The immune system has the ability to discriminate self from non-self proteins and also make appropriate immune responses to pathogens. A fundamental problem is to understand the genomic differences and similarities among the sets of self peptides and non-self peptides. The sequencing of human, mouse and numerous pathogen genomes and cataloging of their respective proteomes allows host self and non-self peptides to be identified. T-cells make this determination at the peptide level based on peptides displayed by MHC molecules.<p>In this project, peptides of specific lengths (k-mers) are generated from each protein in the proteomes of various model organisms. The set of unique k-mers for each species is stored in a library and defines its "immunological self". Using the libraries, organisms can be compared to determine the levels of peptide overlap. The observed levels of overlap can also be compared with levels which can be expected "at random" and statistical conclusions drawn.<p>A problem with this procedure is that sequence information in public protein databases (Swiss-PROT, UniProt, PIR) often contains ambiguities. Three strategies for dealing with such ambiguities have been explored in earlier work and the strategy of removing ambiguous k-mers is used here.<p>Peptide fragments (k-mers) which elicit immune responses are often localized within the sequences of proteins from pathogens. These regions are known as "immunodominants" (i.e., hot spots) and are important in immunological work. After investigating the peptide universes and their overlaps, the question of whether known regions of immunological significance (e.g., epitope) come from regions of low host-similarity is explored. The known regions of epitopes are compared with the regions of low host-similarity (i.e., non-overlaps) between HIV-1 and human proteomes at the 7-mer level. Results show that the correlation between these two regions is not statistically significant. In addition, pairs involving human and human viruses are explored. For these pairs, one graph for each k-mer level is generated showing the actual numbers of matches between organisms versus the expected numbers. From graphs for 5-mer and 6-mer level, we can see that the number of overlapping occurrences increases as the size of the viral proteome increases.<p>A detailed investigation of the overlaps/non-overlaps between viral proteome and human proteome reveals that the distribution of the locations of these overlaps/non-overlaps may have "structure" (e.g. locality clustering). Thus, another question that is explored is whether the locality clustering is statistically significant. A chi-square analysis is used to analyze the locality clustering. Results show that the locality clusterings for HIV-1, HIV-2 and Influenza A virus at the 5-mer, 6-mer and 7-mer levels are statistically significant. Also, for self-similarity of human protein Desmoglein 3 to the remaining human proteome, it shows that the locality clustering is not statistically significant at the 5-mer level while it is at the 6-mer and 7-mer levels.

The immune system has the ability to discriminate self from non-self proteins and also make appropriate immune responses to pathogens. A fundamental problem is to understand the genomic differences and similarities among the sets of self peptides and non-self peptides. The sequencing of human, mouse and numerous pathogen genomes and cataloging of their respective proteomes allows host self and non-self peptides to be identified. T-cells make this determination at the peptide level based on peptides displayed by MHC molecules.<p>In this project, peptides of specific lengths (k-mers) are generated from each protein in the proteomes of various model organisms. The set of unique k-mers for each species is stored in a library and defines its "immunological self". Using the libraries, organisms can be compared to determine the levels of peptide overlap. The observed levels of overlap can also be compared with levels which can be expected "at random" and statistical conclusions drawn.<p>A problem with this procedure is that sequence information in public protein databases (Swiss-PROT, UniProt, PIR) often contains ambiguities. Three strategies for dealing with such ambiguities have been explored in earlier work and the strategy of removing ambiguous k-mers is used here.<p>Peptide fragments (k-mers) which elicit immune responses are often localized within the sequences of proteins from pathogens. These regions are known as "immunodominants" (i.e., hot spots) and are important in immunological work. After investigating the peptide universes and their overlaps, the question of whether known regions of immunological significance (e.g., epitope) come from regions of low host-similarity is explored. The known regions of epitopes are compared with the regions of low host-similarity (i.e., non-overlaps) between HIV-1 and human proteomes at the 7-mer level. Results show that the correlation between these two regions is not statistically significant. In addition, pairs involving human and human viruses are explored. For these pairs, one graph for each k-mer level is generated showing the actual numbers of matches between organisms versus the expected numbers. From graphs for 5-mer and 6-mer level, we can see that the number of overlapping occurrences increases as the size of the viral proteome increases.<p>A detailed investigation of the overlaps/non-overlaps between viral proteome and human proteome reveals that the distribution of the locations of these overlaps/non-overlaps may have "structure" (e.g. locality clustering). Thus, another question that is explored is whether the locality clustering is statistically significant. A chi-square analysis is used to analyze the locality clustering. Results show that the locality clusterings for HIV-1, HIV-2 and Influenza A virus at the 5-mer, 6-mer and 7-mer levels are statistically significant. Also, for self-similarity of human protein Desmoglein 3 to the remaining human proteome, it shows that the locality clustering is not statistically significant at the 5-mer level while it is at the 6-mer and 7-mer levels.

