented for the tablet formulation as a domain of application. The proposed system has improved the performance of the CBR design systems

Application of computational intelligence techniques for load shedding in power systems: A review

International Nuclear Information System (INIS)

Laghari, J.A.; Mokhlis, H.; Bakar, A.H.A.; Mohamad, Hasmaini

2013-01-01

Highlights: • The power system blackout history of last two decades is presented. • Conventional load shedding techniques, their types and limitations are presented. • Applications of intelligent techniques in load shedding are presented. • Intelligent techniques include ANN, fuzzy logic, ANFIS, genetic algorithm and PSO. • The discussion and comparison between these techniques are provided. - Abstract: Recent blackouts around the world question the reliability of conventional and adaptive load shedding techniques in avoiding such power outages. To address this issue, reliable techniques are required to provide fast and accurate load shedding to prevent collapse in the power system. Computational intelligence techniques, due to their robustness and flexibility in dealing with complex non-linear systems, could be an option in addressing this problem. Computational intelligence includes techniques like artificial neural networks, genetic algorithms, fuzzy logic control, adaptive neuro-fuzzy inference system, and particle swarm optimization. Research in these techniques is being undertaken in order to discover means for more efficient and reliable load shedding. This paper provides an overview of these techniques as applied to load shedding in a power system. This paper also compares the advantages of computational intelligence techniques over conventional load shedding techniques. Finally, this paper discusses the limitation of computational intelligence techniques, which restricts their usage in load shedding in real time

Reducing adapter synthesis to controller synthesis

NARCIS (Netherlands)

Gierds, C.; Mooij, A.J.; Wolf, K.

2012-01-01

Service-oriented computing aims to create complex systems by composing less-complex systems, called services. Since services can be developed independently, the integration of services requires an adaptation mechanism for bridging any incompatibilities. Behavioral adapters aim to adjust the

Computer Adaptive Multistage Testing: Practical Issues, Challenges and Principles

Directory of Open Access Journals (Sweden)

Halil Ibrahim SARI

2016-12-01

Full Text Available The purpose of many test in the educational and psychological measurement is to measure test takers’ latent trait scores from responses given to a set of items. Over the years, this has been done by traditional methods (paper and pencil tests. However, compared to other test administration models (e.g., adaptive testing, traditional methods are extensively criticized in terms of producing low measurement accuracy and long test length. Adaptive testing has been proposed to overcome these problems. There are two popular adaptive testing approaches. These are computerized adaptive testing (CAT and computer adaptive multistage testing (ca-MST. The former is a well-known approach that has been predominantly used in this field. We believe that researchers and practitioners are fairly familiar with many aspects of CAT because it has more than a hundred years of history. However, the same thing is not true for the latter one. Since ca-MST is relatively new, many researchers are not familiar with features of it. The purpose of this study is to closely examine the characteristics of ca-MST, including its working principle, the adaptation procedure called the routing method, test assembly, and scoring, and provide an overview to researchers, with the aim of drawing researchers’ attention to ca-MST and encouraging them to contribute to the research in this area. The books, software and future work for ca-MST are also discussed.

Fault-tolerant design of adaptive digital control systems for power plant components

International Nuclear Information System (INIS)

Parlos, A.G.; Menon, S.K.

1992-01-01

An adaptive controller has been designed for the water level of a Westinghouse type U-tube steam generator, and its operation has been demonstrated in the entire power range via computer simulations. The proposed design exhibits improved performance, at low operating powers, a,s compared to existing controller types. The continuous-time controller design is performed systematically via the Linear Quadratic Gaussian/Loop Transfer Recovery method, followed by gain adaptation allowing controller operation in the entire power range. Digital implementation of the controller is accomplished by a digital redesign which results in matching the digital and continuous-time system and controller states. It is only at this stage of the control system design process that issues such as microprocessor induced quantization effects are taken into account. The use of computer-aided-design software greatly expedites the design cycle, allowing the designer to maximize the controller stability robustness to uncertainties via numerous iterations. This inherent controller robustness can be exploited to tolerate incipient plant faults, such as deteriorating U-tube heat transfer properties, without significant loss of controller performance

Self-Adaptive Systems for Machine Intelligence

CERN Document Server

He, Haibo

2011-01-01

This book will advance the understanding and application of self-adaptive intelligent systems; therefore it will potentially benefit the long-term goal of replicating certain levels of brain-like intelligence in complex and networked engineering systems. It will provide new approaches for adaptive systems within uncertain environments. This will provide an opportunity to evaluate the strengths and weaknesses of the current state-of-the-art of knowledge, give rise to new research directions, and educate future professionals in this domain. Self-adaptive intelligent systems have wide application

An adaptive proper orthogonal decomposition method for model order reduction of multi-disc rotor system

Science.gov (United States)

Jin, Yulin; Lu, Kuan; Hou, Lei; Chen, Yushu

2017-12-01

The proper orthogonal decomposition (POD) method is a main and efficient tool for order reduction of high-dimensional complex systems in many research fields. However, the robustness problem of this method is always unsolved, although there are some modified POD methods which were proposed to solve this problem. In this paper, a new adaptive POD method called the interpolation Grassmann manifold (IGM) method is proposed to address the weakness of local property of the interpolation tangent-space of Grassmann manifold (ITGM) method in a wider parametric region. This method is demonstrated here by a nonlinear rotor system of 33-degrees of freedom (DOFs) with a pair of liquid-film bearings and a pedestal looseness fault. The motion region of the rotor system is divided into two parts: simple motion region and complex motion region. The adaptive POD method is compared with the ITGM method for the large and small spans of parameter in the two parametric regions to present the advantage of this method and disadvantage of the ITGM method. The comparisons of the responses are applied to verify the accuracy and robustness of the adaptive POD method, as well as the computational efficiency is also analyzed. As a result, the new adaptive POD method has a strong robustness and high computational efficiency and accuracy in a wide scope of parameter.

Computer performance evaluation of FACOM 230-75 computer system, (2)

International Nuclear Information System (INIS)

Fujii, Minoru; Asai, Kiyoshi

1980-08-01

In this report are described computer performance evaluations for FACOM230-75 computers in JAERI. The evaluations are performed on following items: (1) Cost/benefit analysis of timesharing terminals, (2) Analysis of the response time of timesharing terminals, (3) Analysis of throughout time for batch job processing, (4) Estimation of current potential demands for computer time, (5) Determination of appropriate number of card readers and line printers. These evaluations are done mainly from the standpoint of cost reduction of computing facilities. The techniques adapted are very practical ones. This report will be useful for those people who are concerned with the management of computing installation. (author)

Robustness of critical points in a complex adaptive system: Effects of hedge behavior

Science.gov (United States)

Liang, Yuan; Huang, Ji-Ping

2013-08-01

In our recent papers, we have identified a class of phase transitions in the market-directed resource-allocation game, and found that there exists a critical point at which the phase transitions occur. The critical point is given by a certain resource ratio. Here, by performing computer simulations and theoretical analysis, we report that the critical point is robust against various kinds of human hedge behavior where the numbers of herds and contrarians can be varied widely. This means that the critical point can be independent of the total number of participants composed of normal agents, herds and contrarians, under some conditions. This finding means that the critical points we identified in this complex adaptive system (with adaptive agents) may also be an intensive quantity, similar to those revealed in traditional physical systems (with non-adaptive units).

A Fast Adaptive Receive Antenna Selection Method in MIMO System

Directory of Open Access Journals (Sweden)

Chaowei Wang

2013-01-01

Full Text Available Antenna selection has been regarded as an effective method to acquire the diversity benefits of multiple antennas while potentially reduce hardware costs. This paper focuses on receive antenna selection. According to the proportion between the numbers of total receive antennas and selected antennas and the influence of each antenna on system capacity, we propose a fast adaptive antenna selection algorithm for wireless multiple-input multiple-output (MIMO systems. Mathematical analysis and numerical results show that our algorithm significantly reduces the computational complexity and memory requirement and achieves considerable system capacity gain compared with the optimal selection technique in the same time.

Adaptive hybrid brain-computer interaction: ask a trainer for assistance!

Science.gov (United States)

Müller-Putz, Gernot R; Steyrl, David; Faller, Josef

2014-01-01

In applying mental imagery brain-computer interfaces (BCIs) to end users, training is a key part for novice users to get control. In general learning situations, it is an established concept that a trainer assists a trainee to improve his/her aptitude in certain skills. In this work, we want to evaluate whether we can apply this concept in the context of event-related desynchronization (ERD) based, adaptive, hybrid BCIs. Hence, in a first session we merged the features of a high aptitude BCI user, a trainer, and a novice user, the trainee, in a closed-loop BCI feedback task and automatically adapted the classifier over time. In a second session the trainees operated the system unassisted. Twelve healthy participants ran through this protocol. Along with the trainer, the trainees achieved a very high overall peak accuracy of 95.3 %. In the second session, where users operated the BCI unassisted, they still achieved a high overall peak accuracy of 83.6%. Ten of twelve first time BCI users successfully achieved significantly better than chance accuracy. Concluding, we can say that this trainer-trainee approach is very promising. Future research should investigate, whether this approach is superior to conventional training approaches. This trainer-trainee concept could have potential for future application of BCIs to end users.

An Adaptive and Integrated Low-Power Framework for Multicore Mobile Computing

Directory of Open Access Journals (Sweden)

Jongmoo Choi

2017-01-01

Full Text Available Employing multicore in mobile computing such as smartphone and IoT (Internet of Things device is a double-edged sword. It provides ample computing capabilities required in recent intelligent mobile services including voice recognition, image processing, big data analysis, and deep learning. However, it requires a great deal of power consumption, which causes creating a thermal hot spot and putting pressure on the energy resource in a mobile device. In this paper, we propose a novel framework that integrates two well-known low-power techniques, DPM (Dynamic Power Management and DVFS (Dynamic Voltage and Frequency Scaling for energy efficiency in multicore mobile systems. The key feature of the proposed framework is adaptability. By monitoring the online resource usage such as CPU utilization and power consumption, the framework can orchestrate diverse DPM and DVFS policies according to workload characteristics. Real implementation based experiments using three mobile devices have shown that it can reduce the power consumption ranging from 22% to 79%, while affecting negligibly the performance of workloads.

Adaptable structural synthesis using advanced analysis and optimization coupled by a computer operating system

Science.gov (United States)

Sobieszczanski-Sobieski, J.; Bhat, R. B.

1979-01-01

A finite element program is linked with a general purpose optimization program in a 'programing system' which includes user supplied codes that contain problem dependent formulations of the design variables, objective function and constraints. The result is a system adaptable to a wide spectrum of structural optimization problems. In a sample of numerical examples, the design variables are the cross-sectional dimensions and the parameters of overall shape geometry, constraints are applied to stresses, displacements, buckling and vibration characteristics, and structural mass is the objective function. Thin-walled, built-up structures and frameworks are included in the sample. Details of the system organization and characteristics of the component programs are given.

Diagnosis Penyakit Jantung Menggunakan Adaptive Neuro-Fuzzy Inference System (ANFIS

Directory of Open Access Journals (Sweden)

Khadijah Fahmi Hayati Holle

2016-09-01

Full Text Available The number of uncertain risk factor in heart disease makes experts difficult to diagnose its disease. Computer technology in the health field is mostly used. In this paper, we implement a system to diagnose heart disease. The used method is Adaptive neuro-fuzzy inference system which combine the advantage of fuzzy and neural network. The used data is UCI Cleveland data that have 13 attributes as inputs. Output system diagnosis compared with observational data for evaluation. System performance tested by calculating accuracy. Tests were also conducted on the variation of the learning rate, iteration, minimum error, and the use of membership functions. Accuracy obtained from test is 65,657% where using membership function Beta.

Quantitative adaptation analytics for assessing dynamic systems of systems: LDRD Final Report

Energy Technology Data Exchange (ETDEWEB)

Gauthier, John H. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). System Readiness & Sustainment Technologies (6133, M/S 1188); Miner, Nadine E. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Military & Energy Systems Analysis (6114, M/S 1188); Wilson, Michael L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Resilience and Regulatory Effects (6921, M/S 1138); Le, Hai D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). System Readiness & Sustainment Technologies (6133, M/S 1188); Kao, Gio K. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Networked System Survivability & Assurance (5629, M/S 0671); Melander, Darryl J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Software Systems R& D (9525, M/S 1188); Longsine, Dennis Earl [Sandia National Laboratories, Unknown, Unknown; Vander Meer, Jr., Robert C. [SAIC, Inc., Albuquerque, NM (United States)

2015-01-01

Our society is increasingly reliant on systems and interoperating collections of systems, known as systems of systems (SoS). These SoS are often subject to changing missions (e.g., nation- building, arms-control treaties), threats (e.g., asymmetric warfare, terrorism), natural environments (e.g., climate, weather, natural disasters) and budgets. How well can SoS adapt to these types of dynamic conditions? This report details the results of a three year Laboratory Directed Research and Development (LDRD) project aimed at developing metrics and methodologies for quantifying the adaptability of systems and SoS. Work products include: derivation of a set of adaptability metrics, a method for combining the metrics into a system of systems adaptability index (SoSAI) used to compare adaptability of SoS designs, development of a prototype dynamic SoS (proto-dSoS) simulation environment which provides the ability to investigate the validity of the adaptability metric set, and two test cases that evaluate the usefulness of a subset of the adaptability metrics and SoSAI for distinguishing good from poor adaptability in a SoS. Intellectual property results include three patents pending: A Method For Quantifying Relative System Adaptability, Method for Evaluating System Performance, and A Method for Determining Systems Re-Tasking.

Reconciling White-Box and Black-Box Perspectives on Behavioral Self-adaptation

DEFF Research Database (Denmark)

Bruni, Roberto; Corradini, Andrea; Gadducci, Fabio

2015-01-01

This paper proposes to reconcile two perspectives on behavioral adaptation commonly taken at different stages of the engineering of autonomic computing systems. Requirements engineering activities often take a black-box perspective: A system is considered to be adaptive with respect to an environ......This paper proposes to reconcile two perspectives on behavioral adaptation commonly taken at different stages of the engineering of autonomic computing systems. Requirements engineering activities often take a black-box perspective: A system is considered to be adaptive with respect...... to an environment whenever the system is able to satisfy its goals irrespectively of the environment perturbations. Modeling and programming engineering activities often take a white-box perspective: A system is equipped with suitable adaptation mechanisms and its behavior is classified as adaptive depending...

Environmentally-adapted local energy systems

Energy Technology Data Exchange (ETDEWEB)

Moe, N; Oefverholm, E [NUTEK, Stockholm (Sweden); Andersson, Owe [EKAN Gruppen (Sweden); Froste, H [Swedish Environmental Protection Agency, Stockholm (Sweden)

1997-10-01

Energy companies, municipalities, property companies, firms of consultants, environmental groups and individuals are examples of players working locally to shape environmentally adapted energy systems. These players have needed information making them better able to make decisions on cost-efficient, environmentally-adapted energy systems. This book answers many of the questions they have put. The volume is mainly based on Swedish handbooks produced by the Swedish National Board for Industrial and Technical Development, NUTEK, together with the Swedish Environmental Protection Agency. These handbooks have been used in conjunction with municipal energy planning, local Agenda 21 work, to provide a basis for deciding on concrete local energy systems. The contents in brief: -The book throws new light on the concept of energy efficiency; -A section on the environment compares how air-polluting emissions vary with different methods of energy production; -A section contains more than 40 ideas for measures which can be profitable, reduce energy consumption and the impact on the environment all at the same time; -The book gives concrete examples of new, alternative and environmentally-adapted local energy systems. More efficient use of energy is included as a possible change of energy system; -The greatest emphasis is laid upon alternative energy systems for heating. It may be heating in a house, block of flats, office building or school; -Finally, there are examples of environmentally-adapted local energy planning.

A vector-product information retrieval system adapted to heterogeneous, distributed computing environments

Science.gov (United States)

Rorvig, Mark E.

1991-01-01

Vector-product information retrieval (IR) systems produce retrieval results superior to all other searching methods but presently have no commercial implementations beyond the personal computer environment. The NASA Electronic Library Systems (NELS) provides a ranked list of the most likely relevant objects in collections in response to a natural language query. Additionally, the system is constructed using standards and tools (Unix, X-Windows, Notif, and TCP/IP) that permit its operation in organizations that possess many different hosts, workstations, and platforms. There are no known commercial equivalents to this product at this time. The product has applications in all corporate management environments, particularly those that are information intensive, such as finance, manufacturing, biotechnology, and research and development.

Comparison between iterative wavefront control algorithm and direct gradient wavefront control algorithm for adaptive optics system

Science.gov (United States)

Cheng, Sheng-Yi; Liu, Wen-Jin; Chen, Shan-Qiu; Dong, Li-Zhi; Yang, Ping; Xu, Bing

2015-08-01

Among all kinds of wavefront control algorithms in adaptive optics systems, the direct gradient wavefront control algorithm is the most widespread and common method. This control algorithm obtains the actuator voltages directly from wavefront slopes through pre-measuring the relational matrix between deformable mirror actuators and Hartmann wavefront sensor with perfect real-time characteristic and stability. However, with increasing the number of sub-apertures in wavefront sensor and deformable mirror actuators of adaptive optics systems, the matrix operation in direct gradient algorithm takes too much time, which becomes a major factor influencing control effect of adaptive optics systems. In this paper we apply an iterative wavefront control algorithm to high-resolution adaptive optics systems, in which the voltages of each actuator are obtained through iteration arithmetic, which gains great advantage in calculation and storage. For AO system with thousands of actuators, the computational complexity estimate is about O(n2) ˜ O(n3) in direct gradient wavefront control algorithm, while the computational complexity estimate in iterative wavefront control algorithm is about O(n) ˜ (O(n)3/2), in which n is the number of actuators of AO system. And the more the numbers of sub-apertures and deformable mirror actuators, the more significant advantage the iterative wavefront control algorithm exhibits. Project supported by the National Key Scientific and Research Equipment Development Project of China (Grant No. ZDYZ2013-2), the National Natural Science Foundation of China (Grant No. 11173008), and the Sichuan Provincial Outstanding Youth Academic Technology Leaders Program, China (Grant No. 2012JQ0012).

A computer simulation of an adaptive noise canceler with a single input

Science.gov (United States)

Albert, Stuart D.

1991-06-01

A description of an adaptive noise canceler using Widrows' LMS algorithm is presented. A computer simulation of canceler performance (adaptive convergence time and frequency transfer function) was written for use as a design tool. The simulations, assumptions, and input parameters are described in detail. The simulation is used in a design example to predict the performance of an adaptive noise canceler in the simultaneous presence of both strong and weak narrow-band signals (a cosited frequency hopping radio scenario). On the basis of the simulation results, it is concluded that the simulation is suitable for use as an adaptive noise canceler design tool; i.e., it can be used to evaluate the effect of design parameter changes on canceler performance.

Online adaptive optimal control for continuous-time nonlinear systems with completely unknown dynamics

Science.gov (United States)

Lv, Yongfeng; Na, Jing; Yang, Qinmin; Wu, Xing; Guo, Yu

2016-01-01

An online adaptive optimal control is proposed for continuous-time nonlinear systems with completely unknown dynamics, which is achieved by developing a novel identifier-critic-based approximate dynamic programming algorithm with a dual neural network (NN) approximation structure. First, an adaptive NN identifier is designed to obviate the requirement of complete knowledge of system dynamics, and a critic NN is employed to approximate the optimal value function. Then, the optimal control law is computed based on the information from the identifier NN and the critic NN, so that the actor NN is not needed. In particular, a novel adaptive law design method with the parameter estimation error is proposed to online update the weights of both identifier NN and critic NN simultaneously, which converge to small neighbourhoods around their ideal values. The closed-loop system stability and the convergence to small vicinity around the optimal solution are all proved by means of the Lyapunov theory. The proposed adaptation algorithm is also improved to achieve finite-time convergence of the NN weights. Finally, simulation results are provided to exemplify the efficacy of the proposed methods.

Software Quality Measurement for Distributed Systems. Volume 3. Distributed Computing Systems: Impact on Software Quality.

Science.gov (United States)

1983-07-01

Distributed Computing Systems impact DrnwrR - aehR on Sotwar Quaity. PERFORMING 010. REPORT NUMBER 7. AUTNOW) S. CONTRACT OR GRANT "UMBER(*)IS ThomasY...C31 Application", "Space Systems Network", "Need for Distributed Database Management", and "Adaptive Routing". This is discussed in the last para ...data reduction, buffering, encryption, and error detection and correction functions. Examples of such data streams include imagery data, video

New challenges in grid generation and adaptivity for scientific computing

CERN Document Server

Formaggia, Luca

2015-01-01

This volume collects selected contributions from the “Fourth Tetrahedron Workshop on Grid Generation for Numerical Computations”, which was held in Verbania, Italy in July 2013. The previous editions of this Workshop were hosted by the Weierstrass Institute in Berlin (2005), by INRIA Rocquencourt in Paris (2007), and by Swansea University (2010). This book covers different, though related, aspects of the field: the generation of quality grids for complex three-dimensional geometries; parallel mesh generation algorithms; mesh adaptation, including both theoretical and implementation aspects; grid generation and adaptation on surfaces – all with an interesting mix of numerical analysis, computer science and strongly application-oriented problems.

ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM FOR END MILLING

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ANGELOS P. MARKOPOULOS

2016-09-01

Full Text Available Soft computing is commonly used as a modelling method in various technological areas. Methods such as Artificial Neural Networks and Fuzzy Logic have found application in manufacturing technology as well. NeuroFuzzy systems, aimed to combine the benefits of both the aforementioned Artificial Intelligence methods, are a subject of research lately as have proven to be superior compared to other methods. In this paper an adaptive neuro-fuzzy inference system for the prediction of surface roughness in end milling is presented. Spindle speed, feed rate, depth of cut and vibrations were used as independent input variables, while roughness parameter Ra as dependent output variable. Several variations are tested and the results of the optimum system are presented. Final results indicate that the proposed model can accurately predict surface roughness, even for input that was not used in training.

An embedded implementation based on adaptive filter bank for brain-computer interface systems.

Science.gov (United States)

Belwafi, Kais; Romain, Olivier; Gannouni, Sofien; Ghaffari, Fakhreddine; Djemal, Ridha; Ouni, Bouraoui

2018-07-15

Brain-computer interface (BCI) is a new communication pathway for users with neurological deficiencies. The implementation of a BCI system requires complex electroencephalography (EEG) signal processing including filtering, feature extraction and classification algorithms. Most of current BCI systems are implemented on personal computers. Therefore, there is a great interest in implementing BCI on embedded platforms to meet system specifications in terms of time response, cost effectiveness, power consumption, and accuracy. This article presents an embedded-BCI (EBCI) system based on a Stratix-IV field programmable gate array. The proposed system relays on the weighted overlap-add (WOLA) algorithm to perform dynamic filtering of EEG-signals by analyzing the event-related desynchronization/synchronization (ERD/ERS). The EEG-signals are classified, using the linear discriminant analysis algorithm, based on their spatial features. The proposed system performs fast classification within a time delay of 0.430 s/trial, achieving an average accuracy of 76.80% according to an offline approach and 80.25% using our own recording. The estimated power consumption of the prototype is approximately 0.7 W. Results show that the proposed EBCI system reduces the overall classification error rate for the three datasets of the BCI-competition by 5% compared to other similar implementations. Moreover, experiment shows that the proposed system maintains a high accuracy rate with a short processing time, a low power consumption, and a low cost. Performing dynamic filtering of EEG-signals using WOLA increases the recognition rate of ERD/ERS patterns of motor imagery brain activity. This approach allows to develop a complete prototype of a EBCI system that achieves excellent accuracy rates. Copyright © 2018 Elsevier B.V. All rights reserved.

