440 research outputs found

    What effect does short term Study Abroad (SA) have on learners’ vocabulary knowledge?

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    This thesis describes a study which tracks longitudinal changes in vocabularyknowledge during a short-term Study Abroad (SA) experience. A test ofproductive vocabulary knowledge, Lex30 (Meara & Fitzpatrick, 2000),requiring the production of word association responses, is used to elicit vocabulary from 38 Japanese L1 learners of English at four test times at equal intervals before and after an SA experience. The study starts by investigating whether there are changes in both the total number of words and in the number of less frequently occurring words produced by SA participants. Three additional ways of measuring the development of lexical knowledge over time are then proposed. The first examines changes in the ability of participants of different proficiency levels in producing collocates in response to Lex30 cue words. The second tracks changes in spelling accuracy to measure if improvements take place over time. The third analysis uses an online measuring instrument (Wmatrix; Rayson, 2009) to explore if there are any changes in the mastery of specific semantic domains. The results show that there is significant growth in the productive use of less frequent vocabulary knowledge during the SA period. There is also an increase in collocation production with lower proficiency participants and evidence of some improvement in the way certain vocabulary items are spelled. The tendency for SA learners to produce more words from semantic groups related to SA experiences is also demonstrated. Post-SA tests show that while some knowledge attrition occurs it does not decline to pre-SA levels. The studyshows how short-term SA programmes can be evaluated using a word association test, contributing to a better understanding of how vocabularydevelops during intensive language learning experiences. It also demonstrates the gradual shift of productive vocabulary knowledge from partial word knowledge to a more complete state of productive mastery

