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At least 235 records · Page 13

The symbolic computation of series solutions to ordinary differential equations using trees (extended abstract)

Algorithms previously developed by the author give formulas which can be used for the efficient symbolic computation of series expansions to solutions of nonlinear systems of ordinary differential equations. As a by product of this analysis, formulas are derived which relate to trees to the coefficients of the series expansions, similar to the work of Leroux and Viennot, and Lamnabhi, Leroux and Viennot.

Grossman, Robert↗

Symbolic enhancement of perspective displays

Two exocentric azimuth judgment experiments with a perspective display were conducted with 16 subjects. Previous work has shown these judgments to exhibit a bias possibly due to misinterpretation of the viewing parameters used to generate the display. Though geometric compensations may be used to correct for the bias, an alternate technique selected in the following 2 experiments was the introduction of symbolic enhancements in the form of compass roses. It is suggested that a compass rose with 30 deg divisions results in overall optimal azimuth estimation accuracy when accuracy and decision time are both considered. The data also suggest that the added radial lines on the compass roses may interact with normalization processes that influence the judgment errors.

Ellis, Stephen R.↗

A study of coupled rotor-fuselage vibration with higher harmonic control using a symbolic computing facility

A fundamental study of vibration prediction and vibration reduction in helicopters using active controls was performed. The nonlinear equations of motion for a coupled rotor/flexible fuselage system have been derived using computer algebra on a special purpose symbolic computing facility. The details of the derivation using the MACSYMA program are described. The trim state and vibratory response of the helicopter are obtained in a single pass by applying the harmonic balance technique and simultaneously satisfying the trim and the vibratory response of the helicopter for all rotor and fuselage degrees of freedom. The influence of the fuselage flexibility on the vibratory response is studied. It is shown that the conventional single frequency higher harmonic control (HHC) capable of reducing either the hub loads or only the fuselage vibrations but not both simultaneously. It is demonstrated that for simultaneous reduction of hub shears and fuselage vibrations a new scheme called multiple higher harmonic control (MHHC) is required. The fundamental aspects of this scheme and its uniqueness are described in detail, providing new insight on vibration reduction in helicopters using HHC.

Papavassiliou, I.↗

Ordinal judgments of numerical symbols by macaques (Macaca mulatta)

Two rhesus monkeys (Macaca mulatta) learned that the arabic numerals 0 through 9 represented corresponding quantities of food pellets. By manipulating a joystick, the monkeys were able to make a selection of paired numerals presented on a computer screen. Although the monkeys received a corresponding number of pellets even if the lesser of the two numerals was selected, they learned generally to choose the numeral of greatest value even when pellet delivery was made arrhythmic. In subsequent tests, they chose the numerals of greater value when presented in novel combinations or in random arrays of up to five numerals. Thus, the monkeys made ordinal judgments of numerical symbols in accordance with their absolute or relative values.

Washburn, David A.↗

Multiple symbol partially coherent detection of MPSK

It is shown that by using the known (or estimated) value of carrier tracking loop signal to noise ratio (SNR) in the decision metric, it is possible to improve the error probability performance of a partially coherent multiple phase-shift-keying (MPSK) system relative to that corresponding to the commonly used ideal coherent decision rule. Using a maximum-likeihood approach, an optimum decision metric is derived and shown to take the form of a weighted sum of the ideal coherent decision metric (i.e., correlation) and the noncoherent decision metric which is optimum for differential detection of MPSK. The performance of a receiver based on this optimum decision rule is derived and shown to provide continued improvement with increasing length of observation interval (data symbol sequence length). Unfortunately, increasing the observation length does not eliminate the error floor associated with the finite loop SNR. Nevertheless, in the limit of infinite observation length, the average error probability performance approaches the algebraic sum of the error floor and the performance of ideal coherent detection, i.e., at any error probability above the error floor, there is no degradation due to the partial coherence. It is shown that this limiting behavior is virtually achievable with practical size observation lengths. Furthermore, the performance is quite insensitive to mismatch between the estimate of loop SNR (e.g., obtained from measurement) fed to the decision metric and its true value. These results may be of use in low-cost Earth-orbiting or deep-space missions employing coded modulations.

Simon, M. K.↗

Learning fuzzy information in a hybrid connectionist, symbolic model

An instance-based learning system is presented. SC-net is a fuzzy hybrid connectionist, symbolic learning system. It remembers some examples and makes groups of examples into exemplars. All real-valued attributes are represented as fuzzy sets. The network representation and learning method is described. To illustrate this approach to learning in fuzzy domains, an example of segmenting magnetic resonance images of the brain is discussed. Clearly, the boundaries between human tissues are ill-defined or fuzzy. Example fuzzy rules for recognition are generated. Segmentations are presented that provide results that radiologists find useful.

