bluuebunny/crossref_metadata_2025 huggingface dataset:
Estimating flood discharge at river bridges using the entropy theory. Insights from Computational Fluid Dynamics flow fields
Authors: Bahmanpouri Farhad , Lazzarin Tommaso , Barbetta Silvia , Moramarco Tommaso , Viero Daniele Pietro
Published: December 2023

Abstract. Estimating the flow velocity and discharge in rivers is of particular interest for monitoring, modelling, and research purposes. Instruments for measuring water level and surface velocity are generally mounted on bridge decks, and this poses a challenge because the bridge structure (e.g., piers and abutments) can lead to perturbated flow fields. The current research aims to investigate the applicability of the entropy theory to estimate the velocity distribution and the discharge in the vicinity of river bridges. To this purpose, a Computational Fluid Dynamics (CFD) model is used to obtain three-dimensional flow fields along a stretch of the Paglia River (central Italy), where a historical multi-arch bridge strongly affects flood flows. The input data for the entropy model include the cross-sectional bathymetry and the surface velocity provided by the numerical simulations. Different flow conditions and cross-sections, either upstream and downstream of the bridge, are considered. It is found that the entropy model can be applied safely upstream of the bridge, also when forced with a single (i.e., the maximum) value of the surface velocity, with errors on total discharge below 13 % in the considered case. On the contrary, downstream the bridge, the wakes generated by the bridge piers strongly affect the velocity distribution, both in the spanwise and in the vertical directions, and for very long distances. Here, notwithstanding the complex and multimodal spanwise distribution of flow velocity, the entropy model estimates the discharge with error lower than 8 % if forced with the river-wide distribution of the surface velocity. The present study has important implications for the optimal positioning of sensors and suggest the potential of using CFD modelling and entropy theory jointly to foster the knowledge of river systems.
APPLICATION OF LUCAS-KANADE DENSE FLOW FOR TERRAIN MOTION IN LANDSLIDE MONITORING APPLICATION
Authors: Yordanov V. , Truong X. Q. , Corti M. , Longoni L. , Brovelli M. A.
Published: December 2023

Abstract. Landslides are natural hazards that can cause severe damage and loss of life. Optical cameras are a low-cost and high-resolution alternative among many monitoring systems, as their size and capabilities can vary, allowing for flexible implementation and location. Computer vision is a branch of artificial intelligence that can analyze and understand optical images, using techniques such as optical flow, image correlation and machine learning. The application of such techniques can estimate the motion vectors, displacement fields, providing valuable information for landslide detection, monitoring and prediction. However, computer vision also faces some challenges such as illumination changes, occlusions, image quality, and computational complexity. In this work, a computer vision approach based on Lucas-Kanade optical dense flow was applied to estimate the motion vectors between consecutive images obtained during landslide simulations in a laboratory environment. The approach is applied to two experiments that vary in their illumination and setup parameters to test its applicability. We also discuss the application of this methodology to images from Sentinel-2 satellite optical sensors for landslide monitoring in real-world scenarios.
BENCHMARKING COLLABORATIVE POSITIONING AND NAVIGATION BETWEEN GROUND AND UAS PLATFORMS
Authors: Masiero A. , Morelli L. , Toth C. , Remondino F.
Published: December 2023

Abstract. The availability of Global Positioning System (GPS), or more in general of Global Navigation Satellite Systems (GNSS), and the development of smart mobile devices, able to exploit the geospatial information provided by GPS/GNSS and integrate their use within many applications, have had a dramatic impact on the everyday life of most of the World population. While GNSS allows for real-time positioning in a wide range of scenarios, there are many challenging environments, such as tunnels and urban canyons, where GNSS-based solutions are inaccurate, unreliable, or even unavailable. The enormous interest in applications requiring ubiquitous positioning (e.g., self-driving vehicles) has been motivating the development of alternative positioning systems to support or substitute GNSS when operating in challenging scenarios. Alternative positioning systems to GNSS are usually developed by employing several sensors, such as radio-based, vision, LiDAR (Light Detection and Ranging), and RADAR (Radio Detection and Ranging). Furthermore, a collaborative approach can also be developed to increase the robustness of the navigation solution of inter-connected vehicles. To support research in this area, we are presenting the CONTEST (Collaborative pOsitioning and NavigaTion bEtween ground and uaS plaTforms) dataset, aiming at providing multiple data streams to test collaborative positioning approaches, involving both terrestrial and aerial platforms, based on the use of several sensors, such as Ultra-Wide Band (UWB) transceivers, cameras, LiDARs, GNSS. Data are described and some initial results presented.
M-AFDE-NET: NOVEL DEEP LEARNING-BASED BUILDING CHANGE DETECTION OF FRESHLY BUILT LOCALES FROM SATELLITE IMAGERY IN THE NILE VALLEY, EGYPT
Authors: Holail S. , Saleh T. , Xiao X. , Shao Z. , Sui H. , Li D.
Published: December 2023

