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At least 145 records · Page 8

An Approach for Autonomy: A Collaborative Communication Framework for Multi-Agent Systems

Research done during the last three years has studied the emersion properties of Complex Adaptive Systems (CAS). The deployment of Artificial Intelligence (AI) techniques applied to remote Unmanned Aerial Vehicles has led the author to investigate applications of CAS within the field of Autonomous Multi-Agent Systems. The core objective of current research efforts is focused on the simplicity of Intelligent Agents (IA) and the modeling of these agents within complex systems. This research effort looks at the communication, interaction, and adaptability of multi-agents as applied to complex systems control. The embodiment concept applied to robotics has application possibilities within multi-agent frameworks. A new framework for agent awareness within a virtual 3D world concept is possible where the vehicle is composed of collaborative agents. This approach has many possibilities for applications to complex systems. This paper describes the development of an approach to apply this virtual framework to the NASA Goddard Space Flight Center (GSFC) tetrahedron structure developed under the Autonomous Nano Technology Swarm (ANTS) program and the Super Miniaturized Addressable Reconfigurable Technology (SMART) architecture program. These projects represent an innovative set of novel concepts deploying adaptable, self-organizing structures composed of many tetrahedrons. This technology is pushing current applied Agents Concepts to new levels of requirements and adaptability.

Dufrene, Warren Russell, Jr.↗

Comparing morphologies of drainage basins on Mars and Earth using integral-geometry and neural maps

We compare morphologies of drainage basins on Mars and Earth in order to confine the formation process of Martian valley networks. Basins on both planets are computationally extracted from digital topography. Integral-geometry methods are used to represent each basin by a circularity function that encapsulates its internal structure. The shape of such a function is an indicator of the style of fluvial erosion. We use the self-organizing map technique to construct a similarity graph for all basins. The graph reveals systematic differences between morphologies of basins on the two planets. This dichotomy indicates that terrestrial and Martian surfaces were eroded differently. We argue that morphologies of Martian basins are incompatible with runoff from sustained, homogeneous rainfall. Fluvial environments compatible with observed morphologies are discussed. We also construct a similarity graph based on the comparison of basins hypsometric curves to demonstrate that hypsometry is incapable of discriminating between terrestrial and Martian basins. INDEX TERMS: 1824 Hydrology: Geomorphology (1625); 1886 Hydrology: Weathering (1625); 5415 Planetology: Solid Surface Planets: Erosion and weathering; 6225 Planetology: Solar System Objects Mars. Citation: Stepinski, T. F., and S. Coradetti (2004), Comparing morphologies of drainage basins on Mars and Earth using integral-ge

Stepinski, T. F.↗

Hydrophobic effect at aqueous interfaces

Conceptual basis for hydrophobic effects in bulk water and at aqueous interfaces have similar conceptual basis but often manifests itself differently. Using a wide range of computer simulations as the basis, I will review different forms of hydrophobic effects at a variety of interfaces starting from simple liquid-vapor and water-oil interfaces and progressing to water-membrane interfaces. I will start with discussing how water is organized at different interfaces, stressing both similarities and differences. The main thread is that, as in the bulk liquid, hydrophobic effects have profound influence on conformational equilibria and organization of both small molecules and macromolecules, but the result of this influence is quite different. Specifically, it will be shown that many small, but not necessarily amphiphilic molecules tend to accumulate at the interface and, and this tendency will be explained. Furthermore, I will show that many short peptides that are disordered in water spontaneously fold into well-defined structures in the interfacial environment. Biological implications of this self-organizing effect will be discussed.

Pohorille, Andrew↗

Multipoint sensing by intelligent collectives

Many remote sensing applications require that multiple sensors collect data simultaneously at spatially distributed locations and their information combined in order to characterize the phenomena of interest. Several basic classes of such multipoint measurement systems may be identified. For each, centralized methods exist for combining the raw data from the various sensors. However, recent advancements have given rise to small, integrated nodes comprised of one or more miniaturized sensors, processor, wireless communications capability and power supplies. Collections of these may be deployed and self-organized into intelligent sensor networks capable of performing cooperative signal processing locally, thereby providing substantial benefits.

multipoint measurement sensor networks↗

Improved dot size uniformity and luminescense of InAs quantum dots on InP substrate

InAs self-organized quantum dots have been grown in InGaAs quantum well on InP substrates by metalorganic vapor phase epitaxy. Atomic Force Microscopy confirmed of quantum dot formation with dot density of 3X10(sup 10) cm(sup -2). Improved dot size uniformity and strong room temperature photoluminescence up to 2 micron were observed after modifying the InGaAs well.

