306 research outputs found
LIPIcs, Volume 251, ITCS 2023, Complete Volume
LIPIcs, Volume 251, ITCS 2023, Complete Volum
La traduzione specializzata allâopera per una piccola impresa in espansione: la mia esperienza di internazionalizzazione in cinese di Bioretics© S.r.l.
Global markets are currently immersed in two all-encompassing and unstoppable processes: internationalization and globalization. While the former pushes companies to look beyond the borders of their country of origin to forge relationships with foreign trading partners, the latter fosters the standardization in all countries, by reducing spatiotemporal distances and breaking down geographical, political, economic and socio-cultural barriers. In recent decades, another domain has appeared to propel these unifying drives: Artificial Intelligence, together with its high technologies aiming to implement human cognitive abilities in machinery. The âLanguage Toolkit â Le lingue straniere al servizio dellâinternazionalizzazione dellâimpresaâ project, promoted by the Department of Interpreting and Translation (ForlĂŹ Campus) in collaboration with the Romagna Chamber of Commerce (ForlĂŹ-Cesena and Rimini), seeks to help Italian SMEs make their way into the global market. It is precisely within this project that this dissertation has been conceived. Indeed, its purpose is to present the translation and localization project from English into Chinese of a series of texts produced by Bioretics© S.r.l.: an investor deck, the company website and part of the installation and use manual of the Aliquis© framework software, its flagship product. This dissertation is structured as follows: Chapter 1 presents the project and the company in detail; Chapter 2 outlines the internationalization and globalization processes and the Artificial Intelligence market both in Italy and in China; Chapter 3 provides the theoretical foundations for every aspect related to Specialized Translation, including website localization; Chapter 4 describes the resources and tools used to perform the translations; Chapter 5 proposes an analysis of the source texts; Chapter 6 is a commentary on translation strategies and choices
Advances and Applications of DSmT for Information Fusion. Collected Works, Volume 5
This ïŹfth volume on Advances and Applications of DSmT for Information Fusion collects theoretical and applied contributions of researchers working in different ïŹelds 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 modiïŹed Proportional ConïŹict 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 classiïŹers, 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, identiïŹcation of maritime vessels, fusion of support vector machines (SVM), Silx-Furtif RUST code library for information fusion including PCR rules, and network for ship classiïŹcation.
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 classiïŹcation, and hybrid techniques mixing deep learning with belief functions as well
Mathematical Problems in Rock Mechanics and Rock Engineering
With increasing requirements for energy, resources and space, rock engineering projects are being constructed more often and are operated in large-scale environments with complex geology. Meanwhile, rock failures and rock instabilities occur more frequently, and severely threaten the safety and stability of rock engineering projects. It is well-recognized that rock has multi-scale structures and involves multi-scale fracture processes. Meanwhile, rocks are commonly subjected simultaneously to complex static stress and strong dynamic disturbance, providing a hotbed for the occurrence of rock failures. In addition, there are many multi-physics coupling processes in a rock mass. It is still difficult to understand these rock mechanics and characterize rock behavior during complex stress conditions, multi-physics processes, and multi-scale changes. Therefore, our understanding of rock mechanics and the prevention and control of failure and instability in rock engineering needs to be furthered. The primary aim of this Special Issue âMathematical Problems in Rock Mechanics and Rock Engineeringâ is to bring together original research discussing innovative efforts regarding in situ observations, laboratory experiments and theoretical, numerical, and big-data-based methods to overcome the mathematical problems related to rock mechanics and rock engineering. It includes 12 manuscripts that illustrate the valuable efforts for addressing mathematical problems in rock mechanics and rock engineering
Pre-Trained Driving in Localized Surroundings with Semantic Radar Information and Machine Learning
Entlang der Signalverarbeitungskette von Radar Detektionen bis zur Fahrzeugansteuerung, diskutiert diese Arbeit eine semantischen Radar Segmentierung, einen darauf aufbauenden Radar SLAM, sowie eine im Verbund realisierte autonome Parkfunktion. Die Radarsegmentierung der (statischen) Umgebung wird durch ein Radar-spezifisches neuronales Netzwerk RadarNet erreicht. Diese Segmentierung ermöglicht die Entwicklung des semantischen Radar Graph-SLAM SERALOC. Auf der Grundlage der semantischen Radar SLAM Karte wird eine beispielhafte autonome ParkfunktionalitÀt in einem realen VersuchstrÀger umgesetzt.
