Art painting Data Collection

The classification of Art painting images is a computer vision applications that isgrowing considerably. The goal of this technology, is to classify an art paintingimage automatically, in terms of artistic style, technique used, or its author. For thispurpose, the image is analyzed extracting some visual features. Many articlesrelated with these problems have been issued, but in general the proposed solutionsare focused in a very specific field. In particular, algorithms are tested using imagesat different resolutions, acquired under different illumination conditions. Thatmakes complicate the performance comparison of the different methods. In thiscontext, it will be very interesting to construct a public art image database, in orderto compare all the existing algorithms under the same conditions. This paperpresents a large art image database, with their corresponding labels according to thefollowing characteristics: title, author, style and technique. Furthermore, a tool thatmanages this database have been developed, and it can be used to extract differentvisual features for any selected image. This data can be exported to a file in CSVformat, allowing researchers to analyze the data with other tools. During the datacollection, the tool stores the elapsed time in the calculation. Thus, this tool alsoallows to compare the efficiency, in computation time, of different mathematicalprocedures for extracting image data.

Analysis of warm season thunderstorms using an object-oriented tracking method based on radar and total lightning data

Monitoring thunderstorms activity is an essential part of operational weather surveillance given their potential hazards, including lightning, hail, heavy rainfall, strong winds or even tornadoes. This study has two main objectives: firstly, the description of a methodology, based on radar and total lightning data to characterise thunderstorms in real-time; secondly, the application of this methodology to 66 thunderstorms that affected Catalonia (NE Spain) in the summer of 2006. An object-oriented tracking procedure is employed, where different observation data types generate four different types of objects (radar 1-km CAPPI reflectivity composites, radar reflectivity volumetric data, cloud-to-ground lightning data and intra-cloud lightning data). In the framework proposed, these objects are the building blocks of a higher level object, the thunderstorm. The methodology is demonstrated with a dataset of thunderstorms whose main characteristics, along the complete life cycle of the convective structures (development, maturity and dissipation), are described statistically. The development and dissipation stages present similar durations in most cases examined. On the contrary, the duration of the maturity phase is much more variable and related to the thunderstorm intensity, defined here in terms of lightning flash rate. Most of the activity of IC and CG flashes is registered in the maturity stage. In the development stage little CG flashes are observed (2% to 5%), while for the dissipation phase is possible to observe a few more CG flashes (10% to 15%). Additionally, a selection of thunderstorms is used to examine general life cycle patterns, obtained from the analysis of normalized (with respect to thunderstorm total duration and maximum value of variables considered) thunderstorm parameters. Among other findings, the study indicates that the normalized duration of the three stages of thunderstorm life cycle is similar in most thunderstorms, with the longest duration corresponding to the maturity stage (approximately 80% of the total time).

DEA does not like positive discrimination : a comparison of alternative models based on empirical data

Due to the existence of free software and pedagogical guides, the use of data envelopment analysis (DEA) has been further democratized in recent years. Nowadays, it is quite usual for practitioners and decision makers with no or little knowledge in operational research to run themselves their own efficiency analysis. Within DEA, several alternative models allow for an environment adjustment. Five alternative models, each of them easily accessible to and achievable by practitioners and decision makers, are performed using the empirical case of the 90 primary schools of the State of Geneva, Switzerland. As the State of Geneva practices an upstream positive discrimination policy towards schools, this empirical case is particularly appropriate for an environment adjustment. The alternative of the majority of DEA models deliver divergent results. It is a matter of concern for applied researchers and a matter of confusion for practitioners and decision makers. From a political standpoint, these diverging results could lead to potentially opposite decisions. Grâce à l'existence de logiciels en libre accès et de guides pédagogiques, la méthode data envelopment analysis (DEA) s'est démocratisée ces dernières années. Aujourd'hui, il n'est pas rare que les décideurs avec peu ou pas de connaissances en recherche opérationnelle réalisent eux-mêmes leur propre analyse d'efficience. A l'intérieur de la méthode DEA, plusieurs modèles permettent de tenir compte des conditions plus ou moins favorables de l'environnement. Cinq de ces modèles, facilement accessibles et applicables par les décideurs, sont utilisés pour mesurer l'efficience des 90 écoles primaires du canton de Genève, Suisse. Le canton de Genève pratiquant une politique de discrimination positive envers les écoles défavorisées, ce cas pratique est particulièrement adapté pour un ajustement à l'environnement. La majorité des modèles DEA génèrent des résultats divergents. Ce constat est préoccupant pour les chercheurs appliqués et perturbant pour les décideurs. D'un point de vue politique, ces résultats divergents conduisent à des prises de décision différentes selon le modèle sur lequel elles sont fondées.

