bluuebunny/crossref_metadata_2025 huggingface dataset:
Determinants of out-of-Pocket Healthcare Expenditure by Households in Sierra Leone
Authors: Chikhata, PhD Frank
Published: October 2024

The study sought to identify the determinants that influence Sierra Leonean households’ out-of-pocket healthcare expenditure. The research explicitly examined the demographic and socioeconomic determinants that impact out-of-pocket healthcare expenditure by households in Sierra Leone. The study was based on the positivism philosophy and used secondary data from the 2018 Siera Leone Household Integrated Survey to address the study objectives. Logistic regression analysis was conducted to see whether there were any relationships between the dependent and independent variables. The analysis revealed that Sierra Leone’s out-of-pocket healthcare expenditure is influenced by several demographic and socio-economic determinants which should be monitored by the policymakers. Sierra Leone households’ out-of-pocket healthcare expenditure is influenced by the household size (p < 0.001), place of residence (p=0.03), employment status of the head of household (p=0.008), health provider consultation (p <0.001) and wealth quintile (p<0.001). The government should continue to identify and address the main causes of high OOP healthcare expenditure. A concerted effort is necessary to reduce high out-of-pocket health expenditures by improving prepaid health payment arrangements. The study provides information that governments may use to establish policies that reduce the financial burden that families endure when seeking medical care. To address structural determinants of access to healthcare, such as availability, distribution, accessibility, and quality, regardless of an individual’s location or socioeconomic status, the government could implement policies and activities aimed at increasing the availability, accessibility, and quality of healthcare services without the households suffering financial burden. The study encountered limitations inherent in the use of secondary data; however, these constraints do not undermine the validity of the findings. Such estimations remain crucial in advancing research on healthcare financing, providing valuable insights despite the methodological challenges associated with secondary data sources.
Relación entre variables de combustibles y radiación solar en un bosque de Pinus hartwegii Lindl. y un zacatonal en el Parque Iztaccíhuatl-Popocatépetl
Authors: Rodríguez-Trejo Dante A.
Published: October 2024

Introducción. Los estudios de combustibles brindan información sobre peligro de incendio, comportamiento del fuego, emisiones de gases de invernadero y manejo de combustibles.
Objetivo. Establecer relaciones entre variables de combustibles, índice de área foliar y radiación solar que permitan estimar cargas de combustibles en una masa de Pinus hartwegii Lindl. y un zacatonal subalpino en el Parque Nacional Iztaccíhuatl-Popocatépetl.
Materiales y métodos. Se muestrearon combustibles (carga, cobertura, altura o profundidad), arbolado (variables dasométricas) y radiación solar (difusa, directa, total y fracción de cielo visible). Las relaciones entre variables se establecieron con regresión lineal, considerando coeficiente de determinación, significancia, normalidad, homocedasticidad, multicolinealidad y autocorrelación. Resultados y discusión: En el bosque, la carga media fue de 27.9 Mg∙ha-1  con casi 60 % de hojarasca y capa de fermentación. Existen relaciones directas entre cobertura de zacates y fracción de cielo visible; carga de materiales leñosos e índice de área foliar; y carga total de combustibles con la profundidad de la capa de hojarasca y fermentación. Condiciones con más  radiación  propician mayor carga de zacates, mientras que la radiación baja facilita acumulación de materiales leñosos y hojarasca y capa de fermentación. En el zacatonal, la carga alcanzó 6.8 Mg∙ha-1 y hubo relación directa entre su carga total y cobertura.
Conclusiones. En el bosque de P. hartwegii y en el zacatonal se obtuvieron modelos estadísticos que relacionan cargas de combustibles forestales con variables de radiación o con variables propias de los combustibles, lo cual agiliza estimaciones y sustenta decisiones para el manejo de estos.
Practical Implications of Structural Design of a Two-Span Rc Beam -Column Structure with Unequal Spans
Authors: Samuel Nwokoye Ogonna
Published: October 2024

The structural design of reinforced concrete (RC) beam-column systems with unequal spans poses unique challenges, especially when one span is significantly longer than the other. This paper explores the practical implications of designing a two-span RC beam-column structure where one span is at least three times longer than the other. The study highlights the key considerations in terms of load distribution, deflection control, reinforcement detailing, and the potential for differential settlement and vibrations. This research draws on Eurocode standards for design, provides an analysis of various load cases, and discusses practical solutions for ensuring structural integrity and serviceability.
Stability and Bifurcation Analysis of Measles Model
Authors: Adeboye O. A. , Odebiyi O. A , Oladejo J. K. , Elijah E.O. , Taiwo A. A. , Olajide O. A.
Published: October 2024

