bluuebunny/crossref_metadata_2025_split huggingface dataset:
Standardized Data Integration in the AEC Domains – What does it take to succeed?
Authors: Paskaleva G , Mazak-Huemer A , Sint S , Bednar T 
Published: December 2022

Abstract
Data models are the backbone of digital information exchange, since they contain the structure of data to be exchanged. Just as information requirements vary, so do data models – in level of detail, level of abstraction, and domain coverage. Due to these differences, communication between some data models is easy and between others is difficult. Regarding the Building Information Model (BIM) initiative, the IFC standard data model varies in detail, abstraction level, and large domain coverage. In contrast, the Austrian ÖGG-guideline has a consistent detail and abstraction level focusing on a single domain, subsurface engineering. In order to participate in a loss- and distortion-free information exchange, a reliable translation via a multitude of data models is a must-have.
In this paper, we present formal criteria for distinguishing between semantics-carrying data models, such as IFC and ÖGG, and translating data models that provide reliable communication bridges between them, such as CAEX and SIMULTAN. We will show that translating data models are an indispensable part of the data model infrastructure even within a single domain. For evaluation purpose, we demonstrate our approach on a subsurface engineering use case.
Long video-based action segmentation for earthmoving excavators using improved Temporal Convolutional Network models
Authors: Chen Xuejian , Qin Shuijie , Bai Zhongchen , Guo Yuanjun , Yang Zhile , Jiang Rui , Wu Chengke , Su Shilong 
Published: December 2022

Abstract
Earthwork excavator, as an all-terrain and high-efficiency earthwork excavation equipment, has been widely used in earthwork sites. It is very necessary to analyze the work of earthmoving excavator by means of machine vision. In this paper, the action segmentation method based on long video was applied to the analysis and recogniton of the excavator’s action, and compared with other two current best action segmentation models using the real construction site video. Firstly, the sequence features of the excavator’s work video obtained at the cnstruction site was extracted through 3D convolution method, and then two differernt networks with the extracted sequence features were trained and tested. The experimental results showed that the average frame accuracy of MS-TCN model and ASRF model in excavator action segmentation were 82.6490% and 86.1042% respectively. However, for the recognition task under different working environment, the performance of the two models is quite different. The experimental results manifest that the motion segmentation model based on long video reached good results in excavator motion recognition in earthmoving operation. And it is helpful to analyze the long video working behavior sequence of excavator. This research contributes to the identification of critical elements that explains serial action and to the development of a new application scenario for vision-based behavior segmentation network. Additionally, the results of this study were helpful to automatically analyze the working efficiency and monitor the productivity of earthmoving excavators. Using this kind of data-driven decision can improve the work efficiency of earthmoving excavator and promote the project progress.
Repertory Grid Methodology to Research Tacit Knowledge in Construction
Authors: Aranda-Mena Guillermo , Vaz-Serra Paulo , Edwards Peter 
Published: December 2022

Abstract
Quality and buildability are important issues in construction, and both emerge at the earliest stages of design. However, neither are well-defined concepts. Our premise is that behaviour, values and culture impact on quality and buildability in the design stage, but these are also vulnerable to precise definition and difficult to investigate within a typical hypothesis-driven positivist approach. A better method may lie in a theory of personal constructs or ‘constructivism’ which takes the human experience as a whole. Qualitative research methods and data collection techniques are critically reviewed to assess those methods best fitted for purpose in approaching the research problem. Personal Construct Psychology (PCP), using repertory grids emerges as a suitable candidate and is applied in two pilot studies in Australia and Singapore. Preliminary results show the appropriateness of the approach for engaging in buildability studies.
Structural shop drawings at the Sydney Opera House: An instructive model of information flow?
Authors: Tombesi P , Stracchi P , Cardellicchio L 
Published: December 2022

