bluuebunny/crossref_metadata_2025 huggingface dataset:
TREE-GPT: MODULAR LARGE LANGUAGE MODEL EXPERT SYSTEM FOR FOREST REMOTE SENSING IMAGE UNDERSTANDING AND INTERACTIVE ANALYSIS
Authors: Du S. Q. , Tang S. J. , Wang W. X. , Li X. M. , Guo R. Z.
Published: December 2023

Abstract. This paper introduces a novel framework, Tree-GPT, which incorporates Large Language Models (LLMs) into the forestry remote sensing data workflow, thereby enhancing the efficiency of data analysis. Currently, LLMs are unable to extract or comprehend information from images and may generate inaccurate text due to a lack of domain knowledge, limiting their use in forestry data analysis. To address this issue, we propose a modular LLM expert system, Tree-GPT, that integrates image understanding modules, domain knowledge bases, and toolchains. This empowers LLMs with the ability to comprehend images, acquire accurate knowledge, generate code, and perform data analysis in a local environment. Specifically, the image understanding module extracts structured information from forest remote sensing images by utilizing automatic or interactive generation of prompts to guide the Segment Anything Model (SAM) in generating and selecting optimal tree segmentation results. The system then calculates tree structural parameters based on these results and stores them in a database. Upon receiving a specific natural language instruction, the LLM generates code based on a thought chain to accomplish the analysis task. The code is then executed by an LLM agent in a local environment and . For ecological parameter calculations, the system retrieves the corresponding knowledge from the knowledge base and inputs it into the LLM to guide the generation of accurate code. We tested this system on several tasks, including Search, Visualization, and Machine Learning Analysis. The prototype system performed well, demonstrating the potential for dynamic usage of LLMs in forestry research and environmental sciences.
A HIGH-PRECISION EXPLICIT FOREST CARBON STOCK MODEL BASED ON REMOTE SENSING
Authors: Zhu N. , Yang B. , Gong W. , Ying S. , Dai W. , Dong Z.
Published: December 2023

Abstract. The current status as well as the potential absorption capability of the forest carbon sinks in terrestrial ecosystems are in urgent need of further studies. The ground observation-based methods are labor-intensive, and the resulting statistics from samples are difficult to evaluate, while inversion methods based on remote sensing data lack theoretical explanation and universality. This paper proposes a pixel-level, multi-scale, high-precision Explicit Forest carbon stock Model (EFM) that is universal and adaptive. First, four key variables were used in the construction of the EFM: remote sensing image resolution, forest canopy density, terrain slope, and forest height; Second, simulated forest scene were generated based on the growth characteristics of individual trees, and EFM parameters were solved and analyzed by these simulated pixels; Third, the EFM was tested at various scales and forest saturation levels to verify its accuracy, robustness, and applicability, the simulation and real-life experiments show that the correlation coefficient is greater than 0.98 and the relative error is about 20%. The EFM solves the problem that the existing methods are lack in theoretical interpretation and universal applicability, thus can be used to map forest carbon stocks at high resolution and large scale and even monitor forest carbon dynamics at global scale.
EXPLORING VERY HIGH-RESOLUTION REMOTE SENSING FOR ASSESSING LAND SURFACE TEMPERATURE OF DIFFERENT URBAN LAND COVER PATTERNS
Authors: Asmaryan S. , Muradyan V. , Medvedev A. , Avetisyan R. , Hovsepyan A. , Khlghatyan A. , Ayvazyan G. , Dell’Acqua F.
Published: December 2023

Abstract. Very-high-resolution thermal infrared data has a good potential to detect and monitor LST variations in urban areas. In this work, an attempt was made to estimate Land Surface Temperature (LST) from very high resolution (VHR) data using machine learning technics in an area of Botanical garden of Yerevan, Armenia; UAV-derived and in-situ measured high precision LST of various land cover (LC) patterns were then compared for September and October. The main purpose of this study was to explore the capabilities of UAV imagery (multispectral/TIR) in assessing LST of the different LC patterns. For this purpose, a UAV survey was performed, and VHR data were collected using multispectral and TIR thermal camera while in-situ measurements of temperature and surveying of the different LC patterns were performed. A significant correlation was detected between LSTs in situ measured and detected by UAV in 06 September (r=0.758; p-value <0.01) and in 27 October (r=0.686; p-value <0.01). When comparing the LSTs of separate land-cover patterns the best results were received for Bare soils (r=0.591; p-value <0.05) and Concrete (r=0.927; p-value <0.01) when the survey and measurements was done in September. Despite its limitations, it can be stated that UAV thermal survey has a good potential to detect and monitor LST variations in urban areas.
REALITY CAPTURE METHODS FOR REMOTE INSPECTION OF BUILDING WORK
Authors: Becker S. , Einizinab S. , Radanovic S. , Khoshelham K. , Mirzaei K. , Fang Y.
Published: December 2023

