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A Contoured-Beam Reflector Satellite Antenna Using Two Doubly Curved Circular Polarization Selective Surfaces

We present a reflector antenna system using a circular polarization selective surface (CPSS) to realize a circular polarization (CP) equivalent to the widely used linear polarization (LP) gridded or dual-gridded reflector (DGR). The CPSS is realized by a multilayer stack of non-resonant anisotropic meander line surfaces, achieving a very wide bandwidth. The CPSS reflection and transmission dyadics

Analysis and Design of a 17-GHz All-npn Push-Pull Class-C VCO

A push-pull oscillator topology that uses only one type of active device is proposed in this article. A magnetic transformer is leveraged to set positive feedback around a common-collector differential npn transistor pair, implementing the push-pull operation. This results in half the bias current for a given amplitude of oscillation, compared to more standard oscillator topologies. A thorough pha

Dual Control of Linear Discrete-Time Systems with Time-Varying Parameters

We describe how the optimal dual controller for a discrete-time linear system can be found by approximately solving the corresponding Bellman equation using a neural network to represent the value function. We illustrate the method on an example with time-varying dynamics, where the new method is shown to give improved performance.

Assessment of Amide proton transfer weighted (APTw) MRI for pre-surgical prediction of final diagnosis in gliomas

PURPOSE: Radiological assessment of primary brain neoplasms, both high (HGG) and low grade tumors (LGG), based on contrast-enhancement alone can be inaccurate. We evaluated the radiological value of amide proton transfer weighted (APTw) MRI as an imaging complement for pre-surgical radiological diagnosis of brain tumors.METHODS: Twenty-six patients were evaluated prospectively; (22 males, 4 female

Attitude Control on SU(2): Stability, Robustness, and Similarities

This paper concerns trajectory tracking control of attitude dynamics configured on SU(2). Inspired by a popular geometric tracking controller on SO(3), differential geometric tools are used to derive both continuous and discontinuous attitude controllers on the SU(2) manifold, relating these to preexisting controllers operating with imaginary quaternion errors. Additionally, a robustness result is

Exploiting linear substructure in linear regression Kalman filters

We exploit knowledge of linear substructure in the linear-regression Kalman filters (LRKFs) to simplify the problem of moment matching. The theoretical results yield quantifiable and significant computational speedups at no cost of estimation accuracy, assuming partially linear estimation models. The results apply to any symmetrical LRKF, and reductions in computational complexity are stated as a

Filtered output feedback tracking control of a quadrotor UAV

We present a tracking controller for quadrotor UAVs which uses partial state information and filters measurement noise. We show uniform almost global and locally exponential asymptotic stability of the resulting closed-loop system, which implies robustness against bounded disturbances. We illustrate the performance of the controller by means of several numerical examples, including a complex loopi

Coordination Control of Double-Integrator Systems with Time-Varying Weighted Inputs

This paper considers coordination control of double-integrator systems and proposes general control laws involving time-varying inputs. The nominal control input is weighted by time-varying (time-dependent or state-dependent) positive definite matrices, providing more freedoms in defining the control tasks. We present sufficient conditions to ensure the asymptotic convergence of double-integrator

Improving Performance of Feedback-Based Real-Time Networks using Model Checking and Reinforcement Learning

Traditionally, automatic control techniques arose due to need for automation in mechanical systems. These techniques rely on robust mathematical modelling of physical systems with the goal to drive their behaviour to desired set-points. Decades of research have successfully automated, optimized, and ensured safety of a wide variety of mechanical systems. Recent advancement in digital technology ha

Enforcing the General Planar Motion Model : Bundle Adjustment for Planar Scenes

In this paper we consider the case of planar motion, where a mobile platform equipped with two cameras moves freely on a planar surface. The cameras are assumed to be directed towards the floor, as well as being connected by a rigid body motion, which constrains the relative motion of the cameras and introduces new geometric constraints. In the existing literature, there are several algorithms ava

Integration of Clouds to Industrial Communication Networks

Cloud computing, owing to its ubiquitousness, scalability and on-demand ac- cess, has transformed into many traditional sectors, such as telecommunication and manufacturing production. As the Fifth Generation Wireless Specifica- tions (5G) emerges, the demand on ubiquitous and re-configurable computing resources for handling tremendous traffic from omnipresent mobile devices has been put forward.

[11C]PIB amyloid quantification : effect of reference region selection

Background: The standard reference region (RR) for amyloid-beta (Aβ) PET studies is the cerebellar grey matter (GMCB), while alternative RRs have mostly been utilized without prior validation against the gold standard. This study compared five commonly used RRs to gold standard plasma input-based quantification using the GMCB. Methods: Thirteen subjects from a test–retest (TRT) study and 30 from a

Experimental Exploration of Unlicensed Sub-GHz Massive MIMO for Massive Internet-of-Things

IoT networks are getting overcrowded following the vast increase in number of Internet-of-Things (IoT) devices and connections. Networks can be extended with more gateways, increasing the number of supported devices. However, as investigated in this work, massive MIMO has the potential to increase the number of simultaneous connections and moreover lower the energy expenditure of these devices. We

Anomaly Detection Under Multiplicative Noise Model Uncertainty

State estimators are crucial components of anomaly detectors that are used to monitor cyber-physical systems. Many frequently-used state estimators are suscepti- ble to model risk as they rely critically on the availability of an accurate state-space model. Modeling errors make it more difficult to distinguish whether deviations from expected behavior are due to anomalies or simply a lack of knowl

Fair heat distribution under deficits in district heating networks

In order to improve the energy efficiency in district heating networks and the comfort of their customers, these networks need to overcome the problem of unfair heat distribution under heat deficits. This paper introduces a new strategy to achieve this thermal fairness objective: it is lowcost in terms of communication and computation. The proposed approach is illustrated on a simulation example.

Secondary ice production during the break-up of freezing water drops on impact with ice particles

We provide the first dedicated laboratory study of collisions of supercooled water drops with ice particles as a secondary ice production mechanism. We experimentally investigated collisions of supercooled water drops (∼5 mm in diameter) with ice particles of a similar size (∼6 mm in diameter) placed on a glass slide at temperatures >-12 °C. Our results showed that secondary drops were generated d

Triple collocation-based error estimation and data fusion of global gridded precipitation products over the Yangtze River basin

Error estimation and data fusion are critical to improving the accuracy of global model- and satellite-based precipitation products for practical applications. However, they face challenges over vast areas of the world due to limited ground observations. Triple collocation (TC) method can overcome this limitation and provide an efficient way for error estimation without the “ground truth” and thus

Improving generalisation capability of artificial intelligence-based solar radiation estimator models using a bio-inspired optimisation algorithm and multi-model approach

One way of reducing environmental pollution is to reduce our dependence on fossil fuels by replacing them with solar radiation (Rs), which is one of the main sources of clean and renewable energy. In this study, daily Rs values at seven meteorological stations in Iran (Ahvaz, Isfahan, Kermanshah, Mashhad, Bandar Abbas, Kerman and Tabriz) over 2010-2019 were estimated using empirical models, suppor

Collaborative Aspects of Open Data in Software Engineering

Engineers require high-quality data for the design and implementation of today’s software, especially in the context of machine learning (ML). This puts an emphasis on the need for the publication and sharing of data from and between organizations, public as well as private. Following the paradigm of open innovation, open data provide a mechanism to increase the availability of information, offeri