Koran : manuscript, [1892-1896].

marginal notes/ examined by M. Zacharia 8/24/89."

Plantarum in Mari Rubro hucusque collectarum enumeratio (juvante A. Figari)

"Dabat auctor die 26 aprilis 1858."--Note at end of text.

We/Me

Thesis (Master's)--University of Washington, 2016-06

A Temporary Hometown: Gendered Labor and Social Citizenship in Bremerton, Washington, a Domestic Military Colony

Thesis (Master's)--University of Washington, 2016-06

Searching for schizophrenia in ancient Greek and Roman literature: A systematic review

Objective: The aim of this study was to systematically examine ancient Roman and Greek texts to identify descriptions of schizophrenia and related disorders. Method: Material from Greek and Roman literature dating from the 5th Century BC to the beginning of the 2nd Century AD was systematically reviewed for symptoms of mental illness. DSM IV criteria were applied in order to identify material related to schizophrenia and related disorders. Results: The general public had an awareness of psychotic disorders, because the symptoms were described in works of fiction and in historical accounts of malingering. There were isolated instances of text related to psychotic symptoms in the residents of ancient Rome and Greece, but no written material describing a condition that would meet modern diagnostic criteria for schizophrenia. Conclusion: In contrast to many other psychiatric disorders that are represented in ancient Greek and Roman literature, there were no descriptions of individuals with schizophrenia in the material assessed in this review.

Turning configural processing upside down: Part and whole body postures

Like faces, body postures are susceptible to an inversion effect in untrained viewers. The inversion effect may be indicative of configural processing, but what kind of configural processing is used for the recognition of body postures must be specified. The information available in the body stimulus was manipulated. The presence and magnitude of inversion effects were compared for body parts, scrambled bodies, and body halves relative to whole bodies and to corresponding conditions for faces and houses. Results suggest that configural body posture recognition relies on the structural hierarchy of body parts, not the parts themselves or a complete template match. Configural recognition of body postures based on information about the structural hierarchy of parts defines an important point on the configural processing continuum, between recognition based on first-order spatial relations and recognition based on holistic undifferentiated template matching.

T-Q relation and exact solution for the XYZ chain with general non-diagonal boundary terms

We propose that the Baxter's Q-operator for the quantum XYZ spin chain with open boundary conditions is given by the j -> infinity limit of the corresponding transfer matrix with spin-j (i.e., (2j + I)-dimensional) auxiliary space. The associated T-Q relation is derived from the fusion hierarchy of the model. We use this relation to determine the Bethe Ansatz solution of the eigenvalues of the fundamental transfer matrix. The solution yields the complete spectrum of the Hamiltonian. (c) 2006 Elsevier B.V. All rights reserved.

Authorship Attribution with Support Vector Machines

In this paper we explore the use of text-mining methods for the identification of the author of a text. We apply the support vector machine (SVM) to this problem, as it is able to cope with half a million of inputs it requires no feature selection and can process the frequency vector of all words of a text. We performed a number of experiments with texts from a German newspaper. With nearly perfect reliability the SVM was able to reject other authors and detected the target author in 60–80% of the cases. In a second experiment, we ignored nouns, verbs and adjectives and replaced them by grammatical tags and bigrams. This resulted in slightly reduced performance. Author detection with SVMs on full word forms was remarkably robust even if the author wrote about different topics.

A Correlation Analysis on LSA and HAL Semantic Space Models

In this paper, we compare a well-known semantic spacemodel, Latent Semantic Analysis (LSA) with another model, Hyperspace Analogue to Language (HAL) which is widely used in different area, especially in automatic query refinement. We conduct this comparative analysis to prove our hypothesis that with respect to ability of extracting the lexical information from a corpus of text, LSA is quite similar to HAL. We regard HAL and LSA as black boxes. Through a Pearsonrsquos correlation analysis to the outputs of these two black boxes, we conclude that LSA highly co-relates with HAL and thus there is a justification that LSA and HAL can potentially play a similar role in the area of facilitating automatic query refinement. This paper evaluates LSA in a new application area and contributes an effective way to compare different semantic space models.

Document re-ranking by generality in bio-medical information retrieval

Document ranking is an important process in information retrieval (IR). It presents retrieved documents in an order of their estimated degrees of relevance to query. Traditional document ranking methods are mostly based on the similarity computations between documents and query. In this paper we argue that the similarity-based document ranking is insufficient in some cases. There are two reasons. Firstly it is about the increased information variety. There are far too many different types documents available now for user to search. The second is about the users variety. In many cases user may want to retrieve documents that are not only similar but also general or broad regarding a certain topic. This is particularly the case in some domains such as bio-medical IR. In this paper we propose a novel approach to re-rank the retrieved documents by incorporating the similarity with their generality. By an ontology-based analysis on the semantic cohesion of text, document generality can be quantified. The retrieved documents are then re-ranked by their combined scores of similarity and the closeness of documents’ generality to the query’s. Our experiments have shown an encouraging performance on a large bio-medical document collection, OHSUMED, containing 348,566 medical journal references and 101 test queries.

