Forecasting coal resources and reserves in heterogeneous coal zones using 3D facies models (As Pontes Basin, NW Spain)

Forecasting coal resources and reserves is critical for coal mine development. Thickness maps are commonly used for assessing coal resources and reserves; however they are limited for capturing coal splitting effects in thick and heterogeneous coal zones. As an alternative, three-dimensional geostatistical methods are used to populate facies distributionwithin a densely drilled heterogeneous coal zone in the As Pontes Basin (NWSpain). Coal distribution in this zone is mainly characterized by coal-dominated areas in the central parts of the basin interfingering with terrigenous-dominated alluvial fan zones at the margins. The three-dimensional models obtained are applied to forecast coal resources and reserves. Predictions using subsets of the entire dataset are also generated to understand the performance of methods under limited data constraints. Three-dimensional facies interpolation methods tend to overestimate coal resources and reserves due to interpolation smoothing. Facies simulation methods yield similar resource predictions than conventional thickness map approximations. Reserves predicted by facies simulation methods are mainly influenced by: a) the specific coal proportion threshold used to determine if a block can be recovered or not, and b) the capability of the modelling strategy to reproduce areal trends in coal proportions and splitting between coal-dominated and terrigenousdominated areas of the basin. Reserves predictions differ between the simulation methods, even with dense conditioning datasets. Simulation methods can be ranked according to the correlation of their outputs with predictions from the directly interpolated coal proportion maps: a) with low-density datasets sequential indicator simulation with trends yields the best correlation, b) with high-density datasets sequential indicator simulation with post-processing yields the best correlation, because the areal trends are provided implicitly by the dense conditioning data.

Automatic Comparison and Evaluation of Impressions Left by a Firearm on Fired Cartridge Cases

Recent years have been characterized by a series of publications in the field of firearms investigation questioning the reliability and objectivity of such examination. This research investigates new solutions to decrease the subjective component affecting the evaluation that follows the comparison of impressions left by a firearm on the surface of spent cartridge cases. An automatic comparison system based on 3D measurements has been developed and coupled to a bivariate evaluative model allowing assigning likelihood ratios. Based on a dataset of 79 pistols (all SIG Sauer 9 mm Luger caliber), the system shows a very high discriminating power and the LRs that it provides are very indicative of the true state under both the prosecution and the defense propositions. For example, likelihood ratios exceeding a billion are predominantly obtained when impressions originating from the same source are compared. The system is also characterized by relatively low rates (≤1%) of misleading evidence depending on the firearm considered.

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.

Mobile Communications within the European Union: The Role of Location in the Evolution and Forecasting of the Diffusion Process

In the European Union, the importance of mobile communications was realized early on. The process of mobile communications becoming ubiquitous has taken time, as the innovation of mobile communications diffused into the society. The aim of this study is to find out how the evolution and spatial patterns of the diffusion of mobile communications within the European Union could be taken into account in forecasting the diffusion process. There is relatively lot of research of innovation diffusion on the individual (micro) andthe country (macro) level, if compared to the territorial level. Territorial orspatial diffusion refers either to the intra-country or inter-country diffusionof an innovation. In both settings, the dif- fusion of a technological innovation has gained scarce attention. This study adds knowledge of the diffusion between countries, focusing especially on the role of location in this process. The main findings of the study are the following: The penetration rates of the European Union member countries have become more even in the period of observation, from the year 1981 to 2000. The common digital GSM system seems to have hastened this process. As to the role of location in the diffusion process, neighboring countries have had similar diffusion processes. They can be grouped into three, the Nordic countries, the central and southern European countries, and the remote southern European countries. The neighborhood effect is also domi- nating in thegravity model which is used for modeling the adoption timing of the countries. The subsequent diffusion within a country, measured by the logistic model in Finland, is af- fected positively by its economic situation, and it seems to level off at some 92 %. Considering the launch of future mobile communications systemsusing a common standard should implicate an equal development between the countries. The launching time should be carefully selected as the diffusion is probably delayed in economic downturns. The location of a country, measured by distance, can be used in forecasting the adoption and diffusion. Fi- nally, the result of penetration rates becoming more even implies that in a relatively homoge- nous set of countries, such as the European Union member countries, the estimated final pene- tration of a single country can be used for approximating the penetration of the others. The estimated eventual penetration of Finland, some 92 %, should thus also be the eventual level for all the European Union countries and for the European Union as a whole.