Romaniuk, Steve G.↗

Explicit robust schemes for implementation of a class of principal value-based constitutive models: Symbolic and numeric implementation

The issue of developing effective and robust schemes to implement a class of the Ogden-type hyperelastic constitutive models is addressed. To this end, special purpose functions (running under MACSYMA) are developed for the symbolic derivation, evaluation, and automatic FORTRAN code generation of explicit expressions for the corresponding stress function and material tangent stiffness tensors. These explicit forms are valid over the entire deformation range, since the singularities resulting from repeated principal-stretch values have been theoretically removed. The required computational algorithms are outlined, and the resulting FORTRAN computer code is presented.

Arnold, S. M.↗

CPP-TRS(C): On using visual cognitive symbols to enhance communication effectiveness

Communicative Positioning Program/Text Representation Systems (CPP-TRS) is a visual language based on a system of 12 canvasses, 10 signals and 14 symbols. CPP-TRS is based on the fact that every communication action is the result of a set of cognitive processes and the whole system is based on the concept that you can enhance communication by visually perceiving text. With a simple syntax, CPP-TRS is capable of representing meaning and intention as well as communication functions visually. Those are precisely invisible aspects of natural language that are most relevant to getting the global meaning of a text. CPP-TRS reinforces natural language in human machine interaction systems. It complements natural language by adding certain important elements that are not represented by natural language by itself. These include communication intention and function of the text expressed by the sender, as well as the role the reader is supposed to play. The communication intention and function of a text and the reader's role are invisible in natural language because neither specific words nor punctuation conveys them sufficiently and unambiguously; they are therefore non-transparent.

Tonfoni, Graziella↗

Effects of correlated noise on the full-spectrum combining and complex-symbol combining arraying techniques

The process of combining telemetry signals received at multiple antennas, commonly referred to as arraying, can be used to improve communication link performance in the Deep Space Network (DSN). By coherently adding telemetry from multiple receiving sites, arraying produces an enhancement in signal-to-noise ratio (SNR) over that achievable with any single antenna in the array. A number of different techniques for arraying have been proposed and their performances analyzed in past literature. These analyses have compared different arraying schemes under the assumption that the signals contain additive white Gaussian noise (AWGN) and that the noise observed at distinct antennas is independent. In situations where an unwanted background body is visible to multiple antennas in the array, however, the assumption of independent noises is no longer applicable. A planet with significant radiation emissions in the frequency band of interest can be one such source of correlated noise. For example, during much of Galileo's tour of Jupiter, the planet will contribute significantly to the total system noise at various ground stations. This article analyzes the effects of correlated noise on two arraying schemes currently being considered for DSN applications: full-spectrum combining (FSC) and complex-symbol combining (CSC). A framework is presented for characterizing the correlated noise based on physical parameters, and the impact of the noise correlation on the array performance is assessed for each scheme.

Vazirani, P.↗

Symbolic Heuristic Search for Factored Markov Decision Processes

We describe a planning algorithm that integrates two approaches to solving Markov decision processes with large state spaces. State abstraction is used to avoid evaluating states individually. Forward search from a start state, guided by an admissible heuristic, is used to avoid evaluating all states. We combine these two approaches in a novel way that exploits symbolic model-checking techniques and demonstrates their usefulness for decision-theoretic planning.

Morris, Robert↗

Verification of Java Programs using Symbolic Execution and Invariant Generation

Software verification is recognized as an important and difficult problem. We present a norel framework, based on symbolic execution, for the automated verification of software. The framework uses annotations in the form of method specifications an3 loop invariants. We present a novel iterative technique that uses invariant strengthening and approximation for discovering these loop invariants automatically. The technique handles different types of data (e.g. boolean and numeric constraints, dynamically allocated structures and arrays) and it allows for checking universally quantified formulas. Our framework is built on top of the Java PathFinder model checking toolset and it was used for the verification of several non-trivial Java programs.

