The effects of internal resonances in vibration isolators under absolute velocity feedback control

Conventional vibration isolators are usually assumed to be massless for modelling purposes, which tends to overestimate the isolator performance because the internal resonances (IRs) due to the inertia of the isolator are neglected. Previous research on the IR problem does not clarify all the characteristics of distributed parameter isolators. Furthermore, with the development of active vibration isolation, which can avoid the compromise in the choice of damping in conventional passive isolation systems, the effects of IRs in isolators on the control performance and stability for commonly used control strategies need to be quantified. In this study the effects of IRs on the control performance and stability of an absolute velocity feedback (AVF) control system are presented. A stability condition for AVF control system is proposed and a simple approach to stabilize the control system is studied. Experimental work to validate the theoretical results is also presented

srMO-BO-3GP: A sequential regularized multi-objective constrained Bayesian optimization for design applications

Bayesian optimization (BO) is an efficient and flexible global optimization framework that is applicable to a very wide range of engineering applications. To leverage the capability of the classical BO, many extensions, including multi-objective, multi-fidelity, parallelization, latent-variable model, have been proposed to improve the limitation of the classical BO framework. In this work, we propose a novel multi-objective (MO) extension, called srMO-BO-3GP, to solve the MO optimization problems in a sequential setting. Three different Gaussian processes (GPs) are stacked together, where each of the GP is assigned with a different task: the first GP is used to approximate the single-objective function, the second GP is used to learn the unknown constraints, and the third GP is used to learn the uncertain Pareto frontier. At each iteration, a MO augmented Tchebycheff function converting MO to single-objective is adopted and extended with a regularized ridge term, where the regularization is introduced to smoothen the single-objective function. Finally, we couple the third GP along with the classical BO framework to promote the richness and diversity of the Pareto frontier by the exploitation and exploration acquisition function. The proposed framework is demonstrated using several numerical benchmark functions, as well as a thermomechanical finite element model for flip-chip package design optimization

Private equity: where we have been and the road ahead

© 2019 Informa UK Limited, trading as Taylor & Francis Group. We provide an overview of the systematic evidence relating to the impact of private equity (PE) backed buyouts over the last two decades. We focus on performance; employment and employee relations; innovation, investment and entrepreneurship; longevity and survival. We also explore a future research agenda in the context of a maturing PE industry

Do the Disc Degeneration and Osteophyte Contribute to the Curve Rigidity of Degenerative Scoliosis?

The factors associated with lateral curve flexibility in degenerative scoliosis have not been well documented. Disc degeneration could result in significant change in stiffness and range of motion in lateral bending films. The osteophytes could be commonly observed in degenerative spine but the relationship between osteophyte formation and curve flexibility remains controversial. The aim of the current study is to clarify if the disc degeneration and osteophyte formation were both associated with curve flexibility of degenerative scoliosis

Lehmien ylläpitotarpeen ja muuntokelpoisen energian käytön tehokkuuden perinnöllinen vaihtelu maidontuotannossa

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Learning to Rank when Grades Matter

Graded labels are ubiquitous in real-world learning-to-rank applications, especially in human rated relevance data. Traditional learning-to-rank techniques aim to optimize the ranked order of documents. They typically, however, ignore predicting actual grades. This prevents them from being adopted in applications where grades matter, such as filtering out ``poor'' documents. Achieving both good ranking performance and good grade prediction performance is still an under-explored problem. Existing research either focuses only on ranking performance by not calibrating model outputs, or treats grades as numerical values, assuming labels are on a linear scale and failing to leverage the ordinal grade information. In this paper, we conduct a rigorous study of learning to rank with grades, where both ranking performance and grade prediction performance are important. We provide a formal discussion on how to perform ranking with non-scalar predictions for grades, and propose a multiobjective formulation to jointly optimize both ranking and grade predictions. In experiments, we verify on several public datasets that our methods are able to push the Pareto frontier of the tradeoff between ranking and grade prediction performance, showing the benefit of leveraging ordinal grade information

In vivo detection of cortical optical changes associated with seizure activity with optical coherence tomography.

The most common technology for seizure detection is with electroencephalography (EEG), which has low spatial resolution and minimal depth discrimination. Optical techniques using near-infrared (NIR) light have been used to improve upon EEG technology and previous research has suggested that optical changes, specifically changes in near-infrared optical scattering, may precede EEG seizure onset in in vivo models. Optical coherence tomography (OCT) is a high resolution, minimally invasive imaging technique, which can produce depth resolved cross-sectional images. In this study, OCT was used to detect changes in optical properties of cortical tissue in vivo in mice before and during the induction of generalized seizure activity. We demonstrated that a significant decrease (P < 0.001) in backscattered intensity during seizure progression can be detected before the onset of observable manifestations of generalized (stage-5) seizures. These results indicate the feasibility of minimally-invasive optical detection of seizures with OCT