Factors for speech intelligibility in the symmetric and anti-symmetric speech-masker conditions

Thesis (Ph.D.)--Boston UniversityThe goal of this work is to better understand why it is easier for some than others to understand an in-front target talker presented amid two spatially-distributed interfering talkers. Speech reception thresholds (SRTs) of young listeners (normal-hearing and hearing-impaired) were measured, with the maskers arranged in the following spatial configurations: 1) "colocated", both in-front, 2) "symmetric", at ± 60° azimuth, and 3) "anti-symmetric", both at either +60°, or -60°, azimuth. SRTs were measured both binaurally and monaurally, with monaural stimuli presented to the "better-ear." Binaural benefits were calculated as the decrease in threshold when the second ear was added to the better-ear. Sensitivity to interaural time differences, interaural level differences and interaural cross-correlation were measured in the same listeners, using narrow-band noises centered at a low frequency (500Hz) and at a high frequency (2 or 4kHz). Large inter-subject differences were found for both listener groups among both interaural difference sensitivity thresholds and binaural benefits for the spatially-separated conditions. No correlations, for either of the listener groups, were observed between symmetric binaural benefit and any of the interaural difference sensitivity measures. Anti-symmetric binaural benefit significantly correlated with interaural difference sensitivity for many of the tasks, both for the normal-hearing group and among the set of hearing-impaired listeners with severe-amd-less hearing-loss. SRTs were predicted using the short-time Equalization-Cancellation (EC) model, in which two types of parameters were varied: first, the standard deviations of time-and intensity-jitters at the inputs of the binaural processing mechanism (analogous to changes in interaural sensitivity) and second, the temporal window in the binaural processing mechanism (affecting benefit from short-time binaural advantages). EC-window length was most important for predicting changes in symmetric SRTs. Changes in jitter standard deviations were most important for predicting changes in anti-symmetric SRTs. These results suggest some key differences in the mechanisms related to individual differences for the two speechmasker conditions. Both interaural difference sensitivity and a mechanism suggested by the importance of the EC-window length might be important for the symmetric condition, while interaural difference sensitivity is a key factor for the anti-symmetric condition

On the Jitter Sensitivity of an Adaptive Digital Controller::A Computational Simulation Study

In many real-time control applications, the ability to accurately track a reference trajectory with stable, pre-specified closed-loop dynamics is highly desirable. For fixed gain control systems, the detrimental impact of jitter on performance has been relatively well studied. However, research that quantifies the possible impact of jitter on the performance and relative stability of adaptive control schemes is comparatively much rarer. With technology advances now making real-time adaptive control a viable option for high-speed applications, this situation requires further investigation. In this paper, the jitter sensitivity of a digital parameter adaptive tracking control system is studied using precise software-in-the-loop computational simulations. The results obtained indicated that the adaptive controller was significantly susceptible to jitter. In particular, key metrics such as the phase margin, gain margin, settling time, overshoot and root mean square parameter and tracking errors were all significantly impacted following the introduction of 5% jitter in the controller. The obtained data are thought to be the first detailed results of this kind and present useful insights into the practical complexities when innovating adaptive real-time tracking control systems and indicate that specialized controller implementations that minimize jitter should be employed and that further analysis is warranted

Irregular speech rate dissociates auditory cortical entrainment, evoked responses, and frontal alpha

The entrainment of slow rhythmic auditory cortical activity to the temporal regularities in speech is considered to be a central mechanism underlying auditory perception. Previous work has shown that entrainment is reduced when the quality of the acoustic input is degraded, but has also linked rhythmic activity at similar time scales to the encoding of temporal expectations. To understand these bottom-up and top-down contributions to rhythmic entrainment, we manipulated the temporal predictive structure of speech by parametrically altering the distribution of pauses between syllables or words, thereby rendering the local speech rate irregular while preserving intelligibility and the envelope fluctuations of the acoustic signal. Recording EEG activity in human participants, we found that this manipulation did not alter neural processes reflecting the encoding of individual sound transients, such as evoked potentials. However, the manipulation significantly reduced the fidelity of auditory delta (but not theta) band entrainment to the speech envelope. It also reduced left frontal alpha power and this alpha reduction was predictive of the reduced delta entrainment across participants. Our results show that rhythmic auditory entrainment in delta and theta bands reflect functionally distinct processes. Furthermore, they reveal that delta entrainment is under top-down control and likely reflects prefrontal processes that are sensitive to acoustical regularities rather than the bottom-up encoding of acoustic features

