2,424 research outputs found

    LIPIcs, Volume 251, ITCS 2023, Complete Volume

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    LIPIcs, Volume 251, ITCS 2023, Complete Volum

    The 2023 terahertz science and technology roadmap

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    Terahertz (THz) radiation encompasses a wide spectral range within the electromagnetic spectrum that extends from microwaves to the far infrared (100 GHz–∌30 THz). Within its frequency boundaries exist a broad variety of scientific disciplines that have presented, and continue to present, technical challenges to researchers. During the past 50 years, for instance, the demands of the scientific community have substantially evolved and with a need for advanced instrumentation to support radio astronomy, Earth observation, weather forecasting, security imaging, telecommunications, non-destructive device testing and much more. Furthermore, applications have required an emergence of technology from the laboratory environment to production-scale supply and in-the-field deployments ranging from harsh ground-based locations to deep space. In addressing these requirements, the research and development community has advanced related technology and bridged the transition between electronics and photonics that high frequency operation demands. The multidisciplinary nature of THz work was our stimulus for creating the 2017 THz Science and Technology Roadmap (Dhillon et al 2017 J. Phys. D: Appl. Phys. 50 043001). As one might envisage, though, there remains much to explore both scientifically and technically and the field has continued to develop and expand rapidly. It is timely, therefore, to revise our previous roadmap and in this 2023 version we both provide an update on key developments in established technical areas that have important scientific and public benefit, and highlight new and emerging areas that show particular promise. The developments that we describe thus span from fundamental scientific research, such as THz astronomy and the emergent area of THz quantum optics, to highly applied and commercially and societally impactful subjects that include 6G THz communications, medical imaging, and climate monitoring and prediction. Our Roadmap vision draws upon the expertise and perspective of multiple international specialists that together provide an overview of past developments and the likely challenges facing the field of THz science and technology in future decades. The document is written in a form that is accessible to policy makers who wish to gain an overview of the current state of the THz art, and for the non-specialist and curious who wish to understand available technology and challenges. A such, our experts deliver a 'snapshot' introduction to the current status of the field and provide suggestions for exciting future technical development directions. Ultimately, we intend the Roadmap to portray the advantages and benefits of the THz domain and to stimulate further exploration of the field in support of scientific research and commercial realisation

    Exploration autonome et efficiente de chantiers miniers souterrains inconnus avec un drone filaire

