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En aquest treball de fi de màster s'elabora una eina de recollida d'informació, en format d'enquesta online, sobre les experiències que està vivint el professorat envers la introducció de les Tecnologies d'Aprenentatge i Coneixement a la seva pràctica docent, posant especial èmfasi a la freqüència amb que les utilitza, els principals àmbits on declara que les tecnologies digitals l'ajuden i els principals inconvenients que hi observa. Al llarg de l'enquesta també es demana informació sobre altres aspectes com la formació pel bon ús de les TAC, la Competència Digital Docent, la predisposició a innovar o diferents característiques demogràfiques del professorat participant, entre d'altres. Aquestes dades s'aprofiten per comparar les respostes donades en funció dels diferents col·lectius als que pertany el professorat en cada cas, proposar possibles línies de recerca futura. Finalment s'avalua el procés seguit i es comparteix amb un mentor digital, amb qui s'amplien els punts de vista envers el treball realitzat per acabar oferint unes conclusions amb major criteri.

Today's society demands constant updates based on a type of teaching mediated by the use of technologies, and with it the need for training in digital teaching skills (DTC) that responds to existing demands. The main objective of the study is to find out whether there are statistically significant differences in relation to the level of DDC shown by university teaching staff at the Universidad Continental (Peru), based on different variables: gender, age of the participants, branch of knowledge, teaching experience in the use of ICT, years of use, among others. A study has been carried out, using contrast statistics, on a total of 1658 teachers, who answered the DigCompEdu Check-in questionnaire, which measures the level of competence achieved by them. The results indicate that there are some significant differences between the different groups for each variable., La sociedad actual demanda actualizaciones constantes en base a un tipo de enseñanza mediada por el uso de las tecnologías, y con ello la necesidad de una formación en competencias digitales docentes (CDD) que responda a las exigencias existentes. El objetivo principal perseguido a lo largo del estudio es dar a conocer si existen diferencias estadísticamente significativas en relación con el nivel de CDD mostrado por el profesorado universitario en la Universidad Continental (Perú), en base a diferentes variables: género, edad de los participantes, rama del conocimiento, experiencia docente en el uso de las TIC, años de utilización, entre otras. Se ha llevado a cabo un estudio, empleando la estadística de contraste, a un total de 1658 docentes, los cuales contestaron al cuestionario DigCompEdu Check-in, que mide el nivel competencial alcanzado por los mismos. Los resultados indican que existen algunas diferencias significativas entre los diferentes grupos de cada variable.

Performance of several neural network architectures (convolutional neural network CNN, multilayer perceptron MLP, CNN/MLP hybrid CDD) was evaluated for kinetic analysis of complex processes with overlapping independent reaction mechanisms based on the nucleation-growth Johnson-Mehl-Avrami (JMA) model. Theoretically simulated data used for the testing covered absolute majority of real-life JMA-JMA solid-state kinetics scenarios. The performance of the tested architectures decreased in the following order: MLP > CDD >> CNN. For partially overlapping processes the CDD and MLP architectures provided accurate estimates of the JMA model kinetic parameters, performing on par with traditional methods of kinetic analysis. For the fully overlapping kinetic processes, the accuracy of the estimates provided by the neural networks significantly worsened, however still largely outperforming the traditional approaches of kinetic analysis based on the standard non-linear optimization, such as mathematic or kinetic deconvolution. The corresponding kinetic predictions were of suitable precision for majority of real-life applications preparation (glass-ceramics)., Výkonnost několika architektur neuronových sítí (konvoluční neuronová síť CNN, vícevrstvý perceptron MLP, CNN/MLP hybrid CDD) byla hodnocena pro kinetickou analýzu komplexních procesů s překrývajícími se nezávislými reakčními mechanismy na základě modelu nukleačního růstu Johnson-Mehl-Avrami (JMA) . Teoreticky simulovaná data použitá pro testování pokryla naprostou většinu reálných scénářů kinetiky pevných látek JMA-JMA. Výkon testovaných architektur klesal v následujícím pořadí: MLP > CDD >> CNN. Pro částečně se překrývající procesy architektura CDD a MLP poskytla přesné odhady kinetických parametrů modelu JMA, které fungují na stejné úrovni jako tradiční metody kinetické analýzy. U plně se překrývajících kinetických procesů se přesnost odhadů poskytovaných neuronovými sítěmi výrazně zhoršila, avšak stále do značné míry překonávají tradiční přístupy kinetické analýzy založené na standardní nelineární optimalizaci, jako je matematická nebo kinetická dekonvoluce. Odpovídající kinetické predikce byly dostatečně přesné pro většinu příprav reálných aplikací (sklokeramika).

