scholarly journals An Approach of Automatic SPARQL Generation for BIM Data Extraction

2020 ◽  
Vol 10 (24) ◽  
pp. 8794
Author(s):  
Dongming Guo ◽  
Erling Onstein ◽  
Angela Daniela La Rosa
Keyword(s):  
Large Scale ◽  
Query Language ◽  
Data Extraction ◽  
Building Design ◽  
Query Languages ◽  
Design Data ◽  
Simple Method ◽  
Building Information ◽  
Essential Knowledge ◽  
Multiple Query

Generally, building information modelling (BIM) models contain multiple dimensions of building information, including building design data, construction information, and maintenance-related contents, which are related with different engineering stakeholders. Efficient extraction of BIM data is a necessary and vital step for various data analyses and applications, especially in large-scale BIM projects. In order to extract BIM data, multiple query languages have been developed. However, the use of these query languages for data extraction usually requires that engineers have good programming skills, flexibly master query language(s), and fully understand the Industry Foundation Classes (IFC) express schema or the ontology expression of the IFC schema (ifcOWL). These limitations have virtually increased the difficulties of using query language(s) and raised the requirements on engineers’ essential knowledge reserves in data extraction. In this paper, we develop a simple method for automatic SPARQL (SPARQL Protocol and RDF Query Language) query generation to implement effective data extraction. Based on the users’ data requirements, we match users’ requirements with ifcOWL ontology concepts or instances, search the connected relationships among query keywords based on semantic BIM data, and generate the user-desired SPARQL query. We demonstrate through several case studies that our approach is effective and the generated SPARQL queries are accurate.

scholarly journals Building Information Modeling-Based Building Energy Modeling: Investigation of Interoperability and Simulation Results

2020 ◽  
Vol 6 ◽  
Author(s):  
Mohamed H. Elnabawi
Keyword(s):  
Large Scale ◽  
Building Information Modeling ◽  
Data Transfer ◽  
Building Design ◽  
Building Energy ◽  
Energy Modeling ◽  
Low Energy ◽  
Information Modeling ◽  
Building Energy Modeling ◽  
Building Information

There is increasing need to apply building information modeling (BIM) to low energy buildings, this includes building energy modeling (BEM). If a building energy model can be flawlessly generated from a BIM model, the energy simulation process can be better integrated within the design, can be more competent, and timesaving. However, concerns about both the reliability and integrity of the data transfer process and the interoperability between the BIM and BEM prevent any implementation of BIM-based energy modeling on a large scale. This study addresses the accuracy and integrity of BIM-based energy modeling by investigating how well Autodesk's Revit (BIM), in conjunction with two of the most used energy modeling programs (BEM) known as DesignBuilder and Virtual Environment (IES-ve), were integrated in terms of interoperability, including location and weather files, geometry, construction and materials, thermal zones, occupancy operating schedules, and HVAC systems. All misrepresented data during the interoperability process were identified, followed by benchmarking between the BIM-based energy modeling simulation outcomes and the actual energy consumption of the case study, to assess the reliability of the process. The investigation has revealed a number of interoperability issues regarding the BIM data input and BEM data interpretation. Overall, BIM-based energy modeling proved to be a promising tool for sustainable and low energy building design, however, the BIM to BEM process is a non-standardized method of producing building energy models as it varies from one modeler to another, and the BIM to BEM process. All these might slow down any possible application for the process and might cause some uncertainties for the professionals in the field applying it.

scholarly journals A Large-Scale and Serverless Computational Approach for Improving Quality of NGS Data Supporting Big Multi-Omics Data Analyses

2021 ◽  
Vol 12 ◽  
Author(s):  
Dariusz Mrozek ◽  
Krzysztof Stępień ◽  
Piotr Grzesik ◽  
Bożena Małysiak-Mrozek
Keyword(s):  
Large Scale ◽  
Query Language ◽  
Data Extraction ◽  
Quality Data ◽  
Omics Data ◽  
Rna Sequences ◽  
Data Analyses ◽  
Cleaning Methods ◽  
Ngs Data