InAs quantum dot↗

On Hardware Evolvability and Levels of Granularity

Evolvable hardware addresses hardware that self-organizes/reconfigures under the guidance of evolutionary mechanisms. Some experiments in evolving at transistor level are briefly presented and the perspective of trnsistors as functional approximators is suggested.

Granularity Hardware↗

Probability Simulations by Non-Lipschitz Chaos

It has been demonstrated that classical probabilities, and in particular, probabilistic Turing machine, can be simulated by combining chaos and non-Lipschitz dynamics, without utilization of any man-made devices. Self-organizing properties of systems coupling simulated and calculated probabilities and their link to quantum computations are discussed.

classical dynamics classical probabilities probabi↗

Image and Video Compression with VLSI Neural Networks

An advanced motion-compensated predictive video compression system based on artificial neural networks has been developed to effectively eliminate the temporal and spatial redundancy of video image sequences and thus reduce the bandwidth and storage required for the transmission and recording of the video signal. The VLSI neuroprocessor for high-speed high-ratio image compression based upon a self-organization network and the conventional algorithm for vector quantization are compared. The proposed method is quite efficient and can achieve near-optimal results.

compression artificial neural networks VLSI↗

Simulations of Probabilities for Quantum Computing

It has been demonstrated that classical probabilities, and in particular, probabilistic Turing machine, can be simulated by combining chaos and non-LIpschitz dynamics, without utilization of any man-made devices (such as random number generators). Self-organizing properties of systems coupling simulated and calculated probabilities and their link to quantum computations are discussed.

Turing machines↗

Real Time On-line Space Research Laboratory Environment Monitoring with Off-line Trend and Prediction Analysis

One of the responsibilities of the NASA Glenn Principal Investigator Microgravity Services is to support NASA sponsored investigators in the area of reduced-gravity acceleration data analysis, interpretation and the monitoring of the reduced-gravity environment on-board various carriers. With the International Space Station currently operational, a significant amount of acceleration data is being down-linked and processed on ground for both the space station onboard environment characterization (and verification) and scientific experiments. Therefore, to help principal investigator teams monitor the acceleration level on-board the International Space Station to avoid undesirable impact on their experiment, when possible, the NASA Glenn Principal Investigator Microgravity Services developed an artificial intelligence monitoring system, which detects in near real time any change in the environment susceptible to affect onboard experiments. The main objective of the monitoring system is to help research teams identify the vibratory disturbances that are active at any instant of time onboard the International Space Station that might impact the environment in which their experiment is being conducted. The monitoring system allows any space research scientist, at any location and at any time, to see the current acceleration level on-board the Space Station via the World Wide Web. From the NASA Glenn s Exploration Systems Division web site, research scientists can see in near real time the active disturbances, such as pumps, fans, compressor, crew exercise, re-boost, extra-vehicular activity, etc., and decide whether or not to continue operating or stopping (or making note of such activity for later correlation with science results) their experiments based on the g-level associated with that specific event. A dynamic graphical display accessible via the World Wide Web shows the status of all the vibratory disturbance activities with their degree of confidence as well as their g-level contribution to the environment. The system can detect both known and unknown vibratory disturbance activities. It can also perform trend analysis and prediction by analyzing past data over many Increments of the space station for selected disturbance activities. This feature can be used to monitor the health of onboard mechanical systems to detect and prevent potential system failure as well as for use by research scientists during their science results analysis. Examples of both real time on-line vibratory disturbance detection and off-line trend analysis are presented in this paper. Several soft computing techniques such as Kohonen s Self-Organizing Feature Map, Learning Vector Quantization, Back-Propagation Neural Networks, and Fuzzy Logic were used to design the system.

Jules, Kenol↗

Autonomous Information Unit: Why Making Data Smart Can also Make Data Secured?