Intelligent computer systems in engineering design principles and applications

CERN Document Server

Sunnersjo, Staffan

2016-01-01

This introductory book discusses how to plan and build useful, reliable, maintainable and cost efficient computer systems for automated engineering design. The book takes a user perspective and seeks to bridge the gap between texts on principles of computer science and the user manuals for commercial design automation software. The approach taken is top-down, following the path from definition of the design task and clarification of the relevant design knowledge to the development of an operational system well adapted for its purpose. This introductory text for the practicing engineer working in industry covers most vital aspects of planning such a system. Experiences from applications of automated design systems in practice are reviewed based on a large number of real, industrial cases. The principles behind the most popular methods in design automation are presented with sufficient rigour to give the user confidence in applying them on real industrial problems. This book is also suited for a half semester c...

Nonequilibrium Enhances Adaptation Efficiency of Stochastic Biochemical Systems.

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Chen Jia

Full Text Available Adaptation is a crucial biological function possessed by many sensory systems. Early work has shown that some influential equilibrium models can achieve accurate adaptation. However, recent studies indicate that there are close relationships between adaptation and nonequilibrium. In this paper, we provide an explanation of these two seemingly contradictory results based on Markov models with relatively simple networks. We show that as the nonequilibrium driving becomes stronger, the system under consideration will undergo a phase transition along a fixed direction: from non-adaptation to simple adaptation then to oscillatory adaptation, while the transition in the opposite direction is forbidden. This indicates that although adaptation may be observed in equilibrium systems, it tends to occur in systems far away from equilibrium. In addition, we find that nonequilibrium will improve the performance of adaptation by enhancing the adaptation efficiency. All these results provide a deeper insight into the connection between adaptation and nonequilibrium. Finally, we use a more complicated network model of bacterial chemotaxis to validate the main results of this paper.

Recommendation System for Adaptive Learning.

Science.gov (United States)

Chen, Yunxiao; Li, Xiaoou; Liu, Jingchen; Ying, Zhiliang

2018-01-01

An adaptive learning system aims at providing instruction tailored to the current status of a learner, differing from the traditional classroom experience. The latest advances in technology make adaptive learning possible, which has the potential to provide students with high-quality learning benefit at a low cost. A key component of an adaptive learning system is a recommendation system, which recommends the next material (video lectures, practices, and so on, on different skills) to the learner, based on the psychometric assessment results and possibly other individual characteristics. An important question then follows: How should recommendations be made? To answer this question, a mathematical framework is proposed that characterizes the recommendation process as a Markov decision problem, for which decisions are made based on the current knowledge of the learner and that of the learning materials. In particular, two plain vanilla systems are introduced, for which the optimal recommendation at each stage can be obtained analytically.

Parallel Adaptive Mesh Refinement for High-Order Finite-Volume Schemes in Computational Fluid Dynamics

Science.gov (United States)

Schwing, Alan Michael

For computational fluid dynamics, the governing equations are solved on a discretized domain of nodes, faces, and cells. The quality of the grid or mesh can be a driving source for error in the results. While refinement studies can help guide the creation of a mesh, grid quality is largely determined by user expertise and understanding of the flow physics. Adaptive mesh refinement is a technique for enriching the mesh during a simulation based on metrics for error, impact on important parameters, or location of important flow features. This can offload from the user some of the difficult and ambiguous decisions necessary when discretizing the domain. This work explores the implementation of adaptive mesh refinement in an implicit, unstructured, finite-volume solver. Consideration is made for applying modern computational techniques in the presence of hanging nodes and refined cells. The approach is developed to be independent of the flow solver in order to provide a path for augmenting existing codes. It is designed to be applicable for unsteady simulations and refinement and coarsening of the grid does not impact the conservatism of the underlying numerics. The effect on high-order numerical fluxes of fourth- and sixth-order are explored. Provided the criteria for refinement is appropriately selected, solutions obtained using adapted meshes have no additional error when compared to results obtained on traditional, unadapted meshes. In order to leverage large-scale computational resources common today, the methods are parallelized using MPI. Parallel performance is considered for several test problems in order to assess scalability of both adapted and unadapted grids. Dynamic repartitioning of the mesh during refinement is crucial for load balancing an evolving grid. Development of the methods outlined here depend on a dual-memory approach that is described in detail. Validation of the solver developed here against a number of motivating problems shows favorable

Changing Paradigms: From Schooling to Schools as Adaptive Recommendation Systems

DEFF Research Database (Denmark)

Christiansen, René Boyer; Gynther, Karsten; Petersen, Anne Kristine

2017-01-01

The paper explores a shift in education from educational systems requiring student adaptation to educational recommendation systems adapting to students’ individual needs. The paper discusses the concept of adaptation as addressed in educational research and draws on the system theory of Heinz von...... Foerster to shed light on how the educational system has used and understood adaptation. In this context, we point out two different approaches to educational adaptation: 1) students adapting to the educational system and 2) the attempt of the educational system to adapt to students through automatized...... system adaptation and recommendation systems. These different understandings constitute a design framework that is used to analyze two current trends: Adaptive learning systems and learning analytics. Finally, the paper discusses the potential of looking at adaptation as recommendation systems...

Changing Paradigms: From Schooling to Schools as Adaptive Recommendation Systems

DEFF Research Database (Denmark)

Christiansen, René Boyer; Gynther, Karsten; Petersen, Anne Kristine

2017-01-01

The paper explores a shift in education from educational systems requiring student adaptation to educational recommendation systems adapting to students’ individual needs. The paper discusses the concept of adaptation as addressed in educational research and draws on the system theory of Heinz von...... system adaptation and recommendation systems. These different understandings constitute a design framework that is used to analyze two current trends: Adaptive learning systems and learning analytics. Finally, the paper discusses the potential of looking at adaptation as recommendation systems...... Foerster to shed light on how the educational system has used and understood adaptation. In this context, we point out two different approaches to educational adaptation: 1) students adapting to the educational system and 2) the attempt of the educational system to adapt to students through automatized...

SPADOCK: Adaptive Pipeline Technology for Web System using WebSocket

Directory of Open Access Journals (Sweden)

Aries RICHI

2013-01-01

Full Text Available As information technology grows to the era of IoT(Internet of Things and cloud computing, the performance ofweb application and web service which acts as the informationgateway becomes an issue. Horizontal quality of serviceimprovement through system performance escalation becomesan issue pursued by engineers and scientists, giving birth toBigPipe pipeline technology which was developed by Facebook.We make SPADOCK, an adaptive pipeline system which is builtunder distributed system architecture with the utilization ofHTML5 WebSocket, then measure its performance. Parametersused for the measurement includes latency, workload, andbandwidth. The result shows that SPADOCK could reduceserving latency by 68.28% compared with the conventional web,and it is 20.63% faster than BigPipe.

Computer vision in control systems

CERN Document Server

Jain, Lakhmi

2015-01-01

Volume 1 : This book is focused on the recent advances in computer vision methodologies and technical solutions using conventional and intelligent paradigms. The Contributions include: ·         Morphological Image Analysis for Computer Vision Applications. ·         Methods for Detecting of Structural Changes in Computer Vision Systems. ·         Hierarchical Adaptive KL-based Transform: Algorithms and Applications. ·         Automatic Estimation for Parameters of Image Projective Transforms Based on Object-invariant Cores. ·         A Way of Energy Analysis for Image and Video Sequence Processing. ·         Optimal Measurement of Visual Motion Across Spatial and Temporal Scales. ·         Scene Analysis Using Morphological Mathematics and Fuzzy Logic. ·         Digital Video Stabilization in Static and Dynamic Scenes. ·         Implementation of Hadamard Matrices for Image Processing. ·         A Generalized Criterion ...

Design Specifications for Adaptive Real-Time Systems

Science.gov (United States)

1991-12-01

TICfl \\ E CT E Design Specifications for JAN’\\ 1992 Adaptive Real - Time Systems fl Randall W. Lichota U, Alice H. Muntz - December 1991 \\ \\\\/ 0 / r...268-2056 Technical Report CMU/SEI-91-TR-20 ESD-91-TR-20 December 1991 Design Specifications for Adaptive Real - Time Systems Randall W. Lichota Hughes...Design Specifications for Adaptive Real - Time Systems Abstract: The design specification method described in this report treats a software

An adaptive neuro fuzzy model for estimating the reliability of component-based software systems

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Kirti Tyagi

2014-01-01

Full Text Available Although many algorithms and techniques have been developed for estimating the reliability of component-based software systems (CBSSs, much more research is needed. Accurate estimation of the reliability of a CBSS is difficult because it depends on two factors: component reliability and glue code reliability. Moreover, reliability is a real-world phenomenon with many associated real-time problems. Soft computing techniques can help to solve problems whose solutions are uncertain or unpredictable. A number of soft computing approaches for estimating CBSS reliability have been proposed. These techniques learn from the past and capture existing patterns in data. The two basic elements of soft computing are neural networks and fuzzy logic. In this paper, we propose a model for estimating CBSS reliability, known as an adaptive neuro fuzzy inference system (ANFIS, that is based on these two basic elements of soft computing, and we compare its performance with that of a plain FIS (fuzzy inference system for different data sets.

Neural Computations in a Dynamical System with Multiple Time Scales.

Science.gov (United States)

Mi, Yuanyuan; Lin, Xiaohan; Wu, Si

2016-01-01

Neural systems display rich short-term dynamics at various levels, e.g., spike-frequency adaptation (SFA) at the single-neuron level, and short-term facilitation (STF) and depression (STD) at the synapse level. These dynamical features typically cover a broad range of time scales and exhibit large diversity in different brain regions. It remains unclear what is the computational benefit for the brain to have such variability in short-term dynamics. In this study, we propose that the brain can exploit such dynamical features to implement multiple seemingly contradictory computations in a single neural circuit. To demonstrate this idea, we use continuous attractor neural network (CANN) as a working model and include STF, SFA and STD with increasing time constants in its dynamics. Three computational tasks are considered, which are persistent activity, adaptation, and anticipative tracking. These tasks require conflicting neural mechanisms, and hence cannot be implemented by a single dynamical feature or any combination with similar time constants. However, with properly coordinated STF, SFA and STD, we show that the network is able to implement the three computational tasks concurrently. We hope this study will shed light on the understanding of how the brain orchestrates its rich dynamics at various levels to realize diverse cognitive functions.

Interactive granular computations in networks and systems engineering a practical perspective

CERN Document Server

Jankowski, Andrzej

2017-01-01

The book outlines selected projects conducted under the supervision of the author. Moreover, it discusses significant relations between Interactive Granular Computing (IGrC) and numerous dynamically developing scientific domains worldwide, along with features characteristic of the author’s approach to IGrC. The results presented are a continuation and elaboration of various aspects of Wisdom Technology, initiated and developed in cooperation with Professor Andrzej Skowron. Based on the empirical findings from these projects, the author explores the following areas: (a) understanding the causes of the theory and practice gap problem (TPGP) in complex systems engineering (CSE);(b) generalizing computing models of complex adaptive systems (CAS) (in particular, natural computing models) by constructing an interactive granular computing (IGrC) model of networks of interrelated interacting complex granules (c-granules), belonging to a single agent and/or to a group of agents; (c) developing methodologies based ...

Student Modelling in Adaptive E-Learning Systems

Directory of Open Access Journals (Sweden)

Clemens Bechter

2011-09-01

Full Text Available Most e-Learning systems provide web-based learning so that students can access the same online courses via the Internet without adaptation, based on each student's profile and behavior. In an e-Learning system, one size does not fit all. Therefore, it is a challenge to make e-Learning systems that are suitably “adaptive”. The aim of adaptive e-Learning is to provide the students the appropriate content at the right time, means that the system is able to determine the knowledge level, keep track of usage, and arrange content automatically for each student for the best learning result. This study presents a proposed system which includes major adaptive features based on a student model. The proposed system is able to initialize the student model for determining the knowledge level of a student when the student registers for the course. After a student starts learning the lessons and doing many activities, the system can track information of the student until he/she takes a test. The student’s knowledge level, based on the test scores, is updated into the system for use in the adaptation process, which combines the student model with the domain model in order to deliver suitable course contents to the students. In this study, the proposed adaptive e-Learning system is implemented on an “Introduction to Java Programming Language” course, using LearnSquare software. After the system was tested, the results showed positive feedback towards the proposed system, especially in its adaptive capability.

On Event-Triggered Adaptive Architectures for Decentralized and Distributed Control of Large-Scale Modular Systems.

Science.gov (United States)

Albattat, Ali; Gruenwald, Benjamin C; Yucelen, Tansel

2016-08-16

The last decade has witnessed an increased interest in physical systems controlled over wireless networks (networked control systems). These systems allow the computation of control signals via processors that are not attached to the physical systems, and the feedback loops are closed over wireless networks. The contribution of this paper is to design and analyze event-triggered decentralized and distributed adaptive control architectures for uncertain networked large-scale modular systems; that is, systems consist of physically-interconnected modules controlled over wireless networks. Specifically, the proposed adaptive architectures guarantee overall system stability while reducing wireless network utilization and achieving a given system performance in the presence of system uncertainties that can result from modeling and degraded modes of operation of the modules and their interconnections between each other. In addition to the theoretical findings including rigorous system stability and the boundedness analysis of the closed-loop dynamical system, as well as the characterization of the effect of user-defined event-triggering thresholds and the design parameters of the proposed adaptive architectures on the overall system performance, an illustrative numerical example is further provided to demonstrate the efficacy of the proposed decentralized and distributed control approaches.

On Event-Triggered Adaptive Architectures for Decentralized and Distributed Control of Large-Scale Modular Systems

Directory of Open Access Journals (Sweden)

Ali Albattat

2016-08-01

Full Text Available The last decade has witnessed an increased interest in physical systems controlled over wireless networks (networked control systems. These systems allow the computation of control signals via processors that are not attached to the physical systems, and the feedback loops are closed over wireless networks. The contribution of this paper is to design and analyze event-triggered decentralized and distributed adaptive control architectures for uncertain networked large-scale modular systems; that is, systems consist of physically-interconnected modules controlled over wireless networks. Specifically, the proposed adaptive architectures guarantee overall system stability while reducing wireless network utilization and achieving a given system performance in the presence of system uncertainties that can result from modeling and degraded modes of operation of the modules and their interconnections between each other. In addition to the theoretical findings including rigorous system stability and the boundedness analysis of the closed-loop dynamical system, as well as the characterization of the effect of user-defined event-triggering thresholds and the design parameters of the proposed adaptive architectures on the overall system performance, an illustrative numerical example is further provided to demonstrate the efficacy of the proposed decentralized and distributed control approaches.

Adaptive lag synchronization and parameters adaptive lag identification of chaotic systems

Energy Technology Data Exchange (ETDEWEB)

Xu Yuhua, E-mail: yuhuaxu2004@163.co [College of Information Science and Technology, Donghua University, Shanghai 201620 (China) and Department of Mathematics, Yunyang Teachers' College, Hubei, Shiyan 442000 (China); Zhou Wuneng, E-mail: wnzhou@163.co [College of Information Science and Technology, Donghua University, Shanghai 201620 (China) and Key Laboratory of Wireless Sensor Network and Communication, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050 (China); Fang Jian' an, E-mail: jafang@dhu.edu.c [College of Information Science and Technology, Donghua University, Shanghai 201620 (China); Sun Wen, E-mail: sunwen_2201@163.co [School of Mathematics and Information, Yangtze University, Hubei, Jingzhou 434023 (China)

2010-07-26

This Letter investigates the problem of adaptive lag synchronization and parameters adaptive lag identification of chaotic systems. In comparison with those of existing parameters identification schemes, the unknown parameters are identified by adaptive lag laws, and the delay time is also identified in this Letter. Numerical simulations are also given to show the effectiveness of the proposed method.

Development of a totally computer-controlled triple quadrupole mass spectrometer system

International Nuclear Information System (INIS)

Wong, C.M.; Crawford, R.W.; Barton, V.C.; Brand, H.R.; Neufeld, K.W.; Bowman, J.E.

1983-01-01

A totally computer-controlled triple quadrupole mass spectrometer (TQMS) is described. It has a number of unique features not available on current commercial instruments, including: complete computer control of source and all ion axial potentials; use of dual computers for data acquisition and data processing; and capability for self-adaptive control of experiments. Furthermore, it has been possible to produce this instrument at a cost significantly below that of commercial instruments. This triple quadrupole mass spectrometer has been constructed using components commercially available from several different manufacturers. The source is a standard Hewlett-Packard 5985B GC/MS source. The two quadrupole analyzers and the quadrupole CAD region contain Balzers QMA 150 rods with Balzers QMG 511 rf controllers for the analyzers and a Balzers QHS-511 controller for the CAD region. The pulsed-positive-ion-negative-ion-chemical ionization (PPINICI) detector is made by Finnigan Corporation. The mechanical and electronics design were developed at LLNL for linking these diverse elements into a functional TQMS as described. The computer design for total control of the system is unique in that two separate LSI-11/23 minicomputers and assorted I/O peripherals and interfaces from several manufacturers are used. The evolution of this design concept from totally computer-controlled instrumentation into future self-adaptive or ''expert'' systems for instrumental analysis is described. Operational characteristics of the instrument and initial results from experiments involving the analysis of the high explosive HMX (1,3,5,7-Tetranitro-1,3,5,7-Tetrazacyclooctane) are presented

A Nuclear Safety System based on Industrial Computer

International Nuclear Information System (INIS)

Kim, Ji Hyeon; Oh, Do Young; Lee, Nam Hoon; Kim, Chang Ho; Kim, Jae Hack

2011-01-01

The Plant Protection System(PPS), a nuclear safety Instrumentation and Control (I and C) system for Nuclear Power Plants(NPPs), generates reactor trip on abnormal reactor condition. The Core Protection Calculator System (CPCS) is a safety system that generates and transmits the channel trip signal to the PPS on an abnormal condition. Currently, these systems are designed on the Programmable Logic Controller(PLC) based system and it is necessary to consider a new system platform to adapt simpler system configuration and improved software development process. The CPCS was the first implementation using a micro computer in a nuclear power plant safety protection system in 1980 which have been deployed in Ulchin units 3,4,5,6 and Younggwang units 3,4,5,6. The CPCS software was developed in the Concurrent Micro5 minicomputer using assembly language and embedded into the Concurrent 3205 computer. Following the micro computer based CPCS, PLC based Common-Q platform has been used for the ShinKori/ShinWolsong units 1,2 PPS and CPCS, and the POSAFE-Q PLC platform is used for the ShinUlchin units 1,2 PPS and CPCS. In developing the next generation safety system platform, several factors (e.g., hardware/software reliability, flexibility, licensibility and industrial support) can be considered. This paper suggests an Industrial Computer(IC) based protection system that can be developed with improved flexibility without losing system reliability. The IC based system has the advantage of a simple system configuration with optimized processor boards because of improved processor performance and unlimited interoperability between the target system and development system that use commercial CASE tools. This paper presents the background to selecting the IC based system with a case study design of the CPCS. Eventually, this kind of platform can be used for nuclear power plant safety systems like the PPS, CPCS, Qualified Indication and Alarm . Pami(QIAS-P), and Engineering Safety

A Nuclear Safety System based on Industrial Computer

Energy Technology Data Exchange (ETDEWEB)

Kim, Ji Hyeon; Oh, Do Young; Lee, Nam Hoon; Kim, Chang Ho; Kim, Jae Hack [Korea Electric Power Corporation Engineering and Construction, Daejeon (Korea, Republic of)

2011-05-15

The Plant Protection System(PPS), a nuclear safety Instrumentation and Control (I and C) system for Nuclear Power Plants(NPPs), generates reactor trip on abnormal reactor condition. The Core Protection Calculator System (CPCS) is a safety system that generates and transmits the channel trip signal to the PPS on an abnormal condition. Currently, these systems are designed on the Programmable Logic Controller(PLC) based system and it is necessary to consider a new system platform to adapt simpler system configuration and improved software development process. The CPCS was the first implementation using a micro computer in a nuclear power plant safety protection system in 1980 which have been deployed in Ulchin units 3,4,5,6 and Younggwang units 3,4,5,6. The CPCS software was developed in the Concurrent Micro5 minicomputer using assembly language and embedded into the Concurrent 3205 computer. Following the micro computer based CPCS, PLC based Common-Q platform has been used for the ShinKori/ShinWolsong units 1,2 PPS and CPCS, and the POSAFE-Q PLC platform is used for the ShinUlchin units 1,2 PPS and CPCS. In developing the next generation safety system platform, several factors (e.g., hardware/software reliability, flexibility, licensibility and industrial support) can be considered. This paper suggests an Industrial Computer(IC) based protection system that can be developed with improved flexibility without losing system reliability. The IC based system has the advantage of a simple system configuration with optimized processor boards because of improved processor performance and unlimited interoperability between the target system and development system that use commercial CASE tools. This paper presents the background to selecting the IC based system with a case study design of the CPCS. Eventually, this kind of platform can be used for nuclear power plant safety systems like the PPS, CPCS, Qualified Indication and Alarm . Pami(QIAS-P), and Engineering Safety

Use of computer programs to evaluate effectiveness of security systems

International Nuclear Information System (INIS)

Harris, L. Jr.; Goldman, L.A.; Mc Daniel, T.L.

1987-01-01

Thirty or more computer programs for security vulnerability analysis were developed from 1975 through 1980. Most of these programs are intended for evaluating security system effectiveness against outsider threats, but at least six programs are primarily oriented to insider threats. Some strengths and weaknesses of these programs are described. Six of these programs, four for outsider threats and two for insider threats, have been revised and adapted for use with IBM personal computers. The vulnerability analysis process is discussed with emphasis on data collection. The difference between design data and operational data is described. For performance-type operational data, such as detection probabilities and barrier delay times, the difference between unstressed and stressed performance data is discussed. Stressed performance data correspond to situations where an adversary attempts to weaken a security system by mitigating certain security measures. Suggestions are made on the combined use of manual analysis and computer analysis

A Bayesian framework for adaptive selection, calibration, and validation of coarse-grained models of atomistic systems

Energy Technology Data Exchange (ETDEWEB)

Farrell, Kathryn, E-mail: kfarrell@ices.utexas.edu; Oden, J. Tinsley, E-mail: oden@ices.utexas.edu; Faghihi, Danial, E-mail: danial@ices.utexas.edu

2015-08-15

A general adaptive modeling algorithm for selection and validation of coarse-grained models of atomistic systems is presented. A Bayesian framework is developed to address uncertainties in parameters, data, and model selection. Algorithms for computing output sensitivities to parameter variances, model evidence and posterior model plausibilities for given data, and for computing what are referred to as Occam Categories in reference to a rough measure of model simplicity, make up components of the overall approach. Computational results are provided for representative applications.

A Bayesian framework for adaptive selection, calibration, and validation of coarse-grained models of atomistic systems

Science.gov (United States)

Farrell, Kathryn; Oden, J. Tinsley; Faghihi, Danial

2015-08-01

A general adaptive modeling algorithm for selection and validation of coarse-grained models of atomistic systems is presented. A Bayesian framework is developed to address uncertainties in parameters, data, and model selection. Algorithms for computing output sensitivities to parameter variances, model evidence and posterior model plausibilities for given data, and for computing what are referred to as Occam Categories in reference to a rough measure of model simplicity, make up components of the overall approach. Computational results are provided for representative applications.

A stand alone computer system to aid the development of mirror fusion test facility RF heating systems

International Nuclear Information System (INIS)

Thomas, R.A.

1983-01-01

The Mirror Fusion Test Facility (MFTF-B) control system architecture requires the Supervisory Control and Diagnostic System (SCDS) to communicate with a LSI-11 Local Control Computer (LCC) that in turn communicates via a fiber optic link to CAMAC based control hardware located near the machine. In many cases, the control hardware is very complex and requires a sizable development effort prior to being integrated into the overall MFTF-B system. One such effort was the development of the Electron Cyclotron Resonance Heating (ECRH) system. It became clear that a stand alone computer system was needed to simulate the functions of SCDS. This paper describes the hardware and software necessary to implement the SCDS Simulation Computer (SSC). It consists of a Digital Equipment Corporation (DEC) LSI-11 computer and a Winchester/Floppy disk operating under the DEC RT-11 operating system. All application software for MFTF-B is programmed in PASCAL, which allowed us to adapt procedures originally written for SCDS to the SSC. This nearly identical software interface means that software written during the equipment development will be useful to the SCDS programmers in the integration phase

An adaptive structure data acquisition system using a graphical-based programming language

Science.gov (United States)

Baroth, Edmund C.; Clark, Douglas J.; Losey, Robert W.