Various types of analyses performed over multi-omics data are driven today by next-generation sequencing (NGS) techniques that produce large volumes of DNA/RNA sequences. Although many tools allow for parallel processing of NGS data in a Big Data distributed environment, they do not facilitate the improvement of the quality of NGS data for a large scale in a simple declarative manner. Meanwhile, large sequencing projects and routine DNA/RNA sequencing associated with molecular profiling of diseases for personalized treatment require both good quality data and appropriate infrastructure for efficient storing and processing of the data. To solve the problems, we adapt the concept of Data Lake for storing and processing big NGS data. We also propose a dedicated library that allows cleaning the DNA/RNA sequences obtained with single-read and paired-end sequencing techniques. To accommodate the growth of NGS data, our solution is largely scalable on the Cloud and may rapidly and flexibly adjust to the amount of data that should be processed. Moreover, to simplify the utilization of the data cleaning methods and implementation of other phases of data analysis workflows, our library extends the declarative U-SQL query language providing a set of capabilities for data extraction, processing, and storing. The results of our experiments prove that the whole solution supports requirements for ample storage and highly parallel, scalable processing that accompanies NGS-based multi-omics data analyses.

PROTOTIPE APLIKASI PENYIRAMAN TANAMAN MENGGUNAKAN SENSOR KELEMBABAN TANAH BERBASIS MICRO CONTOLLER ATMEGA 328

2019 ◽  
Vol 5 (1) ◽  
pp. 97-106
Author(s):  
Rudi Budi Agung ◽  
Muhammad Nur ◽  
Didi Sukayadi
Keyword(s):  
Soil Moisture ◽  
Growth And Development ◽  
Large Scale ◽  
Simple Method ◽  
Moisture Sensor ◽  
Sensor Development ◽  
Soil Moisture Sensor ◽  
Application Systems ◽  
Harvesting Systems ◽  
Working Principle

The Indonesian country which is famous for its tropical climate has now experienced a shift in two seasons (dry season and rainy season). This has an impact on cropping and harvesting systems among farmers. In large scale this is very influential considering that farmers in Indonesia are stilldependent on rainfall which results in soil moisture. Some types of plants that are very dependent on soil moisture will greatly require rainfall or water for growth and development. Through this research, researchers tried to make a prototype application for watering plants using ATMEGA328 microcontroller based soil moisture sensor. Development of application systems using the prototype method as a simple method which is the first step and can be developed again for large scale. The working principle of this prototype is simply that when soil moisture reaches a certainthreshold (above 56%) then the system will work by activating the watering system, if it is below 56% the system does not work or in other words soil moisture is considered sufficient for certain plant needs.

A Novel Real-Time Thermal Analysis and Layer Time Control Framework for Large Scale Additive Manufacturing

2020 ◽  
Author(s):  
Sepehr Fathizadan ◽  
Feng Ju ◽  
Kyle Rowe ◽  
Alex Fiechter ◽  
Nils Hofmann
Keyword(s):  
Additive Manufacturing ◽  
Surface Temperature ◽  
Real Time ◽  
Large Scale ◽  
Production Efficiency ◽  
Control Method ◽  
Data Extraction ◽  
Critical Role ◽  
Imaging Data ◽  
Time Data