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    Abstract: Underground mining stopes are often mapped using a sensor located at the end of a pole that the operator introduces into the stope from a secure area. The sensor emits laser beams that provide the distance to a detected wall, thus creating a 3D map. This produces shadow zones and a low point density on the distant walls. To address these challenges, a research team from the UniversitĂ© de Sherbrooke is designing a tethered drone equipped with a rotating LiDAR for this mission, thus benefiting from several points of view. The wired transmission allows for unlimited flight time, shared computing, and real-time communication. For compatibility with the movement of the drone after tether entanglements, the excess length is integrated into an onboard spool, contributing to the drone payload. During manual piloting, the human factor causes problems in the perception and comprehension of a virtual 3D environment, as well as the execution of an optimal mission. This thesis focuses on autonomous navigation in two aspects: path planning and exploration. The system must compute a trajectory that maps the entire environment, minimizing the mission time and respecting the maximum onboard tether length. Path planning using a Rapidly-exploring Random Tree (RRT) quickly finds a feasible path, but the optimization is computationally expensive and the performance is variable and unpredictable. Exploration by the frontier method is representative of the space to be explored and the path can be optimized by solving a Traveling Salesman Problem (TSP) but existing techniques for a tethered drone only consider the 2D case and do not optimize the global path. To meet these challenges, this thesis presents two new algorithms. The first one, RRT-Rope, produces an equal or shorter path than existing algorithms in a significantly shorter computation time, up to 70% faster than the next best algorithm in a representative environment. A modified version of RRT-connect computes a feasible path, shortened with a deterministic technique that takes advantage of previously added intermediate nodes. The second algorithm, TAPE, is the first 3D cavity exploration method that focuses on minimizing mission time and unwound tether length. On average, the overall path is 4% longer than the method that solves the TSP, but the tether remains under the allowed length in 100% of the simulated cases, compared to 53% with the initial method. The approach uses a 2-level hierarchical architecture: global planning solves a TSP after frontier extraction, and local planning minimizes the path cost and tether length via a decision function. The integration of these two tools in the NetherDrone produces an intelligent system for autonomous exploration, with semi-autonomous features for operator interaction. This work opens the door to new navigation approaches in the field of inspection, mapping, and Search and Rescue missions.La cartographie des chantiers miniers souterrains est souvent rĂ©alisĂ©e Ă  l’aide d’un capteur situĂ© au bout d’une perche que l’opĂ©rateur introduit dans le chantier, depuis une zone sĂ©curisĂ©e. Le capteur Ă©met des faisceaux laser qui fournissent la distance Ă  un mur dĂ©tectĂ©, crĂ©ant ainsi une carte en 3D. Ceci produit des zones d’ombres et une faible densitĂ© de points sur les parois Ă©loignĂ©es. Pour relever ces dĂ©fis, une Ă©quipe de recherche de l’UniversitĂ© de Sherbrooke conçoit un drone filaire Ă©quipĂ© d’un LiDAR rotatif pour cette mission, bĂ©nĂ©ficiant ainsi de plusieurs points de vue. La transmission filaire permet un temps de vol illimitĂ©, un partage de calcul et une communication en temps rĂ©el. Pour une compatibilitĂ© avec le mouvement du drone lors des coincements du fil, la longueur excĂ©dante est intĂ©grĂ©e dans une bobine embarquĂ©e, qui contribue Ă  la charge utile du drone. Lors d’un pilotage manuel, le facteur humain entraĂźne des problĂšmes de perception et comprĂ©hension d’un environnement 3D virtuel, et d’exĂ©cution d’une mission optimale. Cette thĂšse se concentre sur la navigation autonome sous deux aspects : la planification de trajectoire et l’exploration. Le systĂšme doit calculer une trajectoire qui cartographie l’environnement complet, en minimisant le temps de mission et en respectant la longueur maximale de fil embarquĂ©e. La planification de trajectoire Ă  l’aide d’un Rapidly-exploring Random Tree (RRT) trouve rapidement un chemin rĂ©alisable, mais l’optimisation est coĂ»teuse en calcul et la performance est variable et imprĂ©visible. L’exploration par la mĂ©thode des frontiĂšres est reprĂ©sentative de l’espace Ă  explorer et le chemin peut ĂȘtre optimisĂ© en rĂ©solvant un Traveling Salesman Problem (TSP), mais les techniques existantes pour un drone filaire ne considĂšrent que le cas 2D et n’optimisent pas le chemin global. Pour relever ces dĂ©fis, cette thĂšse prĂ©sente deux nouveaux algorithmes. Le premier, RRT-Rope, produit un chemin Ă©gal ou plus court que les algorithmes existants en un temps de calcul jusqu’à 70% plus court que le deuxiĂšme meilleur algorithme dans un environnement reprĂ©sentatif. Une version modifiĂ©e de RRT-connect calcule un chemin rĂ©alisable, raccourci avec une technique dĂ©terministe qui tire profit des noeuds intermĂ©diaires prĂ©alablement ajoutĂ©s. Le deuxiĂšme algorithme, TAPE, est la premiĂšre mĂ©thode d’exploration de cavitĂ©s en 3D qui minimise le temps de mission et la longueur du fil dĂ©roulĂ©. En moyenne, le trajet global est 4% plus long que la mĂ©thode qui rĂ©sout le TSP, mais le fil reste sous la longueur autorisĂ©e dans 100% des cas simulĂ©s, contre 53% avec la mĂ©thode initiale. L’approche utilise une architecture hiĂ©rarchique Ă  2 niveaux : la planification globale rĂ©sout un TSP aprĂšs extraction des frontiĂšres, et la planification locale minimise le coĂ»t du chemin et la longueur de fil via une fonction de dĂ©cision. L’intĂ©gration de ces deux outils dans le NetherDrone produit un systĂšme intelligent pour l’exploration autonome, dotĂ© de fonctionnalitĂ©s semi-autonomes pour une interaction avec l’opĂ©rateur. Les travaux rĂ©alisĂ©s ouvrent la porte Ă  de nouvelles approches de navigation dans le domaine des missions d’inspection, de cartographie et de recherche et sauvetage

