bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparing airborne algorithms for greenhouse gas flux measurements over the Alberta oil sands
Authors: Erland Broghan M. , Adams Cristen , Darlington Andrea , Smith Mackenzie L. , Thorpe Andrew K. , Wentworth Gregory R. , Conley Steve , Liggio John , Li Shao-Meng , Miller Charles E. , Gamon John A.
Published: October 2022

Abstract. To combat global warming, Canada has committed to
reducing greenhouse gases to be (GHGs) 40 %–45 % below 2005 emission levels by 2025. Monitoring emissions and deriving accurate inventories are essential to reaching these goals. Airborne methods can provide regional and area source measurements with small error if ideal conditions for sampling are met. In this study, two airborne mass-balance box-flight algorithms were compared to assess the extent of their agreement and their performance under various conditions. The Scientific Aviation's (SciAv) Gaussian algorithm and the Environment and Climate Change Canada's top-down emission rate retrieval algorithm (TERRA) were applied to data from five samples. Estimates were compared using standard procedures, by systematically testing other method fits, and by investigating the effects on the estimates when method assumptions were not met. Results indicate that in standard scenarios the SciAv and TERRA mass-balance box-flight methods produce similar estimates that agree (3 %–25 %) within algorithm uncertainties (4 %–34 %). Implementing a sample-specific surface extrapolation procedure for the SciAv
algorithm may improve emission estimation. Algorithms disagreed when
non-ideal conditions occurred (i.e., under non-stationary atmospheric
conditions). Overall, the results provide confidence in the box-flight
methods and indicate that emissions estimates are not overly sensitive to
the choice of algorithm but demonstrate that fundamental algorithm
assumptions should be assessed for each flight. Using a different method,
the Airborne Visible InfraRed Imaging Spectrometer – Next Generation
(AVIRIS-NG) independently mapped individual plumes with emissions 5 times
larger than the source SciAv sampled three days later. The range in
estimates highlights the utility of increased sampling to get a more
complete understanding of the temporal variability of emissions and to
identify emission sources within facilities. In addition, hourly on-site
activity data would provide insight to the observed temporal variability in
emissions and make a comparison to reported emissions more straightforward.
Quantifying vegetation indices using TLS: methodological complexities and ecological insights from a Mediterranean forest
Authors: Flynn WIlliam Rupert Moore , Owen Harry Jon Foord , Grieve Stuart William David , Lines Emily Rebecca
Published: October 2022

Abstract. Accurate measurement of vegetation density metrics including plant, wood and leaf area indices (PAI, WAI and LAI) is key to monitoring and modelling carbon storage and uptake in forests. Traditional passive sensor approaches, such as Digital Hemispherical Photography (DHP), cannot separate leaf and wood material, nor individual trees, and require many assumptions in processing. Terrestrial Laser Scanning (TLS) data offer new opportunities to improve understanding of tree and canopy structure. Multiple methods have been developed to derive PAI and LAI from TLS data, but there is little consensus on the best approach, nor are methods benchmarked as standard. Using TLS data collected in 33 plots containing 2472 trees of five species in Mediterranean forests, we compare three TLS methods (LiDAR Pulse, 2D Intensity Image and Voxel-Based) to derive PAI and compare with co-located DHP. We then separate leaf and wood in individual tree point clouds to calculate wood to total plant area (α), a metric to correct for non-photosynthetic material in LAI estimates. We use individual tree TLS point clouds to estimate how α varies with species, tree height and stand density. We find the LiDAR Pulse method agrees most closely with DHP, but is limited to single scan data so cannot determine individual tree α. The Voxel-Based method shows promise for ecological studies as it can be applied to individual tree point clouds. Using the Voxel-Based method, we show that species explain some variation in α, however, height and density were stronger predictors. Our findings highlight the value of TLS data to improve fundamental understanding of tree form and function, but also the importance of rigorous testing of TLS data processing methods at a time when new approaches are being rapidly developed. New algorithms need to be compared against traditional methods, and existing algorithms, using common reference data. Whilst promising, our results show that metrics derived from TLS data are not yet reliably calibrated and validated to the extent they are ready to replace traditional approaches for large scale monitoring of PAI and LAI.
A graph neural network (GNN) approach to basin-scale river network learning: the role of physics-based connectivity and data fusion
Authors: Sun Alexander Y. , Jiang Peishi , Yang Zong-Liang , Xie Yangxinyu , Chen Xingyuan
Published: October 2022

