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Agbor, Ikechukwu Wilson: Aperture Coupled Patch Antenna for Integration into Wearable Textile Systems Abstract: With the proliferation of wearable textiles for the purposes of wireless communications, the integration of antennas based on textile materials into textiles has become inevitable. Feed methods for these wearable antennas have become critical factors for optimum performance. The choice of the aperture coupled technique which couples its power into the antenna through an aperture in the ground plane as against a rigid coaxial feed meets the desired optimum operation. A discourse on an aperture coupled Antenna that is integrated into wearable textile systems will be robustly presented Babu, Sachin: A Study Of Guided Mode Resonance With Applications Towards High‐Sensitivity Optical Strain Sensors Abstract: High‐sensitivity optical strain sensors are a promising solution for measuring small strains. The principle of operation behind such devices is called guided mode resonance. In this presentation, the theory of guided mode resonance will be reviewed; a theoretical model, along with simulations, of such an optical strain sensor will be presented; and methods for fabricating, characterizing, and improving the sensitivity of such a device will be discussed. Chen, Jianfei: Mode‐locking of diode lasers Abstract: Short pulse lasers are widely used in industry, medicine, and military, such as the generation of Terahertz radiation, the corneal surgery and photonic sampling. The technique to produce short pulses of picosecond or femtosecond duration is mode locking. The basis of this technique is to induce a fixed‐
phase relationship between the longitudinal modes of the laser’s resonated cavity. Usually there are three methods to produce mode‐locking in a laser: the active method, the passive method and the hybrid method. Active methods typically involve using an external signal to induce a modulation of the intracavity light while passive methods rely on placing some element into the laser cavity which causes self‐modulation of the light without using an external signal. The hybrid methods are the combinations of the active and passive methods. This talk will describe mode‐locking of diode lasers. Discussing theory and limiting factors. The behavior of pulse width, output power and timing jitter will also be discussed. Finally, I will review some results in ultra‐short mode‐locked pulse generation which have been reported in the literature. Dong, Shenggang: High‐speed pipeline ADC design Abstract: J. Wu, A. Chou, C.‐H. Yang, Y. Ding, Y.‐J. Ko, S.‐T. Lin, W. Liu, C.‐M. Hsiao, M.‐H. Hsieh, C.‐C. Huang, J.‐J. Hung, K. Y. Kim, M. Le, T. Li, W.‐T. Shih, A. Shrivastava, Y.‐C. Yang, C.‐Y. Chen, and H.‐S. Huang, “A 5.4GS/s 12b 500mW Pipeline ADC in 28nm CMOS,” in Symp. VLSI Circuits Dig., 2013, pp. 92‐93. “A 5.4GS/s 12b 2‐way interleaved pipeline ADC is presented. To achieve high speed, a complementary switched‐capacitor amplifier is proposed, along with ping‐pong amplifier sharing and digital MDAC equalization. The ADC achieves 61dB SNR and 57dB THD up to 2.6GHz input frequency at 5.4GS/s, consumes 500mW and occupies 0.4mm2 area in 28nm CMOS.” Fang, ei: Channel Property of millimeter wave mobile communications for 5G Abstract: " The global bandwidth shortage facing wireless carriers has motivated the exploration of the underutilized millimeter wave (mm‐wave) frequency spectrum for future broadband cellular communication networks. There is, however, little knowledge about cellular mm‐wave propagation in densely populated indoor and outdoor environments. Obtaining this information is vital for the design and operation of future 5th generation cellular networks that use the mm‐wave spectrum. In this paper, the authors present the motivation for new mm‐wave cellular systems, methodology, and hardware for measurements and offer a variety of measurement results that show 28 and 38 GHz frequencies can be used when employing steerable directional antennas at base stations and mobile devices ". Ganguly, Anshuman: Parallel Feedback Delayless Sub band Active Noise Control with Signal Decomposition techniques Abstract:
This presentation presents a detailed overview of the Delayless Subband based Parallel Feedback Active
Noise Control method using Signal Decomposition (PAFANC-SD) techniques. Effort has been made to
illustrate and explain several Signal Decomposition (SD) techniques using subspace based method and
adaptive linear prediction (ALP) to decompose the noisy error signal into dominant periodic component
and residual random component. Separate Feedback Subband NLMS based adaptive algorithms are
employed to control each component effectively in parallel. Mathematical framework, performance
analysis and computational complexity are also presented for each proposed PAFANC-SD method.
