Solid-State Thin-Film Broadband Short-Wave Infrared Light Emitters

Solid-state broadband light emitters in the visible have revolutionized today's lighting technology achieving compact footprints, flexible form factors, long lifetimes, and high energy saving, although their counterparts in the infrared are still in the development phase. To date, broadband emitters in the infrared have relied on phosphor-downconverted light emitters based on atomic optical transitions in transition metal or rare earth elements in the phosphor layer resulting in limited spectral bandwidths in the near-infrared and preventing their integration into electrically driven light-emitting diodes (LEDs). Herein, phosphor-converted LEDs based on engineered stacks of multi-bandgap colloidal quantum dots (CQDs) are reported as a novel class of broadband emitters covering a broad short-wave infrared (SWIR) spectrum from 1050–1650 nm with a full-width-half-maximum of 400 nm, delivering 14 mW of optical power with a quantum efficiency of 5.4% and power conversion efficiency of 13%. Leveraging the electrical conductivity of the CQD stacks, further, the first broadband SWIR-active LED is demonstrated, paving the way toward complementary metal–oxide–semiconductor integrated broadband emitters for on-chip spectrometers and low-cost volume manufacturing. SWIR spectroscopy is employed to illustrate the practical relevance of the emitters in food and material identification case studies.     

Ultrahigh Carrier Mobility Achieved in Photoresponsive Hybrid Perovskite Films via Coupling with Single‐Walled Carbon Nanotubes

Organolead trihalide perovskites have drawn substantial interest for photovoltaic and optoelectronic applications due to their remarkable physical properties and low processing cost. However, perovskite thin films suffer from low carrier mobility as a result of their structural imperfections such as grain boundaries and pinholes, limiting their device performance and application potential. Here we demonstrate a simple and straightforward synthetic strategy based on coupling perovskite films with embedded single‐walled carbon nanotubes. We are able to significantly enhance the hole and electron mobilities of the perovskite film to record‐high values of 595.3 and 108.7 cm² V^?1 s^?1, respectively. Such a synergistic effect can be harnessed to construct ambipolar phototransistors with an ultrahigh detectivity of 3.7 × 10¹⁴ Jones and a responsivity of 1 × 10⁴ A W^?1, on a par with the best devices available to date. The perovskite/carbon nanotube hybrids should provide a platform that is highly desirable for fields as diverse as optoelectronics, solar energy conversion, and molecular sensing.     

A Cascade Visual Front End for Speaker Independent Automatic Speechreading

We propose a three-stage pixel-based visual front end for automatic speechreading (lipreading) that results in significantly improved recognition performance of spoken words or phonemes. The proposed algorithm is a cascade of three transforms applied on a three-dimensional video region-of-interest that contains the speaker's mouth area. The first stage is a typical image compression transform that achieves a high-energy, reduced-dimensionality representation of the video data. The second stage is a linear discriminant analysis-based data projection, which is applied on a concatenation of a small amount of consecutive image transformed video data. The third stage is a data rotation by means of a maximum likelihood linear transform that optimizes the likelihood of the observed data under the assumption of their class-conditional multivariate normal distribution with diagonal covariance. We applied the algorithm to visual-only 52-class phonetic and 27-class visemic classification on a 162-subject, 8-hour long, large vocabulary, continuous speech audio-visual database. We demonstrated significant classification accuracy gains by each added stage of the proposed algorithm which, when combined, can achieve up to 27% improvement. Overall, we achieved a 60% (49%) visual-only frame-level visemic classification accuracy with (without) use of test set viseme boundaries. In addition, we report improved audio-visual phonetic classification over the use of a single-stage image transform visual front end. Finally, we discuss preliminary speech recognition results.     