Abstract. Conventional building inspection, which requires in-person visits by a qualified inspector, can be costly, time-consuming, and even pose health and safety risks. The travel restrictions of the global Covid-19 pandemic further highlighted the need for remote inspection methods. Using reality capture techniques to create a digital 3D representation of the site offers promise for remote inspection of building work. This paper aims to assess different reality capture methods and their visualizations for remote inspection of building work through a case study conducted in Melbourne, Australia. The reality capture methods included terrestrial and mobile laser scanning, RGB-D imaging, and aerial photogrammetry using a UAV. Professional building inspectors participated in the evaluation process by conducting remote inspection based on the captured data and comparing it to the on-site experience. The assessment involved different visualizations of the data, including 3D panoramas, point clouds, and triangulated surface meshes. The results indicate that image visualisation and the ability to make measurement on images are desirable by professional inspectors. These findings support the adoption of reality capture techniques for remote inspection of building work, which can enhance the safety and efficiency of the process.
ESTIMATION AND MAPPING OF THE SETTLEMENT FIELD POTENTIAL BASING ON REAL TRANSPORTATION CONNECTIONS BETWEEN SETTLEMENTS
Authors: Kuzmin P. , Karpenko M. , Panidi E. , Sebentsov A.
Published: December 2023

Abstract. In the article, we describe an approach to computational estimation of the settlement field potential, and mapping its spatial distribution in the desktop geographic information system software. The settlement field potential is a quantitative geographical variable that reflects mutual impact of settlements according to the population amount in the settlements and distances between settlements (two or many). This geographical variable can be used as an extra metric in human geography alongside with population density metric. We propose a methodology for automation of the settlement field potential mapping, and propose to estimate the settlement field potential value using distances measured in real transportation network instead of traditionally used straight-line measurement of the distances. To test and verify proposed approach and methodology we produced the maps of settlement field potential for the study area that covers Russia-Kazakhstan transborder area.
SPATIAL INTERACTION ANALYSIS OF URBAN FUNCTIONAL DISTRICTS BASED ON TAXI TRAJECTORIES
Authors: Zhang Y. , Liu W. , Zhu X. , Peng Y. , Li R. , Zhao T. , Wang X. , Zhai X. , Di X. , Xu H.
Published: December 2023

Abstract. The functional differences among various components of a city drive the circulation of logistics, human flows, and energy flows within the city. Qualitatively and quantitatively analyzing the spatial interactions among urban functional districts contributes to understanding the spatial structure of it and formulating more efficient urban planning strategies. Based on taxi trips, this paper compares spatial interactions between the Xudong Commercial District and the Zhongnan Road Commercial District in Wuhan, respectively, with other functional districts. Firstly, the spatial interaction based on taxi trips between these two commercial districts, acting as either the origins or destinations for taxi trips, with various functional districts was visualized. Subsequently, we analyzed the intensity and distance of the spatial interactions based on taxi trips during each typical time period (8:00-9:00, 18:00-19:00, and 20:00-21:00 on weekdays; and 9:00-10:00, 19:00-20:00, and 22:00-23:00 on weekends). These results can serve as reference for further research on the influence range, development planning, and transportation optimization of these commercial districts.
MONITORING THE MANGROVES OF INDIAN SUNDARBANS USING GEOSPATIAL TECHNIQUES
Authors: Bhadra T. , Banerjee S. , Ghosh S. , Saha A. , Mukherjee K. , Sardar R. , Roy S. , Das R.
Published: December 2023

Abstract. The world’s largest mangrove ecosystem Sundarbans lies in the southwestern part of the Ganges-Brahmaputra Delta. The health, function, and ecosystem services of the mangrove forest depend on the availability of freshwater flow within the deltaic system. The rivers, which used to feed the delta and nourish the mangrove ecosystem now stand disconnected from their upstream freshwater sources. The unavailability of freshwater restricts the growth of freshwater-loving mangroves and has the potential to affect the health of the existing mangroves limiting their ability to provide ecosystem services. Due to the high salinity, the natural reproduction of these valuable freshwater-loving floral species gradually got ceased. High salinity is considered a stress factor influencing the health, growth, productivity, and distribution of mangrove plants. In this circumstance, the main objective of the study is to monitor the spatiotemporal change of the mangrove ecosystem of Sundarbans in terms of species assemblage, floral diversity, biomass, canopy cover, forest health, etc. Remote sensing techniques and field measurements were used to perform an in-depth mangrove genus-level classification (Maximum Likelihood Classifier). To assess the plant species diversity, Shannon-Wiener Index was used in different plots of the Sundarbans to get an idea of the rich biodiversity of these coastal ecosystems. Different vegetation indices such as NDVI, OSAVI, SAVI, TDVI, etc. were estimated to assess the health of the mangrove forest. The biomass and carbon sequestration potential of the mangrove forest was assessed using field data and microwave remote sensing techniques. The result shows the declining trend of freshwater-loving mangroves from the central section of Sundarbans and an increasing trend of saline water-loving mangroves by replacing the others.
ATTRIBUTION ANALYSIS OF CLIMATE CHANGE AND HUMAN ACTIVITIES TO WATER VOLUME VARIATION IN LARGE LAKES
Authors: Lin Y. , Gao C. , Li X. , Zhang T. , Yu J. , Rong Y. , Li L. , Zhou X. , Cai J. , Sneeuw N.
Published: December 2023

