Search results for " logic"
showing 10 items of 1720 documents
Managing Continuous Digital Service Innovation for Value Co-Creation
2023
Service organizations across various industries are increasingly implementing continuous development methods and practices to transform their digital service innovation and development processes. Consequently, continuous digital service innovation (DSI) has become a way to react to today’s dynamic markets by proposing value to customers quickly while maintaining service quality. However, little is known about how organizations can enable value co-creation (VCC) in their continuous DSI processes. We fill this gap in the literature by focusing on organizational-level continuous DSI processes. Based on findings from 23 industry informants from six Finnish digital service organizations, we pres…
Institutional Logics and the Internationalization of a State-Owned Enterprise : Evaluation of International Venture Opportunities by Telecom Finland …
2020
We contribute to the research on internationalization of state-owned enterprises (SOEs) by studying the coevolution of state governance of SOEs and SOEs’ evaluation of international venture opportunities during a shift in dominant institutional logic from state to market logic. Using a novel digital historical method to study Telecom Finland, we argue that as state governance mechanisms change due to a logic shift, rationales underlying SOEs’ internationalization can significantly change and impact SOEs’ geographical and partner preferences. However, a logic shift also affords SOEs significant influence over the formation of new state governance policies under the new dominant logic. peerRe…
The Relational Syllogistic Revisited
2013
The relational syllogistic is an extension of the language of Classical syllogisms in which predicates are allowed to feature transitive verbs with quantified objects. It is known that the relational syllogistic does not admit a finite set of syllogism-like rules whose associated (direct) derivation relation is sound and complete. We present a modest ex- tension of this language which does.
Hysteretic Systems Subjected to Delta Correlated Input
1994
The paper deals with the evaluation of the probabilistic response of a single degree of freedom elastic-perfectly plastic system subjected to a delta correlated input process. The probabilistic characterisation of the response is here obtained by considering the accumulated plastic deformations as a compound homogeneous Poisson process independent of the external input. In this case the former can be considered as an external noise acting on the linear system. A closed form solution is also obtained and the analytic expression is compared with the customary Monte-Carlo method.
A Self-Contained Biometric Sensor for Ubiquitous Authentication
2007
This paper describes a real-life behavior framework in simulation game based on Probabilistic State Machine (PSM) with Gaussian random distribution. According to the dynamic environment information, NPC can generate behavior planning autonomously associated with defined FSM. After planning process, we illuminate Gaussian probabilistic function for real-life action simulation in time and spatial domains. The expected value of distribution is estimated during behavior planning process and variance is determined by NPC personality in order to realize real life behavior simulation. We experiment the framework and Gaussian PSM on a restaurant simulation game. Furthermore we give some suggestions…
Non-Stationary Probabilistic Response of Linear Systems Under Non-Gaussian Input
1991
The probabilistic characterization of the response of linear systems subjected to non-normal input requires the evaluation of higher order moments than two. In order to obtain the equations governing these moments, in this paper the extension of the Ito’s differential rule for linear systems excited by non-normal delta correlated processes is presented. As an application the case of the delta correlated compound Poisson input process is treated.
Sensitivity analysis of Gaussian processes for oceanic chlorophyll prediction
2015
Gaussian Process Regression (GPR) for machine learning has lately been successfully introduced for chlorophyll content mapping from remotely sensed data. The method provides a fast, stable and accurate prediction of biophysical parameters. However, since GPR is a non-linear kernel regression method, the relevance of the features are not accessible. In this paper, we introduce a probabilistic approach for feature sensitivity analysis (SA) of the GPR in order to reveal the relative importance of the features (bands) being used in the regression process. We evaluated the SA on GPR ocean chlorophyll content prediction. The method revealed the importance of the spectral bands, thus allowing the …
Stochastic Response on Non-Linear Systems under Parametric Non-Gaussian Agencies
1992
The probabilistic response characterization of non-linear systems subjected to non-normal delta correlated parametric excitation is obtained. In order to do this an extension of both Ito’s differential rule and the Fokker-Planck equation is presented, enabling one to account for the effect of the non-normal input. The validity of the approach reported here is confirmed by results obtained by means of a Monte Carlo simulation.
Liftings and extensions of operators in Brownian setting
2020
We investigate the operators T on a Hilbert space H which have 2-isometric liftings S with the property S ∗ S H ⊂ H . We show that such liftings are closely related to some extensions of T, which h...