497 research outputs found
Language Design for Reactive Systems: On Modal Models, Time, and Object Orientation in Lingua Franca and SCCharts
Reactive systems play a crucial role in the embedded domain. They continuously interact with their environment, handle concurrent operations, and are commonly expected to provide deterministic behavior to enable application in safety-critical systems. In this context, language design is a key aspect, since carefully tailored language constructs can aid in addressing the challenges faced in this domain, as illustrated by the various concurrency models that prevent the known pitfalls of regular threads. Today, many languages exist in this domain and often provide unique characteristics that make them specifically fit for certain use cases. This thesis evolves around two distinctive languages: the actor-oriented polyglot coordination language Lingua Franca and the synchronous statecharts dialect SCCharts. While they take different approaches in providing reactive modeling capabilities, they share clear similarities in their semantics and complement each other in design principles. This thesis analyzes and compares key design aspects in the context of these two languages. For three particularly relevant concepts, it provides and evaluates lean and seamless language extensions that are carefully aligned with the fundamental principles of the underlying language. Specifically, Lingua Franca is extended toward coordinating modal behavior, while SCCharts receives a timed automaton notation with an efficient execution model using dynamic ticks and an extension toward the object-oriented modeling paradigm
Current issues of the Russian language teaching XIV
Collection of papers âCurrent issues of the Russian language teaching XIVâ is devoted to issues of methodology of teaching Russian as a foreign language, to issues of linguistics and literary science and includes papers related to the use of online tools and resources in teaching Russian. This collection of papers is a result of the international scientific conference âCurrent issues of the Russian language teaching XIVâ, which was scheduled for 8â10 May 2020, but due to the pandemic COVID-19 took place remotely
Designing a New Tactile Display Technology and its Disability Interactions
People with visual impairments have a strong desire for a refreshable tactile interface that can provide immediate access to full page of Braille and tactile graphics. Regrettably, existing devices come at a considerable expense and remain out of reach for many. The exorbitant costs associated with current tactile displays stem from their intricate design and the multitude of components needed for their construction. This underscores the pressing need for technological innovation that can enhance tactile displays, making them more accessible and available to individuals with visual impairments. This research thesis delves into the development of a novel tactile display technology known as Tacilia. This technology's necessity and prerequisites are informed by in-depth qualitative engagements with students who have visual impairments, alongside a systematic analysis of the prevailing architectures underpinning existing tactile display technologies. The evolution of Tacilia unfolds through iterative processes encompassing conceptualisation, prototyping, and evaluation. With Tacilia, three distinct products and interactive experiences are explored, empowering individuals to manually draw tactile graphics, generate digitally designed media through printing, and display these creations on a dynamic pin array display. This innovation underscores Tacilia's capability to streamline the creation of refreshable tactile displays, rendering them more fitting, usable, and economically viable for people with visual impairments
Towards Scalable, Private and Practical Deep Learning
Deep Learning (DL) models have drastically improved the performance of Artificial Intelligence (AI) tasks such as image recognition, word prediction, translation, among many others, on which traditional Machine Learning (ML) models fall short. However, DL models are costly to design, train, and deploy due to their computing and memory demands. Designing DL models usually requires extensive expertise and significant manual tuning efforts. Even with the latest accelerators such as Graphics Processing Unit (GPU) and Tensor Processing Unit (TPU), training DL models can take prohibitively long time, therefore training large DL models in a distributed manner is a norm. Massive amount of data is made available thanks to the prevalence of mobile and internet-of-things (IoT) devices. However, regulations such as HIPAA and GDPR limit the access and transmission of personal data to protect security and privacy. Therefore, enabling DL model training in a decentralized but private fashion is urgent and critical. Deploying trained DL models in a real world environment usually requires meeting Quality of Service (QoS) standards, which makes adaptability of DL models an important yet challenging matter. In this dissertation, we aim to address the above challenges to make a step towards scalable, private, and practical deep learning. To simplify DL model design, we propose Efficient Progressive Neural-Architecture Search (EPNAS) and FedCust to automatically design model architectures and tune hyperparameters, respectively. To provide efficient and robust distributed training while preserving privacy, we design LEASGD, TiFL, and HDFL. We further conduct a study on the security aspect of distributed learning by focusing on how data heterogeneity affects backdoor attacks and how to mitigate such threats. Finally, we use super resolution (SR) as an example application to explore model adaptability for cross platform deployment and dynamic runtime environment. Specifically, we propose DySR and AdaSR frameworks which enable SR models to meet QoS by dynamically adapting to available resources instantly and seamlessly without excessive memory overheads
