ppxscal/embedding_network huggingface dataset:
On Seeing Robots
Authors: Alan K. Mackworth
Venue:  (1993)

Good Old Fashioned Artificial Intelligence and Robotics (GOFAIR) relies on a set of restrictive Omniscient Fortune Teller Assumptions about the agent, the world and their relationship. The emerging Situated Agent paradigm is challenging GOFAIR by grounding the agent in space and time, relaxing some of those assumptions, proposing new architectures and integrating perception, reasoning and action in behavioral modules. GOFAIR is typically forced to adopt a hybrid architecture for integrating signal-based and symbol-based approaches because of the inherent mismatch between the corresponding on-line and off-line computational models. It is argued that Situated Agents should be designed using a unitary on-line computational model. The Constraint Net model of Zhang and Mackworth satisfies that requirement. Two systems for situated perception built in our laboratory are described to illustrate the new approach: one for visual monitoring of a robot''s arm, the other for real-time visual control of multiple robots competing and cooperating in a dynamic world.
Refining Local Smoothness through Higher Level Geometry
Authors: Patrick C Hew, Michael D Alder
Venue:  (1999)

The Lim-Alder Extended Edge Extraction Algorithm accumulates pixels into ``natural'''' lines and curves. The Algorithm is built on a local smoothness classifier, so we have failures when higher level context is required. We introduce this context through vector models of pixel sequences.
Run-time Techniques for Exploiting Irregular Task Parallelism on Distributed Memory Architectures (Revised version of TCRS95-21)
Authors: Cong Fu, Tao Yang
Venue:  (1997)

Automatic scheduling for directed acyclic graphs (DAG) and its applications for coarse-grained irregular problems such as large n-body simulation have been studied in the literature. However solving irregular problems with mixed granularities such as sparse matrix factorization is challenging since it requires efficient run-time support to execute a DAG schedule. In this paper, we investigate run-time optimization techniques for executing general asynchronous DAG schedules on distributed memory machines and discuss an approach for exploiting parallelism from commuting operations in the DAG model. Our solution tightly integrates the run-time scheme with a fast communication mechanism to eliminate unnecessary overhead in message buffering and copying. We present a consistency model incorporating the above optimizations, and taking advantage of task dependence properties to ensure the correctness of execution. We demonstrate the applications of this scheme in sparse matrix factorizations and triangular equation solving for which actual speedups are hard to obtain. We provide a detailed experimental study on Meiko CS-2 to show that the automatically scheduled code has achieved good performance for these difficult problems and the run-time overhead is small compared to total execution times.
Subpixel Edge Location in Binary Images Using Dithering
Authors: Xiangdong Liu, Roger W. Ehrich
Venue:  (1993)

This paper concerns the problem of obtaining subpixel estimates of the locations of straight lines in digital images for purposes of machine vision. In particular, it presents a dithering method for improving the estimation accuracy on a rectangular sampling lattice. By adding uniformly distributed independent random noise it is shown that estimation bias may be removed and that the estimation variance is inversely proportional to the length of the line segment. The sensitivity to incorrect dither amplitude is calculated, and a novel approach is given for adding the dither by using grey-level image sensor and utilizing the imaging model.
Closing the learning application gap
Authors: Phillip Armour
Venue: Communications of the ACM (2003)

Attempting to overcome the challenges to effectively conveying knowledge.
Brokers and Services: Constructs for the Design and Implementation ofProcess-Oriented Environments
Authors: Dimitrios Tombros, Andreas Geppert, Klaus R. Dittrich
Venue:  (1995)

Cooperative process-oriented environments (CPEs) are federations of human agents and multiple (heterogeneous) software tools which cooperate to accomplish complex and long-lasting tasks. Appropriate abstractions must be available in order to properly design and implement CPEs, including tasks such as the control of and cooperation among their participating entities. In this paper, we introduce the concept of brokers, which are components reacting to environmental stimuli and are used to model participating entities in CPEs: human participants, existing software tools, or parts of the environment infrastructure. Services model the functionality offered by brokers. Although these brokers are actually abstractions on top of active object-oriented database management systems, they are also influenced by concepts developed in other research areas, such as (concurrent) programming languages, artificial intelligence, and software architectures. We therefore also position the broker model with respect to similar concepts from these domains.
A New Method for Influence Diagram Evaluation
Authors: Runping Qi, David Poole
Venue:  (1993)