Abstract Production efficiency and product quality need to be addressed simultaneously to ensure the reliability of large scale additive manufacturing. Specifically, print surface temperature plays a critical role in determining the quality characteristics of the product. Moreover, heat transfer via conduction as a result of spatial correlation between locations on the surface of large and complex geometries necessitates the employment of more robust methodologies to extract and monitor the data. In this paper, we propose a framework for real-time data extraction from thermal images as well as a novel method for controlling layer time during the printing process. A FLIR™ thermal camera captures and stores the stream of images from the print surface temperature while the Thermwood Large Scale Additive Manufacturing (LSAM™) machine is printing components. A set of digital image processing tasks were performed to extract the thermal data. Separate regression models based on real-time thermal imaging data are built on each location on the surface to predict the associated temperatures. Subsequently, a control method is proposed to find the best time for printing the next layer given the predictions. Finally, several scenarios based on the cooling dynamics of surface structure were defined and analyzed, and the results were compared to the current fixed layer time policy. It was concluded that the proposed method can significantly increase the efficiency by reducing the overall printing time while preserving the quality.

Assessing design buildability through virtual reality from the perspective of construction students

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Don Amila Sajeevan Samarasinghe ◽  
Imelda Saran Piri
Keyword(s):  
Virtual Reality ◽  
Tertiary Education ◽  
Building Design ◽  
Assessment Process ◽  
Online Questionnaire ◽  
Sustainable Building ◽  
Content Type ◽  
Building Information ◽  
2D Drawing ◽  
The Impact

PurposeThe purpose of this paper is to evaluate the impact of visual models on the ability of construction students to assess design buildability.Design/methodology/approachThe study engaged 45 construction students from one selected tertiary education institute in New Zealand. The data collection process involved meeting the students face-to-face and demonstrating the VR model to them, after which the students completed an online questionnaire and assessed design buildability using both 2D drawing and virtual reality (VR) models. To make this assessment, the participants considered a residential earth building modelled to promote sustainable building features. The assessment process required the participants to evaluate the design buildability of the same building design using a 2D drawing and a 3D VR model.FindingsThe study found that VR models have significant advantages for assessing design buildability. Students measured 16.80% higher average buildability with the 3D VR model compared to the 2D drawing. The participants in the evaluation felt that the visual model significantly improved the comprehensibility of complex designs, which helped identify and manage design buildability (overall, 83% of participants strongly supported this).Originality/valueThe paper showed construction digitisation such as VR, augmented reality and building information modelling is highly cooperative as it can easily be made available for online learning. Thus, the findings support construction educators use online-based VR learning to promote efficient teaching of design buildability to students.

Investigating Fast- and Slow-settling Phosphorus Fractions in Lakes using Steady-state Modeling

2021 ◽  
Author(s):  
Hamed Khorasani ◽  
Zhenduo Zhu
Keyword(s):  
Steady State ◽  
Mass Balance ◽  
Large Scale ◽  
Hydraulic Residence Time ◽  
Simple Method ◽  
Retention Models ◽  
Mass Balance Models ◽  
Limiting Nutrient ◽  
Fast Settling ◽  
P Retention

<p>Phosphorus (P) is the key and limiting nutrient in the eutrophication of freshwater resources. Modeling P retention in lakes using steady-state mass balance models (i.e. Vollenweider-type models) provides insights into the lake P management and a simple method for large-scale assessments of P in lakes. One of the basic problems in the mass balance modeling of P in lakes is the removal of P from the lake water column by settling. A fraction of the incoming P into the lake from the watershed is associated with fast-settling particles (e.g. sediment particles) that result in the removal of that fraction of P quickly at the lake entrance. However, existing models considering a constant fraction of fast-settling TP for all lakes are shown to result in overestimation of the retention of P in lakes with short hydraulic residence time. In this study, we combine a hypothesis of the fast- and slow-settling P fractions into the steady-state mass balance models of P retention in lakes. We use a large database of lakes to calibrate the model and evaluate the hypothesis. The results of this work can be used for the improvement of the prediction power of P retention models in lakes and help to better understand the processes of P cycling in lakes.</p>

scholarly journals Separation and Purification of Two Flavone Glucuronides fromErigeron multiradiatus(Lindl.) Benth with Macroporous Resins

