GPfit: An R package for Gaussian Process Model Fitting using a New Optimization Algorithm

Gaussian process (GP) models are commonly used statistical metamodels for emulating expensive computer simulators. Fitting a GP model can be numerically unstable if any pair of design points in the input space are close together. Ranjan, Haynes, and Karsten (2011) proposed a computationally stable approach for fitting GP models to deterministic computer simulators. They used a genetic algorithm based approach that is robust but computationally intensive for maximizing the likelihood. This paper implements a slightly modified version of the model proposed by Ranjan et al. (2011), as the new R package GPfit. A novel parameterization of the spatial correlation function and a new multi-start gradient based optimization algorithm yield optimization that is robust and typically faster than the genetic algorithm based approach. We present two examples with R codes to illustrate the usage of the main functions in GPfit. Several test functions are used for performance comparison with a popular R package mlegp. GPfit is a free software and distributed under the general public license, as part of the R software project (R Development Core Team 2012).Comment: 20 pages, 17 image

GPfit: An R Package for Fitting a Gaussian Process Model to Deterministic Simulator Outputs

Gaussian process (GP) models are commonly used statistical metamodels for emulating expensive computer simulators. Fitting a GP model can be numerically unstable if any pair of design points in the input space are close together. Ranjan, Haynes, and Karsten (2011) proposed a computationally stable approach for fitting GP models to deterministic computer simulators. They used a genetic algorithm based approach that is robust but computationally intensive for maximizing the likelihood. This paper implements a slightly modified version ofthe model proposed by Ranjan et al. (2011 ) in the R package GPfit. A novel parameterization of the spatial correlation function and a clustering based multi-start gradient based optimization algorithm yield robust optimization that is typically faster than the genetic algorithm based approach. We present two examples with R codes to illustrate the usage of the main functions in GPfit . Several test functions are used for performance comparison with the popular R package mlegp . We also use GPfit for a real application, i.e., for emulating the tidal kinetic energy model for the Bay of Fundy, Nova Scotia, Canada. GPfit is free software and distributed under the General Public License and available from the Comprehensive R Archive Network

Assistive technology design and development for acceptable robotics companions for ageing years

© 2013 Farshid Amirabdollahian et al., licensee Versita Sp. z o. o. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivs license, which means that the text may be used for non-commercial purposes, provided credit is given to the author.A new stream of research and development responds to changes in life expectancy across the world. It includes technologies which enhance well-being of individuals, specifically for older people. The ACCOMPANY project focuses on home companion technologies and issues surrounding technology development for assistive purposes. The project responds to some overlooked aspects of technology design, divided into multiple areas such as empathic and social human-robot interaction, robot learning and memory visualisation, and monitoring persons’ activities at home. To bring these aspects together, a dedicated task is identified to ensure technological integration of these multiple approaches on an existing robotic platform, Care-O-Bot®3 in the context of a smart-home environment utilising a multitude of sensor arrays. Formative and summative evaluation cycles are then used to assess the emerging prototype towards identifying acceptable behaviours and roles for the robot, for example role as a butler or a trainer, while also comparing user requirements to achieved progress. In a novel approach, the project considers ethical concerns and by highlighting principles such as autonomy, independence, enablement, safety and privacy, it embarks on providing a discussion medium where user views on these principles and the existing tension between some of these principles, for example tension between privacy and autonomy over safety, can be captured and considered in design cycles and throughout project developmentsPeer reviewe

SlicerAstro: a 3-D interactive visual analytics tool for HI data

SKA precursors are capable of detecting hundreds of galaxies in HI in a single 12 hours pointing. In deeper surveys one will probe more easily faint HI structures, typically located in the vicinity of galaxies, such as tails, filaments, and extraplanar gas. The importance of interactive visualization has proven to be fundamental for the exploration of such data as it helps users to receive immediate feedback when manipulating the data. We have developed SlicerAstro, a 3-D interactive viewer with new analysis capabilities, based on traditional 2-D input/output hardware. These capabilities enhance the data inspection, allowing faster analysis of complex sources than with traditional tools. SlicerAstro is an open-source extension of 3DSlicer, a multi-platform open source software package for visualization and medical image processing. We demonstrate the capabilities of the current stable binary release of SlicerAstro, which offers the following features: i) handling of FITS files and astronomical coordinate systems; ii) coupled 2-D/3-D visualization; iii) interactive filtering; iv) interactive 3-D masking; v) and interactive 3-D modeling. In addition, SlicerAstro has been designed with a strong, stable and modular C++ core, and its classes are also accessible via Python scripting, allowing great flexibility for user-customized visualization and analysis tasks.Comment: 18 pages, 11 figures, Accepted by Astronomy and Computing. SlicerAstro link: https://github.com/Punzo/SlicerAstro/wiki#get-slicerastr

