256 research outputs found

    Some complexity and approximation results for coupled-tasks scheduling problem according to topology

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    We consider the makespan minimization coupled-tasks problem in presence of compatibility constraints with a specified topology. In particular, we focus on stretched coupled-tasks, i.e. coupled-tasks having the same sub-tasks execution time and idle time duration. We study several problems in framework of classic complexity and approximation for which the compatibility graph is bipartite (star, chain,. . .). In such a context, we design some efficient polynomial-time approximation algorithms for an intractable scheduling problem according to some parameters

    A Novel Black Box Process Quality Optimization Approach based on Hit Rate

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    Hit rate is a key performance metric in predicting process product quality in integrated industrial processes. It represents the percentage of products accepted by downstream processes within a controlled range of quality. However, optimizing hit rate is a non-convex and challenging problem. To address this issue, we propose a data-driven quasi-convex approach that combines factorial hidden Markov models, multitask elastic net, and quasi-convex optimization. Our approach converts the original non-convex problem into a set of convex feasible problems, achieving an optimal hit rate. We verify the convex optimization property and quasi-convex frontier through Monte Carlo simulations and real-world experiments in steel production. Results demonstrate that our approach outperforms classical models, improving hit rates by at least 41.11% and 31.01% on two real datasets. Furthermore, the quasi-convex frontier provides a reference explanation and visualization for the deterioration of solutions obtained by conventional models

    Approximation algorithms for coupled task scheduling minimizing the sum of completion times

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    In this paper we consider the coupled task scheduling problem with exact delay times on a single machine with the objective of minimizing the total completion time of the jobs. We provide constant-factor approximation algorithms for several variants of this problem that are known to be \mathcal{N}\mathcal{P} N P -hard, while also proving \mathcal{N}\mathcal{P} N P -hardness for two variants whose complexity was unknown before. Using these results, together with constant-factor approximations for the makespan objective from the literature, we also introduce the first results on bi-objective approximation in the coupled task setting

    Fundamental Approaches to Software Engineering

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    This open access book constitutes the proceedings of the 23rd International Conference on Fundamental Approaches to Software Engineering, FASE 2020, which took place in Dublin, Ireland, in April 2020, and was held as Part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2020. The 23 full papers, 1 tool paper and 6 testing competition papers presented in this volume were carefully reviewed and selected from 81 submissions. The papers cover topics such as requirements engineering, software architectures, specification, software quality, validation, verification of functional and non-functional properties, model-driven development and model transformation, software processes, security and software evolution

    Probabilistic Framework for Sensor Management

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    A probabilistic sensor management framework is introduced, which maximizes the utility of sensor systems with many different sensing modalities by dynamically configuring the sensor system in the most beneficial way. For this purpose, techniques from stochastic control and Bayesian estimation are combined such that long-term effects of possible sensor configurations and stochastic uncertainties resulting from noisy measurements can be incorporated into the sensor management decisions

    Distributed Communication in Swarms of Autonomous Underwater Vehicles

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    Effective communication mechanisms are a key requirement for schools of submersible robots and their meaningful deployment. Large schools of identical submersibles require a fully distributed communication system which scales well and optimises for ”many-to-many” communication (omnicast, also known as gossiping). As an additional constraint, communication channels under water are typically very low bandwidth and short range. This thesis discusses possible electric and electro-magnetic wireless communication channels suitable for underwater environments. Theoretical findings on the omnicast communication problem are presented, as well as the implementation of a distributed time division multiple access (TDMA) scheduling algorithm in simulation and in hardware. It is shown theoretically and in simulation that short range links in a robotic swarm are actually an advantage, compared to links that cover large parts of the network. Experiments were carried out on custom-developed digital long-wave radio and optical link modules. The results of the experiments are used to revisit the initial assumptions on communication in multi-hop wireless networks

    Spartan Daily, January 19, 1962

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    Volume 49, Issue 64https://scholarworks.sjsu.edu/spartandaily/4251/thumbnail.jp
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