    Reoveepuhastuse käsiraamat

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    Vett vajavad eluks kõik meie planeedil elavad organismid, sh inimesed. Eestis kasutatakse olmes ja tootmises nii pinna- kui ka põhjavett. Suur osa sellest jõuab kanalisatsiooni ning tuleb enne loodusesse tagasi juhtimist või taaskasutamist puhastada. Seda tehakse reoveepuhastis, milles kulgevate keerukate protsesside rakendamiseks on vaja mitmesuguseid seadmeid ning haritud insenere ja töömehi. Aegade jooksul on Eestis välja antud palju juhendeid ning mõni kanalisatsiooni ja veekaitset käsitleva õpikki, aga kõiki reovee puhastamisega seotud aspekte ühiste kaante vahel varem käsitletud ei ole. Ometi on meil olemas hulk spetsialiste, kes oma lausa legendaarsetelt vanema põlvkonna õpetlastelt ja inseneridelt saadud erialateadmisi järjepidevalt täiendavad ja edasi annavad. Reoveekäitlus on kallis ning selle areng sai Eestis suure tõuke käesoleva sajandi alguses, mil tekkis võimalus kasutada Keskkonnainvesteeringute Keskuse (SA KIK) ja Euroopa Liidu tugiprogrammide toetusi. Kuigi veevarustuse ja kanalisatsiooni suuremad projektid on tänaseks lõppenud ning veevarustus- ja kanalisatsioonitööde hüppelist kasvu ei ole ette näha, tuleb neid süsteeme siiski käigus hoida, arendada ja optimeerida. Keskkonnaministeerium on aastaid korraldanud hankeid reoveepuhastite operaatorite koolitamiseks. Alates 2017. aastast on võimalik Järvamaa Kusehariduskeskuses omandada veekäitlusoperaatori kutse ning Tallinna Tehnikaülikoolis, Eesti Maaülikoolis ja Tartu Ülikoolis koolitatakse reoveekäitluse insenere ja tehnolooge. Kuigi reoveekäitluse eriala on võimalik õppida erineva taseme (kutse- või kõrghariduse vormis) õppekavade järgi, on puudu tänapäevasel tasemel õppekirjandusest, sest viimased põhjalikumad eestikeelsed õpikud pärinevad 1980-ndate esimesest poolest. Nagu muudki majandusvaldkonnad, areneb reovee puhastamine tänapäeval väga kiiresti. Täienevad standardid ning õigusaktidki. Et ajaga kaasas käia, peavad vee- ja reoveevaldkonnas tegutsejad end pidevalt täiendama: lugema erialaõpikuid, tuhlama internetis, külastama reoveepuhasteid ja messe ning tundma huvi selle vastu, mida teevad erialaorganisatsioonid. Meie vee puhtus põhineb ju erialasel pädevusel. Käesolev käsiraamat on valminud projekti LIFE IP CleanEST raames, mida rahastavad Euroopa Komisjoni LIFE-programm ja Eesti riik. Raamatu koostamisel püüti olla nii põhjalik, et seda saaks kasutada kutse- ja kõrgkoolis õpetamisel, oleks aga arusaadav ka neile veemajanduse valdkonna inimestele, kelle töökohustuste hulka reovee puhastamine ei kuulu. Et reoveekäitlus on väga lai ning kiiresti arenev valdkond, ei pruugi raamatus olla kajastatud kõik puhastustehnoloogiad ja -võtted, ent 4 andsime endast parima, et peamine käsitletud saaks. Kuigi raamatu kirjutamisel tugineti suuresti erialastandarditele (peamiselt Saksa normidele) ning välismaistele kõrgkooliõpikutele, arvestati ka teadusuuringute tulemusi, milles on varasemaid teadmisi oluliselt täpsustatud või lausa ümber kujundatud. Erilist rõhku on pööratud eestikeelsele oskussõnavarale, et aidata ühtlustada eri erialade inimeste keelepruuki. Eestikeelsed terminid seoti peamiselt maailma teaduskeele lingua franca'ks kujunenud inglise keelega, ent ka vene keelega, sest arvestatav osa reoveepuhastite operaatoritest on venekeelsed. Oskussõnavalimiku koostasid Aleksander Maastik, Raili Kärmas, Karin Pachel, Vallo Kõrgmaa, Mait Kriipsalu ja Vjačeslav Mutavči, tuginedes peamiselt standardile EVS-EN 16323. Käsiraamatu koostasid Eesti juhtivad teadlased ja erialaspetsialistid, kelle põhitöökohaks on mõni Eesti õppeasutus või projekteerimis- ja konsultatsiooniettevõte. Raamat valmis tänu nende inimeste pikaajalisele ja heale koostööle. Suur tänu kõigile, kes oma pingelise töö kõrvalt leidsid piisavalt aega peatükkide kirjutamiseks ja/või kolleegide kirjutatu retsenseerimiseks. Avaldame siirast tänu emeriitprofessor Aleksander Maastikule, kes ühtlustas autorite esialgsed tekstid lihtsamini loetavaks. Illustreerivad fotod püüdsime valida autorite isiklikest arhiividest ning valdav osa skeemidest on autorite koostatud. Muude autorite jooniseid on vajadusel eestindanud või kohandanud. Kasutatud allikatele on viidatud õpiku põhijaotiste kaupa. Lugeja peab silmas pidama, et viidatud on õigusaktide 2023. aastal kehtivale versioonile, ning et alati on vaja kontrollida, ega seda muudetud ole. Head lugemist! Vallo Kõrgmaa ja Mait KriipsaluKäsiraamat on valminud LIFE IP CleanEST projekti raames, mida rahastavad Euroopa Komisjoni LIFE programm ja Eesti riik. LIFE programmi rahastusleping nr LIFE17 IPE/EE/000007. Käsiraamat kajastab autorite seisukohti ja Euroopa Komisjon ei vastuta sisu kasutamise eest.Käsiraamat on valminud LIFE IP CleanEST projekti raames, mida rahastavad Euroopa Komisjoni LIFE programm ja Eesti riik. LIFE programmi rahastusleping nr LIFE17 IPE/EE/000007. Käsiraamat kajastab autorite seisukohti ja Euroopa Komisjon ei vastuta sisu kasutamise eest

    Is There a Relationship Between Vitamin D Level and Iron Deficiency Anemia in Children?

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    Iron deficiency anemia (IDA) is the most common type of anemia in children and a major cause of morbidity and mortality. Vitamin D deficiency (VDD) is a growing public health issue that has been connected to several chronic diseases, such as osteoporosis, cancer, and metabolic syndrome. Recently, in a meta-analytic study conducted on both children and adults, it was clearly shown that there is a relationship between VDD and the risk of anemia. In this study, we wanted to review the prevalence of vitamin D insufficiency in children with IDA. We conducted a retrospective review of patient records from January 2017 to December 2019 to identify individuals aged 4 months to 18 years who had been diagnosed with IDA. Demographic data, dietary patterns, nutritional supplements, Vitamin D levels, and laboratory tests were recorded. Two hundred thirty girls and 198 boys were enrolled in the study, bringing the total number of patients to 428. The patients had a mean age of 7.24±5.1 months. The distribution of female gender according to vitamin D groups (normal, insufficient, deficient) was 85, 103, and 42, respectively; the male gender is 78, 89, and 31, respectively (p=0.745). No statistically significant difference was found between nutrition categories and vitamin D groups in different age groups (p=0.293; p=0.238; p=0.396). No statistically significant difference was found between continuous quantitative variables such as age, hemoglobin, and ferritin and vitamin D groups in different age groups (p=0.885; p=0.168; p=0.728). There was no significant association observed between the severity of anemia and VDD in children with IDA in our study. In the diagnosis of IDA, it may be useful to look at vitamin D levels by considering the time of admission. Further studies are needed for the association between vitamin D levels and IDA

    optimización da planificación de adquisición de datos LIDAR cara ó modelado 3D de interiores