In this paper, we introduce a new fine-grain distributed information protection mechanism which can self-protect, self-discover, self-organize, and self-manage. In our approach, we decompose data into smaller pieces and provide individualized protection. We also provide a policy control mechanism to allow 'smart' access control and context based re-assembly of the decomposed data. By combining smart policy with individually protected data, we are able to provide better protection of sensitive information and achieve more flexible access during emergency conditions. As a result, this new fine-grain protection mechanism can enable us to achieve better solutions for problems such as distributed information protection and identity theft.

data security↗

Identification and Control of Aircrafts using Multiple Models and Adaptive Critics

We compared two possible implementations of local linear models for control: one approach is based on a self-organizing map (SOM) to cluster the dynamics followed by a set of linear models operating at each cluster. Therefore the gating function is hard (a single local model will represent the regional dynamics). This simplifies the controller design since there is a one to one mapping between controllers and local models. The second approach uses a soft gate using a probabilistic framework based on a Gaussian Mixture Model (also called a dynamic mixture of experts). In this approach several models may be active at a given time, we can expect a smaller number of models, but the controller design is more involved, with potentially better noise rejection characteristics. Our experiments showed that the SOM provides overall best performance in high SNRs, but the performance degrades faster than with the GMM for the same noise conditions. The SOM approach required about an order of magnitude more models than the GMM, so in terms of implementation cost, the GMM is preferable. The design of the SOM is straight forward, while the design of the GMM controllers, although still reasonable, is more involved and needs more care in the selection of the parameters. Either one of these locally linear approaches outperform global nonlinear controllers based on neural networks, such as the time delay neural network (TDNN). Therefore, in essence the local model approach warrants practical implementations. In order to call the attention of the control community for this design methodology we extended successfully the multiple model approach to PID controllers (still today the most widely used control scheme in the industry), and wrote a paper on this subject. The echo state network (ESN) is a recurrent neural network with the special characteristics that only the output parameters are trained. The recurrent connections are preset according to the problem domain and are fixed. In a nutshell, the states of the reservoir of recurrent processing elements implement a projection space, where the desired response is optimally projected. This architecture trades training efficiency by a large increase in the dimension of the recurrent layer. However, the power of the recurrent neural networks can be brought to bear on practical difficult problems. Our goal was to implement an adaptive critic architecture implementing Bellman s approach to optimal control. However, we could only characterize the ESN performance as a critic in value function evaluation, which is just one of the pieces of the overall adaptive critic controller. The results were very convincing, and the simplicity of the implementation was unparalleled.

Principe, Jose C.↗

Probabilistic resource allocation system with self-adaptive capability

A probabilistic resource allocation system is disclosed containing a low capacity computational module (Short Term Memory or STM) and a self-organizing associative network (Long Term Memory or LTM) where nodes represent elementary resources, terminal end nodes represent goals, and weighted links represent the order of resource association in different allocation episodes. Goals and their priorities are indicated by the user, and allocation decisions are made in the STM, while candidate associations of resources are supplied by the LTM based on the association strength (reliability). Weights are automatically assigned to the network links based on the frequency and relative success of exercising those links in the previous allocation decisions. Accumulation of allocation history in the form of an associative network in the LTM reduces computational demands on subsequent allocations. For this purpose, the network automatically partitions itself into strongly associated high reliability packets, allowing fast approximate computation and display of allocation solutions satisfying the overall reliability and other user-imposed constraints. System performance improves in time due to modification of network parameters and partitioning criteria based on the performance feedback.

Yufik, Yan M.↗

Probabilistic resource allocation system with self-adaptive capability

A probabilistic resource allocation system is disclosed containing a low capacity computational module (Short Term Memory or STM) and a self-organizing associative network (Long Term Memory or LTM) where nodes represent elementary resources, terminal end nodes represent goals, and directed links represent the order of resource association in different allocation episodes. Goals and their priorities are indicated by the user, and allocation decisions are made in the STM, while candidate associations of resources are supplied by the LTM based on the association strength (reliability). Reliability values are automatically assigned to the network links based on the frequency and relative success of exercising those links in the previous allocation decisions. Accumulation of allocation history in the form of an associative network in the LTM reduces computational demands on subsequent allocations. For this purpose, the network automatically partitions itself into strongly associated high reliability packets, allowing fast approximate computation and display of allocation solutions satisfying the overall reliability and other user-imposed constraints. System performance improves in time due to modification of network parameters and partitioning criteria based on the performance feedback.