Abstract. Rivers and river habitats around the world are under sustained pressure
from human activities and the changing global environment. Our ability
to quantify and manage the river states in a timely manner is critical
for protecting the public safety and natural resources. In recent
years, vector-based river network models have enabled modeling of
large river basins at increasingly fine resolutions, but are computationally demanding. This work presents a multistage, physics-guided, graph neural network (GNN) approach for basin-scale river network learning
and streamflow forecasting. During training, we train a GNN model
to approximate outputs of a high-resolution vector-based river network
model; we then fine-tune the pretrained GNN model with streamflow
observations. We further apply a graph-based, data-fusion step to
correct prediction biases. The GNN-based framework is first demonstrated
over a snow-dominated watershed in the western United States. A series of experiments are performed to test different training and imputation strategies. Results show that the trained GNN model can effectively serve as a surrogate of the process-based model with high accuracy, with median
Kling–Gupta efficiency (KGE) greater than 0.97. Application of the
graph-based data fusion further reduces mismatch between the GNN model
and observations, with as much as 50 % KGE improvement over
some cross-validation gages. To improve scalability, a graph-coarsening
procedure is introduced and is demonstrated over a much larger basin.
Results show that graph coarsening achieves comparable prediction skills
at only a fraction of training cost, thus providing important insights
into the degree of physical realism needed for developing large-scale
GNN-based river network models.
EFFICIENT SPATIO-TEMPORAL MODELLING TO ENABLE TOPOLOGICAL ANALYSIS
Authors: Jahn M. W. , Kuper P. , Breunig M.
Published: October 2022

Abstract. Time-dependent analysis scenarios such as heat, wind or flood analysis in cities and in landscapes need a correct and consistent modelling of geometry and topology over time. However, hitherto efficient time-dependent geometry models and topological analysis based on a mathematically sound theory were neglected when modelling objects in the built and natural environment. This is surprising as incorrect topological relationships over time such as not fitting neighbourhoods of surfaces or solids inevitably lead to wrong analysis results. In this paper we propose the combination of a spatio-temporal geometry model together with a topological schema to provide accessible and consistent objects over time. Where an efficient spatio-temporal geometry model reduces redundant geometric data and enables spatio-temporal queries, an efficient topological model minimizes the number of relations as far as possible and enables robust topological queries. The geometry model uses the concepts of point tubes, delta storage as well as net components and pre- and post-objects to enable the change of geometry and topology over time for natural structures, e.g., digital terrain models (DTM). Geometry here are the boundary and interior coordinates of the objects whereas topology here is interpreted in a wider sense than only focusing on geometrically induced topology to maintain topological consistency by the management of incidence relations. In addition, the topological schema introduces three basic bidirectional relation types to manage aggregations, abstractions and incidences in order to provide a general abstract topological schema for the management of complex intra- and inter-related spatio-temporal objects to enable the modelling of consistent complex topology over time. Finally, a conclusion is given highlighting the applicability of the approach and future research.
3D POINT CLOUD TO BIM: AUTOMATED APPLICATION TO DEFINE IFC ALIGNMENT AND ROADWAY WIDTH ENTITIES FROM MLS-ACQUIRED LiDAR DATA OF MOUNTAIN ROADS
Authors: Lamas D. , Justo A. , Soilán M. , Riveiro B.
Published: October 2022

Abstract. The growing trend of developing standards of information exchange and management processes is leading to Building Information Models (BIM) being adapted to work with linear infrastructure assets. For this reason, the Industry Foundation Classes (IFC) has developed standards for linear infrastructure such as roads. Furthermore, the usage of remote sensing technologies, such as Mobile Laser Scanning (MLS) systems for infrastructure monitoring is increasingly common. This paper presents an automated methodology that takes as input 3D point cloud tiles from an MLS and its trajectory, and outputs an IFC-compliant file that models the alignment of the road and the width of the roadway along the length of the road. The methodology is evaluated in 48 km of mountain roads, in some cases without road markings, using neither intensity nor colour fields.
GEOVISUALIZATION ANALYSIS OF GENDER-BASED VIOLENCE IN MEXICO CITY USING 3D MAPPING APPROACH
Authors: Saldana-Perez M. , Palma C. , Contreras Y. Z. , Carrillo N. , Moreno-Ibarra M.
Published: October 2022

Abstract. The study of criminal acts is a topic of great interest to society and with the increase of violence against women in the world makes working with this type of data an important subject, where it can be used to detect areas with high crime rates to help in decision making. This work uses open data sets available from government entities of Mexico City, where three sectors of interest were studied: economic, education, and transportation around the criminal investigation reports made by the government. For the processing and analysis of spatial data, QGIS was used with the help of open-source libraries, the 2D and 3D modelling was carried out to create heatmaps and detect hotspots. It was found that the Historic center of Mexico City is the most insecure and that the Cuauhtémoc district stands out as the most dangerous zone, for transport stations, the ones that had the most intersections with other stations are the ones that presented greater problems of gender violence, in the economic sector there was a high incidence in the limits of each district, contrary to the results obtained on the educational services.
A TIME EFFICIENT QUALITY CHECK METHOD BASED ON LASER SCANNING FOR INSTALLATION OF PREFABRICATED WALL PANELS
Authors: Wang M. , Wang C. C. , Sepasgozar S. , Zlatanova S.
Published: October 2022