Today's society demands constant updates based on a type of teaching mediated by the use of technologies, and with it the need for training in digital teaching skills (DTC) that responds to existing demands. The main objective of the study is to find out whether there are statistically significant differences in relation to the level of DDC shown by university teaching staff at the Universidad Continental (Peru), based on different variables: gender, age of the participants, branch of knowledge, teaching experience in the use of ICT, years of use, among others. A study has been carried out, using contrast statistics, on a total of 1658 teachers, who answered the DigCompEdu Check-in questionnaire, which measures the level of competence achieved by them. The results indicate that there are some significant differences between the different groups for each variable., La sociedad actual demanda actualizaciones constantes en base a un tipo de enseñanza mediada por el uso de las tecnologías, y con ello la necesidad de una formación en competencias digitales docentes (CDD) que responda a las exigencias existentes. El objetivo principal perseguido a lo largo del estudio es dar a conocer si existen diferencias estadísticamente significativas en relación con el nivel de CDD mostrado por el profesorado universitario en la Universidad Continental (Perú), en base a diferentes variables: género, edad de los participantes, rama del conocimiento, experiencia docente en el uso de las TIC, años de utilización, entre otras. Se ha llevado a cabo un estudio, empleando la estadística de contraste, a un total de 1658 docentes, los cuales contestaron al cuestionario DigCompEdu Check-in, que mide el nivel competencial alcanzado por los mismos. Los resultados indican que existen algunas diferencias significativas entre los diferentes grupos de cada variable.

Modelling rainfall extremes and dry periods over the Southeast Asia (SEA) region is challenging due to the characteristics of the region, which consists of the Maritime Continent and a mountainous region; it also experiences monsoonal conditions, as it is located between the Asian summer monsoon and the Australian summer monsoon. Representing rainfall extremes is important for flood and drought assessments in the region. This paper evaluates extreme rainfall climatic indices from regional climate models from CORDEX Southeast Asia and compares them with the results of high-resolution global climate models with a comparable spatial resolution from the HighResMIP experiment. Observations indicate a high intensity of rainfall over areas affected by tropical cyclones and long consecutive dry day periods over some areas in Indochina and the southern end of Indonesia. In the model simulations, we find that both coupled and sea surface temperature-forced HighResMIP model experiments are more similar to the observations than CORDEX model results. However, the models produce a poorer simulation of precipitation intensity-related indices due to model biases in the rainfall intensity. This bias is higher in CORDEX than in HighResMIP and is evident in both the low- and high-resolution HighResMIP model versions. The comparable performances of HighResSST (atmosphere-only runs) and Hist-1950 (coupled ocean–atmosphere runs) demonstrate the accuracy of the ocean model. Comparable performances were also found for the two different resolutions of HighResMIP, suggesting that there is no improvement in the performance of the high-resolution HighResMIP model compared to the low-resolution HighResMIP model.

This study evaluates the effect of complete nationwide lockdown in 2020 on residential electricity demand across 13 Indian cities and the role of digitalisation using a public smart meter dataset. We undertake a data-driven approach to explore the energy impacts of work-from-home norms across five dwelling typologies. Our methodology includes climate correction, dimensionality reduction and machine learning-based clustering using Gaussian Mixture Models of daily load curves. Results show that during the lockdown, maximum daily peak demand increased by 150-200% as compared to 2018 and 2019 levels for one room-units (RM1), one bedroom-units (BR1) and two bedroom-units (BR2) which are typical for low- and middle-income families. While the upper-middle- and higher-income dwelling units (i.e., three (3BR) and more-than-three bedroom-units (M3BR)) saw night-time demand rise by almost 44% in 2020, as compared to 2018 and 2019 levels. Our results also showed that new peak demand emerged for the lockdown period for RM1, BR1 and BR2 dwelling typologies. We found that the lack of supporting socioeconomic and climatic data can restrict a comprehensive analysis of demand shocks using similar public datasets, which informed policy implications for India's digitalisation. We further emphasised improving the data quality and reliability for effective data-centric policymaking.

This study evaluates the effect of complete nationwide lockdown in 2020 on residential electricity demand across 13 Indian cities and the role of digitalisation using a public smart meter dataset. We undertake a data-driven approach to explore the energy impacts of work-from-home norms across five dwelling typologies. Our methodology includes climate correction, dimensionality reduction and machine learning-based clustering using Gaussian Mixture Models of daily load curves. Results show that during the lockdown, maximum daily peak demand increased by 150-200% as compared to 2018 and 2019 levels for one room-units (RM1), one bedroom-units (BR1) and two bedroom-units (BR2) which are typical for low- and middle-income families. While the upper-middle- and higher-income dwelling units (i.e., three (3BR) and more-than-three bedroom-units (M3BR)) saw night-time demand rise by almost 44% in 2020, as compared to 2018 and 2019 levels. Our results also showed that new peak demand emerged for the lockdown period for RM1, BR1 and BR2 dwelling typologies. We found that the lack of supporting socioeconomic and climatic data can restrict a comprehensive analysis of demand shocks using similar public datasets, which informed policy implications for India's digitalisation. We further emphasised improving the data quality and reliability for effective data-centric policymaking.

