Hasil untuk "Communities. Classes. Races"

A. Diez-Roux, F. Nieto, C. Muntaner et al.

Andrei-Carlo Papuc, Lasse Peters, Sihao Sun et al.

Autonomous drone racing pushes the boundaries of high-speed motion planning and multi-agent strategic decision-making. Success in this domain requires drones not only to navigate at their limits but also to anticipate and counteract competitors' actions. In this paper, we study a fundamental question that arises in this domain: how deeply should an agent strategize before taking an action? To this end, we compare two planning paradigms: the Model Predictive Game (MPG), which finds interaction-aware strategies at the expense of longer computation times, and contouring Model Predictive Control (MPC), which computes strategies rapidly but does not reason about interactions. We perform extensive experiments to study this trade-off, revealing that MPG outperforms MPC at moderate velocities but loses its advantage at higher speeds due to latency. To address this shortcoming, we propose a Learned Model Predictive Game (LMPG) approach that amortizes model predictive gameplay to reduce latency. In both simulation and hardware experiments, we benchmark our approach against MPG and MPC in head-to-head races, finding that LMPG outperforms both baselines.

Mahak Kumari

The impact of the carceral system and policing on youth led to the development of a separate juvenile system recognizing the special needs of young people. However, policing-based harm remains at the forefront of legal scholarship not just for its continued prevalence in the country as a whole, but also because of the disproportionate impact on Black and Brown people. This impact is compounded when the targets of police violence are youth, who are subjected to extreme force by police at higher rates in comparison to adults and their white youth counterparts. Legal protections that purport to protect citizens’ rights inhibit victims from obtaining any meaningful recourse or compensation after experiencing the most heinous forms of police misconduct or violence. Individual police officers are protected by qualified immunity, and institutional liability is an illusory concept due to the flawed and extremely high bars created by the Monell framework. States have obligations to protect children under the parens patriae doctrine but are shielded from liability both because policing falls under municipal control and because the Eleventh Amendment provides states with sovereign immunity. Municipalities responsible for police conduct and discipline lack a similar common law obligation to their vulnerable citizens. This Note explores how the existing Monell and parens patriae doctrines can be reformed and adapted to ensure that institutions not only have a duty to protect youth from policing-based harm, but also that this duty is enforced with mechanisms for finding liability. Only with a meaningful pathway to liability for harm caused to youth at the hands of police can any real police accountability or long-term reform in policing be expected and racial disparities in this harm be addressed.

Aron Harder, Amar Kulkarni, Madhur Behl

The field of high-speed autonomous racing has seen significant advances in recent years, with the rise of competitions such as RoboRace and the Indy Autonomous Challenge providing a platform for researchers to develop software stacks for autonomous race vehicles capable of reaching speeds in excess of 170 mph. Ensuring the safety of these vehicles requires the software to continuously monitor for different faults and erroneous operating conditions during high-speed operation, with the goal of mitigating any unreasonable risks posed by malfunctions in sub-systems and components. This paper presents a comprehensive overview of the HALO safety architecture, which has been implemented on a full-scale autonomous racing vehicle as part of the Indy Autonomous Challenge. The paper begins with a failure mode and criticality analysis of the perception, planning, control, and communication modules of the software stack. Specifically, we examine three different types of faults - node health, data health, and behavioral-safety faults. To mitigate these faults, the paper then outlines HALO safety archetypes and runtime monitoring methods. Finally, the paper demonstrates the effectiveness of the HALO safety architecture for each of the faults, through real-world data gathered from autonomous racing vehicle trials during multi-agent scenarios.

Maria S. Frolova

In 2021-2023 In Yekaterinburg, 3 volumes of author's essays were published on the development of the cultural sphere of the capital of the Urals. The release of review texts was initiated by the Department of Culture of the Yekaterinburg Administration. On 864 pages, using archival materials, unique historical and contemporary photographs, the “spirit of the development of the arts” is presented - music, theater and cinema in Volume 1, sculpture, painting and architecture in Volume 2, literature, art education and the educational system in Volume 3. The chosen genre - essays - is original and productive. Texts are a form of summing up, recording successes in the development of the Yekaterinburg/Sverdlovsk sphere of culture. The tercentenary anniversary of Yekaterinburg (the city can be scientifically categorized as a regional or peripheral capital), which took place in 2023, is an occasion for reflection and further planning. Richly illustrated, gift-type books are deep and original from the point of view of analytics of the development of the cultural sphere. The authors were leading academic researchers and employees of the largest cultural institutions of Yekaterinburg - the Sverdlovsk Regional Museum of Local Lore, UrFU named after the first President of Russia B. N. Yeltsin, the Museum of the History of Yekaterinburg, the Sverdlovsk Music School named after P. I. Tchaikovsky. Using the general scientific critical method, methods of synthesis and analysis, the text of the review provides a brief overview of all three volumes of essays, characterizes the merits of the publication, and provides criticism.

