Gymnasium. [Waterman]

E.W. Arnold, architect. Built 1894. Funded by a challenge grant of $20,000.00 by Joshua W. Waterman of Detroit with contributions from others, including students, and funding from the Regents. Addition completed in 1916. Demolished in 1977 to make room for the expansion of the adjacent Chemistry Building. View from southwest. Person with horse and cart in front of building.

ALA Library War Service, Bronx, NY

Librarian distributing books from cart at Red Cross army hospital

Constructing and evaluating alternative prediction models for identifying clinically relevant cases in an STD clinic

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

The Kinetics of Myeloid Derived Suppressor Cell Frequency and Function in Chronic Retroviral Infections

Thesis (Ph.D.)--University of Washington, 2016-06

Reliability measures for local nodes assessment in classification trees

Most of the modem developments with classification trees are aimed at improving their predictive capacity. This article considers a curiously neglected aspect of classification trees, namely the reliability of predictions that come from a given classification tree. In the sense that a node of a tree represents a point in the predictor space in the limit, the aim of this article is the development of localized assessment of the reliability of prediction rules. A classification tree may be used either to provide a probability forecast, where for each node the membership probabilities for each class constitutes the prediction, or a true classification where each new observation is predictively assigned to a unique class. Correspondingly, two types of reliability measure will be derived-namely, prediction reliability and classification reliability. We use bootstrapping methods as the main tool to construct these measures. We also provide a suite of graphical displays by which they may be easily appreciated. In addition to providing some estimate of the reliability of specific forecasts of each type, these measures can also be used to guide future data collection to improve the effectiveness of the tree model. The motivating example we give has a binary response, namely the presence or absence of a species of Eucalypt, Eucalyptus cloeziana, at a given sampling location in response to a suite of environmental covariates, (although the methods are not restricted to binary response data).

Molecular cloning and characterization of the mouse Na+ sulfate cotransporter gene (Slc13a4): structure and expression

Sulfate is an essential ion required for numerous functions in mammalian physiology. Due to its hydrophilic nature, cells require sulfate transporters on their plasma membranes to allow entry of sulfate into cells. In this study, we identified a new mouse Na+-sulfate cotransporter (mNaS2), characterized its tissue distribution and determined its cDNA and gene (Slc13a4) structures. mNaS2 mRNA was expressed in placenta, brain, lung, eye, heart, testis, thymus and liver. The mouse NaS2 cDNA spans 3384 nucleotides and its open frame encodes a protein of 624 amino acids. Slc13a4 maps to mouse chromosome 6131 and contains 16 exons, spanning over 40 kb in length. Its 5'-flanking region contains CART- and GC-box motifs and a number of putative transcription factor binding sites, including GATA-1, MTF-1, STAT6 and HNF4 consensus sequences. This is the first study to define the tissue distribution of mNaS2 and resolve its cDNA and gene structures, which will allow us to investigate mNaS2 gene expression in vivo and determine its role in mammalian physiology.

Diagnosis of diabetes mellitus: case of different cutoff values: A data mining approach

Objective: An estimation of cut-off points for the diagnosis of diabetes mellitus (DM) based on individual risk factors. Methods: A subset of the 1991 Oman National Diabetes Survey is used, including all patients with a 2h post glucose load >= 200 mg/dl (278 subjects) and a control group of 286 subjects. All subjects previously diagnosed as diabetic and all subjects with missing data values were excluded. The data set was analyzed by use of the SPSS Clementine data mining system. Decision Tree Learners (C5 and CART) and a method for mining association rules (the GRI algorithm) are used. The fasting plasma glucose (FPG), age, sex, family history of diabetes and body mass index (BMI) are input risk factors (independent variables), while diabetes onset (the 2h post glucose load >= 200 mg/dl) is the output (dependent variable). All three techniques used were tested by use of crossvalidation (89.8%). Results: Rules produced for diabetes diagnosis are: A- GRI algorithm (1) FPG>=108.9 mg/dl, (2) FPG>=107.1 and age>39.5 years. B- CART decision trees: FPG >=110.7 mg/dl. C- The C5 decision tree learner: (1) FPG>=95.5 and 54, (2) FPG>=106 and 25.2 kg/m2. (3) FPG>=106 and =133 mg/dl. The three techniques produced rules which cover a significant number of cases (82%), with confidence between 74 and 100%. Conclusion: Our approach supports the suggestion that the present cut-off value of fasting plasma glucose (126 mg/dl) for the diagnosis of diabetes mellitus needs revision, and the individual risk factors such as age and BMI should be considered in defining the new cut-off value.

