Bringing deep learning techniques to electromagnetic imaging is of interest considering its great success in various fields. Deep neural nets however are known for being data hungry machines, and in many practical cases, such as electromagnetic medical imaging, there is not enough to feed them. Scarcity of data necessitates reliance on simulations to generate a sufficiently large dataset for deep learning to perform any complicated task. Simulations however, can not perfectly represent real environments and therefore, any neural net trained on simulation data will invariably fail when evaluated on real data. This work customizes a deep domain adaptation technique for matching distributions of complex-valued electromagnetic data. We demonstrate the advantage of using complex-valued models over regular ones. An operational neural network trained on simulation data and adapted to practical data to perform brain injury localization is presented.

This paper analyses Disturbance Observer- (DOb-) based robust force control systems in the discrete-time domain. The robust force controller is implemented using velocity and acceleration measurements. A DOb is employed in an inner-loop to achieve robustness, and another DOb, viz. Reaction Force Observer (RFOb), is employed in an outer-loop to estimate interaction forces and improve the performance of force control. First, the inner-loop is analysed. It is shown that the DOb works as a phase-lead/lag compensator tuned by the nominal design parameters in the inner-loop. The phase margin of the inner-loop controller and the bandwidth of the velocity-based (i.e., conventional) DOb are constrained not only by noise-sensitivity but also by the waterbed effect. This explains why we observe unstable responses as the bandwidth of the conventional DOb increases in practice. To eliminate the design constraint due to the waterbed effect, this paper proposes an acceleration-based DOb. Then, the robust force controller is analysed. It is shown that the design parameters of the RFOb have a notable effect on the stability of the robust force control system. For example, the robust force controller has a non-minimum phase zero (zeros) when the RFOb is not properly tuned. This may cause severe stability and performance problems when conducting force control applications. By using the stability and robustness analyses, this paper proposes new design tools which enable one to synthesize a high-performance robust force control system. Simulations and experiments are presented to validate the proposed analysis and synthesis methods.

This paper introduces a novel control approach for Doubly-Fed Induction Generator (DFIG) operating in island mode based on the cascaded control structure with disturbance estimation. The control of the DFIG is a challenging task due to its inherent nonlinearity, fast dynamics, and unpredictable disturbances acting on the system. The proposed control structure involves a nominal controller for plant and disturbance observer (DOB) in each of the inner and outer control loop. The first-order disturbance observers are designed to estimate the time-varying and unknown disturbances. With disturbance estimation, the nominal linear dynamics is obtained in both loops. This enables the same approach for designing controllers for the inner and outer loop which significantly simplifies implementation. The controllers are designed based on the demanded error dynamics and ensure stable operation of the system, while proposed DOBs estimate disturbances including external load. Finally, the effectiveness and quality of the proposed control structure were verified through numerical simulations in terms of external disturbances rejection and closed-loop tracking performance.

The use of elemental analyses and isotope techniques for cement provenancing are reviewed. Based on the currently available data and approaches from related fields, future perspectives and a combined approach for cement provenancing are outlined.

that the air sacs. The morphology of the air sacs system has been described in many domestic and wild bird Abstract | The research was conducted with the aim to investigate the morphology of air sacs system in Crimson Rosella ( Platycercus elegans ) parrots. Five adult birds, two males and three females were used in this study. The lungs and air sac system were injected via trachea with 26% solution of Vinylite mass. The obtained cast showed that these parrots have nine air sacs. The clavicular air sac was the only unpaired, while the cervical, cranial thoracic, caudal thoracic and abdominal air sacs were paired. The morphology of the air sacs was generally similar to that reported in other bird species, however, some specific features were identified. As most prominent among them were a partial fusion of the cervical air sacs, communication between the left and right subpectoral and perirenal diverticula and connection between the claviclar and cranial thoracic air sacs. The present investigation provided detailed and comprehensive data about the morphology of air sacs system in these parrot species and these findings will be very useful for future clinical examination and treatment of this birds.

Abstract This chapter summarizes IRACON contributions related to the application of IoT in healthcare. It consists of the following three sections. Section 8.1 presents the measurement campaigns and the related statistical analysis to obtain various channel models for wearable and implantable devices. In addition, the importance of physical human-body phantoms used for channel, Specific Absorption Rate (SAR), and Electromagnetic (EM) exposure measurements are examined. Methodologies to improve the accuracy of these phantoms for various frequency bands are also discussed. Section 8.2 outlines methodologies to improve the medium access control (MAC) and networking layers of a body area networks along with possible architectures for remote health monitoring. Several applications such as localization, activity recognition, and crowdsensing and their corresponding technical challenges are also presented in this section. Finally, Section 8.3 introduces the concept of nanocommunications which can be considered as the nano-scale limit of the IoT technology spectrum. It provides an overview of the promising mechanisms that can establish data communication at molecular levels inside the human body as well as various interfacing techniques with macro-scale devices. It also highlights the revolutionary healthcare applications that could be enabled by this technology.