Failure mode prediction and energy forecasting of PV plants to assist dynamic maintenance tasks by ANN based models

In the field of renewable energy, reliability analysis techniques combining the operating time of the system with the observation of operational and environmental conditions, are gaining importance over time. In this paper, reliability models are adapted to incorporate monitoring data on operating assets, as well as information on their environmental conditions, in their calculations. To that end, a logical decision tool based on two artificial neural networks models is presented. This tool allows updating assets reliability analysis according to changes in operational and/or environmental conditions. The proposed tool could easily be automated within a supervisory control and data acquisition system, where reference values and corresponding warnings and alarms could be now dynamically generated using the tool. Thanks to this capability, on-line diagnosis and/or potential asset degradation prediction can be certainly improved. Reliability models in the tool presented are developed according to the available amount of failure data and are used for early detection of degradation in energy production due to power inverter and solar trackers functional failures. Another capability of the tool presented in the paper is to assess the economic risk associated with the system under existing conditions and for a certain period of time. This information can then also be used to trigger preventive maintenance activities

SYSTEMY POMIARU ENERGII PRODUKOWANEJ PRZEZ SYSTEM FOTOWOLTAICZNY I POBIERANEJ PRZEZ BUDYNEK LUBELSKIEGO PARKU NAUKOWO-TECHNOLOGICZNEGO

The article contains a description of innovative systems for measuring the energy produced by the photovoltaic system and consumed by the building. The photovoltaic system consists of two micro-installations supplying two sectors of the Lublin Science and Technology Park. An internet platform for monitoring photovoltaic plant operation was presented. The power generated and the amount of electricity produced were assessed. Then, an innovative system for monitoring, analyzing the consumption and production as well as the efficient use of electricity in individual parts of the building was described.W artykule zawarto opis innowacyjnych systemów do pomiaru energii produkowanej przez system fotowoltaiczny oraz pobieranej przez budynek. System fotowoltaiczny składa się z dwóch mikroinstalacji zasilających dwa segmenty Lubelskiego Parku Naukowo-Technologicznego. Przedstawiono platformę internetową do monitoringu pracy systemu fotowoltaicznego. Dokonano oceny generowanej mocy oraz ilości produkowanej energii elektrycznej. Następnie opisano innowacyjny system do monitoringu, analizy zużycia i produkcji oraz efektywnego wykorzystywania energii elektrycznej w poszczególnych segmentach budynku

Understanding potential users of energy community information system:a thematic analysis

Abstract. The continuing global growth of energy consumers, the war in Europe, and climate change are the driving factors for energy revolution. One solution to this concerning issue has been the transformation of energy consumers to become energy producers. Prosumers can be grouped to establish energy communities. Prosumers, energy communities, and other distributed energy resources (DERs) are possible sustainable energy resources that can be connected to the smart grid. The literature review of existing research about smart grids, distributed energy resources, and energy communities, is conducted to gain a better understanding of the complex system and its stakeholders. The Second part of the literature review follows the behaviour of the potential smart grid users and its recent studies. The research questions focus on understanding energy prosumer’s perspectives on information system usage in order to discover the advantages and disadvantages of potential information system within an energy community context. The data were gathered from semi-structured interviews with people who voluntarily replied to application forms which were distributed prior to this study. Qualitative research methods were chosen to be used. A thematic analysis was conducted and as a result a thematic map in which two main themes, 15 sub-themes, and 25 codes were identified. It was discovered that positive user experience, desired functionalities, monitoring, economic benefits, user interface, beneficial information, and platform availability were the driving factors seen as an advantage of the potential information system. On the other hand, data leaks, undesired functionalities, energy community problems, and negative user experience were seen as disadvantages of the information system. This study contributes to the field of sustainable human-computer interaction and the findings of this thesis can be used as a foundation for future research and to design and develop the smart grids from the prosumer’s perspective. Due to several requests from participants, the text of the thesis has been written with accessibility in mind, so that the text does not require special expertise in the field of sustainable human-computer interaction