bluuebunny/crossref_metadata_2025 huggingface dataset:
Use of BIM and visual data collected by UAS and 360° camera for construction progress monitoring
Authors: Barbosa Amanda S , Costa Dayana B
Published: December 2022

Despite progress monitoring is an essential practice for achieving the success of construction, traditional monitoring methods based on manual information gathered through visual inspections are error-prone, depending on the experience of those who carry them out. Furthermore, most studies of progress monitoring using digital technologies focus on activities carried out outdoors, limiting the application of these methods in residential construction sites, which have several indoor activities. This study proposes a method for outdoor and indoor visual monitoring of construction progress using Building Information Modeling (BIM), 360° camera, and photogrammetry aided by an Unmanned Aerial System (UAS). For this purpose, exploratory case studies were carried out. The first exploratory study aimed to understand data collection and processing operationalization using the proposed technologies. Then, these technologies were used and evaluated to monitor progress in a second exploratory case study, enabling the development of a proposed method for using visual data collected by UAS and 360° camera integrated to BIM for progress monitoring. The status of the external area of the construction site was represented by point clouds generated through images collected by UAS. For monitoring inside the buildings, a 360° camera attached to the safety helmet was used. The results include evaluating the use of a 360° camera to monitor the internal progress of works, presenting its strengths, limitations, and use recommendations. In addition, the results also include the proposal of a method for visual progress monitoring of indoor and outdoor activities using BIM, UAS, and 360° cameras.
Using smartwatches to understand the relationship between construction workers’ travelled distance and time spent on direct work
Authors: Pérez C T , Salling S , Wandahl S
Published: December 2022

Construction production processes are, in general, improved by removing non-value-adding activities. This includes reducing workers’ movements (walking) for transportation, inspections, etc. This research analyses the relationship between construction workers’ travelled distance and time spent on Direct Work (DW) at a construction site. An exploratory case study of the tasks performed by the carpenter trade was conducted.. Several sources of evidence, tools, and techniques were adopted: (a) direct observation to characterize the main activities; (b) Work Sampling (WS) technique to estimate the distribution of work time spent on different activities; (c) smartwatches to collect the data on construction workers’ travelled distance on the site during workhours; and (d) questionnaire application to collect workers’ perception of using the smartwatches. The relationship between distance travelled by workers and the time spent on DW was tested using linear regression analysis. The results indicate DW is indirectly correlated to how much workers walk on the construction site (R=0.445). This study presents a pioneering use of data gathered from smartwatches as a tool for collecting workers’ travelled distance. The use of smartwatches has the potential implication to automate the data collection to estimate the time spent on DW based on travelled distances.
Real-time Employee Monitoring Technologies in the Construction Sector – Effect, Readiness and Theoretical Perspectives: The case of New Zealand
Authors: Wu R W , Yiu T W , Jelodar M B
Published: December 2022

Varieties of Real-time Employee monitoring Technology (REMT) are becoming popular and have aroused significant interest in recent years from the construction sector, where the industry explores the use of advanced monitoring technologies to reduce unsafe work behaviours and improve productivity. However, studies identified some concerns about applying these monitoring technologies at construction sites. Consequently, REMT devices and applications have not been well-received for tracking frontline workers. Lack of understanding of REMT, monitoring data protection and privacy management strategy set a barrier for the monitoring technologies to implement in the construction industry. Privacy has become a critical issue for the future digital construction site. This study adopts the literature review and a questionnaire survey, examined the readiness, summarised effects of REMT applied at the New Zealand construction sites, identified the influence factors, and discovered the theories that will potentially explain the factors and address the potential impact. Communication Privacy Management theory (CPM), Equity Theory (ET) and Control Theory of Privacy (CTP) are reviewed, and a theoretical framework is built upon REMT adoption in the construction sector. In conclusion, future studies are recommended for the international construction entities to get ready to adopt the real-time monitoring tools.
Comparing two AI methods for predicting the future trend of New Zealand building projects: Decision Tree and Artificial Neural Network
Authors: Zavvari A , Jelodar M B , Sutrisna M
Published: December 2022

