83,850 research outputs found
A probabilistic model for information and sensor validation
This paper develops a new theory and model for information and sensor validation. The model represents relationships between variables using Bayesian networks and utilizes probabilistic propagation to estimate the expected values of variables. If the estimated value of a variable differs from the actual value, an apparent fault is detected. The fault is only apparent since it may be that the estimated value is itself based on faulty data. The theory extends our understanding of when it is possible to isolate real faults from potential faults and supports the development of an algorithm that is capable of isolating real faults without deferring the problem to the use of expert provided domain-specific rules. To enable practical adoption for real-time processes, an any time version of the algorithm is developed, that, unlike most other algorithms, is capable of returning improving assessments of the validity of the sensors as it accumulates more evidence with time. The developed model is tested by applying it to the validation of temperature sensors during the start-up phase of a gas turbine when conditions are not stable; a problem that is known to be challenging. The paper concludes with a discussion of the practical applicability and scalability of the model
Lower Bounds on the Redundancy of Huffman Codes with Known and Unknown Probabilities
In this paper we provide a method to obtain tight lower bounds on the minimum
redundancy achievable by a Huffman code when the probability distribution
underlying an alphabet is only partially known. In particular, we address the
case where the occurrence probabilities are unknown for some of the symbols in
an alphabet. Bounds can be obtained for alphabets of a given size, for
alphabets of up to a given size, and for alphabets of arbitrary size. The
method operates on a Computer Algebra System, yielding closed-form numbers for
all results. Finally, we show the potential of the proposed method to shed some
light on the structure of the minimum redundancy achievable by the Huffman
code
A modal approach to hyper-redundant manipulator kinematics
This paper presents novel and efficient kinematic modeling techniques for âhyper-redundantâ robots. This approach is based on a âbackbone curveâ that captures the robot's macroscopic geometric features. The inverse kinematic, or âhyper-redundancy resolution,â problem reduces to determining the time varying backbone curve behavior. To efficiently solve the inverse kinematics problem, the authors introduce a âmodalâ approach, in which a set of intrinsic backbone curve shape functions are restricted to a modal form. The singularities of the modal approach, modal non-degeneracy conditions, and modal switching are considered. For discretely segmented morphologies, the authors introduce âfittingâ algorithms that determine the actuator displacements that cause the discrete manipulator to adhere to the backbone curve. These techniques are demonstrated with planar and spatial mechanism examples. They have also been implemented on a 30 degree-of-freedom robot prototype
Source Coding for Quasiarithmetic Penalties
Huffman coding finds a prefix code that minimizes mean codeword length for a
given probability distribution over a finite number of items. Campbell
generalized the Huffman problem to a family of problems in which the goal is to
minimize not mean codeword length but rather a generalized mean known as a
quasiarithmetic or quasilinear mean. Such generalized means have a number of
diverse applications, including applications in queueing. Several
quasiarithmetic-mean problems have novel simple redundancy bounds in terms of a
generalized entropy. A related property involves the existence of optimal
codes: For ``well-behaved'' cost functions, optimal codes always exist for
(possibly infinite-alphabet) sources having finite generalized entropy. Solving
finite instances of such problems is done by generalizing an algorithm for
finding length-limited binary codes to a new algorithm for finding optimal
binary codes for any quasiarithmetic mean with a convex cost function. This
algorithm can be performed using quadratic time and linear space, and can be
extended to other penalty functions, some of which are solvable with similar
space and time complexity, and others of which are solvable with slightly
greater complexity. This reduces the computational complexity of a problem
involving minimum delay in a queue, allows combinations of previously
considered problems to be optimized, and greatly expands the space of problems
solvable in quadratic time and linear space. The algorithm can be extended for
purposes such as breaking ties among possibly different optimal codes, as with
bottom-merge Huffman coding.Comment: 22 pages, 3 figures, submitted to IEEE Trans. Inform. Theory, revised
per suggestions of reader
Alpha Entanglement Codes: Practical Erasure Codes to Archive Data in Unreliable Environments
Data centres that use consumer-grade disks drives and distributed
peer-to-peer systems are unreliable environments to archive data without enough
redundancy. Most redundancy schemes are not completely effective for providing
high availability, durability and integrity in the long-term. We propose alpha
entanglement codes, a mechanism that creates a virtual layer of highly
interconnected storage devices to propagate redundant information across a
large scale storage system. Our motivation is to design flexible and practical
erasure codes with high fault-tolerance to improve data durability and
availability even in catastrophic scenarios. By flexible and practical, we mean
code settings that can be adapted to future requirements and practical
implementations with reasonable trade-offs between security, resource usage and
performance. The codes have three parameters. Alpha increases storage overhead
linearly but increases the possible paths to recover data exponentially. Two
other parameters increase fault-tolerance even further without the need of
additional storage. As a result, an entangled storage system can provide high
availability, durability and offer additional integrity: it is more difficult
to modify data undetectably. We evaluate how several redundancy schemes perform
in unreliable environments and show that alpha entanglement codes are flexible
and practical codes. Remarkably, they excel at code locality, hence, they
reduce repair costs and become less dependent on storage locations with poor
availability. Our solution outperforms Reed-Solomon codes in many disaster
recovery scenarios.Comment: The publication has 12 pages and 13 figures. This work was partially
supported by Swiss National Science Foundation SNSF Doc.Mobility 162014, 2018
48th Annual IEEE/IFIP International Conference on Dependable Systems and
Networks (DSN
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