Michael Thomason - Academia.edu (original) (raw)
Papers by Michael Thomason
Pattern Recognition, 1986
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Cytometry, 1990
A structural pattern recognition approach to the analysis and classification of metaphase chromos... more A structural pattern recognition approach to the analysis and classification of metaphase chromosome band patterns is presented.An operational method of representing band pattern profiles as sharp edged idealized profiles is outlined. These profiles are nonlinearly scaled to a few, but fixed number of “density” levels. Previous experience has shown that profiles of six levels are appropriate and that the differences between successive bands in these profiles are suitable for classification. String representations, which focuses on the sequences of transitions between local band pattern levels, are derived from such “difference profiles.”A method of syntactic analysis of the band transition sequences by dynamic programming for optimal (maximal probability) string‐to‐network alignments is described. It develops automatic data‐driven inference of band pattern models (Markov networks) per class, and uses these models for classification. The method does not use centromere information, but assumes the p‐q‐orientation of the band pattern profiles to be known a priori.It is experimentally established that the method can build Markov network models, which, when used for classification, show a recognition rate of about 92% on test data. The experiments used 200 samples (chromosome profiles) for each of the 22 autosome chromosome types and are designed to also investigate various classifier design problems. It is found that the use of a priori knowledge of Denver Group assignment only improved classification by 1 or 2%. A scheme for typewise normalization of the class relationship measures prove useful, partly through improvements on average results and partly through a more evenly distributed error pattern. The choice of reference of the p‐q‐orientation of the band patterns is found to be unimportant, and results of timing of the execution time of the analysis show that recent and efficient implementations can process one cell in less than 1 min on current standard hardware. A measure of divergence between data sets and Markov network models is shown to provide usable estimates of experimental classification performance.
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IEEE Transactions on Pattern Analysis and Machine Intelligence, 1993
String alignment by dynamic programming is generalized to include cyclic shift and corresponding ... more String alignment by dynamic programming is generalized to include cyclic shift and corresponding optimal alignment cost for strings representing cyclic patterns. A guided search algorithm uses bounds on alignment costs to find all optimal cyclic shifts. The bounds are derived from submatrices of an initial dynamic programming matrix. Algorithmic complexity is analyzed for major stages in the search. The applicability of the method is illustrated with satellite DNA sequences and circularly permuted protein sequences.
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41st ACM Southeast …, 2003
We describe methods for inferring and using probabilistic models that capture characteristic patt... more We describe methods for inferring and using probabilistic models that capture characteristic pattern structures that may exist in symbolic data sequences. Our emphasis is on modeling the sequence of system calls made during the execution of a software application. To obtain learning ...
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Springer eBooks, 1989
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Computer Methods and Programs in Biomedicine, 2004
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Proceedings of the ACM SIGART international symposium on Methodologies for intelligent systems, 1986
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International Journal of Computer & Information Sciences, 1976
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Proceedings of the ... IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE/RSJ International Conference on Intelligent Robots and Systems
Our research focuses on anomaly detection problems in unknown environments using Wireless Sensor ... more Our research focuses on anomaly detection problems in unknown environments using Wireless Sensor Networks (WSN). We are interested in detecting two types of abnormal events: sensory level anomalies (e.g., noise in an office without lights on) and time-related anomalies (e.g., freezing temperature in a mid-summer day).We present a novel, distributed, machine learning based anomaly detector that is able to detect time-related changes. It consists of three components. First, a Fuzzy Adaptive Resonance Theory (ART) neural network classifier is used to label multi-dimensional sensor data into discrete classes and detect sensory level anomalies. Over time, the labeled classes form a sequence of classes. Next, a symbol compressor is used to extract the semantic meaning of the temporal sequence. Finally, a Variable Memory Markov (VMM) model in the form of a Probabilistic Suffix Tree (PST) is used to model and detect time-related anomalies in the environment. To our knowledge, this is the fi...
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2012 IEEE 9th International Conference on Mobile Ad-Hoc and Sensor Systems (MASS 2012), 2012
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Human Behavior Understanding in Networked Sensing, 2014
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Pattern Recognition, 1996
Optimal alignment of two strings of length m and n is computed in time O(mn) by dynamic programmi... more Optimal alignment of two strings of length m and n is computed in time O(mn) by dynamic programming. When the strings represent cyclic patterns, the alignment computation must consider all possible shifts and the computation complexity increases accordingly. We present an algorithm for efficient dynamic programming alignment of cyclic strings which uses a previously established channeling technique to reduce the
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Journal of Parallel and Distributed Computing, 1999
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Information and Software Technology, 2000
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IEEE Transactions on Software Engineering, 1994
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Computers in Biology and Medicine, 1993
Automated analysis of chromosome band patterns using probabilistic Markov networks has been repor... more Automated analysis of chromosome band patterns using probabilistic Markov networks has been reported in previous work. Band patterns are represented as strings of symbols. Inferred from a set of learning strings, a Markov network is a model of intraband and interband relations in these strings. The inference is entirely data-driven and is accomplished using dynamic programming. This paper presents a new model of chromosome band patterns, the constrained Markov network, which is a special case of its predecessor. Substantial experimental evidence of the superiority of the new model over the old is given in terms of equal results in centromere finding and improved results in classification for the 22 autosomes. Furthermore, a method for simplification of constrained Markov networks is shown to be of considerable importance with respect to computational complexity.