Alexis Briggs

Black young adults participate in activism to challenge and transform oppressive systems. In this qualitative study, we employed thematic analysis and used the framework of sociopolitical development (SPD) to explore their motivations and challenges to participation amid the COVID-19 pandemic and the summer of 2020 in the United States. Semi-structured interviews with 22 Black young adults in early 2022 revealed that social identities, sense of legacy, impact, and morals drove their participation. Further, contending with systemic oppression, impact, harm, and working with others challenged their participation. This study holds valuable insights for stakeholders as they support and empower young Black activists navigating social justice efforts in our dynamic and evolving sociopolitical landscape. Further, this work highlights the enduring tradition of activism within the Black community and emphasizes the need to empower young Black activists as change agents in the pursuit of a more equitable society.

Ben Weintraub, Satwik Prabhu Kumble, Cristina Nita-Rotaru et al.

The Lightning Network, a payment channel network with a market cap of over 192M USD, is designed to resolve Bitcoin's scalability issues through fast off-chain transactions. There are multiple Lightning Network client implementations, all of which conform to the same textual specifications known as BOLTs. Several vulnerabilities have been manually discovered, but to-date there have been few works systematically analyzing the security of the Lightning Network. In this work, we take a foundational approach to analyzing the security of the Lightning Network with the help of formal methods. Based on the BOLTs' specifications, we build a detailed formal model of the Lightning Network's single-hop payment protocol and verify it using the Spin model checker. Our model captures both concurrency and error semantics of the payment protocol. We then define several security properties which capture the correct intermediate operation of the protocol, ensuring that the outcome is always certain to both channel peers, and using them we re-discover a known attack previously reported in the literature along with a novel attack, referred to as a Payout Race. A Payout Race consists of a particular sequence of events that can lead to an ambiguity in the protocol in which innocent users can unwittingly lose funds. We confirm the practicality of this attack by reproducing it in a local testbed environment.

Anqi Zhou, Anqi Zhou, Younghwan Pan

Introduction: This study investigated the influence of indoor lighting environments on paper reading efficiency and brain fatigue to explore lighting parameters that benefit users during various reading durations.Methods: The study was conducted in the Smart Lighting Lab, where 12 participants were tested under different illuminance levels and correlated color temperatures (CCT) for three distinct reading durations. Reading efficiency during the task tests and objective measures of brain activity by monitoring participants’ electroencephalograms (EEGs) were used as key factors to assess participants’ fatigue levels.Results: By analyzing the subjective and objective results, we found that paper reading efficiency was significantly affected by changes in the lighting environment. Also, based on the results of this study, we propose lighting recommendations for paper reading tasks of different durations. For a 15 min reading task, the lighting condition of 500 lux-6,500 K were the most efficient for reading; for a 30 min reading task, 500 lux-4,000 K lighting environments were found to be the most effective; and 750 lux-6,500 K was the best lighting environment for a 60 min reading duration.Discussion: These suggestions can serve as a reference for designing indoor lighting environment. In addition, they provide guidance to researchers and reviewers conducting similar studies.

Administrative boundaries are ubiquitous. A vital technology of power within the modern nation-state’s mode of bureaucratic governance, they carve up and abstract land and water alike into conceptual totalities that, in their simplification, render them legible to centralised administrative bodies. This is a foundational tool of state planning, the impact of which permeates all aspects of socio-economic life. These boundaries are not passive; they do not simply define a geographical area. Rather, they are selective in what they encompass and, as a result, what they include and exclude and what is rendered visible and, hence, valuable. This article describes an example of the real-world impact of this selectivity through discussion of the experiences of a community-led charity (Ardagh Community Trust) and the community group that founded it (Friends of Horfield Common). In their work to demonstrate that an administrative-boundary-spanning public green space (Horfield Common) and leisure facility (the Ardagh) was a vital community resource and hub, this article focuses on the work of Friends of Horfield Common/Ardagh Community Trust to ensure that their local community, one dissected by multiple administrative boundaries, was recognised and acknowledged when, in 2008, Bristol City Council in the UK proposed the sale of multiple publicly owned green spaces through their Parks and Green Space Strategy. Administrative boundaries played a key role in defining and determining which sites in the city were proposed for sale and in structuring the accompanying public consultation process, thereby determining which communities were recognised as communities in relation to this policy and, hence, which communities’ opinions were actively sought and heard. This article concludes by highlighting some of the potential political and economic costs attendant on reifying administrative boundaries rather than lived communities in both planning and consultation processes.

