dataesr/scientific-paragraphs-categorization huggingface dataset:
DOOR-SLAM  [62]  followed a similar framework, but used a place recognition module to transfer the brief descriptor of the whole keyframe and a geometric verification submodule to ensure correct data association. In Ref. [63] , a pipeline for collaborative AR assembly in industry supported by multiple visual SLAM systems was presented. It started with scene cognition using multi-view acquisition of industrial environments to provide images for multiple users. Then, pose recovery was derived from different views of AR operators to get the global coordinate. Finally, each agent ran a VIO system to achieve the operation on assembly.
Summary From Table  5 , it can be observed that the majority of previous research only used 2 agents for experiments. With the common platform of UAV and UGV. KITTI is the most frequently used dataset for demonstrations. Although there are fewer papers for LiDARbased collaborative positioning compared with vision-based collaborative positioning, different data association algorithms have been developed to improve accuracy and robustness. Various 3D features, including GLARE (Geometric Landmark Relations) and FPFH descriptor, have been used to establish correspondences between different maps, and point set registration cloud registration is an alternative method for this purpose. While most papers do not analyze the size of data exchange, the size of LiDAR-based collaborative positioning is similar to that of vision-based collaborative positioning, mainly due to the usage of 3D feature descriptors.
Although collaborative localization benefits the machine learning technique, current applications are limited in light of the requirement of large computing resources. It could improve the localization performance in scenarios such as satellite formation flying, indoor positioning and robot systems, since massive training data could be collected to perform supervised learning. However, for the scenarios whose member nodes move randomly, deep learning techniques are not effective in this case. In addition, the Wireless Insite®software could be implemented to provide 3D ray-tracing for the analysis of site-specific radio wave propagation and wireless communication systems. By combining this software with a particular map, the user is able to get an evaluation environment with a series of channel state information data in both time-domain and frequency-domain.
In addition, numerous public fingerprinting datasets are provided for indoor positioning, some of the representative works are  [132] : UJI 1e2, LIB 1e2 (collected at Universitat Jaume I, Spain), MAN 1e2 (collected at University of Mannheim, Germany), TUT 1e7 (collected at Tampere University, Finland) and UTSIndoorLoc (collected at University of Technology Sydney, Australia). Moreover, the existing datasets for indoor-outdoor positioning are summarized in Ref. [133].
One promising approach is to use deep neural networks (DNNs) to learn the positioning error model by testing various scenarios. Several large-scale datasets, including Cityscapes  [151]  (city data), Tartanair  [152]  (simulated data), and UAV data  [153] , have been used to verify correctness and compare performance of many positioning methods. However, it remains challenging to define the differences between cases and establish error rules that apply universally.
Collaborative positioning dataset and framework Positioning datasets usually focus on a single agent  [156]. To simulate scenarios for multiple agent based positioning, single agent based datasets such as KITTI can be divided into multiple parts. However, this kind of simulation is only suitable for method validation, and is far from being applicable for real applications. Developing multiple agent based datasets based on wireless sensors is mainly concentrated in the field of indoor positioning and robot systems, which are based on known and well-calibrated anchors. The difficulties of developing multiple agent based datasets lie in the higher cost compared to single agent based datasets. One economical way to generate such datasets is through computer graphics simulation and certain mathematical functional models.
For example, TitianAir  [152]  used photo-realistic simulation environments that include moving objects, changing light, and various weather conditions. This allows the generation of multi-modal sensor data including RGB, camera poses, and LiDAR data. Going further, different moving platforms and wireless data can be added, and the loss of communication can be considered. Developing more diverse datasets for collaborative positioning in different scenarios, agent sizes, and anchor types is a promising direction for future work. The collaborative positioning community currently lacks an offthe-shelf framework that includes fundamental components such as communication links between agents. If a general framework were to be open-sourced and provided as a platform, the community would be able to focus more on algorithm development with greater convenience.