2009 ◽  
Vol 2009 ◽  
pp. 1-8 ◽  
Author(s):  
Zhi-feng Zhang ◽  
Yuan Liu ◽  
Pei Luo ◽  
Hao Zhang
Keyword(s):  
Large Scale ◽  
Raw Materials ◽  
Sorption Isotherms ◽  
Preparative Separation ◽  
Separation And Purification ◽  
Bioactive Constituents ◽  
Simple Method ◽  
Scale Separation ◽  
Adsorption And Desorption ◽  
Macroporous Resins

Scutellarein-7-O-β-D-glucuronide (SG) and apigenin-7-O-β-D-glucuronide (AG) are two major bioactive constituents with known pharmacological effects inErigeron multiradiatus. In this study, a simple method for preparative separation of the two flavone glucuronides was established with macroporous resins. The performance and adsorption characteristics of eight macroporous resins including AB-8, HPD100, HPD450, HPD600, D100, D101, D141, and D160 have been evaluated. The results confirmed that D141 resin offered the best adsorption and desorption capacities and the highest desorption ratio for the two glucuronides among the tested resins. Sorption isotherms were constructed for D141 resin under optimal ethanol conditions and fitted well to the Freundlich and Langmuir models (R2>0.95). Dynamic adsorption and desorption tests was performed on column packed with D141 resin. After one-run treatment with D141 resin, the two-constituent content in the final product was increased from 2.14% and 1.34 % in the crude extract ofErigeron multiradiatusto 24.63% and 18.42% in the final products with the recoveries of 82.5% and 85.4%, respectively. The preparative separation of SG and AG can be easily and effectively achieved via adsorption and desorption on D141 resin, and the method developed can be referenced for large-scale separation and purification of flavone glucuronides from herbal raw materials.

scholarly journals Adopting Building Information Modeling (BIM) for the Development of Smart Buildings: A Review of Enabling Applications and Challenges

2021 ◽  
Vol 2021 ◽  
pp. 1-26
Author(s):  
Ang Yang ◽  
Mingzhe Han ◽  
Qingcheng Zeng ◽  
Yuhui Sun
Keyword(s):  
Building Information Modeling ◽  
New Technologies ◽  
Building Design ◽  
Economic Benefits ◽  
Information Modeling ◽  
Three Dimensions ◽  
Smart Buildings ◽  
Smart Building ◽  
Building Information ◽  
Whole Life Cycle

The construction industry is undergoing a digital revolution due to the emergence of new technologies. A significant trend is that construction projects have been transformed and upgraded to the digital and smart mode in the whole life cycle. As a critical technology for the construction industry’s innovative development, building information modeling (BIM) is widely adopted in building design, construction, and operation. BIM has gained much interest in the research field of smart buildings in recent years. However, the dimensions of BIM and smart building applications have not been explored thoroughly so far. With an in-depth review of related journal articles published from 1996 to July 2020 on the BIM applications for smart buildings, this paper provides a comprehensive understanding and critical thinking about the nexus of BIM and smart buildings. This paper proposes a framework with three dimensions for the nexus of BIM application in smart buildings, including BIM attributes, project phases, and smart attributes. According to the three dimensions, this paper elaborates on (1) the advantages of BIM for achieving various smartness; (2) applications of BIM in multiple phases of smart buildings; and (3) smart building functions that be achieved with BIM. Based on the analysis of the literature in three dimensions, this paper presents the cross-analysis of the nexus of BIM and smart buildings. Lastly, this paper proposes the critical insights and implications about the research gaps and research trends: (1) enhancing the interoperability of BIM software; (2) further exploring the role of BIM in the operation and refurbishment phase of smart buildings; (3) paying attention to BIM technology in the field of transportation infrastructure; (4) clarifying the economic benefits of BIM projects; and (5) integrating BIM and other technologies.

scholarly journals Symbiosis of life-cycle structural design and asset management based on Building Information Modeling: Application for industrial facility equipment