    Comparative evaluation of acoustic and electric signals of partial discharges

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    Failures of power electric components such as transformers and outages can lead to a huge economical loss in the electric power grid. One of the main parts of a power electric components is the insulation system, namely, insulation oil, impregnated pressboard and paper. Several methods exist for diagnostics of these insulation materials. Partial discharge (PD) measurement known as one of the main non-destructive monitoring systems of the insulation materials. However, it has been mainly done off-line in maintenance periods, and the existing on-line methods generally provide less information due to environment electric noises. In contrast to electric PD measurement system, the acoustic emission (AE) measurement system is well known for its immunity against environment electrical noises. In this thesis comparative evaluation of acoustic and electric signals of PD events generated in oil impregnated pressboard and papers is investigated. The thesis is focused on the characteristic of PD activity and the consequence of that on the electric and AE signal. PD classification is defined by using the relation between acoustic and electric signals of PD events. Although the sensitivity of the AE sensors has been improved over the years, but the detection of the acoustic signals from PD activity in power equipment mainly transformers remain the main challenge of acoustic measurement. Lack of information regarding evaluation of electric PD signals and AE signals beside the mechanical attenuation are two main disadvantages of AE measurement method. Due to mechanical and electrical mechanism of waves generated during PD activities, the mechanical and electrical behaviour of the waves is discussed in more detail to have better understanding about the electric and acoustic signals. PD sources were generated at different electrode configurations such as needle-plane and electrode ball arrangement within a sample in the tank to investigate different types of PD. Electric characteristics of PD and different PD measuring technics such as electric, UHF and acoustic beside the mechanical behaviour of the acoustic waves are also discussed. The corona in oil results regarding the relation between AE and electric PD signals shows the correlated behaviour between AE and PD apparent charge magnitude. However, in surface discharges these behaviours are uncorrelated. In this regards the surface discharge is studied in more detail, leading to the first results of PD with very low acoustic (no acoustic) activity. Regarding these results two different categories in term of AE signals of PDs are defined, silent PD and non-silent PD. Silent PDs are those PD activities without or with very low acoustic signal and non-silent PDs are with acoustic signal. The existence of the silent PD is validated via oscilloscope and digital signal processing (DSP) devices. Also, with different innovative methods and arrangements such as needle plane and ball electrodes with and without oil gap, the probable reasons of creation this phenomenon (silent PD) is investigated. It is found that the carbonization patterns start with non-silent PD and remain the same during silent PD activities even with very high electric apparent charges. It means the development in carbonization traces produce electric and AE signals and in contrast no changes in carbonization traces produce only electric signals with no AE signal. These results verify the advantages of using acoustic technics and electric measurement in terms of PD classification and localization.AusfĂ€lle von Komponenten in elektrischen Energiesystemen wie Transformatoren können zu einem enormen wirtschaftlichen Verlust im Energiesystem fĂŒhren. Einer der Hauptbestandteile der Komponenten in elektrischen Energiesystemen ist das Isoliersystem, nĂ€mlich Öl, imprĂ€gniert Pressboard und Papier. Es gibt mehrere Methoden zur Diagnose dieser Isoliermaterialien. Die Messung der Teilentladung (TE) ist als eines der wichtigsten zerstörungsfreien Überwachungssysteme fĂŒr Isoliermaterialien bekannt. Jedoch wird dies in Wartungsperioden hauptsĂ€chlich offline durchgefĂŒhrt, und die existierenden Online-Verfahren liefern im Allgemeinen weniger Informationen aufgrund von elektromagnetischen Störungen. Im Gegensatz zum elektrischen TE-Messsystem ist das Schallemissionsmesssystem fĂŒr seine ImmunitĂ€t gegen elektrische UmgebungsgerĂ€usche bekannt. In dieser Arbeit wird die vergleichende Auswertung von akustischen und elektrischen Signalen von TE-Ereignissen untersucht, die in ölimprĂ€gnierten Pressboard und Papieren erzeugt werden. Sie konzentriert sich auf die Charakteristik der TE-AktivitĂ€t und deren Einfluss auf akustische Signale. Die TE-Klassifizierung wird definiert, indem die Beziehung zwischen akustischen und elektrischen Signalen von TE-Ereignissen verwendet wird. Obwohl die Empfindlichkeit der akustischen Sensoren im Laufe der Jahre verbessert wurde, bleibt die Erkennung der akustischen Signale von TE-AktivitĂ€t das Hauptproblem bei Komponenten in elektrischen Energiesystemen, hauptsĂ€chlich Transformatoren. Fehlende Informationen zur Auswertung von elektrischen TE-Signalen und akustischen Signalen sind neben der mechanischen DĂ€mpfung zwei Hauptnachteile der akustischen Messung. Wegen der mechanischen und elektrischen Mechanismen von Wellen, die wĂ€hrend der TE-AktivitĂ€ten erzeugt werden, wird deren Verhalten ausfĂŒhrlicher diskutiert, um ein besseres VerstĂ€ndnis ĂŒber die elektrischen und akustischen Signale zu erhalten. An verschiedenen Elektrodenkonfigurationen innerhalb einer Probe im Öltank werden TE-Quellen an verschiedenen Elektrodenkonfigurationen wie Spitze-Platte und Elektrodenkugelanordnung innerhalb einer Probe im Tank erzeugt, um verschiedene Arten von TE zu untersuchen. Neben dem mechanischen Verhalten der akustischen Wellen werden auch elektrische Eigenschaften von TE und verschiedene TE-Messtechniken wie elektrisch, UHF und akustisch behandelt. Die Ergebnisse bezĂŒglich des VerhĂ€ltnisses zwischen AE- und elektrischen TE-Signalen fĂŒr Korona im Öl zeigen das korrelierte Verhalten zwischen AE- und TE-Signalen. Bei OberflĂ€chenentladungen sind diese Verhaltensweisen jedoch unkorreliert. Die OberflĂ€chenentladung wird genauer untersucht, was zu den ersten Ergebnissen von TE mit sehr geringer akustischer (keine akustischen Signale) AktivitĂ€t fĂŒhrt. In Bezug auf diese Ergebnisse werden zwei verschiedene Kategorien in Bezug auf elektrische und AE-Signale von TE definiert, stille TE und nicht-stille TE. Stille TE sind elektrische TE-Signale ohne oder mit sehr geringer akustischer AktivitĂ€t, und nicht-stille TE sind elektrische TE-Signale mit akustischer AktivitĂ€t. Die Existenz der stillen PD wird ĂŒber Oszilloskope und digitale SignalverarbeitungsgerĂ€te (DSP) validiert. Auch mit verschiedenen innovativen Methoden und Anordnungen wie Nadel und Kugelelektroden mit und ohne Ölspalt werden die wahrscheinlichen Entstehungsursachen dieses PhĂ€nomens (Silent TE) untersucht. Es wurde festgestellt, dass die Karbonisierungsmuster mit nicht-stiller TE beginnen und wĂ€hrend stiller TE-AktivitĂ€ten selbst bei sehr hohen scheinbaren elektrischen Ladungen unverĂ€ndert bleiben. Dies bedeutet, dass bei der Entwicklung der Karbonisierungsspuren elektrische und AE-Signale erzeugt werden und im Gegensatz dazu ohne Änderungen der Karbonisierungsspuren nur elektrische Signale (ohne AE-Signale) erzeugt werden. Diese Differenzierung ist nur möglich bei gleichzeitigem Einsatz der akustischen Technik und elektrischen Messung im Hinblick auf die TE-Klassifizierung und Lokalisierung