Finally, the paper identifies and describes various challenges and open issues, including both engineering aspects (e. g. communication, computation burden, dataset, framework, and new sensors) and theoretical aspects (e. g. robustness, accuracy, reliability, integrity, and active collaborative positioning), which need to be addressed for further research in this field. This paper presents a concise overview of collaborative positioning based on vision, LiDAR, and wireless sensors, highlighting recent developments and key components. The review includes a selection of representative research papers, including preprints, to present the latest progress in the field. To improve readability, complex theoretical equations are not included. The authors aim to provide a panoramic reference for scholars with expertise in vision, LiDAR, and wireless sensor-based positioning to initiate further research on collaborative positioning.
Acknowledgements The authors would like to acknowledge  National Natural Science Foundation of China  (Grant No. 62101138 ),  Shandong Natural Science Foundation  (Grant No. ZR2021QD148 ),  Guangdong Natural Science Foundation  (Grant No. 2022A1515012573 ) and  Guangzhou Basic and Applied Basic Research Project  (Grant No. 202102020701 ) for providing funds for publishing this paper.
5 MBs À1 Centralized 3 Robots Indoor environments 2022 [49] RGB-D sensor 3D feature N/A De- 3 UGV Indoor environments Matching centralized 2021 [50] Monocular camera Feature matching N/A Centralized 2e4 UAV KITTI 2021 [51] Monocular camera/inertial Feature matching N/A Centralized 3 UAV EuRoC sensor 2022 [52] Camera and UWB DNN N/A De- 2 UAV Simulation Data and centralized indoor environments 2021 [53] Stereo/RGB-D camera and 3D feature N/A Centralized 3 Robots and UAV Simulated Data and inertial sensors matching EuRoC 2019 [31] ToF camera and inertial Visual Tracking N/A De- 3 Small Scale Underwater sensors centralized spherical environments underwater robot 2021 [57] RGB-D sensor Feature Matching Compare 2G/3G/4G De- 2 UAV/UGV Simulated Data, ICL- scenarios centralized NUIM data and real data 2019 [54] Stereo camera Feature Matching Compared between Centralized 3 Simulated agents KITTI compressed and uncompressed condition 2022 [59] Monocular, stereo, and RGB- Feature Matching N/A Centralized 2 Simulated agents EuRoC, TUM and real D cameras with inertial and Tarot drones data sensor 2018 [61] Vision and inertial sensors Feature N/A Centralized 2 Simulated agents EuRoC Matching 2020 [62] Stereo camera Feature Matching N/A Distributed 2e3 UAV Outdoor environments 2022 [63] Monocular camera Feature Matching N/A Distributed 3e5 Simulated agents ChangeSim dataset and EuRoC 2017 [56] RGB-D sensor N/A <50 KB Distributed 50 Simulated Agents Simulation and and robots outdoor environments 2020 [55] Ranging tag module N/A N/A N/A 2 N/A KITTI.
The channel estimation performance of IEEE 802. 11p, IEEE 802. 11bd-draft, and the unique-word (UW) based physical layer are examined in  [34]. According to the findings, the performance of a UW-based PHY with low complexity channel estimation is comparable to that of an IEEE 802. 11bd-draft implementation with high complexity channel estimation. IEEE 802. 11p, 802. 11bd, LTE-V2X, and NR-V2X standard performance in data rate, latency, packet error rate, and communication distance are compared in  [35]. They are using a MATLAB toolbox, theoretical evaluations, and simulations. The results show NR-V2X outperforming 802. 11bd, surpassing 802. 11p. IEEE 802. 11bd notably enhances IEEE 802. 11p performance, especially in high Doppler scenarios, and the dual-carrier modulation and extended range options further improve cell edge performance and range.
4) Reliability Issues in Vehicular Communications Vehicular communications' reliability is the ability to deliver dependable and consistent communication service. Due to how it could affect both drivers' and passengers' safety, this is significant. A low packet delivery rate can lead to poor communication, and a high packet error rate can affect the data transfer rate; these metrics impact the performance and level of service provided to clients. Various methods are suggested in papers to increase communication reliability in vehicles. The summary of SDN vehicular communications reliability research papers surveyed in this paper can be seen in table  8. Service, packet delivery, and packet error rates are also included.