Abstract. Urban land expansion is a defining characteristic of urbanization, necessitating the monitoring of this phenomenon and the detection of changes to promote sustainable land use and contribute to updating geospatial databases. Methods based on detecting changes in high-resolution satellite imagery have shown poor performance due to downsampling during image processing, resulting in the loss of boundary information. Furthermore, these methods struggle with complex backgrounds where the ground resembles building roofs. This paper delves into the investigation and evaluation of Freshly Built Locales (FBLs) using bi-temporal images through recently proposed computer vision networks. To address the limitations of existing approaches, we have introduced modifications to the AFDE-Net model, which include the novel residual pyramid attention fusion (RPAF) module. This enhancement enables more precise identification of intricate details in complex change detection scenarios. Our proposed model, M-AFDE-Net, has been evaluated on a newly captured dataset from the Nile Valley regions of Egypt, with a spatial resolution of 30 cm. Special attention has been given to New Mansoura and New Tiba as focal areas for analysis. The evaluation results reveal that the modified model, M-AFDE-Net, outperforms other state-of-the-art models in detecting FBLs. It achieves an impressive F1-score of approximately 89.2%, demonstrating its superiority and effectiveness.
COMPARISON OF DEEP LEARNING ARCHITECTURES FOR THE SEMANTIC SEGMENTATION OF SLUM AREAS FROM SATELLITE IMAGES
Authors: Lumban-Gaol Y. A. , Rizaldy A. , Murtiyoso A.
Published: December 2023

Abstract. The mapping of slum areas is an important task when considering the necessity for an inclusive, safe and resilient cities. While many methods exist in this regard, the use of machine learning and more specifically deep learning has gained traction in recent years. In this paper, we present a systematic comparison of existing deep learning architectures and backbones. The experiments in the paper investigate the question of which architecture and backbone combination and which configuration of dataset preparation is best for use in slum mapping. In another experiment we implemented the trained model to predict slums in existing open data. The experiments in the paper used public open data provided by Helber et al. (2018). Results show that FPN with vgg16 backbone showed the most potential in this particular application. The results of the semantic segmentation also shows promise, although the discrepancy in slum characteristic still hinders a proper generalization of its use.
DEFORMATION MONITORING AND TIME-SERIES & DISASTER POTENTIALITY ANALYSIS OF GAS PIPELINE USING SENTINEL DATA
Authors: Wang X. , Zhang P. , Wu J. , Li Z. , Tang W. , Sun Z.
Published: December 2023

Abstract. Synthetic aperture radar interferometry (InSAR) measurement technology is a new remote sensing technology that can effectively monitor slight land deformation. Compared with traditional monitoring technology, InSAR technology has the advantages of wide coverage, all-weather and low cost, providing a technical means of high-resolution, high-precision and low-cost for hidden geological hazard identification and deformation monitoring along pipelines. For purpose of this paper, we performed deformation time-series comprehensive processing and analysis on gas pipeline based on Sentinel-1 image data through small baseline data processing, and extracted pipeline deformation quantities from 2020 to 2022. The land deformation rate of the ascending track data during this period ranges from −43 mm/year to 25 mm/year, and that of the descending track data from −66 mm/year to 33 mm/year. The results show that the area along the gas pipeline is in stable condition on the whole, deformation mainly occurred along a section in the northwest of Haidian District, and a large quantity of deformation occurred since January of 2020 until December of 2021, with the maximum deformation quantity of −70mm, This result provided a reliable reference for safety monitoring and repair & maintenance of the gas pipeline.
SEMANTIC ENRICHMENT OF 3D POINT CLOUDS USING 2D IMAGE SEGMENTATION
Authors: Rai A. , Srivastava N. , Khoshelham K. , Jain K.
Published: December 2023

Abstract. 3D point cloud segmentation is computationally intensive due to the lack of inherent structural information and the unstructured nature of the point cloud data, which hinders the identification and connection of neighboring points. Understanding the structure of the point cloud data plays a crucial role in obtaining a meaningful and accurate representation of the underlying 3D environment. In this paper, we propose an algorithm that builds on existing state-of-the-art techniques of 2D image segmentation and point cloud registration to enrich point clouds with semantic information. DeepLab2 with ResNet50 as backbone architecture trained on the COCO dataset is used for indoor scene semantic segmentation into several classes like wall, floor, ceiling, doors, and windows. Semantic information from 2D images is propagated along with other input data, i.e., RGB images, depth images, and sensor information to generate 3D point clouds with semantic information. Iterative Closest Point (ICP) algorithm is used for the pair-wise registration of consecutive point clouds and finally, optimization is applied using the pose graph optimization on the whole set of point clouds to generate the combined point cloud of the whole scene. 3D point cloud of the whole scene contains pseudo-color information which denotes the semantic class to which each point belongs. The proposed methodology use an off-the-shelf 2D semantic segmentation deep learning model to semantically segment 3D point clouds collected using handheld mobile LiDAR sensor. We demonstrate a comparison of the accuracy achieved compared to a manually segmented point cloud on an in-house dataset as well as a 2D3DS benchmark dataset.
A COMPARATIVE STUDY OF DEEP ARCHITECTURES FOR VOXEL SEGMENTATION IN VOLUME IMAGES
Authors: Wagner F. , Maas H.-G.
Published: December 2023