Abstract
The history of the design decisions directly related to the construction of the Sydney Opera House remains largely anecdotal. A rich group of items recently discovered in Australia may now start filling this gap, as documents brought to light include the drawings issued by the general contractor to build the concrete formwork for the shells, drawings of the temporary structures and falsework, site images, and contractor’s notes. All in all, the drawings display sophisticated combinatory solutions for attaining the structural form required whilst introducing repetition and flexibility in the making of the discrete pieces. While suggesting a remarkable combination of manufacturing and structural shrewdness, these blueprints call into question the canonical history of the building roof’s famous ‘sails’, the rhetoric of the ‘spherical solution’ used to arrive at them, and, most importantly, the information production and knowledge management model we conventionally work within.
A review of methods to specify information requirements in digital construction projects
Authors: Tomczak A , Berlo L v , Krijnen T , Borrmann A , Bolpagni M 
Published: December 2022

Abstract
With the ever-growing digitalisation of the built environment, specifying information requirements (IR) is crucial to control the Building Information Modelling (BIM) data. However, the way of encoding these requirements is subject to a wide range of possibilities, making it difficult for the users to choose the most suitable method. The paper presents a comparative analysis of methods to define IR based on document study and expert group discussions. The study covers Data Dictionaries (ISO12006), Information Delivery Manual (IDM), IFC Property templates, Information Delivery Specification (IDS), Level of Information Need, Model View Definition (mvdXML), and Product Data Templates (PDT), as well as other, non-standardised methods such as Linked Data with SHACL. The comparison is based on criteria from the review of use-cases and covers aspects such as value constraints, properties of fields, geometry representation, metadata, expressiveness and dependency. The paper concludes that no single method covers all the discussed aspects, and selection should be made consciously based on a purpose. The results are relevant to information managers to understand the relations and differences between IR methods, suggest standardisation bodies a way forward to harmonise, integrate or differentiate the standards, and provide a framework for evaluating IR methods.
Automatic BIM Model Auditing for Quantity Take-off Using Knowledge Graph Techniques
Authors: Liu H , Cheng J C P , Gan V J L , Zhou S J 
Published: December 2022

Abstract
Building Information Modeling (BIM) models require sufficient semantic information and consistent modeling style to conduct Quantity Take-off (QTO) smoothly. However, BIM models created by different BIM modelers may have various mistakes about these requirements and auditing such BIM model behavior involves tremendous human effort for manual inspection or the development of rule sets. This study proposes an automatic and efficient BIM model auditing framework for QTO utilizing knowledge graph (KG) techniques. It begins at establishing a BIM-KG definition via identifying required information for auditing purposes. Subsequently, BIM data is automatically transformed into the BIM-KG representations, the embeddings of which are trained using a knowledge graph embedding model. Automatic mechanisms are then developed to utilize the computable embeddings to effectively identify mistake BIM elements. The framework is validated using illustrative examples and the results show that 100% mistake elements can be identified successfully without human intervention.
How Can Blockchain Benefit Payment Systems in Smart Construction Contracts: A Brief Review
Authors: Turnbull C , Sher W , Tang L 
Published: December 2022

Abstract
Construction industry professionals suffer regularly from poor cash-flow which reflects non-payment or payment delays down the hierarchical chain. This issue is important as the construction industry has the highest rates of insolvency in Australia, the UK and many other countries. Payment conditions under current construction contracts have proven to be inefficient in delivering timely payments as human interference has control over processing claims. This paper investigated the status of contracts and contract law in Australia and the potential of smart contract technology in improving payment issues in the industry. Qualitative data was collected from secondary literature sources which included observations from industry professionals, real case studies, secondary research and government surveys. It was found that smart contracts feature self-executing digital contracts, immutable data, require no intermediaries and provide transparency on all levels. Although these features are fit for purpose in resolving current contractual issues, smart contracts are not yet available in the construction industry. It was also found that smart contracts do have the potential to provide a trusted and reliable payment system in the construction industry, although there are some aspects it is unlikely to replace such as human performance. Research limitations and future research directions are also provided.
Geoinformatics approach to classifying landslide hazard in The Hantana Mountain and its vicinity in Sri Lanka
Authors: Wickramasooriya A , Dilini S 
Published: December 2022