As Influence diagrams become a popular representational tool for decision analysis, influence diagram evaluation attracts more and more research interests. In this article, we present a new, two--phase method for influence diagram evaluation. In our method, an influence diagram is first mapped into a decision graph and then the analysis is carried out by evaluating the decision graph. Our method is more efficient than Howard and Matheson''s two--phase method because, among other reasons, the size of the decision graph generated by our method from an influence diagram can be much smaller than that by Howard and Matheson''s method for the same influence diagram. Like those most recent algorithms reported in the literature, our method can also exploit independence relationship among variables of decision problems, and provides a clean interface between influence diagram evaluation and Bayesian net evaluation, thus, various well--established algorithms for Bayesian net evaluation can be used in influence diagram evaluation. In this sense, our method is as efficient as those algorithms. Furthermore, our method has a few unique merits. First, it can take advantage of asymmetric processing in influence diagram evaluation. Second, by using heuristic search techniques, it provides an explicit mechanism for making use of heuristic information that may be available in a domain--specific form. These additional merits make our method more efficient than the current algorithms in general. Finally, by using decision graphs as an intermediate representation, the value of perfect information can be computed in a more efficient way.
Cross-Operating System Process Migration on a Massively Parallel Processor
Authors: Dimitrios Katramatos, Steve J. Chapin, Patricia Hillman, Lee A Fisk, David van Dresser
Venue:  (1998)

As part of the Uniform Kernel project at Sandia National Labs, we developed process migration mechanisms for the Intel Paragon and Teraflop (ASCI Red) machines. The computing paradigm on these massively parallel processors divides the nodes into multiple logical partitions which run differing operating systems. This provides a unique environment for process migration, with homogeneous hardware and heterogeneous systems software. In this paper, we describe mechanisms that allow processes to (1) run on multiple operating systems, and (2) migrate between partitions on demand. The result is the first step towards a system which will allow partition boundaries to change dynamically, thus responding to changes in load mix and resource usage on the machine.
Performance Modelling of Parallel Computations
Authors: Ashok K. Adiga
Venue:  (1988)

The design of parallel computations involves numerous decisions which effect execution efficiency. The choice of an optimum configuration for a computation on a given architecture is essential for attaining the maximum efficiency in terms of achieved speedup. Some of the relevant factors in the configuration space of a computation include the granularity of a task, the communication model used, choice of dependencies between tasks and the host architecture on which the application is to be run. In this dissertation, we present a model for representing parallel computations which can be used to analyze their performance for various configurations. Our model is an extended Petri Net with facilities to model control and data flow mechanisms, as well as synchronization and communication primitives. A methodology is developed for representing the execution of a computation on a given architecture. The methodology consists of viewing the model as consisting of three distinct submodels (the computation, architecture and mapping submodels) which have standard interfaces between them. Specification of a structured methodology enables the automatic generation of model instances. In addition, it becomes possible to specify a library from which architectures can be selected to determine if they are suitable for a given computation. This modelling technique is then used to study the performance of computations under variations in their configuration parameters, including their actual run-time behavior on various target architectures. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
The Cascaded Predictor: Economic and Adaptive BranchTarget Prediction
Authors: Karel Driesen, Urs Holzle
Venue:  (1998)

Two-level predictors improve branch prediction accuracy by allowing predictor tables to hold multiple predictions per branch. Unfortunately, the accuracy of such predictors is impaired by two detrimental effects. Capacity misses increase since each branch may occupies entries proportional to the number of different path histories leading up to the branch. The working set of a given program therefore increases with history length. Similarly, cold start misses increase with history length since the predictor must initially store a prediction separately for each history pattern. We describe a new predictor architecture, cascaded branch prediction, which can alleviate both of these effects while retaining the superior accuracy of two-level predictors. Cascaded predictors dynamically classify and predict easily predicted branches using an inexpensive predictor, preventing insertion of these branches into a more powerful second stage predictor. We show that for path-based indirect branch predictors, cascaded prediction obtains prediction rates equivalent to that of two-level predictors at approximately one fourth the cost. For example, a cascaded predictor with 64+1024 entries achieves the same prediction accuracy as a 4096-entry two-level predictor. Although we have evaluated cascaded prediction only on indirect branches, we believe that it could also improve conditional branch prediction and value prediction.
Modeling Correlated Proxy Web Traffic Using Fourier Analysis
Authors: Abdulla Ghaleb, Nayfeh Ali H., Fox Edward A.
Venue:  (1997)

