Programming Robotic Agents: A Multi-tasking Teleo-Reactive Approach

Keith Clark, Imperial College London
University of Queensland, University New South Wales
joint work with Peter Robinson, University of Queensland

2:00pm Friday, 2 October 2015, ITE325b

We present a multi-threaded/multi-tasking message communicating robotic agent architecture in which the concurrently executing tasks are programmed in TeleoR, a major extension of Nilsson’s Teleo-Reactive Procedures (TR) guard ~> action rule language for robotic agents.

The rule guards query rapidly changing percept facts, and more slowly changing told and remembered facts, using fixed facts, relation and function rules (the agent’s knowledge) in the agent’s deductive BeliefStore. Its operational semantics makes the languages well suited to robot/robot or human/robot co-operative tasks.

TeleoR extends TR in:

• being typed and higher order,
• having a typed higher order LP/FP language, QuLog, for encoding BeliefStore knowledge,
• having extra forms of rules and actions, and o having task atomic procedures to control the deadlock and starvation free sharing of several robotic resources by concurrently executing tasks.

Its use is illustrated in the video at http://bit.ly/teleor. It is being used at UNSW to write the control program for a two armed Baxter robot working in co-operation with a person concurrently engaged in several assembly tasks.

Keith Clark is Emeritus Professor of Computer Science at Imperial College London, England and a Visiting Professor at the University of Queensland and the University New South Wales. He has lectured in both mathematics and computer science.

Host: Tim Finin

Upcoming talks and directions

The UMBC CSEE Seminar Series Presents

 Capturing Brain Activity at Rest: Recent Development of Resting-State Functional MRI and Its Potential in Clinical Applications

Dr. Yihong Yang
Neuroimaging Research Branch
National Institute on Drug Abuse, NIH

12noon-1pm Friday, 2 Oct. 2015, ITE 102

There has been growing interest in the intrinsic brain activity at “rest” that may be used to reveal circuit-level information of brain functions. Alterations of resting-state brain activity have been implicated in various neurological and psychiatric disorders. In this seminar, the recent development of resting-state fMRI techniques will be introduced and discussed. Applications of these new imaging techniques in clinical applications such as cocaine addiction and traumatic brain injury will be demonstrated.

Dr. Yihong Yang received his Ph.D. in Biophysics, 1995, at University of Illinois at Urbana-Champaign, under Paul C. Lauterbur who share 2003 Physiology or Medicine Nobel price with Peter Mansfield on the development of MRI. He is currently a senior investigator and the chief of MR Imaging and Spectroscopy Section at NIDA. Dr. Yang has made significant contributions to the development of MRI methodology and application of neuroimaging techniques to neurological and psychiatric disorders. He has published over 130 original research papers in leading journals and contributed several book chapters in the fields of functional MRI, diffusion tensor imaging and MR spectroscopy, as well as applications of MRI technology to the assessment of brain disorders, particularly in drug addiction. He has served on many NIH Study Sections and other research foundations including Medical Research Council (UK), Alzheimer’s Association, and National Science Foundation of China (NSFC). He is an editorial board member of the Brain Connectivity and Open Neuroimaging Journal. He has trained many post-doctoral and pre-postdoctoral fellows in neuroimaging.

Hosts: Professors Fow-Sen Choa () and Alan T. Sherman ()

Appropriately Valuing Inter-Disciplinary Research
between Computer Science, Creativity and the Arts

Professor Celine Latulipe
Software and Information Systems
University of North Carolina at Charlotte

2:00pm Friday 2 October 2015, PAHB 132

Scientists and technologists conducting research in creativity and engaging with artists face political pressure to justify their work. A case study of the NSF-funded Dance.Draw project is used to illustrate the problematic aspects of pressure. I argue that a shift in dialogue is needed to appropriately value this type of inter-disciplinary research.