1992-01-01

An example of the implementation of data fusion using a PC and a graphical programming language is discussed. A schematic of the data acquisition system and user interface panel for an adaptive structure test are presented. The computer programs (a series of icons 'wired' together) are also discussed. The way in which using graphical-based programming software to control a data acquisition system can simplify analysis of data, promote multidisciplinary interaction, and provide users a more visual key to understanding their data are shown.

WEB-BASED ADAPTIVE TESTING SYSTEM (WATS FOR CLASSIFYING STUDENTS ACADEMIC ABILITY

Directory of Open Access Journals (Sweden)

Jaemu LEE,

2012-08-01

Full Text Available Computer Adaptive Testing (CAT has been highlighted as a promising assessment method to fulfill two testing purposes: estimating student academic ability and classifying student academic level. In this paper, we introduced the Web-based Adaptive Testing System (WATS developed to support a cost effective assessment for classifying students’ ability into different academic levels. Instead of using a traditional paper and pencil test, the WATS is expected to serve as an alternate method to promptly diagnosis and identify underachieving students through Web-based testing. The WATS can also help provide students with appropriate learning contents and necessary academic support in time. In this paper, theoretical background and structure of WATS, item construction process based upon item response theory, and user interfaces of WATS were discussed.

Reliable computer systems.

Science.gov (United States)

Wear, L L; Pinkert, J R

1993-11-01

In this article, we looked at some decisions that apply to the design of reliable computer systems. We began with a discussion of several terms such as testability, then described some systems that call for highly reliable hardware and software. The article concluded with a discussion of methods that can be used to achieve higher reliability in computer systems. Reliability and fault tolerance in computers probably will continue to grow in importance. As more and more systems are computerized, people will want assurances about the reliability of these systems, and their ability to work properly even when sub-systems fail.

Rate Adaptive OFDMA Communication Systems

International Nuclear Information System (INIS)

Abdelhakim, M.M.M.

2009-01-01

Due to the varying nature of the wireless channels, adapting the transmission parameters, such as code rate, modulation order and power, in response to the channel variations provides a significant improvement in the system performance. In the OFDM systems, Per-Frame adaptation (PFA) can be employed where the transmission variables are fixed over a given frame and may change from one frame to the other. Subband (tile) loading offers more degrees of adaptation such that each group of carriers (subband) uses the same transmission parameters and different subbands may use different parameters. Changing the code rate for each tile in the same frame, results in transmitting multiple codewords (MCWs) for a single frame. In this thesis a scheme is proposed for adaptively changing the code rate of coded OFDMA systems via changing the puncturing rate within a single codeword (SCW). In the proposed structure, the data is encoded with the lowest available code rate then it is divided among the different tiles where it is punctured adaptively based on some measure of the channel quality for each tile. The proposed scheme is compared against using multiple codewords (MCWs) where the different code rates for the tiles are obtained using separate encoding processes. For bit interleaved coded modulation architecture two novel interleaving methods are proposed, namely the puncturing dependant interleaver (PDI) and interleaved puncturing (IntP), which provide larger interleaving depth. In the PDI method the coded bits with the same rate over different tiles are grouped for interleaving. In IntP structure the interleaving is performed prior to puncturing. The performance of the adaptive puncturing technique is investigated under constant bit rate constraint and variable bit rate. Two different adaptive modulation and coding (AMC) selection methods are examined for variable bit rate adaptive system. The first is a recursive scheme that operates directly on the SNR whereas the second

DySOA : Making service systems self-adaptive

NARCIS (Netherlands)

Siljee, J; Bosloper, [No Value; Nijhuis, J; Hammer, D; Benatallah, B; Casati, F; Traverso, P

2005-01-01

Service-centric systems exist in a very dynamic environment. This requires these systems to adapt at runtime in order to keep fulfilling their QoS. In order to create self-adaptive service systems, developers should not only design the service architecture, but also need to design the

Operator adaptation to changes in system reliability under adaptable automation.

Science.gov (United States)

Chavaillaz, Alain; Sauer, Juergen

2017-09-01

This experiment examined how operators coped with a change in system reliability between training and testing. Forty participants were trained for 3 h on a complex process control simulation modelling six levels of automation (LOA). In training, participants either experienced a high- (100%) or low-reliability system (50%). The impact of training experience on operator behaviour was examined during a 2.5 h testing session, in which participants either experienced a high- (100%) or low-reliability system (60%). The results showed that most operators did not often switch between LOA. Most chose an LOA that relieved them of most tasks but maintained their decision authority. Training experience did not have a strong impact on the outcome measures (e.g. performance, complacency). Low system reliability led to decreased performance and self-confidence. Furthermore, complacency was observed under high system reliability. Overall, the findings suggest benefits of adaptable automation because it accommodates different operator preferences for LOA. Practitioner Summary: The present research shows that operators can adapt to changes in system reliability between training and testing sessions. Furthermore, it provides evidence that each operator has his/her preferred automation level. Since this preference varies strongly between operators, adaptable automation seems to be suitable to accommodate these large differences.

Cloud Computing Platform for an Online Model Library System

Directory of Open Access Journals (Sweden)

Mingang Chen

2013-01-01

Full Text Available The rapid developing of digital content industry calls for online model libraries. For the efficiency, user experience, and reliability merits of the model library, this paper designs a Web 3D model library system based on a cloud computing platform. Taking into account complex models, which cause difficulties in real-time 3D interaction, we adopt the model simplification and size adaptive adjustment methods to make the system with more efficient interaction. Meanwhile, a cloud-based architecture is developed to ensure the reliability and scalability of the system. The 3D model library system is intended to be accessible by online users with good interactive experiences. The feasibility of the solution has been tested by experiments.

Adaptive weighted anisotropic diffusion for computed tomography denoising

Energy Technology Data Exchange (ETDEWEB)

Yang, Zhi; Silver, Michael D. [Toshiba Medical Research Institute USA, Inc., Vernon Hills, IL (United States); Noshi, Yasuhiro [Toshiba Medical System Corporation, Tokyo (Japan)

2011-07-01

With increasing awareness of radiation safety, dose reduction has become an important task of modern CT system development. This paper proposes an adaptive weighted anisotropic diffusion method and an adaptive weighted sharp source anisotropic diffusion method as image domain filters to potentially help dose reduction. Different from existing anisotropic diffusion methods, the proposed methods incorporate an edge-sensitive adaptive source term as part of the diffusion iteration. It provides better edge and detail preservation. Visual evaluation showed that the new methods can reduce noise substantially without apparent edge and detail loss. The quantitative evaluations also showed over 50% of noise reduction in terms of noise standard deviations, which is equivalent to over 75% of dose reduction for a normal dose image quality. (orig.)

Adaptive Behaviour Assessment System: Indigenous Australian Adaptation Model (ABAS: IAAM)

Science.gov (United States)

du Plessis, Santie

2015-01-01

The study objectives were to develop, trial and evaluate a cross-cultural adaptation of the Adaptive Behavior Assessment System-Second Edition Teacher Form (ABAS-II TF) ages 5-21 for use with Indigenous Australian students ages 5-14. This study introduced a multiphase mixed-method design with semi-structured and informal interviews, school…

Adaptive Statistical Iterative Reconstruction-V Versus Adaptive Statistical Iterative Reconstruction: Impact on Dose Reduction and Image Quality in Body Computed Tomography.

Science.gov (United States)

Gatti, Marco; Marchisio, Filippo; Fronda, Marco; Rampado, Osvaldo; Faletti, Riccardo; Bergamasco, Laura; Ropolo, Roberto; Fonio, Paolo

The aim of this study was to evaluate the impact on dose reduction and image quality of the new iterative reconstruction technique: adaptive statistical iterative reconstruction (ASIR-V). Fifty consecutive oncologic patients acted as case controls undergoing during their follow-up a computed tomography scan both with ASIR and ASIR-V. Each study was analyzed in a double-blinded fashion by 2 radiologists. Both quantitative and qualitative analyses of image quality were conducted. Computed tomography scanner radiation output was 38% (29%-45%) lower (P ASIR-V examinations than for the ASIR ones. The quantitative image noise was significantly lower (P ASIR-V. Adaptive statistical iterative reconstruction-V had a higher performance for the subjective image noise (P = 0.01 for 5 mm and P = 0.009 for 1.25 mm), the other parameters (image sharpness, diagnostic acceptability, and overall image quality) being similar (P > 0.05). Adaptive statistical iterative reconstruction-V is a new iterative reconstruction technique that has the potential to provide image quality equal to or greater than ASIR, with a dose reduction around 40%.

Indirect adaptive soft computing based wavelet-embedded control paradigms for WT/PV/SOFC in a grid/charging station connected hybrid power system.

Directory of Open Access Journals (Sweden)

Sidra Mumtaz

Full Text Available This paper focuses on the indirect adaptive tracking control of renewable energy sources in a grid-connected hybrid power system. The renewable energy systems have low efficiency and intermittent nature due to unpredictable meteorological conditions. The domestic load and the conventional charging stations behave in an uncertain manner. To operate the renewable energy sources efficiently for harvesting maximum power, instantaneous nonlinear dynamics should be captured online. A Chebyshev-wavelet embedded NeuroFuzzy indirect adaptive MPPT (maximum power point tracking control paradigm is proposed for variable speed wind turbine-permanent synchronous generator (VSWT-PMSG. A Hermite-wavelet incorporated NeuroFuzzy indirect adaptive MPPT control strategy for photovoltaic (PV system to extract maximum power and indirect adaptive tracking control scheme for Solid Oxide Fuel Cell (SOFC is developed. A comprehensive simulation test-bed for a grid-connected hybrid power system is developed in Matlab/Simulink. The robustness of the suggested indirect adaptive control paradigms are evaluated through simulation results in a grid-connected hybrid power system test-bed by comparison with conventional and intelligent control techniques. The simulation results validate the effectiveness of the proposed control paradigms.

Indirect adaptive soft computing based wavelet-embedded control paradigms for WT/PV/SOFC in a grid/charging station connected hybrid power system.

Science.gov (United States)

Mumtaz, Sidra; Khan, Laiq; Ahmed, Saghir; Bader, Rabiah

2017-01-01

This paper focuses on the indirect adaptive tracking control of renewable energy sources in a grid-connected hybrid power system. The renewable energy systems have low efficiency and intermittent nature due to unpredictable meteorological conditions. The domestic load and the conventional charging stations behave in an uncertain manner. To operate the renewable energy sources efficiently for harvesting maximum power, instantaneous nonlinear dynamics should be captured online. A Chebyshev-wavelet embedded NeuroFuzzy indirect adaptive MPPT (maximum power point tracking) control paradigm is proposed for variable speed wind turbine-permanent synchronous generator (VSWT-PMSG). A Hermite-wavelet incorporated NeuroFuzzy indirect adaptive MPPT control strategy for photovoltaic (PV) system to extract maximum power and indirect adaptive tracking control scheme for Solid Oxide Fuel Cell (SOFC) is developed. A comprehensive simulation test-bed for a grid-connected hybrid power system is developed in Matlab/Simulink. The robustness of the suggested indirect adaptive control paradigms are evaluated through simulation results in a grid-connected hybrid power system test-bed by comparison with conventional and intelligent control techniques. The simulation results validate the effectiveness of the proposed control paradigms.

Indirect adaptive soft computing based wavelet-embedded control paradigms for WT/PV/SOFC in a grid/charging station connected hybrid power system

Science.gov (United States)

Khan, Laiq; Ahmed, Saghir; Bader, Rabiah

2017-01-01

This paper focuses on the indirect adaptive tracking control of renewable energy sources in a grid-connected hybrid power system. The renewable energy systems have low efficiency and intermittent nature due to unpredictable meteorological conditions. The domestic load and the conventional charging stations behave in an uncertain manner. To operate the renewable energy sources efficiently for harvesting maximum power, instantaneous nonlinear dynamics should be captured online. A Chebyshev-wavelet embedded NeuroFuzzy indirect adaptive MPPT (maximum power point tracking) control paradigm is proposed for variable speed wind turbine-permanent synchronous generator (VSWT-PMSG). A Hermite-wavelet incorporated NeuroFuzzy indirect adaptive MPPT control strategy for photovoltaic (PV) system to extract maximum power and indirect adaptive tracking control scheme for Solid Oxide Fuel Cell (SOFC) is developed. A comprehensive simulation test-bed for a grid-connected hybrid power system is developed in Matlab/Simulink. The robustness of the suggested indirect adaptive control paradigms are evaluated through simulation results in a grid-connected hybrid power system test-bed by comparison with conventional and intelligent control techniques. The simulation results validate the effectiveness of the proposed control paradigms. PMID:28877191

PEAC: A Power-Efficient Adaptive Computing Technology for Enabling Swarm of Small Spacecraft and Deployable Mini-Payloads

Data.gov (United States)

National Aeronautics and Space Administration — This task is to develop and demonstrate a path-to-flight and power-adaptive avionics technology PEAC (Power Efficient Adaptive Computing). PEAC will enable emerging...

Computer program for the automated attendance accounting system

Science.gov (United States)

Poulson, P.; Rasmusson, C.

1971-01-01

The automated attendance accounting system (AAAS) was developed under the auspices of the Space Technology Applications Program. The task is basically the adaptation of a small digital computer, coupled with specially developed pushbutton terminals located in school classrooms and offices for the purpose of taking daily attendance, maintaining complete attendance records, and producing partial and summary reports. Especially developed for high schools, the system is intended to relieve both teachers and office personnel from the time-consuming and dreary task of recording and analyzing the myriad classroom attendance data collected throughout the semester. In addition, since many school district budgets are related to student attendance, the increase in accounting accuracy is expected to augment district income. A major component of this system is the real-time AAAS software system, which is described.

A Pilot-Scale Heat Recovery System for Computer Process Control Teaching and Research.

Science.gov (United States)

Callaghan, P. J.; And Others

1988-01-01

Describes the experimental system and equipment including an interface box for displaying variables. Discusses features which make the circuit suitable for teaching and research in computing. Feedforward, decoupling, and adaptive control, examination of digital filtering, and a cascade loop are teaching experiments utilizing this rig. Diagrams and…

Adaptive protection algorithm and system

Science.gov (United States)

Hedrick, Paul [Pittsburgh, PA; Toms, Helen L [Irwin, PA; Miller, Roger M [Mars, PA

2009-04-28

An adaptive protection algorithm and system for protecting electrical distribution systems traces the flow of power through a distribution system, assigns a value (or rank) to each circuit breaker in the system and then determines the appropriate trip set points based on the assigned rank.

Adaptive Event-Triggered Control Based on Heuristic Dynamic Programming for Nonlinear Discrete-Time Systems.

Science.gov (United States)

Dong, Lu; Zhong, Xiangnan; Sun, Changyin; He, Haibo

2017-07-01

This paper presents the design of a novel adaptive event-triggered control method based on the heuristic dynamic programming (HDP) technique for nonlinear discrete-time systems with unknown system dynamics. In the proposed method, the control law is only updated when the event-triggered condition is violated. Compared with the periodic updates in the traditional adaptive dynamic programming (ADP) control, the proposed method can reduce the computation and transmission cost. An actor-critic framework is used to learn the optimal event-triggered control law and the value function. Furthermore, a model network is designed to estimate the system state vector. The main contribution of this paper is to design a new trigger threshold for discrete-time systems. A detailed Lyapunov stability analysis shows that our proposed event-triggered controller can asymptotically stabilize the discrete-time systems. Finally, we test our method on two different discrete-time systems, and the simulation results are included.

An adaptable Boolean net trainable to control a computing robot

International Nuclear Information System (INIS)

Lauria, F. E.; Prevete, R.; Milo, M.; Visco, S.

1999-01-01

We discuss a method to implement in a Boolean neural network a Hebbian rule so to obtain an adaptable universal control system. We start by presenting both the Boolean neural net and the Hebbian rule we have considered. Then we discuss, first, the problems arising when the latter is naively implemented in a Boolean neural net, second, the method consenting us to overcome them and the ensuing adaptable Boolean neural net paradigm. Next, we present the adaptable Boolean neural net as an intelligent control system, actually controlling a writing robot, and discuss how to train it in the execution of the elementary arithmetic operations on operands represented by numerals with an arbitrary number of digits

Modeling the Internet of Things, Self-Organizing and Other Complex Adaptive Communication Networks: A Cognitive Agent-Based Computing Approach.

Directory of Open Access Journals (Sweden)

Samreen Laghari

Full Text Available Computer Networks have a tendency to grow at an unprecedented scale. Modern networks involve not only computers but also a wide variety of other interconnected devices ranging from mobile phones to other household items fitted with sensors. This vision of the "Internet of Things" (IoT implies an inherent difficulty in modeling problems.It is practically impossible to implement and test all scenarios for large-scale and complex adaptive communication networks as part of Complex Adaptive Communication Networks and Environments (CACOONS. The goal of this study is to explore the use of Agent-based Modeling as part of the Cognitive Agent-based Computing (CABC framework to model a Complex communication network problem.We use Exploratory Agent-based Modeling (EABM, as part of the CABC framework, to develop an autonomous multi-agent architecture for managing carbon footprint in a corporate network. To evaluate the application of complexity in practical scenarios, we have also introduced a company-defined computer usage policy.The conducted experiments demonstrated two important results: Primarily CABC-based modeling approach such as using Agent-based Modeling can be an effective approach to modeling complex problems in the domain of IoT. Secondly, the specific problem of managing the Carbon footprint can be solved using a multiagent system approach.

Modeling the Internet of Things, Self-Organizing and Other Complex Adaptive Communication Networks: A Cognitive Agent-Based Computing Approach.

Science.gov (United States)

Laghari, Samreen; Niazi, Muaz A

2016-01-01

Computer Networks have a tendency to grow at an unprecedented scale. Modern networks involve not only computers but also a wide variety of other interconnected devices ranging from mobile phones to other household items fitted with sensors. This vision of the "Internet of Things" (IoT) implies an inherent difficulty in modeling problems. It is practically impossible to implement and test all scenarios for large-scale and complex adaptive communication networks as part of Complex Adaptive Communication Networks and Environments (CACOONS). The goal of this study is to explore the use of Agent-based Modeling as part of the Cognitive Agent-based Computing (CABC) framework to model a Complex communication network problem. We use Exploratory Agent-based Modeling (EABM), as part of the CABC framework, to develop an autonomous multi-agent architecture for managing carbon footprint in a corporate network. To evaluate the application of complexity in practical scenarios, we have also introduced a company-defined computer usage policy. The conducted experiments demonstrated two important results: Primarily CABC-based modeling approach such as using Agent-based Modeling can be an effective approach to modeling complex problems in the domain of IoT. Secondly, the specific problem of managing the Carbon footprint can be solved using a multiagent system approach.

Specification and Generation of Adapters for System Integration

NARCIS (Netherlands)

Mooij, A.J.; Voorhoeve, M.

2013-01-01

Large systems-of-systems are developed by integrating several smaller systems that have been developed independently. System integration often requires adaptation mechanisms for bridging any technical incompatibilities between the systems. In order to develop adapters in a faster way, we study ways

Computer-assisted design/computer-assisted manufacturing systems: A revolution in restorative dentistry

Directory of Open Access Journals (Sweden)

Arbaz Sajjad

2016-01-01

Full Text Available For the better part of the past 20 years, dentistry has seen the development of many new all-ceramic materials and restorative techniques fueled by the desire to capture the ever elusive esthetic perfection. This has resulted in the fusion of the latest in material science and the pen ultimate in computer-assisted design/computer-assisted manufacturing (CAD/CAM technology. This case report describes the procedure for restoring the esthetic appearance of both the left and right maxillary peg-shaped lateral incisors with a metal-free sintered finely structured feldspar ceramic material using the latest laboratory CAD/CAM system. The use of CAD/CAM technology makes it possible to produce restorations faster with precision- fit and good esthetics overcoming the errors associated with traditional ceramo-metal technology. The incorporation of this treatment modality would mean that the dentist working procedures will have to be adapted in the methods of CAD/CAM technology.

The LLNL Multiuser Tandem Laboratory computer-controlled radiation monitoring system

International Nuclear Information System (INIS)

Homann, S.G.

1992-01-01

The Physics Department of the Lawrence Livermore National Laboratory (LLNL) recently constructed a Multiuser Tandem Laboratory (MTL) to perform a variety of basic and applied measurement programs. The laboratory and its research equipment were constructed with support from a consortium of LLNL Divisions, Sandia National Laboratories Livermore, and the University of California. Primary design goals for the facility were inexpensive construction and operation, high beam quality at a large number of experimental stations, and versatility in adapting to new experimental needs. To accomplish these goals, our main design decisions were to place the accelerator in an unshielded structure, to make use of reconfigured cyclotrons as effective switching magnets, and to rely on computer control systems for both radiological protection and highly reproducible and well-characterized accelerator operation. This paper addresses the radiological control computer system

Data acquisition system using a C 90-10 computer

International Nuclear Information System (INIS)

Smiljanic, Gabro

1969-05-01

The aim of this study is to make possible the acquisition of experimental data by the memory of a numerical calculator. These data come from analog-to-digital converters that analyze the amplitude of the pulses provided by detectors. Normally the computer executes its main program (data processing, transfer on magnetic tape, visualization, etc.). When information is available at the output of a converter, an interruption of the main program is requested, and after agreement a subroutine supports access to the information in the computer. The author has also considered the bi- and tri-parametric acquisition. The calculator and the converters are commercial devices (calculator C 90-10 from CII and converter CA 12 or CA 25 from Intertechnique), while the systems of adaptation of the input-output levels and the visualization were studied and realized at the CEA Saclay. An interface device was built to connect the converters; it's the cable part of the system. On the other hand, the programs necessary for the operation of the calculator have been studied and developed; it is the program aspect of the system. As far as possible the interface is designed to be universal, i.e. it must be able to work with other brands of equipment. The acquisition of the data is carried out in two phases: a) the converter expresses the amplitude of the input signal in the form of a binary number which is transferred into the interface at the same time as an interruption of the main program is asked. b) After acceptance of this interruption, the subprogram supports the transfer of the information of the interface in the computer, then adds a unit to the word located at the address determined from the information received. In other words, the system behaves like an amplitude analyzer whose operation is well known. But it is of a much more flexible use because of the possibilities of quick adaptation of the programs to the needs of the considered experiment, of the possibility to treat

Adaptive feedback synchronization of Lue system

International Nuclear Information System (INIS)

Han, X.; Lu, J.-A.; Wu, X.

2004-01-01

This letter further improves and extends the works of Chen and Lue [Chaos, Solitons and Fractals 14 (2002) 643] and Wang et al. [Phys. Lett. A 312 (2003) 34]. In detail, the linear feedback synchronization and adaptive feedback synchronization for Lue system are discussed. And the lower bound of the feedback gain in linear feedback synchronization is presented. The adaptive feedback synchronization with only one controller is designed, which improves the proof in the work by Wang et al. The adaptive synchronization with two controllers for completely uncertain Lue system is also discussed, which extends the work of Chen and Lue. Also, numerical simulations show the effectiveness of these methods

Adaptive Sliding Mode Observer for a Class of Systems

OpenAIRE

D.Elleuch; T.Damak

2010-01-01

In this paper, the performance of two adaptive observers applied to interconnected systems is studied. The nonlinearity of systems can be written in a fractional form. The first adaptive observer is an adaptive sliding mode observer for a Lipchitz nonlinear system and the second one is an adaptive sliding mode observer having a filtered error as a sliding surface. After comparing their performances throughout the inverted pendulum mounted on a car system, it was shown tha...

A single network adaptive critic (SNAC) architecture for optimal control synthesis for a class of nonlinear systems.