Jornadas Nacionales de InvestigaciĂłn en Ciberseguridad: actas de las VIII Jornadas Nacionales de InvestigaciĂłn en ciberseguridad: Vigo, 21 a 23 de junio de 2023
Jornadas Nacionales de InvestigaciĂłn en Ciberseguridad (8ÂȘ. 2023. Vigo)atlanTTicAMTEGA: Axencia para a modernizaciĂłn tecnolĂłxica de GaliciaINCIBE: Instituto Nacional de Cibersegurida
LIPIcs, Volume 274, ESA 2023, Complete Volume
LIPIcs, Volume 274, ESA 2023, Complete Volum
Humanitarian Protection in International Refugee Law, Sexism and Exclusion: Case for Human Rights Assessment
The overall purpose of the 1951 Convention Relating to the Status of Refugee (Refugee Convention) and its 1967 Protocol is to protect refugees fleeing persecution and threat to life. Established in the aftermath of World War II (WW II), Article 1. A(1) of the Refugee Convention centered the meaning and criteria for refugee protection on the circumstances of the War. Thus, the status of a refugee is framed from persecution feared or suffered âon account ofâ race, religion, nationality, political opinion, and membership in a particular social group. More than seven decades after WW II, the scope of the definition has subsisted, despite the changing paradigm in the circumstances and responses to involuntary migration. This is not without consequences. With compelling demands in forced migration, the international community has developed different approaches towards the refugee crisis, yet with minimal solutions.
Despite the massive outcry to address the complex challenges of refugees, hostile attitudes to protection seekers remained daunting and overly pervasive in the international arena. Humanitarian protection of refugees is one of the most crucial yet mismanaged obligations of international law. With increasing demands for humanitarian protection, many destination countries perceive refugees as symbols of conflict, economic burden, and insecurity. This results in rejection, denials, pushback, detention, and refoulement, as well as a clash between political interests and international obligations to protect. Even where host states may exercise discretion to protect, such commitment is subject to the eligibility requirements of Article 1. A(1) and subject to excludability. Because the state functions as an operational instrument for international refugee law (IRL), the limitations of IRL are replicated in domestic laws with detrimental consequences on âunCoventionâ refugees. Women are the most disadvantaged given that sex is excluded from the status of refugees and grounds of protection. This gives cause to interrogate the nondiscriminatory principle of the Refugee Convention and its 1967 Protocol, and conformity with the norms of international human rights law.
This dissertation explores sexism in IRL and the exclusion of womenâs experience from the framework of humanitarian protection. It traces the problems of nexus generated from the limitations of refugee inclusion and their intersectionality with gender exclusion and the framing of laws of excludability. The analysis of state practice stresses the interconnection between law, policy, and practice. Centering on the United States jurisprudence, the study investigates the irregularities in the construction of the refugee inclusion and exclusion laws and the associated interpretative barriers that affect the application. The findings are contextualized with lessons from other jurisdictions of selected common law countriesâAustralia, Canada, and the United Kingdom (UK). Law and human needs are dynamic. Therefore, this study examined the effects of inflexibility and lack of diversity in a seventy-two-year Refugee Convention and the prospects of change for a sustainable inclusive refugee regime. In view of these, this study makes recommendations including re-conceptualizing the criteria of refugee eligibility that reflect human realities in contemporary society and taking cognizance of the human rights principles of IRL under the Convention Against Torture (CAT)
Reality Bites
Fake news, alternative facts, post truthâterms all too familiar to anyone in U.S. political culture and concepts at the core of Dana L. Cloudâs new book, Reality Bites, which explores truth claims in contemporary political rhetoric in the face of widespread skepticism regarding the utility, ethics, and viability of an empirical standard for political truths. Cloud observes how appeals to truth often assumeâmistakenlyâthat it is a matter of simple representation of facts. However, since neither fact-checking nor âtruthinessâ can respond meaningfully to this problem, she argues for a rhetorical realismâthe idea that communicators can bring knowledge from particular perspectives and experiences into the domain of common sense.
