CS Seminars

Wednesday February 1, 2012 -- 1:30pm in TBD

Teruhisa Misu, NICT

Title: Speech-based Interactive Information Guidance System Using Question-Answering Technique

Abstract: In this talk, a speech-based interactive guidance system based on document retrieval and presentation will be addressed. In conventional audio guidance systems, such as those deployed in museums, the information flow is one-way and the content is fixed. To make the guidance interactive, we prepare two modes, a user-initiative retrieval/QA mode (pull-mode) and a system-initiative recommendation mode (push-mode), and switch between them according to the user's state. In the user-initiative retrieval/QA mode, the user can ask questions about specific facts in the documents in addition to general queries. In the system-initiative recommendation mode, the system actively provides the information the user would be interested in. We implemented a navigation system containing sightseeing information. The effectiveness of the proposed techniques was confirmed through a field trial by a number of real novice users.

Teruhisa Misu received the B.E. degree in 2003, the M.E. degree in 2005, and the Ph.D. degree in 2008, all in information science, from Kyoto University, Kyoto, Japan. From 2005 to 2008, he was a Research Fellow (DC1) of the Japan Society for the Promotion of Science (JSPS). In 2008, he joined NICT Spoken Language Communication Group. His research interests include spoken language processing for spoken dialogue system, in particular dialogue modeling and management, question-answering, language modeling for speech recognition.

POSTPONED: Date to be determined

Sarala Arunagiri, Department of Computer Science, UTEP

Title: FAIRIO: An Algorithm for Differentiated I/O Performance

Abstract: Providing differentiated service in a consolidated storage environment is a challenging task. To address this problem, we introduce FAIRIO, a cycle-based I/O scheduling algorithm that provides differentiated service to workloads concurrently accessing a consolidated RAID storage system. FAIRIO enforces proportional sharing of I/O service through fair scheduling of disk time. During each cycle of the algorithm, I/O requests are scheduled according to the weights and disk-time utilization history of workloads. Experiments, which were driven by the I/O request streams of real and synthetic I/O benchmarks and run on a modified version of DiskSim, provide evidence of FAIRIO's effectiveness and demonstrate that fair scheduling of disk time is key to achieving differentiated service. In particular, the experimental results show that, for a broad range of workload request types, sizes, and access characteristics, the algorithm provides differentiated storage throughput that is within 10% of being perfectly proportional to workload weights; and, it achieves this with little or no degradation of aggregate throughput. The core design concepts of FAIRIO, including service-time allocation and history-driven compensation, potentially can be used to design I/O scheduling algorithms that provide workloads with differentiated service in storage systems comprised of RAIDs, multiple RAIDs, SANs, and hypervisors for Clouds.

This talk is based on a paper that won the best paper award for the software track of the International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD11). It will be presented at the conference in Vitoria, Espirito Santo, Brazil at the end of October 2011.

Monday January 30, 2012 -- 3:30 PM (Room TBD)

Malcom Gethers, Faculty Candidate

Title: An Inductive Framework to Support Software Maintenance

Abstract: Software maintenance and evolution is a particularly complex phenomenon in case of long-lived, large-scale systems. It is not uncommon for such systems to progress through years of development history, a number of developers, and a multitude of software artifacts including millions of lines of code. Therefore, realizing even the slightest change may not always be straightforward. Clearly, changes are the central force driving software evolution. Therefore, it is not surprising that a paramount effort has been (and should be) devoted in the software engineering community to systematically understanding, estimating, and managing changes to software artifacts. This effort includes the three core change related tasks of (1) concept or feature location - locating where a particular functionality is implemented in a code or a starting point of a change, (2) impact analysis/traceability link recovery - identifying which other software artifacts should be changed given an initial software artifact, and (3) expert developer recommendations - identifying who are the most experienced developers to implement needed changes. Our work defines a framework for an integrated approach to support three core software maintenance and evolution tasks: feature location, software change impact analysis, and expert developer recommendation. The approach is centered on the combinations of the conceptual and evolutionary relationships latent in structured and unstructured software artifacts. Information Retrieval (IR) and Mining Software Repositories (MSR) based techniques are used for analyzing and deriving these relationships. All the three tasks are supported under a single, common framework by providing systematic combinations of MSR and IR analyses on single and multiple versions of a software system. This combining ability sets it apart from previously reported relevant solutions in the literature.