Collaborative filtering on data streams

Collaborate Filtering is one of the most popular recommendation algorithms. Most Collaborative Filtering algorithms work with a static set of data. This paper introduces a novel approach to providing recommendations using Collaborative Filtering when user rating is received over an incoming data stream. In an incoming stream there are massive amounts of data arriving rapidly making it impossible to save all the records for later analysis. By dynamically building a decision tree for every item as data arrive, the incoming data stream is used effectively although an inevitable trade off between accuracy and amount of memory used is introduced. By adding a simple personalization step using a hierarchy of the items, it is possible to improve the predicted ratings made by each decision tree and generate recommendations in real-time. Empirical studies with the dynamically built decision trees show that the personalization step improves the overall predicted accuracy.

On sensor network segmentation for urban water distribution monitoring

Identifying water wastage in forms of leaks in a water distribution network of any city becomes essential as droughts are presenting serious threats to few major cities. In this paper, we propose a deployment of sensor network for monitoring water flow in any water distribution network. We cover the issues related with designing such a dedicated sensor network by considering types of sensors required, sensors' functionality, data collection, and providing computation serving as leak detection mechanism. The main focus of this paper is on appropriate network segmentation that provides the base for hierarchical approach to pipes' failure detection. We show a method for sensors allocation to the network in order to facilitate effective pipes monitoring. In general, the identified computational problem belongs to hard problems. The paper shows a heuristic method to build effective hierarchy of the network segmentation.

Concept-based document readability in domain specific information retrieval

Domain specific information retrieval has become in demand. Not only domain experts, but also average non-expert users are interested in searching domain specific (e.g., medical and health) information from online resources. However, a typical problem to average users is that the search results are always a mixture of documents with different levels of readability. Non-expert users may want to see documents with higher readability on the top of the list. Consequently the search results need to be re-ranked in a descending order of readability. It is often not practical for domain experts to manually label the readability of documents for large databases. Computational models of readability needs to be investigated. However, traditional readability formulas are designed for general purpose text and insufficient to deal with technical materials for domain specific information retrieval. More advanced algorithms such as textual coherence model are computationally expensive for re-ranking a large number of retrieved documents. In this paper, we propose an effective and computationally tractable concept-based model of text readability. In addition to textual genres of a document, our model also takes into account domain specific knowledge, i.e., how the domain-specific concepts contained in the document affect the document’s readability. Three major readability formulas are proposed and applied to health and medical information retrieval. Experimental results show that our proposed readability formulas lead to remarkable improvements in terms of correlation with users’ readability ratings over four traditional readability measures.

Refinement-robust fairness

We motivate and study the robustness of fairness notions under refinement of transitions and places in Petri nets. We show that the classical notions of weak and strong fairness are not robust and we propose a hierarchy of increasingly strong, refinement-robust fairness notions. That hierarchy is based on the conflict structure of transitions, which characterizes the interplay between choice and synchronization in a fairness notion. Our fairness notions are defined on non-sequential runs, but we show that the most important notions can be easily expressed on sequential runs as well. The hierarchy is further motivated by a brief discussion on the computational power of the fairness notions.

PELO SAGRADO DIREITO DE DECIDIR: A CONTRIBUIÇÃO DE CATÓLICAS PELO DIREITO DE DECIDIR NAS DISCUSSÕES SOBRE LAICIDADE, DIREITOS REPRODUTIVOS E DESCRIMINALIZAÇÃO DO ABORTO NO BRASIL.

A presente dissertação procura apresentar uma análise sobre a relação entre política e religião numa perspectiva de gênero, com o objetivo de evidenciar de que maneira a relação entre Igreja e Estado legitima as desigualdades sexuais presentes na sociedade brasileira. Essa análise procura demonstrar/ressaltar como as práticas políticas do país tem prejudicado a possibilidade de ampliação dos direitos reprodutivos devido à influência histórica da cosmovisão católica no que se refere à moral sexual. Essa influência religiosa, no que diz respeito à ampliação das políticas públicas para a reprodução, afeta negativamente a vida das mulheres, principalmente as mulheres pobres e fere o caráter laico do Estado brasileiro. Neste sentido, a dissertação, além de evidenciar esta situação, procura apresentar no trabalho da organização Católicas pelo Direito de Decidir, uma possibilidade de atuação política e teórica, que se posiciona contra o discurso radical sobre o aborto advindo da hierarquia da Igreja Católica e que é compartilhado por setores fundamentalistas de outras denominações cristãs. Católicas pelo Direito de Decidir têm como objetivo a construção de um discurso ético-teológico feminista de apoio a descriminalização do aborto e pelo direito das mulheres decidirem sobre a sua vida reprodutiva sem sofrerem nenhum tipo de impedimento ou discriminação por suas decisões.