Integrated methodologies to study human transcriptional regulation from functional genomics data

Abstract : The human body is composed of a huge number of cells acting together in a concerted manner. The current understanding is that proteins perform most of the necessary activities in keeping a cell alive. The DNA, on the other hand, stores the information on how to produce the different proteins in the genome. Regulating gene transcription is the first important step that can thus affect the life of a cell, modify its functions and its responses to the environment. Regulation is a complex operation that involves specialized proteins, the transcription factors. Transcription factors (TFs) can bind to DNA and activate the processes leading to the expression of genes into new proteins. Errors in this process may lead to diseases. In particular, some transcription factors have been associated with a lethal pathological state, commonly known as cancer, associated with uncontrolled cellular proliferation, invasiveness of healthy tissues and abnormal responses to stimuli. Understanding cancer-related regulatory programs is a difficult task, often involving several TFs interacting together and influencing each other's activity. This Thesis presents new computational methodologies to study gene regulation. In addition we present applications of our methods to the understanding of cancer-related regulatory programs. The understanding of transcriptional regulation is a major challenge. We address this difficult question combining computational approaches with large collections of heterogeneous experimental data. In detail, we design signal processing tools to recover transcription factors binding sites on the DNA from genome-wide surveys like chromatin immunoprecipitation assays on tiling arrays (ChIP-chip). We then use the localization about the binding of TFs to explain expression levels of regulated genes. In this way we identify a regulatory synergy between two TFs, the oncogene C-MYC and SP1. C-MYC and SP1 bind preferentially at promoters and when SP1 binds next to C-NIYC on the DNA, the nearby gene is strongly expressed. The association between the two TFs at promoters is reflected by the binding sites conservation across mammals, by the permissive underlying chromatin states 'it represents an important control mechanism involved in cellular proliferation, thereby involved in cancer. Secondly, we identify the characteristics of TF estrogen receptor alpha (hERa) target genes and we study the influence of hERa in regulating transcription. hERa, upon hormone estrogen signaling, binds to DNA to regulate transcription of its targets in concert with its co-factors. To overcome the scarce experimental data about the binding sites of other TFs that may interact with hERa, we conduct in silico analysis of the sequences underlying the ChIP sites using the collection of position weight matrices (PWMs) of hERa partners, TFs FOXA1 and SP1. We combine ChIP-chip and ChIP-paired-end-diTags (ChIP-pet) data about hERa binding on DNA with the sequence information to explain gene expression levels in a large collection of cancer tissue samples and also on studies about the response of cells to estrogen. We confirm that hERa binding sites are distributed anywhere on the genome. However, we distinguish between binding sites near promoters and binding sites along the transcripts. The first group shows weak binding of hERa and high occurrence of SP1 motifs, in particular near estrogen responsive genes. The second group shows strong binding of hERa and significant correlation between the number of binding sites along a gene and the strength of gene induction in presence of estrogen. Some binding sites of the second group also show presence of FOXA1, but the role of this TF still needs to be investigated. Different mechanisms have been proposed to explain hERa-mediated induction of gene expression. Our work supports the model of hERa activating gene expression from distal binding sites by interacting with promoter bound TFs, like SP1. hERa has been associated with survival rates of breast cancer patients, though explanatory models are still incomplete: this result is important to better understand how hERa can control gene expression. Thirdly, we address the difficult question of regulatory network inference. We tackle this problem analyzing time-series of biological measurements such as quantification of mRNA levels or protein concentrations. Our approach uses the well-established penalized linear regression models where we impose sparseness on the connectivity of the regulatory network. We extend this method enforcing the coherence of the regulatory dependencies: a TF must coherently behave as an activator, or a repressor on all its targets. This requirement is implemented as constraints on the signs of the regressed coefficients in the penalized linear regression model. Our approach is better at reconstructing meaningful biological networks than previous methods based on penalized regression. The method is tested on the DREAM2 challenge of reconstructing a five-genes/TFs regulatory network obtaining the best performance in the "undirected signed excitatory" category. Thus, these bioinformatics methods, which are reliable, interpretable and fast enough to cover large biological dataset, have enabled us to better understand gene regulation in humans.

