Differential gene expression profiles of hepatocellular carcinomas associated or not with viral infection

Chronic hepatitis B (HBV) and C (HCV) virus infections are the most important factors associated with hepatocellular carcinoma (HCC), but tumor prognosis remains poor due to the lack of diagnostic biomarkers. In order to identify novel diagnostic markers and therapeutic targets, the gene expression profile associated with viral and non-viral HCC was assessed in 9 tumor samples by oligo-microarrays. The differentially expressed genes were examined using a z-score and KEGG pathway for the search of ontological biological processes. We selected a non-redundant set of 15 genes with the lowest P value for clustering samples into three groups using the non-supervised algorithm k-means. Fisher’s linear discriminant analysis was then applied in an exhaustive search of trios of genes that could be used to build classifiers for class distinction. Different transcriptional levels of genes were identified in HCC of different etiologies and from different HCC samples. When comparing HBV-HCC vs HCV-HCC, HBV-HCC/HCV-HCC vs non-viral (NV)-HCC, HBC-HCC vs NV-HCC, and HCV-HCC vs NV-HCC of the 58 non-redundant differentially expressed genes, only 6 genes (IKBKβ, CREBBP, WNT10B, PRDX6, ITGAV, and IFNAR1) were found to be associated with hepatic carcinogenesis. By combining trios, classifiers could be generated, which correctly classified 100% of the samples. This expression profiling may provide a useful tool for research into the pathophysiology of HCC. A detailed understanding of how these distinct genes are involved in molecular pathways is of fundamental importance to the development of effective HCC chemoprevention and treatment.

The effects of stretching on the flexibility, muscle performance and functionality of institutionalized older women

Stretching has been widely used to increase the range of motion. We assessed the effects of a stretching program on muscle-tendon length, flexibility, torque, and activities of daily living of institutionalized older women. Inclusion/exclusion criteria were according to Mini-Mental State Examination (MMSE) (>13), Barthel Index (>13) and Lysholm Scoring Scale (>84). Seventeen 67 ± 9 year-old elderly women from a nursing home were divided into 2 groups at random: the control group (CG, N = 9) participated in enjoyable cultural activities; the stretching group (SG, N = 8) performed active stretching of hamstrings, 4 bouts of 1 min each. Both groups were supervised three times per week over a period of 8 weeks. Peak torque was assessed by an isokinetic method. Both groups were evaluated by a photogrammetric method to assess muscle-tendon length of uni- and biarticular hip flexors and hamstring flexibility. All measurements were analyzed before and after 8 weeks by two-way ANOVA with the level of significance set at 5%. Hamstring flexibility increased by 30% in the SG group compared to pre-training (76.5 ± 13.0° vs 59.5 ± 9.0°, P = 0.0002) and by 9.2% compared to the CG group (76.5 ± 13.0° vs 64.0 ± 12.0°, P = 0.0018). Muscle-tendon lengths of hip biarticular flexor muscles (124 ± 6.8° vs 118.3 ± 7.6°, 5.0 ± 7.0%, P = 0.031) and eccentric knee extensor peak torque were decreased in the CG group compared to pre-test values (-49.4 ± 16.8 vs -60.5 ± 18.9 Nm, -15.7 ± 20%, P = 0.048). The stretching program was sufficient to increase hamstring flexibility and a lack of stretching can cause reduction of muscle performance.

Psychiatric disorders and cardiac anxiety in exercising and sedentary coronary artery disease patients: a case-control study

Regular physical exercise has been shown to favorably influence mood and anxiety; however, there are few studies regarding psychiatric aspects of physically active patients with coronary artery disease (CAD). The objective of the present study was to compare the prevalence of psychiatric disorders and cardiac anxiety in sedentary and exercising CAD patients. A total sample of 119 CAD patients (74 men) were enrolled in a case-control study. The subjects were interviewed to identify psychiatric disorders and responded to the Cardiac Anxiety Questionnaire. In the exercise group (N = 60), there was a lower prevalence (45 vs 81%; P < 0.001) of at least one psychiatric diagnosis, as well as multiple comorbidities, when compared to the sedentary group (N = 59). Considering the Cardiac Anxiety Questionnaire, sedentary patients presented higher scores compared to exercisers (mean ± SEM = 55.8 ± 1.9 vs 37.3 ± 1.6; P < 0.001). In a regression model, to be attending a medically supervised exercise program presented a relevant potential for a 35% reduction in cardiac anxiety. CAD patients regularly attending an exercise program presented less current psychiatric diagnoses and multiple mental-related comorbidities and lower scores of cardiac anxiety. These salutary mental effects add to the already known health benefits of exercise for CAD patients.