Abstract. This study investigates the performance of eight different deep learning architectures for voxel segmentation in volume images. The motivation is to segment carbon in carbon reinforced concrete (CRC) in micro-tomography (μ-CT) data. Although there are many 3D convolutional neural networks (CNNs) available, it is not yet clear which one works best for these specific tasks. In this study, the authors compare the following networks: DenseVoxNet, HighResNet, Med3D, Residual 3D U-Net, 3D SkipDenseSeg, 3D U-Net, V-Net, and LV-Net. To provide a more general recommendation for selecting a neural network, three medical datasets were added in addition to the three CRC datasets to facilitate the selection of an appropriate network based on the dataset characteristics. The experiments emphasize the importance of the initial random state, used for example to initialize the network weights. On average, the 3D U-Net is the best generalizing CNN, followed by the Residual 3D U-Net and the 3D SkipDenseSeg. While the 3D U-Net is a good architecture to start with, the experiments show that it does not perform best on all domains. To achieve optimal results, the authors propose recommendations for selecting a 3D neural network based on the dataset attributes.
FOREST FEATURE LIDAR SLAM (F2-LSLAM) AND INTEGRATED SCAN SIMULTANEOUS TRAJECTORY ENHANCEMENT AND MAPPING (IS2-TEAM) FOR ACCURATE FOREST INVENTORY USING BACKPACK SYSTEMS
Authors: Zhao C. , Zhou T. , Fei S. , Habib A.
Published: December 2023

Abstract. Under-canopy mapping is desired to derive critical forest biometrics, such as diameter at breast height (DBH), merchantable height, and debris volume. The main challenge of such under-canopy mapping is the intermittent access to the global navigation satellite system (GNSS) signal, which is crucial to deriving accurately georeferenced mapping products. In this study, we propose two frameworks – Forest Feature LiDAR Simultaneous Localization and Mapping (F2-LSLAM) and Integrated Scan Simultaneous Trajectory Enhancement and mapping (IS2-TEAM) – for 3D LiDAR unit mounted on backpack systems to achieve accurate forest inventory. In the F2-LSLAM strategy, ground/tree trunk features are extracted from individual LiDAR scans. On the other hand, when trajectory information provided by navigation sensors is available, these semantic features are derived from LiDAR points within several scans (i.e., integrated scan) for the IS2-TEAM strategy. Then, local/global least squares adjustment (LSA) using derived features is performed to register LiDAR scans to a common reference frame for both strategies. To evaluate the performance of the proposed strategies, three in-house developed backpack systems with varying specifications were used to collect data in complicated forest environments. Through the comparison with point clouds acquired by a commercial backpack LiDAR system, the proposed frameworks are capable of generating point clouds with satisfactory intra-dataset alignment quality (in the range of 2–4 cm) for all backpack systems in natural forest areas with relatively flat terrain. However, for more challenging areas with dense undergrowth vegetation and/or large height differences, F2-LSLAM framework cannot extract sufficient features, while IS2-TEAM still exhibits good performance.
VISION SYSTEM FOR MONITORING SEISMIC TESTS IN CONCRETE SHELLS
Authors: Brandão M. , Valença J. , Júlio E.
Published: December 2023

Abstract. Structural monitoring plays a crucial role in assessing damage and detecting potential faults. Vision systems provide real-time information about the behaviour and state of conservation of structures, enabling precise and efficient analysis. Computer vision algorithms are employed to analyse images and extract relevant structural information. This information may encompass key points' displacement and deformation within the structure.This paper introduces a methodology for monitoring dynamic tests using computer vision. The approach employs a camera to track artificial targets placed on the structure. The camera captures multiple images during the tests and detects the coordinates of the target centres. Subsequently, displacements are calculated based on the differences in coordinates among the aforementioned targets.To validate the methodology, an experimental study was conducted using dynamic tests on a reduced-scale model of a thin concrete shell tested on a seismic table. Five dynamic tests were carried out, involving varied amplitude and frequency values to test the proposed approach. The results substantiate the efficacy of computer vision in monitoring dynamic tests. In conclusion, the developed methodology facilitates dynamic test monitoring through computer vision by continuously tracking artificial targets throughout the tests and computing their displacements.
CONSTRUCTION AND APPLICATION OF THE GEOTECHNICAL AND GEOLOGICAL SPATIOTEMPORAL BIG DATA PLATFORM IN XIONGAN NEW AREA
Authors: Zhang X. , Gong X. , Du Y. N. , Dong T. , Wang Q. , Li B. B. , Yan X. R.
Published: December 2023

Abstract. As an important foundation for the construction of smart cities, spatiotemporal Big data plays a significant role in promoting intelligent urban management and enhancing urban governance capabilities, among which geotechnical and geological data is an indispensable component. Currently, with the implementation of geological investigation and underground space development in Xiongan New Area, a large amount of geotechnical and geological data has been accumulated. However, these data have the characteristics of multiple sources, multiple categories, multi-dimensions, and multiple formats, resulting in isolated and dispersed data, poor integration, and difficulty in achieving data sharing and comprehensive application. In response to the above issues, we have utilized new technologies such as the Internet of Things, Big data, and cloud computing, as well as key technologies such as integration, modeling, visualization, and sharing of geotechnical and geological spatiotemporal Big data, to construct the geotechnical and geological spatiotemporal Big data platform system with the "Three Ones" as the core, namely "a net", "a database", and "a information system". The integrated application of multi-source and heterogeneous geotechnical and geological Big data has been achieved, and a three-dimensional underground digital base has been built in Xiongan New Area. Through the integration of three-dimensional spatiotemporal big aboveground and underground data, the perspective management and auxiliary decision-making of aboveground and underground integration have been achieved, providing strong support for the high-quality development of smart citiy in Xiongan New Area.
UNDERSTANDING USER EQUILIBRIUM STATES OF ROAD NETWORKS USING BIG TRAJECTORY DATA
Authors: Chen B. Y. , Chen X.-Y. , Chen H.-P.
Published: December 2023