Abstract. Lakes are important components of the Earth's surface water bodies, and their fluctuating water levels and changing water volumes can have an important impact on ecological processes and landscape patterns within a watershed. Climate change and human activities are the main drivers of water volume changes in lakes. We applied a long time series analysis approach using classical statistics and geographic information system (GIS) technics to quantitatively attribute water volume variations in Lake Victoria from 2000 to 2019. We examined several drivers of lake water volume variations: meteorological factors including regional climate change (precipitation, evaporation) and global climate change (El Niño/Southern Oscillation events), and anthropogenic factors including socio-economic development and land use/cover change. The results show that regional climate change has a greater impact on lake water volume variations than global climate change; among them, the correlation coefficient between precipitation and lake water volume variations is the largest (0.410), with an impact lag of 1 month. For anthropogenic factors, variations in lake water volume are more pronounced in areas with rapid economic development and high population growth, with correlation coefficients greater than 0.440. Different types of land use/cover have varying impacts on Lake Victoria's water volume variations. Overall, the influence of anthropogenic factors is greater than that of meteorological factors. This study results not only provides a scientific basis for exploring the hydrological changes and their drivers in the world's large transboundary lakes, but also be great scientific significance to rational use of water resources and sustainable regional development.
DETECTION OF HAZARDOUS MATERIALS IN LASER CUTTING USING DEEP LEARNING AND SPECKLE SENSING
Authors: Salem M. A. , ElShenawy A. K. , Ashour H. A.
Published: December 2023

Abstract. The technology of laser cutting is widely used in various industries for processing materials. However, it generates a substantial amount of harmful dust, smoke, and aerosols, which pose a threat to the environment and endanger the health of workers. One potential method that has emerged to monitor the cutting process and identify materials in real-time is speckle sensing. This paper presents a novel material classification technique that employs a new deep-learning model architecture designed for speckle pattern images to classify materials according to the speckle patterns of the material's surface. The proposed approach involves training a convolutional neural network (CNN) on a large dataset of laser speckle patterns to recognize various material types for safe and efficient cutting. Material classification using speckle sensing enhances the process, reducing the time required to train the speckle images and the inference time for predicting the material from the speckle images. Experimental results demonstrate that the suggested method achieves high precision in categorizing materials, particularly hazardous ones. The model was evaluated on a test dataset of 3,000 new images, achieving an F1-score of 0.9781. The utilization of speckle sensing enables the proposed method to offer a fast, reliable, and accurate approach to material-aware laser cutting while mitigating the potential risks associated with the process.
THE IMPACT OF DUST POLLUTION FROM UNPAVED ROADS IN THE AKAMAS PENINSULA, CYPRUS, USING UAV AND SENTINEL-2 IMAGES
Authors: Themistocleous K. , Prodromou M.
Published: December 2023

Abstract. This study examines the effects of dust in the Akamas National Park in Cyprus generated from traffic over the unpaved roads on the roadside vegetation. The Akamas National Park is located on the western tip of Cyprus and covers an area of about 230 km2, containing valleys, gorges and wide sandy bays. Akamas is a mountainous, relatively inaccessible area to standard vehicles and protected from man-made development. It is home to hundreds of animal species and plants that are essential for the ecology of the Mediterranean region. There are several unpaved roads to access the area and more than one million people visit the Akamas peninsula each year, mostly in the summer period, primarily in 4X4 and all-terrain vehicles, which are rented in the nearby area. This unregulated traffic results in dust, especially during the dry weather conditions in the summer that can fall up to a kilometre away on all sides of the vehicle. In this study, images acquired from an Unmanned Aerial Vehicle (UAV) of the roads within the Akamas peninsula were compared with Sentinel-2 satellite images during different seasons. Using the Normalized Vegetation Index (NDVI) from the Sentinel-2 images, it was shown that the vegetation nearest to the unpaved roads exhibited pronounced stress compared to the vegetation that was more distant. Also, spectral signatures as well as infrared and thermal images were taken at different distance intervals from the unpaved road.
CONTENT PLANNING AND STRUCTURE DESIGN OF GLOBAL LAND COVER KNOWLEDGE ATLAS
Authors: Zhu X. , Chen L. , Zhao Y. , Liu W. , Peng Y. , Li R. , Zhai X. , Xu H.
Published: December 2023

Abstract. From 2000 to 2020, three versions of the 30-meter global land cover data products (GlobeLand30) have been made accessible to the public. The dataset with 30-meter spatial resolution and 10-year temporal resolution are widely used for monitoring environment changes and resource management at global, regional and local scales. By analysing and extracting information and knowledge from the GlobeLand30 data, we have planned and designed a global land cover knowledge atlas, which aims to expand the available knowledge base for scientific research, management decision-making, and knowledge dissemination.
CAPACITY BUILDING FOR GIS-BASED SDG INDICATORS ANALYSIS WITH GLOBAL HIGH-RESOLUTION LAND COVER DATASETS
Authors: Oxoli D. , Reyes S. R. , Peng S. , Brovelli M. A. , Coetzee S. , Ivanova I. , Leonardi J. A. , Rawal D. , Vacca G. , Zlatanova S.
Published: December 2023

