The term photonic crystals appears because of the analogy between electron waves in crystals and the light waves in artificial periodic dielectric structures. During the recent years the investigation of one-, two-and three-dimensional periodic structures has attracted a widespread attention of the world optics community because of great potentiality of such structures in advanced applied optical fields. The interest in periodic structures has been stimulated by the fast development of semiconductor technology that now allows the fabrication of artificial structures, whose period is comparable with the wavelength of light in the visible and infrared ranges.

http://ieeexplore.ieee.org/iel5/6354/16969/00781867.pdf

Photonic crystals

In the real world, a realistic setting for computer vision or multimedia recognition problems is that we have some classes containing lots of training data and many classes contain a small amount of training data. Therefore, how to use frequent classes to help learning rare classes for which it is harder to collect the training data is an open question. Learning with Shared Information is an emerging topic in machine learning, computer vision and multimedia analysis. There are different level of components that can be shared during concept modeling and machine learning stages, such as sharing generic object parts, sharing attributes, sharing transformations, sharing regularization parameters and sharing training examples, etc. Regarding the specific methods, multi-task learning, transfer learning and deep learning can be seen as using different strategies to share information. These learning with shared information methods are very effective in solving real-world large-scale problems. This special issue aims at gathering the recent advances in learning with shared information methods and their applications in computer vision and multimedia analysis. Both state-of-the-art works, as well as literature reviews, are welcome for submission. Papers addressing interesting real-world computer vision and multimedia applications are especially encouraged. Topics of interest include, but are not limited to:  • Multi-task learning or transfer learning for large-scale computer vision and multimedia analysis • Deep learning for large-scale computer vision and multimedia analysis • Multi-modal approach for large-scale computer vision and multimedia analysis • Different sharing strategies, e.g., sharing generic object parts, sharing attributes, sharing transformations, sharing regularization parameters and sharing training examples, • Real-world computer vision and multimedia applications based on learning with shared information, e.g., event detection, object recognition, object detection, action recognition, human head pose estimation, object tracking, location-based services, semantic indexing. • New datasets and metrics to evaluate the benefit of the proposed sharing ability for the specific computer vision or multimedia problem. • Survey papers regarding the topic of learning with shared information.  Authors who are unsure whether their planned submission is in scope may contact the guest editors prior to the submission deadline with an abstract, in order to receive feedback.

IEEE transactions on pattern analysis and machine intelligence

Advances in soft robotics, materials science, and stretchable electronics have enabled rapid progress in soft grippers. Here, a critical overview of soft robotic grippers is presented, covering different material sets, physical principles, and device architectures. Soft gripping can be categorized into three technologies, enabling grasping by: a) actuation, b) controlled stiffness, and c) controlled adhesion. A comprehensive review of each type is presented. Compared to rigid grippers, end-effectors fabricated from flexible and soft components can often grasp or manipulate a larger variety of objects. Such grippers are an example of morphological computation, where control complexity is greatly reduced by material softness and mechanical compliance. Advanced materials and soft components, in particular silicone elastomers, shape memory materials, and active polymers and gels, are increasingly investigated for the design of lighter, simpler, and more universal grippers, using the inherent functionality of the materials. Embedding stretchable distributed sensors in or on soft grippers greatly enhances the ways in which the grippers interact with objects. Challenges for soft grippers include miniaturization, robustness, speed, integration of sensing, and control. Improved materials, processing methods, and sensing play an important role in future research.

https://onlinelibrary.wiley.com/doi/pdf/10.1002/adma.201707035

Soft Robotic Grippers.

Finite element methods for Maxwell's equations.

Driven by functionality and purity demand for applications of inorganic nanoparticle colloids in optics, biology, and energy, their surface chemistry has become a topic of intensive research interest. Consequently, ligand-free colloids are ideal reference materials for evaluating the effects of surface adsorbates from the initial state for application-oriented nanointegration purposes. After two decades of development, laser synthesis and processing of colloids (LSPC) has emerged as a convenient and scalable technique for the synthesis of ligand-free nanomaterials in sealed environments. In addition to the high-purity surface of LSPC-generated nanoparticles, other strengths of LSPC include its high throughput, convenience for preparing alloys or series of doped nanomaterials, and its continuous operation mode, suitable for downstream processing. Unscreened surface charge of LSPC-synthesized colloids is the key to achieving colloidal stability and high affinity to biomolecules as well as support materials,...