Through a series of case studiesâincluding the PolitiFact fact-checking project, the Planned Parenthood âselling baby partsâ scandal, the Chelsea Manning and Edward Snowden cases, Neil DeGrasse Tysonâs Cosmos, the rhetoric of Thomas Paine and the American Revolution, and the Black Lives Matter movementâCloud advocates for the usefulness of narrative, myth, embodiment, affect, and spectacle in creating accountability in contemporary U.S. political rhetoric. If dominant reality âbitesââin being oppressive and exploitativeâit is time, Cloud argues, for those in the reality-based community to âbite back.
Efficiency Improvements in the Quality Assurance Process for Data Races
As the usage of concurrency in software has gained importance in the last years, and is still rising, new types of defects increasingly appeared in software. One of the most prominent and critical types of such new defect types are data races. Although research resulted in an increased effectiveness of dynamic quality assurance regarding data races, the efficiency in the quality assurance process still is a factor preventing widespread practical application. First, dynamic quality assurance techniques used for the detection of data races are inefficient. Too much effort is needed for conducting dynamic quality assurance. Second, dynamic quality assurance techniques used for the analysis of reported data races are inefficient. Too much effort is needed for analyzing reported data races and identifying issues in the source code.
The goal of this thesis is to enable efficiency improvements in the process of quality assurance for data races by: (1) analyzing the representation of the dynamic behavior of a system under test. The results are used to focus instrumentation of this system, resulting in a lower runtime overhead during test execution compared to a full instrumentation of this system. (2) Analyzing characteristics and preprocessing of reported data races. The results of the preprocessing are then provided to developers and quality assurance personnel, enabling an analysis and debugging process, which is more efficient than traditional analysis of data race reports. Besides dynamic data race detection, which is complemented by the solution, all steps in the process of dynamic quality assurance for data races are discussed in this thesis.
The solution for analyzing UML Activities for nodes possibly executing in parallel to other nodes or themselves is based on a formal foundation using graph theory. A major problem that has been solved in this thesis was the handling of cycles within UML Activities. This thesis provides a dynamic limit for the number of cycle traversals, based on the elements of each UML Activity to be analyzed and their semantics. Formal proofs are provided with regard to the creation of directed acyclic graphs and with regard to their analysis concerning the identification of elements that may be executed in parallel to other elements. Based on an examination of the characteristics of data races and data race reports, the results of dynamic data race detection are preprocessed and the outcome of this preprocessing is presented to users for further analysis.
This thesis further provides an exemplary application of the solution idea, of the results of analyzing UML Activities, and an exemplary examination of the efficiency improvement of the dynamic data race detection, which showed a reduction in the runtime overhead of 44% when using the focused instrumentation compared to full instrumentation. Finally, a controlled experiment has been set up and conducted to examine the effects of the preprocessing of reported data races on the efficiency of analyzing data race reports. The results show that the solution presented in this thesis enables efficiency improvements in the analysis of data race reports between 190% and 660% compared to using traditional approaches.
Finally, opportunities for future work are shown, which may enable a broader usage of the results of this thesis and further improvements in the efficiency of quality assurance for data races.Da die Verwendung von Concurrency in Software in den letzten Jahren an Bedeutung gewonnen hat, und immer noch gewinnt, sind zunehmend neue Arten von Fehlern in Software aufgetaucht. Eine der prominentesten und kritischsten Arten solcher neuer Fehlertypen sind data races. Auch wenn die Forschung zu einer steigenden EffektivitĂ€t von Verfahren der dynamischen QualitĂ€tssicherung gefĂŒhrt hat, so ist die Effizienz im Prozess der QualitĂ€tssicherung noch immer ein Faktor, der eine weitverbreitete praktische Anwendung verhindert. Zum einen wird zu viel Aufwand benötigt, um dynamische QualitĂ€tssicherung durchzufĂŒhren. Zum anderen sind die Verfahren zur Analyse gemeldeter data races ineffizient; es wird zu viel Aufwand benötigt, um gemeldete data races zu analysieren und Probleme im Quellcode zu identifizieren.