Abstract. Verticality check of prefabricated elements is an essential part of prefabrication construction. Currently, it is mostly carried out by manual methods, which is slow and inefficient. Previous studies have used laser scanning for the quality check but mainly focused on surface defects, flatness, and the dimension of construction elements. Very few studies used laser scanning to evaluate the installation quality of prefabricated elements. Those, who adopted the laser scanning method, compared the as-built with the initial design version of BIM. Such approach requires an accurate design version of BIM with tedious manual tasks relying on human skills that involve errors. This on-going study investigates a verticality check method based on laser scanning for assessing the quality of wall panel installations without relying on previous drawings or BIM. The proposed method enables practitioners to confirm the quality of the wall panel installation and its vertical deviations based on the processed point cloud data. The region growing segmentation and random sample consensus are used to process the acquired data for computing the deviations. This method is validated in a real high-rise prefabrication residential building. Our method took about 9 min/100 m2, versus the conventional method, which took 31 min/100 m2. The experiments indicate that the proposed method is significantly more time-efficient compared to the conventional manual method. The contribution of this study includes suggesting suitable parameters for measuring the vertical dimensions of prefabricated wall panels and deviations that can be replicated in high-rise prefabricated residential projects.
VIZPLAN: A VISUAL ANALYTICS PLATFORM FOR THE ASSESSMENT OF MULTIDIMENSIONAL INDICATORS OVER TIME
Authors: Leplat L. , Torres R. S. , Aspen D. , Amundsen A.
Published: October 2022

Abstract. In this paper, we introduce VizPlan, a new platform to support the assessment of multidimensional indicators over time. VizPlan includes a visualisation scheme based on a radial visual structure that allows the direct comparison of indicator values over time, a search tool to support the identification of entities whose indicators are similar to each other, and a clustering tool to group entities according to their indicator scores. VizPlan was designed and implemented to be flexible; it can be easily tailored to the visualization and analysis of any multidimensional temporal data. In this paper, the use of VizPlan is illustrated in the context of three case studies concerning the analysis of sustainability indicators to support urban planning: key performance indicators related to the sustainable development goals, walkability analysis, and bus service availability assessment. All case studies refer to real data related to Norwegian cities, especially Ålesund. VizPlan is available as an open source software at https://github.com/Rylern/VizPlan – As of May 2022.
PY3DTILERS: AN OPEN SOURCE TOOLKIT FOR CREATING AND MANAGING 2D/3D GEOSPATIAL DATA
Authors: Marnat L. , Gautier C. , Colin C. , Gesquière G.
Published: October 2022

Abstract. In recent years, the production of 3D geospatial data using formats such as IFC, CityGML and GeoJSON, has increased. Visualizing this data on the web requires solving a variety of problems, such as the massive amount of 3D objects to be visualized at the same time and the creation of geometry suitable for a 3D viewer. Cesium and OGC introduced the 3D Tiles format in 2015 to solve these issues. They have created a specific format optimized for streaming and rendering 3D geospatial content, based on the glTF format developed by Khronos. The recency of the 3D Tiles format implies the need to experiment around this format and to test its interoperability with other geospatial and urban data formats. There is also the will to innovate on the organization of 3D objects in order to offer a better control on the visualization. Therefore, there is a need for an open source tool capable of converting 3D geospatial data into 3D Tiles to visualize them on the web, but also to test and develop new methods of spatial clustering and creating Levels of Detail (LoD) of urban objects. We propose Py3DTilers in this paper, an open source tool to convert and manipulate 3D Tiles from the most common 3D geospatial data models: CityGML, IFC, OBJ, and GeoJSON. With this tool, we ensure that the generated 3D Tiles respect the specification described by the OGC, in order to be used in various viewers. We provide a generic solution for spatially organizing objects and for creating LoDs, while allowing the community to customize these methods to go further in finding efficient solutions for visualizing geospatial objects on the web.
DEVELOPMENT OF DETAILED BUILDING DISTRIBUTION MAP TO SUPPORT SMART CITY PROMOTION -AN APPROACH USING SATELLITE IMAGE AND DEEP LEARNING–
Authors: Okada K. , Nishiyama N. , Akiyama Y. , Miyazaki H. , Miyazawa S.
Published: October 2022

Abstract. Detailed demographics play an important role in the development of smart cities. However, especially in developing countries, the maintenance and management of this data is incomplete, which hinders the promotion of smart cities. The objective of this study is to develop a method to create detailed building distribution maps from satellite images, which will serve as a basis for developing detailed demographic data to support the promotion of smart cities around the world. The target area is several areas of Tokyo where validation data is available. We first developed a method for extracting buildings from satellite images and then estimating the building use to determine the buildings where residents are distributed. Both methods use deep learning. As a result, it was possible to extract buildings with an extraction rate (the number of buildings in the automatically extracted building data divided by the number of buildings in the data for verification) of up to 60.3% for the entire target area. In addition, in the estimation of building use, our method was able to classify detached and non-detached buildings with an average accuracy of 78.7% for the entire target area.
SMART CITIES – SYSTEMS OF SYSTEMS INTEROPERABILITY AND OGC ENABLERS
Authors: Atkinson R. A. , Zaborowski P. , Noardo F. , Simonis I.
Published: October 2022