Dr. Celine Latulipe is an Associate Professor in the Department of Software and Information Systems in the College of Computing and Informatics at the University of North Carolina at Charlotte. Her research involves developing and evaluating novel interaction techniques, creativity and collaboration support tools and technologies to support the arts, and developing innovation computer science curriculum design patterns. Dr. Latulipe examines issues of how to support expression and exploration in complex interfaces and how interaction affordances impact satisficing behavior. She also conducts research into how to make computer science education a more social experience, both as a way of more deeply engaging students and as an approach to broadening participation in a field that lacks gender and racial diversity.

If you plan on applying to graduate school for next year or are currently a graduate student in your first or second year and are a US citizen or permanent-resident, you should consider applying to the National Science Foundation Graduate Research Fellowship Program (GRFP). This program makes approximately 2000 new fellowship awards each year.

The GRFP program recognizes and supports outstanding graduate students in NSF-supported science, technology, engineering, and mathematics disciplines who are pursuing research-based Master’s and doctoral degrees at accredited United States institutions. Fellows benefit from a three-year annual stipend of $32,000 along with a $12,000 cost of education allowance for tuition and fees, and opportunities for international research and professional development.

GRFP is the country’s oldest national fellowship program directly supporting graduate students in STEM fields. The hallmark features of the program are: 1) the award of fellowships to individuals on the basis of merit and potential, and 2) the freedom and flexibility provided to Fellows to define their own research and choose the accredited U.S. graduate institution that they will attend.

US citizens and permanent residents who are planning to enter graduate school in an NSF-supported discipline next fall, or in the first two years of such a graduate program, or who are returning to graduate school after being out for two or more years, are eligible. Applications for computing and engineering areas fields are due October 27. The applicant information page and the solicitation contain the necessary details.

Multi-Microphone Speech Enhancement

Sharon Gannot
Bar-Ilan University, Israel

1:30pm Wednesday, 14 October 2015, ITE 325B, UMBC

Microphone array algorithms emerged in the early 1990s as viable solutions to speech processing problems. However, the adaptation of beamforming methods to speech processing is still an open issue. There are many difficulties which arise from the characteristics of the speech signal and the acoustic environment. The speech signal is a wide-band and non-stationary signal. Very long room impulse responses (RIRs), which are several thousands of taps long, may be attributed to multiple reflections of the sound source on objects in the enclosure. Moreover, due to the inevitable movements of both sources (speakers) and receivers (microphones), the room impulse responses become time-varying.

In this talk, we will focus on spatial processors, a.k.a, beamformers, based on the linearly constrained minimum variance (LCMV) criterion, and its special case, the minimum variance distortionless (MVDR) beamformer. We show that classical beamformers that merely take into account angular information (as reflected by the so-called beam-pattern), are too simplistic to fully address the intricate propagation regime of the sound source in reverberant environment. We will therefore reformulate the LCMV beamformer in the shorttime Fourier transform (STFT) domain and substitute the free-field steering vector by the entire acoustic transfer function (ATF). The corresponding relative transfer function (RTF) will be then introduced, and its applicability to the design of beamformers in reverberant environments will be discussed. We will then elaborate on several blind RTF estimation techniques, e.g. based on subspace analysis, that enable the implementation of all necessary beamformer’s blocks. Several applications of the powerful LCMV beamformer, e.g. speech enhancement, extraction of desired speakers in multiple competing speaker environment, and binaural processing, will then be presented.

We will conclude the talk with an overview of the emerging field of distributed algorithms for ad hoc microphone arrays, and discuss the advantages and challenges they raise. The presentation will be accompanied by audio clips demonstrating the capabilities of the introduced schemes.

