This monograph presents a comprehensive treatment of the maximum-entropy sampling problem (MESP), which is a fascinating topic at the intersection of mathematical optimization and data science. The text situates ...
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ISBN:
(数字)9783031130786
ISBN:
(纸本)9783031130779;9783031130809
This monograph presents a comprehensive treatment of the maximum-entropy sampling problem (MESP), which is a fascinating topic at the intersection of mathematical optimization and data science. The text situates MESP in information theory, as the algorithmic problem of calculating a sub-vector of pre-specificed size from a multivariate Gaussian random vector, so as to maximize Shannon's differential entropy. The text collects and expands on state-of-the-art algorithms for MESP, and addresses its application in the field of environmental monitoring. While MESP is a central optimization problem in the theory of statistical designs (particularly in the area of spatial monitoring), this book largely focuses on the unique challenges of its algorithmic side. From the perspective of mathematical-optimization methodology, MESP is rather unique (a 0/1 nonlinear program having a nonseparable objective function), and the algorithmic techniques employed are highly non-standard. In particular, successful techniques come from several disparate areas within the field of mathematical optimization; for example: convex optimization and duality, semidefinite programming, Lagrangian relaxation, dynamic programming, approximation algorithms, 0/1 optimization (e.g., branch-and-bound), extended formulation, and many aspects of matrix theory. The book is mainly aimed at graduate students and researchers in mathematical optimization and data analytics.
The technical literature regarding model-based testing (MBT) has several techniques with different characteristics and goals available to be applied in software projects. Besides the lack of information regarding thes...
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The technical literature regarding model-based testing (MBT) has several techniques with different characteristics and goals available to be applied in software projects. Besides the lack of information regarding these techniques, they could be applied together in a software project aiming at improving the testing coverage. However, this decision needs to be carefully analyzed to avoid loss of resources in a software project. Based on this scenario, this paper proposes an approach with the purpose of supporting the unique or combined selection of MBT techniques for a given software project considering two aspects: the adequacy level between MBT techniques and the software project characteristics and impact of more than one MBT technique in some testing process variables. At the end, preliminary results of an experimental evaluation are presented.
BPMN 2.0 is a widely used notation to model business process that has associated tools and techniques to facilitate process management, execution and monitoring. As a result using BPMN to model Software Development Pr...
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BPMN 2.0 is a widely used notation to model business process that has associated tools and techniques to facilitate process management, execution and monitoring. As a result using BPMN to model Software Development Process (SDP) can leverage on the BPMN's infrastructure to improve SDP quality. Nevertheless, when using BPMN to model Software Processes one can observe the lack of an important feature: means to represent process tailoring. This article introduces the BPMNt, a conservative extension to BPMN that aims at aggregating a tailoring representation mechanism as the one found at SPEM 2.0. BPMNt uses the extensibility classes already present in the BPMN meta-model. Our work also presents an example to illustrate the approach.
In this paper we use execution-driven simulation of a scalable multiprocessor to evaluate the performance of the Andorra-I parallel logic programming system under invalidate and update-based protocols. We use two vers...
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A system for automatic detection of road damages is essential for logistics management. At the core of the system lies an algorithm for classification of damages. This work intends to establish such an algorithm. In t...
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Software quality assurance is a crucial process that ensures software products meet specified requirements and quality standards. Achieving an exhaustive test coverage is essential for quality assurance, particularly ...
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We present two new versions of the fuzzy Markov predictor (FMP) with different dependences among the inputs: first-order and second-order dependences. The FMP is a modification of the hidden Markov model in order to e...
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We present two new versions of the fuzzy Markov predictor (FMP) with different dependences among the inputs: first-order and second-order dependences. The FMP is a modification of the hidden Markov model in order to enable it to predict numerical values. The FMP can be seen as an extension of the fuzzy Bayes predictor. These hybrid systems are applied to the task of monthly electric load forecasting and successfully compared with one fuzzy system, and two traditional forecasting methods: Box-Jenkins and Winters exponential smoothing.
The purpose of this initiative is to ensure that citizens use social media to access information about the state of the city. Social media application offers benefits in the form of a channel of communication between ...
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