We analyze the arrival rate of accesses to Web proxy caching servers. The results show that the data display strong periodic autocorrelation. The examined data sets show a consistent behavior in terms of having periods corresponding to daily and weekly cycles that can be explained in terms of daily and weekly cyclic behavior of Web users. While these results confirm the correlation in the network traffic noticed by other researchers, we emphasize that this correlation is periodic. A new approach is introduced to model data that exhibit such characteristics by a combination of Fourier and statistical analysis techniques. The source of high correlation in the data is shown to come from the periodic and hence the deterministic part. Synthesized data that results from this modeling approach is shown to have a long-range dependent and self-similar behavior.
Estimating and Predicting Error Detection Trends and Relative Manpower Utilization
Authors: Arthur James D., Rosenberg Linda H., Stapko Ruth K., Hyatt Lawrence E.
Venue:  (1998)

The work described in this paper outlines an investigative effort focusing on estimating the number of errors remaining in a software product and the effort required to detect those errors. More specifically, we provide a description of a computational model that, through a non-linear optimization process: (a) determines an error detection trend in a given development effort, (b) provides an estimate of the errors remaining in the product and the time required to detect those errors, and (c) relates the error detection effort to current and future manpower requirements. The model is simple to use, requiring only error counts and detection dates as input, and is grounded in the time-tested theory underlying Musa''s Basic Reliability Model and the Rayleigh Manpower Utilization Curve. The model has been developed under the auspices of the Software Assurance Technology Center (SATC) at NASA/GSFC. Data sets from various NASA projects were used in formulating and tuning the model. For research purposes, the model was initially developed within an Excel framework; a more robust implementation is currently underway.
A Hybrid Fractal-Wavelet Transform Image Data Compression Algorithm
Authors: I. Levy, R. G. Wilson
Venue:  (1995)

This report describes two seemingly distinct areas of work, wavelet analysis and fractal image compression. A review of these two areas is presented, a new algorithm outlined, and some results presented. Finally, some speculations concerning the future direction of this research is included.
Self-Similar Neural Networks Based On A Kohonen Learning Rule
Authors: Simon Clippingdale, R. G. Wilson
Venue:  (1994)

One of the most striking features about the perceptual machinery of mammals is its regularity of structure. This is particularly evident in the mammalian visual system, as the work pioneered by Hubel and Wiesel has demonstrated. The likely source of this regularity is the visual stimulus, which does not change randomly from instant to instant, but is affected primarily by motions of both the animal and objects in the environment. These motions induce structured changes in the visual stimulus, which might well be expected to have a significant effect in shaping the structure of the visual machinery, whether through individual plasticity or longer-term genetic changes. The work reported in this paper is an investigation of the structures that may evolve in a simple artificial neural network driven not by random changes of input pattern, but directly by transformations which are themselves related to transformations of the input signal through an analysis of motion-prediction error. Results are presented which demonstrate that such networks can evolve a remarkable degree of regularity which reflects the underlying symmetry group of the transformations, both in one and two dimensions. An appropriate and visually plausible choice of transformation group can lead to the development of foveal structures in two-dimensional networks. We also present some preliminary results on parameterised function spaces which support the general conclusion that global structure bearing a considerable resemblance to that found in the mammalian visual system can evolve as the result of a simple learning rule in networks driven by transformations similar to those typically encountered in vision.
Optimal Dynamic Range Searching in Non-replicating Index Structures
Authors: K. V. R Kanth, Ambuj K. Singh
Venue:  (1997)

We consider the problem of dynamic range searching in tree structures that do not replicate data. We propose a new dynamic structure, called the {\em O-tree\/}, that achieves a query time complexity of $O(n^{(d-1)/d})$ on $n$ $d$-dimensional points and an amortized insertion/deletion time complexity of $O(\log n)$. We show that this structur e is optimal when data is not replicated. In addition to optimal query and insertion/deletion times, the O-tree also supports exact match queries in worst-case logarithmic time.
A Perceptual Colour Segmentation Algorithm
Authors: Christopher G. Healey, James T. Enns
Venue:  (1996)

A Perceptual Colour Segmentation Algorithm Christopher G. Healey and James T. Enns This paper presents a simple method for segmenting colour regions into categories like red, green, blue, and yellow. We are interested in studying how colour categories influence colour selection during scientific visualization. The ability to name individual colours is also important in other problem domains like real-time displays, user-interface design, and medical imaging systems. Our algorithm uses the Munsell and CIE LUV colour models to automatically segment a colour space like RGB or CIE XYZ into ten colour categories. Users are then asked to name a small number of representative colours from each category. This provides three important results: a measure of the perceptual overlap between neighbouring categories, a measure of a category''s strength, and a user-chosen name for each strong category. We evaluated our technique by segmenting known colour regions from the RGB, HSV, and CIE LUV colour models. The names we obtained were accurate, and the boundaries between different colour categories were well defined. We concluded our investigation by conducting an experiment to obtain user-chosen names and perceptual overlap for ten colour categories along the circumference of a colour wheel in CIE LUV.
Concurrent Access of Priority Queues
Authors: V. N Rao, Vipin Kumar
Venue:  (1988)