    Advances and Applications of DSmT for Information Fusion. Collected Works, Volume 5

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    This ïŹfth volume on Advances and Applications of DSmT for Information Fusion collects theoretical and applied contributions of researchers working in different ïŹelds of applications and in mathematics, and is available in open-access. The collected contributions of this volume have either been published or presented after disseminating the fourth volume in 2015 in international conferences, seminars, workshops and journals, or they are new. The contributions of each part of this volume are chronologically ordered. First Part of this book presents some theoretical advances on DSmT, dealing mainly with modiïŹed Proportional ConïŹ‚ict Redistribution Rules (PCR) of combination with degree of intersection, coarsening techniques, interval calculus for PCR thanks to set inversion via interval analysis (SIVIA), rough set classiïŹers, canonical decomposition of dichotomous belief functions, fast PCR fusion, fast inter-criteria analysis with PCR, and improved PCR5 and PCR6 rules preserving the (quasi-)neutrality of (quasi-)vacuous belief assignment in the fusion of sources of evidence with their Matlab codes. Because more applications of DSmT have emerged in the past years since the apparition of the fourth book of DSmT in 2015, the second part of this volume is about selected applications of DSmT mainly in building change detection, object recognition, quality of data association in tracking, perception in robotics, risk assessment for torrent protection and multi-criteria decision-making, multi-modal image fusion, coarsening techniques, recommender system, levee characterization and assessment, human heading perception, trust assessment, robotics, biometrics, failure detection, GPS systems, inter-criteria analysis, group decision, human activity recognition, storm prediction, data association for autonomous vehicles, identiïŹcation of maritime vessels, fusion of support vector machines (SVM), Silx-Furtif RUST code library for information fusion including PCR rules, and network for ship classiïŹcation. Finally, the third part presents interesting contributions related to belief functions in general published or presented along the years since 2015. These contributions are related with decision-making under uncertainty, belief approximations, probability transformations, new distances between belief functions, non-classical multi-criteria decision-making problems with belief functions, generalization of Bayes theorem, image processing, data association, entropy and cross-entropy measures, fuzzy evidence numbers, negator of belief mass, human activity recognition, information fusion for breast cancer therapy, imbalanced data classiïŹcation, and hybrid techniques mixing deep learning with belief functions as well