Laser Synthesis and Processing of Colloids: Fundamentals and Applications

The proposed paper is related to a case of study of an e-health telemedicine system oriented on homecare assistance and suitable for de-hospitalization processes. The proposed platform is able to transfer efficiently the patient analyses from home to a control room of a clinic, thus potentially reducing costs and providing high-quality assistance services. The goal is to propose an innovative resources management platform (RMP) integrating an innovative homecare decision support system (DSS) based on a multilayer perceptron (MLP) artificial neural network (ANN). The study is oriented in predictive diagnostics by proposing an RMP integrating a KNIME (Konstanz Information Miner) MLP-ANN workflow experimented on blood pressure systolic values. The workflow elaborates real data transmitted via the cloud by medical smart sensors and provides a prediction of the patient status. The innovative RMP-DSS is then structured to enable three main control levels. The first one is a real-time alerting condition triggered when real-time values exceed a threshold. The second one concerns preventative action based on the analysis of historical patient data, and the third one involves alerting due to patient status prediction. The proposed study combines the management of processes with DSS outputs, thus optimizing the homecare assistance activities.

A Study of a Health Resources Management Platform Integrating Neural Networks and DSS Telemedicine for Homecare Assistance

In this paper, we study an unconventional kind of quasi-three-dimensional (3-D) photonic crystal (PhC) with circular lattice pattern: it consists of air holes in a GaAs material (n=3.408) along circular concentric lines. This particular PhC geometry has peculiar behavior if compared with the traditional square and triangular lattices, but it is difficult to model by using conventional numerical approaches such as wave expansion method. The resonance and the radiation aspects are analyzed by the 3-D finite-element method (FEM). The model, based on a scattering matrix approach, considers the cavity resonance frequency and evaluates the input-output relationship by enclosing the photonic crystal slab (PhCS) in a black box in order to define the responses at different input-output ports. The scattering matrix method gives important information about the frequency responses of the passive 3-D crystal in the 3-D spatial domain. A high sensitivity of the scattering parameters to the variation of the geometrical imperfection is also observed. The model is completed by the quality factor (Q-factor) estimation. We fabricated the designed circular photonic crystal over a slab membrane waveguide embedding InAs/GaAs quantum dots emitting around 1.28 mum. Good agreement between numerical and experimental results was found, thus validating the 3-D FEM full-wave investigation.

3-D FEM Modeling and Fabrication of Circular Photonic Crystal Microcavity

Energy harvesting at low frequency is a challenge for microelectromechanical systems. In this work we present a piezoelectric vibration energy harvester based on freestanding molybdenum (Mo) and aluminum nitride (AlN) ring-microelectromechanical-system (RMEMS) resonators. The freestanding ring layout has high energy efficiency due to the additional torsional modes which are absent in planar cantilevers systems. The realized RMEMS prototypes show very low resonance frequencies without adding proof masses, providing the record high power density of 30.20 μW mm−3 at 64 Hz with an acceleration of 2g. The power density refers to the volume of the vibrating RMEMS layout.

Freestanding piezoelectric rings for high efficiency energy harvesting at low frequency

A review, even if not exhaustive, on the current technologies able to harvest energy from Earth’s thermal infrared emission is reported. In particular, we discuss the role of the rectenna system on transforming the thermal energy, provided by the Sun and reemitted from the Earth, in electricity. The operating principles, efficiency limits, system design considerations, and possible technological implementations are illustrated. Peculiar features of THz and IR antennas, such as physical properties and antenna parameters, are provided. Moreover, some design guidelines for isolated antenna, rectifying diode, and antenna coupled to rectifying diode are exploited.

/pdf/new-trends-in-energy-harvesting-from-earth-long-wave-a4sg2iimk4.pdf

New Trends in Energy Harvesting from Earth Long-Wave Infrared Emission

In this paper are investigated the re-engineering approaches for the optimization of pasta production processes. A preliminary study of technologies and information systems architectures to be appl...

https://www.tandfonline.com/doi/pdf/10.1080/21693277.2020.1749180

Alessandro Massaro

Papers

A Study of a Health Resources Management Platform Integrating Neural Networks and DSS Telemedicine for Homecare Assistance

3-D FEM Modeling and Fabrication of Circular Photonic Crystal Microcavity

Freestanding piezoelectric rings for high efficiency energy harvesting at low frequency

New Trends in Energy Harvesting from Earth Long-Wave Infrared Emission

Re-engineering process in a food factory: an overview of technologies and approaches for the design of pasta production processes