902 resultados para Math Applications in Computer Science


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In this commentary, we argue that the term 'prediction' is overly used when in fact, referring to foundational writings of de Finetti, the correspondent term should be inference. In particular, we intend (i) to summarize and clarify relevant subject matter on prediction from established statistical theory, and (ii) point out the logic of this understanding with respect practical uses of the term prediction. Written from an interdisciplinary perspective, associating statistics and forensic science as an example, this discussion also connects to related fields such as medical diagnosis and other areas of application where reasoning based on scientific results is practiced in societal relevant contexts. This includes forensic psychology that uses prediction as part of its vocabulary when dealing with matters that arise in the course of legal proceedings.

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This study presents an innovative methodology for forensic science image analysis for event reconstruction. The methodology is based on experiences from real cases. It provides real added value to technical guidelines such as standard operating procedures (SOPs) and enriches the community of practices at stake in this field. This bottom-up solution outlines the many facets of analysis and the complexity of the decision-making process. Additionally, the methodology provides a backbone for articulating more detailed and technical procedures and SOPs. It emerged from a grounded theory approach; data from individual and collective interviews with eight Swiss and nine European forensic image analysis experts were collected and interpreted in a continuous, circular and reflexive manner. Throughout the process of conducting interviews and panel discussions, similarities and discrepancies were discussed in detail to provide a comprehensive picture of practices and points of view and to ultimately formalise shared know-how. Our contribution sheds light on the complexity of the choices, actions and interactions along the path of data collection and analysis, enhancing both the researchers' and participants' reflexivity.

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Sähköisen liiketoiminnan sovelluksia on voitu toistaiseksi käyttää useimmissa tapauksissa vain langallisen yhteyden kautta. Uudet langattomat teknologiat, jotka ovat kehittyneet nopeasti muutaman viimeisen vuoden aikana, mahdollistavat näiden sovellusten käytön ajasta ja paikasta riippumatta. Tämän työn tavoitteena oli tutkia langattomien sähköisen liiketoiminnan sovellusten käyttöä ja hyötyjä tieto- ja viestintäteollisuudessa. Työssä keskitytään tutkimaan tätä tietotekniikan evoluutioaskelta yksittäisen yrityksen kannalta: rajoittuen omassa toiminnassa käytettäviin sovelluksiin. Tutkimus luo viitekehyksen mobiilisuuden evoluutioon, uuden tietotekniikan vaikutuksiin ja hyötyihin sekä tarkemmin langattomiin sähköisen liiketoiminnan sovelluksiin. Tätä viitekehystä käytetään analysoitaessa nykyistä käyttöä tutkimuksen kohteena olevissa yrityksissä. Tutkimuksen johtopäätökset niin nykyisestä käytöstä kuin myös tulevasta ovat syntyneet viitekehyksen, nykyisen käytön, sekä tehtyjen haastattelujen pohjalta.

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Työn päätavoitteena oli tutkia mobiilipalveluita ja langattomia sovelluksia Suomen terveydenhuollon sektorilla. Tutkimus havainnollistaa avain-alueita, missä mobiilipalvelut ja langattomat sovellukset voivat antaa lisäarvoa perinteiseen lääketieteen harjoittamiseen, ja selvittää, mitkä ovat tähän kehitykseen liittyvät suurimmat ongelmat ja uhkat sekä tutkimustuloksiin pohjautuvat mahdolliset palvelut ja sovellukset 5-10 vuoden kuluttua. Tutkimus oli luonteeltaan kvalitatiivinen ja tutkimuksen toteuttamiseen valittiin tulevaisuudentutkimus ja erityisesti yksi sen menetelmistä, delfoi-menetelmä. Tutkimuksen aineisto kerättiin kahdelta puolistrukturoidulta haastattelukierrokselta. Työn empiirinen osuus keskittyi kuvailemaan Suomen terveydenhuollon sektoria, siinä meneillään olevia projekteja sekä teknisiä esteitä. Lisäksi pyrittiin vastaamaan tutkimuksen pääkysymykseen. Tutkimustulokset osoittivat, että tärkeät alueet, joihin langaton kommunikaatio tulisi vaikuttamaan merkittävästi, ovat ensiaputoiminta, kroonisten potilaiden etämonitorointi, välineiden kehittäminen langattomaan kommunikaatioon kotihoidon parantamiseksi ja uusien toimintamallien luomiseksi sekä lääketieteellinen yhteistyö jakamalla terveydenhuoltoon liittyvät informaation lähteet. Työn tulosten perusteellavoitiin antaa myös muutamia toimenpide-ehdotuksia jatkotutkimuksia varten.