A six compartmental deterministic mathematical model, governed by a system of ordinary differential equations for measles was formulated in other to study and analyze the transmission dynamics of measles in human population. The model was shown to be mathematically and epidemiologically meaningful. The basic reproduction number of the model was obtained and global stability of the disease-free equilibrium and endemic equilibrium were obtained and shown to be asymptotically stable, whenever the basic reproduction and unstable if otherwise. More so, if then the endemic equilibrium of the model equation is globally asymptotically stable The effect of some parameters of the model relatives to the basic reproduction number was calculated using the normalized forward sensitivity indices, and it was shown that increase in the parameters with negative indices will reduce the value of the basic Reproduction number, while increase in those with positive indices will increase the value of basic reproduction number. The bifurcation analysis was also carried out and the model was shown to exhibit backward bifurcation which indicates that is no longer sufficient for effective disease control. The numerical result shows that isolation of infective plays a major role in reducing the transmission of the disease in the population.
Editorial
Authors: Linjamaa Paul
Published: October 2024

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Imagining Science
Authors: Nongbri Brent
Published: October 2024

Disagreement about the trans-cultural applicability of the concept of religion has been a feature of the academic study of religion for decades. In a series of recent essays, Kevin Schilbrack has powerfully reframed these discussions as a debate between realist and antirealist philosophical orientations. Aligning himself with Critical Realism, Schilbrack argues that religion is a transcultural and transhistorical reality and that those who deny this are antirealists. As my own work is among his targets, this article engages Schilbrack's critique. The first part of the article challenges some of Schilbrack's readings of Before Religion. The second part queries Schilbrack's use of examples from the physical sciences as analogies for the relationship between concepts and the real things they are said to designate. The third part models an alternative use of examples from the natural sciences to think about historiography, concluding that the realist/antirealist dichotomy is not a useful tool. The physics of the last 150 years has shown that our most fundamental ideas about the universe – what we think the "real" character of the world might be – can change radically in short intervals of time. Historians should take heed and approach their own engagement with the traces of the past with due humility.
“Wenn es nur einmal so ganz stille wäre...”
Authors: Guggenmos Esther-Maria
Published: October 2024

This article is a revised version of the inaugural lecture delivered on 5 October2023, on the occasion of the author's appointment as Professor of History of Religions at Lund University. It opens by depicting fundamental changes in the study of the history of religions in the twentieth century, followed by biographical notes, including her research on lay Buddhism in urban Taiwan, the emphasis on sensual dimensions of religious practice and the aesthetics of religion, and international academic networking in the analysis of practices of prognostication between Asia and Europe. Three areas are outlined that are central to the author's current research. It is pointed out that a focus on religion in contemporary society certainly includes a healthy awareness of current developments in the politics of religion, particularly in East Asia. In addition, the article addresses two fields of research that the author is currently engaged in: (1) The emergence of "Life Education" as a school subject in Greater China and the pedagogical shift that goes along with it. Particularly in Taiwan, this new subject is tailored to create a space for juveniles to develop self-reflection and life orientation in a success-oriented society while a new trust in religious organizations leads to the organizations' active engagement in these developments. The author is especially interested in how the transforming relationship between religion and public education gains special relevance in a comparative perspective between Asia and Europe. (2) Religious change in East Asia is evident in Buddhist ritual practices that are impacted by a consumer society that moulds emotionally profound experiences into marketable and distinct units that Eva Illouz has termed "emodities". Religious practices are subject to change in our contemporary world as they are reshaped by a growing global digitalized consumer culture. Tracing these changes leads to a deeper understanding of the underlying forces that distinctly reshape contemporary religious life.
Erik Aurelius, Jesu liknelser
Authors: Evertsson Magnus
Published: October 2024

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Victoria S. Harrison & Tyler Dalton McNabb (red.), Philosophy and the Spiritual Life
Authors: Cejvan Ervik
Published: October 2024

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Corruption and emigration from the Western Balkans: evidence from a dynamic system GMM model (2012-2022)
Authors: Malaj Visar , Malaj Emi
Published: October 2024

According to neoclassical models, migration takes place when there is a strong probability that individuals will recoup their human capital investments. As a result, workers typically move from low-income to high-income areas and the larger the expected income gap between areas, the higher the number of migrants. In countries where corruption is endemic, jobs are often secured through political connections and bribes. This will lead to a higher unemployment level as well as to a lower return to human capital. Consequently, a significant proportion of the population considers emigration as the only path to succeed. The present study is focused on the impact of corruption on emigration from six Western Balkan countries. A System Generalized Method of Moments is estimated to analyze migrant stocks in 28 receiving countries during the period from 2012 to 2022. We suggest that corruption can directly influence migration stocks in receiving countries.
PENGARUH LINGKUNGAN SOSIAL TERHADAP PROSES BELAJAR PESERTA DIDIK DI MA AL MAHDI PABUARAN
Authors: HERIANSYAH DEVI ANGGARA , SIROJUDIN RUMBANG , FATURACHMAN NANANG , WASEHUDIN WASEHUDIN , LAZZAVIETAMSI FANDY ADPEN
Published: October 2024