A prospective observational study comparing a non-operator dependent automatic PWV analyser to pulse pressure, in assessing arterial stiffness in hemodialysis.

BACKGROUND: Chronic kidney disease (CKD) accelerates vascular stiffening related to age. Arterial stiffness may be evaluated measuring the carotid-femoral pulse wave velocity (PWV) or more simply, as recommended by KDOQI, monitoring pulse pressure (PP). Both correlate to survival and incidence of cardiovascular disease. PWV can also be estimated on the brachial artery using a Mobil-O-Graph; a non-operator dependent automatic device. The aim was to analyse whether, in a dialysis population, PWV obtained by Mobil-O-Graph (MogPWV) is more sensitive for vascular aging than PP. METHODS: A cohort of 143 patients from 4 dialysis units has been followed measuring MogPWV and PP every 3 to 6 months and compared to a control group with the same risk factors but an eGFR > 30 ml/min. RESULTS: MogPWV contrarily to PP did discriminate the dialysis population from the control group. The mean difference translated in age between the two populations was 8.4 years. The increase in MogPWV, as a function of age, was more rapid in the dialysis group. 13.3% of the dialysis patients but only 3.0% of the control group were outliers for MogPWV. The mortality rate (16 out of 143) was similar in outliers and inliers (7.4 and 8.0%/year). Stratifying patients according to MogPWV, a significant difference in survival was seen. A high parathormone (PTH) and to be dialysed for a hypertensive nephropathy were associated to a higher baseline MogPWV. CONCLUSIONS: Assessing PWV on the brachial artery using a Mobil-O-Graph is a valid and simple alternative, which, in the dialysis population, is more sensitive for vascular aging than PP. As demonstrated in previous studies PWV correlates to mortality. Among specific CKD risk factors only PTH is associated with a higher baseline PWV. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02327962.

Relationships between climate and winter cereal grain quality in Finland and their potential for forecasting

Selostus: Sään vaikutus syysviljojen hehtolitran painoon ennusteen laadinnan näkökulmasta

Using time and stochastic models for software reliability forecasting and analysis

Tämä työ luo katsauksen ajallisiin ja stokastisiin ohjelmien luotettavuus malleihin sekä tutkii muutamia malleja käytännössä. Työn teoriaosuus sisältää ohjelmien luotettavuuden kuvauksessa ja arvioinnissa käytetyt keskeiset määritelmät ja metriikan sekä varsinaiset mallien kuvaukset. Työssä esitellään kaksi ohjelmien luotettavuusryhmää. Ensimmäinen ryhmä ovat riskiin perustuvat mallit. Toinen ryhmä käsittää virheiden ”kylvöön” ja merkitsevyyteen perustuvat mallit. Työn empiirinen osa sisältää kokeiden kuvaukset ja tulokset. Kokeet suoritettiin käyttämällä kolmea ensimmäiseen ryhmään kuuluvaa mallia: Jelinski-Moranda mallia, ensimmäistä geometrista mallia sekä yksinkertaista eksponenttimallia. Kokeiden tarkoituksena oli tutkia, kuinka syötetyn datan distribuutio vaikuttaa mallien toimivuuteen sekä kuinka herkkiä mallit ovat syötetyn datan määrän muutoksille. Jelinski-Moranda malli osoittautui herkimmäksi distribuutiolle konvergaatio-ongelmien vuoksi, ensimmäinen geometrinen malli herkimmäksi datan määrän muutoksille.