Abstract. User equilibrium (UE) has long been regarded as the cornerstone of transport planning studies. Despite its fundamental importance, our understanding of the actual UE state of road networks has remained surprisingly incomplete. Using big datasets of taxi trajectories, this study investigates the UE states of road networks in Wuhan. Effective indicators, namely relative gaps, are introduced to quantify how actual traffic states deviate from theoretical UE states. Advanced machine learning techniques, including XGBoost and SHAP values, are employed to analyze nonlinear relationships between network disequilibrium states and seven influencing factors extracted from trajectory data. The results reveal significant gaps between actual traffic states and the theoretical UE states at various times of the day during both weekdays and weekends. The XGBoost analysis shows that differences in travel distances, travel speeds, and signalized intersection numbers among alternative routes are the primary causes of road network disequilibrium. The results of this study could have several important methodological and policy implications for using the UE models in transport applications.
AN INTERACTIVE EVACUATION TOOL TO IMPROVE THE PUBLIC FLOOD PERCEPTION
Authors: Li W. L. , Treff N. , Amann F. , Lehmen J. , Dehbi Y. , Haunert J.-H.
Published: December 2023

Abstract. The advancing climate change increases the danger of heavy rainfall events and devastating floods, which significantly threaten people’s lives and properties. Geographic information system (GIS) has been a valuable tool for mapping flood risks and emergency management worldwide. In this paper, we develop an interactive evacuation tool to improve public flood perception. This work presents how to create an interactive and animated evacuation tool to strengthen the population’s preparedness and action ability in case of a flood. We simulate water depths and flow velocities for a flood scenario in Bonn, Germany. Afterwards, we investigate the flood’s impact on buildings and streets for different flood situations using geoinformation tools in the software QGIS. Based on thresholds from the literature, we identify endangered buildings where inhabitants have to evacuate and streets still ensuring safe locomotion options during the advancing flood. Taking possible shelter points for the population into account then allows for computing the shortest path to the nearest shelter at each flood situation. Our findings are summarized in evacuation maps that can be used together as interactive information tools for the public and can also serve rescue management and disaster education.
REMOTE SENSING OF URBAN DEVELOPMENT AND ENVIRONMENTAL LANDSCAPE: A STUDY OF GREEN COVER LUNGS OF DELHI AND SURROUNDING CITY REGIONS
Authors: Mohan M.
Published: December 2023

Abstract. The remote sensing satellites have now a days been used for creation of geospatial databases of the earth surface features and natural resources as the land use land cover mapping and monitoring periodically at the local, regional, and global levels using geospatial technologies. The Land cover consider to the type of features present on the surface of the earth. Whereas, the land use considers to the human activity or the economic function associated with a specific piece of land. The supervised classification based on the maximum likelihood classifier technique has been applied to process the digital multi-spectral imagery for LULC classification. The built-up area was about 11.95 per cent in 1977 which increased to 19.74 per cent in 1999 and further increased to about 24.54 per cent in 2009. So, the urban landscape’s urban built-up land was composed by areas of intensive use with much of land covered by built-up structures. The cities, towns, villages, strip development along highways; transportation, power, and communication facilities; shopping centres, industrial and commercial complexes, and institutions found located in the urban areas have been developed over the periods. The forests cover area accounted to about 1.43 per cent in 1977 which increased to about 10.04 per cent in 1999. The forest cover regeneration over the Delhi Ridge recognized as a significant contributor to carbon sequestration, micro-climate change, biodiversity restoration for the Delhi’s urban development and rejuvenation of environmental landscape. So, the remote sensing imagery have commonly been used for urban landscape monitoring and environmental modelling for sustainable development of Delhi and adjoining city regions.
ASSESSING THE RELATION BETWEEN LAND USE / LAND COVER CHANGES AND ENVIRONMENTAL PARAMETERS FOR CHENNAI CITY, TAMIL NADU: A REMOTE SENSING AND GIS APPROACH
Authors: MuraliKrishna I. , Sahithi V. S.
Published: December 2023

Abstract. Land use land cover changes in coastal regions are prone to many factors like rapid urbanization and industrialization, tourism, and tideline changes etc. Chennai city, a coastal city of TamilNadu, India has witnessed tremendous changes in land use land cover over the past two decades due to rapid urbanization and industrialization. Remote sensing and GIS technologies can efficiently help in analyzing these changes. In this study, changes in land use land cover patterns of Chennai city from 2005 to 2016 were assessed using IRS P6 LISS III remotely sensed satellite images. Post classification comparison-based change detection method was used to identify the changes in LU/LC. The study shows an increase in compact built-up and industrial areas by 15.36 % and 7.22 % respectively and a decrease in agricultural land, wetlands, and water bodies by 3.66%, 1.73%, and 5.24% respectively over the past decade. The obtained LU/LC changes were correlated with environmental parameters like Land surface temperature (LST), annual average rainfall and average groundwater level to establish a relation. Observations have shown that the temperature in Chennai metropolitan city has increased by 6̊c from 2005 to 2016 and the rainfall has reduced by 100mm from 2005 to 2016. This study demonstrated the relation between LU/LC changes over the past decade and the variations in environmental parameters like increased LST, reduced rainfall and groundwater.
DYNAMIC MONITORING OF THE CHAO LAKE DURING THE FLOOD SEASON BASED ON GAOFEN-3 SAR IMAGERY
Authors: Zhang X. , Sun J. , Dong D.
Published: December 2023