Sharon Gannot received his B.Sc. degree (summa cum laude) from the Technion-Israel Institute of Technology, Haifa, Israel in 1986 and the M.Sc. (cum laude) and Ph.D. degrees from Tel-Aviv University, Israel in 1995 and 2000 respectively, all in Electrical Engineering. In 2001 he held a post-doctoral position at the department of Electrical Engineering (ESAT-SISTA) at K.U.Leuven, Belgium. In 2002-2003 he held a research and teaching position at the Faculty of Electrical Engineering, Technion-Israel Institute of Technology, Haifa, Israel. Currently, he is a Full Professor at the Faculty of Engineering, Bar-Ilan University, Israel, where he is heading the Speech and Signal Processing laboratory and the Signal Processing Track. Prof. Gannot is the recipient of Bar-Ilan University outstanding lecturer award for 2010 and 2014. Prof. Gannot has served as an Associate Editor of the EURASIP Journal of Advances in Signal Processing in 2003-2012, and as an Editor of several special issues on Multi-microphone Speech Processing of the same journal. He has also served as a Guest Editor of ELSEVIER Speech Communication and Signal Processing journals. Prof. Gannot has served as an Associate Editor of IEEE Transactions on Speech, Audio and Language Processing in 2009-2013. Currently, he is a Senior Area Chair of the same journal. He also serves as a reviewer of many IEEE journals and conferences. Prof. Gannot is a member of the Audio and Acoustic Signal Processing (AASP) technical committee of the IEEE since Jan., 2010. He is also a member of the Technical and Steering committee of the International Workshop on Acoustic Signal Enhancement (IWAENC) since 2005. He was the general co-chair of IWAENC held at Tel-Aviv, Israel in August 2010. Prof. Gannot has served as the general co-chair of the IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA), New-Paltz, NY, USA in October 2013. Prof. Gannot was selected (with colleagues) to present a tutorial sessions in ICASSP 2012, EUSIPCO 2012, ICASSP 2013 and EUSIPCO 2013. His research interests include multi-microphone speech processing and specifically distributed algorithms for ad hoc microphone arrays for noise reduction and speaker separation; machine learning methods in speech processing; dereverberation; single microphone speech enhancement and speaker localization and tracking.

PhD Dissertation Defense Announcement
Electrical Engineering

Polarization-insensitive all-optical dual pump-phase trans-multiplexing from 2 × 10-GBd OOKs to 10-GBd RZ-QPSK using cross-phase modulation in a passive nonlinear birefringent photonic crystal fiber

Tanvir Mahmood

2:00pm Thursday, 24 September 2015, ITE325b

Considering the network size, bit rate, spectral and channel capacity limitations, different modulation formats may be selectively used in future optical networks. Although the traditional metropolitan area networks (MANs) still use the non-return-to-zero on-off keying (NRZ-OOK) modulation format due to its technical simplicity and therefore low cost, QPSK format is more advantageous in spectrally efficient long-haul fiber optic transmission systems because of its constant power envelope, and robustness to various transmission impairments. Consequently, an important problem may arise, in particular how to route the OOK-data streams from MANs to long-haul backbone networks when the state of polarization (SOP) of the remotely generated OOK is unpredictable. Hence, the focus of this dissertation was to investigate a polarization-insensitive (PI) all-optical nonlinear optical signal processing (NOSP) method that can be implemented at the network cross-connect (X-connect) to transfer data from a remotely and a locally generated OOK data simultaneously to more effectual QPSK format for long-haul transmission. By utilizing cross-phase modulation (XPM) and inherent birefringence of the device, the work demonstrated, for the first time, PI all-optical data transfer utilizing dual pump-phase transmultiplexing (DPTM) from 2 × 10-GBd OOKs to 10-GBd RZ-QPSK in a passive nonlinear birefringent photonic crystal fiber (PCF). Polarization insensitivity was achieved by scrambling the SOP of the remotely generated OOK pump and launching the locally generated OOK pump and the probe off-axis. To mitigate polarization induced power fluctuations and detrimental effects due to nearby partially degenerate and non-degenerate four wave mixings, an optimum pump-probe detuning was also utilized. The PI DPTM RZ-QPSK demonstrated a pre-amplified receiver sensitivity penalty < 5.5 dB at 10−9 bit-error-rate (BER), relative to the FPGA-precoded RZ-DQPSK baseline in ASE-limited transmission system. The effect of the remotely generated OOK pump OSNR degradation on the PI DPTM RZ-QPSK was also investigated and it was established that 10−9 BER metric was attainable till the remotely generated OOK pump reached the threshold OSNR limit of 34 dB/0.1nm. Finally, DWDM transmission performance of the PI DPTM RZ-QPSK signal was evaluated using a 138-km long recirculating loop and it was demonstrated that the PI DPTM RZ-QPSK can be transmitted over 1,500 km before it reached ITU-T G.709 7% HD-FEC overhead limit. This propagation distance was well beyond the transmission requisites of any typical metro network (≈ 600 km). Furthermore, it was demonstrated that, within the threshold limit, OSNR degradation of the remotely generated OOK pump had minimal impact on the transmission distance of the PI DPTM RZ-QPSK before it reached 7% HD-FEC overhead limit.

