Frontiers in Electronic Technologies

What makes a social humanoid robot behave like a human? It needs to understand and show emotions, has a chat box, a memory and also a decision-making process. However, more than that, it needs to recognize objects and be able to grasp them in a human way. To become an intimate companion, social robots need to behave the same way as real humans in all areas and understand real situations in order they can react properly. In this chapter, we describe our ongoing research on social robotics. It includes the making of articulated hands of Nadine Robot, the recognition of objects and their signification, as well as how to grasp them in a human way. State of the art is presented as well as some early results.

Massive amounts of data have recently been, and are increasingly being, generated from various fields, such as bioinformatics, neuroscience and social networks. Many of these big datasets were generated to answer specific research questions, and were analysed accordingly. However, the scope of information contained in these datasets can usually answer much broader questions than what was originally intended. Moreover, many existing big datasets are related to each other but have different detailed specifications, and the mutual information that can be extracted from them collectively has been not commonly considered. To bridge this gap between the fast pace of data generation and the slower pace of data analysis, and to exploit the massive amounts of existing data, we suggest employing data-driven explorations to analyse collections of related big datasets. This approach aims at extracting field-specific novel findings which can be revealed from the data without being driven by specific questions or hypotheses. To realise this paradigm, we introduced the binarisation of consensus partition matrices (Bi-CoPaM) method, with the ability of analysing collections of heterogeneous big datasets to identify clusters of consistently correlated objects. We demonstrate the power of data-driven explorations by applying the Bi-CoPaM to two collections of big datasets from two distinct fields, namely bioinformatics and neuroscience. In the first application, the collective analysis of forty yeast gene expression datasets identified a novel cluster of genes and some new biological hypotheses regarding their function and regulation. In the other application, the analysis of 1,856 big fMRI datasets identified three functionally connected neural networks related to visual, reward and auditory systems during affective processing. These experiments reveal the broad applicability of this paradigm to various fields, and thus encourage exploring the large amounts of partially exploited existing datasets, preferably as collections of related datasets, with a similar approach.

Emotions when explicitly demonstrated by an actor are easy for a machine to recognize by analyzing their speech. However in case of day to day, naturally spoken spontaneous speech it is not easy for machines to identify the expressed emotion even though emotion of the speaker are embedded in their speech. One of the main reasons for this is that people, especially non-actors, do not explicitly demonstrate their emotion when they speak, thus making it difficult to recognize the emotion embedded in their spoken speech. In this paper, based on some of our previous published work (example, Chakraborty et al. in Proceedings of the 20th International Conference KES-2016 96:587–596, 2016 [1], Chakraborty et al. in TENCON 2015—2015 IEEE Region 10 Conference 1–5, 2015 [2], Chakraborty et al. in PACLIC, 2016 [3], Pandharipande and Kopparapu in TENCON 2015—2015 IEEE Region 10 Conference 1–4, 2015 [4], Kopparapu in Non-Linguistic Analysis of Call Center Conversations, 2014 [5], Pandharipande and Kopparapu in ECTI Trans Comput Inf Technol 7(2):146–155, 2013 [6], Chakraborty and Kopparapu in 2016 IEEE International Conference on Multimedia and Expo Workshops, 1–6, 2016 [7]) we identify the challenges in recognizing emotions in spontaneous speech and suggest a framework that can assist in determining the emotions expressed in spontaneous speech.

This paper discusses the role of sensors and actuators in Human–Computer Interaction and Virtual Reality. We first introduce the need of sensory input and output and the user senses stimulation. We then present two experiences of immersive games with a comparison of the techniques 20 years ago and today and also discuss the importance of vision-based hand tracking. The main part of the paper is dedicated to haptic and tactile feedbacks with 4 different case studies: haptic feedback using a haptic workstation, a wearable system for mobility improvement of visually impaired people, a system for enhancing pilot performance, and actuators to feel the wind. Finally, we survey a few smart jackets with sensors and actuators.