The linguistic situation in Kirkuk:a sociolinguistic study

This study is concerned with the linguistic situation in the town of Kirkuk in north eastern Iraq. In this town there are three main ethnic groups: Kurds, Arabs and Turkmana with some very smell minorities such as Chaldeene, Assyrians and Armenians. The languages spoken by these three ethnic groups belong to different language Family groups. In the First cart of the study the historical background of the population, a review of the literature, both of the present linguistic situation in Kirkuk end of relevant sociolinguistics in general, and the theoretical Framework, have been discussed in detail in order to provide background to this study which is mainly concerned with the Following areas: 1. The relationships existing between ethnic background and language usage and language loyalty in Kirkuk. 2. The attitudes of Kirkukiane towards language maintenance and language shift in Kirkuk. 3. Bilingual, multilingual individual communicative competence of Kurds, Arabs and Turkmans in the languages concerned, including the degree to which such a speaker is bilingual or multilingual and the nature of bilingualism or multilingualism in different domains and situations in Kirkuk. To throw light a these areas a situationally-oriented language survey was conducted; the relevant data was collected by randomly distributed questionnaire, by parsonal interview, by personal observation of language use and language attitudes in this town. The data subjected to commuter analysis and the results proved that the were no significant and substantial correlations between the language use, attitudes and competence based on the socio-economic status of respondents in this town, on the other hand, the correlations between the ethnic backgrounds and the language, use, attitudes and competence are indisoutable.

A computational model of prosody for Yorùbá text-to-speech synthesis

This work examines prosody modelling for the Standard Yorùbá (SY) language in the context of computer text-to-speech synthesis applications. The thesis of this research is that it is possible to develop a practical prosody model by using appropriate computational tools and techniques which combines acoustic data with an encoding of the phonological and phonetic knowledge provided by experts. Our prosody model is conceptualised around a modular holistic framework. The framework is implemented using the Relational Tree (R-Tree) techniques (Ehrich and Foith, 1976). R-Tree is a sophisticated data structure that provides a multi-dimensional description of a waveform. A Skeletal Tree (S-Tree) is first generated using algorithms based on the tone phonological rules of SY. Subsequent steps update the S-Tree by computing the numerical values of the prosody dimensions. To implement the intonation dimension, fuzzy control rules where developed based on data from native speakers of Yorùbá. The Classification And Regression Tree (CART) and the Fuzzy Decision Tree (FDT) techniques were tested in modelling the duration dimension. The FDT was selected based on its better performance. An important feature of our R-Tree framework is its flexibility in that it facilitates the independent implementation of the different dimensions of prosody, i.e. duration and intonation, using different techniques and their subsequent integration. Our approach provides us with a flexible and extendible model that can also be used to implement, study and explain the theory behind aspects of the phenomena observed in speech prosody.

A modular holistic approach to prosody modelling for Standard Yorùbá speech synthesis

This paper presents a novel prosody model in the context of computer text-to-speech synthesis applications for tone languages. We have demonstrated its applicability using the Standard Yorùbá (SY) language. Our approach is motivated by the theory that abstract and realised forms of various prosody dimensions should be modelled within a modular and unified framework [Coleman, J.S., 1994. Polysyllabic words in the YorkTalk synthesis system. In: Keating, P.A. (Ed.), Phonological Structure and Forms: Papers in Laboratory Phonology III, Cambridge University Press, Cambridge, pp. 293–324]. We have implemented this framework using the Relational Tree (R-Tree) technique. R-Tree is a sophisticated data structure for representing a multi-dimensional waveform in the form of a tree. The underlying assumption of this research is that it is possible to develop a practical prosody model by using appropriate computational tools and techniques which combine acoustic data with an encoding of the phonological and phonetic knowledge provided by experts. To implement the intonation dimension, fuzzy logic based rules were developed using speech data from native speakers of Yorùbá. The Fuzzy Decision Tree (FDT) and the Classification and Regression Tree (CART) techniques were tested in modelling the duration dimension. For practical reasons, we have selected the FDT for implementing the duration dimension of our prosody model. To establish the effectiveness of our prosody model, we have also developed a Stem-ML prosody model for SY. We have performed both quantitative and qualitative evaluations on our implemented prosody models. The results suggest that, although the R-Tree model does not predict the numerical speech prosody data as accurately as the Stem-ML model, it produces synthetic speech prosody with better intelligibility and naturalness. The R-Tree model is particularly suitable for speech prosody modelling for languages with limited language resources and expertise, e.g. African languages. Furthermore, the R-Tree model is easy to implement, interpret and analyse.