Max Boettinger, David Klotz

In the realm of circuit motorsports, race strategy plays a pivotal role in determining race outcomes. This strategy focuses on the timing of pit stops, which are necessary due to fuel consumption and tire performance degradation. The objective of race strategy is to balance the advantages of pit stops, such as tire replacement and refueling, with the time loss incurred in the pit lane. Current race simulations, used to estimate the best possible race strategy, vary in granularity, modeling of probabilistic events, and require manual input for in-laps. This paper addresses these limitations by developing a novel simulation model tailored to GT racing and leveraging artificial intelligence to automate strategic decisions. By integrating the simulation with OpenAI's Gym framework, a reinforcement learning environment is created and an agent is trained. The study evaluates various hyperparameter configurations, observation spaces, and reward functions, drawing upon historical timing data from the 2020 Nürburgring Langstrecken Serie for empirical parameter validation. The results demonstrate the potential of reinforcement learning for improving race strategy decision-making, as the trained agent makes sensible decisions regarding pit stop timing and refueling amounts. Key parameters, such as learning rate, decay rate and the number of episodes, are identified as crucial factors, while the combination of fuel mass and current race position proves most effective for policy development. The paper contributes to the broader application of reinforcement learning in race simulations and unlocks the potential for race strategy optimization beyond FIA Formula~1, specifically in the GT racing domain.

Raphael Trumpp, Denis Hoornaert, Marco Caccamo

The development of vehicle controllers for autonomous racing is challenging because racing cars operate at their physical driving limit. Prompted by the demand for improved performance, autonomous racing research has seen the proliferation of machine learning-based controllers. While these approaches show competitive performance, their practical applicability is often limited. Residual policy learning promises to mitigate this drawback by combining classical controllers with learned residual controllers. The critical advantage of residual controllers is their high adaptability parallel to the classical controller's stable behavior. We propose a residual vehicle controller for autonomous racing cars that learns to amend a classical controller for the path-following of racing lines. In an extensive study, performance gains of our approach are evaluated for a simulated car of the F1TENTH autonomous racing series. The evaluation for twelve replicated real-world racetracks shows that the residual controller reduces lap times by an average of 4.55 % compared to a classical controller and even enables lap time gains on unknown racetracks.

Georg Jank, Matthias Rowold, Boris Lohmann

This paper presents a hierarchical planning algorithm for racing with multiple opponents. The two-stage approach consists of a high-level behavioral planning step and a low-level optimization step. By combining discrete and continuous planning methods, our algorithm encourages global time optimality without being limited by coarse discretization. In the behavioral planning step, the fastest behavior is determined with a low-resolution spatio-temporal visibility graph. Based on the selected behavior, we calculate maneuver envelopes that are subsequently applied as constraints in a time-optimal control problem. The performance of our method is comparable to a parallel approach that selects the fastest trajectory from multiple optimizations with different behavior classes. However, our algorithm can be executed on a single core. This significantly reduces computational requirements, especially when multiple opponents are involved. Therefore, the proposed method is an efficient and practical solution for real-time multi-vehicle racing scenarios.

Anna Paparcone

ABSTRACT This article considers the life and work of Afrodescendant Italian artists Iris Peynado, Nadia Kibout and Nadia Ali. Through my interviews with them and a critical analysis of their films, I underline the cultural value of their achievements and emphasize the discriminations that black women face in contemporary society and in the cinema industry. Racial, class and gender biases often are subjects of their filmmaking, and offer a critical site to reflect on the need for further social and political change. Their collective experience is seen in light of a transnational spatial and temporal continuity between black Italians and the diasporic communities around the world. A variety of nuanced cultural expressions makes it inaccurate to consider Italian Afrodescendant artists as a monolithic group of women having a single identity. In spite of societal biases, they are powerfully emerging as filmmakers, actresses, and activists. They contribute to our understanding that a true postcolonial approach requires a more fluid and flexible consideration of Italian identity as a transnational and multi-faceted expression of a fertile intersection of people of diverse genders, races, and religions.

Tomasz Krzyżowski

PLANS FOR THE CREATION OF A NEW CHURCH SLAVIC ARMENIAN CATHOLIC UNION IN POLAND IN THE 1930S In the second half of the 1930s, a group of Old Catholic and Orthodox priests and believers from Zamość Region and Volhynia tried to join the Catholic Church. Ignacy Jan Wysoczański (1901-1975) was the framer of this plan. A new church structure was to be under the jurisdiction of the Armenian archbishop of Lwów, Józef Teodorowicz (1864-1938), who accepted the idea with enthusiasm. Efforts undertaken to achieve the confirmation of the union in 1935 were negatively assessed by the Vatican Congregation for Eastern Churches, mainly due to formal questions, because – according to the canon law and the concordat signed with Poland – priests and believers expressing willingness to join the Catholic Church should be subordinate to the bishop of the place. It soon turned out that Ignacy Wysoczański was a controversial and unsteady person, which ultimately shattered the plan.