Abstract. Ecological environment of lakes is vital to the people’s livelihood. The flood disaster of lakes not only causes direct economic loss, but also breaks down the social order. Chao Lake, located in the middle and lower reaches of the Yangtze River, is one of the five major freshwater lakes in China with the area of 780 square kilometers. The dynamic monitoring of floods in the Chao Lake plays a crucial role in preventing flood disasters in the Anhui. This paper used CNNs to detect the flooded area of the Chao Lake from the Gaofen-3 SAR imagery from July and September 2020, July 2021, and August 2022. Then, the water area and water level were calculated to conduct a further quantitative analysis. The experiments demonstrate that SAR images play a crucial role in rapidly extracting water body information and monitoring the evolution of flooding.
A CAMERA-LIDAR CALIBRATION METHOD ASSISTED BY INDOOR SPATIAL STRUCTURE
Authors: Ye C. , Kang Z. , Guo X.
Published: December 2023

Abstract. The calibration of the camera and LiDAR is one of the basis for the construction of the multi-sensor fusion mapping system. Planar features of walls and grounds in indoor environments provides effective constraints for multi-sensor calibration. In this paper, we proposed a new camera-LiDAR calibration method with the constraint of indoor spatial structure. Using the image and point cloud data collected by sensors, visual odometry and LiDAR odometry can be constructed to calculate the transformation between sensors. Based on visual odometry and LiDAR odometry, structural parameters in indoor environment are extracted from images and point cloud to constrain rotation estimation between sensors. In the method proposed in this paper, lines are extracted from the images acquired by the camera and used to estimate and track vanishing points. The direction estimated with vanishing points is used as a global constraint to optimize the rotation parameter estimation of the camera. The fitted planes from the point cloud acquired by the LiDAR are used to compute a set of orthogonal normal vectors corresponding to the ground and wall surfaces, which are used as global constraints to optimize the rotation parameter estimation of the LiDAR. The calibration method proposed in this paper is targetless and only constrained by the indoor spatial structure. The result shows that the proposed indoor spatial structure constraint calibration method can calibrate LiDAR and camera without generating cumulative errors during the rotation estimation process.
MEASURING FOREST CANOPY WATER MASS IN THREE DIMENSIONS USING TERRESTRIAL LASER SCANNING
Authors: Elsherif A. , Gaulton R. , Mills J. P. , Sharaf El Din E.
Published: December 2023

Abstract. Canopy water mass is an important plant characteristic that can indicate the water status of vegetation. However, the parameter remains under-investigated because measuring it requires defoliating the canopy. This study introduced a non-destructive approach to estimate canopy water mass using terrestrial laser scanning data. Tree 3D models were generated from dual-wavelength TLS data for six forest canopies, then the models were utilized in estimating the canopy LAI, total leaf area, and vertical profiles of canopy leaf area. The estimates were then coupled with canopy equivalent water thickness estimates and vertical profiles of canopy water mass were generated. The results revealed some over- and underestimation in the estimated LAI, but the obtained accuracy was considered sufficient as leaf-on point clouds were used to generate the 3D models. The vertical profiles of canopy water mass showed that the leaf area distribution within the canopy, and the canopy architecture were the main parameters affecting the water mass distribution within the canopy, with mid canopy layers having higher water mass than the other canopy layers. This study showed the potential of TLS to estimate canopy water mass, but controlled experiments that include defoliating canopies are still needed for a direct and accurate validation of the TLS estimates of canopy water mass.
AIRBORNE SAFETY IN THE AGE OF 5G: ASSESSING THE POTENTIAL INTERFERENCE BETWEEN C-BAND AND AERONAUTICAL RADAR ALTIMETER
Authors: Elsayem A. , Elghamrawy H. , Massoud A. , Noureldin A.
Published: December 2023

Abstract. The recent deployment of 5G technology in the C-band frequency range has raised concerns regarding potential interference with aeronautical radar altimeters. 5G technology utilizes the C-band in the range of 3.7–3.98 GHz, which partially overlaps with the frequency range used by radar altimeters operating in the range of 4.2–4.4 GHz, resulting in an increased possibility of interference between the two systems. In this study, a comprehensive methodology was employed to conduct an interference analysis, investigating the compatibility between 5G wireless systems and radar altimeters. This involved implementing a realistic scenario that replicated the operational interaction between radar altimeters and 5G systems, with the goal of identifying the impact of 5G networks on radar altimeter performance. This paper outlines the scenarios leading to interference, and suggests feasible methods to overcome this issue.
Climatological occurrences of hail and tornadoes associated with mesoscale convective systems in the United States
Authors: Wang Jingyu , Fan Jiwen , Feng Zhe
Published: December 2023