Impact of the noise on the emulated grid voltage signal in hardware-in-the-loop used in power converters

This work evaluates the impact of the input voltage noise on a Hardware-In-the-Loop (HIL) system used in the emulation of power converters. A poor signal-to-noise ratio (SNR) can compromise the accuracy and precision of the model, and even make certain techniques for building mathematical models unfeasible. The case study presents the noise effects on a digitally controlled totem-pole converter emulated with a low-cost HIL system using an FPGA. The effects on the model outputs, and the cost and influence of different hardware implementations, are evaluated. The noise of the input signals may limit the benefits of increasing the resolution of the model.This research was funded by the Spanish Ministry of Science and Innovation under Project PID2021-128941OB-I00 TRENTI–Efficient Energy Transformation in Industrial Environment

Multi‐frequency averaging (MFA) model of a generic electric vehicle powertrain suitable under variable frequency of averaging developed for remote operability

© The Institution of Engineering and Technology 2020. Geographically distributed hardware-in-the-loop (HIL) testing has the potential to allow hybrid vehicle powertrain components (battery, motor drive, and engine) to be developed at geographically remote locations but tested concurrently and coupled. Inter-location internet communication links can allow non-ideal behaviour observed in a physical component in one location (e.g. an electrical drive) to be imposed on another physical component elsewhere (e.g. an ICE), and vice-versa. A key challenge is how to represent the behaviour of a remote, physical component under testing in a local HIL environment. Internet communications are too slow and unreliable to transmit waveforms in real-time and so one solution is to use a local 'slave' model whose behaviour and parameters are tuned based on observations at the remote location. This study proposes a multifrequency averaging (MFA) slave model of an electric motor drive system for use in this application; it addresses a weakness in previously published work by extending the MFA model to variable frequency operation. The model was benchmarked against experimental operation (and its equivalent simulation model) in open-loop and closed-loop space vector pulse-width modulation control strategy, fixed and variable frequency operation. Results show significant reconciliation of model and experiment

Concept and Feasibility Evaluation of Distributed Sensor-Based Measurement Systems Using Formation Flying Multicopters

Unmanned aerial vehicles (UAVs) have been used for increasing research applications in atmospheric measurements. However, most current solutions for these applications are based on a single UAV with limited payload capacity. In order to address the limitations of the single UAV-based approach, this paper proposes a new concept of measurements using tandem flying multicopters as a distributed sensor platform. Key challenges of the proposed concept are identified including the relative position estimation and control in wind-perturbed outdoor environment and the precise alignment of payloads. In the proposed concept, sliding mode control is chosen as the relative position controller and a gimbal stabilization system is introduced to achieve fine payload alignment. The characterization of the position estimation sensors (including global navigation satellite system and real-time kinematics) and flight controller is carried out using different UAVs (a DJI Matrice M600 Pro Hexacopter and Tarot X4 frame based Quadcopter) under different wind levels. Based on the experimental data, the performance of the sliding mode controller and the performance of the gimbal stabilization system are evaluated in a hardware-in-the-loop simulation environment (called ELISSA). Preliminary achievable control accuracies of the relative position and attitude of subsystems in the proposed concept are estimated based on experimental result