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Fetoscopic coagulation of placental anastomoses is the treatment of choice for severe twin-to-twin transfusion syndrome. In the present day, fetal laser therapy is also used to treat amniotic bands, chorioangiomas, sacrococcygeal teratomas, lower urinary tract obstructions and chest masses, all of which will be reviewed in this article. Amniotic band syndrome can cause limb amputation by impairing downstream blood flow. Large chorioangiomas (>4 cm), sacrococcygeal teratomas or fetal hyperechoic lung lesions can lead to fetal compromise and hydrops by vascular steal phenomenon or compression. Renal damage, bladder dysfunction and lastly death because of pulmonary hypolasia may be the result of megacystis caused by a posterior urethral valve. The prognosis of these pathologies can be dismal, and therapy options are limited, which has brought fetal laser therapy to the forefront. Management options discussed here are laser release of amniotic bands, laser coagulation of the placental or fetal tumor feeding vessels and laser therapy by fetal cystoscopy. This review, largely based on case reports, does not intend to provide a level of evidence supporting laser therapy over other treatment options. Centralized evaluation by specialists using strict selection criteria and long-term follow-up of these rare cases are now needed to prove the value of endoscopic or ultrasound-guided laser therapy.

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In recent years, technological advances have allowed manufacturers to implement dual-energy computed tomography (DECT) on clinical scanners. With its unique ability to differentiate basis materials by their atomic number, DECT has opened new perspectives in imaging. DECT has been used successfully in musculoskeletal imaging with applications ranging from detection, characterization, and quantification of crystal and iron deposits; to simulation of noncalcium (improving the visualization of bone marrow lesions) or noniodine images. Furthermore, the data acquired with DECT can be postprocessed to generate monoenergetic images of varying kiloelectron volts, providing new methods for image contrast optimization as well as metal artifact reduction. The first part of this article reviews the basic principles and technical aspects of DECT including radiation dose considerations. The second part focuses on applications of DECT to musculoskeletal imaging including gout and other crystal-induced arthropathies, virtual noncalcium images for the study of bone marrow lesions, the study of collagenous structures, applications in computed tomography arthrography, as well as the detection of hemosiderin and metal particles.

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In recent years, technological advances have allowed manufacturers to implement dual-energy computed tomography (DECT) on clinical scanners. With its unique ability to differentiate basis materials by their atomic number, DECT has opened new perspectives in imaging. DECT has been successfully used in musculoskeletal imaging with applications ranging from detection, characterization, and quantification of crystal and iron deposits, to simulation of noncalcium (improving the visualization of bone marrow lesions) or noniodine images. Furthermore, the data acquired with DECT can be postprocessed to generate monoenergetic images of varying kiloelectron volts, providing new methods for image contrast optimization as well as metal artifact reduction. The first part of this article reviews the basic principles and technical aspects of DECT including radiation dose considerations. The second part focuses on applications of DECT to musculoskeletal imaging including gout and other crystal-induced arthropathies, virtual noncalcium images for the study of bone marrow lesions, the study of collagenous structures, applications in computed tomography arthrography, as well as the detection of hemosiderin and metal particles.