Abstract. The support of geospatial data and technologies for the United Nations Sustainable Development Goals (SDG) framework is critical for assessing and monitoring key indicators, revealing the planet’s trajectory towards sustainability. The availability of global open geospatial datasets, especially high-resolution land cover datasets, provides significant opportunities for computing and comparing indicators across different regions and scales. However, barriers to their proficient use remain due to a lack of data awareness, management and processing capacities using geographic information systems software. To address this, the ”Capacity Building for GIS-based SDG Indicator Analysis with Global High-resolution Land Cover Datasets” project created open training material on discovering, accessing, and manipulating global geospatial datasets for computing SDG indicators. The material focuses on water and terrestrial ecosystems, urban environments, and climate, by leveraging world-class global geospatial datasets and using the Free and Open Source Software QGIS. The training material is released under a Creative Commons Attribution 4.0 License, ensuring broad accessibility and facilitating continuous improvement.
MAPPING LOCAL CLIMATE ZONES WITH MULTIPLE GEODATA AND THE OPEN DATA CUBE: INSIGHTS OF DOMAIN USER REQUIREMENTS AND OUTLOOKS OF THE LCZ-ODC PROJECT
Authors: Vavassori A. , Brovelli M. A. , Capizzi E. , Venuti G. , Betti B. , Siciliani de Cumis M. , Sacco P. , Tapete D.
Published: December 2023

Abstract. Rapid urbanization and climate change are intensifying the urban heat island (UHI) phenomenon across cities worldwide. There is a pressing need to implement evidence-based mitigation and adaptation strategies as well as to develop tools for effectively measuring the impact of such actions on UHI patterns. In this context, the Local Climate Zone (LCZ) concept is a well-established classification system commonly used for the assessment of UHI. With this in mind, we present here the LCZ-ODC project aiming to develop a methodology for LCZ mapping in the Metropolitan City of Milan (northern Italy) by leveraging multiple geospatial data and cutting-edge software tools, including the Open Data Cube (ODC). A key aim of the project is to develop user-oriented solutions facilitating the exploitation of the generated LCZ maps for different application tasks. In this paper, we first present a brief overview of the methodologies and data sources used in the literature for LCZ mapping. Then, we introduce the LCZ-ODC project, with a focus on the end-user requirements which were gathered through a questionnaire distributed to a sample of potential stakeholders. The primary objective of the survey was to collect insights and consolidate requirements related to the key features of LCZ maps that will be produced within the project. The outcomes of the survey play a pivotal role in guiding the project’s development phase, ensuring that the project outputs will effectively address the identified end-user needs.
MR-MD:MULTI-ROBOT MAPPING WITH MANHATTAN DESCRIPTOR
Authors: Wu H. , Zhong R. , Xie D. , Chen C. , Tang J. , Wu C. , Qi X.
Published: December 2023

Abstract. Simultaneous Localization and Mapping (SLAM) technology, utilizing Light Detection and Ranging (LiDAR) sensors, is crucial for 3D environment perception and mapping. However, the absence of absolute observations and the inefficiency of single-robot perception present challenges for LiDAR SLAM in indoor environments. In this paper, we propose a multi-robot (MR) collaborative mapping method based on the Manhattan descriptor (MD) named MR-MD to overcome these limitations and improve the perception accuracy of LiDAR SLAM in indoor environments. The proposed method consists of two modules: MD generation and MD optimization. In the first module, each robot builds a local submap and constructs MD by parameterizing the planes in the submap. In the second module, the global main direction is updated using the historical MD of each robot, and constraints are built for each robot's horizontal and vertical directions according to their current MD and optimized. We conducted extensive comparisons with other multi-robot and single-robot LiDAR SLAM methods using real indoor data, and the results show that our method achieved higher mapping accuracy.
RESEARCH ON POWER TRANSMISSION CHANNEL CHANGE DETECTION BASED ON MULTI-TEMPORAL POINT CLOUD DATA
Authors: Hu W. , Yang G. , Liu N. , Liu F. , Ma C. , Tian M. , Hao C.
Published: December 2023

Abstract. Airborne LiDAR can directly obtain 3D information of ground objects. By comparing the multi-temporal LiDAR data, ground objects change information of power transmission channel can be detected, providing data support for transmission line operation and maintenance. In this paper, an improved ICP algorithm based on multi-temporal LiDAR point cloud data power transmission channel ground object change detection method is proposed. Firstly, based on the classification of point cloud data, a two-level matching method of multi-temporal point cloud data considering the characteristics of power transmission channel was proposed to achieve accurate registration of point cloud data. Then, change detection and analysis of different types of ground feature point cloud data were carried out through elevation difference. Finally, cluster analysis was carried out on the changed ground feature points to generate multi-temporal relative ratio analysis report. Experimental results show that the proposed method can effectively detect power transmission channel changes.
LIDSOR: A FILTER FOR REMOVING RAIN AND SNOW NOISE POINTS FROM LIDAR POINT CLOUDS IN RAINY AND SNOWY WEATHER
Authors: Huang H. , Yan X. , Yang J. , Cao Y. , Zhang X.
Published: December 2023