Role of a GenoType MTBDRplus line probe assay in early detection of multidrug-resistant tuberculosis at a Brazilian reference center

Resistance to Mycobacterium tuberculosis is a reality worldwide, and its diagnosis continues to be difficult and time consuming. To face this challenge, the World Health Organization has recommended the use of rapid molecular tests. We evaluated the routine use (once a week) of a line probe assay (Genotype MTBDRplus) for early diagnosis of resistance and for assessment of the main related risk factors over 2 years. A total of 170 samples were tested: 15 (8.8%) were resistant, and multidrug resistance was detected in 10 (5.9%). The sensitivity profile took 3 weeks (2 weeks for culture and 1 week for rapid testing). Previous treatment for tuberculosis and the persistence of positive acid-fast smears after 4 months of supervised treatment were the major risk factors observed. The use of molecular tests enabled early diagnosis of drug-resistant bacilli and led to appropriate treatment of the disease. This information has the potential to interrupt the transmission chain of resistant M. tuberculosis.

Short-term follow-up of exercise training program and beta-blocker treatment on quality of life in dogs with naturally acquired chronic mitral valve disease

This study aimed to evaluate the effects of carvedilol treatment and a regimen of supervised aerobic exercise training on quality of life and other clinical, echocardiographic, and biochemical variables in a group of client-owned dogs with chronic mitral valve disease (CMVD). Ten healthy dogs (control) and 36 CMVD dogs were studied, with the latter group divided into 3 subgroups. In addition to conventional treatment (benazepril, 0.3-0.5 mg/kg once a day, and digoxin, 0.0055 mg/kg twice daily), 13 dogs received exercise training (subgroup I; 10.3±2.1 years), 10 dogs received carvedilol (0.3 mg/kg twice daily) and exercise training (subgroup II; 10.8±1.7 years), and 13 dogs received only carvedilol (subgroup III; 10.9±2.1 years). All drugs were administered orally. Clinical, laboratory, and Doppler echocardiographic variables were evaluated at baseline and after 3 and 6 months. Exercise training was conducted from months 3-6. The mean speed rate during training increased for both subgroups I and II (ANOVA, P>0.001), indicating improvement in physical conditioning at the end of the exercise period. Quality of life and functional class was improved for all subgroups at the end of the study. The N-terminal pro-brain natriuretic peptide (NT-proBNP) level increased in subgroup I from baseline to 3 months, but remained stable after training introduction (from 3 to 6 months). For subgroups II and III, NT-proBNP levels remained stable during the entire study. No difference was observed for the other variables between the three evaluation periods. The combination of carvedilol or exercise training with conventional treatment in CMVD dogs led to improvements in quality of life and functional class. Therefore, light walking in CMVD dogs must be encouraged.

Spectral Analysis of Symmetric and Anti-Symmetric Pairwise Kernels

This work investigates theoretical properties of symmetric and anti-symmetric kernels. First chapters give an overview of the theory of kernels used in supervised machine learning. Central focus is on the regularized least squares algorithm, which is motivated as a problem of function reconstruction through an abstract inverse problem. Brief review of reproducing kernel Hilbert spaces shows how kernels define an implicit hypothesis space with multiple equivalent characterizations and how this space may be modified by incorporating prior knowledge. Mathematical results of the abstract inverse problem, in particular spectral properties, pseudoinverse and regularization are recollected and then specialized to kernels. Symmetric and anti-symmetric kernels are applied in relation learning problems which incorporate prior knowledge that the relation is symmetric or anti-symmetric, respectively. Theoretical properties of these kernels are proved in a draft this thesis is based on and comprehensively referenced here. These proofs show that these kernels can be guaranteed to learn only symmetric or anti-symmetric relations, and they can learn any relations relative to the original kernel modified to learn only symmetric or anti-symmetric parts. Further results prove spectral properties of these kernels, central result being a simple inequality for the the trace of the estimator, also called the effective dimension. This quantity is used in learning bounds to guarantee smaller variance.