Thursday January 26, 2012 -- 3:30 PM CCS Building G.0208

Collin McMillan, Faculty Candidate

Title: Searching, Selecting, and Synthesizing Source Code Components

Abstract: As programmers develop software, they instinctively sense that source code exists that could be reused if found -- many programming tasks are common to many software projects across different domains. Oftentimes, a programmer will attempt to create new software from this existing source code, such as third-party libraries or code from online repositories. Unfortunately, several major challenges make it difficult to locate the relevant source code and to reuse it. In this talk, I will discuss these challenges and our work in source code search and reuse. Our work relies on structural information such as function calls and Application Programming Interface (API) usage to locate relevant source code, which can be reused in programmers' projects.

Tuesday Jan. 24, 2012 -- 5:00 PM
Undergraduate Learning Center Rm 116

Part of the UTEP Centennial Lecture Series, hosted by President Diana Natalicio and the Department of Computer Science

Richard Talbot, Director, Product Line Management of the IBM Power Systems

Title:Beyond Jeopardy! Putting Watson to Work

Abstract: IBM Watson is an artificial intelligence system capable of answering questions posed in natural language-with precision, confidence and speed. Named after IBM's founder and first president, Thomas J. Watson, the supercomputer is one of the most advanced systems on Earth and was developed by an IBM Research team of 25 scientists. In an historic event, in February 2011, Watson competed on Jeopardy! against the TV quiz show's two most renowned champions, delivered a stellar performance and captured the world's imagination. The IBM Jeopardy! Challenge represented a major milestone in the development of artificial intelligence systems, and was highlighted in IBM's centennial celebration this year as a showcase for its commitment to research and tradition of Grand Challenges. While the Grand Challenge for this IBM Research team was winning the three game Jeopardy! tournament, IBM's bigger vision for Watson targets the development of broadly applicable, commercial technologies capable of digesting a variety of structured and unstructured information and responding with precise answers to questions posed in natural language. IBM has now challenged itself to successfully migrate Watson's sophisticated analytics capabilities to solving real world challenges in Healthcare, Finance, Banking and other industries. Richard Talbot, Director, IBM Power Systems will be presenting highlights of this exciting IBM Research program and delving into present and future business implications of the DeepQA and Natural Language Processing technologies behind Watson. After the presentation, a panel of business and research leaders from the El Paso community will discuss future implications of these exciting new technologies.

Biography: Tichard Talbot currently serves as Director, Product Line Management of the IBM Power Systems business. In this role, he leads development of portfolio definition, business planning and successful world-wide introduction of IBM's next generation Power platforms. His team contributes to the achievement of all Power Systems' business and quality objectives and helped grow this IBM business unit to #1 market share leadership.
Most recently, Richard has been working on the IBM leadership team responsible for transitioning Watson from the game show circuit to solving real world problems in healthcare, financial services, government citizen services and many other industries. He is personally involved in the development of several Watson pilot applications and works frequently with clients to understand how these new analytics and natural language processing technologies can help address their most complex business challenges and accelerate their delivery of new services and offerings. His interests also include developing broad scale IBM partnerships within the healthcare industry and university alliances for the deployment of these new technologies to accelerate the development of new treatment options and cures for complex disease processes.
Richard is an IBM Executive and PMI Certified Project Manager, holds five U.S. Patents and has received several awards in management excellence, business and technical achievement. Prior to this role, he held a number of management and software development roles since starting with IBM in Boca Raton, Florida.
Richard received his Master's degree in Electrical Engineering from the University of Texas in Austin and BA from Rice University. He currently resides with his family in Austin, Texas and remains active in several charitable and community service organizations.