Abstract. As autonomous driving technology advances, ensuring the system's safety in rain and snow has emerged as a pivotal research topic. In rainy and snowy weather, rain and snow can generate noise points within the point cloud captured by the Light Detection and Ranging (LiDAR), significantly impeding the LiDAR's sensing capability. To address this problem, we first manually label the point cloud data gathered in rain and snow, categorizing all points into noise points and non-noise points. Subsequently, we analyze the intensity and spatial distribution characteristics of the rain and snow noise points and employ the gamma distribution curve to illustrate the spatial distribution characteristics of these noise points. Finally, we propose a Low-Intensity Dynamic Statistical Outlier Removal (LIDSOR) filter, an enhancement of the existing Dynamic Statistical Outlier Removal (DSOR) filter. Experimental results suggest that the LIDSOR filter can effectively eliminate rain and snow noise points while preserving more environmental feature points. Additionally, it consumes fewer computational resources. The filter we propose in this paper significantly contributes to the safe operation of the autonomous driving system in diverse complex environments.
EXPLORING THE LIMITS OF TERRESTRIAL LASER SCANNERS ON AEROSPACE MATERIALS
Authors: Pexman K. , Robson S.
Published: December 2023

Abstract. Terrestrial laser scanners are powerful measurement devices commonly used for 3D modelling tasks generating large volumes of data with fast acquisition as a first priority. However, these scanners can alternatively be used to produce near real-time, engineering quality spatial data concerning the changing state of manufactured components. This paper provides a comprehensive analysis of two terrestrial laser scanners capturing aerospace materials and components, and their associated quality measures. In order to explore the limitations of the tested TLS instruments, a mechanical jig was designed incorporating both a rotation and translation stage. This study involved three elements of a point cloud processing workflow: data capture, registration and feature extraction. Sphere-based 7DoF registration is applied using two different commercially available software packages with varying levels of user control. To analyse the quality of the registration, control points extracted from captured point clouds were compared to nominal values measured using a laser tracker. The quality of the registration was consistent, with differences kept between 0.4 mm and 0.6 mm. To evaluate the quality of the captured point clouds, two different tests were conducted. This included planar fit tests on an aluminium drilling template, and sphere fitting tests on white 1.5” spherical targets in magnetic nests. One half of the aluminium drilling template was coated with matte spray to reduce erroneous laser reflections. Finally, the registered point clouds were input to a developed algorithm which automatically extracted drilling holes from the drilling template. Previous scanning work performed on aerospace materials showed evidence of optical rattling caused by high intensity reflections from the interior holes in a drilling template. Further exploration showed that the amount of optical rattle varies systematically with incidence angle. This work demonstrates a systematic offset in the location of extracted hole centres in the drilling template. This offset is dependent on laser incidence angle, and can therefore be accounted for when locating manufacturing components from a known scanning position.
INVESTIGATION OF THE RADIOMETRIC BEHAVIOUR OF A LOW-COST AUTOMOTIVE LIDAR SENSOR
Authors: Zhang Z. , Zeng Z. , Boehm J.
Published: December 2023

Abstract. Terrestrial LiDAR is an established method for 3D data acquisition in close-range applications. A new category of low-cost LiDAR sensors for autonomous driving has become available with similar specifications. However, these new sensors lack the guarantee of survey-grade performance. Initial experiments have broadly confirmed the specification of one such low-cost sensor but have also raised issues with the radiometric behaviour. This study investigates through practical experiments how the intensity information of the Livox-Mid40 laser scanner is influenced by time, reflectance, distance and angle of incidence. The quantitative analysis of the experiments shows an expected relationship between surface reflectance and recorded intensity. However, the result indicate that intensity can significantly influence the distance measurement at very close ranges.
AN EVALUATION OF SOLID-STATE LIDAR FOR LOCALIZATION AND HD POINT CLOUD MAPPING
Authors: Lu Y.-E. , Chiang K.-W. , Tsai M.-L. , Chiu Y.-T. , Srinara S. , Wu T.-C. , El-Sheimy N.
Published: December 2023

Abstract. Cost-effective navigation and positioning systems for autonomous vehicles has become a key focus of research in recent years. Having an accurate position within a lane is vital to enabling high levels of automation and improving safety. Traditionally, vehicle navigation and positioning systems have relied heavily on the Global Navigation Satellite System (GNSS), particularly in open-sky scenarios. However, GNSS signals can be easily disrupted by environmental interferences. These include phenomena such as urban canyons, which result from multi-path interferences, as well as challenges posed by Non-Line-of-Sight (NLOS) situations. In the pursuit of developing robust systems resilient to such issues, the concept of sensor fusion has been widely employed. Among all sensors used in commercial self-driving vehicles, mechanical LiDAR is the primary sensor. Utilizing point cloud data from LiDAR and registering it with a prior point cloud map can result in highly accurate position results. However, the high cost of mechanical LiDAR has limited the mass production of point cloud map and autonomous vehicle. In this paper, we evaluate several successful Simultaneous Localization and Mapping (SLAM) architectures from LiDAR-based to LiDAR-Inertial-based using single Solid-State LiDAR (SSL). Last, we proposed a single SSL mapping and localization framework that can achieve 36 centimeters 3D RMSE and 0.5 degree accuracy in heading estimation.
STRATEGY ON HIGH-DEFINITION POINT CLOUD MAP CREATION FOR AUTONOMOUS DRIVING IN HIGHWAY ENVIRONMENTS
Authors: Srinara S. , Chiu Y.-T. , Chen J.-A. , Chiang K.-W. , Tsai M.-L. , El-Sheimy N.
Published: December 2023

