Hasil untuk "Modern"

G. Fowles

S. Kuznets

A. Berle, G. Means

F. Mernissi

W. Brogan

H. F. Epstein, C. Diane

J. Grotendorst

P. W. Bridgman

J. Lebowitz, M. Lewis, P. Schuck

Ewen Smith, G. Dent

K. Rabe, C. Ahn, J. Triscone

Yuanzhe Deng, Shutong Zhang, Kathy Cheng et al.

Version control is critical in mechanical computer-aided design (CAD) to enable traceability, manage product variation, and support collaboration. Yet, its implementation in modern CAD software as an essential information infrastructure for product development remains plagued by issues due to the complexity and interdependence of design data. This paper presents a systematic review of user-reported challenges with version control in modern CAD tools. Analyzing 170 online forum threads, we identify recurring socio-technical issues that span the management, continuity, scope, and distribution of versions. Our findings inform a broader reflection on how version control should be designed and improved for CAD and motivate opportunities for tools and mechanisms that better support articulation work, facilitate cross-boundary collaboration, and operate with infrastructural reflexivity. This study offers actionable insights for CAD software providers and highlights opportunities for researchers to rethink version control.

Yiran Huang, Karsten Roth, Quentin Bouniot et al.

Transformer-based multimodal large language models often exhibit in-context learning (ICL) abilities. Motivated by this phenomenon, we ask: how do transformers learn to associate information across modalities from in-context examples? We investigate this question through controlled experiments on small transformers trained on synthetic classification tasks, enabling precise manipulation of data statistics and model architecture. We begin by revisiting core principles of unimodal ICL in modern transformers. While several prior findings replicate, we find that Rotary Position Embeddings (RoPE) increases the data complexity threshold for ICL. Extending to the multimodal setting reveals a fundamental learning asymmetry: when pretrained on high-diversity data from a primary modality, surprisingly low data complexity in the secondary modality suffices for multimodal ICL to emerge. Mechanistic analysis shows that both settings rely on an induction-style mechanism that copies labels from matching in-context exemplars; multimodal training refines and extends these circuits across modalities. Our findings provide a mechanistic foundation for understanding multimodal ICL in modern transformers and introduce a controlled testbed for future investigation.

C. Hu

K. S. Brown, C. Marean, A. Herries et al.

Karl Koscher, Alexei Czeskis, Franziska Roesner et al.

Modern automobiles are no longer mere mechanical devices; they are pervasively monitored and controlled by dozens of digital computers coordinated via internal vehicular networks. While this transformation has driven major advancements in efficiency and safety, it has also introduced a range of new potential risks. In this paper we experimentally evaluate these issues on a modern automobile and demonstrate the fragility of the underlying system structure. We demonstrate that an attacker who is able to infiltrate virtually any Electronic Control Unit (ECU) can leverage this ability to completely circumvent a broad array of safety-critical systems. Over a range of experiments, both in the lab and in road tests, we demonstrate the ability to adversarially control a wide range of automotive functions and completely ignore driver input\dash including disabling the brakes, selectively braking individual wheels on demand, stopping the engine, and so on. We find that it is possible to bypass rudimentary network security protections within the car, such as maliciously bridging between our car's two internal subnets. We also present composite attacks that leverage individual weaknesses, including an attack that embeds malicious code in a car's telematics unit and that will completely erase any evidence of its presence after a crash. Looking forward, we discuss the complex challenges in addressing these vulnerabilities while considering the existing automotive ecosystem.

Jincheng Wang, Le Yu, John C. S. Lui et al.