Science.gov (United States)

Padhi, Radhakant; Unnikrishnan, Nishant; Wang, Xiaohua; Balakrishnan, S N

2006-12-01

Even though dynamic programming offers an optimal control solution in a state feedback form, the method is overwhelmed by computational and storage requirements. Approximate dynamic programming implemented with an Adaptive Critic (AC) neural network structure has evolved as a powerful alternative technique that obviates the need for excessive computations and storage requirements in solving optimal control problems. In this paper, an improvement to the AC architecture, called the "Single Network Adaptive Critic (SNAC)" is presented. This approach is applicable to a wide class of nonlinear systems where the optimal control (stationary) equation can be explicitly expressed in terms of the state and costate variables. The selection of this terminology is guided by the fact that it eliminates the use of one neural network (namely the action network) that is part of a typical dual network AC setup. As a consequence, the SNAC architecture offers three potential advantages: a simpler architecture, lesser computational load and elimination of the approximation error associated with the eliminated network. In order to demonstrate these benefits and the control synthesis technique using SNAC, two problems have been solved with the AC and SNAC approaches and their computational performances are compared. One of these problems is a real-life Micro-Electro-Mechanical-system (MEMS) problem, which demonstrates that the SNAC technique is applicable to complex engineering systems.

Supporting Student Learning in Computer Science Education via the Adaptive Learning Environment ALMA

Directory of Open Access Journals (Sweden)

Alexandra Gasparinatou

2015-10-01

Full Text Available This study presents the ALMA environment (Adaptive Learning Models from texts and Activities. ALMA supports the processes of learning and assessment via: (1 texts differing in local and global cohesion for students with low, medium, and high background knowledge; (2 activities corresponding to different levels of comprehension which prompt the student to practically implement different text-reading strategies, with the recommended activity sequence adapted to the student’s learning style; (3 an overall framework for informing, guiding, and supporting students in performing the activities; and; (4 individualized support and guidance according to student specific characteristics. ALMA also, supports students in distance learning or in blended learning in which students are submitted to face-to-face learning supported by computer technology. The adaptive techniques provided via ALMA are: (a adaptive presentation and (b adaptive navigation. Digital learning material, in accordance with the text comprehension model described by Kintsch, was introduced into the ALMA environment. This material can be exploited in either distance or blended learning.

An automatic dose verification system for adaptive radiotherapy for helical tomotherapy

International Nuclear Information System (INIS)

Mo, Xiaohu; Chen, Mingli; Parnell, Donald; Olivera, Gustavo; Galmarini, Daniel; Lu, Weiguo

2014-01-01

Purpose: During a typical 5-7 week treatment of external beam radiotherapy, there are potential differences between planned patient's anatomy and positioning, such as patient weight loss, or treatment setup. The discrepancies between planned and delivered doses resulting from these differences could be significant, especially in IMRT where dose distributions tightly conforms to target volumes while avoiding organs-at-risk. We developed an automatic system to monitor delivered dose using daily imaging. Methods: For each treatment, a merged image is generated by registering the daily pre-treatment setup image and planning CT using treatment position information extracted from the Tomotherapy archive. The treatment dose is then computed on this merged image using our in-house convolution-superposition based dose calculator implemented on GPU. The deformation field between merged and planning CT is computed using the Morphon algorithm. The planning structures and treatment doses are subsequently warped for analysis and dose accumulation. All results are saved in DICOM format with private tags and organized in a database. Due to the overwhelming amount of information generated, a customizable tolerance system is used to flag potential treatment errors or significant anatomical changes. A web-based system and a DICOM-RT viewer were developed for reporting and reviewing the results. Results: More than 30 patients were analysed retrospectively. Our in-house dose calculator passed 97% gamma test evaluated with 2% dose difference and 2mm distance-to-agreement compared with Tomotherapy calculated dose, which is considered sufficient for adaptive radiotherapy purposes. Evaluation of the deformable registration through visual inspection showed acceptable and consistent results, except for cases with large or unrealistic deformation. Our automatic flagging system was able to catch significant patient setup errors or anatomical changes. Conclusions: We developed an automatic

Web-based computer adaptive assessment of individual perceptions of job satisfaction for hospital workplace employees.

Science.gov (United States)

Chien, Tsair-Wei; Lai, Wen-Pin; Lu, Chih-Wei; Wang, Weng-Chung; Chen, Shih-Chung; Wang, Hsien-Yi; Su, Shih-Bin

2011-04-17

To develop a web-based computer adaptive testing (CAT) application for efficiently collecting data regarding workers' perceptions of job satisfaction, we examined whether a 37-item Job Content Questionnaire (JCQ-37) could evaluate the job satisfaction of individual employees as a single construct. The JCQ-37 makes data collection via CAT on the internet easy, viable and fast. A Rasch rating scale model was applied to analyze data from 300 randomly selected hospital employees who participated in job-satisfaction surveys in 2008 and 2009 via non-adaptive and computer-adaptive testing, respectively. Of the 37 items on the questionnaire, 24 items fit the model fairly well. Person-separation reliability for the 2008 surveys was 0.88. Measures from both years and item-8 job satisfaction for groups were successfully evaluated through item-by-item analyses by using t-test. Workers aged 26 - 35 felt that job satisfaction was significantly worse in 2009 than in 2008. A Web-CAT developed in the present paper was shown to be more efficient than traditional computer-based or pen-and-paper assessments at collecting data regarding workers' perceptions of job content.

Web-based computer adaptive assessment of individual perceptions of job satisfaction for hospital workplace employees

Directory of Open Access Journals (Sweden)

Chen Shih-Chung

2011-04-01

Full Text Available Abstract Background To develop a web-based computer adaptive testing (CAT application for efficiently collecting data regarding workers' perceptions of job satisfaction, we examined whether a 37-item Job Content Questionnaire (JCQ-37 could evaluate the job satisfaction of individual employees as a single construct. Methods The JCQ-37 makes data collection via CAT on the internet easy, viable and fast. A Rasch rating scale model was applied to analyze data from 300 randomly selected hospital employees who participated in job-satisfaction surveys in 2008 and 2009 via non-adaptive and computer-adaptive testing, respectively. Results Of the 37 items on the questionnaire, 24 items fit the model fairly well. Person-separation reliability for the 2008 surveys was 0.88. Measures from both years and item-8 job satisfaction for groups were successfully evaluated through item-by-item analyses by using t-test. Workers aged 26 - 35 felt that job satisfaction was significantly worse in 2009 than in 2008. Conclusions A Web-CAT developed in the present paper was shown to be more efficient than traditional computer-based or pen-and-paper assessments at collecting data regarding workers' perceptions of job content.

Model-Based Design of Adaptive Embedded Systems

NARCIS (Netherlands)

Basten, T.; Hamberg, R.; Reckers, F.; Verriet, J.

2013-01-01

Today’s embedded systems have to operate in a wide variety of dynamically changing environmental circumstances. Adaptivity, the ability of a system to autonomously adapt itself, is a means to optimise a system’s behaviour to accommodate changes in its environment. It involves making in-product

Adaptive control system having hedge unit and related apparatus and methods

Science.gov (United States)

Johnson, Eric Norman (Inventor); Calise, Anthony J. (Inventor)

2007-01-01

The invention includes an adaptive control system used to control a plant. The adaptive control system includes a hedge unit that receives at least one control signal and a plant state signal. The hedge unit generates a hedge signal based on the control signal, the plant state signal, and a hedge model including a first model having one or more characteristics to which the adaptive control system is not to adapt, and a second model not having the characteristic(s) to which the adaptive control system is not to adapt. The hedge signal is used in the adaptive control system to remove the effect of the characteristic from a signal supplied to an adaptation law unit of the adaptive control system so that the adaptive control system does not adapt to the characteristic in controlling the plant.

Research Summary 3-D Computational Fluid Dynamics (CFD) Model Of The Human Respiratory System

Science.gov (United States)

The U.S. EPA’s Office of Research and Development (ORD) has developed a 3-D computational fluid dynamics (CFD) model of the human respiratory system that allows for the simulation of particulate based contaminant deposition and clearance, while being adaptable for age, ethnicity,...

Adaptive Dynamic Surface Control for Generator Excitation Control System

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Zhang Xiu-yu

2014-01-01

Full Text Available For the generator excitation control system which is equipped with static var compensator (SVC and unknown parameters, a novel adaptive dynamic surface control scheme is proposed based on neural network and tracking error transformed function with the following features: (1 the transformation of the excitation generator model to the linear systems is omitted; (2 the prespecified performance of the tracking error can be guaranteed by combining with the tracking error transformed function; (3 the computational burden is greatly reduced by estimating the norm of the weighted vector of neural network instead of the weighted vector itself; therefore, it is more suitable for the real time control; and (4 the explosion of complicity problem inherent in the backstepping control can be eliminated. It is proved that the new scheme can make the system semiglobally uniformly ultimately bounded. Simulation results show the effectiveness of this control scheme.

Contrast adaptation in the Limulus lateral eye

OpenAIRE

Valtcheva, Tchoudomira M.; Passaglia, Christopher L.

2015-01-01

Luminance and contrast adaptation are neuronal mechanisms employed by the visual system to adjust our sensitivity to light. They are mediated by an assortment of cellular and network processes distributed across the retina and visual cortex. Both have been demonstrated in the eyes of many vertebrates, but only luminance adaptation has been shown in invertebrate eyes to date. Since the computational benefits of contrast adaptation should apply to all visual systems, we investigated whether thi...

Managing Schools as Complex Adaptive Systems: A Strategic Perspective

Science.gov (United States)

Fidan, Tuncer; Balci, Ali

2017-01-01

This conceptual study examines the analogies between schools and complex adaptive systems and identifies strategies used to manage schools as complex adaptive systems. Complex adaptive systems approach, introduced by the complexity theory, requires school administrators to develop new skills and strategies to realize their agendas in an…

Adapting a computer-delivered brief alcohol intervention for veterans with Hepatitis C.

Science.gov (United States)

Cucciare, Michael A; Jamison, Andrea L; Combs, Ann S; Joshi, Gauri; Cheung, Ramsey C; Rongey, Catherine; Huggins, Joe; Humphreys, Keith

2017-12-01

This study adapted an existing computer-delivered brief alcohol intervention (cBAI) for use in Veterans with the hepatitis C virus (HCV) and examined its acceptability and feasibility in this patient population. A four-stage model consisting of initial pilot testing, qualitative interviews with key stakeholders, development of a beta version of the cBAI, and usability testing was used to achieve the study objectives. In-depth interviews gathered feedback for modifying the cBAI, including adding HCV-related content such as the health effects of alcohol on liver functioning, immune system functioning, and management of HCV, a preference for concepts to be displayed through "newer looking" graphics, and limiting the use of text to convey key concepts. Results from usability testing indicated that the modified cBAI was acceptable and feasible for use in this patient population. The development model used in this study is effective for gathering actionable feedback that can inform the development of a cBAI and can result in the development of an acceptable and feasible intervention for use in this population. Findings also have implications for developing computer-delivered interventions targeting behavior change more broadly.

Intricacies of Feedback in Computer-based Prism Adaptation Therapy

DEFF Research Database (Denmark)

Wilms, Inge Linda; Rytter, Hana Malá

Prism Adaptation Therapy (PAT) is an intervention method for treatment of attentional disorders, such as neglect e.g. 1,2. The method involves repeated pointing at specified targets with or without prism glasses using a specifically designed wooden box. The aim of this study was to ascertain...... whether the PAT method can be executed with similar effect using a computer with a touch screen.   62 healthy subjects were subjected to two experimental conditions: 1) pointing out at targets using the original box, 2) pointing out at targets on a computer attached touch screen. In both conditions......, the subjects performed a pre-test consisting of 30 targets without feedback, then an exposure-test of 90 targets with prism glasses and feedback, and finally a post-test of 60 targets, with no glasses and no feedback. Two experiments were carried out, 1) the feedback was provided by showing a cross...

Selective Adaptive Parallel Interference Cancellation for Multicarrier DS-CDMA Systems

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Ahmed El-Sayed El-Mahdy

2013-07-01

Full Text Available In this paper, Selective Adaptive Parallel Interference Cancellation (SA-PIC technique is presented for Multicarrier Direct Sequence Code Division Multiple Access (MC DS-CDMA scheme. The motivation of using SA-PIC is that it gives high performance and at the same time, reduces the computational complexity required to perform interference cancellation. An upper bound expression of the bit error rate (BER for the SA-PIC under Rayleigh fading channel condition is derived. Moreover, the implementation complexities for SA-PIC and Adaptive Parallel Interference Cancellation (APIC are discussed and compared. The performance of SA-PIC is investigated analytically and validated via computer simulations.

Are We Measuring Teachers’ Attitudes towards Computers in Detail?: Adaptation of a Questionnaire into Turkish Culture

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Nilgün Günbaş

2017-04-01

Full Text Available Teachers’ perceptions of computers play an important role in integrating computers into education. The related literature includes studies developing or adapting a survey instrument in Turkish culture measuring teachers’ attitudes toward computers. These instruments have three to four factors (e.g., computer importance, computer enjoyment, computer confidence and 18 to 26 items under these factors. The purpose of the present study is to adapt a more detailed and stronger survey questionnaire measuring more dimensions related to teachers’ attitudes. The source instrument was developed by Christensen and Kenzek (2009 and called Teachers’ Attitudes toward Computers (TAC. It has nine factors with 51 items. Before testing the instrument, the interaction (e-mail factor was taken out because of the cultural differences. The reliability and validity testing of the translated instrument was completed with 273 teachers’ candidates in a Faculty of Education in Turkey. The results showed that the translated instrument (Cronbach’s Alpha: .94 included eight factors and consisted of 42 items under these factors, which were consistent with the original instrument. These factors were: Interest (α: .83, Comfort (α: .90, Accommodation (α: .87, Concern (α: .79, Utility (α: .90, Perception (α: .89, Absorption (α: .84, and Significance (α: .83. Additionally, the confirmatory factor analysis result for the model with eight factors was: RMSEA=0.050, χ2/df=1.69, RMR=0.075, SRMR=0.057, GFI= 0.81, AGFI= 0.78, NFI= 0.94, NNFI=0.97, CFI=0.97, IFI= 0.97. Accordingly, as a reliable, valid and stronger instrument, the adapted survey instrument can be suggested for the use in Turkish academic studies.

FREQUENCY OPTIMIZATION FOR SECURITY MONITORING OF COMPUTER SYSTEMS

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Вogatyrev V.A.

2015-03-01

Full Text Available The subject areas of the proposed research are monitoring facilities for protection of computer systems exposed to destructive attacks of accidental and malicious nature. The interval optimization model of test monitoring for the detection of hazardous states of security breach caused by destructive attacks is proposed. Optimization function is to maximize profit in case of requests servicing in conditions of uncertainty, and intensity variance of the destructive attacks including penalties when servicing of requests is in dangerous conditions. The vector task of system availability maximization and minimization of probabilities for its downtime and dangerous conditions is proposed to be reduced to the scalar optimization problem based on the criterion of profit maximization from information services (service of requests that integrates these private criteria. Optimization variants are considered with the definition of the averaged periodic activities of monitoring and adapting of these periods to the changes in the intensity of destructive attacks. Adaptation efficiency of the monitoring frequency to changes in the activity of the destructive attacks is shown. The proposed solutions can find their application for optimization of test monitoring intervals to detect hazardous conditions of security breach that makes it possible to increase the system effectiveness, and specifically, to maximize the expected profit from information services.

A Charrelation Matrix-Based Blind Adaptive Detector for DS-CDMA Systems

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Zhongqiang Luo

2015-08-01

Full Text Available In this paper, a blind adaptive detector is proposed for blind separation of user signals and blind estimation of spreading sequences in DS-CDMA systems. The blind separation scheme exploits a charrelation matrix for simple computation and effective extraction of information from observation signal samples. The system model of DS-CDMA signals is modeled as a blind separation framework. The unknown user information and spreading sequence of DS-CDMA systems can be estimated only from the sampled observation signals. Theoretical analysis and simulation results show that the improved performance of the proposed algorithm in comparison with the existing conventional algorithms used in DS-CDMA systems. Especially, the proposed scheme is suitable for when the number of observation samples is less and the signal to noise ratio (SNR is low.

A Charrelation Matrix-Based Blind Adaptive Detector for DS-CDMA Systems.

Science.gov (United States)

Luo, Zhongqiang; Zhu, Lidong

2015-08-14

In this paper, a blind adaptive detector is proposed for blind separation of user signals and blind estimation of spreading sequences in DS-CDMA systems. The blind separation scheme exploits a charrelation matrix for simple computation and effective extraction of information from observation signal samples. The system model of DS-CDMA signals is modeled as a blind separation framework. The unknown user information and spreading sequence of DS-CDMA systems can be estimated only from the sampled observation signals. Theoretical analysis and simulation results show that the improved performance of the proposed algorithm in comparison with the existing conventional algorithms used in DS-CDMA systems. Especially, the proposed scheme is suitable for when the number of observation samples is less and the signal to noise ratio (SNR) is low.

Interactive computer enhanced remote viewing system

International Nuclear Information System (INIS)

Smith, D.A.; Tourtellott, J.A.

1994-01-01

The Interactive, Computer Enhanced, Remote Viewing System (ICERVSA) is a volumetric data system designed to help the Department of Energy (DOE) improve remote operations in hazardous sites by providing reliable and accurate maps of task spaces where robots will clean up nuclear wastes. The ICERVS mission is to acquire, store, integrate and manage all the sensor data for a site and to provide the necessary tools to facilitate its visualization and interpretation. Empirical sensor data enters through the Common Interface for Sensors and after initial processing, is stored in the Volumetric Database. The data can be analyzed and displayed via a Graphic User Interface with a variety of visualization tools. Other tools permit the construction of geometric objects, such as wire frame models, to represent objects which the operator may recognize in the live TV image. A computer image can be generated that matches the viewpoint of the live TV camera at the remote site, facilitating access to site data. Lastly, the data can be gathered, processed, and transmitted in acceptable form to a robotic controller. Descriptions are given of all these components. The final phase of the ICERVS project, which has just begun, will produce a full scale system and demonstrate it at a DOE site to be selected. A task added to this Phase will adapt the ICERVS to meet the needs of the Dismantlement and Decommissioning (D and D) work at the Oak Ridge National Laboratory (ORNL)

Capability-based computer systems

CERN Document Server

Levy, Henry M

2014-01-01

Capability-Based Computer Systems focuses on computer programs and their capabilities. The text first elaborates capability- and object-based system concepts, including capability-based systems, object-based approach, and summary. The book then describes early descriptor architectures and explains the Burroughs B5000, Rice University Computer, and Basic Language Machine. The text also focuses on early capability architectures. Dennis and Van Horn's Supervisor; CAL-TSS System; MIT PDP-1 Timesharing System; and Chicago Magic Number Machine are discussed. The book then describes Plessey System 25

Adaptive Hypermedia Systems for E-Learning

Directory of Open Access Journals (Sweden)

Aammou Souhaib

2010-11-01

Full Text Available The domain of traditional hypermedia is revolutionized by the arrival of the concept of adaptation. Currently the domain of Adaptive Hypermedia Systems (AHS is constantly growing. A major goal of current research is to provide a personalized educational experience that meets the needs specific to each learner (knowledge level, goals, motivation etc.... In this article we have studied the possibility of implementing traditional features of adaptive hypermedia in an open environment, and discussed the standards for describing learning objects and architectural models based on the use of ontologies as a prerequisite for such an adaptation.

Managing adaptively for multifunctionality in agricultural systems.

Science.gov (United States)

Hodbod, Jennifer; Barreteau, Olivier; Allen, Craig; Magda, Danièle

2016-12-01

The critical importance of agricultural systems for food security and as a dominant global landcover requires management that considers the full dimensions of system functions at appropriate scales, i.e. multifunctionality. We propose that adaptive management is the most suitable management approach for such goals, given its ability to reduce uncertainty over time and support multiple objectives within a system, for multiple actors. As such, adaptive management may be the most appropriate method for sustainably intensifying production whilst increasing the quantity and quality of ecosystem services. However, the current assessment of performance of agricultural systems doesn't reward ecosystem service provision. Therefore, we present an overview of the ecosystem functions agricultural systems should and could provide, coupled with a revised definition for assessing the performance of agricultural systems from a multifunctional perspective that, when all satisfied, would create adaptive agricultural systems that can increase production whilst ensuring food security and the quantity and quality of ecosystem services. The outcome of this high level of performance is the capacity to respond to multiple shocks without collapse, equity and triple bottom line sustainability. Through the assessment of case studies, we find that alternatives to industrialized agricultural systems incorporate more functional goals, but that there are mixed findings as to whether these goals translate into positive measurable outcomes. We suggest that an adaptive management perspective would support the implementation of a systematic analysis of the social, ecological and economic trade-offs occurring within such systems, particularly between ecosystem services and functions, in order to provide suitable and comparable assessments. We also identify indicators to monitor performance at multiple scales in agricultural systems which can be used within an adaptive management framework to increase

Managing adaptively for multifunctionality in agricultural systems

Science.gov (United States)

Hodbod, Jennifer; Barreteau, Olivier; Allen, Craig R.; Magda, Danièle

2016-01-01

The critical importance of agricultural systems for food security and as a dominant global landcover requires management that considers the full dimensions of system functions at appropriate scales, i.e. multifunctionality. We propose that adaptive management is the most suitable management approach for such goals, given its ability to reduce uncertainty over time and support multiple objectives within a system, for multiple actors. As such, adaptive management may be the most appropriate method for sustainably intensifying production whilst increasing the quantity and quality of ecosystem services. However, the current assessment of performance of agricultural systems doesn’t reward ecosystem service provision. Therefore, we present an overview of the ecosystem functions agricultural systems should and could provide, coupled with a revised definition for assessing the performance of agricultural systems from a multifunctional perspective that, when all satisfied, would create adaptive agricultural systems that can increase production whilst ensuring food security and the quantity and quality of ecosystem services. The outcome of this high level of performance is the capacity to respond to multiple shocks without collapse, equity and triple bottom line sustainability. Through the assessment of case studies, we find that alternatives to industrialized agricultural systems incorporate more functional goals, but that there are mixed findings as to whether these goals translate into positive measurable outcomes. We suggest that an adaptive management perspective would support the implementation of a systematic analysis of the social, ecological and economic trade-offs occurring within such systems, particularly between ecosystem services and functions, in order to provide suitable and comparable assessments. We also identify indicators to monitor performance at multiple scales in agricultural systems which can be used within an adaptive management framework to

Encoder-decoder optimization for brain-computer interfaces.

Science.gov (United States)

Merel, Josh; Pianto, Donald M; Cunningham, John P; Paninski, Liam

2015-06-01

Neuroprosthetic brain-computer interfaces are systems that decode neural activity into useful control signals for effectors, such as a cursor on a computer screen. It has long been recognized that both the user and decoding system can adapt to increase the accuracy of the end effector. Co-adaptation is the process whereby a user learns to control the system in conjunction with the decoder adapting to learn the user's neural patterns. We provide a mathematical framework for co-adaptation and relate co-adaptation to the joint optimization of the user's control scheme ("encoding model") and the decoding algorithm's parameters. When the assumptions of that framework are respected, co-adaptation cannot yield better performance than that obtainable by an optimal initial choice of fixed decoder, coupled with optimal user learning. For a specific case, we provide numerical methods to obtain such an optimized decoder. We demonstrate our approach in a model brain-computer interface system using an online prosthesis simulator, a simple human-in-the-loop pyschophysics setup which provides a non-invasive simulation of the BCI setting. These experiments support two claims: that users can learn encoders matched to fixed, optimal decoders and that, once learned, our approach yields expected performance advantages.

Encoder-decoder optimization for brain-computer interfaces.