The purpose of this study is to determine the influence on the social environment on the learning process of students, especially at MA Al Mahdi Pabuaran. The social environment should not be underestimated, because it has the potential to significantly affect the learning process of students. The importance of a conducive social environment significantly affects students' learning activities. This study uses an approach with triangulation techniques to test the validity and reality of data in investigating the influence of the social environment on the learning process of students at MA Al Mahdi Pabuaran. By conducting interviews and data collection which involves analyzing various literary repositories from various literature. The findings of this study show that the social environment in grades has an impact on the learning process of students at MA Al Mahdi Pabuaran. The social environment has a direct impact both on the low level of the learning process and the cognitive or affective field of the learner. The environment has an important role in the learning process, acting as a powerful learning resource that can improve the development of students and can improve their learning process and outcomes. This research also offers a more comprehensive understanding of the importance of investigating the social environment about the learning process and achievement of students, especially in MA Al Mahdi Pabuaran.
ABSTRAKTujuan studi ini ialah untuk menentukan Pengaruh pada lingkungan Sosial pada proses belajar peserta didik, khususnya di MA Al Mahdi Pabuaran. Lingkungan sosial tidak boleh diremehkan, karena memiliki potensi untuk mempengaruhi proses belajar peserta didik secara signifikan. Pentingnya lingkungan sosial yang kondusif secara signifikan mempengaruhi kegiatan belajar peserta didik. Penelitian ini menggunakan pendekatan dengan teknik triangulasi untuk menguji validitas dan realibilitas data dalam menyelidiki pengaruh lingkungan soaial terhadap proses belajar siswa di MA Al Mahdi Pabuaran. Dengan melakukan wawancara dan pengumpulan data yang melibatkan analisis berbagai repositori sastra dari berbagai literatur. Temuan penelitian ini menunjukkan bahwa lingkungan sosial di nilai memiliki dampak pada proses belajar peserta didik di MA Al Mahdi Pabuaran. Lingkungan sosial memiliki dampak langsung baik pada tingkat yang rendah dari proses belajar dan bidang kognitif atau afektif peserta didik. Lingkungan memiliki peran penting dalam proses belajar, bertindak sebagai sumber daya belajar yang kuat yang dapat meningkatkan perkembangan peserta didik dan dapat meningkatkan proses serta hasil mereka belajar. Penelitian ini juga menawarkan pemahaman yang lebih komprehensif tentang pentingnya menyelidiki lingkungan sosial tentang proses dan prestasi belajar peserta didik, khususnya di MA Al Mahdi Pabuaran.
ANALISIS KOMPETENSI PEDAGOGIK GURU PAI DI SEKOLAH DASAR NEGERI SE-KECAMATAN PABUARAN KABUPATEN SERANG
Authors: MA’MUR ILZAMUDIN , HERIANSYAH DEVI ANGGARA , HILMIYATI FITRI , WASEHUDIN WASEHUDIN
Published: October 2024

The aim of this study is to analyze the pedagogical competence of PAI teachers in State Elementary Schools in Pabuaran District, Serang Regency. This research uses a triangulation approach that tests the validity and reality of data in analyzing the pedagogical competence of PAI teachers in State Elementary Schools in Pabuaran District, Serang Regency. By conducting interviews and collecting data which involves analyzing various literary repositories from various literature. The findings of this study show that the pedagogical competence of PAI teachers in State Elementary Schools in Pabuaran District is very good in understanding the characteristics of students, in mastering learning theories and principles, in developing curriculum, in organizing learning, in utilizing technology, in facilitating the development of participants' potential. students, in communicating with students, in carrying out assessments and evaluations, in utilizing the results of assessments and evaluations and carrying out reflective actions to improve the quality of learning. This study also offers a more comprehensive understanding of the importance of pedagogical competence for PAI teachers in State Elementary Schools in Pabuaran District.
ABSTRAKTujuan dari studi ini ialah untuk menganalisis bagaimana kompetensi pedagogik guru PAI di Sekolah Dasar Negeri Se-Kecamatan Pabuaran Kabupaten Serang. Penelitian ini menggunakan pendekatan triangulasi yang menguji validitas dan realibitas data dalam menganalisis kompetensi pedagogik guru PAI di Sekolah Dasar Negeri Se-Kecamatan Pabuaran Kabupaten Serang. Dengan melakukan wawancara dan pengumpulan data yang melibatkan analisis berbagai repository sastra dari berbagai literature. Temuan studi ini menunjukan bahwa kompetensi pedagogik guru PAI di Sekolah Dasar Negeri Se-Kecamatan Pabuaran sudah sangat baik dalam memahami karakteristik peserta didik, dalam menguasai teori dan prinsip pembelajaran, dalam mengembangkan kurikulum, dalam menyelenggarakan pembelajaran, dalam memanfaatkan teknologi, dalam memfasilitasi pengembangan potensi peserta didik, dalam berkomunikasi dengan peserta didik, dalam menyelenggarakan penilaian dan evaluasi, dalam memanfaatkan hasil penilaian dan evaluasi dan melakukan tindakan refleksi untuk peninglatan kualitas pembelajaran. Studi ini juga menawarkan pemahaman yang lebih komprehensip tentang pentingnya kompetensi pedagogik bagi guru PAI di Sekolah Dasar Negeri Se-Kecamatan Pabuaran.
A FRAGILIDADE DO JUDICIÁRIO PARA SURDOS NO ESTADO DO TOCANTINS
Authors: Bento Bruno Pio , Disconzi Verônica Silva do Prado
Published: October 2024