Proposed method is capable of controlling broadband and non-stationary noise more effectively as
compared to traditional Parallel Feedback algorithms.
Index Terms— Active noise control, adaptive signal processing, linear prediction, Subband filtering,
NLMS.
Hashmi, Umair Sajid: Implementation of Sphere Decoding Algorithm on NI USRPs Abstract:
Multiple Input Multiple Output (MIMO) in conjunction with Orthogonal Frequency Division Multiplexing (OFDM) is the key technology employed in modern and next generation wireless networks such as IEEE 802.11n, 3GPP‐LTE and mmWave communications. My research started from the performance analysis of channel equalization / decoding schemes in terms of BER and complexity. Simulations were carried for QPSK constellation on different Tx/Rx combinations and it is seen that amongst the heuristic algorithms, the Maximum Likelihood algorithm is superior to other exact methods such as Zero Forcing, Minimum Mean Square Error estimation, Decision‐Feedback Equalization (with/ without Optimal Ordering). The trade‐off for superior ML performance lies in the exhaustive search for all combinations of inputs with exponential complexity. The focus of our research is on implementation of Sphere Decoding algorithm which matches BER performance with reduced computational complexity. The integer least‐squares problem of ML scheme is carried out on a limited number of lattice points which fall within sphere of a defined radius. The premise underlying the Sphere Decoding Algorithm lies in the upper triangular nature of the matrix R formed as a result of QR decomposition of channel matrix H which converts the lattice search problem into a Tree‐Search problem. The complexity can then be translated as the total number of nodes visited in the tree before finding the optimal results. We have simulated 2 different implementations of Sphere Decoding algorithms already discussed in literature. The results although similar show similar BER performance as ML but different complexity behavior as the noise variance σ2 changes. We intend to implement these decoding algorithms for 2x2 MIMO implemented using NI USRPs and compare the results with the theoretical simulations. Hu, Bo: “Neural Acceleration for General‐Purpose Approximate Programs” Abstract: This paper describes a learning‐based approach to the acceleration of approximate programs. We describe the Parrot transformation, a program transformation that selects and trains a neural network to mimic a region of imperative code. After the learning phase, the compiler replaces the original code with an invocation of a low‐power accelerator called a neural processing unit (NPU). The NPU is tightly coupled to the processor pipeline to accelerate small code regions. Since neural networks produce inherently approximate results, we define a programming model that allows programmers to identify approximable code regions code that can produce imprecise but acceptable results. Offloading approximable code regions to NPUs is faster and more energy efficient than executing the original code. For a set of diverse applications, NPU acceleration provides wholeapplication speedup of 2.3× and energy savings of 3.0× on average with quality loss of at most 9.6%. Kalidas, Vignesh: Transient ST‐Segment Episode detection for ECG beat callification Abstract: Sudden Cardiac Death (SCD) is an unexpected death caused by loss of heart function when the electrical impulses fired from the ventricles become irregular. Most common SCDs are caused by cardiac arrhythmias and coronary heart disease. They are mainly due to Acute Myocardial Infarction (AMI), myocardial ischemia and cardiac arrhythmia. This paper aims at automating the recognition of ST‐
segment deviations and transient ST episodes which helps in the diagnosis of myocardial ischemia and also classifying major cardiac arrhythmia. The approach is based on the application of signal processing and artificial intelligence to the heart signal known as the ECG (Electrocardiogram). The paper proposes an improved morphological feature vector including ST‐segment information for heart beat classification by supervised learning using the support vector machine approach. The system has been tested and yielded an accuracy of 93.33% for the ST episode detection on the European ST‐T Database and 96.35% on MIT‐BIH Arrhythmia Database for classifying six major groups, i.e. Normal, Ventricular, Atrial, Fusion, Right Bundle and Left Bundle Branch Block beats. Li, Changyuan: Teleoperation of multi‐robot networks Abstract: When robot are controlled remotely by teleoperation, a time delay occurs as a result of long range data transmission. This time delay will affect the stability and other performance especially for systems with bilateral control, collision avoidance, formation control and tracking. There are some methods for maintaining stability and other performance of a system when it’s affected by the time delay. In this presentation, a few of the methods will be introduced and compared. Meng, Xin: Gallium Nitride High Electron Mobility Transistor Power Device Abstract:
Wide application of power rectifier/switch in smart phone, tablet, wireless base station and
automotive electronics attracts a surge of interest on power device in the past decade. For the
last three decades, silicon power devices (diode, thyristor, MOSFET, Insulated Gate Bipolar
Transistor “IGBT”, etc) have dominated the power device market. However, demanding
requirements (high power, high frequency, high temperature, low on-resistance and
miniaturization, etc) for next-generation application push conventional silicon power devices to
approach the limit. Wide band-gap semiconductors such as silicon carbide (SiC) & gallium
nitride (GaN) are acknowledged as ideal candidates due to high critical field and high saturation
electron velocity.