The rise of Artificial Intelligence and Machine Learning in many aspects of construction management has helped this industry to further improve the management, design, and planning of construction projects. This trend happens in many construction sectors, including in New Zealand. Whilst relatively smaller compared to construction sectors in other OECD countries, the construction sector in New Zealand carries a similar degree of complexity and with its own unique characteristics. Various studies showed that AI and ML can be used for analysis of construction data to generate further insights and to predict future trends in construction sectors. However, the AI approaches have their own set of challenges such as complexity, high cost of training, failure, and change. Aiming to better understand the trends and requirements of New Zealand building projects, this study started with a review of the existing AI methods that are currently being applied. Accordingly, compare and evaluate the accuracy of two AI prediction methods. The two methods of Decision Tree and Artificial Neural Network are selected based on their predictive power and accuracy. These methods are conducted by using available historical building data which is available on StatsNZ website. A portion of the data is used for testing and evaluation purposes, and the rest of the data is used for training the AI methods. It was identified that the Decision Tree method did not show suitable accuracy for prediction building consents issued data. In comparison, Artificial Neural Network shows a reasonable range with 95% of confidence level. Therefore, this method is applied for building consents issued in New Zealand.
Exploring a Digital Twin Framework for lean management of constraints in construction: A literature review
Authors: Mao Zeyu , Gonzalez Vicente A. , Zou Yang
Published: December 2022

Construction constraints are conditions or circumstances that impede the standard progress of production tasks in construction projects towards achieving specific production objectives. Construction constraints are highly dynamic and span different domains. Failing to manage constraints on time could result in out of sequence work and suboptimal productivity. As the construction sector embraces digital technologies, an emerging concept, Digital Twin, has been recognised as a potential solution to solve the endemic problems in construction process management. Digital Twin as a virtual model for cyber-physical bi-directional data-driven management and control of the physical counterpart has emerged over the past decade in the manufacturing industry. However, the implementation of Digital Twin in the construction sector is still in its infancy. Hence, there is an opportunity to adopt Digital Twin to enhance the current implementation of constraint management. This paper presents a literature review of constraint management-related studies, aiming to determine the potential constituents of the Digital Twin framework from a dual technological/lean-based perspective. A total of 55 papers published so far were selected using Scopus. The result shows the potential constituents can include: (1) Information technologies, (2) Swarm Intelligence and Genetic Algorithm, (3) Semantic Web, and (4) Lean-based methods. Our study provides valuable insight concerning which technologies could be used to support the development of DT in the construction sector. These findings can serve as a guideline for future researchers in the construction industry to develop their own DT.
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

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

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

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

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

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

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

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

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

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

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

Jakarta 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

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

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

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

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

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.
Sustainable utilizations of Pohpohan (Pilea melastomoides (Poir.) Wedd) in Tamansari Village, West Java-Indonesia
Authors: Adhiningsih L , Basuni S , Munawir A , Hidayati S , Hartoyo A P P , Sunkar A
Published: December 2022

Forest plays an important role in producing timber and non-timber product to fulfill human beings’ prerequisites and live hood, a source of income for many communities and becomes the solutions to any other challenges. The community in Taman Sari Village cooperates with Gunung Halimun Salak National Park through a conservation partnership program to cultivate and commercialize pohpohan (Pilea melastomoides (Poir.) Wedd) in the traditional zone. This species is known as indigenous fresh aromatic vegetable and contain valuable potential phytochemical such as antibacterial and anti-cancer. Pohpohan is traditionally cultivated by the community since the 1980s in Tamansari village, this culture is still practiced by the community who join as member of the Kelompok Tani Mandiri (KTM). This study aims to document and analyze the sustainable traditional cultivation of pohpohan in Tamansari village by collaborating with all members (56) of the KTM. The study applied mixed qualitative and quantitative methods, to gain more understanding of the community dynamic. Generally, the cultivation and utilization of pohpohan are managed traditionally using manual tools such as hoes and sickles. Yet this approach is considered as environmentally friendly and resourceful for their limited land. A total 34% of pohpohan farmers are in the age class 55-65, indicates the importance of regeneration to verify its sustainability.
Utilization of Kandelia candel (L.) Druce and hypocotyl cutting seedling for mangrove rehabilitation in Indonesia
Authors: Nugraha L A , Kusmana C , Hartoyo A P P
Published: December 2022