O acesso à justiça para surdos pode ser afetado por uma série de desafios, incluindo: barreiras de comunicação, complexidade dos procedimentos legais, custos, ausência de sensibilidade dos profissionais jurídicos com a cultura surda e as necessidades específicas da comunidade surda, falta de acesso a informações jurídicas, etc. O presente estudo teve o objetivo de discutir a acessibilidade dos surdos no Poder Judiciário. Para melhor entendimento dessa matéria, limitou-se essa discussão ao Judiciário do Estado do Tocantins. A metodologia empregada foi a revisão sistemática da literatura, tendo como base artigos científicos, livros, periódicos, jurisprudência e na legislação atual sobre o respectivo tema. A coleta de dados foi feita por meio de banco de dados tais como Scielo, Google Acadêmico, dentre outros, no período de 2019 a 2024. Nos resultados, evidenciou-se que No Estado do Tocantins verificou-se que a fragilidade do Poder Judiciário do Estado para surdos é uma questão crítica que envolve barreiras de comunicação, falta de acessibilidade e ausência de profissionais qualificados para atender adequadamente essa população. Diante desse cenário, entende-se que seja imprescindível investir na profissionalização de intérpretes de Libras-Português, bem como na capacitação desses profissionais, para atuarem de forma competente no Poder Judiciário do Tocantins. Isso é essencial para assegurar o acesso à justiça para a pessoa surda, quebrando as barreiras linguísticas, promovendo a inclusão e a acessibilidade da pessoa surda dentro da esfera jurídica.
Factors influencing lake surface water temperature variability in West Greenland and the role of the ice sheet
Authors: Carrea Laura , Merchant Christopher J. , Woolway Richard I. , McCarroll Niall
Published: October 2024

Abstract. Subarctic West Greenland is populated by thousands of seasonally ice-free lakes. Using remotely sensed observations, we analyse the surface water temperatures of six lakes during 1995–2022 to identify factors influencing their variability. The connectivity to the Greenland Ice Sheet (GrIS) has a clear influence on lake surface temperature, with ice-sheet marginal lakes experiencing smaller average summer maximum temperature (< 6 °C) and minimal inter-annual variability. A lake fed by a GrIS-originating river has the fastest seasonal response and largest seasonal amplitude with average maximum temperatures above 13 °C. The seasonal cycle of surface water temperature for all studied lakes is asymmetrical, with faster warming observed after ice off, and a slower cooling of water towards winter freezing. We find that during the study period, the onset of positive stratification has occurred earlier, at rates of up to 0.5 days year-1, and that July–August temperatures have increased at rates up to 0.1 °C year-1, although the GrIS-connected lakes show smaller increases. Our analysis suggests that the main meteorological factor determining interannual variability of surface water temperature in the studied lakes is air temperature. This study highlights the important role of remote sensing for long-term monitoring of Greenlandic lakes under climate change.
Assesing the Value of High-Resolution Data and Parameters Transferability Across Temporal Scales in Hydrological Modeling: A Case Study in Northern China
Authors: Tudaji Mahmut , Nan Yi , Tian Fuqiang
Published: October 2024

Abstract. The temporal resolution of input data and the computational time step are crucial factors affecting the accuracy of hydrological model forecasts. This study presents a four-source hydrological model tailored to the runoff characteristics of the mountainous areas in Northern China. Using this model, along with meteorological and hydrological data from seven catchments of varying sizes in Northern China, we investigated the impact of different input data resolutions and computational time steps on simulation accuracy, as well as the transferability of parameters across different time scales. The results show that: (1) The proposed model performs well across different spatial and temporal scales, with average NSE for daily and hourly flow forecasts of 0.93 and 0.85, respectively. (2) For daily streamflow simulations, there was a significant improvement in model performance when the data resolution was increased from 24 hours to 12 hours; however, beyond the 12-hour resolution, the improvement became negligible. For hourly streamflow simulations, the enhancement in overall flood process accuracy becomes insignificant when the resolution exceeds 6 hours, although higher resolutions continue to improve the precision of peak flow simulations. (3) When the computational time step is fixed (e.g., 1 hour), model parameters are transferable across different data resolutions; parameters calibrated with daily data can be used in models driven by sub-daily data. However, parameters are not transferable when the computational time step varies. Therefore, it is recommended to utilize smaller computational time step when constructing hydrological models even in the absence of high-resolution input data. This strategy ensures that the same simulation accuracy can be achieved while preserving the transferability of model parameters, thus enhancing the robustness of the model.
Localization in MR-based Indoor Navigation System using point cloud registration
Authors: Chauhan Siddharth Singh , Jayakumar T.V. , Mishra Deepak , Ramiya Anandakumar M.
Published: October 2024