Automatic target validation based on neuroscientific literature mining for tractography.

Target identification for tractography studies requires solid anatomical knowledge validated by an extensive literature review across species for each seed structure to be studied. Manual literature review to identify targets for a given seed region is tedious and potentially subjective. Therefore, complementary approaches would be useful. We propose to use text-mining models to automatically suggest potential targets from the neuroscientific literature, full-text articles and abstracts, so that they can be used for anatomical connection studies and more specifically for tractography. We applied text-mining models to three structures: two well-studied structures, since validated deep brain stimulation targets, the internal globus pallidus and the subthalamic nucleus and, the nucleus accumbens, an exploratory target for treating psychiatric disorders. We performed a systematic review of the literature to document the projections of the three selected structures and compared it with the targets proposed by text-mining models, both in rat and primate (including human). We ran probabilistic tractography on the nucleus accumbens and compared the output with the results of the text-mining models and literature review. Overall, text-mining the literature could find three times as many targets as two man-weeks of curation could. The overall efficiency of the text-mining against literature review in our study was 98% recall (at 36% precision), meaning that over all the targets for the three selected seeds, only one target has been missed by text-mining. We demonstrate that connectivity for a structure of interest can be extracted from a very large amount of publications and abstracts. We believe this tool will be useful in helping the neuroscience community to facilitate connectivity studies of particular brain regions. The text mining tools used for the study are part of the HBP Neuroinformatics Platform, publicly available at http://connectivity-brainer.rhcloud.com/.

Short-term forecasting of power demand in the Nord Pool market

Sähkönkulutuksen lyhyen aikavälin ennustamista on tutkittu jo pitkään. Pohjoismaisien sähkömarkkinoiden vapautuminen on vaikuttanut sähkönkulutuksen ennustamiseen. Aluksi työssä perehdyttiin aiheeseen liittyvään kirjallisuuteen. Sähkönkulutuksen käyttäytymistä tutkittiin eri aikoina. Lämpötila tilastojen käyttökelpoisuutta arvioitiin sähkönkulutusennustetta ajatellen. Kulutus ennusteet tehtiin tunneittain ja ennustejaksona käytettiin yhtä viikkoa. Työssä tutkittiin sähkönkulutuksen- ja lämpötiladatan saatavuutta ja laatua Nord Poolin markkina-alueelta. Syötettävien tietojen ominaisuudet vaikuttavat tunnittaiseen sähkönkulutuksen ennustamiseen. Sähkönkulutuksen ennustamista varten mallinnettiin kaksi lähestymistapaa. Testattavina malleina käytettiin regressiomallia ja autoregressiivistä mallia (autoregressive model, ARX). Mallien parametrit estimoitiin pienimmän neliösumman menetelmällä. Tulokset osoittavat että kulutus- ja lämpötiladata on tarkastettava jälkikäteen koska reaaliaikaisen syötetietojen laatu on huonoa. Lämpötila vaikuttaa kulutukseen talvella, mutta se voidaan jättää huomiotta kesäkaudella. Regressiomalli on vakaampi kuin ARX malli. Regressiomallin virhetermi voidaan mallintaa aikasarjamallia hyväksikäyttäen.

Wireless e-Business Applications - Methods for Forecasting the Demand of Wireless Services and Technologies

