Environmental complaint insights through text mining based on the driver, pressure, state, impact, and response (DPSIR) framework. Evidence from an Italian environmental agency

Individuals, local communities, environmental associations, private organizations, and public representatives and bodies may all be aggrieved by environmental problems concerning poor air quality, illegal waste disposal, water contamination, and general pollution. Environmental complaints represent the expressions of dissatisfaction with these issues. As the time-consuming of managing a large number of complaints, text mining may be useful for automatically extracting information on stakeholder priorities and concerns. The paper used text mining and semantic network analysis to crawl relevant keywords about environmental complaints from two online complaint submission systems: online claim submission system of Regional Agency for Prevention, Environment and Energy (Arpae) (“Contact Arpae”); and Arpae's internal platform for environmental pollution (“Environmental incident reporting portal”) in the Emilia-Romagna Region, Italy. We evaluated the total of 2477 records and classified this information based on the claim topic (air pollution, water pollution, noise pollution, waste, odor, soil, weather-climate, sea-coast, and electromagnetic radiation) and geographical distribution. Then, this paper used natural language processing to extract keywords from the dataset, and classified keywords ranking higher in Term Frequency-Inverse Document Frequency (TF-IDF) based on the driver, pressure, state, impact, and response (DPSIR) framework. This study provided a systemic approach to understanding the interaction between people and environment in different geographical contexts and builds sustainable and healthy communities. The results showed that most complaints are from the public and associated with air pollution and odor. Factories (particularly foundries and ceramic industries) and farms are identified as the drivers of environmental issues. Citizen believed that environmental issues mainly affect human well-being. Moreover, the keywords of “odor”, “report”, “request”, “presence”, “municipality”, and “hours” were the most influential and meaningful concepts, as demonstrated by their high degree and betweenness centrality values. Keywords connecting odor (classified as impacts) and air pollution (classified as state) were the most important (such as “odor-burnt plastic” and “odor-acrid”). Complainants perceived odor annoyance as a primary environmental concern, possibly related to two main drivers: “odor-factory” and “odors-farms”. The proposed approach has several theoretical and practical implications: text mining may quickly and efficiently address citizen needs, providing the basis toward automating (even partially) the complaint process; and the DPSIR framework might support the planning and organization of information and the identification of stakeholder concerns and priorities, as well as metrics and indicators for their assessment. Therefore, integration of the DPSIR framework with the text mining of environmental complaints might generate a comprehensive environmental knowledge base as a prerequisite for a wider exploitation of analysis to support decision-making processes and environmental management activities

Complex adaptive systems based data integration : theory and applications

Data Definition Languages (DDLs) have been created and used to represent data in programming languages and in database dictionaries. This representation includes descriptions in the form of data fields and relations in the form of a hierarchy, with the common exception of relational databases where relations are flat. Network computing created an environment that enables relatively easy and inexpensive exchange of data. What followed was the creation of new DDLs claiming better support for automatic data integration. It is uncertain from the literature if any real progress has been made toward achieving an ideal state or limit condition of automatic data integration. This research asserts that difficulties in accomplishing integration are indicative of socio-cultural systems in general and are caused by some measurable attributes common in DDLs. This research’s main contributions are: (1) a theory of data integration requirements to fully support automatic data integration from autonomous heterogeneous data sources; (2) the identification of measurable related abstract attributes (Variety, Tension, and Entropy); (3) the development of tools to measure them. The research uses a multi-theoretic lens to define and articulate these attributes and their measurements. The proposed theory is founded on the Law of Requisite Variety, Information Theory, Complex Adaptive Systems (CAS) theory, Sowa’s Meaning Preservation framework and Zipf distributions of words and meanings. Using the theory, the attributes, and their measures, this research proposes a framework for objectively evaluating the suitability of any data definition language with respect to degrees of automatic data integration. This research uses thirteen data structures constructed with various DDLs from the 1960\u27s to date. No DDL examined (and therefore no DDL similar to those examined) is designed to satisfy the law of requisite variety. No DDL examined is designed to support CAS evolutionary processes that could result in fully automated integration of heterogeneous data sources. There is no significant difference in measures of Variety, Tension, and Entropy among DDLs investigated in this research. A direction to overcome the common limitations discovered in this research is suggested and tested by proposing GlossoMote, a theoretical mathematically sound description language that satisfies the data integration theory requirements. The DDL, named GlossoMote, is not merely a new syntax, it is a drastic departure from existing DDL constructs. The feasibility of the approach is demonstrated with a small scale experiment and evaluated using the proposed assessment framework and other means. The promising results require additional research to evaluate GlossoMote’s approach commercial use potential

Bibliographic Control in the Digital Ecosystem

With the contributions of international experts, the book aims to explore the new boundaries of universal bibliographic control. Bibliographic control is radically changing because the bibliographic universe is radically changing: resources, agents, technologies, standards and practices. Among the main topics addressed: library cooperation networks; legal deposit; national bibliographies; new tools and standards (IFLA LRM, RDA, BIBFRAME); authority control and new alliances (Wikidata, Wikibase, Identifiers); new ways of indexing resources (artificial intelligence); institutional repositories; new book supply chain; “discoverability” in the IIIF digital ecosystem; role of thesauri and ontologies in the digital ecosystem; bibliographic control and search engines