Open Data (OD) is data available in a machine-readable format and without restrictions on the permissions for using or distributing it. OD may include textual artifacts, images, maps, video content, and other. The data can be published and maintained by different entities, both public and private. Despite its power to distribute knowledge freely and availability of a large number of datasets, OD initiatives face important challenges related to its widespread take up. More specifically, OD provisioning is based on a unidirectional linking from OD providers to OD users without considering requirements and preferences of the users. The OD users also lack metadata, and they need to develop specific technical solutions for providing a continuous OD flow and processing, which is particularly difficult when real-time OD are to be used. In this paper, we propose solving these challenges by envisioning a business ecosystem for OD. It is network-based, federated, and supports interplay between OD provisioning and knowledge management. As a methodological solution, we have applied the capability-driven development approach, which allows modeling of OD processing ecosystems, facilitates knowledge exchange about OD usage among members of the ecosystem, and supports configuring information systems for OD processing. The proposal is explicated with a theoretical study of its usability for the service of road maintenance in varying conditions.

Career Decision Making is essential part of human life. Most of the people are thinking about this since adolescence. Therefore, we should analyze significant features about career decision difficulties of adolescents in Bangladesh. The goal of this work to explore the most affected class of adolescents about career decision difficulties considering family income ranges in Bangladesh. In this situation, we gathered several records of high school going adolescents at Faridganj, Chandpur, Bangladesh using career decision difficulties questionnaire which was proposed by I. Gati et. al. Hence, several regression algorithms were considered for experimental analysis based on the characteristics of our primary career decision difficulties dataset. After that, these algorithms were applied into career decision difficulties dataset of adolescents and explored the best regression algorithm based on experimental results from them. Then, our selected best algorithm was implemented throughout different datasets (split from primary dataset) and interpreted their findings. Finally, we observed that middle level family income ranges (10000-21000 BDT) of adolescents were faced more difficulties to take proper decision about career than others. This analysis is suggested as a complementary tool for further psychological treatment about career decisions.

BACKGROUND & AIMS: Congenital diarrheal disorders are rare inherited intestinal disorders characterized by intractable, sometimes life-threatening, diarrhea and nutrient malabsorption; some have been associated with mutations in diacylglycerol-acyltransferase 1 (DGAT1), which catalyzes formation of triacylglycerol from diacylglycerol and acyl-CoA. We investigated the mechanisms by which DGAT1 deficiency contributes to intestinal failure using patient-derived organoids.METHODS: We collected blood samples from 10 patients, from 6 unrelated pedigrees, who presented with early-onset severe diarrhea and/or vomiting, hypoalbuminemia, and/or (fatal) protein-losing enteropathy with intestinal failure; we performed next-generation sequence analysis of DNA from 8 patients. Organoids were generated from duodenal biopsies from 3 patients and 3 healthy individuals (controls). Caco-2 cells and patient-derived dermal fibroblasts were transfected or transduced with vectors that express full-length or mutant forms of DGAT1 or full-length DGAT2. We performed CRISPR/Cas9-guided disruption of DGAT1 in control intestinal organoids. Cells and organoids were analyzed by immunoblot, immunofluorescence, flow cytometry, chromatography, quantitative real-time PCR, and for activities of caspases 3 and 7.RESULTS: In the 10 patients, we identified 5 bi-allelic loss-of-function mutations in DGAT1. In patient-derived fibroblasts and organoids, the mutations reduced expression of DGAT1 protein and altered triacylglycerol metabolism, resulting in decreased lipid droplet formation after oleic acid addition. Expression of full-length DGAT2 in patient-derived fibroblasts restored formation of lipid droplets. Organoids derived from patients with DGAT1 mutations were more susceptible to lipid-induced cell death than control organoids.CONCLUSIONS: We identified a large cohort of patients with congenital diarrheal disorders with mutations in DGAT1 that reduced expression of its

The Capability-Driven Development (CDD) methodology is supported by the CDD environment, a set of tools that allow design and deployment of capabilities. The environment is constructed to support the CDD method by providing the functionality to model the capabilities and their contexts. Moreover, the environment also receives run-time support for the monitoring and adjustments of capabilities. The run-time functionality is meant to work in tandem with existing IT systems that an organization already has invested in. Thus, the environment tools have several interfaces that allow them to work together and with external systems. This chapter describes the main features of the CDD environment tools and their interfaces. Examples are given for each of the tools.