The heap is an important data structure used as a priority queue in a wide variety of parallel algorithms (e.g., multiprocessor scheduling, branch-and-bound). In these algorithms, contention for the shared heap limits the obtainable speedup. This paper presents an approach to allow concurrent insertions and deletions on the heap in a shared-memory multiprocessor. Our scheme has much smaller overhead and gives a much better performance than a previously reported scheme. The scheme also retains the strict priority ordering of the serial-access heap algorithms; i.e., a delete operation returns the best key of all keys that have been inserted or are being inserted at the time delete is started. Our experimental results on the BBN Butterfly parallel processor demonstrate that the use of the concurrent-heap algorithms in parallel branch-and-bound improves its performance substantially.
DEBUGGING OPTIMIZED CODE WITHOUT BEING MISLED: CURRENCY DETERMINATION
Authors: Max Copperman
Venue:  (1993)

Correct optimization can change the behavior of an incorrent program, therefore at times it is necessary to debug optimized code. However, optimizing compilers produce code that impedes source-level debugging. Optimization can cause an inconsistency between where the user expects a breakpoint to be located and the breakpoint''s actual location. This paper describes a mapping between statements and breakpoint locations that ameliorates this problem. The mapping enables debugger behavior on optimized code that approximates debugger behavior on unoptimized code sufficiently closely for the user to use traditional debugging strategies. Optimization can also cause the value of a variable to be noncurrent---to differ from the value that would be predicted by a close reading of the source code. This paper presents a method of determining when this has occurred, and shows how a debugger can describe the relevant effects of optimization. The determination method is more general than previously published methods; it handles global optimization and many flow graph transformations, and it is not tightly coupled to optimizations performed by a particular compiler. Necessary compiler support is also described.
Probabilistic Conflicts in a Search Algorithm for Estimating Posterior Probabilities in Bayesian Networks
Authors: David Poole
Venue:  (1994)

This paper presents a search algorithm for estimating prior and posterior probabilities in discrete Bayesian networks. It shows how conflicts (as used by the consistency-based diagnosis community) can be adapted to speed up the search. This is an `anytime'' algorithm, that at any stage can estimate probabilities and give an error bound. This algorithm is especially suited to the case where there are skewed distributions, although nothing about the algorithm or the definitions depends on skewness of conditional distributions. Empirical results with Bayesian networks having tens of thousands of nodes are presented.
A New Metric for Self-Organizing Feature Maps allows Mapping of ArbitraryParallel Programs
Authors: Jurgen W. Meyer
Venue:  (1993)

A modification of Kohonen''s self-organizing feature maps offers solutions for a wide range of graph mapping problems. This is reached by replacing the Euclidian metric of the target space by a new metric. A sample implementation for mapping parallel programs onto processor networks demonstrates the properties of this method. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
A Technique for Hiding Proprietary Details While Providing Sufficient Information for Researchers or Do You Recognize This Well-Known Algorithm?
Authors: Sallie M. Henry
Venue:  (1986)

A major problem facing software engineering researchers is the difficulty of performing validation experiments requiring "real-world" data. This data may be composed of the requirements document, design descriptions, source code,test plans, and/or error histories. Most major software organizations object to giving this usually proprietary data to researchers. This objection is understandable since these organizations do not desire their proprietary source code or error history to be made public. This paper describes a technique to translate source code into a meta-language which will maintain the proprietary nature of the original source code by hiding the algorithms and data structures employed in the source code. This technique, however, preserves sufficient data for validation experiments to be performed by some software engineering researchers, particularly those in the software quality metrics community. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Musical Expression in Automated Composition of Phrases
Authors: Brian T McLintock, John W. Roach
Venue:  (1987)

Music composed by computers has always been lacking in "musical" qualities: mood, emotional expression, and a sense of purpose or goal. A musical expert system called EMOTER is the first attempt to address these important musical aspects. EMOTER receives as input a list of moods (e.g., happy, lively) and generates melodic passages intended to evoke those moods in an organized, coherent fashion. EMOTER composes the basic units of music called phrases. Results with EMOTER are excellent. Some of the musical phrases generated from a mood-specification are comparable to music that a reasonably talented composer might produce. More theory is needed, however, before the full complexities of human-composed music are sufficiently captured in code for EMOTER to pass a Turing test in music composition.