Los protocolos de investigación médica requieren que los datos y los resultados sean veraces, para poder determinar las acciones más en salud pública. Es por eso esencial la confianza en la inmutabilidad de los datos recolectados y analizados, así como la protección de la información de los sujetos participantes. Este trabajo se basa en el uso de la tecnología Blockchain y la arquitectura Workspace para brindar una plataforma para conducir estos protocolos de forma segura, confiable y transparente. La organización en la que se basa este trabajo tiene más de 30 años en el Perú realizando protocolos de este tipo. La tesis identificó problemas de errores generados por la recolección manual de información, así como en quiénes debían tener acceso a los datos; además, se encontró problemas en la trazabilidad de los cambios en la información; finalmente, se requería una plataforma de acceso a la información desde cualquier lugar, dispositivo, y momento. La tesis analizó las opciones en el mercado y determinó el uso de Blockchain as a Service (BaaS) de Amazon Web Services (AWS), y Workspace de Citrix Cloud y AWS como la solución más adecuada para el proyecto. Se realizaron pruebas en los algoritmos de enrolamiento y recolección de datos, determinando la efectividad de los mismos al haberse detectado los cambios realizados a la información en el 100% de los casos, así como aceptado los enrolamientos por consenso de los miembros de la red Blockchain. Finalmente, se accedió a los recursos del Workspace desde dispositivos Android y Windows 10, desde una red móvil Entel y una red Wifi de casa Movistar con acceso autorizado. / The medical research investigation protocols require that the data collected and results are trustful, in order to decide the best course of actions in public health. Thus, it is essential the data immutability of the information collected and analyzed, as well as the protection of the information of the enrolled subjects. This thesis is based in the use of Blockchain technology and Workspace architecture to provide a platform to conduct research protocols in a most secure, trustful and transparent way. The organization, which this thesis is based, has over 30 year conducting this type of protocols in Peru. This work identified problems in errors caused by manual data collection process, as well as concerns on who should be able to access the patient’s information; furthermore, we found problems in tracing changes in the information through the protocol; finally, it was identified the need for a platform to access data from anywhere, from any device, anytime. We analyzed technology options in the market and decided to use Blockchain as a service (BaaS) from Amazon Web Services (AWS), and Workspace from Citrix Cloud and AWS as the most suitable solution for this project. We conducted test of the Blockchain enrollment and data collection algorithms, finding a 100% effectiveness in all cases analyzed, and the consensus of enrollment by the Blockchain network members. Finally, we successfully accessed the Workspace resources using Android and Windows 10 devices from a mobile network (ENTEL) and a WI-FI home service (Movistar). / Tesis

El presente trabajo de investigación se centra en cómo mejorar la eficacia y eficiencia de la gestión pública, concretamente, en la Dirección General del Gobierno Interior, DGIN mediante la correcta implementación y aplicación de las Tecnologías de Información y Comunicación, TIC, a fin de que las diferentes instituciones públicas puedan utilizar y aplicar adecuadamente estas herramientas tecnológicas y así optimizar los procesos internos y la interacción e interoperabilidad entre las entidades públicas, en un primer momento, y luego que presten un servicio de eficiencia, de eficacia, de calidad a los usuarios. Otro aspecto que se busca con este trabajo de investigación para mejorar la gestión de la Dirección General del Gobierno Interior, DGIN es implementar una gobernanza de datos abiertos que permita una gobernanza colaborativa institucional, en donde la información fluya, sea transparente, se encuentre disponible en tiempo real, al hacer esto se consigue optimizar tiempo, ahorrar recursos, además, lo que se logra es implementar una gestión pública por resultados, lo que significa que se debe rendir cuentas a partir de las evidencias que existan siendo esta también una forma efectiva para luchar contra la corrupción en el sector público. Existen varios desafíos y compromisos que deben asumir los actores involucrados, siendo entre otros que deben existir procesos serios de capacitación y asistencia técnica, a los funcionarios. Además, se debe privilegiar las competencias personales, y sobre todo, se debe contar con un presupuesto que permita realizar mejoras en la DGIN y así cumpla adecuadamente sus funciones. / This research work focuses on how to improve the effectiveness and efficiency of public management, specifically, in the General Directorate of the Interior Government, DGIN, through the correct implementation and application of Information and Communication Technologies (TIC), so that the different public institutions can use and properly apply these technological tools to optimize internal processes, the interaction, and interoperability between public entities. And also to provide efficient and qualified services. Another aspect of this research is to improve the management of the General Directorate of the Interior Government, DGIN, to implement an open data governance that allows institutional collaborative governance, where information flows, and to be transparent, and available in real time. By doing so, it is possible to optimize time and save resources. In adition, we can achieve an effective public management by results, which means that accounts must be made based on evidence as an effective way to fight corruption in the public sector. There are several challenges and commitments that the involved actors must assume. Among others, training and technical assistance processes for officials. In addition, personal competencies must be privileged, and above all, a budget must be available that allows improvements to be made in the DGIN. Therefore, adequately fulfills its functions. / Tesis

Nowadays, Renewable Energy Sources (RES) are attracting more and more interest. Thus, many countries aim to increase the share of green energy and have to face with several challenges (e.g., balancing, storage, pricing). In this paper, we address the balancing challenge and present the MIRABEL project which aims to prototype an Energy Data Management System (EDMS) which takes benefit of flexibilities to efficiently balance energy demand and supply. The EDMS consists of millions of heterogeneous nodes that each incorporates advanced components (e.g., aggregation, forecasting, scheduling, negotiation). We describe each of these components and their interaction. Preliminary experimental results confirm the feasibility of our EDMS.