To address scalability and reduce single points of failure,  [96]  proposes using Enhanced Hierarchical Software-Defined Vehicular Networks (E-HSDV), which employs local SDN controllers. Meanwhile,  [81]  demonstrates that multiple controllers in the SDN domain can alleviate the load on a single controller and effectively handle MEC service handover. Additionally,  [74]  compares four free-open sources SDN controllers (POX, Floodlight, ONOS, and OpenDaylight) and shows that OpenDaylight has lower latency, among others. To minimize latency and protocol overhead between the SDN controller and network devices,  [93]  suggests deploying a local controller near RSUs. Finally,  [94]  proposes a hierarchical SDVN architecture with shared functions between global and local controllers. The research findings highlight the importance of SDN controllers in achieving efficient network communication and control management in SDVNs  [74] ,  [81] ,  [93] ,  [94] ,  [96].
The controllers' functions vary depending on their level, including managing traffic, regulating inter-area communications, and enforcing SDVN-wide policies. Dynamic load balancing algorithms can be implemented within the SDN domain to address scalability and distribute the load effectively  [81]. These algorithms can intelligently allocate network resources and traffic across multiple controllers based on real-time network conditions and demands, ensuring that no single controller becomes overloaded. To enhance SDN controllers' reliability and fault tolerance, redundant controller architectures can be employed  [96]. Redundancy can help ensure continuous operation even if one  security AI/ML and other algorithms Security system architecture in VCC (vehicular cloud computing)  [125]  security AI/ML and other algorithms, network architecture and design The problem of providing end-to-end security and privacy in C-V2X 5G communication and the detection and handling of different types of attacks  [119]  security AI/ML and other algorithms, network architecture and design The problem of providing secure and context-aware communication in vehicular networks  [126]  security AI/ML and other algorithms, MEC Securing data sharing and storage on vehicular edge computing and networks  [127]  security AI/ML and other algorithms, MEC The lack of access control and unauthorized SDN controllers on SDVN can cause security issues  [128]  security AI/ML and other algorithms Weaknesses in previous defense mechanisms against topology poisoning attack  [118]  security, energy efficiency AI/ML and other algorithms The implementation of an intrusion detection system (IDS) in a centralized database system causes bottlenecks, single points of failure, scalability issues, storage usage, communication overhead  [129]  security, controller load reduction during attacks AI/ML and other algorithms The periodic detection trigger mechanism implementation to overcome DDoS attacks weakness in terms of slow identifying and countering attacks causing an overload on the SDN controller and switch  [130]  security AI/ML and other algorithms Security risks in vehicular communications: taking over vehicle resources, jamming communication channels, confidentiality, availability, integrity, accountability, and high latency caused by security attacks  [119]  security AI/ML and other algorithms, network architecture and design The weakness of the existing pseudonym-changing strategies for connected vehicles: static, rigid, non-adaptive schema  [131]  security AI/ML and other algorithms, routing VANET communication reliability and security not fully examined in previous research  [132]  security AI/ML and other algorithms, routing Malicious vehicles in SDVN potential problems providing false information, misbehaving, and disrupting communication controller fails, reducing the risk of single points of failure and maintaining network stability during critical situations.
In  [88] , an SDN-based DMM with QoS-driven route decision, edge, and cloud computing resources management is proposed. Integrating SDN and edge computing aims to enhance autonomous driving systems by reducing latency and enabling real-time computations. However, this integration can lead to reduced mobility support. To overcome this challenge, the solution proposes using DMM, which separates control and data planes to address scalability and reliability concerns in mobility management. Authors in  [158]  proposes an architecture that integrates networking, caching, and computing to overcome congestion. The scheme reduces network overhead and task exe-cution time. MEC is essential in the proposed architecture as it brings caching and computing resources closer to the vehicles, reducing latency and improving overall system performance.
In  [138] , SDN-assisted MEC network architecture is proposed for the vehicular network to increase control over V2X infrastructure and allocate resources. In  [72] , MEC with multiple RATs and NFV is implemented for AV to overcome limitations in navigation and steering. Cloud computing and MEC servers use a two-tier server structure for optimal resource allocation. In  [150] , MEC combined with NFV and SDN is proposed to be implemented in cooperative, connected, and automated mobility. Various RAT and network paths, SDN controllers, NFV and offloading tasks, spectrum sharing, and pseudonymity are utilized to address the challenges. In  [103] , a three-tier SDN controller (edge controller, domain controller, root controller) is implemented on the MEC server for IoV. Authors in  [169]  discusses moving applications and data from one MEC server to another and uses an SDN framework to coordinate the migration process.
