4,196 research outputs found
Bridges Structural Health Monitoring and Deterioration Detection Synthesis of Knowledge and Technology
INE/AUTC 10.0
EVResponse - Moving Beyond Traditional Emergency Response Notification
Federal, state and local governmental agencies have been investing considerably in emergency response management systems to assist crisis management officers in the assessment, mitigation and response to emergency situations. In crisis management contexts, the timeliness of a response may be determined with reference to a fixed instant in the form of an absolute action threshold. This establishes the last possible point in time where any sort of solution is available. Once an action threshold is passed, a crisis is no longer containable; whatever adverse consequences a problem portends are thereafter inescapable. In this paper, we describe a special GIS-based response management system, EVResponse that combines GIS capabilities with web based voice translation technologies such as VoiceXML to effectively coordinate the pre, current and post crisis management activities. VoiceXML provides open standards based methodology to facilitate the integration and communication of emergency response systems with existing disaster planning systems. The EVResponse application uses web services to provide real-time reporting capabilities to both decision makers and first response units
Developing, Implementing and Evaluating Policies to Support Fisheries Co-management
The aim of this document is to bring together a number of the lessons relating to the development, implementation and evaluation of policies to support co-management that have emerged from projects undertaken through the DFID Fisheries Management Science Programme (FMSP) and elsewhere. It is beyond the scope of this document to provide a comprehensive analysis or guide. It seeks to highlight some experiences and some areas that need to be considered by policy makers when attempting to develop sustainably co-managed fisheries. This document is targeted to fisheries policy makers, and decision-makers concerned with the fisheries sector
Towards a Responsible AI Metrics Catalogue: A Collection of Metrics for AI Accountability
Artificial Intelligence (AI), particularly through the advent of large-scale
generative AI (GenAI) models such as Large Language Models (LLMs), has become a
transformative element in contemporary technology. While these models have
unlocked new possibilities, they simultaneously present significant challenges,
such as concerns over data privacy and the propensity to generate misleading or
fabricated content. Current frameworks for Responsible AI (RAI) often fall
short in providing the granular guidance necessary for tangible application,
especially for Accountability-a principle that is pivotal for ensuring
transparent and auditable decision-making, bolstering public trust, and meeting
increasing regulatory expectations. This study bridges the accountability gap
by introducing our effort towards a comprehensive metrics catalogue, formulated
through a systematic multivocal literature review (MLR) that integrates
findings from both academic and grey literature. Our catalogue delineates
process metrics that underpin procedural integrity, resource metrics that
provide necessary tools and frameworks, and product metrics that reflect the
outputs of AI systems. This tripartite framework is designed to operationalize
Accountability in AI, with a special emphasis on addressing the intricacies of
GenAI
Heterogeneous Anomaly Detection for Software Systems via Semi-supervised Cross-modal Attention
Prompt and accurate detection of system anomalies is essential to ensure the
reliability of software systems. Unlike manual efforts that exploit all
available run-time information, existing approaches usually leverage only a
single type of monitoring data (often logs or metrics) or fail to make
effective use of the joint information among different types of data.
Consequently, many false predictions occur. To better understand the
manifestations of system anomalies, we conduct a systematical study on a large
amount of heterogeneous data, i.e., logs and metrics. Our study demonstrates
that logs and metrics can manifest system anomalies collaboratively and
complementarily, and neither of them only is sufficient. Thus, integrating
heterogeneous data can help recover the complete picture of a system's health
status. In this context, we propose Hades, the first end-to-end semi-supervised
approach to effectively identify system anomalies based on heterogeneous data.
Our approach employs a hierarchical architecture to learn a global
representation of the system status by fusing log semantics and metric
patterns. It captures discriminative features and meaningful interactions from
heterogeneous data via a cross-modal attention module, trained in a
semi-supervised manner. We evaluate Hades extensively on large-scale simulated
data and datasets from Huawei Cloud. The experimental results present the
effectiveness of our model in detecting system anomalies. We also release the
code and the annotated dataset for replication and future research.Comment: In Proceedings of the 2023 IEEE/ACM 45th International Conference on
Software Engineering (ICSE). arXiv admin note: substantial text overlap with
arXiv:2207.0291
LifeLogging: personal big data
We have recently observed a convergence of technologies to foster the emergence of lifelogging as a mainstream activity. Computer storage has become significantly cheaper, and advancements in sensing technology allows for the efficient sensing of personal activities, locations and the environment. This is best seen in the growing popularity of the quantified self movement, in which life activities are tracked using wearable sensors in the hope of better understanding human performance in a variety of tasks. This review aims to provide a comprehensive summary of lifelogging, to cover its research history, current technologies, and applications. Thus far, most of the lifelogging research has focused predominantly on visual lifelogging in order to capture life details of life activities, hence we maintain this focus in this review. However, we also reflect on the challenges lifelogging poses to an information retrieval scientist. This review is a suitable reference for those seeking a information retrieval scientist’s perspective on lifelogging and the quantified self
Regional Data Archiving and Management for Northeast Illinois
This project studies the feasibility and implementation options for establishing a regional data archiving system to help monitor
and manage traffic operations and planning for the northeastern Illinois region. It aims to provide a clear guidance to the
regional transportation agencies, from both technical and business perspectives, about building such a comprehensive
transportation information system. Several implementation alternatives are identified and analyzed. This research is carried
out in three phases.
In the first phase, existing documents related to ITS deployments in the broader Chicago area are summarized, and a
thorough review is conducted of similar systems across the country. Various stakeholders are interviewed to collect
information on all data elements that they store, including the format, system, and granularity. Their perception of a data
archive system, such as potential benefits and costs, is also surveyed. In the second phase, a conceptual design of the
database is developed. This conceptual design includes system architecture, functional modules, user interfaces, and
examples of usage. In the last phase, the possible business models for the archive system to sustain itself are reviewed. We
estimate initial capital and recurring operational/maintenance costs for the system based on realistic information on the
hardware, software, labor, and resource requirements. We also identify possible revenue opportunities.
A few implementation options for the archive system are summarized in this report; namely:
1. System hosted by a partnering agency
2. System contracted to a university
3. System contracted to a national laboratory
4. System outsourced to a service provider
The costs, advantages and disadvantages for each of these recommended options are also provided.ICT-R27-22published or submitted for publicationis peer reviewe
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