Evaluation of Machine Learning Classifiers for Mobile Network Intrusion Detection Systems

Mobile malwares are increasing with the growing number of Mobile users. Mobile malwares can perform several operations which lead to cybersecurity threats such as, stealing financial or personal information, installing malicious applications, sending premium SMS, creating backdoors, keylogging and crypto-ransomware attacks. Knowing the fact that there are many illegitimate Applications available on the App stores, most of the mobile users remain careless about the security of their Mobile devices and become the potential victim of these threats. Previous studies have shown that not every antivirus is capable of detecting all the threats; due to the fact that Mobile malwares use advance techniques to avoid detection. A Network-based IDS at the operator side will bring an extra layer of security to the subscribers and can detect many advanced threats by analyzing their traffic patterns. Machine Learning(ML) will provide the ability to these systems to detect unknown threats for which signatures are not yet known. This research is focused on the evaluation of Machine Learning classifiers in Network-based Intrusion detection systems for Mobile Networks. In this study, different techniques of Network-based intrusion detection with their advantages, disadvantages and state of the art in Hybrid solutions are discussed. Finally, a ML based NIDS is proposed which will work as a subsystem, to Network-based IDS deployed by Mobile Operators, that can help in detecting unknown threats and reducing false positives. In this research, several ML classifiers were implemented and evaluated. This study is focused on Android-based malwares, as Android is the most popular OS among users, hence most targeted by cyber criminals. Supervised ML algorithms based classifiers were built using the dataset which contained the labeled instances of relevant features. These features were extracted from the traffic generated by samples of several malware families and benign applications. These classifiers were able to detect malicious traffic patterns with the TPR upto 99.6% during Cross-validation test. Also, several experiments were conducted to detect unknown malware traffic and to detect false positives. These classifiers were able to detect unknown threats with the Accuracy of 97.5%. These classifiers could be integrated with current NIDS', which use signatures, statistical or knowledge-based techniques to detect malicious traffic. Technique to integrate the output from ML classifier with traditional NIDS is discussed and proposed for future work.

Pretraining Convolutional Neural Networks for Visual Recognition

Convolutional Neural Networks (CNN) have become the state-of-the-art methods on many large scale visual recognition tasks. For a lot of practical applications, CNN architectures have a restrictive requirement: A huge amount of labeled data are needed for training. The idea of generative pretraining is to obtain initial weights of the network by training the network in a completely unsupervised way and then fine-tune the weights for the task at hand using supervised learning. In this thesis, a general introduction to Deep Neural Networks and algorithms are given and these methods are applied to classification tasks of handwritten digits and natural images for developing unsupervised feature learning. The goal of this thesis is to find out if the effect of pretraining is damped by recent practical advances in optimization and regularization of CNN. The experimental results show that pretraining is still a substantial regularizer, however, not a necessary step in training Convolutional Neural Networks with rectified activations. On handwritten digits, the proposed pretraining model achieved a classification accuracy comparable to the state-of-the-art methods.

Oppisopimuskoulutus yritysten tuottamana koulutuspalveluna: tavoitteista vaikutuksiin