These findings highlighted SDN-based MEC's pivotal role in elevating vehicular communication systems. In the future, researchers can explore optimizing MEC service delivery with QoS standards for various vehicular applications. Further development of SDN-based orchestration methods can efficiently manage the network infrastructure and MEC resources, reducing service migration frequency and latency. Additionally, investigations into the seamless migration of applications and data between MEC servers using SDN coordination could lead to more efficient resource allocation. 3) SDN and Network Slicing Network slicing is the key to utilizing network and computing resources with high utilization and reducing the cost of building infrastructure. NFV and VNF are used in SDNbased network infrastructure to realize network slicing.
Pour ce faire, nous avons développé un simulateur numérique d'imagerie de projection. Grâce à ce simulateur et en s'appuyant sur leurs connaissances théoriques, les étudiants apprennent à régler correctement les paramètres nécessaires à la réalisation d'une radiographie. Ils constatent immédiatement les conséquences d'un choix inadapté. En favorisant l'apprentissage par l'erreur, ce simulateur contribue à la consolidation des connaissances théoriques des étudiants. Il leur permet, dès le début de leur formation, d'acquérir un savoirfaire et un savoir-être indispensables pour l'utilisation d'un tube à rayons X. De plus, à l'aide d'une base de données présentant des cas cliniques, cet outil contraint les étudiants à s'interroger sur la qualité d'une radiographie en particulier pour des cas complexes.
Développements informatiques et fonctionnement du simulateur Le front-end (interface graphique) de ce simulateur a été développé en HTML et CSS  [8]. Le back-end (arrièreplan de l'application) a été développé en JavaScript et JQuery  [7]. L'image est automatiquement calculée en tenant compte des paramètres décrits dans la seconde partie de cet article. Pour cela, deux radiographies servent de support. L'une a été réalisée avec une tension d'accélération de 70 kV, et l'autre avec une tension d'accélération de 120 kV. Pour simuler les paramètres utilisés, des filtres numériques, à appliquer sur ces radiographies, ont été implémentés. Ainsi, nous avons utilisé un filtre passe-haut pour simuler l'utilisation du petit foyer (figure  3 ). En effet, en privilégiant les hautes fréquences, ce filtre améliore la résolution spatiale de la radiographie, comme le fait le petit foyer.
CONCLUSION Nous avons montré à l'aide de quelques exemples, comment le simulateur que nous avons développé reproduisait le fonctionnement d'un dispositif d'imagerie radiologique de projection et pouvait être ainsi utilisé pour la formation des étudiants. Grâce à ce simulateur, les utilisateurs comprennent l'influence de chaque paramètre nécessaire à la réalisation d'une radiographie. Ils testent la combinaison de différents paramètres allant jusqu'à utiliser des combinaisons peu contributives. Ils analysent les conséquences de leurs choix tant en termes de qualité du cliché que de la dose délivrée au patient. Cet apprentissage par l'erreur facilite la maîtrise de concepts théoriques indispensables à l'utilisation d'un tube à rayons X. Nous y avons adjoint une base de données de radiographies afin d'évaluer la capacité des étudiants à analyser des clichés complexes.
REMERCIEMENTS La publication de ce numéro des Cahiers québécois de démographie a bénéficié d'une subvention du Fonds de recherche du Québec-Société et culture  (FRQSC). Nous leur sommes reconnaissants du soutien apporté. La rédaction tient également à exprimer sa gratitude au Partenariat de recherche Familles en mouvance dont le soutien financier a contribué à rendre possible la publication de ce numéro. Enfin, nous remercions Benoît Laplante et Hélène Belleau pour leur participation à la préparation de ce numéro à titre d'éditeurs invités. Portail de la revue : www. erudit. org/revue/cqd Courriel : cahiers@demographesqc. org.