Abstract. This paper addresses the pervasive challenge of localization within indoor navigation systems. Many existing systems grapple with this issue, relying on marker-based methods, Bluetooth beacon localization, and image processing. However, these solutions often necessitate the placement of predetermined markers within the environment, presenting limitations such as marker deterioration over time, spatial constraints, and associated costs. In response, we propose a novel point cloud registration-based approach. This method involves the creation of a comprehensive global point cloud representing the entire indoor environment, effectively serving as a three-dimensional virtual map. Concurrently, a mixed-reality device is utilized to generate a local point cloud specific to the device’s current location within the building. By aligning and registering the local cloud with the global counterpart, the device’s precise location within the virtual map can be determined. This approach enables seamless navigation within indoor environments without the reliance on physical markers, offering a versatile and cost-effective solution to the challenge of localization in indoor navigation systems. Finally, an error analysis was also done to test localization accuracy for different illumination conditions, demonstrating the effectiveness of this method.
Incorporating Phenological Patterns and Multi-source Remote Sensing Imagesfor Cropland Change Detection
Authors: Chen Jiage , Du Guangyu
Published: October 2024

Abstract. Accurate information on cropland changes is critical for monitoring arable land minimum, ensuring national food security, and grasping the situation of agricultural production and supply. The change detection using remote sensing images is one of the main methods for quickly extracting cropland changes. However, existing methods were highly susceptible to seasonal differences due to the high heterogeneity of cultivated land. In this study, an integrated framework was proposed to perform change detection by incorporating phenological patterns and multi-source remote sensing images.There were two improvements in this proposed cropland change detection method: 1) the multi-source remote sensing images were utilized to fill the missing data within a time-series image stack by considering phenological patterns of cropland and 2) the Seq2Seq model considering phenological patterns was developed to extract changes in cropland directly. Compared to the traditional change detection methods, the proposed strategy was able to detect change process. Experiments demonstrated that the proposed method can significantly improved change detection accuracies, given a limited number of labeled samples.
Deep Earth System Data Laboratory (DeepESDL)
Authors: Anghelea Anca , Dobrowolska Ewelina , Brandt Gunnar , Reinhardt Martin , Mahecha Miguel , Morbagal Harish Tejas , Meissl Stephan
Published: October 2024

Abstract. The Deep Earth System Data Lab (DeepESDL) provides an AI-ready, collaborative environment for researchers aiming to study the Earth's complex dynamics using various datasets and empirical approaches. Recently opened to Early Adopters, it builds on projects like CAB-LAB and ESDL, utilizing well-established Python and Julia technology stacks. DeepESDL offers programmatic access to extensive analysis-ready data cubes and computational resources, enabling researchers to focus on analysis without extensive preparations. Scientists can use persistently available data cubes or generate user-tailored cubes from own data or publicly available datasets. The goal is to streamline data processing through empirical or AI methods within high-dimensional Earth Observation workflows. DeepESDL addresses the complete research cycle, from discovery of earth data to powerful analyses, collaborative scientific research, advanced data visualisation and publication of results, promoting FAIR and Open Science. Apart from serving as a research environment, DeepESDL showcases scientific use cases and supports educational purposes through capacity building, academic programs, and Open Science initiatives. This paper presents an overview of DeepESDL.
Development of 3D UDTs for Traffic Monitoring in Unreal 5 Game Engine
Authors: Crampen David , Yadav Yogender , Ishar Shofia , Zlatanova Sisi , Tian Wenwen
Published: October 2024

Abstract. Digital Twins recently, are a much regarded research topic in geospatial engineering, offering great potential for optimization of a variety of interrelated processes in urban environments. A major component of a Digital Twin use case is real-time sensor data input and analysis, which is used as foundation for simulations that lead to decision-support for authorities or even automatic response into the physical environment. The use of game engines as platform for urban Digital Twin use cases is promising due to superior visualization and animation capabilities, that facilitate diverse monitoring use cases for highly dynamic sensor data inputs. This contribution evaluates the fit for purpose of the Unreal Engine 5 game engine for digital twin use cases, by conducting a case study on urban traffic monitoring in the city of Liverpool Australia. The case study proved, that the necessary connections of static data provided via a geodatabase and dynamic real-time data from public portals can be integrated into the engine to establish an interactive Digital Twin use cases for evaluating traffic user interactions.
An Approach to Checking Map Tiles by Annotation Recognition
Authors: Ding Lei , Zhang Hongping , Huang Wei , Zhao Wenhao , Tang Dejin , Zheng Xinyan , Wang Cong , Li Heng , Wang Zhen
Published: October 2024