In essence, Open Data (OD) is the information available in a machine-readable format and without restrictions on the permissions for using or distributing it. Open Data may include textual artifacts, or non-textual, such as images, maps, scientific formulas, and other. The data can be publicized and maintained by different entities, both public and private. The data are often federated, meaning that various data sources are aggregated in data sets at a single “online” location. Despite its power to distribute free knowledge, OD initiatives face some important challenges related to its growth. In this paper, we consider one of them, namely, the business and technical concerns of OD clients that would make them able to utilize Open Data in their enterprise information systems and thus benefit in terms of improvements of their service and products in continuous and sustainable ways. Formally, we describe these concerns by means of high-level requirements and guidelines for development and run-time monitoring of IT-supported business capabilities, which should be able to consume Open Data, as well as able to adjust when the data updates based on a situational change. We illustrated our theoretical proposal by applying it on the service concerning regional roads maintenance in Latvia.

En este trabajo analizamos la adquisición y aprendizaje de las competencias digitales metodológicas (CDM) de la competencia digital docente adquiridas en el Máster Universitario en Formación del Profesorado de Educación Secundaria Obligatoria y Bachillerato, Formación Profesional y Enseñanza de Idiomas en la Universidad UPC. La investigación forma parte del Trabajo de Final de Máster de Sílvia Galofre y Caroline Börjesson, dos alumnas que están actualmente cursando el Máster en Formación del Profesorado de Formación Profesional. La adquisición de las competencias digitales metodológicas se analizan desde dos perspectivas: la de los profesores que actualmente imparten asignaturas en el Máster y a través de su actividad profesional, transfieren las competencias digitales metodológicas a sus alumnos; y por otro lado, desde la perspectiva de los alumnos que están cursando el Máster y como futuros profesores, necesitarán acreditar la competencia digital metodológica, para obtener la competencia digital docente. Caroline Börjesson se encarga de analizar la perspectiva del claustro de profesores, mientras que Sílvia Galofré se ocupa de investigar la visión de los alumnos. Ambas investigaciones se desarrollan en paralelo, con un mismo objetivo. En el punto 0 del índice, está indicada la parte común y específica de cada una de las investigaciones. El proyecto se dividen en dos fases: la investigación y el análisis.

This dissertation combines research on three topics in development economics. The first paper estimates the long-term labor performance outcomes for a worker subjected to a negative labor market shock upon entry. The second paper, based on joint work with Alain de Janvry and Elisabeth Sadoulet, examines the political economy of public goods provision through community driven development projects in the context of decentralization . The third paper analyzes household behavior under multiple shocks in rural China. The first paper looks at the impact of labor market shocks upon graduation on the education/work decision and on subsequent employment status in Indonesia where the Asian financial crisis hit in 1997/8. The work/education decision affects the selection of samples when estimating the later impact. Therefore we use a dual selection model to correct the sample selection bias due to the decision process. We find evidence of persistent impacts on later labor market outcomes for junior high and senior high school graduates measured as the probability of working in the informal sector or the agricultural sector. The second paper identifies the impact of increasing decentralization on community targeting using the unique situation of Zambia's Social Investment Fund (SIF) where the degree of decentralization changed in time and space across districts over the 15 years of program implementation. We find that greater decentralization of SIF's functions to districts that had been deemed to have the necessary level of managerial capacity to deserve decentralization led to more progressive targeting across wards, mildly so at the national level and strongly so within districts. We also observe how local electoral politics gained importance with greater decentralization, with more votes received by the candidate from the majority party in the district council attracting more projects to a ward, and more projects in a ward rewarded by more votes for the councilor from the i

A State Price Density (SPD) is the density function of a risk neutral equivalent martingale measure for option pricing, and is indispensible for exotic option pricing and portfolio risk management. Many approaches have been proposed in the last two decades to calibrate a SPD using financial options from the bond and equity markets. Among these, non and semi parametric methods were preferred because they can avoid model mis-specification of the underlying and thus give insight into complex portfolio propelling. However, these methods usually require a large data set to achieve desired convergence properties. Despite recent innovations in finan- cial and insurance markets, many markets remain incomplete and there exists an illiquidity issue. One faces the problem in estimation by e.g. kernel techniques that there are not enough observations locally available. For this situation, we employ a Bayesian quadrature method because it allows us to incorporate prior assumptions on the model parameters and hence avoids problems with data sparsity. It is able to compute the SPD of both call and put options simultaneously, and is particularly robust when the market faces the illiquidity issue. By comparing our approach with other approaches, we show that the traditional way of estimating the SPD by differ- entiating an interpolation of option prices does not hold in practice. As illustration, we calibrate the SPD for weather derivatives, a classical example of incomplete mar- kets with financial contracts payoffs linked to non-tradable assets, namely, weather indices. Finally, we study the dynamics of the implied SPD's and related to weather data.