In this thesis, a tool to visualize duplicate parts in a series of given documents is developed. Text duplicates are very common nowadays in all fields. This behavior severelyharms the rights of the original authors though it facilitates the work of those whocopy from them. Effective legal measures have been taken when it comes to copyrightissue. An increasing large number of people have paid serious attention to what theywrite when they refer to other people's works. Although references are properly madeby many who admire and respect others' achievements, plagiarism takes place all thetime. Therefore, an intuitive way of visualizing duplicate parts is needed so thatpeople can easily grasp the purpose and decide the legality of those duplicates. Whenit comes to computer science, software clone is very typical phenomenon amongdifferent development groups or even within one group. Since a piece of softwareusually have its hierarchy, it is also interesting to group members when they do aclone detection of their own or other software. For example, if a good overview of thehierarchies is provided in a tree representation, one can easily locate the clones of aparticular node in other trees. More interaction techniques can allow concrete codeaccesses through double clicking on a highlighted node. To visualize duplicate parts in a nice and intuitive way, a visualization tool isdeveloped for this thesis project. By the time it is done, the following features shouldbe fulfilled. First, the tool can visualize similar or identical parts given a data set.Second, hierarchies of those files can be demonstrated with proper layout. Third, theuser can manipulate the data items on the screen in order to get a better insight of thedata set and help with analysis tasks. Forth, different levels of abstraction areprovided so that the user can either get an overview of all the files or specificallycheck the duplicate parts in the documents of interest. / Visualization of Text Duplicates in Documents

With the rapid development of Internet technology, as well as extensive use of broadband networks, the issues of network security are increasing. In order to deal with these complex issues, network adminstrators adopt firewalls, intrusion detection systems, intrusion prevention systems to prevent them, in addition, the collection and analysis of log are also very important. By the log analysis, administrators can understand the error messages generated by system and the abnormal behavior of external connections, and develop the corresponding security policy on the use of the security tools. The current log analyzer, besides default rules, administrators have to spend much time reviewing the syslog of their system in detail to set the corresponding rules for their system, and each analyzer has its own unique rules of definitions. The purpose of this study is to transform tens of thounds of logs into a small number of valuable patterns, classify these patterns into abnormal ones and normal ones, and sum up the logs corresponding with listed patterns to assist administrator to review. In this study, we adopt the concept of string similarity comparison, and do similarity comparison for each log to find out all patterns which presented by regular expression. After experimental evaluation, this study can indeed analyze and generate all patterns of logs automatically, and these patterns can be applies to a practical tool of network security.

This dissertation is devoted to several questions that arise in operator algebra theory. In the first part of the work we study the dilations of homomorphisms of subalgebras to the algebras that contain them. We consider the question whether a contractive homomorphism of a logmodular algebra into B(H) is completely contractive, where B(H) denotes the algebra of all bounded operators on a Hilbert space H. We show that every logmodular subalgebra of Mn(C) is unitary equivalent to an algebra of block upper triangular matrices, which was conjectured by V. Paulsen and M. Raghupathi. In particular, this shows that every unital contractive representation of a logmodular subalgebra of Mn(C) is automatically completely contractive. In the second part of the dissertation we investigate certain matrices composed of mixed, second?order moments of unitaries. The unitaries are taken from C??algebras with moments taken with respect to traces, or, alternatively, from matrix algebras with the usual trace. These sets are of interest in light of a theorem of E. Kirchberg about Connes' embedding problem and provide a new approach to it. Finally, we give a modification of I. Klep and M. Schweighofer?s algebraic reformulation of Connes' embedding problem by considering the ?-algebra of the countably generated free group. This allows us to consider only quadratic polynomials in unitary generators instead of arbitrary polynomials in self-adjoint generators.

