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Telesca, Luciano; Cuomo, V.; Lapenna, Vincenzo; Macchiato, M.

doi:10.1023/a:1014275509447

Cited by 26 publications

(6 citation statements)

References 31 publications

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“…A number of scholars prefer the Minkowski-Bouligand or box-counting dimension over alternatives such as the areaperimeter or power spectrum methods for estimating the fractal dimension of natural phenomena as diverse as seismic activity, electrical activity in the brain, and physical surface features at the nanometer scale [42], [39], [43]. Longo and Montévil argue that while it lacks some of the mathematical import found in other definitions of fractal dimension such as the Hausdorff dimension, the boxcounting dimension has an advantage in that it can easily be applied to empirically observed phenomena [37].…”

Section: A Advantages Of the Box-counting Methodsmentioning

confidence: 99%

“…Graphing a time-series in two-dimensional space is useful for natural phenomena such as earthquakes that occur at different times with different intensities [42]. However, in the case of developing a temporal measure for quantifying the work effort of human and artificial managers, we suggest that a different approach is warranted.…”

Section: B Work Effort As a Time Series Of Binary Valuesmentioning

confidence: 99%

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A Fractal Measure for Comparing the Work Effort of Human and Artificial Agents Performing Management Functions

Gladden

2014

Annals of Computer Science and Information Systems

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Abstract-Thanks to the growing sophistication of artificial agent technologies, businesses will increasingly face decisions of whether to have a human employee or artificial agent perform a particular function. This makes it desirable to have a common temporal measure for comparing the work effort that human beings and artificial agents can apply to a role. Existing temporal measures of work effort are formulated to apply either to human employees (e.g., FTE and billable hours) or computer-based systems (e.g., mean time to failure and availability) but not both. In this paper we propose a new temporal measure of work effort based on fractal dimension that applies equally to the work of human beings and artificial agents performing management functions. We then consider four potential cases to demonstrate the measure's diagnostic value in assessing strengths (e.g., flexibility) and risks (e.g., switch costs) reflected by the temporal work dynamics of particular managers. I. THE NEED FOR A COMMON TEMPORAL MEASURE OF WORK EFFORTHE increasing power and sophistication of artificial agent technology is allowing businesses to employ artificial agents in a growing number of roles. Artificial agents are no longer restricted simply to performing logistical functions such as resource scheduling, but are now capable of more complex interpersonal workplace behavior such as using social intelligence to effectively manage the limitations, abilities, and expectations of human employees [1], recognizing and manifesting culture-specific behaviors in interactions with human colleagues [2], and assessing the performance of human members of virtual teams [3]. It is thus gradually becoming more feasible to design artificial agents capable of performing the four key functions carried out by human managers, which are planning, organizing, leading, and controlling [4]. TAs a result of such recent and anticipated future advances, businesses will increasingly be faced with concrete decisions about whether, for example, the manager of a new corporate call center should be an experienced human manager or the latest artificial agent system. Such decisions will be shaped by a large number of strategic, financial, technological, political, legal, ethical, and operational factors. One particular element to be taken into account is that of temporal work effort: i.e., how much time would a human manager actually be able to dedicate to carrying out the necessary work functions, given the fact that physiological, cultural, legal, and ethical constraints limit the number of hours per week that a human being is capable of working? Similarly, how much time would an artificial agent be able to dedicate to carrying out the necessary work functions, given the fact that scheduled maintenance or unscheduled outages can limit the uptime of computer-based systems? Knowing how much time per day (or week, or other relevant time interval) a manager will be available to carry out his or her functions of planning, organizing, leading, and controlling becomes espe...

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Section: A Advantages Of the Box-counting Methodsmentioning

confidence: 99%

Section: B Work Effort As a Time Series Of Binary Valuesmentioning

confidence: 99%

A Fractal Measure for Comparing the Work Effort of Human and Artificial Agents Performing Management Functions

Gladden

2014

Annals of Computer Science and Information Systems

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“…So that the seismicity can be described as a classical example of complex time series or self-affine processes where the magnitude or interevent times are the variables. The earthquakes catalogues have been investigated analyzing their fractal/multifractal features within space and time domain [4][5][6][7][8][9], however, not many works have been focused in the fractality features associated with the magnitude variability of the earthquakes, a few examples are in [10,11,12].…”

Section: Introductionmentioning

confidence: 99%

Multifractal features of the seismicity in Tehuantepec Isthmus, southern México

Rojas

Márquez²

2022

J. Phys.: Conf. Ser.

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On September 07, 2017 occurred an earthquake of M8.2 whose epicenter was located at Tehuantepec Isthmus, México. According with the seismicity monitored, spatial and temporal changes were observed after the earthquake in comparison with the historical seismic activity in the zone. Concerning with the temporal changes, the rate of earthquakes occurrence increased and, regarding with the spatial distribution, the epicenters displayed a clear clusterization located between the so-named Tehuantepec Transform/Ridge and the Middle America Trench off Chiapas which is recognized as a tectonic collision region. Based on the observed dynamical behavior of the seismic activity in the Tehuantepec Isthmus subduction zone, in this paper we analyze the magnitude catalogue from 2010 to 2020. The aim is to characterize by applying the multifractal detrended fluctuation analysis three periods of activity, the regular seismicity previous to the main shock, the aftershocks and the post aftershock activity. Our findings suggest that each period is characterized by their own multifractality.

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“…α ∼ 0, indicating a sort of equiprobability of occurrence of all the involved time scales. On the other hand, positive α is typical of those processes characterized by long-range correlations [8]. The more correlated the process, the higher the value of α [12].…”

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confidence: 98%

“…Second-order power law statistics are generally performed to investigate the temporal properties of earthquakes, in order to identify their correlation structures [7]. Several techniques could be used, but all are related with the power spectrum [8,9]. In particular scaling behavior is revealed by a spectrum that decays as a power law function of the frequency f , i.e.…”

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confidence: 99%