Työpaikoilla tapahtuvan koulutuksen merkitys korostuu yhteiskunnassa kaikilla tasoilla nyt ja tulevaisuudessa. Tämä väitöstutkimus määrittelee oppisopimuskoulutuksen yritysten tuottamana koulutuspalveluna osana ammatillista tutkintoon johtavaa koulutusta, jota tuotetaan työpaikoilla ja yrityksissä. Väitöstutkimuksessa tarkastellaan niitä tavoitteita, joita yrityksissä oppisopimuskoulutukseen liittyy ja vaikutuksia, joita koulutusta tuottamalla yrityksessä syntyy. Tutkimuksen kohteena ovat eri alojen pienet ja keskisuuret yritykset (pk-yritykset), jotka ovat tuottaneet oppisopimuskoulutusta ja joilla on siitä vuosien kokemus. Lisäksi tutkimukseen osallistui pk-yrityksiä, joille oppisopimuskoulutus ja siihen liittyvä toiminta on vierasta. Tutkimus tuo uutta tietoa vain vähän tutkittuun aikuisten oppisopimuskoulutukseen, mutta ei sulje pois nuorten oppisopimuskoulutukseen liittyviä kysymyksiä. Tutkimus yhdistää oppisopimuskoulutuksen ja koulutuksen tuottamisen yrityksissä, mikä uudistaa sekä oppisopimuskoulutukseen, ammatilliseen koulutukseen, palvelun tuottamiseen että osaamiseen liittyvää teoreettista viitekehystä. Lisäksi tutkimus tuo yrityksille sekä oppisopimuskoulutuksen hallinnollisille tahoille palvelun tuottamisen ja siihen liittyvien tavoitteiden ja vaikutusten näkökulman. Väitöstutkimuksen teoreettinen viitekehys perustuu ja jakautuu kolmeen osaan: palveluun ja sen tuottamiseen, osaamispääomiin ja niiden eri muotoihin sekä vaikutuksiin palvelutuotannossa. Teoreettinen viitekehys kuvaa monimuotoisesti oppisopimuskoulutuksen ilmiötä, jonka olemus muuttuu sen mukaan, miten, kuka tai mikä taho sitä arvioi tai tarkastelee. Väitöstutkimus on empiiriseltä luonteeltaan kvalitatiivinen tutkimus, jonka aineisto on kerätty teemahaastatteluilla vuoden 2013 lopulla ja vuoden 2014 alussa. Aineisto on analysoitu sisällönanalyysillä aineistolähtöisesti. Tutkimusote pohjautuu abduktiiviseen päättelyyn. Tutkimustulokset esitetään ja luokitellaan niin tavoitteiden kuin vaikutusten osalta inhimillisen, rakenteellisen ja suhdepääoman kautta. Tutkimuksen mukaan oppisopimuskoulutuksen vaikutukset nähdään positiivisina ja neutraaleina, eikä alakohtaisia eroja vaikutusten osalta juuri ole. Myönteisten vaikutusten saavuttamiseen liittyy tärkeänä osana arvon luomisen ja tuottamisen kokemus molemmilla koulutukseen osallistuvilla osapuolilla. Lisäksi myönteisten vaikutusten taustalla ovat yrityksen sitoutuminen sekä työn ja koulutuksen johtamisosaaminen. Yrityksissä on tärkeää, että imago kouluttajana on hyvä. Oppisopimuskoulutuksen tuottamisesta syntyneet vaikutukset ovat asetettuja tavoitteita laajemmat, erityisesti rakenteelliseen pääomaan liittyvien vaikutusten osalta. Oppisopimuskoulutuksen vaikuttavuus yrityksessä syntyy asetettujen tavoitteiden ja vaikutusten välisestä suhteesta. Kokonaisuutena voidaan todeta, että oppisopimuskoulutuksen vaikuttavuus ja suorituskyky yrityksissä ovat hyvät, vaikka koulutuksen laatu vaihtelee jonkin verran. Oppisopimuskoulutuksen käynnistäminen, aloittaminen ja tuottaminen liittyvät usein niin sanottuihin oppisopimusagentteihin eli sellaisiin kehityshakuisiin henkilöihin, joilla jossakin elämäntilanteessa on ollut myönteisiä kokemuksia oppisopimuskoulutuksen mahdollisuuksista. Tutkimuksen mukaan oppisopimuskoulutuksen kustannukset koostuvat työsuhteesta, tietopuolisen koulutuksen aikaisesta työstä poissaolosta sekä ohjauksesta ja arvioinnista, mutta koulutusta pidetään taloudellisesti kannattavana. Oppisopimuskoulutuksen tuottamista estävät pääasiassa viestinnän ja tiedottamisen puute, koulutusmahdollisuuden tunnistamatta jääminen, yritysten heikko koulutuskulttuuri sekä epäselvät mielikuvat ja käsitykset. Nuorten oppisopimuskoulutuksen toteuttamisen hidasteina ovat tutkimuksen mukaan työsuhteeseen ja talouteen liittyvät seikat, nuorten kasvun vaiheeseen sisältyvät tekijät sekä monenlaiset pedagogiset ja eettiset kysymykset. Lisäksi tutkimuksessa havaittiin, että nuori on käsitteenä ja viiteryhmänä epämääräinen. Ammatillisen koulutuksen ja oppisopimuskoulutuksen eri muodot ja monet käsitteet myös aiheuttavat epäselvyyttä molemmissa tutkimuksen konteksteissa eli yrityksissä, joissa oppisopimuskoulutusta tuotetaan sekä yrityksissä, joissa sitä ei tuoteta.