The increasing availability of online catalogs and bibliographical databases allows not only for copy cataloging, but also for the retrieval of atomic information useful within the catalog. To this end, Dewey decimal numbers were imported from national and international sources by means of the unique identifier ISBN.Technical specifications have been developed to locate the records to be retrieved, to query external databases, to extract the Dewey decimal classification numbers and add them to the catalog.The exceptionally large amount of Dewey numbers added to the catalog has improved the semantic usability of the OPAC.The procedure established has also facilitated the collection of information on the use of the Dewey Decimal System in the various databases used and allowed to make certain comparisons between them.The tools employed can be used analogously for data-retrieval operations in the catalog, as an aid in the cataloging process, or to improve the OPAC in either a static or dynamic manner.Taking into account its virtually exclusive practical purpose, this work is characterized by practical rather than theoretical choices. However, the experience acquired opens up areas even in the field of academic research., La crescente disponibilità di cataloghi online e banche dati bibliografiche permette oltre alla catalogazione derivata, anche il reperimento all'interno del catalogo di informazioni "atomiche" utili. A tal fine, i numeri decimali Dewey sono stati importati nelle fonti nazionali e internazionali mediante l'identificatore univoco ISBN. Sono state sviluppate specifiche tecniche per individuare i record da recuperare, per interrogare i database esterni e per estrarre i numeri di classificazione Dewey e aggiungerli al catalogo. La grande quantità di numeri Dewey aggiunti al catalogo ha migliorato l'usabilità semantica degli OPAC. La procedura stabilita ha anche facilitato la raccolta delle informazioni sull'uso del Sistema di Classificazione Decimale Dewey nelle varie basi di dati utilizzate ed autorizzate a fare taluni confronti tra loro. Gli strumenti impiegati possono essere usati analogamente per le operazioni di recupero dei dati nel catalogo, sia come supporto nel processo di catalogazione sia per arricchire gli OPAC in modo statico e dinamico. Tenendo conto del suo esclusivo scopo pratico, questo lavoro è caratterizzato da scelte concrete, piuttosto che teoriche. Tuttavia, l'esperienza acquisita apre spazi anche nel campo della ricerca accademica.

This paper explores the history, uses cases, and future plans associated with availability of the Dewey Decimal Classification (DDC) system as linked data. Parts of DDC system have been available as linked data since 2009. Initial efforts included the DDC Summaries in eleven languages exposed as linked data in dewey.info. In 2010, the content of dewey.info was further extended by the addition of assignable numbers and captions from the Abridged Edition 14 data files in English, Italian, and Vietnamese. During 2012, we will add assignable numbers and captions from the latest full edition database, DDC 23. In addition to the “old friends” of different Dewey language versions, institutions such as the British Library and Deutsche Nationalbibliothek have made use of Dewey linked data in bibliographic records and authority files, and AGROVOC has linked to our data at a general level. We expect to extend our linked data network shortly to “new acquaintances” such as GeoNames, ISO 639-3 language codes, and Mathematics Subject Classification. In particular, the paper examines the linking process to GeoNames as an example of cross-domain vocabulary alignment. In addition to linking plans, the paper reports on use cases that facilitate machine-assisted categorization and support discovery in the semantic web environment.

This dissertation combines research on three topics in development economics. The first paper estimates the long-term labor performance outcomes for a worker subjected to a negative labor market shock upon entry. The second paper, based on joint work with Alain de Janvry and Elisabeth Sadoulet, examines the political economy of public goods provision through community driven development projects in the context of decentralization . The third paper analyzes household behavior under multiple shocks in rural China. The first paper looks at the impact of labor market shocks upon graduation on the education/work decision and on subsequent employment status in Indonesia where the Asian financial crisis hit in 1997/8. The work/education decision affects the selection of samples when estimating the later impact. Therefore we use a dual selection model to correct the sample selection bias due to the decision process. We find evidence of persistent impacts on later labor market outcomes for junior high and senior high school graduates measured as the probability of working in the informal sector or the agricultural sector. The second paper identifies the impact of increasing decentralization on community targeting using the unique situation of Zambia's Social Investment Fund (SIF) where the degree of decentralization changed in time and space across districts over the 15 years of program implementation. We find that greater decentralization of SIF's functions to districts that had been deemed to have the necessary level of managerial capacity to deserve decentralization led to more progressive targeting across wards, mildly so at the national level and strongly so within districts. We also observe how local electoral politics gained importance with greater decentralization, with more votes received by the candidate from the majority party in the district council attracting more projects to a ward, and more projects in a ward rewarded by more votes for the councilor from the i