Abstract. In recent years, a lot of researchers have been trying the development of efficient ways to create HD maps with centimeter-level precision. Mobile mapping system (MMS) produce 3D HD point cloud map of the surrounding by integrating navigation (i.e., direct georeferencing or DG process) and high-resolution imaging sensor data. Unfortunately, in partially environments, the provided accuracy of the GNSS system degrades dramatically. In order to constraint the drift and correct the georeferenced point cloud map, ground control points (GCPs) are placed along the road. Moreover, there are approaches which use laser-based point cloud registration techniques to construct the point cloud map. However, all promising mapping techniques which currently use the laser as the core sensor for mapping the high-definition point cloud map may not be promised to construct the point cloud map in partially or unfriendly environments. As a literature review and result, a suitable approach for creating the promising point cloud map is to combine the INS/GNSS navigation solution, LiDAR matching techniques, and GCPs. Thus, this study introduces the HD point cloud map generation method that can potentially help researchers create personalized and globalized HD point cloud maps and develop new HD point cloud map generation methodologies.
COST-EFFICIENT METHODS OF DERIVING SLOPE INFORMATION FOR ROAD SEGMENTS IN DRIVER-ASSISTANCE APPLICATIONS
Authors: Horváth V. , Barsi A.
Published: December 2023

Abstract. An advanced driver-assistance system (ADAS) is any of a group of technologies that assist drivers in driving and parking functions. Through a safe human-machine interface, ADAS increase car and road safety. These Advanced driver-assistance systems rely on special maps with extended geometry and attribute information. This extra information includes slope, curvature, and speed limit. ADAS-enabled maps are usually rather expensive in the industry. This paper is focused on finding cost-efficient alternatives for generating the slope aspect of ADAS maps. Slope and height information is not only used in ADAS but is a critical aspect of calculating electronic vehicle (EV) ranges, and truck fuel-efficiency calculations as well. ADAS slope information usually requires high-accuracy surveys. This paper researches the possible generation of slope information for road segments with the use of digital elevation models (DEM) or crowdsourcing with low-cost sensors and Kalman filtering. The first approach is based on globally available DEMs with interpolation and filtering with road geometry. DEMs have variable accuracy depending on the type of technology used in producing them. Such technologies include photogrammetry, aerial and terrestrial laser scanning (ALS, TLS), or aerial or space radar measurements. The other method is by using low-cost GPS and IMU sensors for generating altitude profiles. These produced altitude profiles are compared with a profile generated from a high-accuracy survey using large-resolution DEMs produced by aerial photogrammetry or aerial laser scanning. This paper proposes metrics with which these datasets can be compared, one is using the height differences, and the other compares the slope values at discrete common points. In the conclusion, the paper tries to find use cases for the low-accuracy data.
ENHANCING URBAN VEHICULAR NAVIGATION: IMPROVING CLASSICAL TOPOLOGICAL MAP MATCHING THROUGH RAY-CASTING
Authors: Ragab H. , Givigi S. , Noureldin A.
Published: December 2023

Abstract. Navigation is of paramount importance for land vehicles as it enables efficient and accurate movement from one location to another. Whether it is for personal navigation, commercial transportation, or emergency services, reliable navigation systems play a crucial role in ensuring safety, optimizing routes, and enhancing overall operational efficiency. This paper presents the integration of classical Topological Map Matching (TMM) with the Global Navigation Satellite System (GNSS) and the Inertial Navigation System (INS), addressing the limitations of relying solely on road centerlines. A novel solution is proposed, leveraging the ray-casting algorithm to determine the predicted position’s area and employing a two-stage kinematic update process for enhanced positioning accuracy. The solution’s efficacy is evaluated through tests conducted on simulated GNSS outages within a road experiment conducted in the City of Toronto, demonstrating substantial improvements compared to the classical TMM approach. Notably, the proposed method achieved a considerable 82.33% reduction in RMS positioning error and a 33.71% improvement in maximum positioning error during the longest GNSS outage. By overcoming the limitations of classical TMM algorithms, this research contributes to the advancement of navigation and tracking systems, with future work focusing on practical implementations and optimization for diverse navigation scenarios.
Հանրային գնումների ընթացակարգերը աշխարհում և ՀՀ-ում / Public Procurement Procedures Worldwide and in RA
Authors: SARAFYAN LUIZA
Published: December 2023

Emphasizing the existence of an effective public expenditure management system
and the need to reduce corruption risks in the budget process, in parallel with certain
reforms carried out in the field of public finance, since 2000 the authorities of the Republic
of Armenia have initiated the introduction of a unified public sector procurement system
that meets international standards.
For a more purposeful implementation of the public procurement process in the
RA, in accordance with the RA Law “On Procurement”, special procurement procedures
have been established for the purchase of various types of goods, works and services.
Lewis, Sophie, Abolish the Family, Londres, Verso Books, 2022, 122 pp.
Authors: Terán Ira
Published: December 2023

