Efficient Forecasting for Hierarchical Time Series

Forecasting is used as the basis for business planning in many application areas such as energy, sales and traffic management. Time series data used in these areas is often hierarchically organized and thus, aggregated along the hierarchy levels based on their dimensional features. Calculating forecasts in these environments is very time consuming, due to ensuring forecasting consistency between hierarchy levels. To increase the forecasting efficiency for hierarchically organized time series, we introduce a novel forecasting approach that takes advantage of the hierarchical organization. There, we reuse the forecast models maintained on the lowest level of the hierarchy to almost instantly create already estimated forecast models on higher hierarchical levels. In addition, we define a hierarchical communication framework, increasing the communication flexibility and efficiency. Our experiments show significant runtime improvements for creating a forecast model at higher hierarchical levels, while still providing a very high accuracy

Creación de datos multilingües para diversos enfoques basados en corpus en el ámbito de la traducción y la interpretación

Accordingly, this research work aims at exploiting and developing new technologies and methods to better ascertain not only translators’ and interpreters’ needs, but also professionals’ and ordinary people’s on their daily tasks, such as corpora and terminology compilation and management. The main topics covered by this work relate to Computational Linguistics (CL), Natural Language Processing (NLP), Machine Translation (MT), Comparable Corpora, Distributional Similarity Measures (DSM), Terminology Extraction Tools (TET) and Terminology Management Tools (TMT). In particular, this work examines three main questions: 1) Is it possible to create a simpler and user-friendly comparable corpora compilation tool? 2) How to identify the most suitable TMT and TET for a given translation or interpreting task? 3) How to automatically assess and measure the internal degree of relatedness in comparable corpora? This work is composed of thirteen peer-reviewed scientific publications, which are included in Appendix A, while the methodology used and the results obtained in these studies are summarised in the main body of this document. Fecha de lectura de Tesis Doctoral: 22 de noviembre 2019Corpora are playing an increasingly important role in our multilingual society. High-quality parallel corpora are a preferred resource in the language engineering and the linguistics communities. Nevertheless, the lack of sufficient and up-to-date parallel corpora, especially for narrow domains and poorly-resourced languages is currently one of the major obstacles to further advancement across various areas like translation, language learning and, automatic and assisted translation. An alternative is the use of comparable corpora, which are easier and faster to compile. Corpora, in general, are extremely important for tasks like translation, extraction, inter-linguistic comparisons and discoveries or even to lexicographical resources. Its objectivity, reusability, multiplicity and applicability of uses, easy handling and quick access to large volume of data are just an example of their advantages over other types of limited resources like thesauri or dictionaries. By a way of example, new terms are coined on a daily basis and dictionaries cannot keep up with the rate of emergence of new terms

Tree Growth Dynamics, Fire History, and Fire-Climate Relationships in Pine Rocklands of the Florida Keys, U.S.A.

Pine rocklands are globally endangered, fire-maintained communities currently restricted to small habitat areas in southern Florida, Cuba, and the Bahamas. The purpose of this dissertation research was to identify the long-term ecological disturbance regimes and climatic trends responsible for the persistence of pine rocklands, and examine how human-induced changes during the 20th century contributed to decline of these communities. This research applied techniques of dendrochronology in extreme southern Florida, in a subtropical region where tree‐ring science has never been applied, to increase the understanding of how anthropogenic and natural disturbance events have decreased the spatial distribution of South Florida slash pine (Pinus elliottii Engelm. var. densa Little and Dorman; hereafter slash pine), the foundation species of pine rocklands. To investigate the complex dynamics of declining pine rockland communities, I analyzed (1) the dendrochronological potential and climate response of slash pine, (2) the intra-annual ring formation characteristics and relationships to monthly climatic conditions, (3) the influence of historical fire regimes and varied fire management practices since the 1950s on the structure of slash pine savannas on adjacent islands in the Lower Florida Keys, and (4) the control of global-scale oceanic/atmospheric oscillations on historical wildfire occurrence. The analyses presented here demonstrate that slash pine forms anatomically distinct, annual growth rings with the consistent year-to-year variability necessary for rigorous dendrochronological studies. Annual radial growth of slash pine is primarily influenced by water availability during the growing season; however intra-annual cellular growth is driven by daily insolation. In the Lower Florida Keys, the growing season of slash pine occurs between February and November, with trees experiencing dormancy between November and January. Reconstructions of fire history and savanna structure revealed that, over the past 150 years, frequent fires occurring every ca. 6 years promoted pine recruitment and ensured the persistence of pine rockland habitat. However, the recent lack of fire in some areas could result in the loss of pine rockland habitat, as pine savannas are currently succeeding to tropical hardwood hammock. Over the past several centuries, interacting effects of two Pacific climatic forcing mechanisms (El Niño-Southern Oscillation, Pacific Decadal Oscillation) drove wildfire occurrence in the Lower Florida Keys