Abstract. The concepts of smart cities and digital twins are more and more investigated and accepted as critical tools for the cities of the future. In order to make them a concrete reality, several aspects related to the management of data have to be considered: technical issues to collect, retrieve, exchange, analyse and process data; data sovereignty issues; data semantics, features and metadata specifications. In current projects and higher level frameworks specifications, some of these issues are explored and solutions are proposed for subset of them. However, an overall framework connecting those aspects in a unique model has not been defined and tested yet. In this paper, we propose a reference model to build an interoperable system of systems supporting the implementation of smart cities and digital twins. We start from reviewing current experiences and in particular considering the OGC standards and initiatives intended to provide Open solutions for specific parts of the framework.
USING REMOTE SENSING AND BIG DATA TO ANALYSIS DIRECT SOLAR RADIATION IMPACTS ON THE SPREAD OF COVID-19 (CASE STUDIES: SIX STATES OF THE UNITED STATES)
Authors: Veisi O. , Mohammadi M. , Behnamifard F.
Published: October 2022

Abstract. The COVID-19 virus and its outbreak were among the most considered research areas in different science branches throughout last year. Meanwhile, some extensive studies have been conducted on the factors influential in increasing the infection rate. The present study examines the relationship between two sets of factors. Firstly, the rate of infection with the virus and the ways it spreads are considered. Secondly, one of the most important climatic factors (direct solar radiation and radiation duration) is studied. This study aims to examine the relationship between these factors and the infection rate with COVID-19 in the six selected U.S. states, including Arizona, California, Colorado, Nevada, New Mexico, and Utah, which receive the maximum radiation and whose population density is at a high level. In order to conduct this study, the analysis of big data and referring to the United States Geological Survey (USGS) have been implemented. This quantitative study is based on analyzing satellite data in the GIS and R software applications. Generally, the research comprises three phases. Firstly, it produces data. Secondly, it examines the satellite images. Finally, it explores and analyses data via sampling techniques and regression tests. The results of this study have revealed that direct solar radiation and density are significantly related to the spread of COVID-19. In the case of radiation duration, investigations show that this variable does not influence the spread of the COVID-19 virus.
EVALUATING THE PERFORMANCE OF HIGH LEVEL-OF-DETAIL TREE MODELS IN MICROCLIMATE SIMULATION
Authors: Xu H. , Wang C. C. , Shen X. , Zlatanova S.
Published: October 2022

Abstract. Present urbanization influences urban morphology by the increasing number of dense buildings and infrastructure, which effects climate change. Microclimate simulations including urban vegetation help in mitigating climate change. Most of existing microclimate simulations simplify trees and thereby may introduce some erroneous estimates. Tree models of high levels of detail (LOD) can provide a more accurate measure. Technology advances make it possible to reconstruct detailed tree models, which can be further used in microclimate simulations. However, the few studies presenting detailed tree models focus predominantly on the reconstruction process and omit the microclimate simulations. The objective of this study is to investigate high LOD tree models in microclimate simulation to estimate the potential gain in accuracy. This study focuses on voxel-based tree models and microclimate simulations using computer fluid dynamics software. A series of microclimate simulations are completed in two scenarios, which are single tree and a set of trees with buildings. Based on the simulation results, the advantages of detailed voxel tree models are demonstrated. Final discussion elaborates on the needed and preferred levels of detail for tree models.
PUBLIC SPACES UNDER THE SMART CITIES PARADIGM IN INDIA
Authors: Das I. , Praharaj S.
Published: October 2022

Abstract. Rapid urbanization in the emerging economies leads to immense pressure on existing amenities and urban services, and hence the congregation of smart technologies, with efficient data-driven solutions are a desirable requisite for a better quality of life, thus forming the basis of Smart cities. The concept of a smart city is multi-dimensional and is a mix of multiple factors and indicators that constitute the core concept of sustainability. One of the key indicators of a smart city is active public spaces and their consolidated wholesome implications on well-being. Hence, addressing the consequences of smart city initiatives, with respect to the access to the public realm to engage, interact, share, and recreate, through extensive literature review and case-based study seemed of prime importance. This paper attempts to unpack the smart city paradigm in India, in conjunction with aspects of social sustainability, technological interventions, and the on-ground reality while learning about their implications on the quality of life, specifically, in the case of the marginalized groups. The literature review and case-based study of three Indian smart cities, namely New Delhi, Indore, and Bhopal have opened possibilities for the identification of factors responsible for the smartness of public spaces and a realization of the extent to which theoretical concepts translate from paper to ground realities, and their immediate implications on the ‘informal’ aspects and groups of our society.
AUTOMATIC DETECTION AND DIMENSIONAL MEASUREMENT OF MINOR CONCRETE CRACKS WITH CONVOLUTIONAL NEURAL NETWORK
Authors: Guo Y. , Wang Z. , Shen X. , Barati K. , Linke J.
Published: October 2022