A derivative-free distributed filtering approach for sensorless control of nonlinear systems

This article examines the problem of sensorless control for nonlinear dynamical systems with the use of derivative-free Extended Information Filtering (EIF). The system is first subject to a linearisation transformation and next state estimation is performed by applying the standard Kalman Filter to the linearised model. At a second level, the standard Information Filter is used to fuse the state estimates obtained from local derivative-free Kalman filters running at the local information processing nodes. This approach has significant advantages because unlike the EIF (i) is not based on local linearisation of the nonlinear dynamics (ii) does not assume truncation of higher order Taylor expansion terms thus preserving the accuracy and robustness of the performed estimation and (iii) does not require the computation of Jacobian matrices. As a case study a robotic manipulator is considered and a cameras network consisting of multiple vision nodes is assumed to provide the visual information to be used in the control loop. A derivative-free implementation of the EIF is used to produce the aggregate state vector of the robot by processing local state estimates coming from the distributed vision nodes. The performance of the considered sensorless control scheme is evaluated through simulation experiments.     

Nonlinear Kalman Filters and Particle Filters for integrated navigation of unmanned aerial vehicles

The paper studies and compares nonlinear Kalman Filtering methods and Particle Filtering methods for estimating the state vector of Unmanned Aerial Vehicles (UAVs) through the fusion of sensor measurements. Next, the paper proposes the use of the estimated state vector in a control loop for autonomous navigation and trajectory tracking by the UAVs. The proposed nonlinear controller is derived according to the flatness-based control theory. The estimation of the UAV’s state vector is carried out with the use of (i) Extended Kalman Filtering (EKF), (ii) Sigma-Point Kalman Filtering (SPKF), (iii) Particle Filtering (PF), and (iv) a new nonlinear estimation method which is the Derivative-free nonlinear Kalman Filtering (DKF). The performance of the nonlinear control loop which is based on these nonlinear state estimation methods is evaluated through simulation tests. Comparing the aforementioned filtering methods in terms of estimation accuracy and computation speed, it is shown that the Sigma-Point Kalman Filtering is a reliable and computationally efficient approach to state estimation-based control, while Particle Filtering is well-suited to accommodate non-Gaussian measurements. Moreover, it is shown that the Derivative-free nonlinear Kalman Filter is faster than the rest of the nonlinear filters while also succeeding accurate, in terms of variance, state estimates.     

Information Seeking Spoken Dialogue Systems— Part II: Multimodal Dialogue

For pt.1see ibid., vol. 9, p. 3 (2007). In this paper, the task and user interface modules of a multimodal dialogue system development platform are presented. The main goal of this work is to provide a simple, application-independent solution to the problem of multimodal dialogue design for information seeking applications. The proposed system architecture clearly separates the task and interface components of the system. A task manager is designed and implemented that consists of two main submodules: the electronic form module that handles the list of attributes that have to be instantiated by the user, and the agenda module that contains the sequence of user and system tasks. Both the electronic forms and the agenda can be dynamically updated by the user. Next a spoken dialogue module is designed that implements the speech interface for the task manager. The dialogue manager can handle complex error correction and clarification user input, building on the semantics and pragmatic modules presented in Part I of this paper. The spoken dialogue system is evaluated for a travel reservation task of the DARPA Communicator research program and shown to yield over 90% task completion and good performance for both objective and subjective evaluation metrics. Finally, a multimodal dialogue system which combines graphical and speech interfaces, is designed, implemented and evaluated. Minor modifications to the unimodal semantic and pragmatic modules were required to build the multimodal system. It is shown that the multimodal system significantly outperforms the unimodal speech-only system both in terms of efficiency (task success and time to completion) and user satisfaction for a travel reservation task     

Optimization of SIMOX for VLSI by electrical characterization

A comprehensive electrical characterization study which was conducted to optimize the fabrication of SIMOX substrates for VLSI is discussed. The oxygen implantation was carried out using medium-current and high-current implanters. The wafers were annealed at 1275°C and 1300°C to produce high-quality, precipitate-free material. The effect of dose, the effect of multiple implantation (by sequentially implanting and annealing), and the effect of the anneal ambient gas and the capping layer during annealing were studied. MOSFETs of various geometries with a gate oxide of ~20 nm were fabricated by a CMOS process incorporating the addition of a thin epitaxial Si layer. A general evaluation of each transistor was conducted by studying its static characteristics. The interface states, bulk traps, and carrier generation phenomena were studied. Good-quality interfaces were obtained. Better implantation control reduced contamination and suppressed deep traps below the detection limit. Multiple implantation resulted in superior material quality. as evidenced by very long generation lifetime values (> 100 μs)