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

Actually MEMS technology allows to fabricate free standing and bended cantilevers by acting on stress/strain properties and thicknesses of materials. In particular, by means of MEMS technology it is possible to realize ring or spiral layouts with piezoelectric materials. The mechanical movement due to the piezoelectric resonance can be used in order to modulate a signal travelling in the MEMS and radiating in the free space as happens in antennas. In this work we provide an accurate study regarding the design approach of piezoelectric aluminium nitride (AlN) ring antenna. The study is developed by means of a tailored 3D FEM tool which allows to analyze the piezoelectric resonances and to design the ring micro-antenna in the THz range. Finally we provide the technology and we measure the piezoelectric resonances of ring antennas.

/pdf/3d-fem-modeling-and-technology-of-piezoelectric-ring-mems-3dnxe5bxmm.pdf

3d fem modeling and technology of piezoelectric ring mems antenna

This review will focus on advances in electronic and optoelectronic technologies by through the analysis of a full research and industrial application scenario. Starting with the analysis of nanocomposite sensors, and electronic/optoelectronic/mechatronic systems, the review describes in detail the principles and the models for finding possible implementations of Industry 5.0 applications. The study then addresses production processes and advanced detection systems integrating Artificial Intelligence (AI) algorithms. Specifically, the review introduces new research topics in Industry 5.0 about AI self-adaptive systems and processes in electronics, robotics and production management. The paper proposes also new Business Process Modelling and Notation (BPMN) Process Mining (PM) workflows, and a simulation of a complex Industry 5.0 manufacturing framework. The performed simulation estimates the diffusion heat parameters of a hypothesized production-line layout, describing the information flux of the whole framework. The simulation enhances the technological key elements, enabling an industrial upscale in the next digital revolution. The discussed models are usable in management engineering and informatics engineering, as they merge the perspectives of advanced sensors with Industry 5.0 requirements. The goal of the paper is to provide concepts, research topics and elements to design advanced production network in manufacturing industry.

https://www.mdpi.com/2076-3417/13/7/4582/pdf?version=1680837127

Advanced Electronic and Optoelectronic Sensors, Applications, Modelling and Industry 5.0 Perspectives

In this paper, the authors introduce an innovative and complete tool for the automatic diagnostic and detection of small notches on analyzed components. The tool is based on the analysis of the data of a nanocomposite optical sensor accurately moved by a robotic arm, whose gripper catches and moves the optical sensor, for scanning without contact the external surface of mechanical components. The recent optical sensor is composed of an optical fiber source made up of a nanocomposite material, and it allows detecting the characteristics of the target by monitoring the backscattered light. The innovative tool here presented is based on the analysis of several experiments carried out, considering small notches of different lengths. The proposed algorithm, together with the used device, is able to point out the presence or not of a small notch on the scanned component and also to estimate with a good precision its length and position.

An Innovative Tool for Detection of Small Notches Using a Nanocomposite Optical Sensor

In this paper a new algorithm for multi-class classification is presented The algorithm, that is named Vertex Feature Classification (VFC), maps input data sets into an ad-hoc built space, called "simplex space" in order to perform geometric classification More precisely, each class is first associated to a specific vertex of the polytope computed in the feature space Successively, pattern classification is performed according to the geometric arrangement of patterns in a higher dimensional feature space The experimental results, carried out on datasets of the UCI Machine Learning Repository, demonstrate the accuracy of the new algorithm is comparable with KNN, VDA and SVM, without or with a little training phase An important aspect of this algorithm is its training time, which takes often a few milliseconds Furthermore, the algorithm is robust and computationally efficient

Vertex Feature Classification (VFC)

In the construction of polarization beam-splitters (PBS) and switches a structure can be employed, that is based on the birefringence of periodically laminated dielectric thin films [2,7]. In this work we derive an estimate of the split angle in laminated polarization splitters behaving as negative uniaxial crystals, in the case of oblique incidence. This analysis has been applied to an artificial anisotropic dielectric medium realized by means of layers of a-Si:H and SiO2 [7].

/pdf/negative-uniaxial-optical-behaviour-of-laminated-177n5zrni6.pdf

Alessandro Massaro

Papers

3d fem modeling and technology of piezoelectric ring mems antenna

Advanced Electronic and Optoelectronic Sensors, Applications, Modelling and Industry 5.0 Perspectives

An Innovative Tool for Detection of Small Notches Using a Nanocomposite Optical Sensor

Vertex Feature Classification (VFC)

Negative Uniaxial Optical Behaviour of Laminated Polarization Beam-splitters