Abstract. As the capabilities of geographic information services increase, web geographic information services represented by internet mapping have become increasingly popular, widely used in various location-based services. It is precisely because of the surge in demand that higher requirements have been put forward for the updating and quality control of internet map data. The quality inspection of geographic vector data is relatively well-developed, with many inspection rules and automated processes, but there is a clear deficiency in the quality inspection of map tiles, which mainly relies on manual visual inspection, restricting the rapid updating and release of map tiles. To solve this problem, this paper proposes an automated map tile inspection method. First, web crawling technology is used to capture map tiles, and to avoid the problem of incomplete display of annotations across tiles, adjacent tiles are all captured and merged into one image; second, OCR technology is used for image text detection and text recognition, and finally, the newly added recognition results are stored in the database and compared and confirmed with the results in the database. The experiment proves that the method proposed in this paper is feasible and may greatly improve work efficiency, especially as the updating speed of online maps accelerates, an automated tile quality inspection method can greatly improve the updating speed.
Design and Implementation of a Geographic Scenario Computation System Based on Knowledge Base
Authors: Feng Yunlong , Jing Changfeng , Li Jianing , Liang Tao
Published: October 2024

Abstract. The promotion and expansion of Geographic Information System (GIS) applications have increased the complexity of geocomputation. The concept of a geographic scene, which encompasses both geographic entities and complex spatial interaction relationships, serves as a means of organizing and expressing geographic information. Existing methods of organizing and computing geographic scenes often focus on single geometric elements or single-category objects, neglecting the complexity of the geocomputation process and leading to biased results. To address this issue, this study designs and implements a geographic scenario computation system based on WebGIS to overcome the lack of integration of knowledge elements in traditional geographic scenario computation methods. The system consists of a data management module, a geographic scenario visualization module, and a geographic scenario computation module. It not only realizes the visualization of geographic scenarios but also introduces a knowledge base into the geographic scenario computation process, enabling accurate management of geographic scenarios. This paper uses a farmland scenario in Shandong Province, China, as a case study to verify the effectiveness and feasibility of the system. The application of this system provides new technical support for the computation process of geographic scenarios, promoting the refinement and intelligent development of geographic scenario management. This method can also be applied to similar applications of intelligent sensors and the Internet of Things in the organization and management of sensing information in the future.
A Machine Learning Approach for Modeling the Spatial-temporal Propagation Pattern of COVID-19
Authors: Foruzandeh Mohsen , Neysani Samany Najmeh , Khodakaramian Bigard
Published: October 2024

Abstract. Predicting infections resulting from epidemiological contagions involves a complex therapeutic endeavor that necessitates the consideration of various factors within the available data. COVID-19, a globally recognized highly dangerous disease, presents an opportunity to effectively understand its patterns and spatial determinants to combat similar ailments. This study seeks to employ a deep neural network and several machine learning techniques to identify the crucial factors influencing COVID-19 infections and to forecast the spatial-temporal spread of the disease. Previous research has focused on predicting outcomes using a limited set of 8 patient variables. To contribute to this field, the current investigation analyzes a dataset comprising 47,029 records of infected individuals who sought medical attention, with 18,433 of them testing positive for the coronavirus and requiring hospitalization. The study explores the prediction of illness and hospitalization needs based on geographical locations by utilizing machine learning algorithms such as Random Forest, Naive Bayes, Decision Tree, and K-Nearest Neighbor. The machine learning process commences with input data (comprising the 47,029 records), enabling the machine to identify patterns within the dataset and subsequently make informed decisions based on these patterns and insights gained. The primary objective is to allow the machine to autonomously learn and refine its predictions without human intervention. Applying these algorithms to COVID-19 data for spatial-temporal prediction revealed that the Random Forest algorithm achieved the highest accuracy of 0.84, while the Simple Bayes algorithm exhibited the lowest accuracy at 0.50. Additionally, the study compared random forest, decision tree, simple bayes, and K-nearest neighbor algorithms to predict the severity of road accidents.
Research on New Spatial Data Infrastructure Supports the Circulation of Geographic Information Data Elements
Authors: Li Heng , Huang Wei , Zhai Yong , Zhao Wenhao , Zheng Xinyan , Liu Jin
Published: October 2024

Abstract. Data is an important factor of production in the digital economy era and an important support for building a new development pattern. As an important part of data resources, geographic information data is also an important new factor of production, which plays a unique role in the construction of digital China and economic and social development. From the perspective of releasing the value of data elements, data infrastructure is a new type of infrastructure that provides integrated data aggregation, processing,circulation, application, operation, and security services for society under the support of network, computing power and other facilities. It is an organic whole covering hardware, software, open source protocols, standards, and mechanism design. Spatial data infrastructure (SDI) is a collection of technologies, policies and systems that realize the access and access of spatial data. Through the construction of new spatial data infrastructure (NSDI), it supports the circulation of geographic information data elements,making it an important part of data infrastructure. Firstly, this paper gives the connotation of geographic information data elements circulation. Secondly, it proposed to construct the circulation system of geographic information data elements on the basis of enumerating and summarizing the spatial data infrastructure, in order to better support the construction of digital China and economic and social development. Thirdly, the basic requirements, technical indicators and overall architecture of NSDI are designed. Finally, the opportunities and challenges faced by the circulation of geographic information data elements were summarized, mainly focusing on the aspects of policy mechanisms and security systems. At the end of the paper is a summary and acknowledgments.
3D Voxel-based Path Planning for AVs in Dynamic Complex Environments
Authors: Lin Zhaoyu , Wang Zhiyong , Gong Tailin
Published: October 2024