Abstract. Hail and tornadoes are hazardous weather events responsible for significant property damage and economic loss worldwide. The most devastating occurrences of hail and tornadoes are commonly produced by supercells in the United States. However, these supercells may also grow upscale into mesoscale convective systems (MCSs) or be embedded within them. The relationship between hail and tornado occurrences with MCSs in the long-term climatology has not been thoroughly examined. In this study, radar features associated with MCSs are extracted from a 14-year MCS tracking database across the contiguous United States, and hazard reports are mapped to these MCS features. We investigate the characteristics of hail and tornadoes in relation to MCSs, considering seasonal and regional variabilities. On average, 8 %–17 % of hail events and 17 %–32 % of tornado events are associated with MCSs, depending on the criteria used to define MCSs. The highest total and MCS-associated hazard events occur from March to May, while the highest MCS-associated portion (23 % for hail and 45 % for tornadoes) is observed in winter (December–February) due to the dominance of MCSs caused by strong synoptic forcing. As hailstone size increases, the fraction associated with MCS decreases, but there is an increasing trend for tornado severity from EF0 to EF3 (Enhanced Fujita Scale). Violent tornadoes at EF4 and EF5 associated with MCSs were also observed, which are generated by supercells embedded within MCSs.
A Study on Awareness and Usage Pattern of J-Gate plus Web Portal Among the Research Scholars of Bharathiar University, Coimbatore
Authors: V. Rajendran  , P. Mahalakshmi
Published: December 2023

The paper provides information regarding awareness and usage pattern of j-gate plus web portal among the research scholars of Bharathiar University, Coimbatore. The main objective of the study was to assess the awareness of j-gate Plus (Online databases) and to assess the impact of online databases among the users in Bharathiar University. A structured questionnaire was used to gather data from 254 Research Scholars in the Bharathiar University. It is found that most of the respondents are using J-Gate and they are satisfied with the online databases available in the library.
Il “Marx” di Simone Weil. Un’analisi della critica weiliana del marxismo
Authors: Franco Alessia
Published: December 2023

Questo saggio esplora la critica a Marx e al “marxismo” sviluppata da Simone Weil nel corso della sua opera. Vengono identificati tre nuclei principali della critica weiliana al marxismo: la validità del metodo materialistico per lo studio delle scienze sociali; il presunto “messianesimo” di Marx, inteso come la concezione della storia come un progresso intelligente verso il meglio; e l’identificazione del marxismo tout court con una filosofia determinista e meccanicista. Si cerca di definire a quale “Marx” effettivamente sia rivolta la critica di Weil: si sostiene infatti che alcune delle sue argomentazioni siano riferibili alla “vulgata” marxiana, ossia a una lettura semplificata e schematica del marxismo, o alla “tendenza deteriore” del marxismo caratterizzata dall’economicismo e dal meccanicismo, dibattuta anche all’interno della Seconda Internazionale, o a posizioni di Engels e Lenin, o ancora all’operato del PCF o delle organizzazioni operaie, piuttosto che all’effettiva opera di Marx.
Rosi Braidotti (2022), Feminismo posthumano. Barcelona: Editorial Gedisa, 270 p. ISBN: 9788418914768
Authors: Perelman Wasilczuk Sebastián
Published: December 2023

Reseña del último libro de la filósofa italo-australiana Rosi Braidotti: Feminismo Posthumano (2022)
Avrupa Kamusal Alanında Sivil Bir Hareket Olarak Alevi Toplumu: Almanya Örneği
Authors: ÇEVİK Selman
Published: December 2023

Türkiye’den 1960’lı yılların sonundan itibaren başlayan ve diğer Avrupa ve Ortadoğu ülkelerine devam eden iş gücü göçü 60 yıllık bir birikimi içermektedir. Göç sürecinin hali hazırda yer alan ve değişen dinamikleri kendisini yeniden üretebilen anlamlarıyla karşımızda durmaktadır. Türkiye’den başlayan süreç her ne kadar ekonomik temelli olsa da sonraki süreçte dinî, siyasi, sosyal ve kültürel dinamikleri de etkilemiştir. Mevcut dinamiklerin en önemlileri arasına Türkiye’nin toplumsal yapısında yer alan bazı grupları ve odak tartışmaları da içerisinde dâhil etmiştir. Alevîlik veya Alevî toplumu da bu tartışmalardan etkilenmiş ve tartışmaları etkileyecek hamlelerde bulunmuştur. Birçok değiştirici ve dönüştürücü etkiyi özellikle dinî ve siyasi zeminde tarihi arka planıyla birlikte içeren süreçler de hali hazırdaki durumu şekillendiren sonuçları bünyesinde barındırmaktadır. Avrupa kamusal alanında Müslüman imgesinin son 20 yılda değişen boyutları hem Türk diasporasının hem de diğer Müslüman toplulukların yaşamında önemli etkileri bulunan bir başlangıcı oluşturmaktadır. Avrupa kamusal alanında Almanya üzerine odaklanan çalışma Almanya’da Alevî toplumunun kamusal alandaki görünümü, diğer göçmen gruplarından farklılaşan yönleri, geçmişten bugüne gerçekleşen olayları ve olguları gündeme getirmeyi ve nitel bir analiz şeması üzerinden betimleyerek ortaya koymayı amaçlamaktadır. Çalışma 2021 yılı içerisinde Almanya’da bulunan farklı Alevî sivil toplum kuruluşlarından temsilciler ile nitel araştırma yöntemlerinden mülakat tekniği kullanılarak yapılmıştır. Mülakat tekniği ile yapılan görüşmeler araştırmanın sınırlılıkları ve salgın koşulları çerçevesinde telefon veya görüntülü bağlantılar üzerinden yapılmıştır. Görüşmeler ortalama 40 dakika civarında sürmüş ve Alevî toplumuna ait sivil toplum kuruluşlarının yöneticileriyle gerçekleştirilmiştir. Araştırma sonucunda Alevi toplumunun Almanya kamusal alanında oluşturmuş olduğu sivil toplum yapısının Türk diasporasının diğer kuruluşlarından daha görünür ve ön planda olduğu tespit edilmiştir. Bununla birlikte Alevi sivil toplum kuruluşlarının Türkiye’ye dair taleplerinin kamusal alanda oluşan STK’lar üzerinden kendisini gösterdiği ve Almanya özelinde Avrupa’da da kendi inanç ve ritüellerini yaşamaya devam ettikleri görülmüştür.
A Study of Sultan Bahu’s Poetry through Arran Stibbe’s Eco Linguistic Framework
Authors: Baig Imrana Arif , Naeem Tamsila , Zafar Ayesha
Published: December 2023