Abstract
Landslide is one of the common natural disasters experience in central highlands in Sri Lanka. Even though landslide risk predominates in the central highlands, urbanization has been increasing within last three to four decades in this region. This study has focused to classify landslide hazard in the Hantana mountain and its vicinity in the Kandy district which is belong to the central highlands. Initially a base map of the study area was prepared using 1:10,000 topographic sheets of the survey department of Sri Lanka. According to the criteria of landslide hazard and risk classification introduced by the National Building Research Organization (NBRO) - Sri Lanka, bedrock geology, surface deposits, slope, hydrology and drainage, land use and landform are the main six factors influenced to create landslides. Also based on the influence of creating landslide, this criterion has introduced different weightages and ranks for each factor and conditions within each factor respectively. These weightages and ranks are considered to create weighted thematic layers for six factors mentioned in the above using hard copy maps, digital maps, and aerial photographs. Thereafter, the landslide hazard map for the study area has created using ArcGIS software with the help of Multi Criteria Decision Analysis (MCDA) method and overlay analysis technique. Finally, landslide hazard map has created and classified into five landslide hazardous zones i.e. very high, high, moderate, low, and very low and are distributed about 4%, 11%, 31%, 33% and 21% of the total extension of the study area respectively.
Normalized Difference Drought Index (NDDI) computation for mapping drought severity in Bojonegoro Regency, East Java, Indonesia
Authors: Artikanur S D , Widiatmaka  , Setiawan Y , Marimin  
Published: December 2022

Abstract
Drought is a natural disaster that causes difficulties meeting household, agriculture, and industrial water needs. Drought often occurs in various regions in Indonesia, one of which is the Bojonegoro Regency. Bojonegoro Regency has the highest number of villages experiencing drought in East Java Province in 2019. This study aims to map the drought severity in the Bojonegoro Regency based on the results of the Normalized Difference Drought Index (NDDI) computation. The method used to obtain NDDI was by subtracting the Normalized Difference Vegetation Index (NDVI) by the Normalized Difference Water Index (NDWI) and then dividing by the NDVI plus the NDWI. The results showed five drought severity classes in Bojonegoro Regency: very low, low, medium, high, and very high. Areas classified as high and very high severity have an area of 1,534.32 (0.66%) and 99.38 ha (0.04%), respectively. These results indicate that many areas have the potential to experience drought in Bojonegoro Regency. The results of this analysis can be an input to the government to carry out mitigation efforts such as building reservoirs and infiltration wells, preserving the karst area, and increasing the vegetation cover against drought disasters in the future.
Analysis of the benefits of social assistance policy for victims of natural disasters
Authors: Kuntjorowati E , Hermawati I , Ikawati  , Rusmiyati C , Cahyono S A T , Purnama A 
Published: December 2022

Abstract
Indonesia, which consists of a group of islands, has a very high potential for natural disasters and has an impact on victims, even causing fatalities. The social assistance program is aimed at victims of natural disasters at the stage of prevention and control as well as post-disaster recovery. This study aims to (1) examine the effectiveness of social assistance for victims of natural disasters in terms of timeliness, targets, and handling, and (2) examine factors that support and hinder social assistance for victims of natural disasters. This research used mixed methods and was conducted in 10 disaster-prone locations, namely in Karo, Pidie Jaya, Karang Asem, North Lombok, Kapuas, Pacitan, Pandeglang, Palu, Garut, and Banjarnegara districts. Each location involved 60 respondents who were determined by cluster random sampling technique. Data collection techniques used questionnaires, interviews, FGDs, and documentation studies. Quantitatively the data were analyzed using Wilcoxon Sign Ranks and qualitatively using SWOT. The results showed that social assistance for disaster victims was on time, on target, and appropriate in handling and use. Recommendations for the elderly and people with disabilities to pay more attention, especially at the stage of disaster evacuation.
Urban tree bark analysis for monitoring of air pollution level in Jakarta business district
Authors: Rahman M M , Adzkia U , Nandika D , Siregar I Z , Karlinasari L 
Published: December 2022