The SAP HANA database is positioned as the core of the SAP HANA Appliance to support complex business analytical processes in combination with transactionally consistent operational workloads. Within this paper, we outline the basic characteristics of the SAP HANA database, emphasizing the distinctive features that differentiate the SAP HANA database from other classical relational database management systems. On the technical side, the SAP HANA database consists of multiple data processing engines with a distributed query processing environment to provide the full spectrum of data processing -- from classical relational data supporting both row- and column-oriented physical representations in a hybrid engine, to graph and text processing for semi- and unstructured data management within the same system. From a more application-oriented perspective, we outline the specific support provided by the SAP HANA database of multiple domain-specific languages with a built-in set of natively implemented business functions. SQL -- as the lingua franca for relational database systems -- can no longer be considered to meet all requirements of modern applications, which demand the tight interaction with the data management layer. Therefore, the SAP HANA database permits the exchange of application semantics with the underlying data management platform that can be exploited to increase query expressiveness and to reduce the number of individual application-to-database round trips.

<p>Artificial neural networks (ANNs) have achieved extraordinary performance in various domains in recent years. However, some studies reveal that ANNs may be vulnerable in three aspects: label scarcity, perturbations, and open-set emerging classes. Noisy labeling and self-supervised learning approaches address the label scarcity issues, but most of the work couldn't handle the perturbations. Adversarial training methods, topological denoising methods, and mechanism designing methods aim to mitigate the negative effects caused by perturbations. However, adversarial training methods can barely train a robust model under the circumstance of extensive label scarcity; topological denoising methods are not efficient on dynamic data structures; and mechanism designing methods often depend on heuristic explorations. Detection-based methods devote to identifying novel or anomaly instances for further downstream tasks. Nonetheless, such instances may belong to open-set new emerging classes. To embrace the aforementioned challenges, we address the robustness issues of ANNs from two aspects. First, we propose a series of Bayesian label transition models to improve the robustness of Graph Neural Networks (GNNs) in the presence of label scarcity and perturbations in the graph domain. Second, we propose a new non-exhaustive learning model, named NE-GM-GAN, to handle both open-set problems and class-imbalance issues in network intrusion datasets. Extensive experiments with several datasets demonstrate that our proposed models can effectively improve the robustness of ANNs.</p>

<p>The web and digital technologies have been continuously growing in the recent five years. The data generated from the Internet of Things (IoT) devices are heterogeneous, increasing data storage and management difficulties. The thesis developed user-friendly data management system frameworks in the local environment and cloud platform. The two frameworks applied to two applications in the industrial field: the agriculture informatics system and the personal healthcare management system. The systems are capable of information management and two-way communication through a user-friendly interface. </p>

The rapid growth of current data warehouse systems makes random sampling a crucial component of modern data management systems. Although there is a large body of work on database sampling, the problem of automatic sample selection remained (almost) unaddressed. In this paper, we tackle the problem with a sample advisor. We propose a cost model to evaluate a sample for a given query. Based on this, our sample advisor determines the optimal set of samples for a given set of queries specified by an expert. We further propose an extension to utilize recorded workload information. In this case, the sample advisor takes the set of queries and a given memory bound into account for the computation of a sample advice. Additionally, we consider the merge of samples in case of overlapping sample advice and present both an exact and a heuristic solution. Within our evaluation, we analyze the properties of the cost model and compare the proposed algorithms. We further demonstrate the effectiveness and the efficiency of the heuristic solutions with a variety of experiments.

