How To Control Text Simplification? An Empirical Study of Control Tokens for Meaning Preserving Controlled Simplification

Text simplification rewrites text to be more readable for a specific audience, while preserving its meaning. However, determining what makes a text easy to read depends on who are the intended readers. Recent work has introduced a wealth of techniques to control output simplicity, ranging from specifying the desired reading grade level to providing control tokens that directly encode low-level simplification edit operations. However, it remains unclear how to set the input parameters that control simplification in practice. Existing approaches set them at the corpus level, disregarding the complexity of individual source text, and do not directly evaluate them at the instance level. In this work, we conduct an empirical study to understand how different control mechanisms impact the adequacy and simplicity of model outputs. Based on these insights, we introduce a simple method for predicting control tokens at the sentence level to enhance the quality of the simplified text. Predicting control token values using features extracted from the original complex text and a user-specified degree of complexity improves the quality of the simplified outputs over corpus-level search-based heuristics.Comment: work in progres

Regulation of magnetically actuated satellites using model predictive control with disturbance modelling

The problem of magnetic attitude regulation of low Earth orbiting satellites is addressed using model predictive control. This paper considers extending the current literature within this area by combining a standard predictive controller with a suitable disturbance model. For low Earth orbiting satellites the disturbances due to the external environment are very significant and consideration of these torques within the control law is imperative to obtain the best possible controller performance. In order to obtain an estimate of the external disturbance, a state estimator of varying complexity is used. This estimator initially assumes that the disturbances acting on the satellite remain constant with time, but this assumption is then improved to assume harmonic variation of the disturbance. Simulations show that inclusion of a feed-forward element to the control offers notable performance benefits. Interestingly, increasing the complexity of the disturbance model seems to offer little improvement in performance and a simple constant disturbance model provides a suitable solution to the problem while maintaining simplicity of the state estimator

Maximum power point tracking using P&O control optimized by a neural network approach: a good compromise between accuracy and complexity

In the field of power optimization of photovoltaic panels (PV), there exist many maximum power point tracking (MPPT) control algorithms, such as: the perturb and observe (P&O) one, the algorithms based on fuzzy logic and the ones using a neural network approaches. Among these MPPT control algorithms, P&O is one of the most widely used due to its simplicity of implementation. However, the major drawback of this kind of algorithm is the lack of accuracy due to oscillations around the PPM. Conversely, MPPT control using neural networks have shown to be a very efficient solution in term of accuracy. However, this approach remains complex. In this paper we propose an original optimization of the P&O MPPT control with a neural network algorithm leading to a significant reduction of the computational cost required to train it, ensuring a good compromise between accuracy and complexity. The algorithm has been applied to the models of two different types of solar panels, which have been experimentally validated

Distributed admission control for QoS and SLS management

This article proposes a distributed admission control (AC) model based on on-line monitoring to manage the quality of Internet services and Service Level Specifications (SLSs) in class-based networks. The AC strategy covers intra- and interdomain operation, without adding significant complexity to the network control plane and involving only edge nodes. While ingress nodes perform implicit or explicit AC resorting to service-oriented rules for SLS and QoS parameters control, egress nodes collect service metrics providing them as inputs for AC. The end-to-end operation is viewed as a cumulative and repetitive process of AC and available service computation.We discuss crucial key points of the model implementation and evaluate its two main components: themonitoring process and the AC criteria. The results show that, using proper AC rules and safety margins, service commitments can be efficiently satisfied, and the simplicity and flexibility of the model can be explored to manage successfully QoS requirements of multiple Internet services.(undefined

Creating complex protocells and prototissues using simple DNA building blocks

Building synthetic protocells and prototissues hinges on the formation of biomimetic skeletal frameworks. Recreating the complexity of cytoskeletal and exoskeletal fibers, with their widely varying dimensions, cellular locations and functions, represents a major material hurdle and intellectual challenge which is compounded by the additional demand of using simple building blocks to ease fabrication and control. Here we harness simplicity to create complexity by assembling structural frameworks from subunits that can support membrane-based protocells and prototissues. We show that five oligonucleotides can anneal into nanotubes or fibers whose tunable thicknesses and lengths spans four orders of magnitude. We demonstrate that the assemblies' location inside protocells is controllable to enhance their mechanical, functional and osmolar stability. Furthermore, the macrostructures can coat the outside of protocells to mimic exoskeletons and support the formation of millimeter-scale prototissues. Our strategy could be exploited in the bottom-up design of synthetic cells and tissues, to the generation of smart material devices in medicine

Fault-Tolerant Torque Controller Based on Adaptive Decoupled Multi-Stator Modeling for Multi-Three-Phase Induction Motor Drives

Among the multiphase solutions, multi-three-phase drives are becoming more and more widespread in practice as they can be modularly supplied by conventional three-phase inverters. The literature reports several control approaches to perform the torque regulation of multi-three-phase machines. Most of such solutions use the vector space decomposition (VSD) approach since it allows the control of a multi-three-phase machine using the conventional control schemes of three-phase drives, thus reducing the complexity of the control algorithm. However, this advantage is practically lost in the case of open-three-phase faults. Indeed, the postfault operation of the VSD-based drive schemes requires the implementation of additional control modules, often specifically designed for the machine under consideration. Therefore, this article aims to propose a novel control approach that allows using any control scheme developed for three-phase motors to perform the torque regulation of a multi-three-phase machine both in healthy and faulty operation. In this way, the previously mentioned drawbacks of the VSD-based control schemes in dealing with the faulty operation of the machine are avoided. Moreover, the simplicity of the control algorithm is always preserved, regardless of the machine's operating condition. The proposed solution has been experimentally validated through a 12-phase induction motor, rated 10 kW at 6000 r/min, using a quadruple-three-phase configuration of the stator winding

Fault-Tolerant Torque Controller Based on Adaptive Decoupled Multi-Stator Modeling for Multi-Three-Phase Induction Motor Drives

Among the multiphase solutions, multi-three- phase drives are becoming more and more widespread in practice as they can be modularly supplied by conventional three-phase inverters. The literature reports several control approaches to perform the torque regulation of multi-three- phase machines. Most of such solutions use the vector space decomposition (VSD) approach since it allows the control of a multi-three-phase machine using the conventional control schemes of three-phase drives, thus reducing the complexity of the control algorithm. However, this advantage is practically lost in the case of open-three-phase faults. Indeed, the post-fault operation of the VSD-based drive schemes requires the implementation of additional control modules, often specifically designed for the machine under consideration. Therefore, this paper aims to propose a novel control approach that allows using any control scheme developed for three-phase motors to perform the torque regulation of a multi-three-phase machine both in healthy and faulty operation. In this way, the previously mentioned drawbacks of the VSD-based control schemes in dealing with the faulty operation of the machine are avoided. Moreover, the simplicity of the control algorithm is always preserved, regardless of the machine's operating condition. The proposed solution has been experimentally validated through a 12-phase induction motor, rated 10 kW at 6000 r/min, using a quadruple-three-phase configuration of the stator windin