The increasing availability of online catalogs and bibliographical databases allows not only for copy cataloging, but also for the retrieval of atomic information useful within the catalog. To this end, Dewey decimal numbers were imported from national and international sources by means of the unique identifier ISBN.Technical specifications have been developed to locate the records to be retrieved, to query external databases, to extract the Dewey decimal classification numbers and add them to the catalog.The exceptionally large amount of Dewey numbers added to the catalog has improved the semantic usability of the OPAC.The procedure established has also facilitated the collection of information on the use of the Dewey Decimal System in the various databases used and allowed to make certain comparisons between them.The tools employed can be used analogously for data-retrieval operations in the catalog, as an aid in the cataloging process, or to improve the OPAC in either a static or dynamic manner.Taking into account its virtually exclusive practical purpose, this work is characterized by practical rather than theoretical choices. However, the experience acquired opens up areas even in the field of academic research., La crescente disponibilità di cataloghi online e banche dati bibliografiche permette oltre alla catalogazione derivata, anche il reperimento all'interno del catalogo di informazioni "atomiche" utili. A tal fine, i numeri decimali Dewey sono stati importati nelle fonti nazionali e internazionali mediante l'identificatore univoco ISBN. Sono state sviluppate specifiche tecniche per individuare i record da recuperare, per interrogare i database esterni e per estrarre i numeri di classificazione Dewey e aggiungerli al catalogo. La grande quantità di numeri Dewey aggiunti al catalogo ha migliorato l'usabilità semantica degli OPAC. La procedura stabilita ha anche facilitato la raccolta delle informazioni sull'uso del Sistema di Classificazione Decimale Dewey nelle varie basi di dati utilizzate ed autorizzate a fare taluni confronti tra loro. Gli strumenti impiegati possono essere usati analogamente per le operazioni di recupero dei dati nel catalogo, sia come supporto nel processo di catalogazione sia per arricchire gli OPAC in modo statico e dinamico. Tenendo conto del suo esclusivo scopo pratico, questo lavoro è caratterizzato da scelte concrete, piuttosto che teoriche. Tuttavia, l'esperienza acquisita apre spazi anche nel campo della ricerca accademica.

This paper explores the history, uses cases, and future plans associated with availability of the Dewey Decimal Classification (DDC) system as linked data. Parts of DDC system have been available as linked data since 2009. Initial efforts included the DDC Summaries in eleven languages exposed as linked data in dewey.info. In 2010, the content of dewey.info was further extended by the addition of assignable numbers and captions from the Abridged Edition 14 data files in English, Italian, and Vietnamese. During 2012, we will add assignable numbers and captions from the latest full edition database, DDC 23. In addition to the “old friends” of different Dewey language versions, institutions such as the British Library and Deutsche Nationalbibliothek have made use of Dewey linked data in bibliographic records and authority files, and AGROVOC has linked to our data at a general level. We expect to extend our linked data network shortly to “new acquaintances” such as GeoNames, ISO 639-3 language codes, and Mathematics Subject Classification. In particular, the paper examines the linking process to GeoNames as an example of cross-domain vocabulary alignment. In addition to linking plans, the paper reports on use cases that facilitate machine-assisted categorization and support discovery in the semantic web environment.

A State Price Density (SPD) is the density function of a risk neutral equivalent martingale measure for option pricing, and is indispensible for exotic option pricing and portfolio risk management. Many approaches have been proposed in the last two decades to calibrate a SPD using financial options from the bond and equity markets. Among these, non and semi parametric methods were preferred because they can avoid model mis-specification of the underlying and thus give insight into complex portfolio propelling. However, these methods usually require a large data set to achieve desired convergence properties. Despite recent innovations in finan- cial and insurance markets, many markets remain incomplete and there exists an illiquidity issue. One faces the problem in estimation by e.g. kernel techniques that there are not enough observations locally available. For this situation, we employ a Bayesian quadrature method because it allows us to incorporate prior assumptions on the model parameters and hence avoids problems with data sparsity. It is able to compute the SPD of both call and put options simultaneously, and is particularly robust when the market faces the illiquidity issue. By comparing our approach with other approaches, we show that the traditional way of estimating the SPD by differ- entiating an interpolation of option prices does not hold in practice. As illustration, we calibrate the SPD for weather derivatives, a classical example of incomplete mar- kets with financial contracts payoffs linked to non-tradable assets, namely, weather indices. Finally, we study the dynamics of the implied SPD's and related to weather data.

