Search results for "computer.software_genre"

Low-cost approximate reconstructing of heterogeneous microstructures

2016

We propose an approximate reconstruction of random heterogeneous microstructures using the two-exponent power-law (TEPL). This rule originates from the entropic descriptor (ED) that is a multi-scale measure of spatial inhomogeneity for a given microstructure. A digitized target sample is a cube of linear size L in voxels. Then, a number of trial configurations can be generated by a model of overlapping spheres of a fixed radius, which are randomly distributed on a regular lattice. The TEPL describes the averaged maximum of the ED as a function of the phase concentration and the radius. Thus, it can be used to determine the radius. The suggested approach is tested on surrogate samples of cer…

Extending formal language hierarchies to higher dimensions

1999

Adapted Transfer of Distance Measures for Quantitative Structure-Activity Relationships and Data-Driven Selection of Source Datasets

2012

Quantitative structure–activity relationships are regression models relating chemical structure to biological activity. Such models allow to make predictions for toxicologically relevant endpoints, which constitute the target outcomes of experiments. The task is often tackled by instance-based methods, which are all based on the notion of chemical (dis-)similarity. Our starting point is the observation by Raymond and Willett that the two families of chemical distance measures, fingerprint-based and maximum common subgraph-based measures, provide orthogonal information about chemical similarity. This paper presents a novel method for finding suitable combinations of them, called adapted tran…

Managing information security risks during new technology adoption

2012

Author's version of an article in the journal: Computers and Security. Also available from the publisher at: http://dx.doi.org/10.1016/j.cose.2012.09.001 In the present study, we draw on previous system dynamics research on operational transition and change of vulnerability to investigate the role of incident response capability in controlling the severity of incidents during the adoption of new technology. Toward this end, we build a system dynamics model using the Norwegian Oil and Gas Industry as the context. The Norwegian Oil and Gas Industry has started to adopt new information communication technology to connect its offshore platforms, onshore control centers, and suppliers. In oil co…

Safeguarding the Ultra-dense Networks with the aid of Physical Layer Security: A review and a case study

2016

In the wake of the extensive application of the fourth generation system, investigations of new technologies have been moving ahead vigorously to embrace the next generation communications in 2020. Thereinto, the technique of ultra-dense networks (UDNs) serves as a key enabler in meeting the roaring mobile traffic demands. With the prevalence of mobile Internet services especially those involve the mobile payment, security has gained an unprecedented amount of attention and become a highlighted feature for the fifth generation. Resource allocation, one of the most significant tools on getting over the obstacle of ubiquitous interference as well as elevating the spectrum/energy efficiency, h…

A Widrow–Hoff Learning Rule for a Generalization of the Linear Auto-associator

1996

Abstract A generalization of the linear auto-associator that allows for differential importance and nonindependence of both the stimuli and the units has been described previously by Abdi (1988). This model was shown to implement the general linear model of multivariate statistics. In this note, a proof is given that the Widrow–Hoff learning rule can be similarly generalized and that the weight matrix will converge to a generalized pseudo-inverse when the learning parameter is properly chosen. The value of the learning parameter is shown to be dependent only upon the (generalized) eigenvalues of the weight matrix and not upon the eigenvectors themselves. This proof provides a unified framew…

IMPROVEMENTS IN THE SYSTEMS-BASED MODELS GENERATOR SIGEM

1994

Program generators, for us, are computer programs that produce other computer programs. SIGEM is an expert system program generator that can help in the modeling process of real systems. It is associated with a methodology well adapted to modeling practice. In this paper, we present and compare this methodology with other similar ones. Static models (databases), dynamic models, rule-based expert systems, literal and/or numerical variables, probabilistic uncertainty in data and in functions, dimensioned variables, discrete event simulation, and other related problems can be treated with this methodology. We suggest a systems modeling methodology and a programming tool to increase generality …

2014

This paper investigates the proficiency of support vector machine (SVM) using datasets generated by Tennessee Eastman process simulation for fault detection. Due to its excellent performance in generalization, the classification performance of SVM is satisfactory. SVM algorithm combined with kernel function has the nonlinear attribute and can better handle the case where samples and attributes are massive. In addition, with forehand optimizing the parameters using the cross-validation technique, SVM can produce high accuracy in fault detection. Therefore, there is no need to deal with original data or refer to other algorithms, making the classification problem simple to handle. In order to…

Interpretable Option Discovery Using Deep Q-Learning and Variational Autoencoders

2021

Deep Reinforcement Learning (RL) is unquestionably a robust framework to train autonomous agents in a wide variety of disciplines. However, traditional deep and shallow model-free RL algorithms suffer from low sample efficiency and inadequate generalization for sparse state spaces. The options framework with temporal abstractions [18] is perhaps the most promising method to solve these problems, but it still has noticeable shortcomings. It only guarantees local convergence, and it is challenging to automate initiation and termination conditions, which in practice are commonly hand-crafted.

2020

Piping erosion is one form of water erosion that leads to significant changes in the landscape and environmental degradation. In the present study, we evaluated piping erosion modeling in the Zarandieh watershed of Markazi province in Iran based on random forest (RF), support vector machine (SVM), and Bayesian generalized linear models (Bayesian GLM) machine learning algorithms. For this goal, due to the importance of various geo-environmental and soil properties in the evolution and creation of piping erosion, 18 variables were considered for modeling the piping erosion susceptibility in the Zarandieh watershed. A total of 152 points of piping erosion were recognized in the study area that…