Directory of Open Access Journals (Sweden)

Josh Merel

2015-06-01

Full Text Available Neuroprosthetic brain-computer interfaces are systems that decode neural activity into useful control signals for effectors, such as a cursor on a computer screen. It has long been recognized that both the user and decoding system can adapt to increase the accuracy of the end effector. Co-adaptation is the process whereby a user learns to control the system in conjunction with the decoder adapting to learn the user's neural patterns. We provide a mathematical framework for co-adaptation and relate co-adaptation to the joint optimization of the user's control scheme ("encoding model" and the decoding algorithm's parameters. When the assumptions of that framework are respected, co-adaptation cannot yield better performance than that obtainable by an optimal initial choice of fixed decoder, coupled with optimal user learning. For a specific case, we provide numerical methods to obtain such an optimized decoder. We demonstrate our approach in a model brain-computer interface system using an online prosthesis simulator, a simple human-in-the-loop pyschophysics setup which provides a non-invasive simulation of the BCI setting. These experiments support two claims: that users can learn encoders matched to fixed, optimal decoders and that, once learned, our approach yields expected performance advantages.

Adaptive Multi-Agent Systems for Constrained Optimization

Science.gov (United States)

Macready, William; Bieniawski, Stefan; Wolpert, David H.

2004-01-01

Product Distribution (PD) theory is a new framework for analyzing and controlling distributed systems. Here we demonstrate its use for distributed stochastic optimization. First we review one motivation of PD theory, as the information-theoretic extension of conventional full-rationality game theory to the case of bounded rational agents. In this extension the equilibrium of the game is the optimizer of a Lagrangian of the (probability distribution of) the joint state of the agents. When the game in question is a team game with constraints, that equilibrium optimizes the expected value of the team game utility, subject to those constraints. The updating of the Lagrange parameters in the Lagrangian can be viewed as a form of automated annealing, that focuses the MAS more and more on the optimal pure strategy. This provides a simple way to map the solution of any constrained optimization problem onto the equilibrium of a Multi-Agent System (MAS). We present computer experiments involving both the Queen s problem and K-SAT validating the predictions of PD theory and its use for off-the-shelf distributed adaptive optimization.

Partial update least-square adaptive filtering

CERN Document Server

Xie, Bei

2014-01-01

Adaptive filters play an important role in the fields related to digital signal processing and communication, such as system identification, noise cancellation, channel equalization, and beamforming. In practical applications, the computational complexity of an adaptive filter is an important consideration. The Least Mean Square (LMS) algorithm is widely used because of its low computational complexity (O(N)) and simplicity in implementation. The least squares algorithms, such as Recursive Least Squares (RLS), Conjugate Gradient (CG), and Euclidean Direction Search (EDS), can converge faster a

Robust adaptive control for a hybrid solid oxide fuel cell system

Science.gov (United States)

Snyder, Steven

2011-12-01

Solid oxide fuel cells (SOFCs) are electrochemical energy conversion devices. They offer a number of advantages beyond those of most other fuel cells due to their high operating temperature (800-1000°C), such as internal reforming, heat as a byproduct, and faster reaction kinetics without precious metal catalysts. Mitigating fuel starvation and improving load-following capabilities of SOFC systems are conflicting control objectives. However, this can be resolved by the hybridization of the system with an energy storage device, such as an ultra-capacitor. In this thesis, a steady-state property of the SOFC is combined with an input-shaping method in order to address the issue of fuel starvation. Simultaneously, an overall adaptive system control strategy is employed to manage the energy sharing between the elements as well as to maintain the state-of-charge of the energy storage device. The adaptive control method is robust to errors in the fuel cell's fuel supply system and guarantees that the fuel cell current and ultra-capacitor state-of-charge approach their target values and remain uniformly, ultimately bounded about these target values. Parameter saturation is employed to guarantee boundedness of the parameters. The controller is validated through hardware-in-the-loop experiments as well as computer simulations.

Specialized Computer Systems for Environment Visualization

Science.gov (United States)

Al-Oraiqat, Anas M.; Bashkov, Evgeniy A.; Zori, Sergii A.

2018-06-01

The need for real time image generation of landscapes arises in various fields as part of tasks solved by virtual and augmented reality systems, as well as geographic information systems. Such systems provide opportunities for collecting, storing, analyzing and graphically visualizing geographic data. Algorithmic and hardware software tools for increasing the realism and efficiency of the environment visualization in 3D visualization systems are proposed. This paper discusses a modified path tracing algorithm with a two-level hierarchy of bounding volumes and finding intersections with Axis-Aligned Bounding Box. The proposed algorithm eliminates the branching and hence makes the algorithm more suitable to be implemented on the multi-threaded CPU and GPU. A modified ROAM algorithm is used to solve the qualitative visualization of reliefs' problems and landscapes. The algorithm is implemented on parallel systems—cluster and Compute Unified Device Architecture-networks. Results show that the implementation on MPI clusters is more efficient than Graphics Processing Unit/Graphics Processing Clusters and allows real-time synthesis. The organization and algorithms of the parallel GPU system for the 3D pseudo stereo image/video synthesis are proposed. With realizing possibility analysis on a parallel GPU-architecture of each stage, 3D pseudo stereo synthesis is performed. An experimental prototype of a specialized hardware-software system 3D pseudo stereo imaging and video was developed on the CPU/GPU. The experimental results show that the proposed adaptation of 3D pseudo stereo imaging to the architecture of GPU-systems is efficient. Also it accelerates the computational procedures of 3D pseudo-stereo synthesis for the anaglyph and anamorphic formats of the 3D stereo frame without performing optimization procedures. The acceleration is on average 11 and 54 times for test GPUs.

Global adaptation in networks of selfish components: emergent associative memory at the system scale.

Science.gov (United States)

Watson, Richard A; Mills, Rob; Buckley, C L

2011-01-01

In some circumstances complex adaptive systems composed of numerous self-interested agents can self-organize into structures that enhance global adaptation, efficiency, or function. However, the general conditions for such an outcome are poorly understood and present a fundamental open question for domains as varied as ecology, sociology, economics, organismic biology, and technological infrastructure design. In contrast, sufficient conditions for artificial neural networks to form structures that perform collective computational processes such as associative memory/recall, classification, generalization, and optimization are well understood. Such global functions within a single agent or organism are not wholly surprising, since the mechanisms (e.g., Hebbian learning) that create these neural organizations may be selected for this purpose; but agents in a multi-agent system have no obvious reason to adhere to such a structuring protocol or produce such global behaviors when acting from individual self-interest. However, Hebbian learning is actually a very simple and fully distributed habituation or positive feedback principle. Here we show that when self-interested agents can modify how they are affected by other agents (e.g., when they can influence which other agents they interact with), then, in adapting these inter-agent relationships to maximize their own utility, they will necessarily alter them in a manner homologous with Hebbian learning. Multi-agent systems with adaptable relationships will thereby exhibit the same system-level behaviors as neural networks under Hebbian learning. For example, improved global efficiency in multi-agent systems can be explained by the inherent ability of associative memory to generalize by idealizing stored patterns and/or creating new combinations of subpatterns. Thus distributed multi-agent systems can spontaneously exhibit adaptive global behaviors in the same sense, and by the same mechanism, as with the organizational

Self-Adaptive On-Chip System Based on Cross-Layer Adaptation Approach

Directory of Open Access Journals (Sweden)

Kais Loukil

2013-01-01

Full Text Available The emergence of mobile and battery operated multimedia systems and the diversity of supported applications mount new challenges in terms of design efficiency of these systems which must provide a maximum application quality of service (QoS in the presence of a dynamically varying environment. These optimization problems cannot be entirely solved at design time and some efficiency gains can be obtained at run-time by means of self-adaptivity. In this paper, we propose a new cross-layer hardware (HW/software (SW adaptation solution for embedded mobile systems. It supports application QoS under real-time and lifetime constraints via coordinated adaptation in the hardware, operating system (OS, and application layers. Our method relies on an original middleware solution used on both global and local managers. The global manager (GM handles large, long-term variations whereas the local manager (LM is used to guarantee real-time constraints. The GM acts in three layers whereas the LM acts in application and OS layers only. The main role of GM is to select the best configuration for each application to meet the constraints of the system and respect the preferences of the user. The proposed approach has been applied to a 3D graphics application and successfully implemented on an Altera FPGA.

A novel joint-processing adaptive nonlinear equalizer using a modular recurrent neural network for chaotic communication systems.

Science.gov (United States)

Zhao, Haiquan; Zeng, Xiangping; Zhang, Jiashu; Liu, Yangguang; Wang, Xiaomin; Li, Tianrui

2011-01-01

To eliminate nonlinear channel distortion in chaotic communication systems, a novel joint-processing adaptive nonlinear equalizer based on a pipelined recurrent neural network (JPRNN) is proposed, using a modified real-time recurrent learning (RTRL) algorithm. Furthermore, an adaptive amplitude RTRL algorithm is adopted to overcome the deteriorating effect introduced by the nesting process. Computer simulations illustrate that the proposed equalizer outperforms the pipelined recurrent neural network (PRNN) and recurrent neural network (RNN) equalizers. Copyright © 2010 Elsevier Ltd. All rights reserved.

Design and implementation of adaptive inverse control algorithm for a micro-hand control system

Directory of Open Access Journals (Sweden)

Wan-Cheng Wang

2014-01-01

Full Text Available The Letter proposes an online tuned adaptive inverse position control algorithm for a micro-hand. First, the configuration of the micro-hand is discussed. Next, a kinematic analysis of the micro-hand is investigated and then the relationship between the rotor position of micro-permanent magnet synchronous motor and the tip of the micro-finger is derived. After that, an online tuned adaptive inverse control algorithm, which includes an adaptive inverse model and an adaptive inverse control, is designed. The online tuned adaptive inverse control algorithm has better performance than the proportional–integral control algorithm does. In addition, to avoid damaging the object during the grasping process, an online force control algorithm is proposed here as well. An embedded micro-computer, cRIO-9024, is used to realise the whole position control algorithm and the force control algorithm by using software. As a result, the hardware circuit is very simple. Experimental results show that the proposed system can provide fast transient responses, good load disturbance responses, good tracking responses and satisfactory grasping responses.

Complete synchronization of uncertain chaotic systems via a single proportional adaptive controller: A comparative study

Energy Technology Data Exchange (ETDEWEB)

Ahmad, Israr, E-mail: iak-2000plus@yahoo.com; Saaban, Azizan Bin, E-mail: azizan.s@uum.edu.my; Ibrahim, Adyda Binti, E-mail: adyda@uum.edu.my [School of Quantitative Sciences, College of Arts & Sciences, UUM (Malaysia); Shahzad, Mohammad, E-mail: dmsinfinite@gmail.com [College of Applied Sciences Nizwa, Ministry of Higher Education, Sultanate of Oman (Oman)

2015-12-11

This paper addresses a comparative computational study on the synchronization quality, cost and converging speed for two pairs of identical chaotic and hyperchaotic systems with unknown time-varying parameters. It is assumed that the unknown time-varying parameters are bounded. Based on the Lyapunov stability theory and using the adaptive control method, a single proportional controller is proposed to achieve the goal of complete synchronizations. Accordingly, appropriate adaptive laws are designed to identify the unknown time-varying parameters. The designed control strategy is easy to implement in practice. Numerical simulations results are provided to verify the effectiveness of the proposed synchronization scheme.

Impact on Congestion and Fuel Consumption of a Cooperative Adaptive Cruise Control System with Lane-Level Position Estimation

Directory of Open Access Journals (Sweden)

Edgar Talavera

2018-01-01

Full Text Available In recent years, vehicular communications systems have evolved and allowed for the improvement of adaptive cruise control (ACC systems to make them cooperative (cooperative adaptive cruise control, CACC. Conventional ACC systems use sensors on the ego-vehicle, such as radar or computer vision, to generate their behavioral decisions. However, by having vehicle-to-X (V2X onboard communications, the need to incorporate perception in the vehicle is drastically reduced. Thus, in this paper a CACC solution is proposed that only uses communications to make its decisions with the help of previous road mapping. At the same time, a method to develop these maps is presented, combining the information of a computer vision system to correct the positions obtained from the navigation system. In addition, the cut-in and cut-out maneuvers for a CACC platoon are taken into account, showing the tests of these situations in real environments with instrumented vehicles. To show the potential of the system in a larger-scale implementation, simulations of the behavior are provided under dense traffic conditions where the positive impact on the reduction of traffic congestion and fuel consumption is appreciated.

Visual Cues for an Adaptive Expert System.

Science.gov (United States)

Miller, Helen B.

NCR (National Cash Register) Corporation is pursuing opportunities to make their point of sale (POS) terminals easy to use and easy to learn. To approach the goal of making the technology invisible to the user, NCR has developed an adaptive expert prototype system for a department store POS operation. The structure for the adaptive system, the…

Adaptive versus Non-Adaptive Security of Multi-Party Protocols

DEFF Research Database (Denmark)

Canetti, Ran; Damgård, Ivan Bjerre; Dziembowski, Stefan

2004-01-01

Security analysis of multi-party cryptographic protocols distinguishes between two types of adversarial settings: In the non-adaptive setting the set of corrupted parties is chosen in advance, before the interaction begins. In the adaptive setting the adversary chooses who to corrupt during...... the course of the computation. We study the relations between adaptive security (i.e., security in the adaptive setting) and nonadaptive security, according to two definitions and in several models of computation....

Relational adaptivity - enacting human-centric systems design

DEFF Research Database (Denmark)

Petersen, Kjell Yngve

2016-01-01

Human centered design approaches places the experiencing human at the center of concern, situated in relation to the dynamics of the environmental condition and the variables of the system of control and sensing. Taking the approach of enacted design methods to enforce the experience...... of the inhabitant as core in human-centered design solutions, the intelligence of the connected sensors is suggested to be developed as an actual learning and self-adjusting adaptive environment, where the adaptive system is part of a negotiation with users on the qualities of the environment. We will present...... a fully functional sketching environment for adaptive sensor-control systems, which enable integration of the complex situation of everyday activities and human well-being. The proposed sketching environment allows for the development of sensor systems related to lighting conditions and human occupancy...

Computer systems a programmer's perspective

CERN Document Server

Bryant, Randal E

2016-01-01

Computer systems: A Programmer’s Perspective explains the underlying elements common among all computer systems and how they affect general application performance. Written from the programmer’s perspective, this book strives to teach readers how understanding basic elements of computer systems and executing real practice can lead them to create better programs. Spanning across computer science themes such as hardware architecture, the operating system, and systems software, the Third Edition serves as a comprehensive introduction to programming. This book strives to create programmers who understand all elements of computer systems and will be able to engage in any application of the field--from fixing faulty software, to writing more capable programs, to avoiding common flaws. It lays the groundwork for readers to delve into more intensive topics such as computer architecture, embedded systems, and cybersecurity. This book focuses on systems that execute an x86-64 machine code, and recommends th...

Computing Adaptive Feature Weights with PSO to Improve Android Malware Detection

Directory of Open Access Journals (Sweden)

Yanping Xu

2017-01-01

Full Text Available Android malware detection is a complex and crucial issue. In this paper, we propose a malware detection model using a support vector machine (SVM method based on feature weights that are computed by information gain (IG and particle swarm optimization (PSO algorithms. The IG weights are evaluated based on the relevance between features and class labels, and the PSO weights are adaptively calculated to result in the best fitness (the performance of the SVM classification model. Moreover, to overcome the defects of basic PSO, we propose a new adaptive inertia weight method called fitness-based and chaotic adaptive inertia weight-PSO (FCAIW-PSO that improves on basic PSO and is based on the fitness and a chaotic term. The goal is to assign suitable weights to the features to ensure the best Android malware detection performance. The results of experiments indicate that the IG weights and PSO weights both improve the performance of SVM and that the performance of the PSO weights is better than that of the IG weights.

Computer interfacing of the unified systems for personnel supervising in nuclear units

International Nuclear Information System (INIS)

Staicu, M.

1997-01-01

The dosimetric supervising of the personnel working in nuclear units is based on the information supplied by: 1) the dosimetric data obtained by the method of thermoluminescence; 2) the dosimetric data obtained by the method of photo dosimetry: 3) the records from medical periodic control. To create a unified system of supervising the following elements were combined: a) an Automatic System of TLD Reading and Data Processing (SACDTL). The data from this system are transmitted 'on line' to the computer; b) the measuring line of the optical density of exposed dosimetric films. The interface achieved within the general ensemble SACDTL could be adapted to this line of measurement. The transmission of the data from the measurement line to the computer is made 'on line'; c) the medical surveillance data for each person transmitted 'off line' to the database computer. The unified system resulting from the unification of the three supervising systems will achieve the following general functions: - registering of the personnel working in the nuclear field; - recording the dosimetric data; - processing and presentation of the data; - issuing of measurement bulletins. Thus, by means of unified database, dosimetric intercomparison and correlative studies can be undertaken. (author)

Computer Operating System Maintenance.

Science.gov (United States)

1982-06-01

FACILITY The Computer Management Information Facility ( CMIF ) system was developed by Rapp Systems to fulfill the need at the CRF to record and report on...computer center resource usage and utilization. The foundation of the CMIF system is a System 2000 data base (CRFMGMT) which stores and permits access

Adaptive traffic control systems for urban networks

Directory of Open Access Journals (Sweden)

Radivojević Danilo

2017-01-01

Full Text Available Adaptive traffic control systems represent complex, but powerful tool for improvement of traffic flow conditions in locations or zones where applied. Many traffic agencies, especially those that have a large number of signalized intersections with high variability of the traffic demand, choose to apply some of the adaptive traffic control systems. However, those systems are manufactured and offered by multiple vendors (companies that are competing for the market share. Due to that fact, besides the information available from the vendors themselves, or the information from different studies conducted on different continents, very limited amount of information is available about the details how those systems are operating. The reason for that is the protecting of the intellectual property from plagiarism. The primary goal of this paper is to make a brief analysis of the functionalities, characteristics, abilities and results of the most recognized, but also less known adaptive traffic control systems to the professional public and other persons with interest in this subject.

Complex and Adaptive Dynamical Systems A Primer

CERN Document Server

Gros, Claudius

2011-01-01

We are living in an ever more complex world, an epoch where human actions can accordingly acquire far-reaching potentialities. Complex and adaptive dynamical systems are ubiquitous in the world surrounding us and require us to adapt to new realities and the way of dealing with them. This primer has been developed with the aim of conveying a wide range of "commons-sense" knowledge in the field of quantitative complex system science at an introductory level, providing an entry point to this both fascinating and vitally important subject. The approach is modular and phenomenology driven. Examples of emerging phenomena of generic importance treated in this book are: -- The small world phenomenon in social and scale-free networks. -- Phase transitions and self-organized criticality in adaptive systems. -- Life at the edge of chaos and coevolutionary avalanches resulting from the unfolding of all living. -- The concept of living dynamical systems and emotional diffusive control within cognitive system theory. Techn...

Complex and adaptive dynamical systems a primer

CERN Document Server

Gros, Claudius

2007-01-01

We are living in an ever more complex world, an epoch where human actions can accordingly acquire far-reaching potentialities. Complex and adaptive dynamical systems are ubiquitous in the world surrounding us and require us to adapt to new realities and the way of dealing with them. This primer has been developed with the aim of conveying a wide range of "commons-sense" knowledge in the field of quantitative complex system science at an introductory level, providing an entry point to this both fascinating and vitally important subject. The approach is modular and phenomenology driven. Examples of emerging phenomena of generic importance treated in this book are: -- The small world phenomenon in social and scale-free networks. -- Phase transitions and self-organized criticality in adaptive systems. -- Life at the edge of chaos and coevolutionary avalanches resulting from the unfolding of all living. -- The concept of living dynamical systems and emotional diffusive control within cognitive system theory. Techn...

Adaptive feedforward in the LANL rf control system

International Nuclear Information System (INIS)

Ziomek, C.D.

1992-01-01

This paper describes an adaptive feedforward system that corrects repetitive errors in the amplitude and phase of the RF field of a pulsed accelerator. High-frequency disturbances that are beyond the effective bandwidth of the RF field feedback control system can be eliminated with a feedforward system. Many RF field disturbances for a pulsed accelerator are repetitive, occurring at the same relative time in every pulse. This design employs digital signal processing hardware to adaptively determine and track the control signals required to eliminate the repetitive errors in the feedback control system. In order to provide the necessary high-frequency response, the adaptive feedforward hardware provides the calculated control signal prior to the repetitive disturbance that it corrects. This system has been demonstrated to reduce the transient disturbances caused by beam pulses. Furthermore, it has been shown to negate high-frequency phase and amplitude oscillations in a high-power klystron amplifier caused by PFN ripple on the high-voltage. The design and results of the adaptive feedforward system are presented

Towards a Pattern Language for Adaptive Web-Based Educational Systems

NARCIS (Netherlands)

Avgeriou, P.; Vogiatzis, D.; Tzanavari, A.; Retalis, S.

2004-01-01

Adaptive Web-based Educational Systems represent an emerging technology that provides a unique advantage over traditional Web-based Educational Systems; that is the ability to adapt to the user's needs, goals, preferences etc. Adaptive Web-based Educational Systems are increasingly becoming part of

Design Patterns in Adaptive Web-Based Educational Systems : An Overview

NARCIS (Netherlands)

Avgeriou, Paris; Vogiatzis, Dimitrios; Tzanavari, Aimilia; Retalis, Symeon

2004-01-01

Adaptive Web-based Educational Systems represent an emerging technology that provides a unique advantage over traditional Web-based Educational Systems; that is the ability to adapt to the user's needs, goals, preferences etc. Adaptive Web-based Educational Systems are increasingly becoming part of

Certification Considerations for Adaptive Systems

Science.gov (United States)

Bhattacharyya, Siddhartha; Cofer, Darren; Musliner, David J.; Mueller, Joseph; Engstrom, Eric

2015-01-01

Advanced capabilities planned for the next generation of aircraft, including those that will operate within the Next Generation Air Transportation System (NextGen), will necessarily include complex new algorithms and non-traditional software elements. These aircraft will likely incorporate adaptive control algorithms that will provide enhanced safety, autonomy, and robustness during adverse conditions. Unmanned aircraft will operate alongside manned aircraft in the National Airspace (NAS), with intelligent software performing the high-level decision-making functions normally performed by human pilots. Even human-piloted aircraft will necessarily include more autonomy. However, there are serious barriers to the deployment of new capabilities, especially for those based upon software including adaptive control (AC) and artificial intelligence (AI) algorithms. Current civil aviation certification processes are based on the idea that the correct behavior of a system must be completely specified and verified prior to operation. This report by Rockwell Collins and SIFT documents our comprehensive study of the state of the art in intelligent and adaptive algorithms for the civil aviation domain, categorizing the approaches used and identifying gaps and challenges associated with certification of each approach.

Opportunity for Realizing Ideal Computing System using Cloud Computing Model

OpenAIRE

Sreeramana Aithal; Vaikunth Pai T

2017-01-01

An ideal computing system is a computing system with ideal characteristics. The major components and their performance characteristics of such hypothetical system can be studied as a model with predicted input, output, system and environmental characteristics using the identified objectives of computing which can be used in any platform, any type of computing system, and for application automation, without making modifications in the form of structure, hardware, and software coding by an exte...

Method and system for training dynamic nonlinear adaptive filters which have embedded memory

Science.gov (United States)

Rabinowitz, Matthew (Inventor)

2002-01-01

Described herein is a method and system for training nonlinear adaptive filters (or neural networks) which have embedded memory. Such memory can arise in a multi-layer finite impulse response (FIR) architecture, or an infinite impulse response (IIR) architecture. We focus on filter architectures with separate linear dynamic components and static nonlinear components. Such filters can be structured so as to restrict their degrees of computational freedom based on a priori knowledge about the dynamic operation to be emulated. The method is detailed for an FIR architecture which consists of linear FIR filters together with nonlinear generalized single layer subnets. For the IIR case, we extend the methodology to a general nonlinear architecture which uses feedback. For these dynamic architectures, we describe how one can apply optimization techniques which make updates closer to the Newton direction than those of a steepest descent method, such as backpropagation. We detail a novel adaptive modified Gauss-Newton optimization technique, which uses an adaptive learning rate to determine both the magnitude and direction of update steps. For a wide range of adaptive filtering applications, the new training algorithm converges faster and to a smaller value of cost than both steepest-descent methods such as backpropagation-through-time, and standard quasi-Newton methods. We apply the algorithm to modeling the inverse of a nonlinear dynamic tracking system 5, as well as a nonlinear amplifier 6.