A State Price Density (SPD) is the density function of a risk neutral equivalent martingale measure for option pricing, and is indispensible for exotic option pricing and portfolio risk management. Many approaches have been proposed in the last two decades to calibrate a SPD using financial options from the bond and equity markets. Among these, non and semi parametric methods were preferred because they can avoid model mis-specification of the underlying and thus give insight into complex portfolio propelling. However, these methods usually require a large data set to achieve desired convergence properties. Despite recent innovations in finan- cial and insurance markets, many markets remain incomplete and there exists an illiquidity issue. One faces the problem in estimation by e.g. kernel techniques that there are not enough observations locally available. For this situation, we employ a Bayesian quadrature method because it allows us to incorporate prior assumptions on the model parameters and hence avoids problems with data sparsity. It is able to compute the SPD of both call and put options simultaneously, and is particularly robust when the market faces the illiquidity issue. By comparing our approach with other approaches, we show that the traditional way of estimating the SPD by differ- entiating an interpolation of option prices does not hold in practice. As illustration, we calibrate the SPD for weather derivatives, a classical example of incomplete mar- kets with financial contracts payoffs linked to non-tradable assets, namely, weather indices. Finally, we study the dynamics of the implied SPD's and related to weather data.

CAT-Bonds und Wetterderivate sind die Endprodukte eines Verbriefungprozesses, der nicht handelbare Risikofaktoren (Wetterschäden oder Naturkatastrophenschäden) in handelbare Finanzanlagen verwandelt. Als Ergebnis sind die Märkte für diese Produkte in der Regel unvollständig. Da geeignete Risikomaße in Bezug auf einen bestimmten Preis Voraussetzung sind zur Preisbestimmung, ist es notwendig den Marktpreis des Risikos (MPR), welcher ein wichtiger Parameter des zugehörigen äquivalenten Martingalmaß ist, zu berücksichtigen. Die Mehrheit der bisherigen Veröffentlichungen haben die Preise der nicht handelbaren Vermögenswerte mittels der Annahme geschätzt, dass der MPR gleich null ist. Diese Annahme verzerrt allerdings die Preise und wurde bisher noch nicht quantifiziert. Diese Doktorarbeit beschäftigt sich mit den Unterschieden zwischen dem historischen und dem risikoneutralen Verhalten der nicht handelbaren Basiswerte und gibt Einblicke in den Marktpreis für Wetterrisiko und die Wetterrisikoprämie. Diese Arbeit beginnt mit einer Darstellung der Instrumente zur Übertragung der Risiken, gefolgt von den finanziellen - statistischen Verfahren und endet mit einer Untersuchung reeller Daten, wobei der Schwerpunkt auf die implizierten Trigger-Intensitätsraten eines parametrischen CAT-Bond für Erdbeben und auf den MPR der Temperatur Derivate gelegt wird., CAT bonds and weather derivatives are end-products of a process known as securitization that transform non-tradable (natural catastrophes or weather related) risk factors into tradable financial assets. As a result the markets for such products are typically incomplete. Since appropiate measures of the risk associated to a particular price become necessary for pricing, one essentially needs to incorporate the market price of risk (MPR), which is an important parameter of the associated equivalent martingale measure. The majority of papers so far has priced non-tradable assets assuming zero MPR, but this assumption yields biased prices and has never been quantified earlier. This thesis deals with the differences between historical and risk neutral behaviors of the non-tradable underlyings and gives insights into the behaviour of the market price of weather risk and weather risk premium. The thesis starts by introducing the risk transfering instruments, the financial - statistical techniques and ends up by examining the real data applications with particular focus on the implied trigger intensity rates of a parametric CAT bond for earthquakes and the MPR of temperature derivatives.

CAT-Bonds und Wetterderivate sind die Endprodukte eines Verbriefungprozesses, der nicht handelbare Risikofaktoren (Wetterschäden oder Naturkatastrophenschäden) in handelbare Finanzanlagen verwandelt. Als Ergebnis sind die Märkte für diese Produkte in der Regel unvollständig. Da geeignete Risikomaße in Bezug auf einen bestimmten Preis Voraussetzung sind zur Preisbestimmung, ist es notwendig den Marktpreis des Risikos (MPR), welcher ein wichtiger Parameter des zugehörigen äquivalenten Martingalmaß ist, zu berücksichtigen. Die Mehrheit der bisherigen Veröffentlichungen haben die Preise der nicht handelbaren Vermögenswerte mittels der Annahme geschätzt, dass der MPR gleich null ist. Diese Annahme verzerrt allerdings die Preise und wurde bisher noch nicht quantifiziert. Diese Doktorarbeit beschäftigt sich mit den Unterschieden zwischen dem historischen und dem risikoneutralen Verhalten der nicht handelbaren Basiswerte und gibt Einblicke in den Marktpreis für Wetterrisiko und die Wetterrisikoprämie. Diese Arbeit beginnt mit einer Darstellung der Instrumente zur Übertragung der Risiken, gefolgt von den finanziellen - statistischen Verfahren und endet mit einer Untersuchung reeller Daten, wobei der Schwerpunkt auf die implizierten Trigger-Intensitätsraten eines parametrischen CAT-Bond für Erdbeben und auf den MPR der Temperatur Derivate gelegt wird., CAT bonds and weather derivatives are end-products of a process known as securitization that transform non-tradable (natural catastrophes or weather related) risk factors into tradable financial assets. As a result the markets for such products are typically incomplete. Since appropiate measures of the risk associated to a particular price become necessary for pricing, one essentially needs to incorporate the market price of risk (MPR), which is an important parameter of the associated equivalent martingale measure. The majority of papers so far has priced non-tradable assets assuming zero MPR, but this assumption yields biased prices and has never been quantified earlier. This thesis deals with the differences between historical and risk neutral behaviors of the non-tradable underlyings and gives insights into the behaviour of the market price of weather risk and weather risk premium. The thesis starts by introducing the risk transfering instruments, the financial - statistical techniques and ends up by examining the real data applications with particular focus on the implied trigger intensity rates of a parametric CAT bond for earthquakes and the MPR of temperature derivatives.