Kandelia candel (L.) Druce is one of the rare mangrove species in Indonesia. Additionally, mangrove rehabilitation requires effective and efficient methods. Accelerating the growth of mangrove species using vegetative propagation, specifically hypocotyl cutting, is necessary. The objectives of this study were to investigate the scientific literature on the use of K. candel for mangrove rehabilitation in Indonesia and to analyze the growth of K. candel seedling from hypocotyl cuttings. Scientific literature was collected from 2012 to 2022 in some search engines and library databases. An experimental study was carried out with different treatments (hypocotyl cuttings, planting media, plant growth regulator) and three replications. We found 576 articles on mangrove rehabilitation in Indonesia and only an article uses K. candel (0,002%) as a species in mangrove rehabilitation. There was no study on hypocotyl cutting of K. candel. The best combination of intact hypocotyl treatment was intact hypocotyl, mud+sand growing medium, and growth regulator 15.000 ppm. In contrast, the best combination of cut hypocotyl treatment was bottom hypocotyl, mud+sand planting medium, and growth regulator 15.000 ppm.
The status of bamboo research and development for sustainable use in Indonesia: A systematic literature review
Authors: Ekawati D , Karlinasari L , Soekmadi R , Machfud M
Published: December 2022

The current global situation of bamboo utilization has shifted from traditional to modern bamboo, along with improved technology and innovations. However, the literature on bamboo research and development in Indonesia is still minimal and fragmented. Moreover, it has not yet clearly seen the strategy and direction of future utilization and its sustainability. Therefore, it is urgent to know the current status of bamboo research and development, especially its sustainable use. A systematic literature review was carried out on the research and development of bamboo in Indonesia, examining and comparing publications from both academic and professional works of literature in the period 2001 to 2021. This study was conducted by building insights from past reviews and initial scoping analysis of two decades of bamboo R&D. The findings of this study build upon the research and efforts on the social-cultural, economic, and ecological aspects underpinnings of bamboo utilization and development. Furthermore, the typology and other supporting factors that have already been carried out will be proposed to help connect fragmented and detached aspects into an integrated strategy and direction of research and development. Finally, future orders for progressing and sustainable bamboo utilization and development in Indonesia are identified.
Biomass-based energy potential in Semujur Island, a small remote area in Indonesia
Authors: Siregar U J , Nugroho A , Hartoyo A P P , Siregar C A
Published: December 2022

Electricity has not been spread equally in Indonesia, especially in remote areas. Forest biomass could potentially be utilized as bioenergy and fuel for an electricity generator, particularly in remote areas with no electricity access. The objectives of this research were to identify vegetation species composition and estimate tree biomass’s potential as fuel for power plants in Semujur Island, Bangka Belitung Province, Indonesia. The method used was vegetation analysis throughout the study area. The result showed that Terminalia catappa dominated vegetation species at the seedling, sapling, and pole levels. At tree level was dominated by Ficus caulocarpa with an importance value index (IVI) of 166.81%, while non-tree species was dominated by Cocos nucifera (IVI of 200%) as palm species. Liana and understory that dominated the study site in order were Imperata cylindrica (IVI 52.50%) and Mikania sp. (IVI 143.59%). The total biomass on this island was 2,298.94 tons/ha, which could potentially generate electrical energy amounted to 3,371.78 MWh. This amount of energy can fulfill the electrical needs of the local community for 237 years to the future without any replanting activity. The recommended crops that can be planted on this island are vetiver and sesame to reserve biomass and prevent abrasion.
Study of beam divergence and thrust vector eccentricity characteristics of the Hall thruster based on dual Faraday probe array planes and its applications
Authors: CHEN Xinwei , ZHAO Yong , TIAN Kai , GAO Jun , SUN Mingming , SUN Xinfeng , GUO Ning , ZHANG Hong , WANG Shangmin , FENG Jie , CHEN Tao , GENG Hai , YANG Juntai , SHI Kai
Published: December 2022