Spectral retinal image processing and analysis for ophthalmology

Diabetic retinopathy, age-related macular degeneration and glaucoma are the leading causes of blindness worldwide. Automatic methods for diagnosis exist, but their performance is limited by the quality of the data. Spectral retinal images provide a significantly better representation of the colour information than common grayscale or red-green-blue retinal imaging, having the potential to improve the performance of automatic diagnosis methods. This work studies the image processing techniques required for composing spectral retinal images with accurate reflection spectra, including wavelength channel image registration, spectral and spatial calibration, illumination correction, and the estimation of depth information from image disparities. The composition of a spectral retinal image database of patients with diabetic retinopathy is described. The database includes gold standards for a number of pathologies and retinal structures, marked by two expert ophthalmologists. The diagnostic applications of the reflectance spectra are studied using supervised classifiers for lesion detection. In addition, inversion of a model of light transport is used to estimate histological parameters from the reflectance spectra. Experimental results suggest that the methods for composing, calibrating and postprocessing spectral images presented in this work can be used to improve the quality of the spectral data. The experiments on the direct and indirect use of the data show the diagnostic potential of spectral retinal data over standard retinal images. The use of spectral data could improve automatic and semi-automated diagnostics for the screening of retinal diseases, for the quantitative detection of retinal changes for follow-up, clinically relevant end-points for clinical studies and development of new therapeutic modalities.

The nature of avidyÄ in Buddhism and VedÄ nta

This thesis deals with the nature of ignorance as it was interpreted in the Upani~adic tradition, specifically in Advaita Vedanta, and in early and Mahayana Buddhism , e specially in the Madhyamika school of Buddhism. The approach i s a historical and comparative one. It examines the early thoughts of both the upanis.a ds and Buddhism abou t avidya (ignorance), shows how the notion was treated by the more speculative and philosphically oriented schools which base d themselves on the e arly works, and sees how their views differ. The thesis will show that the Vedinta tended to treat avidya as a topic for metaphysical s peculation as t he s chool developed, drifting from its initial e xistential concerns, while the Madhyamika remained in contact with the e xistential concerns evident in the first discourses of the Buddha. The word "notion" has been chosen for use in referring t o avidya, even though it may have non-intellectual and emotional connotations, to avoid more popular a lternatives such as "concept" or "idea". In neither the Upani,ads, Advaita Vedanta, or Buddhism is ignorance merely a concept or an idea. Only in a secondary sense, in texts and speech , does it become one. Avidya has more to do with the lived situation in which man finds himself, with the subjectobject separation in which he f eels he exists, than with i i i intel lect ual constr ucts . Western thought has begun to r ealize the same with concerns such as being in modern ontology, and has chosen to speak about i t i n terms of the question of being . Avidya, however, i s not a 'question' . If q ue stions we r e to be put regarding the nature of a vidya , they would be more of t he sort "What is not avidya?", though e ven here l anguage bestows a status t o i t which avidya does not have. In considering a work of the Eastern tradition, we f ace t he danger of imposing Western concepts on it. Granted t hat avidya is customari ly r endered i n English as ignorance, the ways i n which the East and West view i gno rance di f f er. Pedagogically , the European cultures, grounded in the ancient Greek culture, view ignorance as a l ack or an emptiness. A child is i gnorant o f certain t hings and the purpose o f f ormal education , in f act if not in theory, is to fill him with enough knowledge so that he can cope wit h t he complexities and the e xpectations of s ociety. On another level, we feel t hat study and research will l ead t o the discovery o f solutions, which we now lack , for problems now defying solut i on . The East, on the o t her hand, sees avidya in a d i fferent light.Ignorance isn't a lack, but a presence. Religious and philosophical l iterature directs its efforts not towards acquiring something new, but at removing t.he ideas and opinions that individuals have formed about themselves and the world. When that is fully accomplished, say the sages , t hen Wisdom, which has been obscured by those opinions, will present itself. Nothing new has to be learned, t hough we do have t o 'learn' that much. The growing interest in t he West with Eastern religions and philosophies may, in time, influence our theoretical and practical approaches to education and learning, not only in the established educati onal institutions, but in religious , p sychological, and spiritual activities as well. However, the requirements o f this thesis do no t permit a formulation of revolutionary method or a call to action. It focuses instead on the textual arguments which attempt to convince readers that t he world in which they take themselves to exist is not, in essence, real, on the ways i n which the l imitations of language are disclosed, and on the provisional and limited schemes that are built up to help students see through their ignorance. The metaphysic s are provisional because they act only as spurs and guides. Both the Upanisadic and Buddhist traditions that will be dealt with here stress that language constantly fails to encompass the Real. So even terms s uch as 'the Real', 'Absolute', etc., serve only to lead to a transcendent experience . The sections dealing with the Upanisads and Advaita Vedanta show some of the historical evolution of the notion of avidya, how it was dealt with as maya , and the q uestions that arose as t o its locus. With Gau?apada we see the beginnings of a more abstract treatment of the topic, and , the influence of Buddhism. Though Sankhara' S interest was primarily directed towards constructing a philosophy to help others attain mok~a ( l iberation), he too introduced t echnica l t e rminology not found in the works of his predecessors. His work is impressive , but areas of it are incomplete. Numbers of his followers tried to complete the systematic presentation of his insi ghts . Their work focuses on expl anat i ons of adhyasa (superimposition ) , t he locus and object of ignorance , and the means by which Brahman takes itself to be the jiva and the world. The section on early Buddhism examines avidya in the context o f the four truths, together with dubkha (suffering), the r ole it p l ays in t he chain of dependent c ausation , a nd t he p r oblems that arise with t he doctrine of anatman. With t he doct rines of e arly Buddhism as a base, the Madhyamika elaborated questions that the Buddha had said t e nded not t o edi f ication. One of these had to do with own - being or svabhava. Thi s serves a s a centr e around which a discussion o f i gnorance unfolds, both i ndividual and coll ective ignorance. There follows a treatment of the cessation of ignorance as it is discussed within this school . The final secti on tries to present t he similarities and differences i n the natures o f ignorance i n t he two traditions and discusses the factors responsible for t hem . ACKNOWLEDGEMENTS I would like to thank Dr. Sinha for the time spent II and suggestions made on the section dealing with Sankara and the Advait.a Vedanta oommentators, and Dr. Sprung, who supervised, direoted, corrected and encouraged the thesis as a whole, but especially the section on Madhyamika, and the final comparison.