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    The main objective of this doctoral thesis is the design, validation and implementation of methodologies that allow the geometric and topological modelling of navigable spaces, whether inside buildings or urban environments, to be integrated into three-dimensional geographic information systems (GIS-3D). The input data of this work will consist mainly of point clouds (which can be classified) acquired by LiDAR systems both indoors and outdoors. In addition, the use of BIM infrastructure models and cadastral maps is proposed depending on their availability. Point clouds provide a large amount of environmental information with high accuracy compared to data offered by other acquisition technologies. However, the lack of data structure and volume requires a great deal of processing effort. For this reason, the first step is to structure the data by dividing the input cloud into simpler entities that facilitate subsequent processes. For this first division, the physical elements present in the cloud will be considered, since they can be walls in the case of interior environments or kerbs in the case of exteriors. In order to generate navigation routes adapted to different mobile agents, the next objective will try to establish a semantic subdivision of space according to the functionalities of space. In the case of internal environments, it is possible to use BIM models to evaluate the results and the use of cadastral maps that support the division of the urban environment. Once the navigable space is divided, the design of topologically coherent navigation networks will be parameterized both geometrically and topologically. For this purpose, several spatial discretization techniques, such as 3D tessellations, will be studied to facilitate the establishment of topological relationships, adjacency, connectivity and inclusion between subspaces. Based on the geometric characterization and the topological relations established in the previous phase, the creation of three-dimensional navigation networks with multimodal support will be addressed and different levels of detail will be considered according to the mobility specifications of each agent and its purpose. Finally, the possibility of integrating the networks generated in a GIS-3D visualization system will be considered. For the correct visualization, the level of detail can be adjusted according to geometry and semantics. Aspects such as the type of user or transport, mobility, rights of access to spaces, etc. They must be considered at all times.El objetivo principal de esta tesis doctoral es el diseño, la validación y la implementación de metodologías que permitan el modelado geométrico y topológico de espacios navegables, ya sea de interiores de edificios o entornos urbanos, para integrarse en sistemas de información geográfica tridimensional (SIG). -3D). Los datos de partida de este trabajo consistirán principalmente en nubes de puntos (que pueden estar clasificados) adquiridas por sistemas LiDAR tanto en interiores como en exteriores. Además, se propone el uso de modelos BIM de infraestructuras y mapas catastrales en función de su disponibilidad. Las nubes de puntos proporcionan una gran cantidad de información del entorno con gran precisión con respecto a los datos ofrecidos por otras tecnologías de adquisición. Sin embargo, la falta de estructura de datos y su volumen requiere un gran esfuerzo de procesamiento. Por este motivo, el primer paso que se debe realizar consiste en estructurar los datos dividiendo la nube de entrada en entidades más simples que facilitan los procesos posteriores. Para esta primera división se considerarán los elementos físicos presentes en la nube, ya que pueden ser paredes en el caso de entornos interiores o bordillos en el caso de los exteriores. Con el propósito de generar rutas de navegación adaptadas a diferentes agentes móviles, el próximo objetivo intentará establecer una subdivisión semántica del espacio de acuerdo con las funcionalidades del espacio. En el caso de entornos internos, es posible utilizar modelos BIM para evaluar los resultados y el uso de mapas catastrales que sirven de apoyo en la división del entorno urbano. Una vez que se divide el espacio navegable, se parametrizará tanto geométrica como topológicamente al diseño de redes de navegación topológicamente coherentes. Para este propósito, se estudiarán varias técnicas de discretización espacial, como las teselaciones 3D, para facilitar el establecimiento de relaciones topológicas, la adyacencia, la conectividad y la inclusión entre subespacios. A partir de la caracterización geométrica y las relaciones topológicas establecidas en la fase anterior, se abordará la creación de redes de navegación tridimensionales con soporte multimodal y se considerarán diversos niveles de detalle según las especificaciones de movilidad de cada agente y su propósito. Finalmente, se contemplará la posibilidad de integrar las redes generadas en un sistema de visualización tridimensional 3D SIG 3D. Para la correcta visualización, el nivel de detalle se puede ajustar en función de la geometría y la semántica. Aspectos como el tipo de usuario o transporte, movilidad, derechos de acceso a espacios, etc. Deben ser considerados en todo momento.O obxectivo principal desta tese doutoral é o deseño, validación e implementación de metodoloxías que permitan o modelado xeométrico e topolóxico de espazos navegables, ben sexa de interiores de edificios ou de entornos urbanos, ca fin de seren integrados en Sistemas de Información Xeográfica tridimensionais (SIX-3D). Os datos de partida deste traballo constarán principalmente de nubes de puntos (que poden estar clasificadas) adquiridas por sistemas LiDAR tanto en interiores como en exteriores. Ademáis plantease o uso de modelos BIM de infraestruturas e mapas catastrais dependendo da súa dispoñibilidade. As nubes de puntos proporcionan unha gran cantidade de información do entorno cunha gran precisión respecto os datos que ofrecen outras tecnoloxías de adquisición. Sen embargo, a falta de estrutura dos datos e a seu volume esixe un amplo esforzo de procesado. Por este motivo o primeiro paso a levar a cabo consiste nunha estruturación dos datos mediante a división da nube de entrada en entidades máis sinxelas que faciliten os procesos posteriores. Para esta primeira división consideraranse elementos físicos presentes na nube como poden ser paredes no caso de entornos interiores ou bordillos no caso de exteriores. Coa finalidade de xerar rutas de navegación adaptadas a distintos axentes móbiles, o seguinte obxectivo tratará de establecer unha subdivisión semántica do espazo de acordo as funcionalidades do espazo. No caso de entornos interiores plantease a posibilidade de empregar modelos BIM para avaliar os resultados e o uso de mapas catastrais que sirvan de apoio na división do entorno urbano. Unha vez divido o espazo navigable parametrizarase tanto xeométricamente como topolóxicamene de cara ao deseño de redes de navegación topolóxicamente coherentes. Para este fin estudaranse varias técnicas de discretización de espazos como como son as teselacións 3D co obxectivo de facilitar establecer relacións topolóxicas, de adxacencia, conectividade e inclusión entre subespazos. A partir da caracterización xeométrica e das relación topolóxicas establecidas na fase previa abordarase a creación de redes de navegación tridimensionais con soporte multi-modal e considerando varios niveis de detalle de acordo as especificacións de mobilidade de cada axente e a súa finalidade. Finalmente comtemplarase a posibilidade de integrar as redes xeradas nun sistema SIX 3D visualización tridimensional. Para a correcta visualización o nivel de detalle poderá axustarse en base a xeometría e a semántica. Aspectos como o tipo de usuario ou transporte, mobilidade, dereitos de acceso a espazos, etc. deberán ser considerados en todo momento