Committee: Drs. Gary M. Carter (Chair), Anthony M. Johnson, Fow-Sen Choa, Tinoosh Mohsenin, Thomas E. Murphy (ECE,UMCP), William Astar

Ph.D. Dissertation Proposal

Verifiable Randomness and its Applications

Christopher Vatcher

10:30am Thursday, 24 September 2015, ITE 325b

We propose to create a public verifiable randomness beacon, to integrate with the Random-Sample Voting system, constructed to be secure against adversaries who have even almost complete control over the system’s source of public randomness including the entropy source.

By verifiable randomness, we do not mean we can prove a sequence of bits to be random. Instead, verifiability means it is possible to prove: (a) a consumer used uniform bits originating from a specific entropy source and therefore cannot lie about the bits used; and (b) the bits used were unpredictable prior to their generation and, with overwhelming probability, were free of adversarial influence. This is in contrast to ordinary public randomness where parties must agree to trust some randomness provider, who becomes a target of corruption. Verifiable randomness is an enhancement of public randomness used to perform random selection in voting, conduct random audits, preserve privacy, generate random challenges for secure multi-party computation, and public lottery draws. Random-Sample Voting specifically requires verifiable randomness for random voter selection and random audits.

Our work extends the work of Eastlake and Clark and Hengartner by considering (a) adversaries who have fine control over the entropy source and (b) physical entropy sources, which we can make verifiable.

Our specific aims include (a) creating adversary models for three entropy source abstractions based on trusted providers, sensor networks, and distributed proof-of-work systems; (b) create a verifiable random beacon that integrates each model; (c) integrate our work with the Random-Sample Voting system; and (d) integrate with NIST’s beacon and propose a verifiable randomness standard based on our work.

Our method is to weaken the trust assumption on the entropy source by introducing verifiable entropy sources, which have mechanisms for limiting adversarial influence and accumulating evidence that their outputs obey a known distribution. Combined with an appropriate randomness extractor, we can generate verifiable random bits. Using sources like weather, we will construct a verifiable randomness beacon: a public randomness provider unencumbered by generous and often unfounded trust assumptions. Such a beacon can serve as a singular gateway for accessing and aggregating multiple entropy sources without compromising the randomness provided to consumers.

Committee: Drs. Alan T. Sherman (Chair), Konstantinos Kalpakis, Weining Kang (Math/Stat), David Chaum (Random-Sample Voting), Aggelos Kiayias (University of Athens)

The UMBC CSEE Seminar Series Presents

Technical challenges and opportunities
in studying the brain’s network activity

Dr. Hanbing Lu
National Institute of Drug Abuse, NIH

12:00-1:00pm, Friday 25 September 2015, ITE 325b

Brain structures do not work in isolation; they work in concert to produce sensory perception, motivation and behavior. Recent advances in fMRI technology offer the opportunity to investigate brain’s network activity. Data are accumulated suggesting that dysregulations within and between network activity are implicated in a number of neurodegenerative and neuropsychiatric disorders, including Alzheimer’s disease and drug addiction. Despite wide application of this approach in systems neuroscience, the fundamentals of brain network activity remain poorly understood. Animal models permit invasive manipulations and are uniquely advantageous in this regard. In this talk, Dr. Lu will discuss technical challenges and opportunities in studying brain networks by integrating multiple modalities, including MRI, electrophysiological recording, optical and electromagnetic neural modulation.