The effects of a general excercise program on task self-efficacy and social physique anxiety in older adults

Older adults represent the most sedentary segment of the adult population, and thus it is critical to investigate factors that influence exercise behaviour for this age group. The purpose of this study was to examine the influence of a general exercise program, incorporating cardiovascular, strength, flexibility, and balance components, on task selfefficacy and SPA in older adult men and women. Participants (n=114, Mage = 67 years) were recruited from the Niagara region and randomly assigned to a 12-week supervised exercise program or a wait-list control. Task self-efficacy and SPA measures were taken at baseline and program end. The present study found that task self-efficacy was a significant predictor of leisure time physical activity for older adults. In addition, change in task self-efficacy was a significant predictor of change in SPA. The findings of this study suggest that sources of task self-efficacy should be considered for exercise interventions targeting older adults.

Warren Hartman fonds, 1970, 1972-1996, 1998, n.d.

Warren Hartman was born in 1942 in Toronto, Ontario. He received a B.A. in Fine Arts and Drama from Brock University in 1981 and a Masters of Arts in Humanities at the State University of New York at Buffalo in 1987. In the 1950s he did considerable work as a child-actor both in theatre and television. From 1953 to 1961 he was in the New Play Society under the direction of Dora Mavor Moore. His last two years there were spent as a scholarship student. From 1963 to 1966 he did an apprenticeship with Suzanne Mess, Head of Costume Design at The Canadian Opera Company in Toronto. In 1976 Warren attended a Master Class in Scenography at the Banff School of Fine Arts with Josef Svoboda. In the spring of 1970 Warren was a guest designer at Brock University and from 1970 to 1972 he remained at Brock as resident designer and special lecturer. During this time he was also an instructor and costume designer at Sheridan College in Oakville. It was in 1972 that he became the designer-in-residence at Brock University. From 1984 he held the position of Associate Professor at The Department of Fine Arts at Brock University until the fall of 1996. Some of the highlights of Warren’s career also include: stage managager with the Street Hat Players in Port Carling, Ontario, 1960-1961; a freelance designer for over 100 shows; costume coordinator(production manager) for the Canadian Opera Company, 1964 -1970; resident costume designer for The Canadian Opera Company, 1965- 1970; founder and artistic director of Dei Gelosi Campagnia, St.Catharines, Ontario, 1970-1973; freelance director of some thirty-five shows; co-producer for Quebec City Summer Stock Company, Quebec City, Quebec, 1975; a consultant with Alberta Culture for the Provincial Government of Alberta, 1986-1987 and associate artistic director at Theatre Network, Edmonton, Alberta, 1986-1987. Warren Hartman was the recipient of the Jean Chalmers Award for contributions to Canadian Theatre for persons 25 years of age or under, in 1965. He was a founding member of Associated Designers of Canada and was affiliated with Canadian Actors Equity. Warren Hartman died on Feb. 11, 1998 several days after suffering a massive stroke. A memorial service was held at Brock University in May of 1998 and a bursary fund was established in his name.