Robust and secure resource management for automotive cyber-physical systems

2022 Spring.Includes bibliographical references.Modern vehicles are examples of complex cyber-physical systems with tens to hundreds of interconnected Electronic Control Units (ECUs) that manage various vehicular subsystems. With the shift towards autonomous driving, emerging vehicles are being characterized by an increase in the number of hardware ECUs, greater complexity of applications (software), and more sophisticated in-vehicle networks. These advances have resulted in numerous challenges that impact the reliability, security, and real-time performance of these emerging automotive systems. Some of the challenges include coping with computation and communication uncertainties (e.g., jitter), developing robust control software, detecting cyber-attacks, ensuring data integrity, and enabling confidentiality during communication. However, solutions to overcome these challenges incur additional overhead, which can catastrophically delay the execution of real-time automotive tasks and message transfers. Hence, there is a need for a holistic approach to a system-level solution for resource management in automotive cyber-physical systems that enables robust and secure automotive system design while satisfying a diverse set of system-wide constraints. ECUs in vehicles today run a variety of automotive applications ranging from simple vehicle window control to highly complex Advanced Driver Assistance System (ADAS) applications. The aggressive attempts of automakers to make vehicles fully autonomous have increased the complexity and data rate requirements of applications and further led to the adoption of advanced artificial intelligence (AI) based techniques for improved perception and control. Additionally, modern vehicles are becoming increasingly connected with various external systems to realize more robust vehicle autonomy. These paradigm shifts have resulted in significant overheads in resource constrained ECUs and increased the complexity of the overall automotive system (including heterogeneous ECUs, network architectures, communication protocols, and applications), which has severe performance and safety implications on modern vehicles. The increased complexity of automotive systems introduces several computation and communication uncertainties in automotive subsystems that can cause delays in applications and messages, resulting in missed real-time deadlines. Missing deadlines for safety-critical automotive applications can be catastrophic, and this problem will be further aggravated in the case of future autonomous vehicles. Additionally, due to the harsh operating conditions (such as high temperatures, vibrations, and electromagnetic interference (EMI)) of automotive embedded systems, there is a significant risk to the integrity of the data that is exchanged between ECUs which can lead to faulty vehicle control. These challenges demand a more reliable design of automotive systems that is resilient to uncertainties and supports data integrity goals. Additionally, the increased connectivity of modern vehicles has made them highly vulnerable to various kinds of sophisticated security attacks. Hence, it is also vital to ensure the security of automotive systems, and it will become crucial as connected and autonomous vehicles become more ubiquitous. However, imposing security mechanisms on the resource constrained automotive systems can result in additional computation and communication overhead, potentially leading to further missed deadlines. Therefore, it is crucial to design techniques that incur very minimal overhead (lightweight) when trying to achieve the above-mentioned goals and ensure the real-time performance of the system. We address these issues by designing a holistic resource management framework called ROSETTA that enables robust and secure automotive cyber-physical system design while satisfying a diverse set of constraints related to reliability, security, real-time performance, and energy consumption. To achieve reliability goals, we have developed several techniques for reliability-aware scheduling and multi-level monitoring of signal integrity. To achieve security objectives, we have proposed a lightweight security framework that provides confidentiality and authenticity while meeting both security and real-time constraints. We have also introduced multiple deep learning based intrusion detection systems (IDS) to monitor and detect cyber-attacks in the in-vehicle network. Lastly, we have introduced novel techniques for jitter management and security management and deployed lightweight IDSs on resource constrained automotive ECUs while ensuring the real-time performance of the automotive systems

A long-range and long-life telemetry data-acquisition system for heart rate and multiple body temperatures from free-ranging animals

The system includes an implantable transmitter, external receiver-retransmitter collar, and a microprocessor-controlled demodulator. The size of the implant is suitable for animals with body weights of a few kilograms or more; further size reduction of the implant is possible. The ECG is sensed by electrodes designed for internal telemetry and to reduce movement artifacts. The R-wave characteristics are then specifically selected to trigger a short radio frequency pulse. Temperatures are sensed at desired locations by thermistors and then, based on a heartbeat counter, transmitted intermittently via pulse interval modulation. This modulation scheme includes first and last calibration intervals for a reference by ratios with the temperature intervals to achieve good accuracy even over long periods. Pulse duration and pulse sequencing are used to discriminate between heart rate and temperature pulses as well as RF interference

Advanced laboratory testing methods using real-time simulation and hardware-in-the-loop techniques : a survey of smart grid international research facility network activities

The integration of smart grid technologies in interconnected power system networks presents multiple challenges for the power industry and the scientific community. To address these challenges, researchers are creating new methods for the validation of: control, interoperability, reliability of Internet of Things systems, distributed energy resources, modern power equipment for applications covering power system stability, operation, control, and cybersecurity. Novel methods for laboratory testing of electrical power systems incorporate novel simulation techniques spanning real-time simulation, Power Hardware-in-the-Loop, Controller Hardware-in-the-Loop, Power System-in-the-Loop, and co-simulation technologies. These methods directly support the acceleration of electrical systems and power electronics component research by validating technological solutions in high-fidelity environments. In this paper, members of the Survey of Smart Grid International Research Facility Network task on Advanced Laboratory Testing Methods present a review of methods, test procedures, studies, and experiences employing advanced laboratory techniques for validation of range of research and development prototypes and novel power system solutions