Abstract. The increasing number of aging infrastructures has drawn attention among the industry as the results caused by critical infrastructure failure could be destructive. It is essential to monitor the infrastructure assets and provide timely maintenance. However, one of the crucial problems is that the budget allocated to the maintenance stage is much less than that for the designing and construction stages. The cost of labor, equipment, and vehicles are significant. Therefore, it is impossible to perform a thorough inspection by human inspectors over each asset. A more efficient method will be needed to solve this problem. This paper aims to provide an automatic approach to detecting and measuring the dimensions of minor cracks that appear on concrete structures with a noisy background. This research also investigates the relationship between image pixel size, accuracy, detection rate of cracks, and shooting distance of images. The proposed method will be able to reduce the cost and increase accuracy. A case study was performed on a concrete sewer with cracks distributed on the surface in Sydney, New South Wales, Australia.
OPTIMIZING URBAN MONITORING BETWEEN STATIONARY, OPPORTUNISTIC VEHICULAR, AND HYBRID SENSING
Authors: Hu W. , Winter S. , Khoshelham K.
Published: October 2022

Abstract. Urban monitoring based on wireless sensor networks is a recent paradigm that exploits a large number of low-cost sensors deployed in certain places or/and on mobile devices to collect data ubiquitously at a large scale. In this study, we explore and compare the coverage of stationary and opportunistic vehicular sensing methods with respect to the requirements of a task at hand. We distinguish spatial granularity, temporal granularity, and budget constraints. First we compare the spatio-temporal coverage of stationary sensing and opportunistic vehicular sensing for various tasks, which demonstrates that these two sensing methods are suitable for different tasks. Then we propose a hybrid sensing deployment framework integrating a genetic algorithm to achieve the maximum spatio-temporal coverage for specific tasks. Experiments with a real-world vehicle trajectory dataset demonstrate that the proposed hybrid sensing framework achieves the maximum spatio-temporal coverage in various tasks. Our results provide fundamental guidelines on network planning for urban monitoring applications.
APPLYING VERSIONING TO MULTI-LOD 3D CITY MODELS
Authors: Vitalis S. , Arroyo Ohori K. , Stoter J.
Published: October 2022

Abstract. Level of Detail (LoD) is a well known concept in 3D city models, used to designate different geometric detail that can be used in different applications. Nevertheless, multi-LoD datasets are hard to maintain and manage because of their intrinsic complexity. Versioning is a solution that aids in the storage and management of big and complex dataset, with its main goal being to facilitate the tracking of changes and collaboration. In this paper, we investigate the effects of utilising versioning and, more specifically, the concept of branches as a way to manage the evolution of multi-LoD datasets. We propose a framework according to which every LoD is stored in its own branch and can be extracted and updated independently. We tested this framework on a tile from 3D BAG, a dataset of 3D buildings for the whole of the Netherlands containing four LoDs (namely, LoD0, LoD1.2, LoD1.3 and LoD2.2). Our results suggest that there are certain benefits from this solution, such as the efficient tracking of changes for individual LoDs and the ability to extract and update the model using one LoD at a time. Nevertheless, there is a lot of complexity added to the process as a set of rules needs to be enforced when managing the model.
RESIDENT'S SATISFACTION IN STREET LANDSCAPE USING THE IMMERSIVE VIRTUAL ENVIRONMENT-BASED EYE-TRACKING TECHNIQUE AND DEEP LEARNING MODEL
Authors: Han J. , Lee S.
Published: October 2022

Abstract. Virtual reality technology provides a significant clue to understanding the human visual perception process by enabling the interaction between humans and computers. In addition, deep learning techniques in the visual field provide analysis methods for image classification, processing, and segmentation. This study reviewed the applicability of gaze movement and deep learning-based satisfaction evaluation on the landscape using an immersive virtual reality-based eye-tracking device. To this end, the following research procedures were established and analysed. First, the gaze movement of the test taker is measured using an immersive virtual environment-based eye tracker. The relationship between the gaze movement pattern of the test taker and the satisfaction evaluation result for the landscape image is analysed. Second, using the Convolutional Neural Networks (CNN)-based Class Activation Map (CAM) technique, a model for estimating the satisfaction evaluation result is constructed, and the gaze pattern of the test taker is derived. Third, we compare and analyse the similarity between the gaze heat map derived through the immersive virtual environment-based gaze tracker and the heat map generated by CAM. This study suggests the applicability of urban environment technology and deep learning methods to understand landscape planning factors that affect urban landscape satisfaction, resulting from the three-dimensional and immediate visual cognitive activity.
3D RECONSTRUCTION OF SIMPLE BUILDINGS FROM POINT CLOUDS USING NEURAL NETWORKS WITH CONTINUOUS CONVOLUTIONS (CONVPOINT)
Authors: Kada M.
Published: October 2022