Das Ziel dieser Dissertation ist es, Effizienzsteigerungen im QualitĂ€tssicherungsprozess fĂŒr data races zu ermöglichen, durch: (1) Analyse der ReprĂ€sentation des dynamischen Verhaltens des zu testenden Systems. Mit den Ergebnissen wird die Instrumentierung dieses Systems fokussiert, so dass ein im Vergleich zur vollen Instrumentierung des Systems geringerer Mehraufwand an Laufzeit benötigt wird. (2) Analyse der Charakteristiken von und Vorverarbeitung der gemeldeten data races. Die Ergebnisse der Vorverarbeitung werden Mitarbeitenden in der Entwicklung und QualitĂ€tssicherung prĂ€sentiert, so dass ein Analyse- und Fehlerbehebungsprozess ermöglicht wird, welcher effizienter als traditionelle Analysen gemeldeter data races ist. Mit Ausnahme der dynamischen data race Erkennung, welche durch die Lösung komplementiert wird, werden alle Schritte im Prozess der dynamischen QualitĂ€tssicherung fĂŒr data races in dieser Dissertation behandelt.
Die Lösung zur Analyse von UML AktivitĂ€ten auf Knoten, die möglicherweise parallel zu sich selbst oder anderen Knoten ausgefĂŒhrt werden, basiert auf einer formalen Grundlage aus dem Bereich der Graphentheorie. Eines der Hauptprobleme, welches gelöst wurde, war die Verarbeitung von Zyklen innerhalb der UML AktivitĂ€ten. Diese Dissertation fĂŒhrt ein dynamisches Limit fĂŒr die Anzahl an ZyklusdurchlĂ€ufen ein, welches die Elemente jeder zu analysierenden UML AktivitĂ€t sowie deren Semantiken berĂŒcksichtigt. Ebenso werden formale Beweise prĂ€sentiert in Bezug auf die Erstellung gerichteter azyklischer Graphen, sowie deren Analyse zur Identifizierung von Elementen, die parallel zu anderen Elementen ausgefĂŒhrt werden können. Auf Basis einer Untersuchung von Charakteristiken von data races sowie Meldungen von data races werden die Ergebnisse der dynamischen Erkennung von data races vorverarbeitet, und das Ergebnis der Vorverarbeitung gemeldeter data races wird Benutzern zur weiteren Analyse prĂ€sentiert.
Diese Dissertation umfasst weiterhin eine exemplarische Anwendung der Lösungsidee und der Analyse von UML AktivitĂ€ten, sowie eine exemplarische Untersuchung der Effizienzsteigerung der dynamischen Erkennung von data races. Letztere zeigte eine Reduktion des Mehraufwands an Laufzeit von 44% bei fokussierter Instrumentierung im Vergleich zu voller Instrumentierung auf. AbschlieĂend wurde ein kontrolliertes Experiment aufgesetzt und durchgefĂŒhrt, um die Effekte der Vorverarbeitung gemeldeter data races auf die Effizienz der Analyse dieser gemeldeten data races zu untersuchen. Die Ergebnisse zeigen, dass die in dieser Dissertation vorgestellte Lösung verglichen mit traditionellen AnsĂ€tzen Effizienzsteigerungen in der Analyse gemeldeter data races von 190% bis zu 660% ermöglicht.
AbschlieĂend werden Möglichkeiten fĂŒr zukĂŒnftige Arbeiten vorgestellt, welche eine breitere Anwendung der Ergebnisse dieser Dissertation ebenso wie weitere Effizienzsteigerungen im QualitĂ€tssicherungsprozess fĂŒr data races ermöglichen können
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