AbstractJakarta has become one of the cities with the highest air pollution levels among emerging countries. In urban areas such as Jakarta, trees on the roadside have the potential for biomonitoring due to significant pollutants sourced from the traffic. The bark provides information about air pollution due to its furrowed surface and collects atmospheric particle matter (PM). Therefore, the structure of the bark and surface pollutants of 20 rain trees (Samanea saman(Jacq.) Merr.) in the four lots at Sudirman Central Business District (SCBD) Jakarta were assessed. The study aimed to evaluate of air condition in the SCBD area based on the analysis of the bark structure and concentrations of important pollutant elements of Pb (plumbum), Cd (cadmium), Cu (cuprum), Cr (chromium), Mn (manganese), and Zn (zinc) on the bark. The results showed the bark thickness ranges from 3-9 mm with an average of 6.13 mm. The cuticula was gray-black in color, the phloem was brownish, and the cambium layer was very thin. Cu, Cr, Mn, and Zn were detected based on the analysis of the elements. However, Cd was not found in all trees in these four lots. Furthermore, Mn is the dominant pollutant in all trees, more than 40 ppm or more than 69% of the total, followed by Cu, Zn, and Cr. Based on the result, pollutant analysis through accumulated matter on the bark have the potential to be used as biomonitoring in urban areas.
Assessment of space-based tropical smouldering peatlands: mixed pixel analysis
Authors: Sofan P , Chulafak G A , Pambudi A I , Yulianto F 
Published: December 2022

Abstract
Detection of tropical smouldering peatlands from space remains a challenge in a mixed pixel issue. This study aims to discriminate the mixed pixel containing smouldering fire resulting from Tropical Peatland Combustion Algorithm (ToPeCAl) applied to Landsat-8. The assessment of the smouldering pixel was conducted by applying a modification of the contextual test to select the smouldering pixel and then proceed it to linear spectral mixture analysis. The smouldering and burnt areas used for endmembers were determined from field observation. Our study areas span from South to West Kalimantan’s peatlands covering six path-rows of Landsat-8 in the fire seasons of 2018-2019. There were 53,224 candidate smouldering pixels from ToPeCAl which 80% of them passed the contextual test. Based on mixed pixel analysis, most of the selected smouldering pixels consisted of more than 0.79 of smouldering fraction. This was confirmed by the smoke features on the ground from the high spatial PlanetScope images acquired on the same day with Landsat-8. The actual false alarms pixel may consist of 0.74 of smouldering fraction and more than 0.20 of the burnt area or vegetated area fraction with no smoke features on the ground. Further research on smoke mapping or aerosol properties over burning peatland could enhance the performance of smouldering pixel detection.
Thirty years of change of Pekalongan coastline based on Landsat imagery
Authors: Chulafak G A , Khomarudin M R , Ardha M , Pranowo W S , Prayudha B , Mujio  
Published: December 2022

Abstract
The northern coastal area of Java Island is where many economic and industrial centers are located. Many big cities are located in this area, such as Jakarta, Semarang, and Surabaya. One of the problems in this area is the occurrence of tidal flooding. One of those affected by the tidal flood is Pekalongan, where the city also experienced land subsidence which is more severe than other big cities in Indonesia. One of the impacts of tidal flooding is the occurrence of coastal abrasion, where land areas are increasingly disappearing. This research objective is to see how big the coastline changes occurred in the Pekalongan area for 30 years through remote sensing data. Landsat image was used to see changes in coastlines from 1988 to 2021 on an annual basis. NDWI (Normalized Difference Water Index) was used to clarify the difference between land and water areas. Moreover, to reduce subjectivity, Otsu’s method was used for thresholding. The results show that most Pekalongan area is subject to abrasion, with the most severe conditions up to around 232 m. In addition, there are also problems related to tidal flooding, whose conditions are increasingly widespread every year.
Salt pond detection on Sentinel 2 Satellite Imagery using Object-Based Image Analysis (OBIA) Approach
Authors: Darmawan M , Sutrisno D , Agus S B , Nahid I , Rudiastuti A W , Suryanta J , Sangadji M S 
Published: December 2022

