Municipal distribution of bladder cancer mortality in Spain: Possible role of mining and industry

BACKGROUND Spain shows the highest bladder cancer incidence rates in men among European countries. The most important risk factors are tobacco smoking and occupational exposure to a range of different chemical substances, such as aromatic amines. METHODS This paper describes the municipal distribution of bladder cancer mortality and attempts to "adjust" this spatial pattern for the prevalence of smokers, using the autoregressive spatial model proposed by Besag, York and Molliè, with relative risk of lung cancer mortality as a surrogate. RESULTS It has been possible to compile and ascertain the posterior distribution of relative risk for bladder cancer adjusted for lung cancer mortality, on the basis of a single Bayesian spatial model covering all of Spain's 8077 towns. Maps were plotted depicting smoothed relative risk (RR) estimates, and the distribution of the posterior probability of RR>1 by sex. Towns that registered the highest relative risks for both sexes were mostly located in the Provinces of Cadiz, Seville, Huelva, Barcelona and Almería. The highest-risk area in Barcelona Province corresponded to very specific municipal areas in the Bages district, e.g., Suría, Sallent, Balsareny, Manresa and Cardona. CONCLUSION Mining/industrial pollution and the risk entailed in certain occupational exposures could in part be dictating the pattern of municipal bladder cancer mortality in Spain. Population exposure to arsenic is a matter that calls for attention. It would be of great interest if the relationship between the chemical quality of drinking water and the frequency of bladder cancer could be studied.

The demand-supply balancing process in supply chain management - case mining & metals industry equipment

The aim of this thesis is to search how to match the demand and supply effectively in industrial and project-oriented business environment. The demand-supply balancing process is searched through three different phases: the demand planning and forecasting, synchronization of demand and supply and measurement of the results. The thesis contains a single case study that has been implemented in a company called Outotec. In the case study the demand is planned and forecasted with qualitative (judgmental) forecasting method. The quantitative forecasting methods are searched further to support the demand forecast and long term planning. The sales and operations planning process is used in the synchronization of the demand and supply. The demand forecast is applied in the management of a supply chain of critical unit of elemental analyzer. Different meters on operational and strategic level are proposed for the measurement of performance.

A Competitive assessment of the U.S. mining machinery industry /

"October 1986."

Kaivoskoneiden kustannusseurannan ja -raportoinnin kehittäminen

Työn tavoitteena oli kehittää kaivoskoneita valmistavalle yritykselle raportointimalli uusittujen tuotteiden kustannusten seuraamiseksi. Raporttien toivottiin olevan tarvelähtöisiä, sisällöltään luotettavia, vaivattomia päivittää sekä helposti saatavissa. Tutkimuksen toisena tavoitteena oli kartoittaa kohdeyrityksen tuotekohtaisenkustannusseurannan nykytilaa ja sen kehityskohteita. Tutkimuksen aineistoa kerättiin strukturoimattomilla haastatteluilla, yrityksen dokumentteihin tutustumalla, havainnoinnilla, keskusteluilla sekä benchmarking-menetelmällä. Luonteeltaan tutkimus oli konstruktiivinen eli sen tavoitteena oli luoda uusi ratkaisumalliongelmalliseksi koettuun tilanteeseen. Tutkimuksen tuloksena syntyi pitkälle automatisoitu kustannusraportointimalli, joka sisältää kaksi tuotekohtaista kustannusraporttityyppiä. Raportit ovat ns. on-line -raportteja eli käyttäjien on mahdollisuus lukea niitä yrityksen intranetin kautta haluamanaan aikana. Prototyyppiraportit laadittiin erään nykyisen tuoterakenteen mukaisen koneen tiedoilla.Raporttien avulla voidaan tehokkaasti seurata konekohtaisia kustannuksia ja tunnistaa ne tekijät joihin vaikuttamalla voidaan saavuttaa asetetut tavoitekustannukset. Mallissa määriteltiin myös raporttien käyttäjät, jakelu, vastuut ja päivitykset. Todellinen hyöty raportointimallista saadaan siinä vaiheessa, kun sen avulla voidaan seurata uuden tuoterakenteen kustannuksia. Tutkimuksen perusteella annettiin lisäksi suosituksia kohdeyrityksen kustannusseurannan kehittämiseksi tulevaisuudessa.

