On Integrity Constraints for a Waste Management Information System

There is a waste problem in nearly every country. A model of a waste generating system and an efficient waste management information system are the first steps to control this problem. Some countries have already enacted laws which force communities and enterprises to report annually the amounts of wastes produced. For example, the German federal state, Lower Saxony, enacted such a law in 1992. This YSSP-Project deals with a case study on the development of a waste management information system for this state. The quality of the system essentially depends on the consistency of the underlying database system. Therefore, the point of view of a database designer is given. The design of the data structures and the support of integrity constraints in the underlying database system is thereby especially emphasized. The data structures are modelled using an extended entity relationship model. They are implemented with a relational database management system. In contrast to the traditional way of supporting integrity constraints in the application program, we define triggers which are implemented in the database system itself to enforce main consistency rules. In the final chapter some conclusions about further steps are given

A review of microgrid development in the United States – A decade of progress on policies, demonstrations, controls, and software tools

Microgrids have become increasingly popular in the United States. Supported by favorable federal and local policies, microgrid projects can provide greater energy stability and resilience within a project site or community. This paper reviews major federal, state, and utility-level policies driving microgrid development in the United States. Representative U.S. demonstration projects are selected and their technical characteristics and non-technical features are introduced. The paper discusses trends in the technology development of microgrid systems as well as microgrid control methods and interactions within the electricity market. Software tools for microgrid design, planning, and performance analysis are illustrated with each tool's core capability. Finally, the paper summarizes the successes and lessons learned during the recent expansion of the U.S. microgrid industry that may serve as a reference for other countries developing their own microgrid industries

Learning from AI : new trends in database technology

Recently some researchers in the areas of database data modelling and knowledge representations in artificial intelligence have recognized that they share many common goals. In this survey paper we show the relationship between database and artificial intelligence research. We show that there has been a tendency for data models to incorporate more modelling techniques developed for knowledge representations in artificial intelligence as the desire to incorporate more application oriented semantics, user friendliness, and flexibility has increased. Increasing the semantics of the representation is the key to capturing the "reality" of the database environment, increasing user friendliness, and facilitating the support of multiple, possibly conflicting, user views of the information contained in a database

Auto-generated materials database of Curie and Néel temperatures via semi-supervised relationship extraction.

Large auto-generated databases of magnetic materials properties have the potential for great utility in materials science research. This article presents an auto-generated database of 39,822 records containing chemical compounds and their associated Curie and Néel magnetic phase transition temperatures. The database was produced using natural language processing and semi-supervised quaternary relationship extraction, applied to a corpus of 68,078 chemistry and physics articles. Evaluation of the database shows an estimated overall precision of 73%. Therein, records processed with the text-mining toolkit, ChemDataExtractor, were assisted by a modified Snowball algorithm, whose original binary relationship extraction capabilities were extended to quaternary relationship extraction. Consequently, its machine learning component can now train with ≤ 500 seeds, rather than the 4,000 originally used. Data processed with the modified Snowball algorithm affords 82% precision. Database records are available in MongoDB, CSV and JSON formats which can easily be read using Python, R, Java and MatLab. This makes the database easy to query for tackling big-data materials science initiatives and provides a basis for magnetic materials discovery

PassivBIM: enhancing interoperability between BIM and low energy design software

The process of building design is currently undergoing some major changes. In an attempt to mitigate climate change, the design of more sustainable buildings is advocated by the UK government. Furthermore, standalone design methods are being replaced with the concept of Building Information Modelling (BIM). The adoption of BIM has been documented to result in many benefits, which range from time to cost savings. During the initial planning stages, building performance simulation (BPS) can be used to inform design decisions. Data can be exchanged between BIM and BPS tools using data transfer schemas such as the Industry Foundation Classes (IFC). The IFC schema lacks an energy domain, and as a result, an extension is proposed in this paper. This contains energy concepts from a BPS tool called Passive House Planning Package (PHPP). The extended schema was developed by way of an externally coupled Java tool, which facilitates the transfer of data, and informs the building design decision-making process. The process of geometry extraction has been validated with several case studies, which are based on certified Passivhaus buildings in Hannover Kronsberg, Germany and Ebbw Vale, Wales. The amount of error is acceptable, and it is mostly due to differences in the initial BIM model setup, not due to the processing of IFC files

Open-Source, Open-Architecture SoftwarePlatform for Plug-InElectric Vehicle SmartCharging in California

This interdisciplinary eXtensible Building Operating System–Vehicles project focuses on controlling plug-in electric vehicle charging at residential and small commercial settings using a novel and flexible open-source, open-architecture charge communication and control platform. The platform provides smart charging functionalities and benefits to the utility, homes, and businesses.This project investigates four important areas of vehicle-grid integration research, integrating technical as well as social and behavioral dimensions: smart charging user needs assessment, advanced load control platform development and testing, smart charging impacts, benefits to the power grid, and smart charging ratepayer benefits