Interestingly, compared to costly silicon carbide, GaN demonstrates much higher carrier
concentration and electron mobility due to the ability to fabricate HEMT device with reduced
ionized impurities scattering. The combination of high carrier concentration and high electron
mobility results in a high current density and a low channel resistance, which are especially
important for high frequency operation and power switching applications.
Though with intrinsic advantages, GaN HEMT power devices still face great challenges
related to the techniques for normally-off operation with large threshold voltage, development of
new device architectures, gate scaling, substrate costs, thermal management, degradation
modes and mechanisms not yet fully understood, that today are limiting the market penetration
of GaN HEMT power device. In this presentation, fundamentals of GaN materials and GaN
HEMT device will be reviewed. Key parameters (figure of merit, power-added efficiency (PAE), on-state resistance, etc) relevant to power device performance will be summarized as well.
More specifically, challenges (“normally-on” operation, current collapse, etc) and innovative
solutions including our preliminary proposals to realize enhancement-mode GaN HEMT device
are discussed.
Momson, Ibukunoluwa Adedapo: ‘A 1.2 nJ/b, 2.4 GHz Receiver with a Sliding‐IF Phase‐to‐Digital Converter for Wireless Personal/Body‐
Area‐Networks’ Abstract: The paper presents an ultra‐low‐power (ULP) 2.4 GHz receiver for short‐range wireless personal and body‐area networks. As such applications are usually battery powered, and the RF transceiver typically consumes up to 90% of the total energy, the primary design goal is to extend operation lifetime through improved energy efficiency, expressed as power consumption/data‐rate (J/bit). Ogunmolu, Olalekan Patrick: A Real‐Time Surface Image‐Guided Soft Robotic Patient Positioning System for Maskless Head‐and‐Neck Cancer Radiotherapy Abstract:
Due to positioning inaccuracies in head and neck cancer radiotherapy, high conformal doses delivered to
patients have been reported to cause loco-regional failures and toxicity due to dose deviation from the
treatment plan. We present a novel solution using position-based visual-servoing of a radio-transparent
soft robot to control a patient's head-and-neck flexion/extension motion during frameless image-guided
radiotherapy. The soft robot combines an inflatable air bladder, two proportional solenoid valves and an
air compressor. We show that automated positioning is possible using a Microsoft Kinect 3D camera for
head position monitoring/feedback and a National Instruments myRIO microcontroller to process image
data and generate control signals. The approach consists of two stages: first, we stream depth images from
the Kinect Sensor, segment the patient head, then collect unique head feature points for position
estimation; second, to implement the actuation mechanism, estimated head position is used as feedback
on the RIO in a cascade and feedforward control scheme.
Our validation model is a mannequin head with a ball-joint neck resting on a single air bladder. Initial
results show the system is capable of tracking a steady state set-point value to within 12%. This
establishes a proof-of-concept solution that can deliver optimal treatment irrespective of anatomic
deformations. Future efforts include refining the system model for the bladder, developing a more
accurate and robust controller, and incorporating multiple bladders to achieve multi-axis positioning of
the patient’s head.