Entlang eines aufgezeichneten Referenzfades parkt die Funktion ausschlieĂlich auf Basis der Radar Wahrnehmung mit bisher unerreichter Positioniergenauigkeit.
Im ersten Schritt wird ein Datensatz von 8.2 · 10^6 punktweise semantisch gelabelten Radarpunktwolken ĂŒber eine Strecke von 2507.35m generiert. Es sind keine vergleichbaren DatensĂ€tze dieser Annotationsebene und Radarspezifikation öffentlich verfĂŒgbar. Das ĂŒberwachte
Training der semantischen Segmentierung RadarNet erreicht 28.97% mIoU auf sechs Klassen.
AuĂerdem wird ein automatisiertes Radar-Labeling-Framework SeRaLF vorgestellt, welches das Radarlabeling multimodal mittels Referenzkameras und LiDAR unterstĂŒtzt.
FĂŒr die kohĂ€rente Kartierung wird ein Radarsignal-Vorfilter auf der Grundlage einer Aktivierungskarte entworfen, welcher Rauschen und andere dynamische Mehrwegreflektionen unterdrĂŒckt. Ein speziell fĂŒr Radar angepasstes Graph-SLAM-Frontend mit Radar-Odometrie
Kanten zwischen Teil-Karten und semantisch separater NDT Registrierung setzt die vorgefilterten semantischen Radarscans zu einer konsistenten metrischen Karte zusammen. Die Kartierungsgenauigkeit und die Datenassoziation werden somit erhöht und der erste semantische Radar Graph-SLAM fĂŒr beliebige statische Umgebungen realisiert.
Integriert in ein reales Testfahrzeug, wird das Zusammenspiel der live RadarNet Segmentierung und des semantischen Radar Graph-SLAM anhand einer rein Radar-basierten autonomen ParkfunktionalitĂ€t evaluiert. Im Durchschnitt ĂŒber 42 autonome Parkmanöver
(â
3.73 km/h) bei durchschnittlicher ManöverlĂ€nge von â
172.75m wird ein Median absoluter Posenfehler von 0.235m und End-Posenfehler von 0.2443m erreicht, der vergleichbare
Radar-Lokalisierungsergebnisse um â 50% ĂŒbertrifft. Die Kartengenauigkeit von verĂ€nderlichen, neukartierten Orten ĂŒber eine Kartierungsdistanz von â
165m ergibt eine â 56%-ige Kartenkonsistenz bei einer Abweichung von â
0.163m. FĂŒr das autonome Parken wurde ein gegebener Trajektorienplaner und Regleransatz verwendet
LIPIcs, Volume 261, ICALP 2023, Complete Volume
LIPIcs, Volume 261, ICALP 2023, Complete Volum
Geographic information extraction from texts
A large volume of unstructured texts, containing valuable geographic information, is available online. This information â provided implicitly or explicitly â is useful not only for scientific studies (e.g., spatial humanities) but also for many practical applications (e.g., geographic information retrieval). Although large progress has been achieved in geographic information extraction from texts, there are still unsolved challenges and issues, ranging from methods, systems, and data, to applications and privacy. Therefore, this workshop will provide a timely opportunity to discuss the recent advances, new ideas, and concepts but also identify research gaps in geographic information extraction
Towards an Effective Organization-Wide Bulk Email System
Bulk email is widely used in organizations to communicate messages to
employees. It is an important tool in making employees aware of policies,
events, leadership updates, etc. However, in large organizations, the problem
of overwhelming communication is widespread. Ineffective organizational bulk
emails waste employees' time and organizations' money, and cause a lack of
awareness or compliance with organizations' missions and priorities. This
thesis focuses on improving organizational bulk email systems by 1) conducting
qualitative research to understand different stakeholders; 2) conducting field
studies to evaluate personalization's effects on getting employees to read bulk
messages; 3) designing tools to support communicators in evaluating bulk
emails. We performed these studies at the University of Minnesota, interviewing
25 employees (both senders and recipients), and including 317 participants in
total. We found that the university's current bulk email system is ineffective
as only 22% of the information communicated was retained by employees. To
encourage employees to read high-level information, we implemented a
multi-stakeholder personalization framework that mixed
important-to-organization messages with employee-preferred messages and
improved the studied bulk email's recognition rate by 20%. On the sender side,
we iteratively designed a prototype of a bulk email evaluation platform. In
field evaluation, we found bulk emails' message-level performance helped
communicators in designing bulk emails. We collected eye-tracking data and
developed a neural network technique to estimate how much time each message is
being read using recipients' interactions with browsers only, which improved
