Automatic evaluation and data generation for analytical chemistry instrumental analysis exercises

In general, laboratory activities are costly in terms of time, space, and money. As such, the ability to provide realistically simulated laboratory data that enables students to practice data analysis techniques as a complementary activity would be expected to reduce these costs while opening up very interesting possibilities. In the present work, a novel methodology is presented for design of analytical chemistry instrumental analysis exercises that can be automatically personalized for each student and the results evaluated immediately. The proposed system provides each student with a different set of experimental data generated randomly while satisfying a set of constraints, rather than using data obtained from actual laboratory work. This allows the instructor to provide students with a set of practical problems to complement their regular laboratory work along with the corresponding feedback provided by the system's automatic evaluation process. To this end, the Goodle Grading Management System (GMS), an innovative web-based educational tool for automating the collection and assessment of practical exercises for engineering and scientific courses, was developed. The proposed methodology takes full advantage of the Goodle GMS fusion code architecture. The design of a particular exercise is provided ad hoc by the instructor and requires basic Matlab knowledge. The system has been employed with satisfactory results in several university courses. To demonstrate the automatic evaluation process, three exercises are presented in detail. The first exercise involves a linear regression analysis of data and the calculation of the quality parameters of an instrumental analysis method. The second and third exercises address two different comparison tests, a comparison test of the mean and a t-paired test.

CLASSIFICATION OF FOREST ROADS AND DETERMINATION OF ROUTE USING GEOGRAPHIC INFORMATION SYSTEM

ABSTRACT Geographic Information System (GIS) is an indispensable software tool in forest planning. In forestry transportation, GIS can manage the data on the road network and solve some problems in transportation, such as route planning. Therefore, the aim of this study was to determine the pattern of the road network and define transport routes using GIS technology. The present research was conducted in a forestry company in the state of Minas Gerais, Brazil. The criteria used to classify the pattern of forest roads were horizontal and vertical geometry, and pavement type. In order to determine transport routes, a data Analysis Model Network was created in ArcGIS using an Extension Network Analyst, allowing finding a route shorter in distance and faster. The results showed a predominance of horizontal geometry classes average (3) and bad (4), indicating presence of winding roads. In the case of vertical geometry criterion, the class of highly mountainous relief (4) possessed the greatest extent of roads. Regarding the type of pavement, the occurrence of secondary coating was higher (75%), followed by primary coating (20%) and asphalt pavement (5%). The best route was the one that allowed the transport vehicle travel in a higher specific speed as a function of road pattern found in the study.

Lean, Six Sigma ja Total Welding Management hitsaavassa verkostossa

Diplomityössä tarkastellaan hitsaavan verkoston laadunhallintaa ja siinä ilmeneviä erilaisia ongelmakohtia. Tämän lisäksi työssä tarkastellaan kolmen eri laatutyökalun Lean, Six Sigma ja Total Welding Management soveltamista hitsaavan verkoston laadunhallinnassa. Teoriaosassa käsitellään sekä yleisesti että hitsauksen osalta laatua ja laadunhallintaa, sekä edellä mainittuja laatutyökaluja. Tutkimusosaan tietoja hitsaavista verkostoista kerättiin kaikkiaan kolmesta eri verkostosta. Näiden kerättyjen tietojen pohjalta tarkasteltiin valittujen laatutyökalujen soveltuvuutta verkostomaiseen käyttöön. Verkostoitunut toiminta aiheuttaa monia uusia haasteita yritysten laadunhallinnalle verrattuna yksittäisiin hitsaaviin yrityksiin. Suurimpia tutkimuksessa havaittuja ongelmakohtia ovat suunnittelun ja valmistuksen yhteistyön erilaiset puutteet, laatutasoon ja sen varmistukseen liittyvät asiat, sekä verkoston sisälle syntyvä niin sanottu hiljainen tieto ja sen häviäminen. Tutkimuksen tarkastelujen perusteella havaittiin, että kaikkien tutkimukseen valitun kolmen laatutyökalun soveltaminen myös verkostomaisessa toiminnassa on mahdollista, mutta se vaatii huomattavasti suurempaa työpanosta kuin soveltaminen yksittäisessä yrityksessä. Myös näiden kaikkien kolmen työkalun yhtä aikainen käyttö on mahdollista. Juuri oikean työkalun valitseminen kullekin hitsaavalle verkostolle vaatii tarkkaa perehtymistä verkostoon ja sen tilanteeseen.