Real-time wavefront processors for the next generation of adaptive optics systems: a design and analysis

Science.gov (United States)

Truong, Tuan; Brack, Gary L.; Troy, Mitchell; Trinh, Thang; Shi, Fang; Dekany, Richard G.

2003-02-01

Adaptive optics (AO) systems currently under investigation will require at least two orders of magitude increase in the number of actuators, which in turn translates to effectively a 104 increase in compute latency. Since the performance of an AO system invariably improves as the compute latency decreases, it is important to study how today's computer systems will scale to address this expected increase in actuator utilization. This paper answers this question by characterizing the performance of a single deformable mirror (DM) Shack-Hartmann natural guide star AO system implemented on the present-generation digital signal processor (DSP) TMS320C6701 from Texas Instruments. We derive the compute latency of such a system in terms of a few basic parameters, such as the number of DM actuators, the number of data channels used to read out the camera pixels, the number of DSPs, the available memory bandwidth, as well as the inter-processor communication (IPC) bandwidth and the pixel transfer rate. We show how the results would scale for future systems that utilizes multiple DMs and guide stars. We demonstrate that the principal performance bottleneck of such a system is the available memory bandwidth of the processors and to lesser extent the IPC bandwidth. This paper concludes with suggestions for mitigating this bottleneck.

Adaptive oxide electronics: A review

Science.gov (United States)

Ha, Sieu D.; Ramanathan, Shriram

2011-10-01

Novel information processing techniques are being actively explored to overcome fundamental limitations associated with CMOS scaling. A new paradigm of adaptive electronic devices is emerging that may reshape the frontiers of electronics and enable new modalities. Creating systems that can learn and adapt to various inputs has generally been a complex algorithm problem in information science, albeit with wide-ranging and powerful applications from medical diagnosis to control systems. Recent work in oxide electronics suggests that it may be plausible to implement such systems at the device level, thereby drastically increasing computational density and power efficiency and expanding the potential for electronics beyond Boolean computation. Intriguing possibilities of adaptive electronics include fabrication of devices that mimic human brain functionality: the strengthening and weakening of synapses emulated by electrically, magnetically, thermally, or optically tunable properties of materials.In this review, we detail materials and device physics studies on functional metal oxides that may be utilized for adaptive electronics. It has been shown that properties, such as resistivity, polarization, and magnetization, of many oxides can be modified electrically in a non-volatile manner, suggesting that these materials respond to electrical stimulus similarly as a neural synapse. We discuss what device characteristics will likely be relevant for integration into adaptive platforms and then survey a variety of oxides with respect to these properties, such as, but not limited to, TaOx, SrTiO3, and Bi4-xLaxTi3O12. The physical mechanisms in each case are detailed and analyzed within the framework of adaptive electronics. We then review theoretically formulated and current experimentally realized adaptive devices with functional oxides, such as self-programmable logic and neuromorphic circuits. Finally, we speculate on what advances in materials physics and engineering may

Adaptive pseudolinear compensators of dynamic characteristics of automatic control systems

Science.gov (United States)

Skorospeshkin, M. V.; Sukhodoev, M. S.; Timoshenko, E. A.; Lenskiy, F. V.

2016-04-01

Adaptive pseudolinear gain and phase compensators of dynamic characteristics of automatic control systems are suggested. The automatic control system performance with adaptive compensators has been explored. The efficiency of pseudolinear adaptive compensators in the automatic control systems with time-varying parameters has been demonstrated.

Adaptive stimulus optimization and model-based experiments for sensory systems neuroscience

Directory of Open Access Journals (Sweden)

Christopher eDiMattina

2013-06-01

Full Text Available In this paper we review several lines of recent work aimed at developing practical methods for adaptive on-line stimulus generation for sensory neurophysiology. We consider various experimental paradigms where on-line stimulus optimization is utilized, including the classical textit{optimal stimulus} paradigm where the goal of experiments is to identify a stimulus which maximizes neural responses, the textit{iso-response} paradigm which finds sets of stimuli giving rise to constant responses, and the textit{system identification} paradigm where the experimental goal is to estimate and possibly compare sensory processing models. We discuss various theoretical and practical aspects of adaptive firing rate optimization, including optimization with stimulus space constraints, firing rate adaptation, and possible network constraints on the optimal stimulus. We consider the problem of system identification, and show how accurate estimation of nonlinear models can be highly dependent on the stimulus set used to probe the network. We suggest that optimizing stimuli for accurate model estimation may make it possible to successfully identify nonlinear models which are otherwise intractable, and summarize several recent studies of this type. Finally, we present a two-stage stimulus design procedure which combines the dual goals of model estimation and model comparison and may be especially useful for system identification experiments where the appropriate model is unknown beforehand. We propose that fast, on-line stimulus optimization enabled by increasing computer power can make it practical to move sensory neuroscience away from a descriptive paradigm and towards a new paradigm of real-time model estimation and comparison.

Adaptive Backstepping Sliding-Mode Control of the Electronic Throttle System in Modern Automobiles

Directory of Open Access Journals (Sweden)

Rui Bai

2014-01-01

Full Text Available In modern automobiles, electronic throttle is a DC-motor-driven valve that regulates air inflow into the vehicle’s combustion system. The electronic throttle is increasingly being used in order to improve the vehicle drivability, fuel economy, and emissions. Electronic throttle system has the nonlinear dynamical characteristics with the unknown disturbance and parameters. At first, the dynamical nonlinear model of the electronic throttle is built in this paper. Based on the model and using the backstepping design technique, a new adaptive backstepping sliding-mode controller of the electronic throttle is developed. During the backstepping design process, parameter adaptive law is designed to estimate the unknown parameter, and sliding-mode control term is applied to compensate the unknown disturbance. The proposed controller can make the actual angle of the electronic throttle track its set point with the satisfactory performance. Finally, a computer simulation is performed, and simulation results verify that the proposed control method can achieve favorable tracking performance.

A case study of evolutionary computation of biochemical adaptation

International Nuclear Information System (INIS)

François, Paul; Siggia, Eric D

2008-01-01

Simulations of evolution have a long history, but their relation to biology is questioned because of the perceived contingency of evolution. Here we provide an example of a biological process, adaptation, where simulations are argued to approach closer to biology. Adaptation is a common feature of sensory systems, and a plausible component of other biochemical networks because it rescales upstream signals to facilitate downstream processing. We create random gene networks numerically, by linking genes with interactions that model transcription, phosphorylation and protein–protein association. We define a fitness function for adaptation in terms of two functional metrics, and show that any reasonable combination of them will yield the same adaptive networks after repeated rounds of mutation and selection. Convergence to these networks is driven by positive selection and thus fast. There is always a path in parameter space of continuously improving fitness that leads to perfect adaptation, implying that the actual mutation rates we use in the simulation do not bias the results. Our results imply a kinetic view of evolution, i.e., it favors gene networks that can be learned quickly from the random examples supplied by mutation. This formulation allows for deductive predictions of the networks realized in nature

A dynamically adaptive wavelet approach to stochastic computations based on polynomial chaos - capturing all scales of random modes on independent grids

International Nuclear Information System (INIS)

Ren Xiaoan; Wu Wenquan; Xanthis, Leonidas S.

2011-01-01

Highlights: → New approach for stochastic computations based on polynomial chaos. → Development of dynamically adaptive wavelet multiscale solver using space refinement. → Accurate capture of steep gradients and multiscale features in stochastic problems. → All scales of each random mode are captured on independent grids. → Numerical examples demonstrate the need for different space resolutions per mode. - Abstract: In stochastic computations, or uncertainty quantification methods, the spectral approach based on the polynomial chaos expansion in random space leads to a coupled system of deterministic equations for the coefficients of the expansion. The size of this system increases drastically when the number of independent random variables and/or order of polynomial chaos expansions increases. This is invariably the case for large scale simulations and/or problems involving steep gradients and other multiscale features; such features are variously reflected on each solution component or random/uncertainty mode requiring the development of adaptive methods for their accurate resolution. In this paper we propose a new approach for treating such problems based on a dynamically adaptive wavelet methodology involving space-refinement on physical space that allows all scales of each solution component to be refined independently of the rest. We exemplify this using the convection-diffusion model with random input data and present three numerical examples demonstrating the salient features of the proposed method. Thus we establish a new, elegant and flexible approach for stochastic problems with steep gradients and multiscale features based on polynomial chaos expansions.

Adaptive Home System Using Wireless Sensor Network And Multi Agent System

OpenAIRE

Jayarani Kamble; Prof.Nandini Dhole

2014-01-01

Smart Home is an emerging technology growing continuously which includes number of new technologies which helps to improve human’s quality of living. This paper proposes an adaptive home system for optimum utilization of power, through Artificial Intelligence and Wireless Sensor network. Artificial Intelligence is a technology for developing adaptive system that can perceive the enviornmrnt, learn from the environment and can make decision using Rule based system.Zigbee is a w...

Efficient Skyline Computation in Structured Peer-to-Peer Systems

DEFF Research Database (Denmark)

Cui, Bin; Chen, Lijiang; Xu, Linhao

2009-01-01

An increasing number of large-scale applications exploit peer-to-peer network architecture to provide highly scalable and flexible services. Among these applications, data management in peer-to-peer systems is one of the interesting domains. In this paper, we investigate the multidimensional...... skyline computation problem on a structured peer-to-peer network. In order to achieve low communication cost and quick response time, we utilize the iMinMax(\\theta ) method to transform high-dimensional data to one-dimensional value and distribute the data in a structured peer-to-peer network called BATON....... Thereafter, we propose a progressive algorithm with adaptive filter technique for efficient skyline computation in this environment. We further discuss some optimization techniques for the algorithm, and summarize the key principles of our algorithm into a query routing protocol with detailed analysis...

Adaptive Iterative Soft-Input Soft-Output Parallel Decision-Feedback Detectors for Asynchronous Coded DS-CDMA Systems

Directory of Open Access Journals (Sweden)

Zhang Wei

2005-01-01

Full Text Available The optimum and many suboptimum iterative soft-input soft-output (SISO multiuser detectors require a priori information about the multiuser system, such as the users' transmitted signature waveforms, relative delays, as well as the channel impulse response. In this paper, we employ adaptive algorithms in the SISO multiuser detector in order to avoid the need for this a priori information. First, we derive the optimum SISO parallel decision-feedback detector for asynchronous coded DS-CDMA systems. Then, we propose two adaptive versions of this SISO detector, which are based on the normalized least mean square (NLMS and recursive least squares (RLS algorithms. Our SISO adaptive detectors effectively exploit the a priori information of coded symbols, whose soft inputs are obtained from a bank of single-user decoders. Furthermore, we consider how to select practical finite feedforward and feedback filter lengths to obtain a good tradeoff between the performance and computational complexity of the receiver.

Computer System Design System-on-Chip

CERN Document Server

Flynn, Michael J

2011-01-01

The next generation of computer system designers will be less concerned about details of processors and memories, and more concerned about the elements of a system tailored to particular applications. These designers will have a fundamental knowledge of processors and other elements in the system, but the success of their design will depend on the skills in making system-level tradeoffs that optimize the cost, performance and other attributes to meet application requirements. This book provides a new treatment of computer system design, particularly for System-on-Chip (SOC), which addresses th

Changing Paradigms: From Schooling to Schools as Adaptive Recommendation Systems

Science.gov (United States)

Petersen, Anne Kristine; Christiansen, Rene B.; Gynther, Karsten

2017-01-01

The paper explores a shift in education from educational systems requiring student adaptation to educational recommendation systems adapting to students' individual needs. The paper discusses the concept of adaptation as addressed in educational research and draws on the system theory of Heinz von Foerster to shed light on how the educational…

Reconstruction of sparse-view X-ray computed tomography using adaptive iterative algorithms.

Science.gov (United States)

Liu, Li; Lin, Weikai; Jin, Mingwu

2015-01-01

In this paper, we propose two reconstruction algorithms for sparse-view X-ray computed tomography (CT). Treating the reconstruction problems as data fidelity constrained total variation (TV) minimization, both algorithms adapt the alternate two-stage strategy: projection onto convex sets (POCS) for data fidelity and non-negativity constraints and steepest descent for TV minimization. The novelty of this work is to determine iterative parameters automatically from data, thus avoiding tedious manual parameter tuning. In TV minimization, the step sizes of steepest descent are adaptively adjusted according to the difference from POCS update in either the projection domain or the image domain, while the step size of algebraic reconstruction technique (ART) in POCS is determined based on the data noise level. In addition, projection errors are used to compare with the error bound to decide whether to perform ART so as to reduce computational costs. The performance of the proposed methods is studied and evaluated using both simulated and physical phantom data. Our methods with automatic parameter tuning achieve similar, if not better, reconstruction performance compared to a representative two-stage algorithm. Copyright © 2014 Elsevier Ltd. All rights reserved.

AK-SYS: An adaptation of the AK-MCS method for system reliability

International Nuclear Information System (INIS)

Fauriat, W.; Gayton, N.

2014-01-01

A lot of research work has been proposed over the last two decades to evaluate the probability of failure of a structure involving a very time-consuming mechanical model. Surrogate model approaches based on Kriging, such as the Efficient Global Reliability Analysis (EGRA) or the Active learning and Kriging-based Monte-Carlo Simulation (AK-MCS) methods, are very efficient and each has advantages of its own. EGRA is well suited to evaluating small probabilities, as the surrogate can be used to classify any population. AK-MCS is built in relation to a given population and requires no optimization program for the active learning procedure to be performed. It is therefore easier to implement and more likely to spend computational effort on areas with a significant probability content. When assessing system reliability, analytical approaches and first-order approximation are widely used in the literature. However, in the present paper we rather focus on sampling techniques and, considering the recent adaptation of the EGRA method for systems, a strategy is presented to adapt the AK-MCS method for system reliability. The AK-SYS method, “Active learning and Kriging-based SYStem reliability method”, is presented. Its high efficiency and accuracy are illustrated via various examples

ICAN Computer Code Adapted for Building Materials

Science.gov (United States)

Murthy, Pappu L. N.

1997-01-01

The NASA Lewis Research Center has been involved in developing composite micromechanics and macromechanics theories over the last three decades. These activities have resulted in several composite mechanics theories and structural analysis codes whose applications range from material behavior design and analysis to structural component response. One of these computer codes, the Integrated Composite Analyzer (ICAN), is designed primarily to address issues related to designing polymer matrix composites and predicting their properties - including hygral, thermal, and mechanical load effects. Recently, under a cost-sharing cooperative agreement with a Fortune 500 corporation, Master Builders Inc., ICAN was adapted to analyze building materials. The high costs and technical difficulties involved with the fabrication of continuous-fiber-reinforced composites sometimes limit their use. Particulate-reinforced composites can be thought of as a viable alternative. They are as easily processed to near-net shape as monolithic materials, yet have the improved stiffness, strength, and fracture toughness that is characteristic of continuous-fiber-reinforced composites. For example, particlereinforced metal-matrix composites show great potential for a variety of automotive applications, such as disk brake rotors, connecting rods, cylinder liners, and other hightemperature applications. Building materials, such as concrete, can be thought of as one of the oldest materials in this category of multiphase, particle-reinforced materials. The adaptation of ICAN to analyze particle-reinforced composite materials involved the development of new micromechanics-based theories. A derivative of the ICAN code, ICAN/PART, was developed and delivered to Master Builders Inc. as a part of the cooperative activity.

Sinusoidal error perturbation reveals multiple coordinate systems for sensorymotor adaptation.

Science.gov (United States)

Hudson, Todd E; Landy, Michael S

2016-02-01

A coordinate system is composed of an encoding, defining the dimensions of the space, and an origin. We examine the coordinate encoding used to update motor plans during sensory-motor adaptation to center-out reaches. Adaptation is induced using a novel paradigm in which feedback of reach endpoints is perturbed following a sinewave pattern over trials; the perturbed dimensions of the feedback were the axes of a Cartesian coordinate system in one session and a polar coordinate system in another session. For center-out reaches to randomly chosen target locations, reach errors observed at one target will require different corrections at other targets within Cartesian- and polar-coded systems. The sinewave adaptation technique allowed us to simultaneously adapt both dimensions of each coordinate system (x-y, or reach gain and angle), and identify the contributions of each perturbed dimension by adapting each at a distinct temporal frequency. The efficiency of this technique further allowed us to employ perturbations that were a fraction the size normally used, which avoids confounding automatic adaptive processes with deliberate adjustments made in response to obvious experimental manipulations. Subjects independently corrected errors in each coordinate in both sessions, suggesting that the nervous system encodes both a Cartesian- and polar-coordinate-based internal representation for motor adaptation. The gains and phase lags of the adaptive responses are not readily explained by current theories of sensory-motor adaptation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Adaptive control of Parkinson's state based on a nonlinear computational model with unknown parameters.

Science.gov (United States)

Su, Fei; Wang, Jiang; Deng, Bin; Wei, Xi-Le; Chen, Ying-Yuan; Liu, Chen; Li, Hui-Yan

2015-02-01

The objective here is to explore the use of adaptive input-output feedback linearization method to achieve an improved deep brain stimulation (DBS) algorithm for closed-loop control of Parkinson's state. The control law is based on a highly nonlinear computational model of Parkinson's disease (PD) with unknown parameters. The restoration of thalamic relay reliability is formulated as the desired outcome of the adaptive control methodology, and the DBS waveform is the control input. The control input is adjusted in real time according to estimates of unknown parameters as well as the feedback signal. Simulation results show that the proposed adaptive control algorithm succeeds in restoring the relay reliability of the thalamus, and at the same time achieves accurate estimation of unknown parameters. Our findings point to the potential value of adaptive control approach that could be used to regulate DBS waveform in more effective treatment of PD.

Autonomic intrusion detection: Adaptively detecting anomalies over unlabeled audit data streams in computer networks

KAUST Repository

Wang, Wei; Guyet, Thomas; Quiniou, René ; Cordier, Marie-Odile; Masseglia, Florent; Zhang, Xiangliang

2014-01-01

In this work, we propose a novel framework of autonomic intrusion detection that fulfills online and adaptive intrusion detection over unlabeled HTTP traffic streams in computer networks. The framework holds potential for self-managing: self-labeling, self-updating and self-adapting. Our framework employs the Affinity Propagation (AP) algorithm to learn a subject’s behaviors through dynamical clustering of the streaming data. It automatically labels the data and adapts to normal behavior changes while identifies anomalies. Two large real HTTP traffic streams collected in our institute as well as a set of benchmark KDD’99 data are used to validate the framework and the method. The test results show that the autonomic model achieves better results in terms of effectiveness and efficiency compared to adaptive Sequential Karhunen–Loeve method and static AP as well as three other static anomaly detection methods, namely, k-NN, PCA and SVM.

Autonomic intrusion detection: Adaptively detecting anomalies over unlabeled audit data streams in computer networks

KAUST Repository

Wang, Wei

2014-06-22

In this work, we propose a novel framework of autonomic intrusion detection that fulfills online and adaptive intrusion detection over unlabeled HTTP traffic streams in computer networks. The framework holds potential for self-managing: self-labeling, self-updating and self-adapting. Our framework employs the Affinity Propagation (AP) algorithm to learn a subject’s behaviors through dynamical clustering of the streaming data. It automatically labels the data and adapts to normal behavior changes while identifies anomalies. Two large real HTTP traffic streams collected in our institute as well as a set of benchmark KDD’99 data are used to validate the framework and the method. The test results show that the autonomic model achieves better results in terms of effectiveness and efficiency compared to adaptive Sequential Karhunen–Loeve method and static AP as well as three other static anomaly detection methods, namely, k-NN, PCA and SVM.

Application of Complex Adaptive Systems in Portfolio Management

Science.gov (United States)

Su, Zheyuan

2017-01-01

Simulation-based methods are becoming a promising research tool in financial markets. A general Complex Adaptive System can be tailored to different application scenarios. Based on the current research, we built two models that would benefit portfolio management by utilizing Complex Adaptive Systems (CAS) in Agent-based Modeling (ABM) approach.…

Adaptive Output Tracking Control for Nonlinear Systems with Failed Actuators and Aircraft Flight System Applications

OpenAIRE

Hou, Chuanjing; Hu, Lisheng; Zhang, Yingwei

2015-01-01

An adaptive failure compensation scheme using output feedback is proposed for a class of nonlinear systems with nonlinearities depending on the unmeasured states of systems. Adaptive high-gain K-filters are presented to suppress the nonlinearities while the proposed backstepping adaptive high-gain controller guarantees the stability of the closed-loop system and small tracking errors. Simulation results verify that the adaptive failure compensation scheme is effective.

Adaptation in the auditory system: an overview

Directory of Open Access Journals (Sweden)

David ePérez-González

2014-02-01

Full Text Available The early stages of the auditory system need to preserve the timing information of sounds in order to extract the basic features of acoustic stimuli. At the same time, different processes of neuronal adaptation occur at several levels to further process the auditory information. For instance, auditory nerve fiber responses already experience adaptation of their firing rates, a type of response that can be found in many other auditory nuclei and may be useful for emphasizing the onset of the stimuli. However, it is at higher levels in the auditory hierarchy where more sophisticated types of neuronal processing take place. For example, stimulus-specific adaptation, where neurons show adaptation to frequent, repetitive stimuli, but maintain their responsiveness to stimuli with different physical characteristics, thus representing a distinct kind of processing that may play a role in change and deviance detection. In the auditory cortex, adaptation takes more elaborate forms, and contributes to the processing of complex sequences, auditory scene analysis and attention. Here we review the multiple types of adaptation that occur in the auditory system, which are part of the pool of resources that the neurons employ to process the auditory scene, and are critical to a proper understanding of the neuronal mechanisms that govern auditory perception.

Applying computer adaptive testing to optimize online assessment of suicidal behavior: a simulation study.

NARCIS (Netherlands)

de Beurs, D.P.; de Vries, A.L.M.; de Groot, M.H.; de Keijser, J.; Kerkhof, A.J.F.M.

2014-01-01

Background: The Internet is used increasingly for both suicide research and prevention. To optimize online assessment of suicidal patients, there is a need for short, good-quality tools to assess elevated risk of future suicidal behavior. Computer adaptive testing (CAT) can be used to reduce

On Adaptive vs. Non-adaptive Security of Multiparty Protocols

DEFF Research Database (Denmark)

Canetti, Ran; Damgård, Ivan Bjerre; Dziembowski, Stefan

2001-01-01

highlights of our results are: – - According to the definition of Dodis-Micali-Rogaway (which is set in the information-theoretic model), adaptive and non-adaptive security are equivalent. This holds for both honest-but-curious and Byzantine adversaries, and for any number of parties. – - According......Security analysis of multiparty cryptographic protocols distinguishes between two types of adversarialsettings: In the non-adaptive setting, the set of corrupted parties is chosen in advance, before the interaction begins. In the adaptive setting, the adversary chooses who to corrupt during...... the course of the computation. We study the relations between adaptive security (i.e., security in the adaptive setting) and non-adaptive security, according to two definitions and in several models of computation. While affirming some prevailing beliefs, we also obtain some unexpected results. Some...

An interactive, multitask computer system for heavy-ion physics research with the spin spectrometer: [Progress report, 1982

International Nuclear Information System (INIS)

Sarantites, D.G.

1982-01-01

The scope of this proposal is to assemble an interactive off-line data analysis system based on a DEC VAX 11/780 computer interfaced with an array processor, which is capable of meeting the needs of modern heavy-ion physics experiments involving data of large dimensionality as created in the Spin Spectrometer at the Holifield Heavy-ion Research Facility, to adapt the existing PDP 11 software for the Spin Spectrometer for this computer system in a form completely compatible with other laboratories with VAX 11 computers, and to develop new general and efficient software for automatic but fully interactive data analysis making use of an attach array processor

Resilient computer system design

CERN Document Server

Castano, Victor

2015-01-01

This book presents a paradigm for designing new generation resilient and evolving computer systems, including their key concepts, elements of supportive theory, methods of analysis and synthesis of ICT with new properties of evolving functioning, as well as implementation schemes and their prototyping. The book explains why new ICT applications require a complete redesign of computer systems to address challenges of extreme reliability, high performance, and power efficiency. The authors present a comprehensive treatment for designing the next generation of computers, especially addressing safety-critical, autonomous, real time, military, banking, and wearable health care systems.   §  Describes design solutions for new computer system - evolving reconfigurable architecture (ERA) that is free from drawbacks inherent in current ICT and related engineering models §  Pursues simplicity, reliability, scalability principles of design implemented through redundancy and re-configurability; targeted for energy-,...