The accurate knowledge of the thrust vector eccentricity and beam divergence characteristics of Hall thrusters are of significant engineering value for the beneficial integration and successful application of Hall thrusters on spacecraft. For the characteristics of the plume bipolar diffusion due to the annular discharge channel of the Hall thruster, a Gaussian-fitted method for thrust vector deviation angle and beam divergence of Hall thrusters based on dual Faraday probe array planes was proposed in respect of the Hall thruster beam characteristics. The results show that the ratios of the deviation between the maximum and minimum values of the beam divergence angle and the thrust vector eccentricity angle using a Gaussian fit to the optimized Faraday probe dual plane to the mean value are 1.4% and 11.5%, respectively. The optimized thrust vector eccentricity angle obtained has been substantially improved, by approximately 20%. The beam divergence angle calculated using a Gaussian fitting to the optimized Faraday probe dual plane is approximately identical to the non-optimized one. The beam divergence and thrust vector eccentricity angles for different anode mass flow rates were obtained by averaging the beam divergence and thrust vector eccentricity angles calculated by the dual-plane, Gaussian-fitted ion current density method for different cross-sections. The study not only allows for an immediate and effective tool for determining the design of thrust vector adjustment mechanisms of spacecraft with different power Hall thrusters but also for characterizing the 3D spatial distribution of the Hall thruster plume.
Numerical studies on the influences of gas temperature on atmospheric-pressure helium dielectric barrier discharge characteristics
Authors: HUO Weigang , LIN Jingsong , YU Tanxue , WANG Yuxin , ZHANG Hua
Published: December 2022

A fast-rising gas temperature is due to frequent collisions of the heavy particles in an atmospheric-pressure dielectric barrier discharge. In this paper, a two-dimensional fluid model is applied to investigate the influences of rising gas temperature on an atmospheric-pressure helium dielectric barrier discharge. With the increase in the gas temperature, it is found that: (1) a helium discharge can evolve from the discharge column to a homogeneous discharge; (2) the breakdown time is in advance and the gas breakdown voltage decreases; (3) the spatial distribution evolution of the electron density is similar to that of the helium atom density. The most significant discrepancy between them is that the electron densities are high at some positions where the helium atom densities are nevertheless low. Furthermore, the radial reduced electric fields are obtained under different gas temperatures. The physical reasons for the gas temperature effects are discussed. The simulation results provide a better understanding of the roles of the radial reduced electric field and the heavy particle.
Investigation on the effect of grinding wheel for grinding of AISI D3 tool steel under different conditions
Authors: Ali Syed Mansoor , Johnson Nevan Nicholas , Madhavadas Vaishnav , Giri Anoj , Sahu Jambeswar , Anand Suya Prem , Srivas C S
Published: December 2022