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This study uses pitfall traps to collect ground-dwelling invertebrates in Nanjen Forest. The ground-dwelling invertebrates in Gufu Area are mainly contributed by Hymenoptera, Collembola, Coleoptera, Araneida. There is no significant difference between the diversity index of pitfalls with various distances to the edge of forest in Gufu Area. The similarity index between each pitfall is relatively low, it suggests that the heterogeneity of various micro-habitats is high. The sex-ratio of different spider species varied from 0.09 - 1.73, and the habitat preference is specific. The number of the spiders is positive-correlated with the number of the Collembola and the Orthoptera.

In this dissertation I will present and test a model linking actual applicant-interviewer demographic, human capital, and cultural capital similarity to an interviewer??s recommendation to hire. Actual similarity is proposed to influence an interviewer??s perceptions of similarity with an applicant. These perceptions, in turn, lead to the interviewer??s perceptions of the applicant??s Person-Organization (PO) fit and the applicant??s Person-Job (PJ) fit. Two main mechanisms are proposed to mediate the relationship between an interviewer??s perceptions of similarity and an interviewer??s perceptions of an applicant??s fit: liking and negative behavioral expectations. Lastly, both an interviewer??s PO and PJ fit perceptions of an applicant are posited to influence the interviewer??s recommendation to hire. A total of 118 interviewer-applicant dyads contacted through the Career Center Office at a University located in the southwestern United States participated in the study. Results partially support the model. An interviewer??s perceptions of similarity with an applicant are positively related to an interviewer??s fit evaluations. An interviewer??s negative behavioral expectations of an applicant mediate this relationship. Furthermore, perceived similarity is positively related to an interviewer??s liking of an applicant. In turn, liking is positively related to an interviewer??s PO fit perceptions. However, liking does not function as a mediator between perceived similarity and fit evaluations. Finally, fit evaluations are positively related to hiring recommendations. I discuss the main implications of the study as well as strengths, limitations, and future research.

<p>When two distributed parties want to share information stored in ontologies, they have to make sure that they refer to the same concepts. This is done matching the ontologies.</p><p>This thesis will show the implementation of a method for automatic ontology matching based on the representation of polygons. The method is used to compare two ontologies and determine the degree of similarity between them.</p><p>The first of the ontologies will be taken as the standard, while the other will be compared to it by analyzing the elements in both. According to the degrees of similarity obtained from the comparison of elements, a set of polygons is represented for the standard ontology and another one for the second ontology.</p><p>Comparing the polygons we obtain the final result of the similarity between the ontologies.</p><p>With that result it is possible to determine if two ontologies handle information referred to the same concept.</p>

<p>In this thesis, a tool to visualize duplicate parts in a series of given documents is developed.</p><p>Text duplicates are very common nowadays in all fields. This behavior severelyharms the rights of the original authors though it facilitates the work of those whocopy from them. Effective legal measures have been taken when it comes to copyrightissue. An increasing large number of people have paid serious attention to what theywrite when they refer to other people's works. Although references are properly madeby many who admire and respect others' achievements, plagiarism takes place all thetime. Therefore, an intuitive way of visualizing duplicate parts is needed so thatpeople can easily grasp the purpose and decide the legality of those duplicates. Whenit comes to computer science, software clone is very typical phenomenon amongdifferent development groups or even within one group. Since a piece of softwareusually have its hierarchy, it is also interesting to group members when they do aclone detection of their own or other software. For example, if a good overview of thehierarchies is provided in a tree representation, one can easily locate the clones of aparticular node in other trees. More interaction techniques can allow concrete codeaccesses through double clicking on a highlighted node.</p><p>To visualize duplicate parts in a nice and intuitive way, a visualization tool isdeveloped for this thesis project. By the time it is done, the following features shouldbe fulfilled. First, the tool can visualize similar or identical parts given a data set.Second, hierarchies of those files can be demonstrated with proper layout. Third, theuser can manipulate the data items on the screen in order to get a better insight of thedata set and help with analysis tasks. Forth, different levels of abstraction areprovided so that the user can either get an overview of all the files or specificallycheck the duplicate parts in the documents of interest.</p> / Visualization of Text Duplicates in Documents