Data-driven topo-climatic mapping with machine learning methods

Automatic environmental monitoring networks enforced by wireless communication technologies provide large and ever increasing volumes of data nowadays. The use of this information in natural hazard research is an important issue. Particularly useful for risk assessment and decision making are the spatial maps of hazard-related parameters produced from point observations and available auxiliary information. The purpose of this article is to present and explore the appropriate tools to process large amounts of available data and produce predictions at fine spatial scales. These are the algorithms of machine learning, which are aimed at non-parametric robust modelling of non-linear dependencies from empirical data. The computational efficiency of the data-driven methods allows producing the prediction maps in real time which makes them superior to physical models for the operational use in risk assessment and mitigation. Particularly, this situation encounters in spatial prediction of climatic variables (topo-climatic mapping). In complex topographies of the mountainous regions, the meteorological processes are highly influenced by the relief. The article shows how these relations, possibly regionalized and non-linear, can be modelled from data using the information from digital elevation models. The particular illustration of the developed methodology concerns the mapping of temperatures (including the situations of Föhn and temperature inversion) given the measurements taken from the Swiss meteorological monitoring network. The range of the methods used in the study includes data-driven feature selection, support vector algorithms and artificial neural networks.

Health consultation : Buchanan Bulk Oil -- Ma & Pa Stores West 6th Avenue and South F Street, Oskaloosa, Mahaska County, Iowa (2006)

The Iowa Department of Natural Resources (IDNR) has requested the Iowa Department of Public Health (IDPH) Hazardous Waste Site Health Assessment Program to evaluate the potential health impacts of the future development at the Buchanan Bulk Oil – Ma & Pa Stores site. A Targeted Brownfields Assessment was completed by the IDNR at this site to measure existing on-site contaminants. Assistance was sought from the IDPH to determine potential health risks if the site was developed for residential use. This health consultation addresses potential health risks to people from exposure to the contaminants found in the soil and groundwater within the property boundary. The information in this health consultation was current at the time of writing. Data that emerges later could alter this document’s conclusions and recommendations.

Introducing massively parallel computers into operational weather forecasting

Numerical weather prediction and climate simulation have been among the computationally most demanding applications of high performance computing eversince they were started in the 1950's. Since the 1980's, the most powerful computers have featured an ever larger number of processors. By the early 2000's, this number is often several thousand. An operational weather model must use all these processors in a highly coordinated fashion. The critical resource in running such models is not computation, but the amount of necessary communication between the processors. The communication capacity of parallel computers often fallsfar short of their computational power. The articles in this thesis cover fourteen years of research into how to harness thousands of processors on a single weather forecast or climate simulation, so that the application can benefit as much as possible from the power of parallel high performance computers. The resultsattained in these articles have already been widely applied, so that currently most of the organizations that carry out global weather forecasting or climate simulation anywhere in the world use methods introduced in them. Some further studies extend parallelization opportunities into other parts of the weather forecasting environment, in particular to data assimilation of satellite observations.

DATA WAREHOUSING IN A GLOBAL METAL INDUSTRIAL COMPANY

Työn tavoittena oli selvittää, miten tietovarastointi voi tukea yrityksessä tapahtuvaa päätöksentekoa. Tietovarastokomponenttien ja –prosessien kuvauksen jälkeen on käsitelty tietovarastoprojektin eri vaiheita. Esitettyä teoriaa sovellettiin käytäntöön globaalissa metalliteollisuusyrityksessä, jossa tietovarastointikonseptia testattiin. Testauksen perusteella arvioitiin olemassa olevan tiedon tilaa sekä kahden käytetyn ohjelmiston toimivuutta tietovarastoinnissa. Yrityksen operatiivisten järjestelmien tiedon laadun todettiin olevan tutkituilta osin epäyhtenäistä ja puutteellista. Siksi tiedon suora yrityslaajuinen hyödyntäminen luotettavien ja hyvälaatuisten raporttien luonnissa on vaikeaa. Lisäksi eri yksiköiden välillä havaittiin epäyhtenäisyyttä käytettyjen liiketoiminnan käsitteiden sekä järjestelmien käyttötapojen suhteen. Testauksessa käytetyt ohjelmistot suoriutuivat perustietovarastoinnista hyvin, vaikkakin joitain rajoituksia ja erikoisuuksia ilmenikin. Työtä voidaan pitää ennen varsinaista tietovarastoprojektia tehtävänä esitutkimuksena. Jatkotoimenpiteinä ehdotetaan testauksen jatkamista nykyisillä työkaluilla kohdistaen tavoitteet konkreettisiin tuloksiin. Tiedon laadun tärkeyttä tulee korostaa koko organisaatiossa ja olemassa olevan tiedon laatua pitää parantaa tulevaisuudessa.