Tämä tutkimus oli osa sähköistä liiketoimintaa ja langattomia sovelluksia tutkivaa projektia ja tutkimuksen tavoitteena oli selvittää ennustamisen rooli päätöksenteko- ja suunnitteluprosessissa ja määrittää parhaiten soveltuvat ja useimmin käytetyt teknologian ennustusmenetelmät. Ennustusmenetelmiä tarkasteltiin erityisesti uuden teknologian ja pitkän aikavälin ennustamisen näkökulmasta. Tutkimus perustui teknologista ennustamista, pitkän aikavälin suunnittelua ja innovaatioprosesseja käsittelevän kirjallisuuden analysointiin. Materiaalin perusteella kuvataan teknologian ennustamista informaation hankkimisvälineenä organisaatioiden suunnitteluprosessin apuna. Työssä arvioidaan myös seuraavat teknologisen ennustamisen menetelmät: trendianalyysi-, Delfoi-, cross-impact analyysi-, morfologinen analyysi- ja skenaario analyysimenetelmä. Työ tuo esille jokaisen ennustusmenetelmä ominaispiirteet, rajoitukset ja sovellusmahdollisuudet. Käyttäen esiteltyjä menetelmiä, saadaan kerättyä hyödyllistä informaatiota tulevaisuuden näkymistä, joita sitten voidaan käyttää hyväksi organisaatioiden suunnitteluprosesseissa.

Automatic Segmentation of the Eye in 3D Magnetic Resonance Imaging: A Novel Statistical Shape Model for Treatment Planning of Retinoblastoma.

PURPOSE: Proper delineation of ocular anatomy in 3-dimensional (3D) imaging is a big challenge, particularly when developing treatment plans for ocular diseases. Magnetic resonance imaging (MRI) is presently used in clinical practice for diagnosis confirmation and treatment planning for treatment of retinoblastoma in infants, where it serves as a source of information, complementary to the fundus or ultrasonographic imaging. Here we present a framework to fully automatically segment the eye anatomy for MRI based on 3D active shape models (ASM), and we validate the results and present a proof of concept to automatically segment pathological eyes. METHODS AND MATERIALS: Manual and automatic segmentation were performed in 24 images of healthy children's eyes (3.29 ± 2.15 years of age). Imaging was performed using a 3-T MRI scanner. The ASM consists of the lens, the vitreous humor, the sclera, and the cornea. The model was fitted by first automatically detecting the position of the eye center, the lens, and the optic nerve, and then aligning the model and fitting it to the patient. We validated our segmentation method by using a leave-one-out cross-validation. The segmentation results were evaluated by measuring the overlap, using the Dice similarity coefficient (DSC) and the mean distance error. RESULTS: We obtained a DSC of 94.90 ± 2.12% for the sclera and the cornea, 94.72 ± 1.89% for the vitreous humor, and 85.16 ± 4.91% for the lens. The mean distance error was 0.26 ± 0.09 mm. The entire process took 14 seconds on average per eye. CONCLUSION: We provide a reliable and accurate tool that enables clinicians to automatically segment the sclera, the cornea, the vitreous humor, and the lens, using MRI. We additionally present a proof of concept for fully automatically segmenting eye pathology. This tool reduces the time needed for eye shape delineation and thus can help clinicians when planning eye treatment and confirming the extent of the tumor.

Preface: Extreme events induced by weather and climate change: evaluation, forecasting and proactive planning

This special issue of Natural Hazards and Earth System Sciences (NHESS) contains eight papers presented as oral or poster contributions in the Natural Hazards NH-1.2 session on"Extreme events induced by weather and climate change: evaluation, forecasting and proactive planning", held at the European Geosciences Union (EGU) General Assembly in Vienna, Austria, on 13-18 April 2008. The aim of the session was to provide an international forum for presenting new results and for discussing innovative ideas and concepts on extreme hydro-meteorological events, including: (i) the assessment of the risk posed by the extreme events, (ii) the expected changes in the frequency and intensity of the events driven by a changing climate and by multiple human- induced causes, (iii) new modelling approaches and original forecasting methods to predict extreme events and their consequences, and (iv) strategies for hazard mitigation and risk reduction, and for a improved adaptation to extreme hydro-meteorological events ...