Model of Big Data Failure: Review of Information System Failure

In the new age of information technology, big data has grown to be the prominent phenomena. As information technology evolves, organizations have begun to adopt big data and apply it as a tool throughout their decision-making processes. Research on big data has grown in the past years however mainly from a technical stance and there is a void in business related cases. This thesis fills the gap in the research by addressing big data challenges and failure cases. The Technology-Organization-Environment framework was applied to carry out a literature review on trends in Business Intelligence and Knowledge management information system failures. A review of extant literature was carried out using a collection of leading information system journals. Academic papers and articles on big data, Business Intelligence, Decision Support Systems, and Knowledge Management systems were studied from both failure and success aspects in order to build a model for big data failure. I continue and delineate the contribution of the Information System failure literature as it is the principal dynamics behind technology-organization-environment framework. The gathered literature was then categorised and a failure model was developed from the identified critical failure points. The failure constructs were further categorized, defined, and tabulated into a contextual diagram. The developed model and table were designed to act as comprehensive starting point and as general guidance for academics, CIOs or other system stakeholders to facilitate decision-making in big data adoption process by measuring the effect of technological, organizational, and environmental variables with perceived benefits, dissatisfaction and discontinued use.

Model of Big Data Failure: Review of Information System Failure

In the new age of information technology, big data has grown to be the prominent phenomena. As information technology evolves, organizations have begun to adopt big data and apply it as a tool throughout their decision-making processes. Research on big data has grown in the past years however mainly from a technical stance and there is a void in business related cases. This thesis fills the gap in the research by addressing big data challenges and failure cases. The Technology-Organization-Environment framework was applied to carry out a literature review on trends in Business Intelligence and Knowledge management information system failures. A review of extant literature was carried out using a collection of leading information system journals. Academic papers and articles on big data, Business Intelligence, Decision Support Systems, and Knowledge Management systems were studied from both failure and success aspects in order to build a model for big data failure. I continue and delineate the contribution of the Information System failure literature as it is the principal dynamics behind technology-organization-environment framework. The gathered literature was then categorised and a failure model was developed from the identified critical failure points. The failure constructs were further categorized, defined, and tabulated into a contextual diagram. The developed model and table were designed to act as comprehensive starting point and as general guidance for academics, CIOs or other system stakeholders to facilitate decision-making in big data adoption process by measuring the effect of technological, organizational, and environmental variables with perceived benefits, dissatisfaction and discontinued use.

AnaBench: a Web/CORBA-based workbench for biomolecular sequence analysis

Affiliation: Département de biochimie, Faculté de médecine, Université de Montréal

La signification de la qualité de vie au travail pour des infirmiers œuvrant en CSSS, mission CLSC et déclarant avoir une qualité de vie positive au travail

Depuis le début des années 90, le réseau de la santé au Québec est soumis à une vaste restructuration qui a eu des conséquences négatives sur la qualité de vie au travail (QVT) des infirmières et infirmiers. Les hommes se retrouvent en nombre croissant dans toutes les sphères de la pratique infirmière, mais les études existantes ne font malheureusement pas mention de la qualité de vie au travail de ceux-ci. Alors, il apparaît pertinent de s’attarder au phénomène de la qualité de vie au travail des hommes infirmiers dans la profession infirmière, et ce, plus précisément en CSSS mission CLSC. Le but de cette étude phénoménologique consiste à décrire et à comprendre la signification de la qualité de vie au travail pour des infirmiers œuvrant en CSSS mission CLSC. L’essence du phénomène, les huit thèmes et les 35 sous-thèmes qui se dégagent directement des entrevues énoncent que la signification de la qualité de vie au travail pour des infirmiers œuvrant en centre de santé et des services sociaux (CSSS), mission CLSC et déclarant avoir une qualité de vie positive au travail, signifie « un climat empreint de caring qui favorise l'épanouissement de l'infirmier en CLSC en œuvrant pour le maintien de l'harmonie entre les sphères professionnelle et familiale ». Si certains résultats corroborent ceux d’études antérieures, d’autres apportent des éléments nouveaux favorisant la santé des infirmiers par le biais de la qualité de vie au travail. Enfin, des avenues concrètes visant la mise en place de programmes d’optimisation de la qualité de vie au travail, sont proposées.

Zoning of the commercial poultry industry in Ontario as a method of avian influenza mitigation