Community Policing in Switzerland's Major Urban Areas: An Observational Study of the Implementation and Impact Using Geospatial Data Mining

La présente étude est à la fois une évaluation du processus de la mise en oeuvre et des impacts de la police de proximité dans les cinq plus grandes zones urbaines de Suisse - Bâle, Berne, Genève, Lausanne et Zurich. La police de proximité (community policing) est à la fois une philosophie et une stratégie organisationnelle qui favorise un partenariat renouvelé entre la police et les communautés locales dans le but de résoudre les problèmes relatifs à la sécurité et à l'ordre public. L'évaluation de processus a analysé des données relatives aux réformes internes de la police qui ont été obtenues par l'intermédiaire d'entretiens semi-structurés avec des administrateurs clés des cinq départements de police, ainsi que dans des documents écrits de la police et d'autres sources publiques. L'évaluation des impacts, quant à elle, s'est basée sur des variables contextuelles telles que des statistiques policières et des données de recensement, ainsi que sur des indicateurs d'impacts construit à partir des données du Swiss Crime Survey (SCS) relatives au sentiment d'insécurité, à la perception du désordre public et à la satisfaction de la population à l'égard de la police. Le SCS est un sondage régulier qui a permis d'interroger des habitants des cinq grandes zones urbaines à plusieurs reprises depuis le milieu des années 1980. L'évaluation de processus a abouti à un « Calendrier des activités » visant à créer des données de panel permettant de mesurer les progrès réalisés dans la mise en oeuvre de la police de proximité à l'aide d'une grille d'évaluation à six dimensions à des intervalles de cinq ans entre 1990 et 2010. L'évaluation des impacts, effectuée ex post facto, a utilisé un concept de recherche non-expérimental (observational design) dans le but d'analyser les impacts de différents modèles de police de proximité dans des zones comparables à travers les cinq villes étudiées. Les quartiers urbains, délimités par zone de code postal, ont ainsi été regroupés par l'intermédiaire d'une typologie réalisée à l'aide d'algorithmes d'apprentissage automatique (machine learning). Des algorithmes supervisés et non supervisés ont été utilisés sur les données à haute dimensionnalité relatives à la criminalité, à la structure socio-économique et démographique et au cadre bâti dans le but de regrouper les quartiers urbains les plus similaires dans des clusters. D'abord, les cartes auto-organisatrices (self-organizing maps) ont été utilisées dans le but de réduire la variance intra-cluster des variables contextuelles et de maximiser simultanément la variance inter-cluster des réponses au sondage. Ensuite, l'algorithme des forêts d'arbres décisionnels (random forests) a permis à la fois d'évaluer la pertinence de la typologie de quartier élaborée et de sélectionner les variables contextuelles clés afin de construire un modèle parcimonieux faisant un minimum d'erreurs de classification. Enfin, pour l'analyse des impacts, la méthode des appariements des coefficients de propension (propensity score matching) a été utilisée pour équilibrer les échantillons prétest-posttest en termes d'âge, de sexe et de niveau d'éducation des répondants au sein de chaque type de quartier ainsi identifié dans chacune des villes, avant d'effectuer un test statistique de la différence observée dans les indicateurs d'impacts. De plus, tous les résultats statistiquement significatifs ont été soumis à une analyse de sensibilité (sensitivity analysis) afin d'évaluer leur robustesse face à un biais potentiel dû à des covariables non observées. L'étude relève qu'au cours des quinze dernières années, les cinq services de police ont entamé des réformes majeures de leur organisation ainsi que de leurs stratégies opérationnelles et qu'ils ont noué des partenariats stratégiques afin de mettre en oeuvre la police de proximité. La typologie de quartier développée a abouti à une réduction de la variance intra-cluster des variables contextuelles et permet d'expliquer une partie significative de la variance inter-cluster des indicateurs d'impacts avant la mise en oeuvre du traitement. Ceci semble suggérer que les méthodes de géocomputation aident à équilibrer les covariables observées et donc à réduire les menaces relatives à la validité interne d'un concept de recherche non-expérimental. Enfin, l'analyse des impacts a révélé que le sentiment d'insécurité a diminué de manière significative pendant la période 2000-2005 dans les quartiers se trouvant à l'intérieur et autour des centres-villes de Berne et de Zurich. Ces améliorations sont assez