Patil, Devendra Ramesh:
A magnetically enhanced wireless power transfer system for compensation of misalignment in mobile charging platforms Abstract: Misalignment in wirelessly charged electric vehicles is unavoidable as perfect alignment of the pickup coil on the electric vehicle with respect to transmitter is quite difficult. Notably, even a small coil misalignment leads to significant reduction of the effective coupling. Due to which this problem is of quite significance for maintaining high efficiency over the complete misalignment range. This work proposes a two auxiliary coil solution for compensating misalignment in lateral and longitudinal directions. Two auxiliary coils are mounted on the receiver; both auxiliary coils are mounted perpendicular to each other. Auxiliary coil mounted on lateral direction compensates the drop in voltage due to lateral misalignment and auxiliary coil mounted on longitudinal direction compensates for drop in voltage due to longitudinal misalignment. Output of both auxiliary coils is then connected to the respective rectifier and the outputs of rectifiers are connected in series. Total addition of voltage due to auxiliary coils and receiver coils is provided to the load. Qaradaghi, Vahid: Thermal piezoresistive transduction in micro scale resonant structures Abstract:
Thermal actuation is one of the most conveniently implementable mechanisms widely used in
microelectromechanical systems (MEMS). Operation of such actuators is typically based on thermal
expansion through Joule heating upon passing a current through an actuator element. Different versions of
thermally actuated micromechanical resonators coupled to electrostatic actuators are utilized as highly
sensitive force/displacement sensors. The force generated by the actuator strains the associated resonator
changing its resonant frequency. The presentation will includes fabrication, characterization, and
modeling of micro/nanoelectromechanical resonators actuated using thermal forces with piezoresistive
readout. It will include principle, operation and modeling of thermal piezoresistive transduction. Ranjan, Shivesh: I‐vectors based Gender Identification for Severely Noisy Data Abstract: An automatic gender identification approach, based only on speech, can serve a plenitude of purposes like: improving speaker independent speech recognition accuracy; help in identifying salient features for male/female speech synthesis; help in identifying and implementing acoustic features best suited for a variety of speech based strategies for age identification, accent identification, and speaker health identification. Motivated by prior works on gender identification using Gaussian Mixture Model – Universal Background Model (GMM‐UBM), this work proposes to use an I‐vector based approach to gender identification. Within the I‐vector framework, clean gender‐labeled Fisher English (FE) data is first used to train the total variability matrix (T matrix). Subsequently, the T matrix is used to extract the I‐vectors for the test utterances, followed by a Probabilistic Linear Discriminant Analysis (PLDA) back‐
end scoring, to perform gender identification. The results indicate a very high classification accuracy of 97.65 on FE test utterances, and an Equal Error Rate (EER) of 2.30. Gender Identification results are also reported for the severely degraded Robust Automatic Transcription of Speech (RATS) corpora test utterances, where the setup is able to achieve an appreciable accuracy of 76.48 at an EER of 20.89, without using any labeled RATS development data. To overcome the lack of any development data for the RATS test utterances, a novel unsupervised domain adaptation strategy is also presented that utilizes unlabeled RATS data to adapt the PLDA parameters derived from the FE training data. The strategy is able to offer a 6.8% relative improvement in classification accuracy, with a 14.75% relative reduction in the EER for the RATS test utterances. Ren, Jiajun: A 10GS/s 6 b Time‐Interleaved Partially Active Flash ADC Abstract: This qualifying exam presentation will discuss the following paper: X. Yang and J. Liu, “A 10GS/s 6 b Time‐Interleaved Partially Active Flash ADC,” IEEE Trans. Circuits Syst. I, vol. 61, no. 8, pp. 2272‐2280, Aug. 2014. “A 10 GS/s 6 b four‐way time‐interleaved ADC prototype in 65 nm CMOS demonstrated that this new ADC architecture offers better power efficiency than traditional ADC architectures in the 10 GS/s speed range. Various considerations towards high‐speed ADC designs are discussed including a proposed source‐follower based boot‐strap track‐and‐hold circuit to reduce input kickback and improve the ADC bandwidth. Also discussed is the generation and skew calibration of the four‐phase clocks for the interleaved channels to improve the ADC effective resolution at high input frequencies. By deriving the four‐phase clocks from a Nyquist frequency input clock through pass gates, accurate timing skew calibration is achieved through a simple duty cycle correction. Measured SNDR is 34.3 dB at low input frequencies and 32.0 dB at the Nyquist input frequency. The ADC including the input clock buffer consumes 83 mW with a FOM of 197 fJ/cs.” Vyas, Pratik B: Approach to Room Temperature Integrated Quantum Devices in Silicon CMOS Abstract: The 2011 International Technology Roadmap for Semiconductors (ITRS) challenges the CMOS industry with very aggressive targets well beyond state‐of‐the‐art capabilities in high frequency operation, very high precision/speed analog‐digital