L’Organisation mondiale de la santé animale (OIE) est l’institution internationale responsable de la mise en place des mesures sanitaires associées aux échanges commerciaux d’animaux vivants. Le zonage est une méthode de contrôle recommandée par l’OIE pour certaines maladies infectieuses, dont l’influenza aviaire. Les éclosions d’influenza aviaire été extrêmement coûteuses pour l’industrie avicole partout dans le monde. Afin d’évaluer la possibilité d’user de cette approche en Ontario, les données sur les sites de production avicole ont été fournies par les fédérations d’éleveurs de volailles ce cette province. L’information portant sur les industries associées à la production avicole, soit les meuneries, les abattoirs, les couvoirs, et les usines de classification d’œufs, a été obtenue par l’entremise de plusieurs sources, dont des représentants de l’industrie avicole. Des diagrammes de flux a été crée afin de comprendre les interactions entre les sites de production et les industries associées à ceux-ci. Ces industries constituaient les éléments de bas nécessaires au zonage. Cette analyse a permis de créer une base de données portant sur intrants et extrants de production pour chaque site d’élevage avicole, ainsi que pour les sites de production des industries associées à l’aviculture. À l’aide du logiciel ArcGIS, cette information a été fusionnée à des données géospatiales de Statistique Canada de l’Ontario et du Québec. La base de données résultante a permis de réaliser les essais de zonage. Soixante-douze essais ont été réalisés. Quatre ont été retenus car celles minimisaient de façon similaire les pertes de production de l’industrie. Ces essais montrent que la méthode utilisée pour l’étude du zonage peut démontrer les déficits et les surplus de production de l’industrie avicole commerciale en Ontario. Ceux-ci pourront servir de point de départ lors des discussions des intervenants de l’industrie avicole, étant donné que la coopération et la communication sont essentielles au succès du zonage.

‘Reliability Concepts in Quantile-based Analysis of Lifetime Data

Reliability analysis is a well established branch of statistics that deals with the statistical study of different aspects of lifetimes of a system of components. As we pointed out earlier that major part of the theory and applications in connection with reliability analysis were discussed based on the measures in terms of distribution function. In the beginning chapters of the thesis, we have described some attractive features of quantile functions and the relevance of its use in reliability analysis. Motivated by the works of Parzen (1979), Freimer et al. (1988) and Gilchrist (2000), who indicated the scope of quantile functions in reliability analysis and as a follow up of the systematic study in this connection by Nair and Sankaran (2009), in the present work we tried to extend their ideas to develop necessary theoretical framework for lifetime data analysis. In Chapter 1, we have given the relevance and scope of the study and a brief outline of the work we have carried out. Chapter 2 of this thesis is devoted to the presentation of various concepts and their brief reviews, which were useful for the discussions in the subsequent chapters .In the introduction of Chapter 4, we have pointed out the role of ageing concepts in reliability analysis and in identifying life distributions .In Chapter 6, we have studied the first two L-moments of residual life and their relevance in various applications of reliability analysis. We have shown that the first L-moment of residual function is equivalent to the vitality function, which have been widely discussed in the literature .In Chapter 7, we have defined percentile residual life in reversed time (RPRL) and derived its relationship with reversed hazard rate (RHR). We have discussed the characterization problem of RPRL and demonstrated with an example that the RPRL for given does not determine the distribution uniquely

Drastic variation in the surface boundary layer parameters over Cochin during the annular solar eclipse: Analysis using sonic anemometer data

Atmospheric surface boundary layer parameters vary anomalously in response to the occurrence of annular solar eclipse on 15th January 2010 over Cochin. It was the longest annular solar eclipse occurred over South India with high intensity. As it occurred during the noon hours, it is considered to be much more significant because of its effects in all the regions of atmosphere including ionosphere. Since the insolation is the main driving factor responsible for the anomalous changes occurred in the surface layer due to annular solar eclipse, occurred on 15th January 2010, that played very important role in understanding dynamics of the atmosphere during the eclipse period because of its coincidence with the noon time. The Sonic anemometer is able to give data of zonal, meridional and vertical wind as well as the air temperature at a temporal resolution of 1 s. Different surface boundary layer parameters and turbulent fluxes were computed by the application of eddy correlation technique using the high resolution station data. The surface boundary layer parameters that are computed using the sonic anemometer data during the period are momentum flux, sensible heat flux, turbulent kinetic energy, frictional velocity (u*), variance of temperature, variances of u, v and w wind. In order to compare the results, a control run has been done using the data of previous day as well as next day. It is noted that over the specified time period of annular solar eclipse, all the above stated surface boundary layer parameters vary anomalously when compared with the control run. From the observations we could note that momentum flux was 0.1 Nm 2 instead of the mean value 0.2 Nm-2 when there was eclipse. Sensible heat flux anomalously decreases to 50 Nm 2 instead of the mean value 200 Nm 2 at the time of solar eclipse. The turbulent kinetic energy decreases to 0.2 m2s 2 from the mean value 1 m2s 2. The frictional velocity value decreases to 0.05 ms 1 instead of the mean value 0.2 ms 1. The present study aimed at understanding the dynamics of surface layer in response to the annular solar eclipse over a tropical coastal station, occurred during the noon hours. Key words: annular solar eclipse, surface boundary layer, sonic anemometer

RMAC-M: Extending the R-MAC Protocol for an Energy Efficient, Delay Tolerant Underwater Acoustic Sensor Network application with a mobile data mule node