SOURCES QUÉBÉCOISES En termes de données sur la résidence des enfants, la situation québécoise est un peu plus enviable que la canadienne. En plus des sources décrites précédemment, on retrouve des données d'enquêtes menées par l'Institut de la statistique du Québec (ISQ), et donc facilement accessibles aux 9. Toutes les statistiques excluent du dénominateur les 0,7 % d'enfants ne vivant chez aucun de leurs parents. chercheurs, ou encore des rapports décrivant diverses bases de données administratives provinciales.
Les modèles locational attainment peuvent générer des problèmes dus à l'autocorrélation spatiale, puisque les individus vivant dans un même secteur ont tous la même valeur pour la variable dépendante, celle-ci étant en partie influencée par leur présence dans le secteur  (Cort, 2011 ; Logan et collab. 1996 ; Pelletier, 2012). Ceci a pour effet de sous-estimer l'erreur-type des paramètres, puisque les erreurs sont corrélées. Dans une telle situation, les auteurs utilisant ce type de modèle recommandent généralement d'estimer les paramètres par la méthode des moindres carrés généralisés faisables (feasible generalized least squares)  (Cort, 2011 ; Myles et Hou, 2003) , ce qui permet de prendre en compte la corrélation des termes d'erreur à l'intérieur d'un même secteur  (Greene, 1997). Nos analyses nécessitent une base de données individuelles qui contient une information sur la localisation résidentielle à un petit niveau géographique en plus des caractéristiques individuelles, dont la dimension ethnoculturelle.
La base de données la plus récente fournissant ce genre d'information est l'Enquête nationale auprès des ménages de 2011 (ENM)  (Statistique Canada, 2013) , qui contient non seulement les caractéristiques individuelles telles que le sexe, l'âge, la structure familiale, le revenu, l'éducation, l'année d'immigration, la langue, etc. , mais aussi des informations sur le lieu de naissance du répondant et de ses parents qui permettent de construire des communautés immigrantes basées sur le pays d'origine de la première et de la deuxième génération d'immigrants. L'ENM découpe aussi la région métropolitaine de Montréal en 921 secteurs de recensements qui comptent entre 2 500 et 8 000 habitants et peuvent être assimilés à des quartiers. Cependant, puisque l'ENM, qui remplace le formulaire long des recensements précédents, n'est pas obligatoire, le taux de réponse est de 70 % et peut varier fortement entre les groupes.
Québec, Presses de l'Université du Québec. Belleau, H. 2008. « Entre le partage des dépenses et le partage des avoirs. Les comptes conjugaux des ménages québécois », dans H. Belleau et C. Henchoz (dir. ), L'usage de l'argent dans le couple. Pratiques et perceptions des comptes amoureux, perspective internationale, Paris : L'Harmattan : 113-148. Bonnet, C. , B. Garbinti et A. Solaz. 2016. Gender inequality after divorce : The flip side of marital specialization. Evidence from a French administrative database. Paris : Institut national de la statistique et des études économiques (Document de travail G2016/03 de la Direction des études et synthèses économiques). Conseil du statut de la femme (csf). 1978. Pour les Québécoises : égalité et indépendance. Québec : Éditeur officiel du Québec. Conseil du statut de la femme (csf).
Remerciements Les auteurs remercient Marion Blanchard et Cindy Chaillou (psychologues cliniciennes), Pauline Meme (assistante sociale en médecine légale), Déborah Iwanikow (médecin légiste responsable de l'Unité médico-judiciaire), Nathalie Jousset (maître de conférences des universités-praticien hospitalier, chef de service).
Punishment can be direct, that is to say visible, such as public blame. It can also be covert, for example by trying to involve people with sufficient power to deal directly with the perpetrator, or by the witness reducing the level of help offered to the perpetrator  (Brockner, Tyler & Cooper-Schneider, 1992). This may trigger a cycle of vengeance. The concepts tested in our experiment on each of the three levels of analysis are summarized below: world belief, level of cynical hostility and personal experience of injustice (moderator variables) are measured using 7-point Likert-type scales. To ensure the effectiveness of these experiment scenario, a pre-test was carried out on 40 employees, 20 for each version of the text. The objective was to calibrate the average amount of relevant data memorized by participants and to adjust the wording to perfect the desired inductions  (Delhomme & Meyer, 2002) , in this case attribution of responsibility for the act of derogation.