robustes face à des biais dus à des covariables inobservées et covarient dans le temps et l'espace avec la mise en oeuvre de la police de proximité. L'hypothèse alternative envisageant que les diminutions observées dans le sentiment d'insécurité soient, partiellement, un résultat des interventions policières de proximité semble donc être aussi plausible que l'hypothèse nulle considérant l'absence absolue d'effet. Ceci, même si le concept de recherche non-expérimental mis en oeuvre ne peut pas complètement exclure la sélection et la régression à la moyenne comme explications alternatives. The current research project is both a process and impact evaluation of community policing in Switzerland's five major urban areas - Basel, Bern, Geneva, Lausanne, and Zurich. Community policing is both a philosophy and an organizational strategy that promotes a renewed partnership between the police and the community to solve problems of crime and disorder. The process evaluation data on police internal reforms were obtained through semi-structured interviews with key administrators from the five police departments as well as from police internal documents and additional public sources. The impact evaluation uses official crime records and census statistics as contextual variables as well as Swiss Crime Survey (SCS) data on fear of crime, perceptions of disorder, and public attitudes towards the police as outcome measures. The SCS is a standing survey instrument that has polled residents of the five urban areas repeatedly since the mid-1980s. The process evaluation produced a "Calendar of Action" to create panel data to measure community policing implementation progress over six evaluative dimensions in intervals of five years between 1990 and 2010. The impact evaluation, carried out ex post facto, uses an observational design that analyzes the impact of the different community policing models between matched comparison areas across the five cities. Using ZIP code districts as proxies for urban neighborhoods, geospatial data mining algorithms serve to develop a neighborhood typology in order to match the comparison areas. To this end, both unsupervised and supervised algorithms are used to analyze high-dimensional data on crime, the socio-economic and demographic structure, and the built environment in order to classify urban neighborhoods into clusters of similar type. In a first step, self-organizing maps serve as tools to develop a clustering algorithm that reduces the within-cluster variance in the contextual variables and simultaneously maximizes the between-cluster variance in survey responses. The random forests algorithm then serves to assess the appropriateness of the resulting neighborhood typology and to select the key contextual variables in order to build a parsimonious model that makes a minimum of classification errors. Finally, for the impact analysis, propensity score matching methods are used to match the survey respondents of the pretest and posttest samples on age, gender, and their level of education for each neighborhood type identified within each city, before conducting a statistical test of the observed difference in the outcome measures. Moreover, all significant results were subjected to a sensitivity analysis to assess the robustness of these findings in the face of potential bias due to some unobserved covariates. The study finds that over the last fifteen years, all five police departments have undertaken major reforms of their internal organization and operating strategies and forged strategic partnerships in order to implement community policing. The resulting neighborhood typology reduced the within-cluster variance of the contextual variables and accounted for a significant share of the between-cluster variance in the outcome measures prior to treatment, suggesting that geocomputational methods help to balance the observed covariates and hence to reduce threats to the internal validity of an observational design. Finally, the impact analysis revealed that fear of crime dropped significantly over the 2000-2005 period in the neighborhoods in and around the urban centers of Bern and Zurich. These improvements are fairly robust in the face of bias due to some unobserved covariate and covary temporally and spatially with the implementation of community policing. The alternative hypothesis that the observed reductions in fear of crime were at least in part a result of community policing interventions thus appears at least as plausible as the null hypothesis of absolutely no effect, even if the observational design cannot completely rule out selection and regression to the mean as alternative explanations.