The state of climate change in AK: agency and networking of the governmental kind

Master's Project (M.S.) University of Alaska Fairbanks, 2017Alaska coastal villages are faced with relocating their communities' due to erosion, flooding, permafrost thaw and other slow-moving natural hazards that risk their safety. State and federal efforts to relocate, specifically, indigenous communities are thwarted by insufficient policy and restrictive agency missions, and coordination of actors, authority, responsibility, accountability, access and funding is lacking between levels of government, further complicating action. Networks are created to view mission statements from tribal, state, and federal agencies, nonprofits and private industry were coded to analyze coordination between key actors involved in climate governance and planned relocation. State and federal climate and disaster response policies are reviewed to identify areas to strengthen climate governance that is inclusive of indigenous communities' rights, culture, traditions and livelihoods

Reengineering and development of IoT Systems for Home Automation

BEng Thesis, Instituto Superior de Engenharia do Porto.With the increasing adoption of technology in today’s houses, electricity is at an all-time high demand. In fact, given the plethora of vital electricity-powered appliances used every day, such as refrigerators, washing machines, and so forth, it has been proven difficult to even handle all devices’ electric consumption. To reduce consumption costs and turn it into a more manageable process, the concept of flex-offers was created. A flex-offer is built around scheduling energy usage in conjunction with the prices of electricity, as provided by an energy market. More specifically, a flex-offer is an energy consumption offer containing the user’s energy consumption flexibility, which is sent to an entity called the Aggregator, who aggregates together flex-offers from multiple parties, bargains with the energy market, and responds to each flex-offer with a schedule that meets the lowest prices for consumption, while still satisfying the users’ needs. By using flex-offers on a house’s equipment, the idea of FlexHousing was born. The aspired goal of the CISTER Research Center’s FlexHousing project is to deliver a platform where users can register their smart appliances, regardless of its brand and distributor, set up preferences for the devices’ usage, and let the system manage the energy consumption and device activation schedules based on the energy market prices. A previous project had already built a prototype of the FlexHousing system. Nevertheless, the original platform had many limitations and lacked maturity from a software engineering point of view, and the goal of this internship is to apply a reengineering process on the FlexHousing project, while also adding new features to it. Thus, the project’s domain model, its database, and class structures were altered to satisfy the new requirements. Furthermore, its web platform was rebuilt from the ground up. Also, a new interface was developed to facilitate support for devices of different brands. As a proof of concept for the benefits provided by this new interface, a connection with a new device (Sonoff Pow) was also established. Moreover, a new functionality was developed to identify a device’s type of appliance based on its energy consumption, in other words, to specify if a device is, for instance, a refrigerator or not. Finally, another new feature was added in which, based on a device’s type and its energy consumption pattern, the flex-offer creation is automated, minimizing user input. As planned, the FlexHousing platform now supports multiple types of devices, and has a software interface to support more types in the future with minimal effort. The flex-offer creation process has been simplified and is now partially automated. Finally, the web platform’s UI has been updated, becoming more intuitive and appealing to the user.info:eu-repo/semantics/publishedVersio

A Time-Series Compression Technique and its Application to the Smart Grid

Time-series data is increasingly collected in many domains. One example is the smart electricity infrastructure, which generates huge volumes of such data from sources such as smart electricity meters. Although today this data is used for visualization and billing in mostly 15-min resolution, its original temporal resolution frequently is more fine-grained, e.g., seconds. This is useful for various analytical applications such as short-term forecasting, disaggregation and visualization. However, transmitting and storing huge amounts of such fine-grained data is prohibitively expensive in terms of storage space in many cases. In this article, we present a compression technique based on piecewise regression and two methods which describe the performance of the compression. Although our technique is a general approach for time-series compression, smart grids serve as our running example and as our evaluation scenario. Depending on the data and the use-case scenario, the technique compresses data by ratios of up to factor 5,000 while maintaining its usefulness for analytics. The proposed technique has outperformed related work and has been applied to three real-world energy datasets in different scenarios. Finally, we show that the proposed compression technique can be implemented in a state-of-the-art database management system