ABSTRACT
Biodrying is an essential part of the mechanical–biological treatment process that minimizes moisture content and simultaneously maximizes heating value for refuse-derived fuel (RDF) production. Although the mechanical separation process operates effectively in Thailand's RDF production, high organic content levels and their degradation cause moisture contamination in RDF, producing wet RDF. Aeration is essential for an effective biodrying process, and can reduce RDF's moisture content as well as increase its heating value. To maximize the biodrying effect, aeration should be optimized based on the waste conditions. This study proposes a modified aeration-supplied configuration for wet RDF biodrying. The aeration rate was modified based on the period within the biodrying operation;the first period is from the beginning until day 2.5, and the second period is from day 2.5 to day 5. The optimal aeration supply configuration was 0.5 m3/kg/day in the first period and then 0.3 m3/kg/day until the end of the process;this configuration yielded the greatest moisture content decrease of 35% and increased the low heating value of the biodried product by 11%. The final moisture content and low heating value were 24.07% and 4787 kcal/kg, respectively. Therefore, this optimal aeration-supplied configuration could be applied to meet the moisture content and low heating value requirements of the RDF production standard for Thailand's local cement industry.
ABSTRACT
[...]they proposed a framework focusing on facilitating the information exchange and interoperability for existing buildings. [...]semantic Web technologies and standards, such as Web Ontology Language and existing AEC domain ontologies, were used to enhance and improve the proposed framework. [...]four levels of awareness were developed based on Endsley’s situation awareness model. Furthermore, they addressed the lack of an organised digital content asset dedicated to producing VR site scenarios that emerged as one of the most limiting factors for implementing BIM and VR for construction workers’ safety training. [...]a dedicated site object library was proposed to improve this critically time-consuming process.
ABSTRACT
Open government data (OGD) provide an opportunity for developing various services by disclosing information monopolized by the government to the public so that the private sector can use it. The private sector is utilizing this to improve the work efficiency and productivity by collecting, analyzing, and reprocessing OGD for various work steps of a BIM-based design project. However, most studies on OGD focus on the functionality and usability of data portals and the factors for evaluating the data itself such as openness, accountability, and transparency. This study aims to provide an evaluation framework for OGD for the AEC industry to assess the data utilization environment in order to improve the productivity of BIM-based projects. Several OGD principles found within related literature are discussed, and from them we extract evaluation framework levels. Then, we validate the proposed framework by applying it to a case of developing a BIM-based design support system using OGD datasets. This research concludes by suggesting that to effectively utilize OGD in the construction industry, the private sector should simply view data after collecting them, create an institutional environment for creating new values by reprocessing data, and build an active data utilization roadmap based on this environment.
ABSTRACT
The current COVID-19 pandemic situation and the associated restrictions have increased the amount of generated waste. It results from the necessity to wear personal protective equipment. Thus, the disposal of masks and gloves is a topical issue and requires immediate investigation. The main aims of this work are management and environmental studies of municipal solid wastes (MSW), which have been generated during the COVID-19 pandemic time. Effective waste management in relation to a circular economy is presented. A sample of refuse derived fuel (RDF) with a high content of plastics was used for the experimental and calculation studies. Pyrolysis was selected as the best thermal decomposition process for this kind of wastes. Proximate and ultimate analyses were performed for RDF and its products. Pyrolysis was carried out using a pilot-scale reactor with a continuous flow of 250 kg/h at 900 °C. Thermogravimetric analysis was applied during the pyrolysis investigation and showed that the main decomposition of RDF took place in the temperature range of 250-500 °C. The pyrolysis gas contained combustible compounds like CO (19.8%), H2 (13.2%), CH4 (18.9%) and C2H4 (7.1%), giving a high calorific value - 24.4 MJ/m3. The experimental results were implemented for numerical calculations. Chemkin-Pro software was applied to predict the chemical composition of the pyrolysis gas. The performed computer simulations demonstrated very good agreement with the results obtained during the experiments. They also indicated that there is a strong relationship between the chemical composition of the pyrolysis gas, the process temperature and residence time in the reactor.
ABSTRACT
COVID-19 is one of the dangerous viruses that appears in 2020. The virus has gained popularity with its massive spread across the countries. The number of casualties has increased dramatically, which led many countries to declare a state of emergency as a result of the outbreak of this epidemic and their inability to control it. Several studies and researches have emerged to shed light on the mechanism of the virus and ways to prevent it, making it easier to control in the future. The World Health Organization (WHO) has begun to publish detailed numbers of injuries, deaths, and recovery cases and has given many advices, including the imposition of a total and partial curfew in many areas in addition to emphasizing the principle of social divergence in order to prevent the rapid spread of the virus among groups of society. The main goal of this paper is to design a system that used genetic algorithms (GAs) and the principles of linked open data (LOD) for improving the immunity system by enhancing social divergence. The system starts using GA for the purpose of finding the characteristics that must be present in a person who is dangerous to society in order to get away from him as much as possible. After taking these features, the system will take the values of these features and add it to the features for all persons in order to check it in the future and give alarm to all their friends or people around them. The RDF (Resource Description Framework) is a standard model for data interchange on the Web. The main idea for using RDF in this paper is finding a proper representation for user personal file and give the flexibility to connect many personal files in order to find a deep information and can reach an unknown person from known person using the FOAF (Friend Of A Friend) and vCard (virtual card) as a standard for vocabularies. The system takes the Statistics from the WHO which show the total infected cases in all countries arranged in decreasing order. The system gives a good result for analyzing the COVID-19 virus information and detecting the infected (possible infected) person and send warning to all nearest people and his friend and family, because sometimes the person has no coronavirus symptoms but he is infected so we need a technique for detecting that virus and take a proper action as soon as possible. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
Information related to the COVID-19 pandemic ranges from biological to bibliographic, from geographical to genetic and beyond. The structure of the raw data is highly complex, so converting it to meaningful insight requires data curation, integration, extraction and visualization, the global crowdsourcing of which provides both additional challenges and opportunities. Wikidata is an interdisciplinary, multilingual, open collaborative knowledge base of more than 90 million entities connected by well over a billion relationships. It acts as a web-scale platform for broader computer-supported cooperative work and linked open data, since it can be written to and queried in multiple ways in near real time by specialists, automated tools and the public. The main query language, SPARQL, is a semantic language used to retrieve and process information from databases saved in Resource Description Framework (RDF) format. Here, we introduce four aspects of Wikidata that enable it to serve as a knowledge base for general information on the COVID-19 pandemic: its flexible data model, its multilingual features, its alignment to multiple external databases, and its multidisciplinary organization. The rich knowledge graph created for COVID-19 in Wikidata can be visualized, explored, and analyzed for purposes like decision support as well as educational and scholarly research.