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Tuning the legacy survey of space and time observing strategy for solar system science: incremental templates in Year 1
No full textThe Vera C. Rubin Observatory is due to commence the 10 yr Legacy Survey of Space and Time (LSST) at the end of 2025. To detect transient/variable sources and identify solar system objects (SSOs), the processing pipelines require templates of the static sky to perform difference imaging. During the first year of the LSST, templates must be generated as the survey progresses; otherwise, SSOs cannot be discovered nightly. The incremental template generation strategy has not been finalized; therefore, we use the Metric Analysis Framework (MAF) and a simulation of the survey cadence (one_snap_v4.0_10yrs) to explore template generation in Year 1. We have assessed the effects of generating templates over timescales of days–weeks, when at least four images of sufficient quality are available for ≥90% of the visit. We predict that SSO discoveries will begin ∼2–3 months after the start of the survey. We find that the ability of the LSST to discover SSOs in real time is reduced in Year 1. This is especially true for detections in areas of the sky that receive fewer visits, such as the North Ecliptic Spur (NES), and in less commonly used filters, such as the u and g bands. The lack of templates in the NES dominates the loss of real-time SSO discoveries; across the whole sky the MAF main-belt asteroid (MBA) discovery metric decreases by up to 63% compared to the baseline observing strategy, whereas the metric decreases by up to 79% for MBAs in the NES alone
Toward efficient asynchronous single-source shortest path
No full textSingle-Source Shortest Path (SSSP) is a fundamental graph problem that arises in various applications and complex problems. State-of-the-art solutions to the parallel SSSP problem create parallelism through priority coarsening, which results in redundant work and reduces the efficiency of the solution. This paper introduces Wasp, a novel solution for SSSP that addresses the parallelism-redundant work problem using an asynchronous work-stealing scheduler. The experimental evaluation of Wasp on SSSP shows that it provides competitive or better performance than GAP, GBBS, and the MultiQueue on 13 diverse graphs, including road networks, scale-free and random graphs, with speedups up to 2.94× higher than the state of the art
Joint intelligence distribution and fine-tuning for multi-agent intelligence manufacturing
No full textThe intelligent manufacturing environment imposes extremely high requirements on real-time performance and accuracy. However, due to the dual constraints of communication and computing resources, meeting these requirements poses significant challenges. In this paper, we investigate how to achieve joint optimization of intelligence distribution and fine-tuning in the process of acquiring and applying intelligent models by agents. The framework efficiently provides intelligent models to the agents at a low cost while optimizing the intelligent models to ensure the overall performance of the system. Firstly, to achieve ubiquitous collaboration across computing resources driven by network awareness, we propose a multi-agent intelligent manufacturing architecture based on Computing Power Network (CPN). Secondly, to balance computing and communication resources and enhance model accuracy performance, we formulate a hierarchical optimization framework based on a dual spatial scale approach, combining intelligence distribution and fine-tuning. We further design a joint optimization algorithm based on the Differential Evolutionary (DE) framework and a synergy between Coalition Game Theory (CGT) and Federated Learning (FL) to effectively solve this problem. Finally, extensive simulation experiments validate the effectiveness and superiority of the proposed solution
Blockchain-based approach to improve environmental, social, and governance (ESG) reporting in construction organizations
No full textExisting ESG reporting tools in construction organizations often lack transparency and accountability, presenting significant challenges in effectively managing and reporting ESG data. This research addresses the gap in current reporting practices by proposing and validating a hybrid blockchain solution aimed at enhancing ESG reporting in the Architecture, Engineering, and Construction (AEC) industry. The primary objective is to develop a blockchain-based solution that automates ESG reporting, addressing issues such as data fragmentation, lack of verification, and inefficiencies. Adopting a design science approach, the study develops a conceptual framework that combines Ethereum and Hyperledger Fabric to create a hybrid blockchain model for the prototype. The comprehensive literature review highlights key challenges in ESG practices and emphasizes the potential of blockchain technology to overcome these barriers. The findings show that the hybrid blockchain model successfully automates the ESG reporting process, ensuring transparency, immutability, and accountability. The prototype, validated through a case study involving two construction organizations, demonstrates the feasibility of combining Ethereum and Hyperledger Fabric to manage ESG data, reducing errors, preventing manipulation, and enabling real-time reporting. This research enriches the theoretical understanding of blockchain applications in ESG practices. It provides practical implications by offering a tangible, blockchain-based solution that ensures transparent, reliable, and accountable ESG reporting in the construction industry, ultimately contributing to more sustainable practices
The Oxford handbook of Irish song, from the earliest beginnings to 1850
No full textThe Oxford History of Irish Song explores song in Ireland from early times to the modern period across all traditions. From descriptions of song in the Old Irish period to an exploration of the music of keening, the volume breaks new ground in Irish musical and cultural studies. Thirty-nine chapters explore the rich diversity of singing traditions in Ireland, including sacred and ceremonial song, traditional singing in Irish and anglophone ballads, songs of love and of political activism, and examine how songs circulated in print, manuscript and oral forms. Turlough Carolan (Toirdhealbhach Ó Cearbhalláin) and Thomas Moore feature as identifiable and famous song-composers, in addition to eighteenth-century Gaelic poets and song-writers such as Seán Clárach Mac Domhnaill, Eoghan Rua Ó Súilleabháin and Máire Bhuí Ní Laeire. Notable collectors of Irish song also form an important strand: from Bunting’s coterie of scribes to the work of Petrie and Goodman. Equally important, however, are the anonymous singers who transmitted diverse traditions of song through families and communities. This authoritative overview provides a platform for researchers across multiple disciplines to access knowledge about Irish song traditions as well as setting the scene for new research directions on the performance, social contexts, historical significance, and modern adaptations of Irish song