conversion, and extremely low noise performance. It is dubious whether the evolution of presently cutting‐ edge semi‐classical CMOS devices will be able to achieve such challenging goals. Going off the standard semi‐classical CMOS research path, it has been known for decades that exploiting explicitly quantum charge transport through quantized states can leapfrog past semi‐ classical performance limits. However, manifesting quantum transport behavior has traditionally required heterostructures using III‐V and Si/Ge semiconductors, often at cryogenic temperatures, which are incompatible with the needs of Si CMOS, the dominant segment of the semiconductor industry. This proposed research aims to demonstrate a path towards room temperature quantum Si CMOS devices fabricated using industrially accepted CMOS processing standards. The research will involve fabrication as well as theoretical interpretation of a new class of CMOS devices – quantum well CMOS transistors – specially designed to introduce explicit quantum transport characteristics into transistor operations. Quantum mechanical simulation of electron transport in these devices will be done to generate a data‐
tested predictive device model that can help develop explicit device designs that maximize visible quantum behavior. Zhang, Chunlei: i‐Vector Based Physical Task Stress Detection with Different Fusion Strategies Abstract: Stress is an external fact that impacts speech production when people produce speech. Only addressing noise is not sufficient to overcome performance loss in stressful scenarios for robust speech systems, even if noise is eliminated completely. Speech production variability introduced by stress or emotion can severely degrade speech/speaker recognition performance. And it’s a common scenario that people produce speech under physical task. Variability introduced by physical task stress degrade the performance of most speech systems. Detection of paralinguistic information, such as physical task load, gender and cognitive load can guide human computer interaction systems to automatically understand and adapt to different users and also can be used to increase the performance of speech systems including spoken dialog system, stress level classification and emotion state surveillance. Due to great importance of stress detection in practical speech applications, more and more attention has been drawn in the past decade. Inspired by nonlinear speech production model, TEO based features have been well known to represent traits of stressed state by reflecting variability in the excitation. Linear speech production model based features such as MFCCs are still effective since these features carry excitation characteristics. In INTERSPEECH 2014 Computational Paralinguistic Challenge, low‐level descriptors (LLD) features via OpenSMILE extractor were generated as input of baseline system, which has been widely used in emotion recognition tasks. Speaker recognition systems based on i‐Vector extraction and PLDA classifier are able to obtain relatively high accuracy and become a mainstream framework for speaker identification (SID) tasks. When it comes to physical stress detection, few work are published using i‐Vector‐PLDA based systems. In this study, we present a method for detecting physical task stress from speech. We employ UT‐Scope corpus for system development and experimental evaluation. A state‐of‐the‐art i‐Vector framework is investigated with MFCCs and our previously formulated TEO‐CB‐Auto‐Env features for neutral/physical stress detection. MFCCs and TEO‐CB‐Auto‐Env features are believed to have complementary effect on physical stress detection task for the reason that MFCCs are derived from a linear speech production model and TEO‐CB‐Auto‐Env features are from nonlinear model. Performance on MFCCs and TEO‐CB‐
Auto‐Env features are given respectively. A fusion of these features in i‐Vector level is considered to supplement performance since MFCCs and TEO‐CB‐Auto‐Env are derived from different speech production models. We also propose a score level fusion approach using Adaboost, which further improves both accuracy and EER of the whole system. Zhu, Hanqi: Challenges and Researches in High Performance Powered Lower Limb Orthoses (PLLO) Abstract: Powered Lower Limb Orthoses (PLLO) is an innovative kind of wearable rehabilitation robot to improve quality of life for patients with lower limb disabilities. Shown by early stage research and clinic application, PLLO have potential to accelerate the rehabilitation process for patients. With increased patients with lower limb disabilities in United States, like stroke and spine injury, it is no doubt that PLLO will become an important part of future clinic therapy for lower limb disabilities treatment and have great value in its commercial application. Due to recent advances in torque control algorithms for PLLO and several clinical applications, the actuation system already become one limitation of high performance PLLO, include high torque density actuator and low level torque control algorithm. During my presentation, early stage researches and existed challenges of PLLO will be reviewed and analyzed to introduce the requirement of next generation high performance PLLO. Also, researches about Iterative Learning Controller (ILC), Axial Flux Permanent Magnetic Synchronous motor (AFPMSM) and motor drive methods will be discussed in the presentation to demonstrate several possible research directions to solve the existed engineering challenges of PLLO.