Weather derivatives (WD) are different from most financial derivatives because the underlying weather cannot be traded and therefore cannot be replicated by other financial instruments. The market price of risk (MPR) is an important parameter of the associated equivalent martingale measures used to price and hedge weather futures/options in the market. The majority of papers so far have priced non-tradable assets assuming zero MPR, but this assumption underestimates WD prices. We study the MPR structure as a time dependent object with concentration on emerging markets in Asia. We find that Asian Temperatures (Tokyo, Osaka, Beijing, Teipei) are normal in the sense that the driving stochastics are close to a Wiener Process. The regression residuals of the temperature show a clear seasonal variation and the volatility term structure of CAT temperature futures presents a modified Samuelson effect. In order to achieve normality in standardized residuals, the seasonal variation is calibrated with a combination of a fourier truncated series with a GARCH model and with a local linear regression. By calibrating model prices, we implied the MPR from Cumulative total of 24-hour average temperature futures (C24AT) for Japanese Cities, or by knowing the formal dependence of MPR on seasonal variation, we price derivatives for Kaohsiung, where weather derivative market does not exist. The findings support theoretical results of reverse relation between MPR and seasonal variation of temperature process.

Weather derivatives (WD) are different from most financial derivatives because the underlying weather cannot be traded and therefore cannot be replicated by other financial instruments. The market price of risk (MPR) is an important parameter of the associated equivalent martingale measures used to price and hedge weather futures/options in the market. The majority of papers so far have priced non-tradable assets assuming zero MPR, but this assumption underestimates WD prices. We study the MPR structure as a time dependent object with concentration on emerging markets in Asia. We find that Asian Temperatures (Tokyo, Osaka, Beijing, Teipei) are normal in the sense that the driving stochastics are close to a Wiener Process. The regression residuals of the temperature show a clear seasonal variation and the volatility term structure of CAT temperature futures presents a modified Samuelson effect. In order to achieve normality in standardized residuals, the seasonal variation is calibrated with a combination of a fourier truncated series with a GARCH model and with a local linear regression. By calibrating model prices, we implied the MPR from Cumulative total of 24-hour average temperature futures (C24AT) for Japanese Cities, or by knowing the formal dependence of MPR on seasonal variation, we price derivatives for Kaohsiung, where weather derivative market does not exist. The findings support theoretical results of reverse relation between MPR and seasonal variation of temperature process.

Weather derivatives (WD) are different from most financial derivatives because the underlying weather cannot be traded and therefore cannot be replicated by other financial instruments. The market price of risk (MPR) is an important parameter of the associated equivalent martingale measures used to price and hedge weather futures/options in the market. The majority of papers so far have priced non-tradable assets assuming zero MPR, but this assumption underestimates WD prices. We study the MPR structure as a time dependent object with concentration on emerging markets in Asia. We find that Asian Temperatures (Tokyo, Osaka, Beijing, Teipei) are normal in the sense that the driving stochastics are close to a Wiener Process. The regression residuals of the temperature show a clear seasonal variation and the volatility term structure of CAT temperature futures presents a modified Samuelson effect. In order to achieve normality in standardized residuals, the seasonal variation is calibrated with a combination of a fourier truncated series with a GARCH model and with a local linear regression. By calibrating model prices, we implied the MPR from Cumulative total of 24-hour average temperature futures (C24AT) for Japanese Cities, or by knowing the formal dependence of MPR on seasonal variation, we price derivatives for Kaohsiung, where weather derivative market does not exist. The findings support theoretical results of reverse relation between MPR and seasonal variation of temperature process.