    On the Utility of Representation Learning Algorithms for Myoelectric Interfacing

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    Electrical activity produced by muscles during voluntary movement is a reflection of the firing patterns of relevant motor neurons and, by extension, the latent motor intent driving the movement. Once transduced via electromyography (EMG) and converted into digital form, this activity can be processed to provide an estimate of the original motor intent and is as such a feasible basis for non-invasive efferent neural interfacing. EMG-based motor intent decoding has so far received the most attention in the field of upper-limb prosthetics, where alternative means of interfacing are scarce and the utility of better control apparent. Whereas myoelectric prostheses have been available since the 1960s, available EMG control interfaces still lag behind the mechanical capabilities of the artificial limbs they are intended to steer—a gap at least partially due to limitations in current methods for translating EMG into appropriate motion commands. As the relationship between EMG signals and concurrent effector kinematics is highly non-linear and apparently stochastic, finding ways to accurately extract and combine relevant information from across electrode sites is still an active area of inquiry.This dissertation comprises an introduction and eight papers that explore issues afflicting the status quo of myoelectric decoding and possible solutions, all related through their use of learning algorithms and deep Artificial Neural Network (ANN) models. Paper I presents a Convolutional Neural Network (CNN) for multi-label movement decoding of high-density surface EMG (HD-sEMG) signals. Inspired by the successful use of CNNs in Paper I and the work of others, Paper II presents a method for automatic design of CNN architectures for use in myocontrol. Paper III introduces an ANN architecture with an appertaining training framework from which simultaneous and proportional control emerges. Paper Iv introduce a dataset of HD-sEMG signals for use with learning algorithms. Paper v applies a Recurrent Neural Network (RNN) model to decode finger forces from intramuscular EMG. Paper vI introduces a Transformer model for myoelectric interfacing that do not need additional training data to function with previously unseen users. Paper vII compares the performance of a Long Short-Term Memory (LSTM) network to that of classical pattern recognition algorithms. Lastly, paper vIII describes a framework for synthesizing EMG from multi-articulate gestures intended to reduce training burden

    Introduction to Facial Micro Expressions Analysis Using Color and Depth Images: A Matlab Coding Approach (Second Edition, 2023)

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    The book attempts to introduce a gentle introduction to the field of Facial Micro Expressions Recognition (FMER) using Color and Depth images, with the aid of MATLAB programming environment. FMER is a subset of image processing and it is a multidisciplinary topic to analysis. So, it requires familiarity with other topics of Artifactual Intelligence (AI) such as machine learning, digital image processing, psychology and more. So, it is a great opportunity to write a book which covers all of these topics for beginner to professional readers in the field of AI and even without having background of AI. Our goal is to provide a standalone introduction in the field of MFER analysis in the form of theorical descriptions for readers with no background in image processing with reproducible Matlab practical examples. Also, we describe any basic definitions for FMER analysis and MATLAB library which is used in the text, that helps final reader to apply the experiments in the real-world applications. We believe that this book is suitable for students, researchers, and professionals alike, who need to develop practical skills, along with a basic understanding of the field. We expect that, after reading this book, the reader feels comfortable with different key stages such as color and depth image processing, color and depth image representation, classification, machine learning, facial micro-expressions recognition, feature extraction and dimensionality reduction. The book attempts to introduce a gentle introduction to the field of Facial Micro Expressions Recognition (FMER) using Color and Depth images, with the aid of MATLAB programming environment.Comment: This is the second edition of the boo