Abolish the Family [abolid la familia] es la incendiaria consigna con la que la pensadora transfeminista y socialista Sophie Lewis titula su último ensayo. Tras la publicación del también controvertido Otra subrogación es posible (2019), la hija intelectual y queer de Shulamith Firestone ha regresado dispuesta a derribar el teatro edípico de la sociedad capitalista desde sus cimientos. Para tal fin, Lewis organiza un desfile de genealogías radicales en el que se dan cita filosofías políticas, experimentos revolucionarios, diversas tradiciones militantes y prácticas de resistencia en torno a comunidades oprimidas, que le asisten en la ardua tarea conceptual y libidinal de trazar el horizonte de la abolición de la familia, de imaginar, en última instancia, una vida más allá de los parentescos conocidos.
En el corazón de la política: medios y fines. El uso del mal. El enfoque de Simone Weil
Authors: Álvarez Yágüez Jorge
Published: December 2023

De manera analítica pretende exponerse aquí la respuesta de Simone Weil a la cuestión que dejara formulada en el inicio de la modernidad, Maquiavelo, la cuestión del uso del mal. Esta cuestión queda inscrita en toda la larga reflexión que la autora francesa hiciera sobre la lógica entre medios y fines que fatalmente rige nuestra cultura, y conduce a una constante inversión en la que los medios se convierten en el auténtico fin. Entendiendo que estas dos cuestiones constituyen el núcleo de todo pensamiento político, que se ocupe de la organización de nuestra vida en común, Simone Weil no podía por menos de ocuparse intensamente en ello, de principio a fin de su obra.
EVAAN: An empirical verification argument against naturalism
Authors: Blondé Ward
Published: December 2023

Alvin Plantinga’s evolutionary argument against naturalism (EAAN) claims that if both naturalism (N) and evolutionary theory (E) are true, then all our beliefs are unreliable (premiss 1). Consequently, given N&E, the belief in N&E is unreliable (premiss 2) and N&E is self-defeating (conclusion). The empirical verification argument against naturalism (EVAAN) is more cautious and improves EAAN by withstanding a rejoinder of the evolutionary naturalist to premiss 1. EVAAN claims that non-abstract beliefs that are not empirically verifiable are unreliable, given N&E (premiss 1a). This anticipates the evolutionary naturalist’s claim that empirical verifications play a crucial role in peer assessments and sexual selection of intelligence, and that, therefore, N&E makes empirically verifiable beliefs often reliable (premiss-1 rejoinder). However, even then it can be argued that the belief in N&E is unreliable, given N&E (premiss 2), because N&E is neither abstract, nor empirically verifiable (premiss 1b). EVAAN distinguishes reliably verifiable intelligence from metaphysical intelligence and claims that, if N&E is true, humans are lacking metaphysical intelligence. This paper also contains an argument against EAAN, by supporting the premiss-1 rejoinder.
Desdicha, lenguaje y universalidad: variaciones sobre el concepto de malheur en tres momentos de la obra de Simone Weil.
Authors: Ariza Sadurní Martí
Published: December 2023

En el pensamiento político weiliano despunta significativamente la noción de malheur. Se trata de un concepto que opera como lugar privilegiado desde el que poder enlazar coherentemente las múltiples dimensiones de la filosofía weiliana. Asimismo, resulta especialmente fértil para comprender el alcance y la vigencia de las reflexiones políticas de la pensadora francesa. Con la intención de ensayar un vínculo entre los estudios weilianos y parte destacada de la filosofía política contemporánea, en este artículo se proponen tres ejes fundamentales de investigación: atender al desajuste entre lenguaje y desdicha; delimitar analíticamente la noción de malheur estableciendo las coordenadas para una distinción con respecto a la victimidad; y examinar el privilegio del particular-desdichado que anuncia repetidamente Weil en su obra. El presente artículo tratará de mostrar en qué medida Simone Weil tematiza con asombrosa precisión tres cuestiones de interés fundamental para la comprensión de nuestro presente: desdicha, lenguaje y universalidad.
El «momento marxista» de Foucault: La sociedad punitiva en perspectiva
Authors: Chamorro Emmanuel
Published: December 2023

El presente artículo analiza el curso que Michel Foucault dictó en 1973 en el Collège de France titulado La sociedad punitiva. Mediante una reconstrucción conceptual y contextual del curso trataremos de evidenciar su deuda con la perspectiva marxista. Esta deuda da forma a un análisis que atiende a la especificidad de las relaciones de poder, pero –en consonancia con el planteamiento de buena parte de los movimientos radicales y contraculturales de la época– las vincula con el desarrollo de la sociedad capitalista. Crítica de la economía política, genealogía de la moral y análisis del poder constituyen, así, los tres ejes desde los que se propone una historia de la sociedad disciplinaria sensiblemente diferente de la que el propio Foucault ofrecerá solo dos años después en Vigilar y castigar. De este modo, el curso de 1973 evidencia el fundamento marxista de las investigaciones que Foucault desarrolla en la primera mitad de la década de los setenta y cuyo abandono impactará enormemente en su obra alrededor del gobierno y el cuidado de sí.
Hígado graso no alcohólico: clasificación e historia natural
Authors: Hernández Teixidó Carlos
Published: December 2023