The surface finish of ground samples is highly influenced by the grinding parameters, grinding conditions and the type of grinding wheel. This paper emphasizes on the effect of various grinding factors such as the grinding conditions, the type of grinding wheel and operating process parameters like depth of cut and table speed on the surface roughness of the ground samples. Two types of grinding wheels alumina (Al2O3) and cubic boron nitride (CBN) were used for grinding AISI D3 tool steel under dry and wet conditions. The material removal rate and surface roughness were evaluated for all the ground samples. The results showed that wet grinding outperformed dry grinding and provided a better surface finish while using both grinding wheels. Machine Learning was implemented to optimize the grinding parameters. Multi-objective optimization using genetic algorithm was done and a Pareto frontier chart was made to help determine what values for the input parameters would achieve the required outputs such as material removal rate and surface roughness. Two different approaches Genetic Algorithm and Principle Component Analysis were then compared for multi-objective optimization. The type of grinding wheel used had a dominant effect on the surface roughness of ground samples while the depth of cut had a lesser effect.
Protective responses of older adults for avoiding injury during falls: evidence from video capture of real-life falls in long-term care
Authors: Robinovitch Stephen N , Dojnov Aleksandra , Komisar Vicki , Yang Yijian , Shishov Nataliya , Yu Ying , Bercovitz Ian , Cusimano Michael D , Becker Clemens , Mackey Dawn C , Chong Helen
Published: December 2022

Background

falls are common in older adults, and any fall from standing height onto a rigid surface has the potential to cause a serious brain injury or bone fracture. Safe strategies for falling in humans have traditionally been difficult to study.

Objective

to determine whether specific ‘safe landing’ strategies (body rotation during descent, and upper limb bracing) separate injurious and non-injurious falls in seniors.

Design

observational cohort study.

Setting

two long-term care homes in Vancouver BC.

Methods

videos of 2,388 falls experienced by 658 participants (mean age 84.0 years; SD 8.1) were analysed with a structured questionnaire. General estimating equations were used to examine how safe landing strategies associated with documented injuries.

Results

injuries occurred in 38% of falls, and 4% of falls caused injuries treated in hospitals. 32% of injuries were to the head. Rotation during descent was common and protective against injury. In 43% of falls initially directed forward, participants rotated to land sideways, which reduced their odds for head injury 2-fold. Upper limb bracing was used in 58% of falls, but rather than protective, bracing was associated with an increased odds for injury, possibly because it occurred more often in the demanding scenario of forward landings.

Conclusions

the risk for injury during falls in long-term care was reduced by rotation during descent, but not by upper limb bracing. Our results expand our understanding of human postural responses to falls, and point towards novel strategies to prevent fall-related injuries.
Validation of the Dutch Version of the BODY-Q Measuring Appearance, Health-Related Quality of Life, and Experience of Healthcare in Patients Undergoing Bariatric and Body Contouring Surgery
Authors: de Vries Claire E E , Tsangaris Elena , Makarawung Dennis J S , Mink van der Molen Aebele B , van Veen Ruben N , Hoogbergen Maarten M , Pusic Andrea L , Terwee Caroline B , Cano Stefan , Klassen Anne F
Published: December 2022

Background

The BODY-Q is a patient-reported outcome measure developed for use in bariatric and body contouring surgery.

Objectives

The objective of this study was to examine the validity and reliability of the Dutch version of the BODY-Q.

Methods

The BODY-Q consists of 163 items in 21 independently functioning scales that measure appearance, health-related quality of life, and experience of care. The data used to validate the Dutch BODY-Q were provided by 2 prospective multicenter cohort studies across 3 hospitals in the Netherlands. The BODY-Q was administered before and after surgery at 3 or 4 months and 12 months. Rasch measurement theory (RMT) analysis was used to evaluate the BODY-Q for targeting, category threshold order, Rasch model fit, Person Separation Index, and differential item functioning by language (original English data vs Dutch data).

Results

Data were collected between January 2016 and May 2019. The study included 876 participants, who provided 1614 assessments. Validity was supported by 3 RMT findings: most scales showed good targeting, 160 out of 163 items (98.2%) evidenced ordered thresholds, and 142 out of 163 items (87.1%) fitted the RMT model. Reliability was high with Person Separation Index values >0.70 for 19 out of 21 scales. There was negligible influence of differential item functioning by language on person item locations and the scale scoring.

Conclusions

This study provides evidence for the reliability and validity of the Dutch BODY-Q for use in bariatric and body contouring patients in the Netherlands. The Dutch BODY-Q can be used in (inter)national research and clinical practice.

Level of Evidence: 2