A fuzzy decision tree-based duration model for Standard Yorùbá text-to-speech synthesis

In this paper, we present syllable-based duration modelling in the context of a prosody model for Standard Yorùbá (SY) text-to-speech (TTS) synthesis applications. Our prosody model is conceptualised around a modular holistic framework. This framework is implemented using the Relational Tree (R-Tree) techniques. An important feature of our R-Tree framework is its flexibility in that it facilitates the independent implementation of the different dimensions of prosody, i.e. duration, intonation, and intensity, using different techniques and their subsequent integration. We applied the Fuzzy Decision Tree (FDT) technique to model the duration dimension. In order to evaluate the effectiveness of FDT in duration modelling, we have also developed a Classification And Regression Tree (CART) based duration model using the same speech data. Each of these models was integrated into our R-Tree based prosody model. We performed both quantitative (i.e. Root Mean Square Error (RMSE) and Correlation (Corr)) and qualitative (i.e. intelligibility and naturalness) evaluations on the two duration models. The results show that CART models the training data more accurately than FDT. The FDT model, however, shows a better ability to extrapolate from the training data since it achieved a better accuracy for the test data set. Our qualitative evaluation results show that our FDT model produces synthesised speech that is perceived to be more natural than our CART model. In addition, we also observed that the expressiveness of FDT is much better than that of CART. That is because the representation in FDT is not restricted to a set of piece-wise or discrete constant approximation. We, therefore, conclude that the FDT approach is a practical approach for duration modelling in SY TTS applications. © 2006 Elsevier Ltd. All rights reserved.

Le cognitive enhancement en milieu universitaire : entre souffrance psychique individuelle, culture de performance et insécurités sociales

Ce projet de mémoire s’intéresse à la mise en relation du cognitive enhancement observé dans les universités occidentales contemporaines et de la société dans laquelle il s’insère. Nous avons voulu détacher la perspective du phénomène des analyses principalement orientées vers les programmes de sciences de la santé et de droit, ainsi que de l’approche quantitative, clinique, athéorique et somme toute moralisatrice qui lui est usuellement accordée afin d’explorer la nature des pratiques d’usages de psychotropes des étudiants universitaires en sciences humaines et sociales en vue d’augmenter leurs performances cognitives, d’approfondir la compréhension des raisonnements sous-jacents à ces pratiques, puis de resituer ces derniers dans leur contexte élargi. Nous avons interrogé treize étudiants de divers programmes de sciences humaines et sociales consommant, ou ayant déjà consommé, des psychotropes en vue de rehausser leurs performances cognitives en contexte académique. Les résultats suggèrent un écart dans la nature de leurs pratiques d’usage par rapport aux domaines d’études habituellement préconisés en ce sens qu’une grande variété de substances sont considérées comme supports cognitifs ; ensuite, que le recours aux psychotropes dans une visée de performance cognitive s’éloigne des logiques de la nécessité médicale et de la toxicomanie. En premier lieu, le cognitive enhancement est associé par plusieurs à une souffrance psychique liée à une perte de repères existentiels et les étudiants y ont recours dans une optique de compréhension de soi et de quête de repères dans un monde qu’ils ressentent comme instable. En second lieu, la consommation de psychotropes s’apparente davantage à un désir de satisfaire aux conditions incertaines et menaçantes des demandes externes de performance telles qu’ils les appréhendent qu’à un souci de soigner quelque condition médicale de la cognition. Nous pensons que le rapport au psychotrope qu’entretiennent les étudiants universitaires en sciences humaines et sociales s’insère en toute cohérence dans les discours et injonctions contemporaines de performance, en ce sens que leur souffrance psychique individuelle expose les limites de ce que la société attend d’eux.