Abstract. With the rapid advancement of science and technology, autonomous driving technology has been widely applied in various fields such as the automotive industry, intelligent warehousing, and emergency rescue. Traditional 2D path planning has limitations in dealing with the complex and dynamic environments of the real world, making it difficult to meet the high precision and complex path planning requirements of autonomous vehicles. With the development of data acquisition technology, large-scale point cloud data has become easily accessible, which can better extract the three-dimensional complex of the environment. Nevertheless, the unstructured nature and vast amount of point cloud data make path planning on it extremely challenging. Voxel models can effectively compress point cloud data and provide neighboring topological structures. In view of this, we propose a voxel-based framework for the path planning of autonomous vehicles in dynamic and complex 3D environments, which involves converting point cloud data into voxels and extracting navigation spaces. Subsequently, deep reinforcement learning techniques are utilized to achieve obstacle avoidance and navigation on the voxel map. It is expected that this framework will contribute to the development of 3D path planning and enhance the utilization of point cloud data in the navigation field.
AI upscaling Supporting Image Alignment in Photogrammetric Reconstruction
Authors: Martinelli Alessandro , Toni Agnese , Brescia Sara
Published: October 2024

Abstract. This research aims to investigate and analyze the contribution provided by preventive image processing using AI in the SfM data acquisition process. Specifically, the objective is to observe qualities and defects of "AI upscaling" integrated into the normal workflow of digital restitution, with the hypothesis that greater sharpness and resolution can lead to better alignments and better model generations. Other similar experiments have been carried out previously on the AI intervention in the photos to improve the alignments, but a generic procedure and with untrained public AI has not yet been experimented. In the first phase of the research, the most suitable AI upscaling method for the purpose is selected, processing example images and comparing them with the original and various settings of the AI parameters to maintain likeness. In the second phase, the procedure efficiency was evaluated in several ways: through the automatic evaluation of Agisoft Metashape's Image Quality, by directly comparing the resulting model with the standard digital reconstruction of the same objects, comparing with a model produced with the native AI upscaling of the return program, and finally comparing with a high-level survey without defects. This test was repeated for four case studies specifically diversified by several factors, including subject scale, level of detail, lighting, color, blur, and type of camera used. Clear improvements emerge in all cases of AI upscaling, even reaching successful reconstructions that would not have started with the canonical method. It can therefore be stated that this preventive upscaling procedure is decisive in cases of low quality or damaged datasets, while in cases of already qualitatively sufficient photos it can be a useful support for increasing the level of detail.
A Novel Platform and Workflow for Underwater Photogrammetry Surveys
Authors: Mufti Alaa , Helmholz Petra , Belton David , Allahvirdi-Zadeh Amir , Parnum Iain
Published: October 2024

Abstract. Underwater photogrammetry has gained popularity for creating three-dimensional (3D) maps and ortho-images of marine environments as compared to traditional echosounder surveys, they can be more cost-effective at creating high-resolution 3D models, and orthoimages are usually more informative than acoustic backscatter maps. This paper builds on previous work by the authors that developed an underwater image-capturing platform with several additional sensors, including GNSS, IMU, pressure depth sensor and single beam echosounder. This study aims to analyse the impact of calibration and sensor data integration into the photogrammetric processing workflow. The tests were performed using two underwater sites. The low-cost device's pressure sensor and tide station data outperform GNSS PPK-derived heights. Furthermore, it was observed that incorporating IMU motion sensor data did not improve the processing results. Additionally, utilising the echosounder point cloud proves valuable for enhancing the overall quality of the survey. Despite its lower density, it serves a dual purpose by validating the photogrammetry dataset and, more importantly, can be employed for correcting DSM height. This study further underlined the importance of reliable camera calibration for accurate 3D reconstruction.
A Preliminary Study on the Construction of a Natural Resource Comprehensive Survey System
Authors: Bai Jie , Li Ming
Published: October 2024

Abstract. The establishment of a comprehensive survey, monitoring and evaluation system for natural resources is important for determining the background of China's natural resources, fulfilling the "two unification" responsibilities of the Ministry of Natural Resources, and implementing the construction of an ecological civilization. According to the task requirements of the unified survey and monitoring of natural resources, we summarize the progress of natural resource management systems, monitoring systems, technical development and implementation of major projects, propose upgrading the "3rd National Land Resource Survey" to "the 1st Comprehensive Natural Resource Survey", and explore the construction of natural resource survey systems. Combined with the pilot project of comprehensive investigation of natural resources with multiple elements, the next major work for the comprehensive investigation of natural resources is to accelerate the formulation of standards and specifications, carry out application demonstrations, and establish and improve the working mechanism and investigation team.
Smart Building Digital Twin for Interior Water Distribution System Management
Authors: Rajan Gopika , Li Songnian
Published: October 2024