Electrical Machine Product Development; Transmission to Lean Approach

The requirements set by the market for electrical machines become increasingly demanding requiring more sophisticated technological solutions. Companies producing electrical ma-chines are challenged to develop machines that provide competitive edge for the customer for example through increased efficiency, reliability or some customer specific special requirement. The objective of this thesis is to derive a proposal for the first steps to transform the electrical machine product development process of a manufacturing company towards lean product development. The current product development process in the company is presented together with the processes of four other companies interviewed for the thesis. On the basis of current processes of the electrical machine industry and the related literature, a generalized electrical machine product development process is derived. The management isms and –tools utilized by the companies are analyzed. Adoption of lean Pull-Event –reviews, Oobeya –management and Knowledge based product development are suggested as the initial steps of implementing lean product development paradigm in the manufacturing company. Proposals for refining the cur-rent product development process and increasing the stakeholder involvement in the development projects are made. Lean product development is finding its way to Finnish electrical machine industry, but the results will be available only after the methods have been implemented and adopted by the companies. There is some enthusiasm about the benefits of lean approach and if executed successfully it will provide competitive edge for the Finnish electrical machine industry.

Replacing Copper with New Carbon Nanomaterials in Electrical Machine Windings

Electrical machines have significant improvement potential. Nevertheless, the field is characterized by incremental innovations. Admittedly, steady improvement has been achieved, but no breakthrough development. Radical development in the field would require the introduction of new elements, such that may change the whole electrical machine industry system. Recent technological advancements in nanomaterials have opened up new horizons for the macroscopic application of carbon nanotube (CNT) fibres. With values of 100 MS/m measured on individual CNTs, CNT fibre materials hold promise for conductivities far beyond those of metals. Highly conductive, lightweight and strong CNT yarn is finally within reach; it could replace copper as a potentially better winding material. Although not yet providing low resistivity, the newest CNT yarn offers attractive perspectives for accelerated efficiency improvement of electrical machines. In this article, the potential for using new CNT materials to replace copper in machine windings is introduced. It does so, firstly, by describing the environment for a change that could revolutionize the industry and, secondly, by presenting the breakthrough results of a prototype construction. In the test motor, which is to our knowledge the first in its kind, the presently most electrically conductive carbon nanotube yarn replaces usual copper in the windings.

Using Neural Network Classifier Support Vector Machine Regression for the prediction of Melting Point of Drug – like compounds

In our study we use a kernel based classification technique, Support Vector Machine Regression for predicting the Melting Point of Drug – like compounds in terms of Topological Descriptors, Topological Charge Indices, Connectivity Indices and 2D Auto Correlations. The Machine Learning model was designed, trained and tested using a dataset of 100 compounds and it was found that an SVMReg model with RBF Kernel could predict the Melting Point with a mean absolute error 15.5854 and Root Mean Squared Error 19.7576

History of the manufacture of iron in all ages, and particularly in the United States from colonial time to 1891. Also a short history of early coal mining in the United States ...

Mode of access: Internet.

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.

Solar Intensity Forecasting using Artificial Neural Networks and Support Vector Machines

This paper presents several forecasting methodologies based on the application of Artificial Neural Networks (ANN) and Support Vector Machines (SVM), directed to the prediction of the solar radiance intensity. The methodologies differ from each other by using different information in the training of the methods, i.e, different environmental complementary fields such as the wind speed, temperature, and humidity. Additionally, different ways of considering the data series information have been considered. Sensitivity testing has been performed on all methodologies in order to achieve the best parameterizations for the proposed approaches. Results show that the SVM approach using the exponential Radial Basis Function (eRBF) is capable of achieving the best forecasting results, and in half execution time of the ANN based approaches.

Between specialization and globalization. The marketing of agrarian products and its environmental impacts seen from a historical perspective: the province of Barcelona in the mid-nineteenth century

Ecological economics has five good reasons to consider that economic globalisation, spurred by commercial and financial fluxes, to be one of the main driving forces responsible for causing environmental degradation to our planet. The first, is the energy consumption and the socio-environmental impacts which long-distance haulage entails. The second, is the ever-increasing flow of goods to far-away destinations which renders their recycling practically impossible. This is particularly significant, because it prevents the metabolic lock of the nutrients present in food and other agrarian products from taking place. The third, is that the high degree of specialization attained in agriculture, forestry, cattle, mining and industry in each region, generates deleterious effects not only on the eco-landscape structure of the uses of the soil, but on the capability to provide habitat and environmental functions to maintain biodiversity as well