One of the major applications of underwater acoustic sensor networks (UWASN) is ocean environment monitoring. Employing data mules is an energy efficient way of data collection from the underwater sensor nodes in such a network. A data mule node such as an autonomous underwater vehicle (AUV) periodically visits the stationary nodes to download data. By conserving the power required for data transmission over long distances to a remote data sink, this approach extends the network life time. In this paper we propose a new MAC protocol to support a single mobile data mule node to collect the data sensed by the sensor nodes in periodic runs through the network. In this approach, the nodes need to perform only short distance, single hop transmission to the data mule. The protocol design discussed in this paper is motivated to support such an application. The proposed protocol is a hybrid protocol, which employs a combination of schedule based access among the stationary nodes along with handshake based access to support mobile data mules. The new protocol, RMAC-M is developed as an extension to the energy efficient MAC protocol R-MAC by extending the slot time of R-MAC to include a contention part for a hand shake based data transfer. The mobile node makes use of a beacon to signal its presence to all the nearby nodes, which can then hand-shake with the mobile node for data transfer. Simulation results show that the new protocol provides efficient support for a mobile data mule node while preserving the advantages of R-MAC such as energy efficiency and fairness.

Network properties of folksonomies

Social resource sharing systems like YouTube and del.icio.us have acquired a large number of users within the last few years. They provide rich resources for data analysis, information retrieval, and knowledge discovery applications. A first step towards this end is to gain better insights into content and structure of these systems. In this paper, we will analyse the main network characteristics of two of the systems. We consider their underlying data structures – socalled folksonomies – as tri-partite hypergraphs, and adapt classical network measures like characteristic path length and clustering coefficient to them. Subsequently, we introduce a network of tag co-occurrence and investigate some of its statistical properties, focusing on correlations in node connectivity and pointing out features that reflect emergent semantics within the folksonomy. We show that simple statistical indicators unambiguously spot non-social behavior such as spam.

Network properties of folksonomies

Social resource sharing systems like YouTube and del.icio.us have acquired a large number of users within the last few years. They provide rich resources for data analysis, information retrieval, and knowledge discovery applications. A first step towards this end is to gain better insights into content and structure of these systems. In this paper, we will analyse the main network characteristics of two of these systems. We consider their underlying data structures – so-called folksonomies – as tri-partite hypergraphs, and adapt classical network measures like characteristic path length and clustering coefficient to them. Subsequently, we introduce a network of tag cooccurrence and investigate some of its statistical properties, focusing on correlations in node connectivity and pointing out features that reflect emergent semantics within the folksonomy. We show that simple statistical indicators unambiguously spot non-social behavior such as spam.

Compositional Data in Biomedical Research

Modern methods of compositional data analysis are not well known in biomedical research. Moreover, there appear to be few mathematical and statistical researchers working on compositional biomedical problems. Like the earth and environmental sciences, biomedicine has many problems in which the relevant scienti c information is encoded in the relative abundance of key species or categories. I introduce three problems in cancer research in which analysis of compositions plays an important role. The problems involve 1) the classi cation of serum proteomic pro les for early detection of lung cancer, 2) inference of the relative amounts of di erent tissue types in a diagnostic tumor biopsy, and 3) the subcellular localization of the BRCA1 protein, and it's role in breast cancer patient prognosis. For each of these problems I outline a partial solution. However, none of these problems is \solved". I attempt to identify areas in which additional statistical development is needed with the hope of encouraging more compositional data analysts to become involved in biomedical research

Statistical Analysis of Eco-Toxicologic Data of Mammals from a Polluted Area

Several eco-toxicological studies have shown that insectivorous mammals, due to their feeding habits, easily accumulate high amounts of pollutants in relation to other mammal species. To assess the bio-accumulation levels of toxic metals and their in°uence on essential metals, we quantified the concentration of 19 elements (Ca, K, Fe, B, P, S, Na, Al, Zn, Ba, Rb, Sr, Cu, Mn, Hg, Cd, Mo, Cr and Pb) in bones of 105 greater white-toothed shrews (Crocidura russula) from a polluted (Ebro Delta) and a control (Medas Islands) area. Since chemical contents of a bio-indicator are mainly compositional data, conventional statistical analyses currently used in eco-toxicology can give misleading results. Therefore, to improve the interpretation of the data obtained, we used statistical techniques for compositional data analysis to define groups of metals and to evaluate the relationships between them, from an inter-population viewpoint. Hypothesis testing on the adequate balance-coordinates allow us to confirm intuition based hypothesis and some previous results. The main statistical goal was to test equal means of balance-coordinates for the two defined populations. After checking normality, one-way ANOVA or Mann-Whitney tests were carried out for the inter-group balances