2020 ◽  
Vol 12 (1) ◽  
pp. 2170-2180
Author(s):  
Lisa Lenz ◽  
Kai Christian Weist ◽  
Marvin Hoepfner ◽  
Panagiotis Spyridis ◽  
Mike Gralla
Keyword(s):  
Life Cycle ◽  
Asset Management ◽  
Large Scale ◽  
Fatigue Loading ◽  
Life Cycle Management ◽  
Information Modeling ◽  
Cycle Performance ◽  
Industrial Facilities ◽  
Building Information ◽  
Time Dependencies

AbstractIn the last few years, particular focus has been devoted to the life cycle performance of fastening systems, which is reflected in increasing numbers of publications, standards and large-scale research efforts. Simultaneously, experience shows that in many cases, where fastening systems are implemented – such as industrial facilities – the design of fasteners is governed by fatigue loading under dynamic characteristics. In order to perform an adequate design and to specify the most efficient and appropriate fastening product, the engineer needs to access and process a broad range of technical and commercial information. Building information modelling (BIM), as a data management method in the construction industry, can supply such information and accommodate a comprehensive design and specification process. Furthermore, the application of BIM-based processes, such as the generation of a BIM-model, allows to use the important information for the construction as well as the life cycle management with different actions and time dependencies of the asset and its components. As a consequence, the BIM model offers the potential to correlate different data relevant for achieving the goals of the respective application, in order to ensure a more effective and correct design of the fastening. This paper demonstrates such a BIM-based design framework for an Industry 4.0 case, and in particular, the installation of a factory robot through post-installed anchors under fatigue-relevant loading in concrete.

scholarly journals Pregnancy-related complications and incidence of atrial fibrillation: a systematic review and meta-analysis

EP Europace ◽  
2021 ◽  
Vol 23 (Supplement_3) ◽  
Author(s):  
T Al Bahhawi ◽  
A Aqeeli ◽  
S L Harrison ◽  
D A Lane ◽  
I Buchan ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Systematic Review ◽  
Cohort Studies ◽  
Observational Studies ◽  
Large Scale ◽  
Data Extraction ◽  
Meta Analysis ◽  
Significant Heterogeneity ◽  
Random Effects Models ◽  
Increased Risk

Abstract Funding Acknowledgements Type of funding sources: None. Background Pregnancy-related complications have been previously associated with incident cardiovascular disease. However, data are scarce on the association between pregnancy-related complications and incident atrial fibrillation (AF). This systematic review examines associations between pregnancy-related complications and incident AF. Methods A systematic search of the literature utilising MEDLINE and EMBASE (Ovid) was conducted from 1990 to 6 April 2020. Observational studies examining the association between pregnancy-related complications including hypertensive disorders of pregnancy (HDP), gestational diabetes, placental abruption, preterm birth, low birth weight, small-for-gestational-age and stillbirth, and incidence of AF were included. Screening and data extraction were conducted independently by two reviewers. Inverse-variance random-effects models were used to pool hazard ratios. Results: Six observational studies met the inclusion criteria one case-control study and five retrospective cohort studies, with four studies eligible for meta-analysis.  Sample sizes ranged from 1,839-1,303,365. Mean/median follow-up for the cohort studies ranged from 7-36 years. Most studies reported an increased risk of incident AF associated with pregnancy-related complications. The pooled summary statistic from four studies reflected a greater risk of incident AF for HDP (hazard ratio (HR) 1.47, 95% confidence intervals (CI) 1.18-1.84; I2 = 84%) and from three studies for pre-eclampsia (HR 1.71, 95% CI 1.41-2.06; I2 = 64%; Figure). Conclusions The results of this review suggest that pregnancy-related complications particularly pre-eclampsia appear to be associated with higher risk of incident AF. The small number of included studies and the significant heterogeneity in the pooled results suggest further large-scale prospective studies are required to confirm the association between pregnancy-related complications and AF. Abstract Figure.

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