Semantic-Representation-Provenance-Contextual-Information-Scientific-Research Die Computer- und Informationstechnologie ist eine der größten Errungenschaften des letzten Jahrhunderts -- eine Revolution, welche die Art und Weise beeinflusst, auf die wir im täglichen Leben auf technische und soziale Problemen reagieren. Obwohl diese Technologien bereits Forschungsaktivitäten an sich beeinflussen, so ist zu erwarten, dass sie auch einen Einfluss auf das Publizieren und Teilen von Forschungsergebnissen haben werden. Bisher wurden in wissenschaftlichen Publikationen nur in geringem Maße Daten beigefügt. Forschungförderungseinrichtungen drängen zu konkreten Lösungen zum Verbreiten, Teilen und Wiederverwenden von Forschungsergebnissen. Berichte wie “Riding the Wave - How Europe can gain from the rising tide of scientific data” der High Level Expert Group on Scientific Data der Europäischen Kommission zeichnen eine Vision, bei der die Herausforderungen einer Diversität an Datenformaten, Menschen und Gemeinschaften durch die Anwendung technischer, semantischer und sozialer Eigenschaften der Interoperabilität vermieden werden. Diese Forschung adressiert derartige Herausforderungen aus einer technischer Perspektive. Fokus dieser Arbeit ist die Exploration eines neuartigen Ansatzes zur Unterstützung der Kuration (Sichtung und Korrektur) von Forschungsdaten mittels der Entwicklung einer Methodologie und mittels der Definition eines automatischen Datenkurationsprozesses in welchem Daten auf einfache Weise annotiert werden können. Ein Beitrag besteht in einem formalen Modell (COSI), welches die Integration großer Mengen an Metadaten erlaubt, welche als logische Konzepte behandelt werden können anstatt nur als Literale. Diese Konzepte werden in einer Ontologie definiert, welche, unter anderem, Inferenzen und Schlussfolgerungen ermöglicht. Der zweite Beitrag dieser Arbeit besteht in einer pragmatischen Lösung die es erlaubt, Metadaten on-the-fly zu annotieren. / Computational and information technology is one of the biggest advancement of the last century, a revolution that is influencing the way we approach social and technical problems in our day to day life. While these technologies have already influenced the research activity per sé, it is to be expected that these innovations will significantly influence the publishing and sharing of scientific results as well. So far, scientific publications have relied on limited result data attached inline in research paper publications. Establishments supporting research are pushing for concrete solutions that allow dissemination, share and reuse of research results. Reports such as “Riding the Wave - How Europe can gain from the rising tide of scientific data” of the High Level Expert Group on Scientific Data, European Commission (High Level Expert Group on Scientific Data, October 2010) presents a vision where the challenges of diverse data formats, people and communities are avoided due to the application of technical, semantic and social features of interoperability. This research is an effort to address similar concerns from a technical perspective. Focus of this research is the exploration of a novel approach on supporting research data curation by developing a method and defining an automated data curation process where data can be easily annotated. As a contribution, this work offers a formal model (COSI) that allows integration of plentiful metadata that can be treated as logic concepts and not merely as literals. These concepts are defined in an ontology that allows among other actions, inference and reasoning operations. The second contribution of this work is associated to a pragmatic solution that facilitates annotation of metadata on the fly. This solution is referred as sheer curation and shows how data can be annotated (based on COSI) and published while investigations are executed.

<p dir="ltr">We propose a fully online procedure to conduct statistical inference with adaptively collected data. The low-rank structure of the model parameter and the adaptivity nature of the data collection process make this task challenging: standard low-rank estimators are biased and cannot be obtained in a sequential manner while existing inference approaches in sequential decision-making algorithms fail to account for the low-rankness and are also biased. To tackle the challenges previously outlined, we first develop an online low-rank estimation process employing Stochastic Gradient Descent with noisy observations. Subsequently, to facilitate statistical inference using the online low-rank estimator, we introduced a novel online debiasing technique designed to address both sources of bias simultaneously. This method yields an unbiased estimator suitable for parameter inference. Finally, we developed an inferential framework capable of establishing an online estimator for performing inference on the optimal policy value. In theory, we establish the asymptotic normality of the proposed online debiased estimators and prove the validity of the constructed confidence intervals for both inference tasks. Our inference results are built upon a newly developed low-rank stochastic gradient descent estimator and its non-asymptotic convergence result, which is also of independent interest.</p>

Background: In the treatment of diabetes mellitus, the challenge is to integrate adequate self-management into clinical care. Customization including goal setting, monitoring, and feedback could be achieved through digitization. Digital linking between different devices could simplify and promote self-management. The aim of this study is to evaluate the outcome of diabetes treatment assisted by a digital health application compared with standard diabetes therapy. - Methods: The DAVOS study is a 6-month-period prospective, multicentric, randomized controlled trial. In total, 154 diabetes patients (age ≥18; treated with insulin) will be recruited and randomized into control group or intervention group. Both groups will receive standard diabetes care. The intervention group will additionally use a diabetes app. HbA1c value will be monitored on three separate defined visits. Primary endpoint is the overall reduction of HbA1c value. Secondary endpoints (eg, usability of the app) will be determined through patient-reported outcome questionnaires. - Discussion: Through enhanced interaction of health care professionals, providers of the app, and patients, the study aims to demonstrate improvement in the self-management of diabetes. As part of the closure management, all patients will be invited to use the examined application after completion of the study. The DAVOS study will be conducted in accordance with the valid version of the present study protocol and the internationally recognized International Conference on Harmonization–Good Clinical Practice (ICH-GCP) Guidelines. Special attention will be paid to European, national, and regional requirements for the approval, provision, and use of medical devices. The study was registered in the German Register of Clinical Trials (DRKS) with number DRKS00025996.