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Citeseer
This paper describes a number of visualization techniques for ren-dering variable-order probabili... more This paper describes a number of visualization techniques for ren-dering variable-order probabilistic tree and automata models. The techniques, which are presented in the context of a graphical user interface for analysis of malicious mobile code, are ...
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Journal of Big Data, 2021
Detecting and delineating hot spots in data from radiation sensors is required in applications ra... more Detecting and delineating hot spots in data from radiation sensors is required in applications ranging from monitoring large geospatial areas to imaging small objects in close proximity. This paper describes a computational method for localizing potential hot spots in matrices of independent Poisson data where, in numerical terms, a hot spot is a cluster of locally higher sample mean values (higher Poisson intensity) embedded in lower sample mean values (lower background intensity). Two numerical algorithms are computed sequentially for a 3D array of 2D matrices of gross Poisson counts: (1) nonnegative tensor factorization of the 3D array to maximize a Poisson likelihood and (2) phase congruency in pertinent matrices. The indicators of potential hot spots are closed contours in phase congruency in these matrices. The method is illustrated for simulated Poisson radiation datasets, including visualization of the phase congruency contours. The method may be useful in other applications...
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Erasure codes have profound uses in wide- and medium-area storage applications. While infinite-si... more Erasure codes have profound uses in wide- and medium-area storage applications. While infinite-size codes have been developed with optimal properties, there remains a need to develop small codes with optimal properties. In this paper, we provide a framework for exploring very small codes, and we use this framework to derive optimal and near-optimal ones for discrete numbers of data bits and coding bits. These codes have heretofore been unknown and unpublished, and should be useful in practice. We also use our exploration to make observations about upper bounds for these codes, in order to gain a better understanding of them and to lead the way for future derivations of larger, optimal and near-optimal codes.
Bookmarks Related papers MentionsView impact
Pattern Recognition, 1986
Bookmarks Related papers MentionsView impact
Cytometry, 1990
A structural pattern recognition approach to the analysis and classification of metaphase chromos... more A structural pattern recognition approach to the analysis and classification of metaphase chromosome band patterns is presented.An operational method of representing band pattern profiles as sharp edged idealized profiles is outlined. These profiles are nonlinearly scaled to a few, but fixed number of “density” levels. Previous experience has shown that profiles of six levels are appropriate and that the differences between successive bands in these profiles are suitable for classification. String representations, which focuses on the sequences of transitions between local band pattern levels, are derived from such “difference profiles.”A method of syntactic analysis of the band transition sequences by dynamic programming for optimal (maximal probability) string‐to‐network alignments is described. It develops automatic data‐driven inference of band pattern models (Markov networks) per class, and uses these models for classification. The method does not use centromere information, but assumes the p‐q‐orientation of the band pattern profiles to be known a priori.It is experimentally established that the method can build Markov network models, which, when used for classification, show a recognition rate of about 92% on test data. The experiments used 200 samples (chromosome profiles) for each of the 22 autosome chromosome types and are designed to also investigate various classifier design problems. It is found that the use of a priori knowledge of Denver Group assignment only improved classification by 1 or 2%. A scheme for typewise normalization of the class relationship measures prove useful, partly through improvements on average results and partly through a more evenly distributed error pattern. The choice of reference of the p‐q‐orientation of the band patterns is found to be unimportant, and results of timing of the execution time of the analysis show that recent and efficient implementations can process one cell in less than 1 min on current standard hardware. A measure of divergence between data sets and Markov network models is shown to provide usable estimates of experimental classification performance.
Bookmarks Related papers MentionsView impact
Bookmarks Related papers MentionsView impact
IEEE Transactions on Pattern Analysis and Machine Intelligence, 1993
String alignment by dynamic programming is generalized to include cyclic shift and corresponding ... more String alignment by dynamic programming is generalized to include cyclic shift and corresponding optimal alignment cost for strings representing cyclic patterns. A guided search algorithm uses bounds on alignment costs to find all optimal cyclic shifts. The bounds are derived from submatrices of an initial dynamic programming matrix. Algorithmic complexity is analyzed for major stages in the search. The applicability of the method is illustrated with satellite DNA sequences and circularly permuted protein sequences.
Bookmarks Related papers MentionsView impact
41st ACM Southeast …, 2003
We describe methods for inferring and using probabilistic models that capture characteristic patt... more We describe methods for inferring and using probabilistic models that capture characteristic pattern structures that may exist in symbolic data sequences. Our emphasis is on modeling the sequence of system calls made during the execution of a software application. To obtain learning ...