    Data models for dataset drift controls in machine learning with optical images

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    Camera images are ubiquitous in machine learning research. They also play a central role in the delivery of important public services spanning medicine or environmental surveying. However, the application of machine learning models in these domains has been limited because of robustness concerns. A primary failure mode are performance drops due to differences between the training and deployment data. While there are methods to prospectively validate the robustness of machine learning models to such dataset drifts, existing approaches do not account for explicit models of machine learning’s primary object of interest: the data. This limits our ability to study and understand the relationship between data generation and downstream machine learning model performance in a physically accurate manner. In this study, we demonstrate how to overcome this limitation by pairing traditional machine learning with physical optics to obtain explicit and differentiable data models. We demonstrate how such data models can be constructed for image data and used to control downstream machine learning model performance related to dataset drift. The findings are distilled into three applications. First, drift synthesis enables the controlled generation of physically faithful drift test cases to power model selection and targeted generalization. Second, the gradient connection between machine learning task model and data model allows advanced, precise tolerancing of task model sensitivity to changes in the data generation. These drift forensics can be used to precisely specify the acceptable data environments in which a task model may be run. Third, drift optimization opens up the possibility to create drifts that can help the task model learn better faster, effectively optimizing the data generating process itself to support the downstream machine vision task. This is an interesting upgrade to existing imaging pipelines which traditionally have been optimized to be consumed by human users but not machine learning models. The data models require access to raw sensor images as commonly processed at scale in industry domains such as microscopy, biomedicine, autonomous vehicles or remote sensing. Alongside the data model code we release two datasets to the public that we collected as part of this work. In total, the two datasets, Raw-Microscopy and Raw-Drone, comprise 1,488 scientifically calibrated reference raw sensor measurements, 8,928 raw intensity variations as well as 17,856 images processed through twelve data models with different configurations. A guide to access the open code and datasets is available at https://github.com/aiaudit-org/raw2logit

    Towards Cooperative MARL in Industrial Domains

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    Virtuosity in Computationally Creative Musical Performance for Bass Guitar