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In this paper we present a multi-stage classifier for magnetic resonance spectra of human brain tumours which is being developed as part of a decision support system for radiologists. The basic idea is to decompose a complex classification scheme into a sequence of classifiers, each specialising in different classes of tumours and trying to reproducepart of the WHO classification hierarchy. Each stage uses a particular set of classification features, which are selected using a combination of classical statistical analysis, splitting performance and previous knowledge.Classifiers with different behaviour are combined using a simple voting scheme in order to extract different error patterns: LDA, decision trees and the k-NN classifier. A special label named "unknown¿ is used when the outcomes of the different classifiers disagree. Cascading is alsoused to incorporate class distances computed using LDA into decision trees. Both cascading and voting are effective tools to improve classification accuracy. Experiments also show that it is possible to extract useful information from the classification process itself in order to helpusers (clinicians and radiologists) to make more accurate predictions and reduce the number of possible classification mistakes.

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Stratospheric ozone can be measured accurately using a limb scatter remote sensing technique at the UV-visible spectral region of solar light. The advantages of this technique includes a good vertical resolution and a good daytime coverage of the measurements. In addition to ozone, UV-visible limb scatter measurements contain information about NO2, NO3, OClO, BrO and aerosols. There are currently several satellite instruments continuously scanning the atmosphere and measuring the UVvisible region of the spectrum, e.g., the Optical Spectrograph and Infrared Imager System (OSIRIS) launched on the Odin satellite in February 2001, and the Scanning Imaging Absorption SpectroMeter for Atmospheric CartograpHY (SCIAMACHY) launched on Envisat in March 2002. Envisat also carries the Global Ozone Monitoring by Occultation of Stars (GOMOS) instrument, which also measures limb-scattered sunlight under bright limb occultation conditions. These conditions occur during daytime occultation measurements. The global coverage of the satellite measurements is far better than any other ozone measurement technique, but still the measurements are sparse in the spatial domain. Measurements are also repeated relatively rarely over a certain area, and the composition of the Earth’s atmosphere changes dynamically. Assimilation methods are therefore needed in order to combine the information of the measurements with the atmospheric model. In recent years, the focus of assimilation algorithm research has turned towards filtering methods. The traditional Extended Kalman filter (EKF) method takes into account not only the uncertainty of the measurements, but also the uncertainty of the evolution model of the system. However, the computational cost of full blown EKF increases rapidly as the number of the model parameters increases. Therefore the EKF method cannot be applied directly to the stratospheric ozone assimilation problem. The work in this thesis is devoted to the development of inversion methods for satellite instruments and the development of assimilation methods used with atmospheric models.

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Virtual screening is a central technique in drug discovery today. Millions of molecules can be tested in silico with the aim to only select the most promising and test them experimentally. The topic of this thesis is ligand-based virtual screening tools which take existing active molecules as starting point for finding new drug candidates. One goal of this thesis was to build a model that gives the probability that two molecules are biologically similar as function of one or more chemical similarity scores. Another important goal was to evaluate how well different ligand-based virtual screening tools are able to distinguish active molecules from inactives. One more criterion set for the virtual screening tools was their applicability in scaffold-hopping, i.e. finding new active chemotypes. In the first part of the work, a link was defined between the abstract chemical similarity score given by a screening tool and the probability that the two molecules are biologically similar. These results help to decide objectively which virtual screening hits to test experimentally. The work also resulted in a new type of data fusion method when using two or more tools. In the second part, five ligand-based virtual screening tools were evaluated and their performance was found to be generally poor. Three reasons for this were proposed: false negatives in the benchmark sets, active molecules that do not share the binding mode, and activity cliffs. In the third part of the study, a novel visualization and quantification method is presented for evaluation of the scaffold-hopping ability of virtual screening tools.

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The Differential Scanning Calorimetry (DSC) was used to study the thermal behavior of hair samples and to verify the possibility of identifying an individual based on DSC curves from a data bank. Hair samples of students and officials from Instituto de Química de Araraquara, UNESP were obtained to build up a data bank. Thus to sought an individual, under incognito participant of this data bank, was identified using DSC curves.