Dr. Hanbing Lu received his doctorate training in Biophysics at the Medical College of Wisconsin, during which he developed hardware and imaging sequence for functional magnetic resonance imaging (fMRI) in rodents. He is currently a staff scientist in the Neuroimaging Research Branch, National Institute on Drug Abuse, NIH. Dr. Lu pioneered animal models to investigate brain’s large scale networks. Current efforts include integrating multiple modalities to better understand the neurobiology of brain’s network activity

Hosts: Professors Fow-Sen Choa () and Alan T. Sherman ()

· More talks and directions ·

PhD Dissertation Proposal

Secured Embedded Many-Core Accelerator for Big Data Processing

Amey Kulkarni

2:00-4:00pm Friday, 18 September 2015, ITE 325b

I/O bandwidth and stringent delay constraints on processing time, limits the use of streaming Big Data for a large variety of real world problems. On the other hand, examining Big Data in applications such as intelligence, surveillance and reconnaissance unveils sensitive information in terms of hidden patterns or unknown correlations, thus demanding secured processing environment. In this PhD research, we propose a scalable and secured framework for a many-core accelerator architecture for efficient big data parallel processing. We propose to merge a compressive sensing-based framework to reduce IO Bandwidth and a machine learning-based framework to secure many-core communications. Four different reduced complexity architectures and two different modifications to Orthogonal Matching Pursuit (OMP) compressive sensing reconstruction algorithm are proposed. We implement the proposed OMP architectures on FPGA, ASIC, CPU/GPU and Many-Core to investigate hardware overhead cost. To secure communications within many-core, we propose two different machine learning-based Trojan detection framework which have minimal hardware overhead. To conclude this work, we aim to implement and evaluate the proposed scalable and secured many-core accelerator hardware for image and multi-channel biomedical signal processing on quad-core and sixteen-core architectures.

Committee: Drs. Tinoosh Mohsenin, (Chair), Mohamed Younis, Seung-Jun Kim, Farinaz Koushanfar (Rice University) and Houman Homayoun (George Mason University)

The UMBC CSEE Seminar Series Presents

Optical Measurements and Devices for Biotechnology and Biomedicine

Dr. Yordan Kostov

Assistant Director, Center for Advanced Sensor Technology, UMBC

12-1pm Friday, 18 September 2015
ITE 102 (Lecture Hall VIII)

A variety of approaches for measurement of bioprocess and biomedical variables are presented. Classical optical measurements (fluorescence, absorption, decay time, etc.) are employed together with miniaturized versions of benchtop spectroscopy equipment to measure a number of bioprocess variables (pH, DO, protein concentration, etc.).  Similar approach allows for measurement of biomedical parameters (transcutaneous O2 and CO2, glucose). The sensing is made possible by the developed miniaturized versions of lab equipment, use of microfluidics and actuation, as well as the use of proper data processing coupled with customizable user interface. A number of examples will be given.

Dr. Yordan Kostov holds an M.Sc. in Electrical engineering from Odessa Polytechnical Institute (Ukraine) and a combined Ph.D. Degree in ChemE./EE from Bulgarian Academy of Sciences. He has industry experience as electronic technology engineer. In his doctoral studies, he focused on optical sensing of biomedical parameters, and pursues this line of research ever since. Currently, he is Assistant Director of the Center for Advanced Sensor Technology at UMBC and Adjunct Professor at CSEE. His main interests are in the area of Biomedical measurements and devices.

Hosts: Professors Fow-Sen Choa () and Alan T. Sherman ()