Bookmarks Related papers MentionsView impact
Springer eBooks, 1989
Bookmarks Related papers MentionsView impact
Computer Methods and Programs in Biomedicine, 2004
Bookmarks Related papers MentionsView impact
Proceedings of the ACM SIGART international symposium on Methodologies for intelligent systems, 1986
Bookmarks Related papers MentionsView impact
International Journal of Computer & Information Sciences, 1976
Bookmarks Related papers MentionsView impact
Proceedings of the ... IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE/RSJ International Conference on Intelligent Robots and Systems
Our research focuses on anomaly detection problems in unknown environments using Wireless Sensor ... more Our research focuses on anomaly detection problems in unknown environments using Wireless Sensor Networks (WSN). We are interested in detecting two types of abnormal events: sensory level anomalies (e.g., noise in an office without lights on) and time-related anomalies (e.g., freezing temperature in a mid-summer day).We present a novel, distributed, machine learning based anomaly detector that is able to detect time-related changes. It consists of three components. First, a Fuzzy Adaptive Resonance Theory (ART) neural network classifier is used to label multi-dimensional sensor data into discrete classes and detect sensory level anomalies. Over time, the labeled classes form a sequence of classes. Next, a symbol compressor is used to extract the semantic meaning of the temporal sequence. Finally, a Variable Memory Markov (VMM) model in the form of a Probabilistic Suffix Tree (PST) is used to model and detect time-related anomalies in the environment. To our knowledge, this is the fi...
Bookmarks Related papers MentionsView impact
2012 IEEE 9th International Conference on Mobile Ad-Hoc and Sensor Systems (MASS 2012), 2012
Bookmarks Related papers MentionsView impact
Human Behavior Understanding in Networked Sensing, 2014
Bookmarks Related papers MentionsView impact
Pattern Recognition, 1996
Optimal alignment of two strings of length m and n is computed in time O(mn) by dynamic programmi... more Optimal alignment of two strings of length m and n is computed in time O(mn) by dynamic programming. When the strings represent cyclic patterns, the alignment computation must consider all possible shifts and the computation complexity increases accordingly. We present an algorithm for efficient dynamic programming alignment of cyclic strings which uses a previously established channeling technique to reduce the
Bookmarks Related papers MentionsView impact
Journal of Parallel and Distributed Computing, 1999
Bookmarks Related papers MentionsView impact
Information and Software Technology, 2000
Bookmarks Related papers MentionsView impact
IEEE Transactions on Software Engineering, 1994
Bookmarks Related papers MentionsView impact
Computers in Biology and Medicine, 1993
Automated analysis of chromosome band patterns using probabilistic Markov networks has been repor... more Automated analysis of chromosome band patterns using probabilistic Markov networks has been reported in previous work. Band patterns are represented as strings of symbols. Inferred from a set of learning strings, a Markov network is a model of intraband and interband relations in these strings. The inference is entirely data-driven and is accomplished using dynamic programming. This paper presents a new model of chromosome band patterns, the constrained Markov network, which is a special case of its predecessor. Substantial experimental evidence of the superiority of the new model over the old is given in terms of equal results in centromere finding and improved results in classification for the 22 autosomes. Furthermore, a method for simplification of constrained Markov networks is shown to be of considerable importance with respect to computational complexity.
Bookmarks Related papers MentionsView impact
Citeseer
This paper describes a number of visualization techniques for ren-dering variable-order probabili... more This paper describes a number of visualization techniques for ren-dering variable-order probabilistic tree and automata models. The techniques, which are presented in the context of a graphical user interface for analysis of malicious mobile code, are ...
Bookmarks Related papers MentionsView impact
Journal of Big Data, 2021
Detecting and delineating hot spots in data from radiation sensors is required in applications ra... more Detecting and delineating hot spots in data from radiation sensors is required in applications ranging from monitoring large geospatial areas to imaging small objects in close proximity. This paper describes a computational method for localizing potential hot spots in matrices of independent Poisson data where, in numerical terms, a hot spot is a cluster of locally higher sample mean values (higher Poisson intensity) embedded in lower sample mean values (lower background intensity). Two numerical algorithms are computed sequentially for a 3D array of 2D matrices of gross Poisson counts: (1) nonnegative tensor factorization of the 3D array to maximize a Poisson likelihood and (2) phase congruency in pertinent matrices. The indicators of potential hot spots are closed contours in phase congruency in these matrices. The method is illustrated for simulated Poisson radiation datasets, including visualization of the phase congruency contours. The method may be useful in other applications...
Bookmarks Related papers MentionsView impact
Erasure codes have profound uses in wide- and medium-area storage applications. While infinite-si... more Erasure codes have profound uses in wide- and medium-area storage applications. While infinite-size codes have been developed with optimal properties, there remains a need to develop small codes with optimal properties. In this paper, we provide a framework for exploring very small codes, and we use this framework to derive optimal and near-optimal ones for discrete numbers of data bits and coding bits. These codes have heretofore been unknown and unpublished, and should be useful in practice. We also use our exploration to make observations about upper bounds for these codes, in order to gain a better understanding of them and to lead the way for future derivations of larger, optimal and near-optimal codes.
Bookmarks Related papers MentionsView impact