The current study aims to analyze Sultan Bahu's poetry through Arran Stibbe's Eco linguistic framework (2015). The study helps in bringing a contemporary change in Sultan Bahu's mystic verse by identifying different stories of mind presented in Arran Stibbe's framework (2015): framing metaphor, identity, salience, erasure, ideology, conviction and evaluation. The study is qualitative in nature, in which different excerpts are selected from Bahu’s poetry through propulsive sampling technique. The analysis shows that Bahu uses different metaphors from the surrounding environment to preach his people the Divine message of God. The study is significant, since its findings establish a relationship between environment and language through a study of sufi poetry.
Assessing Environmental Awareness and Conservation Behavior in Schools for Sustainable Development
Authors: Fayyaz Sara , Lashari Ajab Ali , Nandwani Shazma , Chang Mansoor Ali
Published: December 2023

Environmental awareness in learners is one of the most critical aspects that must be considered in our educational institutes to promote conservation learner behavior for sustainable development. Schools are places where children prepare for the real world and unpredictable future and best be inculcated conservation behavior to protect the environment. The study uses a qualitative approach. The study conducted in happy home school society campus at Karachi.  This study is designed to explore the eco-friendly initiatives or practices this school is practicing for environmental awareness to promote conservation behavior in learners for sustainable development. Using purposive sampling, data was collected through semi-structured interviews and personal visits from the three teachers. The finding shows that this school is practicing different practices that help improve learners' environmental awareness to promote conservation behavior for sustainable development. This study will be helpful for the teachers and school management to know about such eco-friendly initiatives or practices to improve environmental awareness in learners that promote conservation behavior for sustainability because without traditional efforts and without protecting the environment, we can't achieve sustainable development.
Microfinance Institutions as Catalysts for Sustainable Entrepreneurship: Examining the Role of Social Capital and Training in Achieving SDG-aligned Success of Entrepreneurs
Authors: Abdullah Aseela , Riaz Kashif , Jan Amna , Wahab Anosha
Published: December 2023

The issue addressed in this study holds importance as it explores the significant role of microfinance institutions in fostering entrepreneurial success through the provision of non-financial services. Employing a quantitative research design, the study examines the impact of these factors on the success of entrepreneurs within the microfinance sector in Pakistan. The collected data analyze through statistical softwares, such as SPSS and PLS-SEM. The findings reveal a positive and significant impact of social capital on the success of entrepreneurs, indicating that entrepreneurs with strong social networks, access to resources, and positive reputation are more likely to succeed. Similarly, training and development are found to have a positive and significant influence on entrepreneurial success, highlighting the importance of continuous learning and skill development for entrepreneurs. The study also identifies a moderating effect of entrepreneurial experience, suggesting that the positive impact of training and development is stronger for individuals with higher levels of experience. These findings emphasize the importance of financial inclusion and its potential to drive economic growth and reduce inequalities in Pakistan. Despite limitations in sample size and context, this study provides valuable insights for future research and the development of effective strategies to support entrepreneurial growth and development in the microfinance sector.
Przyczynek do historii Zgromadzenia Misji w okresie rządów wizytatorskich ks. Michała Kownackiego
Authors: Schletz Alfons
Published: December 2023

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Cztery źródła do żywota św. Świrada
Authors: Kapiszewski Henryk
Published: December 2023

Św. Świrad i towarzysz jego , św. Benedykt, są postaciami historycznymi, a dzieje ich udokumentowane są kilkoma źródłami. Żyli oni na przełomie X i XI wieku, obejmując swoją działalnością misyjną nie tylko ziemie Polski południowej, Słowacji zachodniej i Panonii, ale — jeśli chodzi o św. Świrada — prawdopodobnie także tereny Ołomuńca i Jagru. Wiadomości o jego życiu pochodzą głównie z czterech źródeł pisanych. Szkic niniejszy, zestawiający i omawiający te cztery źródła, podejmuje próbę przedstawienia dziejów św. Świrada.
SPOUSAL SUPPORT AND AFFECTING FACTORS IN PREGNANT WOMEN WITH HYPEREMESIS GRAVIDARUM: THE CASE OF SOUTH EASTERN ANATOLIA REGION
Authors: GÜL Sidar , KILIÇLI Ayşegül
Published: December 2023

