73,026 research outputs found
The Responsibility Quantification (ResQu) Model of Human Interaction with Automation
Intelligent systems and advanced automation are involved in information
collection and evaluation, in decision-making and in the implementation of
chosen actions. In such systems, human responsibility becomes equivocal.
Understanding human casual responsibility is particularly important when
intelligent autonomous systems can harm people, as with autonomous vehicles or,
most notably, with autonomous weapon systems (AWS). Using Information Theory,
we develop a responsibility quantification (ResQu) model of human involvement
in intelligent automated systems and demonstrate its applications on decisions
regarding AWS. The analysis reveals that human comparative responsibility to
outcomes is often low, even when major functions are allocated to the human.
Thus, broadly stated policies of keeping humans in the loop and having
meaningful human control are misleading and cannot truly direct decisions on
how to involve humans in intelligent systems and advanced automation. The
current model is an initial step in the complex goal to create a comprehensive
responsibility model, that will enable quantification of human causal
responsibility. It assumes stationarity, full knowledge regarding the
characteristic of the human and automation and ignores temporal aspects.
Despite these limitations, it can aid in the analysis of systems designs
alternatives and policy decisions regarding human responsibility in intelligent
systems and advanced automation
Automation in organizations: Eternal conflict
Some ideas on and insights into the problems associated with automation in organizations are presented with emphasis on the concept of automation, its relationship to the individual, and its impact on system performance. An analogy is drawn, based on an American folk hero, to emphasize the extent of the problems encountered when dealing with automation within an organization. A model is proposed to focus attention on a set of appropriate dimensions. The function allocation process becomes a prominent aspect of the model. The current state of automation research is mentioned in relation to the ideas introduced. Proposed directions for an improved understanding of automation's effect on the individual's efficiency are discussed. The importance of understanding the individual's perception of the system in terms of the degree of automation is highlighted
Automation of surface observations program
At present, surface weather observing methods are still largely manual and labor intensive. Through the nationwide implementation of Automated Surface Observing Systems (ASOS), this situation can be improved. Two ASOS capability levels are planned. The first is a basic-level system which will automatically observe the weather parameters essential for aviation operations and will operate either with or without supplemental contributions by an observer. The second is a more fully automated, stand-alone system which will observe and report the full range of weather parameters and will operate primarily in the unattended mode. Approximately 250 systems are planned by the end of the decade. When deployed, these systems will generate the standard hourly and special long-line transmitted weather observations, as well as provide continuous weather information direct to airport users. Specific ASOS configurations will vary depending upon whether the operation is unattended, minimally attended, or fully attended. The major functions of ASOS are data collection, data processing, product distribution, and system control. The program phases of development, demonstration, production system acquisition, and operational implementation are described
Track 3: Computations in theoretical physics -- techniques and methods
Here, we attempt to summarize the activities of Track 3 of the 17th
International Workshop on Advanced Computing and Analysis Techniques in Physics
Research (ACAT 2016).Comment: 10 pages, 3 figures, to appear in the proceedings of ACAT 201
Statistical Delay Bound for WirelessHART Networks
In this paper we provide a performance analysis framework for wireless
industrial networks by deriving a service curve and a bound on the delay
violation probability. For this purpose we use the (min,x) stochastic network
calculus as well as a recently presented recursive formula for an end-to-end
delay bound of wireless heterogeneous networks. The derived results are mapped
to WirelessHART networks used in process automation and were validated via
simulations. In addition to WirelessHART, our results can be applied to any
wireless network whose physical layer conforms the IEEE 802.15.4 standard,
while its MAC protocol incorporates TDMA and channel hopping, like e.g.
ISA100.11a or TSCH-based networks. The provided delay analysis is especially
useful during the network design phase, offering further research potential
towards optimal routing and power management in QoS-constrained wireless
industrial networks.Comment: Accepted at PE-WASUN 201
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