Distributed Denial of Service (DDoS) attacks persist as significant threats to online services and infrastructure, evolving rapidly in sophistication and eluding traditional detection mechanisms. This evolution demands a comprehensive examination of current trends in DDoS attacks and the efficacy of modern detection strategies. This paper offers an comprehensive survey of emerging DDoS attacks and detection strategies over the past decade. We delve into the diversification of attack targets, extending beyond conventional web services to include newer network protocols and systems, and the adoption of advanced adversarial tactics. Additionally, we review current detection techniques, highlighting essential features that modern systems must integrate to effectively neutralize these evolving threats. Given the technological demands of contemporary network systems, such as high-volume and in-line packet processing capabilities, we also explore how innovative hardware technologies like programmable switches can significantly enhance the development and deployment of robust DDoS detection systems. We conclude by identifying open problems and proposing future directions for DDoS research. In particular, our survey sheds light on the investigation of DDoS attack surfaces for emerging systems, protocols, and adversarial strategies. Moreover, we outlines critical open questions in the development of effective detection systems, e.g., the creation of defense mechanisms independent of control planes.

Volodymyr Shlapak, Andriy Kryvoruchko, Andrii Panasiuk et al.

The article examines the problem of improving productivity at crushed stone quarries through optimization of motor transport and loading equipment. The limitations of the existing fleet of dump trucks and loading machines, as well as the geometric parameters of transport trenches that prevent the use of traditional heavy-duty two-axle dump trucks, are analyzed. The feasibility of using modern three-axle dump trucks with optimized overall dimensions in combination with appropriate loading equipment is substantiated, which ensures an increase in body volume with a smaller vehicle width and a rational ratio of excavator and dump truck parameters. It is proven that the implementation of a coordinated transport-loading complex allows for organizing efficient two-way traffic in trenches of limited width and increases the overall productivity of mining operations by 25–30 %. The research results can be used in modernizing transport systems of existing quarries and designing new mining enterprises.

Yunlang Guo, Bo Wang, Xiangdong Li et al.

Eclipsing millisecond pulsars (MSPs) are a type of pulsar binaries with close orbits (≲1.0 day). They are important objects for studying the accretion history of neutron stars (NSs), pulsar winds, and the origin of isolated MSPs, etc. Recently, a new eclipsing MSP, PSR J1928+1815, was discovered by the Five-hundred-meter Aperture Spherical radio Telescope. It is the first known pulsar with a He star companion, as suggested in Yang et al. The system features a short orbital period of ∼0.15 days and a relatively massive companion ≳1.0 M _⊙ . However, the origin of PSR J1928+1815 remains highly uncertain. In this paper, we investigated the formation of the new subclass of eclipsing MSPs containing (evolved) He star companions through the NS + He star channel. We found that if an NS binary undergoes subsequent mass-transfer phases following Case BA or Case BB, it may appear as an eclipsing MSP during the detached phase. Additionally, we obtained the initial parameter space for producing eclipsing MSPs with He star companions. Using the binary population synthesis approach, we estimated their birth rate to be ∼2.1–4.7 × 10 ^−4 yr ^−1 , corresponding to a total number of ∼220 systems in the Galaxy. Moreover, we concluded that PSR J1928+1815 may originate from the evolution of an NS + He star system with an initial orbital period of ∼0.1 days, which can undergo the Case BB mass transfer.

Aditya Kapoor, Rishi Sethi, Rakesh Yadav

The challenges and rigors of the modern-day health care systems demand a critical reappraisal of our training paradigms in cardiology. Today, modern day DM and DNB Cardiology training needs to seamlessly amalgamate traditional teaching methodologies with the rapidly evolving technology based educational tools now available to us for personalized and adaptive learning. The contemporary cardiology curricula need to incorporate ALL components of clinical competency including cognitive, psychomotor and affective skills to enable the next generation of cardiologists to provide truly holistic care to their patients. In addition, a greater focus on impactful cardiology research with an intent to publish it while in training, is likely to encourage at least some of the young trainees to pursue careers in academia. Most importantly, the exit examination patterns need to be restructured. We need to decide whether we need cardiologists who simply follow textbooks and are trained in procedures —or we need those who have the ability to themselves write the next chapters in cardiology, have the precision of thought, the depth of empathy, and the courage to question.