    Functional connectivity and dendritic integration of feedback in visual cortex

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    A fundamental question in neuroscience is how different brain regions communicate with each other. Sensory processing engages distributed circuits across many brain areas and involves information flow in the feedforward and feedback direction. While feedforward processing is conceptually well understood, feedback processing has remained mysterious. Cortico-cortical feedback axons are enriched in layer 1, where they form synapses with the apical dendrites of pyramidal neurons. The organization and dendritic integration of information conveyed by these axons, however, are unknown. This thesis describes my efforts to link the circuit-level and dendritic-level organization of cortico-cortical feedback in the mouse visual system. First, using cellular resolution all-optical interrogation across cortical areas, I characterized the functional connectivity between the lateromedial higher visual area (LM) and primary visual cortex (V1). Feedback influence had both facilitating and suppressive effects on visually-evoked activity in V1 neurons, and was spatially organized: retinotopically aligned feedback was relatively more suppressive, while retinotopically offset feedback was relatively more facilitating. Second, to examine how feedback inputs are integrated in apical dendrites, I optogenetically stimulated presynaptic neurons in LM while using 2-photon calcium imaging to map feedback-recipient spines in the apical tufts of layer 5 neurons in V1. Activation of a single feedback-providing input was sufficient to boost calcium signals and recruit branch-specific local events in the recipient dendrite, suggesting that feedback can engage dendritic nonlinearities directly. Finally, I measured the recruitment of apical dendrites during visual stimulus processing. Surround visual stimuli, which should recruit relatively more facilitating feedback, drove local calcium events in apical tuft branches. Moreover, global dendritic event size was not purely determined by somatic activity but modulated by visual stimuli and behavioural state, in a manner consistent with the spatial organization of feedback. In summary, these results point toward a possible involvement of active dendritic processing in the integration of feedback signals. Active dendrites could thus provide a biophysical substrate for the integration of essential top-down information streams, including contextual or predictive processing

    Towards Object-Centric Scene Understanding

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    Visual perception for autonomous agents continues to attract community attention due to the disruptive technologies and the wide applicability of such solutions. Autonomous Driving (AD), a major application in this domain, promises to revolutionize our approach to mobility while bringing critical advantages in limiting accident fatalities. Fueled by recent advances in Deep Learning (DL), more computer vision tasks are being addressed using a learning paradigm. Deep Neural Networks (DNNs) succeeded consistently in pushing performances to unprecedented levels and demonstrating the ability of such approaches to generalize to an increasing number of difficult problems, such as 3D vision tasks. In this thesis, we address two main challenges arising from the current approaches. Namely, the computational complexity of multi-task pipelines, and the increasing need for manual annotations. On the one hand, AD systems need to perceive the surrounding environment on different levels of detail and, subsequently, take timely actions. This multitasking further limits the time available for each perception task. On the other hand, the need for universal generalization of such systems to massively diverse situations requires the use of large-scale datasets covering long-tailed cases. Such requirement renders the use of traditional supervised approaches, despite the data readily available in the AD domain, unsustainable in terms of annotation costs, especially for 3D tasks. Driven by the AD environment nature and the complexity dominated (unlike indoor scenes) by the presence of other scene elements (mainly cars and pedestrians) we focus on the above-mentioned challenges in object-centric tasks. We, then, situate our contributions appropriately in fast-paced literature, while supporting our claims with extensive experimental analysis leveraging up-to-date state-of-the-art results and community-adopted benchmarks

    Management of socio-economic transformations of business processes: current realities, global challenges, forecast scenarios and development prospects

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    The authors of the scientific monograph have come to the conclusion that ĐŒanagement of socio-economic transformations of business processes requires the use of mechanisms to support of entrepreneurship, sectors of the national economy, the financial system, and critical infrastructure. Basic research focuses on assessment the state of social service provision, analysing economic security, implementing innovation and introducing digital technologies. The research results have been implemented in the different models of costing, credit risk and capital management, tax control, use of artificial intelligence and blockchain. The results of the study can be used in the developing of policies, programmes and strategies for economic security, development of the agricultural sector, transformation of industrial policy, implementation of employment policy in decision-making at the level of ministries and agencies that regulate the management of socio-economic and European integration processes. The results can also be used by students and young scientists in the educational process and conducting scientific research on global challenges and creation scenarios for the development of socio-economic processes
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