Adjusting for the environment in DEA: a comparison of alternative models based on empirical data

Due to the existence of free software and pedagogical guides, the use of Data Envelopment Analysis (DEA) has been further democratized in recent years. Nowadays, it is quite usual for practitioners and decision makers with no or little knowledge in operational research to run their own efficiency analysis. Within DEA, several alternative models allow for an environmental adjustment. Four alternative models, each user-friendly and easily accessible to practitioners and decision makers, are performed using empirical data of 90 primary schools in the State of Geneva, Switzerland. Results show that the majority of alternative models deliver divergent results. From a political and a managerial standpoint, these diverging results could lead to potentially ineffective decisions. As no consensus emerges on the best model to use, practitioners and decision makers may be tempted to select the model that is right for them, in other words, the model that best reflects their own preferences. Further studies should investigate how an appropriate multi-criteria decision analysis method could help decision makers to select the right model.

The Effect of Operational Disturbances on Reliability and Operation Time Distribution of NCmachine Tools in FMS

This thesis concentrates on studying the operational disturbance behavior of machine tools integrated into FMS. Operational disturbances are short term failures of machine tools which are especially disruptive to unattended or unmanned operation of FMS. The main objective was to examine the effect of operational disturbances on reliability and operation time distribution for machine tools. The theoretical part of the thesis covers the fimdamentals of FMS relating to the subject of this study. The concept of FMS, its benefits and operator's role in FMS operation are reviewed. The importance of reliability is presented. The terms describing the operation time of machine tools are formed by adopting standards and references. The concept of failure and indicators describing reliability and operational performance for machine tools in FMSs are presented. The empirical part of the thesis describes the research methodology which is a combination of automated (ADC) and manual data collection. By using this methodology it is possible to have a complete view of the operation time distribution for studied machine tools. Data collection was carried out in four FMSs consisting of a total of 17 machine tools. Each FMS's basic features and the signals of ADC are described. The indicators describing the reliability and operation time distribution of machine tools were calculated according to collected data. The results showed that operational disturbances have a significant influence on machine tool reliability and operational performance. On average, an operational disturbance occurs every 8,6 hours of operation time and has a down time of 0,53 hours. Operational disturbances cause a 9,4% loss in operation time which is twice the amount of losses caused by technical failures (4,3%). Operational disturbances have a decreasing influence on the utilization rate. A poor operational disturbance behavior decreases the utilization rate. It was found that the features of a part family to be machined and the method technology related to it are defining the operational disturbance behavior of the machine tool. Main causes for operational disturbances were related to material quality variations, tool maintenance, NC program errors, ATC and machine tool control. Operator's role was emphasized. It was found that failure recording activity of the operators correlates with the utilization rate. The more precisely the operators record the failure, the higher is the utilization rate. Also the FMS organizations which record failures more precisely have fewer operational disturbances.

Economical and operational analysis of outsourced warehouse function

The target of the thesis was to find out has the decision to outsource part of Filtronic LK warehouse function been profitable. Furthermore, another thesis target was to demonstrate current logistics processes between TPLP and company and find out the targets for developing these processes. The decision to outsource part of logistical funtions have been profitable during the first business year. Partnership includes always business risks. Risk increases high asset specific investments. In the other hand investment to partnership increases mutual trust and commitment between parties. By developing partnership risks and opportunitic behaviour can be decreased. The potential of managing material and data flows between logistic service provider and company observed. By analyzing inventory effiency were highlighted the need for decreasing the capital invested to inventories. The recommendations for managing outsourced logistical funtions were established such as improving partnership, process development, performance measurement and invoice checking.