Abstract. A smart campus integrates the Internet of Things, artificial intelligence, and real-time sensor data to optimize campus functions and create a context-aware decision-support platform for effective campus management. A crucial aspect of a smart campus is the water distribution system, which faces several challenges due to bursts, leaks, and water quality issues. This study uses Digital Twin technology to address these challenges through real-time monitoring, detection, and management of campus water distribution networks. A building-level digital twin is developed for the interior water networks of the Daphne Cockwell Complex at Toronto Metropolitan University. The major components include a 3D network model capable of analysis and simulations, a smart water management system, and real-time visualization. A 3D static model of the interior water utility network is created using the Industrial Foundation Class data. The semantic and topological models based on graph models are developed for network analysis. The models are integrated into the ESRI ArcGIS Pro to facilitate BIM-GIS integration. A dynamic model is created by incorporating automatic meter readings based on IoT. Combined with the 3D model of the utility network, the digital twin monitors and visualizes building water consumption, facilitating anomaly detection and real-time maintenance by the facilities management department. This study provides practical guidance for managing water distribution systems in university buildings, with potential applications in other complex environments. Future work aims to develop a system for detecting complex event processes by integrating different utilities.
Augmented Reality for Air Quality Monitoring: Case Study in the Marche Region (Italy)
Authors: Sanità Marsia , Fratini Jonathan , Muralikrishna Nikhil , Pierdicca Roberto , Malinverni Eva Savina
Published: October 2024

Abstract. Augmented Reality (AR) allows the real world to be enhanced through the overlapping of digital information generated by an algorithm or software amplifying the user's perception. In this research, the potential of AR is exploited by applying it to the problem of air pollution visualization to raise awareness of the issue. It is well known that the principal sources of air pollution include industry, domestic heating, traffic, production processes and more others. According to European Environment Agency, air pollution is the largest environmental health risk in Europe in 2022 affecting respiratory and cardiovascular diseases and premature deaths. A suitable combination of GIS-based procedures for data analysis and georeferencing, AR systems for the visualization and exploitation of the results, can be a strategic driver. The research presented in this paper has been experimented in the Marche Region, in the central part of Italy, and in particular the city of Ancona. The pollutant data collected come from 17 Agenzia Regionale per la Protezione Ambientale delle Marche (ARPAM) meteorological ground-based stations located in Marche Region. The data processing have been executed using the software ArcGis Pro instead of a 3D City Model has been acquired from the online 3D ArcGIS platform. According to the Dlgs.155/2010 regulation, the AQI index (Air Quality Index) has been provided by the interpolation of the meteorological ground stations data. The visualization phase has been tackled exploiting in a WebGIS platform and an APP by AR. A 3D immersive visualization is made using five AQI level of air quality (excellent, good, fair, poor, bad) in order to increase the urban sensing.
High-precision 3D Modeling of Construction Waste Pile Bodies by Integrating Multi-source Data
Authors: Shi Leyan , Zhao Wenji , Wang Yanhui , Yan Xing
Published: October 2024

Abstract. The instability of construction waste pile bodies, as an increasingly concerning disaster, poses significant risks to the safety of people's lives and property. Currently, there is limited research on high-precision 3D modeling techniques for construction waste pile bodies, which significantly hinders the accuracy and reliability of early detection and risk assessment of pile body instability. Therefore, constructing high-precision 3D models of construction waste pile bodies using multi-source data plays a crucial role in improving the accuracy and timeliness of early warning systems for pile body instability, offering significant theoretical research and practical application value. Building 3D models of construction waste pile bodies solely based on unmanned aerial vehicle (UAV) oblique photography data faces challenges, such as various degrees of data voids and insufficient model completeness, and few methods currently address the construction of 3D models of construction waste pile bodies through the fusion of multi-source data. This paper attempts to use the Iterative Closest Point (ICP) algorithm, combining SLAM laser point cloud data with UAV oblique photography data to fill data voids, and utilizes the fused point cloud to reconstruct the triangulation network, achieving the transformation from 3D point cloud models to 3D surface models. On the basis of texture mapping, a high-precision 3D model of the construction waste pile body is constructed. The research results show that the 3D model of the construction waste pile body, integrated with multi-source data, has a planar error of 0.0187m and an elevation error of 0.0368m, meeting the corresponding model accuracy requirements. It can more realistically restore the fine 3D features of the construction waste pile body, effectively compensating for the shortcomings of single-source data in 3D modeling of construction waste pile bodies, providing a new method for the 3D model reconstruction of construction waste pile bodies, and offering effective data support for construction waste research.