Sähkölaitekaapelipäätteiden kokoonpanotuotannon siirtäminen alihankkijalle

Työn tavoitteena oli selvittää kustannussäästöjä sähkölaitekomponentin kokoonpano- tuotannossa. Työssä vertaillaan oman ja alihankintatuotannon välisiä kustannuksia sekä tarkastellaan toiminnan joustavuutta, kun kokoonpano muodostuu kokonaisuudessaan ostettavista osista ja kuljetusmatka osien tuottajilta sekä myyjiltä on lyhyempi alihankkijalle, kuin omalle tehtaalle. Työssä järjestellään tuotteen kokoonpanolle edellytykset siirtymiseen alihankkijan hoidetta-vaksi niin, ettei siitä aiheudu ongelmia osavalmistuksen ja hankinnan, sekä valmiiden tuotteiden hallinnassa. Työssä selvitellään tuotteenmerkitystä ja sen kehittämistä sähkölaiteteollisuudelle. Tuotteen ja tuotannon kehittämisestä oli kohdeyrityksessä perustettu erityinen projekti, johon kuului myös muita sähkökaapeliliitäntään kuuluvia osia. Tuoteryhmä,jota tämä tutkimus käsittelee, siirrettiin alihankkijan kokoonpanotuotantoon vuonna 2000. Kaapelipäätteet kuuluvat yhtenä vaihtoehtoisena osana sähkölaitteiden voimakaape- loinnin läpivientiin ja suojaukseen. Projektissa kehitettiin 3 erilaista kaapelipäättä, joiden tehtävänä oli korvata 20 aikaisempaa mallia. Tällä tavoin kyseisen tuotteen ja sen komponenttien valmistussarjakokoja voitiin nostaa ja silti tuotannonkiertoa nopeuttaa, koska puskurivarastossa olevien variaatioiden määrä väheni 20:sta 3:een. Myös osa kokoonpanossa käytettävistä komponenteista voitiin käyttää kaikkien kaapelipäätemallien kokoonpanossa. Työssä vertaillaan kuljetuskustannusten eroa osahankinnassa oman ja alihankinta- tuotannon välillä, sekä vertaillaan varaston ja tuotannon tilankäyttöä ja tuotantokapasiteettia. Työn tarkoituksena on perustella ajatusta, että kuljetusmatkoja lyhentämällä voitaisiin saada kustannussäästöjä. Oman ja alihankintatyön kustannuksia vertaillaan ja huomattava säästö kokoonpanotyössä on tässä tapauksessa se, että alihankkijan laskutushinta työlle on alhaisempi, kuin mitä työn osuudelle on määritelty omassa tuotannossa. Varastotilan osalta vertailuatehtiin ainoastaan tilan käytön suhteen.

Toimittajasuhteiden kehittäminen kuormitusvaihteluiden tasaamiseksi

Työn tavoitteena oli varteenotettavien toimittajayhteistyökumppanien löytäminen pitkäaikaiseen ja vastavuoroiseen yhteistyöhön kuormitusvaihteluiden hallitsemiseksi. Yhteistyökumppania päädyttiin etsimään toimialoilta, joiden suhdannevaihtelut riippuisivat eri tekijöistä kuin massa- ja paperikoneiden valmistus -toimialan suhdannevaihtelut. Yhteistyön mahdollistamiseksi suhdanne- ja kapasiteettivaihteluiden tuli yhteistyökumppaneiden kesken kulkea mahdollisimman vastakkaiseen tahtiin.Toimialoja verrattiin niiden tuotannon bruttoarvon- sekä trendiarvon muutosprosenttien avulla. Mahdollisia yhteistyökumppaniyrityksiä etsittiin neljältä sopivimmalta toimialalta. Parhaiksi todettujen yritysten kanssa keskusteltiin yhteistyöstä ja tutustuttiin yritysten tuotantoihin ja yrityskulttuureihin. Kyseisten yritysten edustajat vierailivat myös Järvenpäässä. Työn lopuksi arvioitiin yhteistyön mahdollisuuksia parhaiksi todettujen yhteistyökumppaneiden ja Järvenpään Metso Paper Oy:n tuotannon komponenttivalmistuksen kanssa. Lisäksi esitettiin ehdotus jatkotoimenpiteistä yhteistyön syventämiseksi.

Creating Global Competitive Advantage by Global Product Technology Transfers

Globalization is the trend which is realized in all areas in today’s business world. Pressure for cost reduction, changes in market situation and available scale economies have changed business environment more global than ever. To respond to new situation, companies are establishing global strategies. In this thesis, available global competitive advantages in electrical machine industry are studied in context of gaining them by global technology transfers. In theory part, establishing global strategy and competitive advantage is considered with connection to global sourcing and supply chain management. Additionally, market development in 21st century and its impact on global strategies is studied. In practice, global manufacturing is enabled by technology transfer projects. Smooth and fast project implementation enables faster and more flexible production ramp up. By starting the production available competitive advantages can be realized. In this thesis the present situation of technology transfer projects and the risks and advantages related to global manufacturing are analyzed. The analysis of implemented technology transfer projects indicates that project implementation is in good level. For further development of project execution 10 minor suggestions could be presented with two major ones: higher level standardization and development of product information model to support better global manufacturing.