Abstract. The automatic reconstruction of 3D building models from airborne laser scanning point clouds or aerial imagery data in a model-driven fashion most often consists of a recognition of standardized building primitives with typically rectangular footprints and parameterized roof shapes based on a pre-defined collection, and a parameter estimation so that the selected primitives best fit the input data. For more complex buildings that consist of multiple parts, several such primitives need to be combined. This paper focuses on the reconstruction of such simple buildings, and explores the potential of Deep Learning by presenting a neural network architecture that takes a 3D point cloud of a single building as input and outputs the geometric information needed to construct a 3D building model in half-space representation with up to four roof faces like saddleback, hip, and pyramid roof. The proposed neural network architecture consists of a roof face segmentation module implemented with continuous convolutions as used in ConvPoint, which performs feature extraction directly from a set of 3D points, and four PointNet modules that predict from sampled subsets of the feature-enriched points the presence of four roof faces and their slopes. Trained with the RoofN3D dataset, which contains roof point segmentations and geometric information for 3D reconstruction purposes for about 118,000 simple buildings, the neural network achieves a performance of about 80% intersection over union (IoU) for roof face segmentation, 1.8° mean absolute error (MAE) for roof slope angles, and 95% overall accuracy (OA) for predicting the presence of faces.
INTEGRATION OF GEOSPATIAL AND CITIZEN PARTICIPATION USING GEOGRAPHIC INFORMATION SYSTEM FOR SMART CITY: A STUDY OF PRIORITY VILLAGES PROGRAM IN JAKARTA, INDONESIA
Authors: Anugraha A. S. , Erdiza H. P. , Apriyadi D. , Aguscandra B.
Published: October 2022

Abstract. Jakarta, the capital city of Indonesia, is the city with the largest population in Indonesia with a population of 10,609,681. In line with the rapid growth and the increment of the population in Jakarta lead to the increment in the number of buildings in Jakarta. However, the building increment in Jakarta leads to the emergence of buildings ownership problems. Meanwhile, the increasing urbanization promotes the need for a system that accommodates the smart city concepts which require complex interactions between governments and citizens. Therefore, the Jakarta Provincial Government established a breakthrough program called Priority Villages, a program that integrates geospatial and citizen participation using the Geographic Information System (GIS) for the smart city planning model. This program focused on the distribution acceleration of building establishment decision letters. This research aims to visualize the concept and advantages of the Priority Village program as an analysis-oriented application for the development of intelligent city concepts. The outputs of the Priority Villages program are the issuances of 112 building establishment decision letters per region and 7,534 building establishment decision letters per individual building. The integration of geospatial and citizen participation using Geographic Information System (GIS) in Priority Villages program strongly supports the sustainability of the Jakarta Smart City program, shortening the Estimated Time of Arrival (ETA) of the building establishment decision letter making from 16 days to 7 days and give the positive impact on the broader citizen in Jakarta.
CONDITIONS THAT INFLUENCE USERS TO SHARE MEDICAL INFORMATION VIA CONSUMER APPLICATIONS. AN EVIDENCE FROM ISRAEL HEALTHCARE SECTOR
Authors: Katz T. , Grimaldi D.
Published: October 2022

Abstract. Data-driven technologies are being greatly adopted in healthcare in order to create a better ecosystem of health for citizens in the development of smart cities. As we develop smart devices and services, there are growing concerns in the population's perception around privacy concerns in using these devices and services, and the necessity to share their medical sensitive information is often perceived as a holdback. The following study goal is to develop a model to better understand the conditions affecting privacy concerns in medical devices and services. Using primary research to test the suggested model using secondary research methods, and data analysis tools using python program with pandas library and ANOVA statistics. The solution proposed can offer a methodology for building health services in smarter and more connected cities.
Morbimortality Analysis of Diabetic Ketoacidosis in a Second Level Hospital in Mexico
Authors: Rodrigo Durán Alvarado , Adrián Maldonado Mancillas Jesús , Alejandra Landeros Sáenz , Alberto Tinoco Álvarez Mario
Published: October 2022

Background: Diabetic ketoacidosis (DKA) is a very frequent entity that presents as an acute complication of diabetes mellitus, in which there is a state of hyperglycemia, metabolic acidosis and ketosis. Acute complications of diabetes represent a high percentage of admissions to the emergency department of second level hospitals in Mexico. Methods: This is a retrospective, observational, comparative, cohort and descriptive study with documented analysis technique. We obtained information from a diary of records of the intensive care unit of our hospital and included all patients older than 14 years with a diagnosis of diabetic ketoacidosis. Patients younger than 14 years were excluded as well as hyperosmolar states. Results: Of the 1725 patients admitted to the ICU only 134 had diabetic ketoacidosis; 91% of which were of metabolic origin; 3 patients had acute pancreatitis, and complications were equal to 0.7%, being acute renal injury, urosepsis, preeclampsia and pneumonia. The most frequent age group was between 20 and 30 years old, while mortality was 10%. The incidence of diabetic ketoacidosis was more frequent in the male sex in contrast with the study of Li et al who report a predominance in the female sex. In the age group we agree with Ramphul et al. who determine an average age of 18 to 44 years in the U.S. population. Therefore, we take into account that our casuistry in Mexico is partially similar and that the tendency of diabetic ketoacidosis has been greater in the male population, as well as an increased mortality. Conclusions: In this study involving patients with diabetic ketoacidosis, the incidence and mortality tend to be increasing in our hospital and is that related to economic and sociocultural factors given the fact that our country and hospital of origin is in the means of development.
Acute Effects of Different Intensity and Duration of Static Stretching on the Muscle-Tendon Unit Stiffness of the Hamstrings
Authors: Takeuchi Kosuke , Akizuki Kazunori , Nakamura Masatoshi
Published: October 2022