Verification and Validation Challenges for Adaptive Flight Control of Complex Autonomous Systems

Science.gov (United States)

Nguyen, Nhan T.

2018-01-01

Autonomy of aerospace systems requires the ability for flight control systems to be able to adapt to complex uncertain dynamic environment. In spite of the five decades of research in adaptive control, the fact still remains that currently no adaptive control system has ever been deployed on any safety-critical or human-rated production systems such as passenger transport aircraft. The problem lies in the difficulty with the certification of adaptive control systems since existing certification methods cannot readily be used for nonlinear adaptive control systems. Research to address the notion of metrics for adaptive control began to appear in the recent years. These metrics, if accepted, could pave a path towards certification that would potentially lead to the adoption of adaptive control as a future control technology for safety-critical and human-rated production systems. Development of certifiable adaptive control systems represents a major challenge to overcome. Adaptive control systems with learning algorithms will never become part of the future unless it can be proven that they are highly safe and reliable. Rigorous methods for adaptive control software verification and validation must therefore be developed to ensure that adaptive control system software failures will not occur, to verify that the adaptive control system functions as required, to eliminate unintended functionality, and to demonstrate that certification requirements imposed by regulatory bodies such as the Federal Aviation Administration (FAA) can be satisfied. This presentation will discuss some of the technical issues with adaptive flight control and related V&V challenges.

Adaptive architectures for resilient control of networked multiagent systems in the presence of misbehaving agents

Science.gov (United States)

Torre, Gerardo De La; Yucelen, Tansel

2018-03-01

Control algorithms of networked multiagent systems are generally computed distributively without having a centralised entity monitoring the activity of agents; and therefore, unforeseen adverse conditions such as uncertainties or attacks to the communication network and/or failure of agent-wise components can easily result in system instability and prohibit the accomplishment of system-level objectives. In this paper, we study resilient coordination of networked multiagent systems in the presence of misbehaving agents, i.e. agents that are subject to exogenous disturbances that represent a class of adverse conditions. In particular, a distributed adaptive control architecture is presented for directed and time-varying graph topologies to retrieve a desired networked multiagent system behaviour. Apart from the existing relevant literature that make specific assumptions on the graph topology and/or the fraction of misbehaving agents, we show that the considered class of adverse conditions can be mitigated by the proposed adaptive control approach that utilises a local state emulator - even if all agents are misbehaving. Illustrative numerical examples are provided to demonstrate the theoretical findings.

Attacks on computer systems

Directory of Open Access Journals (Sweden)

Dejan V. Vuletić

2012-01-01

Full Text Available Computer systems are a critical component of the human society in the 21st century. Economic sector, defense, security, energy, telecommunications, industrial production, finance and other vital infrastructure depend on computer systems that operate at local, national or global scales. A particular problem is that, due to the rapid development of ICT and the unstoppable growth of its application in all spheres of the human society, their vulnerability and exposure to very serious potential dangers increase. This paper analyzes some typical attacks on computer systems.

Adaptive Systems in Education: A Review and Conceptual Unification

Science.gov (United States)

Wilson, Chunyu; Scott, Bernard

2017-01-01

Purpose: The purpose of this paper is to review the use of adaptive systems in education. It is intended to be a useful introduction for the non-specialist reader. Design/methodology/approach: A distinction is made between intelligent tutoring systems (ITSs) and adaptive hypermedia systems (AHSs). The two kinds of system are defined, compared and…

Adaptive Output Tracking Control for Nonlinear Systems with Failed Actuators and Aircraft Flight System Applications

Directory of Open Access Journals (Sweden)

Chuanjing Hou

2015-01-01

Full Text Available An adaptive failure compensation scheme using output feedback is proposed for a class of nonlinear systems with nonlinearities depending on the unmeasured states of systems. Adaptive high-gain K-filters are presented to suppress the nonlinearities while the proposed backstepping adaptive high-gain controller guarantees the stability of the closed-loop system and small tracking errors. Simulation results verify that the adaptive failure compensation scheme is effective.

End-User Recommendations on LOGOMON - a Computer Based Speech Therapy System for Romanian Language

Directory of Open Access Journals (Sweden)

SCHIPOR, O. A.

2010-11-01

Full Text Available In this paper we highlight the relations between LOGOMON - a Computer Based Speech Therapy System and dyslalia's training steps. Dyslalia is a speech disorder that affects pronunciation of one or many sounds. This presentation of the system is completed by a research regarding end-user (i.e. teachers and parents attitude about the speech assisted therapy in general and about LOGOMON System in particular. The results of this research allow the improvement of our CBST system because the obtained information can be a source of adaptability to different expectations of the beneficiaries.

Adaptive control of bifurcation and chaos in a time-delayed system

International Nuclear Information System (INIS)

Li Ning; Zhang Qing-Ling; Yuan Hui-Qun; Sun Hai-Yi

2013-01-01

In this paper, the stabilization of a continuous time-delayed system is considered. To control the bifurcation and chaos in a time-delayed system, a parameter perturbation control and a hybrid control are proposed. Then, to ensure the asymptotic stability of the system in the presence of unexpected system parameter changes, the adaptive control idea is introduced, i.e., the perturbation control parameter and the hybrid control parameter are automatically tuned according to the adaptation laws, respectively. The adaptation algorithms are constructed based on the Lyapunov-Krasovskii stability theorem. The adaptive parameter perturbation control and the adaptive hybrid control methods improve the corresponding constant control methods. They have the advantages of increased stability, adaptability to the changes of the system parameters, control cost saving, and simplicity. Numerical simulations for a well-known chaotic time-delayed system are performed to demonstrate the feasibility and superiority of the proposed control methods. A comparison of the two adaptive control methods is also made in an experimental study

A Conceptual Architecture for Adaptive Human-Computer Interface of a PT Operation Platform Based on Context-Awareness

Directory of Open Access Journals (Sweden)

Qing Xue

2014-01-01

Full Text Available We present a conceptual architecture for adaptive human-computer interface of a PT operation platform based on context-awareness. This architecture will form the basis of design for such an interface. This paper describes components, key technologies, and working principles of the architecture. The critical contents covered context information modeling, processing, relationship establishing between contexts and interface design knowledge by use of adaptive knowledge reasoning, and visualization implementing of adaptive interface with the aid of interface tools technology.

Adaptive Step Size Gradient Ascent ICA Algorithm for Wireless MIMO Systems

Directory of Open Access Journals (Sweden)

Zahoor Uddin

2018-01-01

Full Text Available Independent component analysis (ICA is a technique of blind source separation (BSS used for separation of the mixed received signals. ICA algorithms are classified into adaptive and batch algorithms. Adaptive algorithms perform well in time-varying scenario with high-computational complexity, while batch algorithms have better separation performance in quasistatic channels with low-computational complexity. Amongst batch algorithms, the gradient-based ICA algorithms perform well, but step size selection is critical in these algorithms. In this paper, an adaptive step size gradient ascent ICA (ASS-GAICA algorithm is presented. The proposed algorithm is free from selection of the step size parameter with improved convergence and separation performance. Different performance evaluation criteria are used to verify the effectiveness of the proposed algorithm. Performance of the proposed algorithm is compared with the FastICA and optimum block adaptive ICA (OBAICA algorithms for quasistatic and time-varying wireless channels. Simulation is performed over quadrature amplitude modulation (QAM and binary phase shift keying (BPSK signals. Results show that the proposed algorithm outperforms the FastICA and OBAICA algorithms for a wide range of signal-to-noise ratio (SNR and input data block lengths.

Adaptive Synchronization of Memristor-based Chaotic Neural Systems

Directory of Open Access Journals (Sweden)

Xiaofang Hu

2014-11-01

Full Text Available Chaotic neural networks consisting of a great number of chaotic neurons are able to reproduce the rich dynamics observed in biological nervous systems. In recent years, the memristor has attracted much interest in the efficient implementation of artificial synapses and neurons. This work addresses adaptive synchronization of a class of memristor-based neural chaotic systems using a novel adaptive backstepping approach. A systematic design procedure is presented. Simulation results have demonstrated the effectiveness of the proposed adaptive synchronization method and its potential in practical application of memristive chaotic oscillators in secure communication.

A hydraulic hybrid propulsion method for automobiles with self-adaptive system

International Nuclear Information System (INIS)

Wu, Wei; Hu, Jibin; Yuan, Shihua; Di, Chongfeng

2016-01-01

A hydraulic hybrid vehicle with the self-adaptive system is proposed. The mode-switching between the driving mode and the hydraulic regenerative braking mode is realised by the pressure cross-feedback control. Extensive simulated and tested results are presented. The control parameters are reduced and the energy efficiency can be increased by the self-adaptive system. The mode-switching response is fast. The response time can be adjusted by changing the controlling spool diameter of the hydraulic operated check valve in the self-adaptive system. The closing of the valve becomes faster with a smaller controlling spool diameter. The hydraulic regenerative braking mode can be achieved by changing the hydraulic transformer controlled angle. Compared with the convention electric-hydraulic system, the self-adaptive system for the hydraulic hybrid vehicle mode-switching has a higher reliability and a lower cost. The efficiency of the hydraulic regenerative braking is also increased. - Highlights: • A new hybrid system with a self-adaptive system for automobiles is presented. • The mode-switching is realised by the pressure cross-feedback control. • The energy efficiency can be increased with the self-adaptive system. • The control parameters are reduced with the self-adaptive system.

Adaptive mechanism-based congestion control for networked systems

Science.gov (United States)

Liu, Zhi; Zhang, Yun; Chen, C. L. Philip

2013-03-01

In order to assure the communication quality in network systems with heavy traffic and limited bandwidth, a new ATRED (adaptive thresholds random early detection) congestion control algorithm is proposed for the congestion avoidance and resource management of network systems. Different to the traditional AQM (active queue management) algorithms, the control parameters of ATRED are not configured statically, but dynamically adjusted by the adaptive mechanism. By integrating with the adaptive strategy, ATRED alleviates the tuning difficulty of RED (random early detection) and shows a better control on the queue management, and achieve a more robust performance than RED under varying network conditions. Furthermore, a dynamic transmission control protocol-AQM control system using ATRED controller is introduced for the systematic analysis. It is proved that the stability of the network system can be guaranteed when the adaptive mechanism is finely designed. Simulation studies show the proposed ATRED algorithm achieves a good performance in varying network environments, which is superior to the RED and Gentle-RED algorithm, and providing more reliable service under varying network conditions.

Adaptive PI Controller for a Nonlinear System

Directory of Open Access Journals (Sweden)

D. Rathikarani

2009-10-01

Full Text Available Most of the industrial processes are inherently nonlinear in their behaviour. Designs of controllers for these nonlinear processes are difficult, as they do not follow superposition theorem. Adaptive controller can change its behaviour in response to changes in the dynamics of the process and disturbances. Hence adaptive controller can be used to control nonlinear processes. Direct Model Reference Adaptive Control is a technique, in which a reference model involving the desired performances is specified. In the present work, a DMRAC is designed and implemented to achieve satisfactory control of a nonlinear system in all its local linear operating regions. The closed loop system is made BIBO stable by proper control techniques. The controller is designed through simulation in Matlab platform and is validated in real time by conducting experiments on the laboratory Air Flow Control System using the dSPACE interface.

New computer systems

International Nuclear Information System (INIS)

Faerber, G.

1975-01-01

Process computers have already become indespensable technical aids for monitoring and automation tasks in nuclear power stations. Yet there are still some problems connected with their use whose elimination should be the main objective in the development of new computer systems. In the paper, some of these problems are summarized, new tendencies in hardware development are outlined, and finally some new systems concepts made possible by the hardware development are explained. (orig./AK) [de

Fundamentals of Adaptive Intelligent Tutoring Systems for Self-Regulated Learning

Science.gov (United States)

2015-03-01

ARL-SR-0318 ● MAR 2015 US Army Research Laboratory Fundamentals of Adaptive Intelligent Tutoring Systems for Self-Regulated...Adaptive Intelligent Tutoring Systems for Self-Regulated Learning by Robert A Sottilare Human Research and Engineering Directorate, ARL...TITLE AND SUBTITLE Fundamentals of Adaptive Intelligent Tutoring Systems for Self-Regulated Learning 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c

Adaptive, full-spectrum solar energy system

Science.gov (United States)

Muhs, Jeffrey D.; Earl, Dennis D.

2003-08-05

An adaptive full spectrum solar energy system having at least one hybrid solar concentrator, at least one hybrid luminaire, at least one hybrid photobioreactor, and a light distribution system operably connected to each hybrid solar concentrator, each hybrid luminaire, and each hybrid photobioreactor. A lighting control system operates each component.

Evaluation framework based on fuzzy measured method in adaptive learning systems

OpenAIRE

Houda Zouari Ounaies, ,; Yassine Jamoussi; Henda Hajjami Ben Ghezala

2008-01-01

Currently, e-learning systems are mainly web-based applications and tackle a wide range of users all over the world. Fitting learners’ needs is considered as a key issue to guaranty the success of these systems. Many researches work on providing adaptive systems. Nevertheless, evaluation of the adaptivity is still in an exploratory phase. Adaptation methods are a basic factor to guaranty an effective adaptation. This issue is referred as meta-adaptation in numerous researches. In our research...

Adaptive processes in economic systems

CERN Document Server

Murphy, Roy E

1965-01-01

In this book, we study theoretical and practical aspects of computing methods for mathematical modelling of nonlinear systems. A number of computing techniques are considered, such as methods of operator approximation with any given accuracy; operator interpolation techniques including a non-Lagrange interpolation; methods of system representation subject to constraints associated with concepts of causality, memory and stationarity; methods of system representation with an accuracy that is the best within a given class of models; methods of covariance matrix estimation;. methods for low-rank m

Novel Fuzzy-Modeling-Based Adaptive Synchronization of Nonlinear Dynamic Systems

Directory of Open Access Journals (Sweden)

Shih-Yu Li

2017-01-01

Full Text Available In this paper, a novel fuzzy-model-based adaptive synchronization scheme and its fuzzy update laws of parameters are proposed to address the adaptive synchronization problem. The proposed fuzzy controller does not share the same premise of fuzzy system, and the numbers of fuzzy controllers is reduced effectively through the novel modeling strategy. In addition, based on the adaptive synchronization scheme, the error dynamic system can be guaranteed to be asymptotically stable and the true values of unknown parameters can be obtained. Two identical complicated dynamic systems, Mathieu-Van der pol system (M-V system with uncertainties, are illustrated for numerical simulation example to show the effectiveness and feasibility of the proposed novel adaptive control strategy.

Adaptive Hypermedia Educational System Based on XML Technologies.

Science.gov (United States)

Baek, Yeongtae; Wang, Changjong; Lee, Sehoon

This paper proposes an adaptive hypermedia educational system using XML technologies, such as XML, XSL, XSLT, and XLink. Adaptive systems are capable of altering the presentation of the content of the hypermedia on the basis of a dynamic understanding of the individual user. The user profile can be collected in a user model, while the knowledge…

Water System Adaptation To Hydrological Changes: Module 6, Synchronous Management of Storm Surge, Sea Level Rise, and Salt Water Intrusion: Case Study in Mattapoisett, Massachusetts, U.S.A.

Science.gov (United States)

This course will introduce students to the fundamental principles of water system adaptation to hydrological changes, with emphasis on data analysis and interpretation, technical planning, and computational modeling. Starting with real-world scenarios and adaptation needs, the co...

Belle computing system

International Nuclear Information System (INIS)

Adachi, Ichiro; Hibino, Taisuke; Hinz, Luc; Itoh, Ryosuke; Katayama, Nobu; Nishida, Shohei; Ronga, Frederic; Tsukamoto, Toshifumi; Yokoyama, Masahiko

2004-01-01

We describe the present status of the computing system in the Belle experiment at the KEKB e+e- asymmetric-energy collider. So far, we have logged more than 160fb-1 of data, corresponding to the world's largest data sample of 170M BB-bar pairs at the -bar (4S) energy region. A large amount of event data has to be processed to produce an analysis event sample in a timely fashion. In addition, Monte Carlo events have to be created to control systematic errors accurately. This requires stable and efficient usage of computing resources. Here, we review our computing model and then describe how we efficiently proceed DST/MC productions in our system

Adaptive process triage system cannot identify patients with gastrointestinal perforation

DEFF Research Database (Denmark)

Bohm, Aske Mathias; Tolstrup, Mai-Britt; Gögenur, Ismail

2017-01-01

INTRODUCTION: Adaptive process triage (ADAPT) is a triage tool developed to assess the severity and address the priority of emergency patients. In 2009-2011, ADAPT was the most frequently used triage system in Denmark. Until now, no Danish triage system has been evaluated based on a selective group...... triaged as green or yellow had a GIP that was not identified by the triage system. CONCLUSION: ADAPT is incapable of identifying one of the most critically ill patient groups in need of emergency abdominal surgery. FUNDING: none. TRIAL REGISTRATION: HEH-2013-034 I-Suite: 02336....

Bacterial computing: a form of natural computing and its applications.

Science.gov (United States)

Lahoz-Beltra, Rafael; Navarro, Jorge; Marijuán, Pedro C

2014-01-01

The capability to establish adaptive relationships with the environment is an essential characteristic of living cells. Both bacterial computing and bacterial intelligence are two general traits manifested along adaptive behaviors that respond to surrounding environmental conditions. These two traits have generated a variety of theoretical and applied approaches. Since the different systems of bacterial signaling and the different ways of genetic change are better known and more carefully explored, the whole adaptive possibilities of bacteria may be studied under new angles. For instance, there appear instances of molecular "learning" along the mechanisms of evolution. More in concrete, and looking specifically at the time dimension, the bacterial mechanisms of learning and evolution appear as two different and related mechanisms for adaptation to the environment; in somatic time the former and in evolutionary time the latter. In the present chapter it will be reviewed the possible application of both kinds of mechanisms to prokaryotic molecular computing schemes as well as to the solution of real world problems.

Petascale Computational Systems

OpenAIRE

Bell, Gordon; Gray, Jim; Szalay, Alex

2007-01-01

Computational science is changing to be data intensive. Super-Computers must be balanced systems; not just CPU farms but also petascale IO and networking arrays. Anyone building CyberInfrastructure should allocate resources to support a balanced Tier-1 through Tier-3 design.

Adaptive self-correcting control system

International Nuclear Information System (INIS)

Ellis, S.H.

1984-01-01

A control system for regulating a controlled device or process, such as a turbofan engine, produces independent multiple estimates of one or more controlled variables of the device or process by combining the signals from a plurality of feedback sensors, which provide information related to the controlled variables, in weighted nonordered pairs. The independent multiple estimates of each controlled variable are combined into a weighted average, and individual estimates which differ by more than a specified amount from the weighted average are edited and temporarily removed from consideration. A revised weighted average value of each controlled variable is then produced, and this value is used to limit or control operation of the device or process. Adaptive trim is provided to compensate for changes in the device or process being controlled, such as engine deterioration, by slowly trimming each individual estimate toward the mean, and includes error compensation which constrains the weighted sum of the adaptive trims to equal zero, thereby preventing the adaptive trim from changing the operating level of the device or process. A secondary editing circuit based on a majority rule principle identifies a failed feedback sensor and permanently excludes all individual estimates of the controlled variable based on the failed sensor. Editing boundaries are increased and adaptive trim rate is varied when a transient occurs in the operation of the device or process. Further transient compensation may be required for a system with more severe transient requirements, and this invention includes compensation to selected feedback parameters such as turbine temperature to account for differences between steady state and transient values

Potential of Cognitive Computing and Cognitive Systems

Science.gov (United States)

Noor, Ahmed K.

2015-01-01

Cognitive computing and cognitive technologies are game changers for future engineering systems, as well as for engineering practice and training. They are major drivers for knowledge automation work, and the creation of cognitive products with higher levels of intelligence than current smart products. This paper gives a brief review of cognitive computing and some of the cognitive engineering systems activities. The potential of cognitive technologies is outlined, along with a brief description of future cognitive environments, incorporating cognitive assistants - specialized proactive intelligent software agents designed to follow and interact with humans and other cognitive assistants across the environments. The cognitive assistants engage, individually or collectively, with humans through a combination of adaptive multimodal interfaces, and advanced visualization and navigation techniques. The realization of future cognitive environments requires the development of a cognitive innovation ecosystem for the engineering workforce. The continuously expanding major components of the ecosystem include integrated knowledge discovery and exploitation facilities (incorporating predictive and prescriptive big data analytics); novel cognitive modeling and visual simulation facilities; cognitive multimodal interfaces; and cognitive mobile and wearable devices. The ecosystem will provide timely, engaging, personalized / collaborative, learning and effective decision making. It will stimulate creativity and innovation, and prepare the participants to work in future cognitive enterprises and develop new cognitive products of increasing complexity. http://www.aee.odu.edu/cognitivecomp

Adaptation of MPDATA Heterogeneous Stencil Computation to Intel Xeon Phi Coprocessor

Directory of Open Access Journals (Sweden)

Lukasz Szustak

2015-01-01

Full Text Available The multidimensional positive definite advection transport algorithm (MPDATA belongs to the group of nonoscillatory forward-in-time algorithms and performs a sequence of stencil computations. MPDATA is one of the major parts of the dynamic core of the EULAG geophysical model. In this work, we outline an approach to adaptation of the 3D MPDATA algorithm to the Intel MIC architecture. In order to utilize available computing resources, we propose the (3 + 1D decomposition of MPDATA heterogeneous stencil computations. This approach is based on combination of the loop tiling and fusion techniques. It allows us to ease memory/communication bounds and better exploit the theoretical floating point efficiency of target computing platforms. An important method of improving the efficiency of the (3 + 1D decomposition is partitioning of available cores/threads into work teams. It permits for reducing inter-cache communication overheads. This method also increases opportunities for the efficient distribution of MPDATA computation onto available resources of the Intel MIC architecture, as well as Intel CPUs. We discuss preliminary performance results obtained on two hybrid platforms, containing two CPUs and Intel Xeon Phi. The top-of-the-line Intel Xeon Phi 7120P gives the best performance results, and executes MPDATA almost 2 times faster than two Intel Xeon E5-2697v2 CPUs.

Adaptive Finite Element Method Assisted by Stochastic Simulation of Chemical Systems

KAUST Repository

Cotter, Simon L.; Vejchodský , Tomá š; Erban, Radek

2013-01-01

Stochastic models of chemical systems are often analyzed by solving the corresponding Fokker-Planck equation, which is a drift-diffusion partial differential equation for the probability distribution function. Efficient numerical solution of the Fokker-Planck equation requires adaptive mesh refinements. In this paper, we present a mesh refinement approach which makes use of a stochastic simulation of the underlying chemical system. By observing the stochastic trajectory for a relatively short amount of time, the areas of the state space with nonnegligible probability density are identified. By refining the finite element mesh in these areas, and coarsening elsewhere, a suitable mesh is constructed and used for the computation of the stationary probability density. Numerical examples demonstrate that the presented method is competitive with existing a posteriori methods. © 2013 Society for Industrial and Applied Mathematics.