Baltic Journal of English Language, Literature and Culture, Vol.10

Kontorslokaler nyttjas generellt cirka 2500 av årets 8760 timmar. Ett vanligt problem med kontorslokaler är det termiska klimatet, antingen är det för varmt, för kallt, eller så drar det. Höga temperaturer, över ca 26°C, bidrar till trötthet, nedsatt koncentration och gör att luften känns mindre fräsch. Stora variationen av lasten mellan dag och nattetid kan också resultera i att lokalerna överventileras under nattetid och underventileras under dagtid. Syftet med examensarbetet var att undersöka och jämföra Ecoclimes komforttaks lösning med andra olika värme och kylsystem i kontorslokaler. Att undersöka vilka eventuella fördelar Ecoclimes komforttak har gällande komfort, kyla, ventilation och ur energisynpunkt. Simuleringsprogrammet IDA ICE har använts för att simulera komforten och rumstemperaturer för ett kontor och ett konferensrum i en byggnad placerad i centrala Umeå. Resultaten från simuleringar indikerar att Ecoclimes komforttak, sänker den operativa temperaturen och höjer komforten med en mindre andel missnöjda i sitt rum jämfört med andra system trots samma rumstemperatur. För att bedömma andelen missnöjda i ett rum har komfortindexet PMV(Predicted mean vote) och PPD(Predicted percentage dissatisfied) använts. Den höga passiva effekten bidrar också till mindre energianvändning av ventilationsfläktar ifall ett VAV-system med rumstempertaurreglering används. Vidare har en känslighetsanalys genomförts på komforttaken där det undersöks hur kyleffekten påverkar kyltider, temperatur och komfort. Känslighetsanalysen visar att en ökning eller minskning av kyleffekten med 10% påverkar resultaten mest under en mycket varm dag jämfört med en normalvarm. Skillnaden i komfort var dock liten, endast 0,2 procentenheter från grundfallet

EG-ICE 2021 Workshop on Intelligent Computing in Engineering

The 28th EG-ICE International Workshop 2021 brings together international experts working at the interface between advanced computing and modern engineering challenges. Many engineering tasks require open-world resolutions to support multi-actor collaboration, coping with approximate models, providing effective engineer-computer interaction, search in multi-dimensional solution spaces, accommodating uncertainty, including specialist domain knowledge, performing sensor-data interpretation and dealing with incomplete knowledge. While results from computer science provide much initial support for resolution, adaptation is unavoidable and most importantly, feedback from addressing engineering challenges drives fundamental computer-science research. Competence and knowledge transfer goes both ways

Building information modeling – A game changer for interoperability and a chance for digital preservation of architectural data?

Digital data associated with the architectural design-andconstruction process is an essential resource alongside -and even past- the lifecycle of the construction object it describes. Despite this, digital architectural data remains to be largely neglected in digital preservation research – and vice versa, digital preservation is so far neglected in the design-and-construction process. In the last 5 years, Building Information Modeling (BIM) has seen a growing adoption in the architecture and construction domains, marking a large step towards much needed interoperability. The open standard IFC (Industry Foundation Classes) is one way in which data is exchanged in BIM processes. This paper presents a first digital preservation based look at BIM processes, highlighting the history and adoption of the methods as well as the open file format standard IFC (Industry Foundation Classes) as one way to store and preserve BIM data

Technologies and Applications for Big Data Value

This open access book explores cutting-edge solutions and best practices for big data and data-driven AI applications for the data-driven economy. It provides the reader with a basis for understanding how technical issues can be overcome to offer real-world solutions to major industrial areas. The book starts with an introductory chapter that provides an overview of the book by positioning the following chapters in terms of their contributions to technology frameworks which are key elements of the Big Data Value Public-Private Partnership and the upcoming Partnership on AI, Data and Robotics. The remainder of the book is then arranged in two parts. The first part “Technologies and Methods” contains horizontal contributions of technologies and methods that enable data value chains to be applied in any sector. The second part “Processes and Applications” details experience reports and lessons from using big data and data-driven approaches in processes and applications. Its chapters are co-authored with industry experts and cover domains including health, law, finance, retail, manufacturing, mobility, and smart cities. Contributions emanate from the Big Data Value Public-Private Partnership and the Big Data Value Association, which have acted as the European data community's nucleus to bring together businesses with leading researchers to harness the value of data to benefit society, business, science, and industry. The book is of interest to two primary audiences, first, undergraduate and postgraduate students and researchers in various fields, including big data, data science, data engineering, and machine learning and AI. Second, practitioners and industry experts engaged in data-driven systems, software design and deployment projects who are interested in employing these advanced methods to address real-world problems