Vita Christi / ex euangeliis [et] scriptoribus orthodoxis p[er] Ludolphum Saxonem ... carthusianum excerpta, ad vetustorum exe[m]plarium fidem recognita ... ; Io. Amplexor ad lectorem ...

Colofón

Data Mining for Network Intrusion Detection : A comparison of data mining algorithms and an analysis of relevant features for detecting cyber-attacks

Data mining can be defined as the extraction of implicit, previously un-known, and potentially useful information from data. Numerous re-searchers have been developing security technology and exploring new methods to detect cyber-attacks with the DARPA 1998 dataset for Intrusion Detection and the modified versions of this dataset KDDCup99 and NSL-KDD, but until now no one have examined the performance of the Top 10 data mining algorithms selected by experts in data mining. The compared classification learning algorithms in this thesis are: C4.5, CART, k-NN and Naïve Bayes. The performance of these algorithms are compared with accuracy, error rate and average cost on modified versions of NSL-KDD train and test dataset where the instances are classified into normal and four cyber-attack categories: DoS, Probing, R2L and U2R. Additionally the most important features to detect cyber-attacks in all categories and in each category are evaluated with Weka’s Attribute Evaluator and ranked according to Information Gain. The results show that the classification algorithm with best performance on the dataset is the k-NN algorithm. The most important features to detect cyber-attacks are basic features such as the number of seconds of a network connection, the protocol used for the connection, the network service used, normal or error status of the connection and the number of data bytes sent. The most important features to detect DoS, Probing and R2L attacks are basic features and the least important features are content features. Unlike U2R attacks, where the content features are the most important features to detect attacks.

Étude exploratoire des transitions de milieux de vie en communauté des personnes présentant une déficience intellectuelle

Cette étude exploratoire dresse un portrait des transitions de milieux de vie (MDV) dans des Centres de réadaptation en déficience intellectuelle et en troubles envahissants du développement (CRDITED) de la grande région de Montréal. Elle permet d’identifier 1) les pratiques de transition de MDV des intervenants pivots en CRDITED, 2) les critères de succès de la transition de MDV et les moyens de les évaluer selon les personnes présentant une déficience intellectuelle et les intervenants pivots et 3) l’écart entre les pratiques souhaitées et les pratiques actuelles à partir du point de vue des deux types de participants. Des personnes présentant une déficience intellectuelle (N = 9) et des intervenants pivots (N = 19) se sont exprimés sur leurs expériences de transition de MDV en participant à des entretiens de groupe. Une analyse qualitative de contenu a permis d’identifier une typologie des expériences de transition de MDV du point de vue des intervenants pivots. Un seul type de transition de MDV parmi les cinq identifiés, le type préparée, offre des conditions favorisant la réalisation de la transition dans des conditions satisfaisantes pour les intervenants pivots. Les autres types de transitions (types dernière minute, explosive, clé en main et salle d’attente) offrent peu d’occasions pour la personne présentant une déficience intellectuelle de s’impliquer dans le processus de transition. Les propos des intervenants pivots permettent d’identifier les caractéristiques d’une transition de MDV qu’ils jugent idéale (type comme si c’était moi). Les types de transitions sont comparés entre eux sur deux axes, soit sur l’axe représentant un continuum d’implication de la personne présentant une déficience intellectuelle dans sa propre transition et sur l’axe identifiant les grandes étapes de réalisation de la transition. Les résultats permettent de déceler un écart important entre les transitions actuellement effectuées et les politiques, intentions et engagements de l’offre de service auprès de cette clientèle, notamment au regard de l’implication de la personne présentant une déficience intellectuelle dans les décisions relatives à sa transition de MDV. L’étude permet aussi d’identifier trois dimensions importantes de l’évaluation du succès de la transition selon les perspectives des personnes présentant une déficience intellectuelle et des intervenants pivots. Les dimensions identifiées sont : bien-être psychologique et comportement, santé physique et collaboration. Les propos des intervenants pivots permettent de constater qu’il existe parfois un paradoxe entre leurs perceptions du succès de la transition de MDV et celles des personnes présentant une déficience intellectuelle. L’interprétation des résultats a permis d’élaborer des recommandations afin de favoriser de meilleures pratiques de transition.