The effects of static stretching are influenced by prescribed and applied loads of stretching. The prescribed load is calculated from the stretching duration and intensity, whereas the applied load is assessed from the force of static stretching exerted on the targeted muscle. No previous study has investigated the prescribed and applied loads of static stretching on the muscle-tendon unit stiffness simultaneously. Therefore, the purpose of the present study was to examine the acute effects of the prescribed and applied load of static stretching on the change in the muscle-tendon unit stiffness of the hamstrings by using different intensities and durations of static stretching. Twenty-three participants underwent static stretching at the intensity of high (50 seconds, 3 sets), moderate (60 seconds, 3 sets), and low (75 seconds, 3 sets), in random order. The parameters were the range of motion, passive torque, and muscle-tendon unit stiffness. These parameters were measured before stretching, between sets, and immediately after stretching by using a dynamometer machine. The static stretching load was calculated from the passive torque during static stretching. The muscle-tendon unit stiffness decreased in high- and moderate-intensity after 50 (p < 0.01, d = -0.73) and 180 seconds (p < 0.01, d = -1.10) of stretching respectively, but there was no change in low-intensity stretching for 225 seconds (p = 0.48, d = -0.18). There were significant correlations between the static stretching load and relative change in the muscle-tendon unit stiffness in moderate- (r = -0.64, p < 0.01) and low-intensity (r = -0.54, p < 0.01), but not in high-intensity (r = -0.16, p = 0.18). High-intensity static stretching was effective for a decrease in the muscle-tendon unit stiffness even when the prescribed load of static stretching was unified. The applied load of static stretching was an important factor in decreasing the muscle-tendon unit stiffness in low- and moderate-intensity static stretching, but not in high-intensity stretching.
APPROACHES TO THE EVOLUTION OF THE SOCIAL CONTEXT THROUGH THE LENS OF THE SOCIAL INSURANCE BUDGET EFFORT IN ROMANIA. REALITIES AND PERSPECTIVES
Authors:   Stefan cel Mare University of Suceava, Romania, Sorici Monica-Laura , Mihaila Svetlana ,   Academy of Economic Studies of Moldova, Grosu Veronica ,   Stefan cel Mare University of Suceava, Romania
Published: October 2022

The social context in Romania is determined by the issue of the degree of social security, through the budgetary effort in a context of rising inflation and elements of geo-political instability manifested by recession and social insecurity, especially for the low-income population. The objective of the study is to identify the current situation affecting the social status of citizens in Romania and the prospects for its evolution by introducing a social security index based on statistical and econometric forecasting methods. The methods used are of an empirical nature represented by the study of the specialized literature and of an analytical nature, respectively the consolidation of databases, econometric modelling, prospective analysis and economic forecasts. The results of the study are useful for national decision-makers in order to adjust social policy elements in line with the sustainability objectives agreed at European level and in relation to the growing needs of the population at risk of poverty, continuing inflation and economic recession.
SOUTH AFRICA’S STRUCTURAL UNEMPLOYMENT OF WOMEN AND YOUTH: AN ANALYSIS OF THE EXPANDED PUBLIC WORKS PROGRAMME MODEL
Authors:   University of Pretoria, South Africa, Sibanda Nomazulu , Thebe Vusilizwe ,   University of Pretoria, South Africa
Published: October 2022

This paper presents an analysis of the Expanded Public Works Programme (EPWP), one of the key South African government policy initiatives that are meant to ease the burden of poverty or unemployment on the poor and unskilled. Historically, such programmes have been used as a relief during short-term crises. Of late, countries have adopted them for long-term structural challenges. In South Africa the programme is meant to protect women and youth. This paper uses a mixed methodology approach to determine the active participation of women and youth in the EPWP and their chances of transitioning into the labour market. The study also solicited the views of the EPWP participants (active and former) and officials to get information which is not captured in the programme’s official reports. The analytical procedure involved document analysis, focusing on EPWP reports from phases One (1) to Three (3) of the programme. The study makes two propositions: the need for public private partnerships to solve the country’s unemployment challenge because independent policies for government or markets are inadequate; a new programme design which separates job seekers from social protection beneficiaries. In its current form, the EPWP is designed as a lower tier poverty trap.
WHAT IS SOCIAL INTELLIGENCE?
Authors:   Swiss Technology Association, Electronics Group, Switzerland, Bajenescu Titu-Marius
Published: October 2022