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    This thesis focuses on the development and implementation of a theory for a computationally creative musical performance system aimed at producing virtuosic interpretations of musical pieces for performance on bass guitar. This theory has been developed and formalised using Wiggins’ Creative Systems Framework (CSF) and uses case-base reasoning (CBR) and an engagement-reflection cycle to adorn monophonic musical note sequences with explicit performance directions, selected to maximise the virtuosity when performed using a bass guitar. A survey of 497 bass players’ playing competences was conducted and used to develop a playing complexity rating for adorned musical pieces. Measures of musical similarity used within the case-base reasoning were assessed by a listening test of 12 participants. A study into the perceived difficulty of bass performances was also conducted and an appropriate model of perceived bass playing difficulty determined. The complexity rating and perceived playing difficulties are utilised within the heuristic used by the system to determine what performances are considered to be virtuosic. The output of the system was rendered on a digital waveguide model of an electric bass, that was updated with newly developed digital waveguide synthesis methods for advanced bass guitar playing techniques. These audio renderings were evaluated with a perceptual study of 60 participants, the results of which were used to validate the heuristic used within the system. This research makes contribution to the fields of Computational Creativity (CC), AI Music Creativity, Music Information Retrieval and Musicology. It demonstrates how the CSF can be used as a tool to aid in designing computationally creative musical performance systems, provides a method to assess musical complexity and perceived difficulty of bass guitar performances, tested a suitable musical similarity measure for use within creative systems, and made advances in bass guitar digital waveguide synthesis methods

    Evaluating Stability in Massive Social Networks: Efficient Streaming Algorithms for Structural Balance

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    Structural balance theory studies stability in networks. Given a nn-vertex complete graph G=(V,E)G=(V,E) whose edges are labeled positive or negative, the graph is considered \emph{balanced} if every triangle either consists of three positive edges (three mutual ``friends''), or one positive edge and two negative edges (two ``friends'' with a common ``enemy''). From a computational perspective, structural balance turns out to be a special case of correlation clustering with the number of clusters at most two. The two main algorithmic problems of interest are: (i)(i) detecting whether a given graph is balanced, or (ii)(ii) finding a partition that approximates the \emph{frustration index}, i.e., the minimum number of edge flips that turn the graph balanced. We study these problems in the streaming model where edges are given one by one and focus on \emph{memory efficiency}. We provide randomized single-pass algorithms for: (i)(i) determining whether an input graph is balanced with O(logn)O(\log{n}) memory, and (ii)(ii) finding a partition that induces a (1+ε)(1 + \varepsilon)-approximation to the frustration index with O(npolylog(n))O(n \cdot \text{polylog}(n)) memory. We further provide several new lower bounds, complementing different aspects of our algorithms such as the need for randomization or approximation. To obtain our main results, we develop a method using pseudorandom generators (PRGs) to sample edges between independently-chosen \emph{vertices} in graph streaming. Furthermore, our algorithm that approximates the frustration index improves the running time of the state-of-the-art correlation clustering with two clusters (Giotis-Guruswami algorithm [SODA 2006]) from nO(1/ε2)n^{O(1/\varepsilon^2)} to O(n2log3n/ε2+nlogn(1/ε)O(1/ε4))O(n^2\log^3{n}/\varepsilon^2 + n\log n \cdot (1/\varepsilon)^{O(1/\varepsilon^4)}) time for (1+ε)(1+\varepsilon)-approximation. These results may be of independent interest

    Domain Generalization for Medical Image Analysis: A Survey

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    Medical Image Analysis (MedIA) has become an essential tool in medicine and healthcare, aiding in disease diagnosis, prognosis, and treatment planning, and recent successes in deep learning (DL) have made significant contributions to its advances. However, DL models for MedIA remain challenging to deploy in real-world situations, failing for generalization under the distributional gap between training and testing samples, known as a distribution shift problem. Researchers have dedicated their efforts to developing various DL methods to adapt and perform robustly on unknown and out-of-distribution data distributions. This paper comprehensively reviews domain generalization studies specifically tailored for MedIA. We provide a holistic view of how domain generalization techniques interact within the broader MedIA system, going beyond methodologies to consider the operational implications on the entire MedIA workflow. Specifically, we categorize domain generalization methods into data-level, feature-level, model-level, and analysis-level methods. We show how those methods can be used in various stages of the MedIA workflow with DL equipped from data acquisition to model prediction and analysis. Furthermore, we include benchmark datasets and applications used to evaluate these approaches and analyze the strengths and weaknesses of various methods, unveiling future research opportunities
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