The effect of dynamic capabilities on operational-level innovation – Empirical study in magazine publishing industry

This master’s thesis aims to examine the relationship between dynamic capabilities and operational-level innovations. In addition, measures for the concept of dynamic capabilities are developed. The study was executed in the magazine publishing industry which is considered favourable for examining dynamic capabilities, since the sector is characterized by rapid change. As a basis for the study and the measure development, a literary review was conducted. Data for the empirical section was gathered by a survey targeted to chief-editors of Finnish consumer magazines. The relationship between dynamic capabilities and innovation was examined by multiple linear regression. The results indicate that dynamic capabilities have effect on the emergence of radical innovations. Environmental dynamism’s effect on radical innovations was not detected. Also, dynamic capabilities’ effect on innovation was not greater in turbulent operating environment.

Tiedonkeruujärjestelmän kehittäminen voimalaitoksen toiminnan tehostamisessa

Diplomityössä kehitetään tiedonkeruujärjestelmää voimalaitoksen toiminnan tehostamiseksi. Aihetta käsitellään tiedonkeruujärjestelmän käyttäjän ja ylläpitäjän näkökulmasta. Tiedonkeruujärjestelmällä kerätään prosessitietoa automaatiojärjestelmästä ja tallennetaan prosessitieto tietokantaan. Työssä on kuvattu sekä automaatio- että tiedonkeruujärjestelmää prosessitiedon keruun, tallentamisen ja hallinnan ymmärtämiseksi. Prosessitiedon merkitystä voimalaitoksen toiminnan kannalta on myös pohdittu. Diplomityö tehtiin Mertaniemen voimalaitoksella, jossa käytännön kehityskohteina olivat laskenta- ja raportointisovellukset. Lisäksi tarkistettiin tietokantamuuttujia. Tiedonkeruujärjestelmää kehitetään ja päivitetään voimalaitoksen laitteisto- ja toimintamuutosten takia. Kehityksellä pyritään tarjoamaan oikeampaa ja luotettavampaa tietoa, korjaamaan virheitä sekä kartoittamaan mahdollisia puutteita.

Implementing an open data system and showing its benefits

Open data refers to publishing data on the web in machine-readable formats for public access. Using open data, innovative applications can be developed to facilitate people‟s lives. In this thesis, based on the open data cases (discussed in the literature review), Open Data Lappeenranta is suggested, which publishes open data related to opening hours of shops and stores in Lappeenranta City. To prove the possibility of creating Open Data Lappeenranta, the implementation of an open data system is presented in this thesis, which publishes specific data related to shops and stores (including their opening hours) on the web in standard format (JSON). The published open data is used to develop web and mobile applications to demonstrate the benefits of open data in practice. Also, the open data system provides manual and automatic interfaces which make it possible for shops and stores to maintain their own data in the system. Finally in this thesis, the completed version of Open Data Lappeenranta is proposed, which publishes open data related to other fields and businesses in Lappeenranta beyond only stores‟ data.

Communicating trustworthiness in online stores

Even though e-commerce systems are expected to have many advantages compared to the traditional ways of doing business, it is not always the reality. Lack of trust is still said to be one of the most important barriers to online shopping. In traditional stores, trust has usually been established in a direct contact between the customer and the company or its personnel. In online stores, there is no direct interaction. The purpose of this thesis is to identify the key antecedents to online trust and to distinguish between effective and ineffective practices. A model on how consumers establish initial trust towards an unknown online vendor was proposed based on previous theories. The model was tested empirically by targeting an online survey at higher degree students in Finland and in Germany. The data confirmed the proposed view that trusting intentions are affected by individual characteristics, characteristics of the company as well as characteristics of the website. Additionally national differences were found between Finnish and German respondents. The data suggested that online vendors can convey a message of trustworthiness by improving information quality and overall usefulness of the website. Perceived risk of online shopping was found to depend especially on general trust in the Internet, service quality and ease of use. A trustworthy online store should include several payment methods as well as means to access and modify given data. The vendors should also make sure that inquiries are addressed quickly, transactions are confirmed automatically and that customers have a possibility to track their order. A model that includes three different sources of trust should contribute to the theoretical understanding of trust formation in online stores. The resulting list of trust antecedents can also be used as a checklist when e-commerce practitioners wish to optimize the trust building.