A pesar de que la acumulación de grasa en el hígado es común, la mayoría de las personas con NAFLD no experimenta síntomas, pero un subconjunto desarrolla una forma más grave de la enfermedad conocida como esteatohepatitis no alcohólica (NASH). Existen varios sistemas de clasificación utilizados en la práctica clínica. La clasificación más comúnmente utilizada es la del American Association for the Study of Liver Diseases (AASLD), que se basa en la histología hepática y divide la enfermedad en cuatro estadios: esteatosis simple, NASH sin fibrosis, NASH con fibrosis y cirrosis. Comienza con el acumulo de grasa en el hígado que puede progresar a una inflamación crónica (NASH), fibrosis y, finalmente, cirrosis, insuficiencia hepática y cáncer de hígado. Varios estudios experimentales han demostrado que los hígados esteatósicos presentan un riesgo del 25 % de progresar por sí mismos a NASH con y sin fibrosis. Este riesgo se ve sustancialmente aumentado por la concomitancia de factores de riesgo metabólicos. La diabetes, el aumento de peso, la hipertensión, la menopausia y los polimorfismos genéticos son los principales factores de riesgo para la progresión de la NAFLD. Un tercio de los pacientes con esteatosis simple y NASH, presenta progresión de la fibrosis, pero un 20 % aproximado presenta regresión de la misma. La fibrosis hepática es el único predictor mayor independiente de mortalidad.
Digital-Awareness Age and Foam Consciousness Cycle: A Model Essay on the New Form of Consciousness
Authors: ÖZTÜRK Ali
Published: December 2023

Human consciousness is a complex phenomenon that involves various activities such as perception, interpretation, positioning, and development. However, these activities are influenced by the cultural zeitgeist, available tools, and existing consciousness infrastructure. In the digital age, people are faced with a new awareness contract, which requires us to find new ways of engaging with the consequences of these interactions, rather than relying on fixed working principles of the human mind. To achieve this, we need a new model that can explain how human consciousness is shaped by the big data of the digital age. This model should also describe how significant mechanisms manipulate human consciousness and prevent us from questioning them and developing systematic answers. To develop this model, I conducted a qualitative study that involved face-to-face interviews with 17 participants. The study enriched two models: a "foam consciousness cycle diagram" and a complicated consciousness algorithm cycle. These models are based on image epistemology and incorporate philosophical, sociological, and psychological perspectives. In summary, the digital age requires us to rethink our understanding of human consciousness and develop new models that can help us navigate the complex interactions between technology and society.
Dijital Çağda Dini Ritüel Algısının Dönüşümü
Authors: BERK Selver , ÇETİN Beyzade Nadir
Published: December 2023

Bu çalışma, tarihsel süreç içerisinde yaşanan gelişmelerden en güncel olan dijital çağın toplumsal kurumlar arasından din kurumuna etkileri ve bunun sonucunda ortaya çıkan bireysel ve toplumsal anlamdaki değişiklikleri belirleme amacı taşımaktadır. Bu noktada dijital çağda din eğitimi alan bireyler ve dijitalleşme ile din kurumunun kesişimi ile karşılaştıkları deneyimler ve verdikleri tepkiler önem arz etmektedir. Bu çalışmada teknolojik gelişmelerin dini alana sirayet etmesi neticesinde görüşmecilerin tekno- dini pratikleri yaşamlarına yansıtış biçimlerini ve din kurumu algısının değişimi ve dönüşümünü belirlemek amacıyla derinlemesine görüşme tekniği kullanılmıştır. Tekno dini pratikler bağlamında değişen, dönüşen ve farklılaşan din fenomeni üzerinden oluşturulan çalışma, Kahramanmaraş İlinde yer alan Hacı Mehmet Kalay Kız Anadolu İmam Hatip Lisesi'nde eğitim gören 15 gönüllü kız öğrenci ile yapılan görüşmelerin sonucudur. Alan araştırması sonunda dijital iletişim teknolojilerinin gün geçtikçe çeşitlenmesi, fonksiyonlarının artması ve yaygınlaşması, bireysel ve toplumsal düzeyde hızlı bir dijitalleşme sürecine geçilmesini sağlayarak din olgusunu da etkisi altına aldığı görülmüştür. Bu bağlamda, üretilen dijital dini uygulamaların varlığı söz konusu olmuştur. Dijital gelişmelerin dini eğitime ve pek çok dini alana kolaylık sağladığı, katılımcıların yaşamlarının daha pratik hale geldiği gerçeği ortaya çıkmıştır. Katılımcıların teknolojik gelişmeleri dini yaşam alanlarında etkin bir şekilde tercih ettikleri görülmüştür.
The Success of Public Private Partnerships with Transparency and Accountability Principles
Authors: ÇAKMAK Mustafa Doğukan , GEDİZ ORAL Burcu
Published: December 2023

Harsh debates on the restructuring of public administration and the failures of states have continued for decades, Public Private Partnership (PPP) suggests a different function to the state as an application of the "New Public Management" approach, for solving some of these debates. Although PPP can be briefly defined as the provision of public services by the private sector, its complex relationship structure and risks behind this definition do likely make the model unsuccessful. In pursuit of the best model, international organizations and mechanisms, including the OECD, the UN, and the European Commission, have attempted to apply some models of successful examples, procedures, and laws. Some studies learning from faulty designs and experiences have focused on what should not be. As a result, the critical success factors seem to be the most proper tool to improve the PPP method. This study focuses on providing support information for countries trying to design and develop a PPP model. Afterward, it deals with the performance-measured PPP applications in the world in the context of transparency and accountability and reveals the significance of the principles of transparency and accountability in the success of the PPP model.