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Deep learning has proven itself to be a powerful tool to develop datadriven signal processing algorithms for challenging engineering problems. By learning the key features and characteristics of the input signals instead of requiring a human to first identify and model them, learned algorithms can beat many human-made algorithms. In particular, deep neural networks are capable of learning the comp
The damping ratio is a key performance measure in systems that can be modelled as networks of masses and springs. We derive a lower bound on this quantity that applies to such networks when the masses are subject to viscous damping. The result allows the size of the damping ratio to be understood as a function of the system parameters. We use this to derive a decentralised criterion which, if sati
The erection process of in situ cast concrete frameworks in multi-storey housing consists of multiple on site activities in which labour, equipment and materials are interacting in a complex system. Studies have shown that the current process involves a wide range of non-value adding activities, resulting in poor process efficiency. This paper presents a model developed for discrete-event simulati
In this paper, we address mixed-criticality applications characterized by their safety criticality and time-dependent performance, which are virtualized on a Fog Computing Platform (FCP). The FCP is implemented as a set of interconnected multicore computing nodes, and brings computation and communication closer to the edge of the network, where the machines are located in industrial applications.
This paper investigates potential factors that control the El Niño–Southern Oscillation (ENSO) Spring Persistence Barrier (SPB) strength in two different ENSO regimes and apply it to explain the ENSO SPB strength modulation after the 21st century. In a damped, noise-driven model, the theoretical solution of SPB strength illustrates that a weaker ENSO growth rate strengthens SPB. In the self-sustai
Class-C operation is leveraged to implement a K-band CMOS voltage-controlled oscillator (VCO) where the upconversion of 1/f current noise from the cross-coupled transistors in the oscillator core is robustly contained at a very low level. Implemented in a bulk 28-nm CMOS technology, the 12%-tuning-range VCO shows a phase noise as low as -112 dBc/Hz at 1-MHz offset (-86 dBc/Hz at 100 kHz offset) fr
BACKGROUND: Atrioventricular plane displacement (AVPD) reflects longitudinal left ventricular (LV) systolic function, and wall thickening (WT) regional radial LV function. The temporal evolution of these measures after STEMI with CMR has not been evaluated. We aimed to investigate how AVPD and WT are affected globally and regionally from the sub-acute to the chronic phase after ST-elevation myocar
Assessments of long-term changes of air quality and global radiative forcing at a large scale heavily rely on satellite aerosol optical depth (AOD) datasets, particularly their temporal binning products. Although some attempts focusing on the validation of long-term satellite AOD have been conducted, there is still a lack of comprehensive quantification and understanding of the representativeness
Iterative learning control (ILC) is an approach to improve the performance of a system that repeats the sameoperation. In this paper, we apply the theory of pseudospectra to transient analysis of ILC. The focus of thispaper is on frequency-domain analysis of filter-based ILC. Moreover, the effect of finite trial length on thetransient growth is discussed.
We show that the structured singular value of a real matrix with respect to five full complex uncertainty blocks equals its convex upper bound. This is done by formulating the equality conditions as a feasibility SDP and invoking a result on the existence of a low-rank solution. A counterexample is given for the case of six uncertainty blocks. Known results are also revisited using the proposed ap
Background: The frequent emergence of the re-positive patients with COVID-19 is a potential threat worldwide. This study aimed to describe data from admission to follow-up for patients with COVID-19 and analyze the possible causes for re-positive nucleic acid tests to provide more scientific basis for reducing the numbers of re-positive patients after discharge. Methods: We retrospectively recorde
We characterize a class of systems for which the H-infinity optimal control problem can be simplified in a way that enables sparse solutions and efficient computation. For a subclass of the systems, an optimal controller can be explicitly expressed in terms of the matrices of the system's state-space representation. In many applications, the controller given by this formula, which is st
A novel method using the cloud to implement a variable horizon model predictive controller is presented. In case of sudden long delays and downtime, a graceful degradation is used. Robust, best effort strategies allow industrial grade use of the powerful, efficient, and quickly improving cloud ecosystems. The variable horizon strategy finds use in, for example, non-linear control problems, and the
A two-tier architecture for cloud-based MPC is presented consisting of a high rate MPC in the cloud and a low rate MPC on the local device. The system use the cloud MPC as the nominal controller but switches to local MPC in case of connectivity loss. The two MPCs are designed to be as similar to each other as possible except for the sampling rate. Different alternatives for when to execute the loc
In this contribution, a recently conducted measurement campaign for indoor millimeter-wave (mm-wave) propagation channels is introduced. A vector network analyzer (VNA)-based channel sounder was exploited to record the channel characteristics at the frequency band from 28-30 GHz. A virtual uniform circular array (UCA) with a radius of 0.25 m was formed using a rotator with 360 steps. Moreover, by
A physical network node controls allocation and/or deallocation of resources of an interconnected hardware infrastructure. The physical network node determines a number of requests currently queued at a first service node of a plurality of serially-connected service nodes at a current time. The plurality of serially-connected service nodes supports a packet flow using resources of the interconnect
Proportional-integral-derivative (PID) controllers are very common in the process industry. In a regular factory there may be hundreds or thousands of them in use. Each of these controllers needs to be tuned, and even though the PID controller is simple, tuning the controllers still requires several hours of work and adequate knowledge in order to achieve a desired performance. Because of that, ma
A multi-variable PI (proportional integrating) controller is proved to be optimal for an important class of control problems where performance is specified in terms of frequency weighted H-infinity norms. The problem class includes networked systems with a subsystem in each node and control action along each edge. For such systems, the optimal PI controller is decentralized in the sense that contr
This paper develops a novel framework for power system stability analysis, that allows for the decentralised design of inverter based controllers. The method requires that each individual inverter satisfies a standard H∞ design requirement. Critically each requirement depends only on the dynamics of the components and inverters at each individual bus, and the aggregate susceptance of the transmiss
Modeling of robot motion as dynamical movement primitives (DMPs) has becomean important framework within robot learning and control. The ability of DMPs to adapt online with respect to the surroundings, e.g., to moving targets, has been used and developed by several researchers. In this work, a method for handling perturbations during execution of DMPs on robots was developed. Two-degree-of-freedo