Johannes Betz, Hongrui Zheng, Alexander Liniger et al.

The rising popularity of self-driving cars has led to the emergence of a new research field in the recent years: Autonomous racing. Researchers are developing software and hardware for high performance race vehicles which aim to operate autonomously on the edge of the vehicles limits: High speeds, high accelerations, low reaction times, highly uncertain, dynamic and adversarial environments. This paper represents the first holistic survey that covers the research in the field of autonomous racing. We focus on the field of autonomous racecars only and display the algorithms, methods and approaches that are used in the fields of perception, planning and control as well as end-to-end learning. Further, with an increasing number of autonomous racing competitions, researchers now have access to a range of high performance platforms to test and evaluate their autonomy algorithms. This survey presents a comprehensive overview of the current autonomous racing platforms emphasizing both the software-hardware co-evolution to the current stage. Finally, based on additional discussion with leading researchers in the field we conclude with a summary of open research challenges that will guide future researchers in this field.

Shivansh Beohar, Fabian Heinrich, Rahul Kala et al.

Learn-to-Race Autonomous Racing Virtual Challenge hosted on www<dot>aicrowd<dot>com platform consisted of two tracks: Single and Multi Camera. Our UniTeam team was among the final winners in the Single Camera track. The agent is required to pass the previously unknown F1-style track in the minimum time with the least amount of off-road driving violations. In our approach, we used the U-Net architecture for road segmentation, variational autocoder for encoding a road binary mask, and a nearest-neighbor search strategy that selects the best action for a given state. Our agent achieved an average speed of 105 km/h on stage 1 (known track) and 73 km/h on stage 2 (unknown track) without any off-road driving violations. Here we present our solution and results.

Lauren E. Mullenbach, A. Mowen, B. L. Baker et al.

Abstract The ability of urban parks and public spaces to address distrust and social isolation needs to be rigorously tested, as the predominance of such claims may crowd out discussions of environmental racism and structural inequality. This study tested some commonly stated claims about parks’ influence on social well-being using a survey of residents in St. Louis, Missouri. We tested relationships between park and public space visitation frequency, positive and negative social contact with people of other races/ethnicities, and trust, using structural equation modeling. The model had strong fit but had few significant paths, indicating assertions are not fully supported by our data. Recommendations for urban park planners, managers, and community advocates include improving the design and planning process to accommodate diverse users, as well as modifying their discourse to reflect the growing need for social equity.

Ron Siegel

Sergio Coll-Pla, Josep Lluis Ginovart, Agustí Costa Jover et al.

El Valle de Arán se caracteriza por su aislamiento, de tal manera que hoy encontramos algunas construcciones románicas poco modificadas. La arquitectura románica pirenaica se caracteriza por el uso de las bóvedas que provocan grandes deformaciones en el resto de la iglesia. En este artículo se estudia la forma actual de las bóvedas mediante estudios topográficos para localizar el punto más deformado y estudiar la estabilidad de la sección transversal en ese punto. El primer estudio desarrollado en la bóveda es una topografía para encontrar el punto de bóveda más deformado. A partir de este punto se desplegará y estudiará una sección vertical a través de la línea de máxima presión. Los resultados concretarán el tipo de bóveda con que se construyeron las iglesias y nos permitirán conocer si estas son estables a la vez que reafirmaran la unidad formal y constructiva del primer románico.

Andreea Costea, Abhishek Tiwari, Sigmund Chianasta et al.

Implementing bug-free concurrent programs is a challenging task in modern software development. State-of-the-art static analyses find hundreds of concurrency bugs in production code, scaling to large codebases. Yet, fixing these bugs in constantly changing codebases represents a daunting effort for programmers, particularly because a fix in the concurrent code can introduce other bugs in a subtle way. In this work, we show how to harness compositional static analysis for concurrency bug detection, to enable a new Automated Program Repair (APR) technique for data races in large concurrent Java codebases. The key innovation of our work is an algorithm that translates procedure summaries inferred by the analysis tool for the purpose of bug reporting, into small local patches that fix concurrency bugs (without introducing new ones). This synergy makes it possible to extend the virtues of compositional static concurrency analysis to APR, making our approach effective (it can detect and fix many more bugs than existing tools for data race repair), scalable (it takes seconds to analyse and suggest fixes for sizeable codebases), and usable (generally, it does not require annotations from the users and can perform continuous automated repair). Our study conducted on popular open-source projects has confirmed that our tool automatically produces concurrency fixes similar to those proposed by the developers in the past.