Joint Adaptive Modulation and Combining for Hybrid FSO/RF Systems

KAUST Repository

Rakia, Tamer

2015-11-12

In this paper, we present and analyze a new transmission scheme for hybrid FSO/RF communication system based on joint adaptive modulation and adaptive combining. Specifically, the data rate on the FSO link is adjusted in discrete manner according to the FSO link\\'s instantaneous received signal-to-noise-ratio (SNR). If the FSO link\\'s quality is too poor to maintain the target bit-error-rate, the system activates the RF link along with the FSO link. When the RF link is activated, simultaneous transmission of the same modulated data takes place on both links, where the received signals from both links are combined using maximal ratio combining scheme. In this case, the data rate of the system is adjusted according to the instantaneous combined SNRs. Novel analytical expression for the cumulative distribution function (CDF) of the received SNR for the proposed adaptive hybrid system is obtained. This CDF expression is used to study the spectral and outage performances of the proposed adaptive hybrid FSO/RF system. Numerical examples are presented to compare the performance of the proposed adaptive hybrid FSO/RF system with that of switch-over hybrid FSO/RF and FSO-only systems employing the same adaptive modulation schemes. © 2015 IEEE.

Computationally efficient video restoration for Nyquist sampled imaging sensors combining an affine-motion-based temporal Kalman filter and adaptive Wiener filter.

Science.gov (United States)

Rucci, Michael; Hardie, Russell C; Barnard, Kenneth J

2014-05-01

In this paper, we present a computationally efficient video restoration algorithm to address both blur and noise for a Nyquist sampled imaging system. The proposed method utilizes a temporal Kalman filter followed by a correlation-model based spatial adaptive Wiener filter (AWF). The Kalman filter employs an affine background motion model and novel process-noise variance estimate. We also propose and demonstrate a new multidelay temporal Kalman filter designed to more robustly treat local motion. The AWF is a spatial operation that performs deconvolution and adapts to the spatially varying residual noise left in the Kalman filter stage. In image areas where the temporal Kalman filter is able to provide significant noise reduction, the AWF can be aggressive in its deconvolution. In other areas, where less noise reduction is achieved with the Kalman filter, the AWF balances the deconvolution with spatial noise reduction. In this way, the Kalman filter and AWF work together effectively, but without the computational burden of full joint spatiotemporal processing. We also propose a novel hybrid system that combines a temporal Kalman filter and BM3D processing. To illustrate the efficacy of the proposed methods, we test the algorithms on both simulated imagery and video collected with a visible camera.

Expert-systems and computer-based industrial systems

International Nuclear Information System (INIS)

Terrien, J.F.

1987-01-01

Framatome makes wide use of expert systems, computer-assisted engineering, production management and personnel training. It has set up separate business units and subsidiaries and also participates in other companies which have the relevant expertise. Five examples of the products and services available in these are discussed. These are in the field of applied artificial intelligence and expert-systems, in integrated computer-aid design and engineering, structural analysis, computer-related products and services and document management systems. The structure of the companies involved and the work they are doing is discussed. (UK)

Development of an Adaptable Display and Diagnostic System for the Evaluation of Tropical Cyclone Forecasts

Science.gov (United States)

Kucera, P. A.; Burek, T.; Halley-Gotway, J.

2015-12-01

NCAR's Joint Numerical Testbed Program (JNTP) focuses on the evaluation of experimental forecasts of tropical cyclones (TCs) with the goal of developing new research tools and diagnostic evaluation methods that can be transitioned to operations. Recent activities include the development of new TC forecast verification methods and the development of an adaptable TC display and diagnostic system. The next generation display and diagnostic system is being developed to support evaluation needs of the U.S. National Hurricane Center (NHC) and broader TC research community. The new hurricane display and diagnostic capabilities allow forecasters and research scientists to more deeply examine the performance of operational and experimental models. The system is built upon modern and flexible technology that includes OpenLayers Mapping tools that are platform independent. The forecast track and intensity along with associated observed track information are stored in an efficient MySQL database. The system provides easy-to-use interactive display system, and provides diagnostic tools to examine forecast track stratified by intensity. Consensus forecasts can be computed and displayed interactively. The system is designed to display information for both real-time and for historical TC cyclones. The display configurations are easily adaptable to meet the needs of the end-user preferences. Ongoing enhancements include improving capabilities for stratification and evaluation of historical best tracks, development and implementation of additional methods to stratify and compute consensus hurricane track and intensity forecasts, and improved graphical display tools. The display is also being enhanced to incorporate gridded forecast, satellite, and sea surface temperature fields. The presentation will provide an overview of the display and diagnostic system development and demonstration of the current capabilities.

Computational Intelligence Agent-Oriented Modelling

Czech Academy of Sciences Publication Activity Database

Neruda, Roman

2006-01-01

Roč. 5, č. 2 (2006), s. 430-433 ISSN 1109-2777 R&D Projects: GA MŠk 1M0567 Institutional research plan: CEZ:AV0Z10300504 Keywords : multi-agent systems * adaptive agents * computational intelligence Subject RIV: IN - Informatics, Computer Science

Adaptive Control Of Remote Manipulator

Science.gov (United States)

Seraji, Homayoun

1989-01-01

Robotic control system causes remote manipulator to follow closely reference trajectory in Cartesian reference frame in work space, without resort to computationally intensive mathematical model of robot dynamics and without knowledge of robot and load parameters. System, derived from linear multivariable theory, uses relatively simple feedforward and feedback controllers with model-reference adaptive control.

Simulated climate adaptation in storm-water systems: Evaluating the efficiency of within-system flexibility

Directory of Open Access Journals (Sweden)

Adam D. McCurdy

Full Text Available Changes in regional temperature and precipitation patterns resulting from global climate change may adversely affect the performance of long-lived infrastructure. Adaptation may be necessary to ensure that infrastructure offers consistent service and remains cost effective. But long service times and deep uncertainty associated with future climate projections make adaptation decisions especially challenging for managers. Incorporating flexibility into systems can increase their effectiveness across different climate futures but can also add significant costs. In this paper we review existing work on flexibility in climate change adaptation of infrastructure, such as robust decision-making and dynamic adaptive pathways, apply a basic typology of flexibility, and test alternative strategies for flexibility in distributed infrastructure systems comprised of multiple emplacements of a common, long-lived element: roadway culverts. Rather than treating a system of dispersed infrastructure elements as monolithic, we simulate “options flexibility” in which inherent differences in individual elements is incorporated into adaptation decisions. We use a virtual testbed of highway drainage crossing structures to examine the performance under different climate scenarios of policies that allow for multiple adaptation strategies with varying timing based on individual emplacement characteristics. Results indicate that a strategy with options flexibility informed by crossing characteristics offers a more efficient method of adaptation than do monolithic policies. In some cases this results in more cost-effective adaptation for agencies building long-lived, climate-sensitive infrastructure, even where detailed system data and analytical capacity is limited. Keywords: Climate adaptation, Stormwater management, Adaptation pathways

Adaptive neuro-fuzzy and expert systems for power quality analysis and prediction of abnormal operation

Science.gov (United States)

Ibrahim, Wael Refaat Anis

The present research involves the development of several fuzzy expert systems for power quality analysis and diagnosis. Intelligent systems for the prediction of abnormal system operation were also developed. The performance of all intelligent modules developed was either enhanced or completely produced through adaptive fuzzy learning techniques. Neuro-fuzzy learning is the main adaptive technique utilized. The work presents a novel approach to the interpretation of power quality from the perspective of the continuous operation of a single system. The research includes an extensive literature review pertaining to the applications of intelligent systems to power quality analysis. Basic definitions and signature events related to power quality are introduced. In addition, detailed discussions of various artificial intelligence paradigms as well as wavelet theory are included. A fuzzy-based intelligent system capable of identifying normal from abnormal operation for a given system was developed. Adaptive neuro-fuzzy learning was applied to enhance its performance. A group of fuzzy expert systems that could perform full operational diagnosis were also developed successfully. The developed systems were applied to the operational diagnosis of 3-phase induction motors and rectifier bridges. A novel approach for learning power quality waveforms and trends was developed. The technique, which is adaptive neuro fuzzy-based, learned, compressed, and stored the waveform data. The new technique was successfully tested using a wide variety of power quality signature waveforms, and using real site data. The trend-learning technique was incorporated into a fuzzy expert system that was designed to predict abnormal operation of a monitored system. The intelligent system learns and stores, in compressed format, trends leading to abnormal operation. The system then compares incoming data to the retained trends continuously. If the incoming data matches any of the learned trends, an

Adaptive feed forward in the LANL RF control system

International Nuclear Information System (INIS)

Ziomek, C.D.

1992-01-01

This paper describes an adaptive feed forward system that corrects repetitive errors in the amplitude and phase of the RF field of a pulsed accelerator. High-frequency disturbances that are beyond the effective bandwidth of the RF-field feedback control system can be eliminated with a feed forward system. Many RF-field disturbances for a pulsed accelerator are repetitive, occurring at the same relative time in every pulse. This design employs digital signal processing hardware to adaptively determine and track the control signals required to eliminate the repetitive errors in the feedback control system. In order to provide the necessary high-frequency response, the adaptive feed forward hardware provides the calculated control signal prior to the repetitive disturbance that it corrects. This system has been demonstrated to reduce the transient disturbances caused by beam pulses. Furthermore, it has been shown to negate high-frequency phase and amplitude oscillations in a high-power klystron amplifier caused by PFN ripple on the high-voltage. The design and results of the adaptive feed forward system are presented. (Author) 3 figs., 2 refs

Decentralized Adaptive Overcurrent Protection for Medium Voltage Maritime Power Systems

DEFF Research Database (Denmark)

Ciontea, Catalin-Iosif; Bak, Claus Leth; Blaabjerg, Frede

2016-01-01

the entire electrical network and changes the relay settings accordingly, but this approach is not adequate for the maritime power systems. This paper propose a decentralized adaptive protection method, where each protection relay is able to identify by itself the network status without the need of a central...... control unit. The new adaptive protection method is based on communication between the overcurrent relays and the equipment that could affect the protection system, such as circuit breakers and generators. Using PSCAD, the proposed method is implemented in a test medium voltage maritime power system......More and more maritime applications as marine vessels and offshore platforms need an adaptive protection power system. However, the adaptive protection is yet to be implemented in the maritime sector. Usually, the adaptive protection implies the existence of a central control unit that monitors...

Mathematical Foundations of Quantum Information and Computation and Its Applications to Nano- and Bio-systems

CERN Document Server

Ohya, Masanori

2011-01-01

This monograph provides a mathematical foundation  to  the theory of quantum information and computation, with applications to various open systems including nano and bio systems. It includes introductory material on algorithm, functional analysis, probability theory, information theory, quantum mechanics and quantum field theory. Apart from standard material on quantum information like quantum algorithm and teleportation, the authors discuss findings on the theory of entropy in C*-dynamical systems, space-time dependence of quantum entangled states, entangling operators, adaptive dynamics, relativistic quantum information, and a new paradigm for quantum computation beyond the usual quantum Turing machine. Also, some important applications of information theory to genetics and life sciences, as well as recent experimental and theoretical discoveries in quantum photosynthesis are described.

Full-Scaled Advanced Systems Testbed: Ensuring Success of Adaptive Control Research Through Project Lifecycle Risk Mitigation

Science.gov (United States)

Pavlock, Kate M.

2011-01-01

The National Aeronautics and Space Administration's Dryden Flight Research Center completed flight testing of adaptive controls research on the Full-Scale Advance Systems Testbed (FAST) in January of 2011. The research addressed technical challenges involved with reducing risk in an increasingly complex and dynamic national airspace. Specific challenges lie with the development of validated, multidisciplinary, integrated aircraft control design tools and techniques to enable safe flight in the presence of adverse conditions such as structural damage, control surface failures, or aerodynamic upsets. The testbed is an F-18 aircraft serving as a full-scale vehicle to test and validate adaptive flight control research and lends a significant confidence to the development, maturation, and acceptance process of incorporating adaptive control laws into follow-on research and the operational environment. The experimental systems integrated into FAST were designed to allow for flexible yet safe flight test evaluation and validation of modern adaptive control technologies and revolve around two major hardware upgrades: the modification of Production Support Flight Control Computers (PSFCC) and integration of two, fourth-generation Airborne Research Test Systems (ARTS). Post-hardware integration verification and validation provided the foundation for safe flight test of Nonlinear Dynamic Inversion and Model Reference Aircraft Control adaptive control law experiments. To ensure success of flight in terms of cost, schedule, and test results, emphasis on risk management was incorporated into early stages of design and flight test planning and continued through the execution of each flight test mission. Specific consideration was made to incorporate safety features within the hardware and software to alleviate user demands as well as into test processes and training to reduce human factor impacts to safe and successful flight test. This paper describes the research configuration

Adaptive and Rational Anticipations in Risk Management Systems and Economy

Science.gov (United States)

Dubois, Daniel M.; Holmberg, Stig C.

2010-11-01

The global financial crisis of year 2009 is explained as a result of uncoordinated risk management decisions in business firms and economic organisations. The underlying reason for this can be found in the current financial system. As the financial market has lost much of its direct coupling to the concrete economy it provides misleading information to economic decision makers at all levels. Hence, the financial system has moved from a state of moderate and slow cyclical fluctuations into a state of fast and chaotic ones. Those misleading decisions can further be described, but not explained, by help of adaptive and rational expectations from macroeconomic theory. In this context, AE, the Adaptive Expectations are related to weak passive Exo-anticipation, and RE, the Rational expectations can be related to a strong, active and design oriented anticipation. The shortcomings of conventional cures, which builds on a reactive paradigm, have already been demonstrated in economic literature and are here further underlined by help of Ashby's "Law of Requisite Variety", Weaver's distinction between systems of "Disorganized Complexity" and those of "Organized Complexity", and Klir's "Reconstructability Analysis". Anticipatory decision-making is hence here proposed as a replacement to current expectation based and passive risk management. An anticipatory model of the business cycle is presented for supporting that proposition. The model, which is an extension of the Kaldor-Kalecki model, includes both retardation and anticipation. While cybernetics with the feedback process in control system deals with an explicit goal or purpose given to a system, the anticipatory system discussed here deals with a behaviour for which the future state of the system is built by the system itself, without explicit goal. A system with weak anticipation is based on a predictive model of the system, while a system with strong anticipation builds its own future by itself. Numerical simulations on

Optimizing Input/Output Using Adaptive File System Policies

Science.gov (United States)

Madhyastha, Tara M.; Elford, Christopher L.; Reed, Daniel A.

1996-01-01

Parallel input/output characterization studies and experiments with flexible resource management algorithms indicate that adaptivity is crucial to file system performance. In this paper we propose an automatic technique for selecting and refining file system policies based on application access patterns and execution environment. An automatic classification framework allows the file system to select appropriate caching and pre-fetching policies, while performance sensors provide feedback used to tune policy parameters for specific system environments. To illustrate the potential performance improvements possible using adaptive file system policies, we present results from experiments involving classification-based and performance-based steering.

Soft computing integrating evolutionary, neural, and fuzzy systems

CERN Document Server

Tettamanzi, Andrea

2001-01-01

Soft computing encompasses various computational methodologies, which, unlike conventional algorithms, are tolerant of imprecision, uncertainty, and partial truth. Soft computing technologies offer adaptability as a characteristic feature and thus permit the tracking of a problem through a changing environment. Besides some recent developments in areas like rough sets and probabilistic networks, fuzzy logic, evolutionary algorithms, and artificial neural networks are core ingredients of soft computing, which are all bio-inspired and can easily be combined synergetically. This book presents a well-balanced integration of fuzzy logic, evolutionary computing, and neural information processing. The three constituents are introduced to the reader systematically and brought together in differentiated combinations step by step. The text was developed from courses given by the authors and offers numerous illustrations as

EVALUATION OF THE BODY ADAPTIVE POTENTIAL AND ORIGINAL OF THE SYMPATHETIC NERVOUS SYSTEM TONE IN GIRLS AGED FROM 8 TO 17

Directory of Open Access Journals (Sweden)

A.A. Bolova

2008-01-01

Full Text Available The article highlights the findings obtained from the examination of 200 girls aged from 8 to 17, who underwent active orthostatic tests to study the adaptive capabilities of the body and initial tone of the sympathetic nervous system. The examination was carried out with ankar 131 computer cardio analyzer. The given try allowed the researchers to get an idea about the state of the compensatory and adaptive mechanisms of the girls during the puberty and identify the high risk groups of school students in terms of dysregulation of the sympathetic nervous system and genital system pathology.Key words: puberty, vegetative tone, active orthostatic test, girls.

Exploring adaptive program behavior

DEFF Research Database (Denmark)

Bonnichsen, Lars Frydendal; Probst, Christian W.

Modern computer systems are increasingly complex, with ever changing bottlenecks. This makes it difficult to ensure consistent performance when porting software, or even running it. Adaptivity, ie, switching between program variations, and dynamic recompilation have been suggested as solutions....... Both solutions come at a cost; adaptivity issues a runtime overhead and requires more design effort, while dynamic recompilation takes time to perform. In this project, we plan to investigate the possibilities, limitations, and benefits of these techniques. This abstract covers our thoughts on how...

Fast Adaptive Blind MMSE Equalizer for Multichannel FIR Systems

Directory of Open Access Journals (Sweden)

Abed-Meraim Karim

2006-01-01

Full Text Available We propose a new blind minimum mean square error (MMSE equalization algorithm of noisy multichannel finite impulse response (FIR systems, that relies only on second-order statistics. The proposed algorithm offers two important advantages: a low computational complexity and a relative robustness against channel order overestimation errors. Exploiting the fact that the columns of the equalizer matrix filter belong both to the signal subspace and to the kernel of truncated data covariance matrix, the proposed algorithm achieves blindly a direct estimation of the zero-delay MMSE equalizer parameters. We develop a two-step procedure to further improve the performance gain and control the equalization delay. An efficient fast adaptive implementation of our equalizer, based on the projection approximation and the shift invariance property of temporal data covariance matrix, is proposed for reducing the computational complexity from to , where is the number of emitted signals, the data vector length, and the dimension of the signal subspace. We then derive a statistical performance analysis to compare the equalization performance with that of the optimal MMSE equalizer. Finally, simulation results are provided to illustrate the effectiveness of the proposed blind equalization algorithm.

A Weibull distribution accrual failure detector for cloud computing.

Science.gov (United States)

Liu, Jiaxi; Wu, Zhibo; Wu, Jin; Dong, Jian; Zhao, Yao; Wen, Dongxin

2017-01-01

Failure detectors are used to build high availability distributed systems as the fundamental component. To meet the requirement of a complicated large-scale distributed system, accrual failure detectors that can adapt to multiple applications have been studied extensively. However, several implementations of accrual failure detectors do not adapt well to the cloud service environment. To solve this problem, a new accrual failure detector based on Weibull Distribution, called the Weibull Distribution Failure Detector, has been proposed specifically for cloud computing. It can adapt to the dynamic and unexpected network conditions in cloud computing. The performance of the Weibull Distribution Failure Detector is evaluated and compared based on public classical experiment data and cloud computing experiment data. The results show that the Weibull Distribution Failure Detector has better performance in terms of speed and accuracy in unstable scenarios, especially in cloud computing.

Adaptive Non-linear Control of Hydraulic Actuator Systems

DEFF Research Database (Denmark)

Hansen, Poul Erik; Conrad, Finn

1998-01-01

Presentation of two new developed adaptive non-liner controllers for hydraulic actuator systems to give stable operation and improved performance.Results from the IMCIA project supported by the Danish Technical Research Council (STVF).......Presentation of two new developed adaptive non-liner controllers for hydraulic actuator systems to give stable operation and improved performance.Results from the IMCIA project supported by the Danish Technical Research Council (STVF)....

Outage Performance of Hybrid FSO/RF System with Low-Complexity Power Adaptation

KAUST Repository

Rakia, Tamer

2016-02-26

Hybrid free-space optical (FSO) / radio-frequency (RF) systems have emerged as a promising solution for high data- rate wireless communication systems. We consider truncated channel inversion based power adaptation strategy for coherent and non- coherent hybrid FSO/RF systems, employing an adaptive combining scheme. Specifically, we activate the RF link along with the FSO link when FSO link quality is unacceptable, and adaptively set RF transmission power to ensure constant combined signal-to-noise ratio at receiver terminal. Analytical expressions for the outage probability of the hybrid system with and without power adaptation are derived. Numerical examples show that, the hybrid FSO/RF systems with power adaptation achieve considerable outage performance improvement over conventional hybrid FSO/RF systems without power adaptation. © 2015 IEEE.

Development of fault tolerant adaptive control laws for aerospace systems

Science.gov (United States)

Perez Rocha, Andres E.

The main topic of this dissertation is the design, development and implementation of intelligent adaptive control techniques designed to maintain healthy performance of aerospace systems subjected to malfunctions, external parameter changes and/or unmodeled dynamics. The dissertation is focused on the development of novel adaptive control configurations that rely on non-linear functions that appear in the immune system of living organisms as main source of adaptation. One of the main goals of this dissertation is to demonstrate that these novel adaptive control architectures are able to improve overall performance and protect the system while reducing control effort and maintaining adequate operation outside bounds of nominal design. This research effort explores several phases, ranging from theoretical stability analysis, simulation and hardware implementation on different types of aerospace systems including spacecraft, aircraft and quadrotor vehicles. The results presented in this dissertation are focused on two main adaptivity approaches, the first one is intended for aerospace systems that do not attain large angles and use exact feedback linearization of Euler angle kinematics. A proof of stability is presented by means of the circle Criterion and Lyapunov's direct method. The second approach is intended for aerospace systems that can attain large attitude angles (e.g. space systems in gravity-less environments), the adaptation is incorporated on a baseline architecture that uses partial feedback linearization of quaternions kinematics. In this case, the closed loop stability was analyzed using Lyapunov's direct method and Barbalat's Lemma. It is expected that some results presented in this dissertation can contribute towards the validation and certification of direct adaptive controllers.

A System based on Adaptive Background Subtraction Approach for Moving Object Detection and Tracking in Videos

Directory of Open Access Journals (Sweden)

Bahadır KARASULU

2013-04-01

Full Text Available Video surveillance systems are based on video and image processing research areas in the scope of computer science. Video processing covers various methods which are used to browse the changes in existing scene for specific video. Nowadays, video processing is one of the important areas of computer science. Two-dimensional videos are used to apply various segmentation and object detection and tracking processes which exists in multimedia content-based indexing, information retrieval, visual and distributed cross-camera surveillance systems, people tracking, traffic tracking and similar applications. Background subtraction (BS approach is a frequently used method for moving object detection and tracking. In the literature, there exist similar methods for this issue. In this research study, it is proposed to provide a more efficient method which is an addition to existing methods. According to model which is produced by using adaptive background subtraction (ABS, an object detection and tracking system’s software is implemented in computer environment. The performance of developed system is tested via experimental works with related video datasets. The experimental results and discussion are given in the study

Towards Measuring the Adaptability of an AO4BPEL Process

OpenAIRE

Botangen, Khavee Agustus; Yu, Jian; Sheng, Michael

2017-01-01

Adaptability is a significant property which enables software systems to continuously provide the required functionality and achieve optimal performance. The recognised importance of adaptability makes its evaluation an essential task. However, the various adaptability dimensions and implementation mechanisms make adaptive strategies difficult to evaluate. In service oriented computing, several frameworks that extend the WS-BPEL, the de facto standard in composing distributed business applica...

Adaptive control of solar energy collector systems

CERN Document Server

Lemos, João M; Igreja, José M

2014-01-01

This book describes methods for adaptive control of distributed-collector solar fields: plants that collect solar energy and deliver it in thermal form. Controller design methods are presented that can overcome difficulties found in these type of plants:they are distributed-parameter systems, i.e., systems with dynamics that depend on space as well as time;their dynamics is nonlinear, with a bilinear structure;there is a significant level of uncertainty in plant knowledge.Adaptive methods form the focus of the text because of the degree of uncertainty in the knowledge of plant dynamics. Parts

CHIME : service-oriented framework for adaptive web-based systems

NARCIS (Netherlands)

Chepegin, V.; Aroyo, L.M.; De Bra, P.M.E.; Houben, G.J.P.M.; De Bra, P.M.E.

2003-01-01

In this paper we present our view on how the current development of knowledge engineering in the context of Semantic Web can contribute to the better applicability, reusability and sharability of adaptive web-based systems. We propose a service-oriented framework for adaptive web-based systems,

Energy efficient distributed computing systems