Forecasting tourism demand using consumer expectations

Abstract Purpose- There is a lack of studies on tourism demand forecasting that use non-linear models. The aim of this paper is to introduce consumer expectations in time-series models in order to analyse their usefulness to forecast tourism demand. Design/methodology/approach- The paper focuses on forecasting tourism demand in Catalonia for the four main visitor markets (France, the UK, Germany and Italy) combining qualitative information with quantitative models: autoregressive (AR), autoregressive integrated moving average (ARIMA), self-exciting threshold autoregressions (SETAR) and Markov switching regime (MKTAR) models. The forecasting performance of the different models is evaluated for different time horizons (one, two, three, six and 12 months). Findings- Although some differences are found between the results obtained for the different countries, when comparing the forecasting accuracy of the different techniques, ARIMA and Markov switching regime models outperform the rest of the models. In all cases, forecasts of arrivals show lower root mean square errors (RMSE) than forecasts of overnight stays. It is found that models with consumer expectations do not outperform benchmark models. These results are extensive to all time horizons analysed. Research limitations/implications- This study encourages the use of qualitative information and more advanced econometric techniques in order to improve tourism demand forecasting. Originality/value- This is the first study on tourism demand focusing specifically on Catalonia. To date, there have been no studies on tourism demand forecasting that use non-linear models such as self-exciting threshold autoregressions (SETAR) and Markov switching regime (MKTAR) models. This paper fills this gap and analyses forecasting performance at a regional level. Keywords Tourism, Forecasting, Consumers, Spain, Demand management Paper type Research paper

Forecasting a language shift based on cellular automata

Language extinction as a consequence of language shifts is a widespread social phenomenon that affects several million people all over the world today. An important task for social sciences research should therefore be to gain an understanding of language shifts, especially as a way of forecasting the extinction or survival of threatened languages, i.e., determining whether or not the subordinate language will survive in communities with a dominant and a subordinate language. In general, modeling is usually a very difficult task in the social sciences, particularly when it comes to forecasting the values of variables. However, the cellular automata theory can help us overcome this traditional difficulty. The purpose of this article is to investigate language shifts in the speech behavior of individuals using the methodology of the cellular automata theory. The findings on the dynamics of social impacts in the field of social psychology and the empirical data from language surveys on the use of Catalan in Valencia allowed us to define a cellular automaton and carry out a set of simulations using that automaton. The simulation results highlighted the key factors in the progression or reversal of a language shift and the use of these factors allowed us to forecast the future of a threatened language in a bilingual community.

Papaya seedlings growth using a low-cost, automatic watering controller

The study assessed growth and physiological parameters of 'Sunrise Golden' and 'Tainung 01' papaya seedlings grown in 280mL plastic tubes and watered using a low-cost automatic irrigation system adjusted to operate at substrate water tension for starting irrigation (STI) of 3.0, 6.0 or 9.0 kPa. The water depths applied by the dripping system and drainage were monitored during germination and seedling growth. Germination, emergence velocity index (EVI), leaf area, plant height, shoot and root dry weight, stomatal conductance, relative water content (RWC) and relative chlorophyll content (RCC) were evaluated. Soil nutrient levels were determined by electrical conductivity (EC). Water use efficiency (WUE) corresponded to the ratio of plant dry mass to depth of water applied. STI settings did not affect papaya germination or EVI. System configuration to 3.0 and 6.0 kPa STI exhibited the highest drainage and lowest EC and RCC, indicating soil nutrient loss and plant nutrient deficiency. Drainage was greater in tubes planted with the 'Tainung 01' variety, which developed smaller root systems and lower stomatal conductance than 'Sunrise Golden' seedlings. The highest values for shoot dry weight and WEU were obtained at 6.0 kPa STI for 'Sunrise Golden' (0.62 g and 0.69 g L-1) and at 9.0 kPa in 'Tainung 01' (0.35 g and 0.82 g L-1). RWC at 9.0 kPa STI was lower than at 3.0 kPa in both varieties. The results indicate that the low-cost technology developed for irrigation automation is promising. Even so, new studies are needed to evaluate low-flow irrigation systems as well as the nutrient and water needs of different papaya varieties.