Pasareanu, Corina↗

Effects of Symbol Brightness Cueing on Attention During a Visual Search of a Cockpit Display of Traffic Information

This study investigated visual search performance for target aircraft symbols on a Cockpit Display of Traffic Information (CDTI). Of primary interest was the influence of target brightness (intensity) and highlighting validity (search directions) on the ability to detect a target aircraft among distractor aircraft. Target aircraft were distinguished by an airspace course that conflicted with Ownship (that is, the participant's aircraft). The display could present all (homogeneous) bright aircraft, all (homogeneous) dim aircraft, or mixed bright and dim aircraft, with the target aircraft being either bright or dim. In the mixed intensity condition, participants may or may not have been instructed whether the target was bright or dim. Results indicated that highlighting validity facilitated better detection times. However, instead of bright targets being detected faster, dim targets were found to be detected more slowly in the mixed intensity display than in the homogeneous display. This relative slowness may be due to a delay in confirming the dim aircraft to be a target when it it was among brighter distractor aircraft. This hypothesis will be tested in future research. Funding for this work was provided by the Advanced Air Transportation Technologies Project of NASA's Airspace Operation Systems Program.

Johnson, Walter W.↗

Improving the Flight Path Marker Symbol on Rotorcraft Synthetic Vision Displays

Two potential improvements to the flight path marker symbol were evaluated on a panel-mounted, synthetic vision, primary flight display in a rotorcraft simulation. One concept took advantage of the fact that synthetic vision systems have terrain height information available ahead of the aircraft. For this first concept, predicted altitude and ground track information was added to the flight path marker. In the second concept, multiple copies of the flight path marker were displayed at 3, 4, and 5 second prediction times as compared to a single prediction time of 3 seconds. Objective and subjective data were collected for eight rotorcraft pilots. The first concept produced significant improvements in pilot attitude control, ground track control, workload ratings, and preference ratings. The second concept did not produce significant differences in the objective or subjective measures.

Szoboszlay, Zoltan P.↗

Anomaly Detection in Large Sets of High-Dimensional Symbol Sequences

This paper addresses the problem of detecting and describing anomalies in large sets of high-dimensional symbol sequences. The approach taken uses unsupervised clustering of sequences using the normalized longest common subsequence (LCS) as a similarity measure, followed by detailed analysis of outliers to detect anomalies. As the LCS measure is expensive to compute, the first part of the paper discusses existing algorithms, such as the Hunt-Szymanski algorithm, that have low time-complexity. We then discuss why these algorithms often do not work well in practice and present a new hybrid algorithm for computing the LCS that, in our tests, outperforms the Hunt-Szymanski algorithm by a factor of five. The second part of the paper presents new algorithms for outlier analysis that provide comprehensible indicators as to why a particular sequence was deemed to be an outlier. The algorithms provide a coherent description to an analyst of the anomalies in the sequence, compared to more normal sequences. The algorithms we present are general and domain-independent, so we discuss applications in related areas such as anomaly detection.

Budalakoti, Suratna↗

Solving the AI Planning Plus Scheduling Problem Using Model Checking via Automatic Translation from the Abstract Plan Preparation Language (APPL) to the Symbolic Analysis Laboratory (SAL)

This paper describes a translator from a new planning language named the Abstract Plan Preparation Language (APPL) to the Symbolic Analysis Laboratory (SAL) model checker. This translator has been developed in support of the Spacecraft Autonomy for Vehicles and Habitats (SAVH) project sponsored by the Exploration Technology Development Program, which is seeking to mature autonomy technology for the vehicles and operations centers of Project Constellation.

Butler, Ricky W.↗

Generalized Abstract Symbolic Summaries

Current techniques for validating and verifying program changes often consider the entire program, even for small changes, leading to enormous V&V costs over a program s lifetime. This is due, in large part, to the use of syntactic program techniques which are necessarily imprecise. Building on recent advances in symbolic execution of heap manipulating programs, in this paper, we develop techniques for performing abstract semantic differencing of program behaviors that offer the potential for improved precision.

Person, Suzette↗

Statechart Analysis with Symbolic PathFinder

We report here on our on-going work that addresses the automated analysis and test case generation for software systems modeled using multiple Statechart formalisms. The work is motivated by large programs such as NASA Exploration, that involve multiple systems that interact via safety-critical protocols and are designed with different Statechart variants. To verify these safety-critical systems, we have developed Polyglot, a framework for modeling and analysis of model-based software written using different Statechart formalisms. Polyglot uses a common intermediate representation with customizable Statechart semantics and leverages the analysis and test generation capabilities of the Symbolic PathFinder tool. Polyglot is used as follows: First, the structure of the Statechart model (expressed in Matlab Stateflow or Rational Rhapsody) is translated into a common intermediate representation (IR). The IR is then translated into Java code that represents the structure of the model. The semantics are provided as "pluggable" modules.

Pasareanu, Corina S.↗