Feature Selection and Classification Using Age Layered Population Structure Genetic Programming

The curse of dimensionality is a major problem in the fields of machine learning, data mining and knowledge discovery. Exhaustive search for the most optimal subset of relevant features from a high dimensional dataset is NP hard. Sub–optimal population based stochastic algorithms such as GP and GA are good choices for searching through large search spaces, and are usually more feasible than exhaustive and deterministic search algorithms. On the other hand, population based stochastic algorithms often suffer from premature convergence on mediocre sub–optimal solutions. The Age Layered Population Structure (ALPS) is a novel metaheuristic for overcoming the problem of premature convergence in evolutionary algorithms, and for improving search in the fitness landscape. The ALPS paradigm uses an age–measure to control breeding and competition between individuals in the population. This thesis uses a modification of the ALPS GP strategy called Feature Selection ALPS (FSALPS) for feature subset selection and classification of varied supervised learning tasks. FSALPS uses a novel frequency count system to rank features in the GP population based on evolved feature frequencies. The ranked features are translated into probabilities, which are used to control evolutionary processes such as terminal–symbol selection for the construction of GP trees/sub-trees. The FSALPS metaheuristic continuously refines the feature subset selection process whiles simultaneously evolving efficient classifiers through a non–converging evolutionary process that favors selection of features with high discrimination of class labels. We investigated and compared the performance of canonical GP, ALPS and FSALPS on high–dimensional benchmark classification datasets, including a hyperspectral image. Using Tukey’s HSD ANOVA test at a 95% confidence interval, ALPS and FSALPS dominated canonical GP in evolving smaller but efficient trees with less bloat expressions. FSALPS significantly outperformed canonical GP and ALPS and some reported feature selection strategies in related literature on dimensionality reduction.

Feature Selection and Classification Using Age Layered Population Structure Genetic Programming

The curse of dimensionality is a major problem in the fields of machine learning, data mining and knowledge discovery. Exhaustive search for the most optimal subset of relevant features from a high dimensional dataset is NP hard. Sub–optimal population based stochastic algorithms such as GP and GA are good choices for searching through large search spaces, and are usually more feasible than exhaustive and determinis- tic search algorithms. On the other hand, population based stochastic algorithms often suffer from premature convergence on mediocre sub–optimal solutions. The Age Layered Population Structure (ALPS) is a novel meta–heuristic for overcoming the problem of premature convergence in evolutionary algorithms, and for improving search in the fitness landscape. The ALPS paradigm uses an age–measure to control breeding and competition between individuals in the population. This thesis uses a modification of the ALPS GP strategy called Feature Selection ALPS (FSALPS) for feature subset selection and classification of varied supervised learning tasks. FSALPS uses a novel frequency count system to rank features in the GP population based on evolved feature frequencies. The ranked features are translated into probabilities, which are used to control evolutionary processes such as terminal–symbol selection for the construction of GP trees/sub-trees. The FSALPS meta–heuristic continuously refines the feature subset selection process whiles simultaneously evolving efficient classifiers through a non–converging evolutionary process that favors selection of features with high discrimination of class labels. We investigated and compared the performance of canonical GP, ALPS and FSALPS on high–dimensional benchmark classification datasets, including a hyperspectral image. Using Tukey’s HSD ANOVA test at a 95% confidence interval, ALPS and FSALPS dominated canonical GP in evolving smaller but efficient trees with less bloat expressions. FSALPS significantly outperformed canonical GP and ALPS and some reported feature selection strategies in related literature on dimensionality reduction.