The objective of this study was to examine the level of spousal support and identify the factors that influence it among pregnant women who have been diagnosed with hyperemesis gravidarum. This descriptive study was conducted with a sample of 125 pregnant women who were hospitalized in the septic unit of a training and research hospital in a province in the Southeastern Anatolia Region between October 1, 2022, and December 30, 2022. The data were collected through face-to-face interviews using a descriptive information form and the Spousal Support Scale. The participants' mean score on the Spousal Support Scale was 58.87±12.06 at a moderate level. The levels of spousal support of the participants differed significantly according to socio-demographics (age, education, employment status, perceived economic status, most spoken language, spouse’s age, spouse’s educational status and spouse’s employment status), marital (age at first marriage, duration of marriage, marriage type), fertility (gravidity, number of living children, planning of the current pregnancy) characteristics and whether the marriage was affected by hyperemesis gravidarum (p
Does Accreditation of Museum Contribute to Attracting More Visitors? : Focusing on Accreditation of National and Public Museum
Authors:   Korean Association of Arts Management, Na Bori
Published: December 2023

Museums play an important role in the development of cultural and artistic disciplines and contribute to the cultural enjoyment of the general public. As such, museum visitors are important for brand building and marketing, expanding cultural enjoyment, public contribution, and active communication. Korean museums have been focusing on improving the quality experience by holding interesting exhibitions and programs and acquiring new collections. To ensure the quality control and operational efficiency of museum exhibitions, Korea has legally required public museums to participate in evaluation and certification since 2017 and national museums since 2020. If museum accreditation is considered as a signal that a museum will provide a desirable experience, it might be able to secure visitors by responding to it. This raises the question of whether efforts to improve museum quality, as represented by accreditation, lead to increased museum attendance. To examine the impact of accreditation on the number of visitors to national and public museums, the study conducted a double difference analysis and a panel analysis between the years 2013-2021. The study found that the Difference in Difference analysis did not show a significant difference in the number of visitors to museums before and after accreditation, but the fixed effect analysis showed that the number of visitors to public museums increased significantly in the year of accreditation and then decreased significantly in the following year. The study result suggests that accreditation had a temporary signaling effect, but it did not fundamentally change attendance. There is a need for increased publicity about certification and measurement of the effectiveness of certification in attracting visitors, as well as increased incentives for museums to participate in certification.
Psikolojik Danışma Sürecindeki Terapötik Beceri ve Koşulların Metin Analizi Yöntemiyle İncelenmesi: “In Treatment” Dizisi
Authors: ÖKSÜZ Yücel , YILDIRIM Oğuzhan
Published: December 2023

Film ve dizilerde canlandırılan psikoterapi sahneleri aracılığıyla terapötik süreçleri ve müdahaleleri incelemek, kuramları farklı perspektiften analiz etmek ve bunları psikolojik danışman eğitiminde kullanmak mümkündür. Bu araştırmada terapi sahneleri bakımından zengin veriler sunan “In Treatment” dizisinde kullanılan terapötik becerilerin ve sağlanan terapötik koşulların metin analizi yöntemi ile incelenmesi amaçlanmıştır. Nitel araştırma yönteminin kullanıldığı bu araştırmada elde edilen veriler betimsel analize tabi tutulmuştur. Veriler analiz edildiğinde terapistin en sık başvurduğu becerinin kişiselleştirme becerisi en çok sağlanan terapötik koşulun ise ilişkinin şimdi ve buradalığı olduğu görülmektedir. Bunun yanında terapistin konuşmaya açık davet, kendini açma, bağlama, koşulsuz kabul, yüzleştirme, yansıtma, somutlaştırma, saydamlık, yapılama, empati, özetleme, amaç belirleme, bilgilendirme ve sessizlik beceri ve koşullara da başvurduğu saptanmıştır. Danışanın ise terapiste yoğun bir direnç gösterdiği, eşi, çocuğu, babası ve yakın arkadaşı ile yaşadığı ilişki ve sorunlarından bahsettiği, yer yer kendi hakkında içgörü kazandığı ancak çoğunlukla farkındalık kazanmaktan kaçındığı, kimi zaman terapist ile sorunlar yaşadığı ve son olarak terapiyi yarıda bıraktığı görülmektedir. Filmlerde yer alan terapi sahnelerinin analiz edildiği bu araştırmalar eğitim sürecinde, yaşanan problemleri somutlaştırmada ve profesyonellere çeşitli bakış açıları kazandırmada alanyazına çok büyük katkılar sunmaktadır.
Experimental study of the degradation of HDPE packaging under accelerated thermal aging
Authors: Elkori Rabiaa , Lamarti Amal , Salmi Houda , Had Khalid El , Hachim Abdelilah
Published: December 2023

In this work, accelerated thermal aging at different temperatures was performed on high-density polyethylene (HDPE) bottles and specimens for food packaging. The degradation of HDPE was followed macroscopically by tensile and compression tests to evaluate the decrease in mechanical properties. The data obtained from these tests are used to calculate a new static damage law and the life fraction of this polymer. A prediction of the lifetime of HDPE was determined by thermogravimetric analysis (TGA) in dynamic mode. The evolution of the crystallinity rate during accelerated thermal aging was carried out using FOURIER transform infrared spectrometry (FTIR). The results obtained show a remarkable degradation of the mechanical properties in traction and compression by calculation of the static damage, and the physical and chemical properties by the analysis of the rate of crystallinity as well as the prediction by the law of Arrhenius.