The article analyses a social problem with a major impact on the development of society, the macroeconomics, but also on each individual. The ability of some people to understand the behaviours, thoughts, and feelings of others and to interact effectively with them is called social intelligence. Also called interpersonal intelligence, it is closely related to emotional intelligence. Emotional intelligence is a person’s ability to understand and control their own emotions, as well as the ability to deal with those of others. Although complicated to measure, these two forms of intelligence are particularly useful in everyday life: family or friends, married life, professional life…
DEMOCRACY AND ECONOMIC GROWTH:THE CASE OF MOLDOVA
Authors:   Presidency of the Republic of Moldova, Pavliuc Cristina , Buga Alexandru ,   Technical University of Moldova
Published: October 2022

This article addresses the issue of the cause-and-effect relationship between democracy and economic growth in Moldova from 1990 to 2020. This problem is one of the key topics of modern economic political science, but the results concerning the influence of the political system on economy are still ambiguous. No research has been conducted to date on this issue for Moldova. The econometric analysis was conducted using tree composite indexes of democracy, published by Freedom house, Polity V and V-Dem Varieties of Democracy. The causal impact between democracy indexes and per capita GDP growth is tested using Granger causality analysis. The results show that the choice of the democracy indicator and the time interval influences the modeling outcome. All three democracy indices depict different democratic trends at the country level. Although there is a positive causal link between the Polity index and GDP per capita in a short period, other results show no evidence that democratic reforms did contribute to economic growth in Moldova and vice versa. We conclude that democratization in conditions of weak law and political instability contributed to the emergency of a so-called hybrid democracy in Moldova.
Echoes of Our Favourite Childhood Figures
Authors: Griszbacher Norbert , Kemény Ildikó , Varga Ákos
Published: October 2022

Since its founding, Disney has become the symbol of values such as joy, magic, entertainment, and family in our lives through loveable stories, characters, and unique experiences. Disney also has had a significant impact on youth culture with its ability to appeal to universal human experiences through its versatile character portfolio. Disney's recent tendency to reproduce their earlier success in modern adaptations (e.g., The Little Mermaid and Snow White coming in 2023) is the focus of this paper. It aims to examine the influence of Disney's representation of the mechanisms of our world on youth character development by comparing the responses given for the ‘classic’ and the ‘modern’ versions. For this reason, in addition to explicit measures (survey), an Implicit Associations Test (IAT) was used to discover those attitudes which would generally be hidden from explicit methods of analysis due to their subversive nature (e.g., deep affective content like nostalgia). The analysis revealed a significant correlation between IAT-measured implicit attitudes and explicit measures of attitudes and behaviour toward modern and classic (our target) categories. The results also indicate the significance of these scenes (especially the childhood ‘classic’ ones) as they can form strong bonds with the young audience, affecting their preferences, values, worldview, and, thus, their character development.
Capítulo 1. La alfabetización mediática e informacional en la educación formal: un reto necesario
Authors: Francisco Amat Andrea , Pallarés Piquer Marc , Abellán Fabrés Gemma , Farné Alessandra
Published: October 2022

El objetivo de este capítulo es abordar la relevancia de la Alfabetización Mediática e Informacional (AMI), especialmente entre la juventud. Para ello, el texto comienza respondiendo a qué entendemos por AMI y al por qué y para qué es necesario incluirla dentro del sistema educativo formal del siglo XXI. En un segundo apartado nos centraremos en el contexto donde ubicamos nuestra propuesta: el sistema de educación formal de la juventud en el estado español.  Analizaremos cómo se está abordando la competencia informacional y mediática en los niveles de educación secundaria y bachillerato y cuáles son los retos de los centros educativos, del estudiantado y del profesorado.
Palabras clave: alfabetización mediática e informacional, educación, revisión conceptual, evolución histórica, juventud, competencia informacional, competencia mediática, educación formal.
Capítulo 6. Medios de comunicación y educación. La necesidad de la Educomunicación en la formación universitaria española
Authors: Elías Zambrano Rodrigo , Barrientos Bueno Mónica , Ramírez Alvarado Maria del Mar
Published: October 2022

El presente capítulo propone una reflexión general sobre las distintas perspectivas y aplicaciones de la Educomunicación audiovisual, incidiendo en el valor que ha de tener en la formación universitaria, partiendo de la experiencia desarrollada por sus autores tanto en el ámbito académico como en el profesional.

Palabras clave: Educomunicación, audiovisual, universidad, sociedad digital, educación, comunicación.
Capítulo 8. Tendencias en la producción científica iberoamericana sobre alfabetización informacional y mediática
Authors: Pinto María , Uribe Tirado Alejandro
Published: October 2022

En los últimos años se ha comenzado a publicar artículos tanto teóricos, teóricos-prácticos como aplicados que pretenden desarrollar la integración entre la alfabetización informacional y la alfabetización mediática. Basado en una revisión temática de la literatura desde el año 2009 a 2020 en el contexto iberoamericano, este capítulo pretende analizar esa producción e identificar las principales tendencias y perspectivas.

Palabras clave: alfabetización informacional, alfabetización en medios, alfabetización mediática, multialfabetismo, Iberoamérica, estado del arte.