the estimation accuracy to 73%. In summary, this work sheds light on how to
design organizational bulk email systems that communicate effectively and
respect different stakeholders' value.Comment: PhD Thesi
Applications
Volume 3 describes how resource-aware machine learning methods and techniques are used to successfully solve real-world problems. The book provides numerous specific application examples: in health and medicine for risk modelling, diagnosis, and treatment selection for diseases in electronics, steel production and milling for quality control during manufacturing processes in traffic, logistics for smart cities and for mobile communications
Technology Assessment of Dual-Use ICTs - How to Assess Diffusion, Governance and Design
Technologies that can be used in military and civilian applications are referred to as dual-use. The dual-use nature of many information and communications technologies (ICTs) raises new questions for research and development for national, international, and human security. Measures to deal with the risks associated with the various dual-use technologies, including proliferation control, design approaches, and policy measures, vary widely. For example, Autonomous Weapon Systems (AWS) have not yet been regulated, while cryptographic products are subject to export and import controls. Innovations in artificial intelligence (AI), robotics, cybersecurity, and automated analysis of publicly available data raise new questions about their respective dual-use risks.
Dual-use risks have been systematically discussed so far, especially in the life sciences, which have contributed to the development of methods for assessment and risk management. Dual-use risks arise, among other things, from the fact that safety-critical technologies can be easily disseminated or modified, as well as used as part of a weapon system. Therefore, the development and adaptation of robots and software requires an independent consideration that builds on the insights of related dual-use discourses. Therefore, this dissertation considers the management of such risks in terms of the proliferation, regulation, and design of individual dual-use information technologies. Technology Assessment (TA) is the epistemological framework for this work, bringing together the concepts and approaches of Critical Security Studies (CSS) and Human-Computer Interaction (HCI) to help evaluate and shape dual-use technologies.
In order to identify the diffusion of dual-use at an early stage, the dissertation first examines the diffusion of dual-use innovations between civilian and military research in expert networks on LinkedIn, as well as on the basis of AI patents in a patent network. The results show low diffusion and tend to confirm existing studies on diffusion in patent networks. In the following section, the regulation of dual-use technologies is examined in the paper through two case studies. The first study uses a discourse analysis to show the value conflicts with regard to the regulation of autonomous weapons systems using the concept of Meaningful Human Control (MHC), while a second study, as a long-term comparative case study, analyzes the change and consequences of the regulation of strong cryptography in the U.S. as well as the programs of intelligence agencies for mass surveillance. Both cases point to the central role of private companies, both in the production of AWS and as intermediaries for the dissemination of encryption, as well as surveillance intermediaries. Subsequently, the dissertation examines the design of a dual-use technology using an Open Source Intelligence System (OSINT) for cybersecurity. For this purpose, conceptual, empirical, and technical studies are conducted as part of the Value-Sensitive Design (VSD) framework. During the studies, implications for research on and design of OSINT were identified. For example, the representative survey of the German population has shown that transparency of use while reducing mistrust is associated with higher acceptance of such systems. Additionally, it has been shown that data sparsity through the use of expert networks has many positive effects, not only improving the performance of the system, but is also preferable for legal and social reasons. Thus, the work contributes to the understanding of specific dual-use risks of AI, the regulation of AWS and cryptography, and the design of OSINT in cybersecurity. By combining concepts from CSS and participatory design methods in HCI, this work provides an interdisciplinary and multi-method contribution
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