SiNx and SiNx: Tb³⁺ thin layers deposited by reactive magnetron co-sputtering have been studied with the aim of optimizing the light management in Si solar cells. Those Si-based layers are developed to be compatible with the Si-PV technology. An efficient energy transfer between matrix and terbium ions has been demonstrated and optimized. The layer composition and microstructure as well as its optical properties have been analyzed to favor the required optical properties for achieving a good solar cell, i.e., good anti-reflective properties and high luminescence emission intensity. Finally a Tb-doped SiNx thin film has been deposited on the top of a Si solar cells and solar cell characteristics studied.

We report the fabrication and characterization of a 320 × 256 infrared focal-plane imager fabricated using an strain-coupled quaternary capped InAs quantum dots heterostructure, which showed multiple photoluminescence peak and activation energy of 207.38 meV for dominant peak. Multiple ground state peaks in photoluminescence spectra indicates multimodal dot size distribution which was confirmed using cross-sectional transmission microscopy images. We discuss the fabrication and characterization of single-pixel detectors that can measure intersubband spectral responses with peak intensity at 6.9 µm and narrow spectral linewidth of 19%. The highest detectivity of 2.48 × 10¹⁰ cm Hz^1/2/W at 77 K was observed from proposed structure. Using the fabricated device, infrared images were captured at 50–100 K. Device optimization led to approximately 95% of the pixels in the imaging array being operational and a reasonably low noise equivalent temperature of approximately 0.080 °C at 100 K.

Microstrip patch antenna is used extensively in wireless and mobile applications due to its low profile and lightweight. However, this antenna is prone to low gain, limited bandwidth and increased cross polarization levels. Metamaterial can be integrated onto an antenna to improve its performance. A possible approach to enhance the performance is by suppressing surface waves. This can be achieved by using Electromagnetic Bandgap (EBG) structures. In addition, plane waves that come in contact with EBG structures can be reflected in phase thereby enhancing the radiation properties of the microstrip antenna. Therefore, the main motivation underlying this work is to provide an overview on the evolution, characterization and performance enhancement of microstrip antennas with EBG structures.

This paper presents detailed over view of four different novel memristor-based nano-crossbar structures that are employed for designing a Non-Volatile Look-Up Table (NVLUT) of a Field Programmable Gate Array (FPGA) with particular focus on efficient READ and WRITE operations; techniques to overcome the effect sneak path current on unselected memristors. Cross-point memory array structure, MOS accessed memory array structure, Memory array structure with transistors at BL and Columns isolated memory array structure are the different structures considered in this paper. The paper analyzes in detail about the LUT structures and their WRITE and READ operations. Also the analysis on the SPICE simulation results of the READ and WRITE delay, energy dissipation and energy delay product of four LUT structures are presented. Among the LUT structures, Columns isolated memory array structure seems to be potential candidate for NVLUT as it eliminates the effect of sneak path current on the unselected memristors. Also it showed a fast WRITE time, significantly reduced READ power dissipation and no power dissipation in the stand-by mode. In addition, it eliminates the write half-select issue. Moreover, it prevents the data integrity when compared with other structures as this structure has better controllability of the NSPs for the unselected memristors.

The boom of wireless and mobile networks has led to an ever-increasing demand for high performance, low-power, and low-cost radio-frequency integrated circuit (RFIC) design. Advances in silicon and silicon–germanium-based technologies can now provide highly integrated system-on-chip (SOC). In spite of this significant motivation, this talk provides information about the fundamentals of RFIC design for wireless communication systems. The talk starts with a discussion on the potential applications, the technology trade-offs, and challenges on the RFIC design. We then focus on wireless transceiver IC designs with the brief analysis for each analogy front-end block, such as low-noise-amplifier (LNA), mixer, and voltage-controlled oscillator (VCO) designs. We will also present some essential topics in RFIC testing and practical implementations.

The 2020 wireless strategy is centred on creative 5G and IoT with the front runners from US, EU, China, Japan and Korea. There are trillions of dollars invested towards 2020. The wireless future is designated to be mobile. While the confidence of the future mobile technology will help innovate our government, workforce, industry and social media, the key threat to future mobile wireless development is the growing concern of its security and privacy through anomaly detection. This keynote presents key features of 2020 wireless strategy and new approaches on cyber situation awareness—the enablement to achieve 2020 wireless leadership.