Abstract
Object-based image analysis (OBIA) is an image classification that is oriented to object patterns that use image objects as the basis for processing, calculates characteristics per object, and extracts land cover information from remotely sensed images. This study aims to detect salt ponds using Sentinel 2 satellite data with an object-based classification model. The center of salt production, which is also an experimental area for the development of industrial salt from the ministry of maritime affairs and fisheries on the north coast of the island of Java was selected as the study area. The unit of analysis for this classification is the segmented object of sentinel image. The classification scheme built to detect salt ponds using OBIA consists of level 1, level 2, and level 3. Level 1 is to separate land and water using a Near Infrared canal. Level 2 is to separate land use from object segmentation results in land class at level 1 using NDVI transformation, and level 3 is to separate salt and non-salt ponds from the segmentation results of land use at level 2 using sentinel image transformation algorithm for the distribution of chlorophyll-a. The result shows chlorophyll-a estimation image transformation from sentinel useful to separate salt and non-salt ponds. Many researchers have been reported that chlorophyll-a does not live in the salinity range of salt ponds greater than 50 ppt, meanwhile, in non-salt ponds, chlorophyll-a is used as natural feed for cultivated animals. Furthermore, the research shows a classification scheme of salt ponds and non-salt ponds can be derived from sentinel 2 imagery with OBIA approach
Evaluate land suitability analysis for rice cultivation using a GIS-based AHP multi-criteria decision-making approach: Majalengka Regency, West Java Province
Authors: Adrian  , Widiatmaka  , Munibah K , Firmansyah I 
Published: December 2022

Abstract
This research is motivated by the agricultural sector ranks first and plays a vital role in GRDP income in Majalengka Regency. This study aims to predict areas suitable for land use for sustainable food agriculture (LP2B) and evaluate land suitability for rice. We use the Analytical Hierarchical Process (AHP), and Geography Information System (GIS) approaches to give weight to the suitability of criteria and sub-criteria that influence multi-criteria decisions. Including using parameters; Soil morphology, elevation, rainfall, water cover, land area, disaster risk, erosion, and slope are the criteria identified as requirements for the intended application. The resulting weights to build a suitability map layer using a weighted sum overlay tool on a GIS platform by involving government stakeholders in Majalengka Regency. The results showed that the map of the evaluation of the suitability of rice production in the study area with the land was very suitable, namely 11% (15,038.49 ha) of the total study area, which was very suitable for rice production. The relationship between suitability maps and changes in spatial patterns in 2022 in the study area has also overlapped. The results showed the suitability of the spatial plan with the results of the suitability map of paddy fields.
Physical and social vulnerability to coastal erosion: An assessment of Kalutara Coastal Belt, Sri Lanka
Authors: Kirishanthan P 
Published: December 2022

Abstract
The shoreline of Kalutara, Sri Lanka has become more prone to erosion because of environmental changes caused by natural and anthropogenic factors including climate change. The study aimed to assess and map the physical and social vulnerability to coastal erosion in the shoreline between the Kalu and Bolgoda River mouths in Southwest Sri Lanka. This study relied on secondary data sources such as topographic, digitized, and satellite maps obtained from the Survey Department and the website of the United States Geological Survey (USGS). The Coastal Vulnerability Index (CVI) was calculated using only five variables namely coastal slope, geology, soil, shoreline change (End Point Rate), and Land Use and Land Cover (LULC). On the other hand, for the Social Coastal Vulnerable Index (SVI), several socioeconomic variables were examined. Kalutara North and Thotupala have been identified as having a higher risk of Physical and Social Coastal Vulnerability. This research, therefore, revealed that the coastal zone along Kalutara – Panadura in Sri Lanka is vulnerable both physically and socially due to the accelerating rate of coastal erosion. Because of the potential effects of climate change and rising sea levels, this scenario would pose a serious threat to the environment and communities in the foreseeable future.