Yufik, Yan M.↗

Dependence of Microelastic-plastic Nonlinearity of Martensitic Stainless Steel on Fatigue Damage Accumulation

Self-organized substructural arrangements of dislocations formed in wavy slip metals during cyclic stress-induced fatigue produce substantial changes in the material microelastic-plastic nonlinearity, a quantitative measure of which is the nonlinearity parameter Beta extracted from acoustic harmonic generation measurements. The contributions to Beta from the substructural evolution of dislocations and crack growth for fatigued martensitic 410Cb stainless steel are calculated from the Cantrell model as a function of percent full fatigue life to fracture. A wave interaction factor f(sub WI) is introduced into the model to account experimentally for the relative volume of material fatigue damage included in the volume of material swept out by an interrogating acoustic wave. For cyclic stress-controlled loading at 551 MPa and f(sub WI) = 0.013 the model predicts a monotonic increase in Beta from dislocation substructures of almost 100 percent from the virgin state to roughly 95 percent full life. Negligible contributions from cracks are predicted in this range of fatigue life. However, over the last five percent of fatigue life the model predicts a rapid monotonic increase of Beta by several thousand percent that is dominated by crack growth. The theoretical predictions are in good agreement with experimental measurements of 410Cb stainless steel samples fatigued in uniaxial, stress-controlled cyclic loading at 551 MPa from zero to full tensile load with a measured f(sub WI) of 0.013.

Cantrell, John H.↗

A Data Type for Efficient Representation of Other Data Types

A self-organizing, monomorphic data type denoted a sequence has been conceived to address certain concerns that arise in programming parallel computers. A sequence in the present sense can be regarded abstractly as a vector, set, bag, queue, or other construct. Heretofore, in programming a parallel computer, it has been necessary for the programmer to state explicitly, at the outset, what parts of the program and the underlying data structures must be represented in parallel form. Not only is this requirement not optimal from the perspective of implementation; it entails an additional requirement that the programmer have intimate understanding of the underlying parallel structure. The present sequence data type overcomes both the implementation and parallel structure obstacles. In so doing, the sequence data type provides unified means by which the programmer can represent a data structure for natural and automatic decomposition to a parallel computing architecture. Sequences exhibit the behavioral and structural characteristics of vectors, but the underlying representations are automatically synthesized from combinations of programmers advice and execution use metrics. Sequences can vary bidirectionally between sparseness and density, making them excellent choices for many kinds of algorithms. The novelty and benefit of this behavior lies in the fact that it can relieve programmers of the details of implementations. The creation of a sequence enables decoupling of a conceptual representation from an implementation. The underlying representation of a sequence is a hybrid of representations composed of vectors, linked lists, connected blocks, and hash tables. The internal structure of a sequence can automatically change from time to time on the basis of how it is being used. Those portions of a sequence where elements have not been added or removed can be as efficient as vectors. As elements are inserted and removed in a given portion, then different methods are utilized to provide both an access and memory strategy that is optimized for that portion and the use to which it is put.

James, Mark↗

Fabricating Nanodots using Lift-Off of a Nanopore Template

A process for fabricating a planar array of dots having characteristic dimensions of the order of several nanometers to several hundred nanometers involves the formation and use of a thin alumina nanopore template on a semiconductor substrate. The dot material is deposited in the nanopores, then the template is lifted off the substrate after the dots have been formed. This process is expected to be a basis for development of other, similar nanofabrication processes for relatively inexpensive mass production of nanometerscale optical, optoelectronic, electronic, and magnetic devices. Alumina nanopore templates are self-organized structures that result from anodization of aluminum under appropriate conditions. Alumina nanopore templates have been regarded as attractive for use in fabricating the devices mentioned above, but prior efforts to use alumina nanopore templates for this purpose have not been successful. One reason for the lack of success is that the aspect ratios (ratios between depth and diameter) of the pores have been too large: large aspect ratios can result in blockage of deposition and/or can prevent successful lift-off. The development of the present process was motivated partly by a requirement to reduce aspect ratios to values (of the order of 10) for which there is little or no blockage of deposition and attempts at lift-off are more likely to be successful. The fabrication process is outlined.

Yang, Eui-Hyeok↗