Monday January 23, 2012 -- 10:00 AM in OLD CS Building Rm 321

Kristen Brent Venable, Faculty Candidate

Title: Sequential aggregation of compact preferences

Abstract: We consider scenarios where a set of agents needs to select a common decision from a set of possible decisions, over which they express their preferences. We also assume that such a decision set has a combinatorial structure, that is, that each decision can be seen as the combination of certain features, where each feature has a set of possible instances. This occurs in several AI applications, such as combinatorial auctions, web recommender systems, and configuration systems. Even if the number of features and instances is small, the number of possible decisions can be very large.Fortunately, in the presence of such a combinatorial structure, agents may describe their preference in a compact and efficient way, using one of the several formalisms available in the literature, such as, for example soft constraints and CP-nets. We consider a sequential procedure that chooses one candidate by asking the agents to vote on one feature at a time. We investigate this approach to preference aggregation from a computational social choice point of view. In particular, we study when and if desirable properties, such as, for example, anonymity, strategy-proofness and resistance to bribery hold.

Tuesday December 6, 2011 -- 2:00pm in CS 308 (NOTE special day and time)

Timo Baumann, Uni Hamburg

Title: Real-time End-to-end Incrementality in Spoken Dialog Systems

Abstract: Current spoken dialogue systems are not yet suitable for natural, conversational dialogue for a number of reasons. One of these is a lack of responsiveness. A way to overcome this shortcoming is incremental processing, that is, processing of user input while it is still ongoing. However, processing delays must be kept to a minimum in order to allow for advanced dialog behaviour such as giving feedback during a user's turn, interrupting, or co-completing the user.

As a proof of concept that end-to-end incremental dialog processing can work in real-time, I will present a system that is able to speak in synchrony with the user, that is, speak the same words at the same time as the user says them (given that the user's utterance is known).

Friday November 18, 2011 -- 1:30pm in CS 308

Nigel Ward, Department of Computer Science, UTEP

Title: Towards Responsiveness in Information-Exchange Dialogs

Abstract: Today's spoken dialog systems (voice user interfaces) are widely disliked for the bad user experiences they provide. At the same time, interaction by voice offers unique opportunities to provide comfortable and rewarding experiences. Indeed, one research group has demonstrated a dialog system augmented with responsive back-channeling that was perceived as a better listener than humans on average; other responsive behaviors relating to turn-taking and emotional dimensions are also effective.

We are about to start a new project, aiming to build such responsive behaviors into a dialog system for a real information-exchange domain. Challenges include: discovering responsive behaviors, which are often dependent on subtle aspects of tone of voice and prosody; coordinating these with the current dialog state, and concisely representing that state; adapting these behaviors to specific users and user types; and building a full system able to carry out a complete task with real users.

Friday November 4, 2011 -- 1:30pm in CS221

Vladik Kreinovich, Department of Computer Science, UTEP

Title: Decorated Intervals: A Way to Optimally Propagate Properties through Numerical Computations

Abstract: One of the main problems of interval computations is to find an enclosure Y that contains the range f(X1, ..., Xn) of a given function f(x1, ..., xn) over given intervals X1, ..., Xn. Most of the techniques for estimating this range are based on propagating the range through computations. Specifically, we follow the computations of f(x1, ..., xn) step-by-step: we start with ranges X1, ..., Xn of the inputs, and then we sequentially compute the enclosures for the ranges of all intermediate results, until, on the last computation step, we get the desired enclosure Y.
A similar propagation of "decorations" -- information about continuity -- enables us to make conclusions about the continuity of the resulting function f(x1, ..., xn). In this talk, we describe the corresponding algorithms, and explain how the interval propagation results can be naturally extended to the general case of arbitrary sets.

Friday October 7, 2011 -- 1:30pm in CS221

Deana Pennington, Cyber-ShARE Center of Excellence, UTEP

Title:Science and Technology Research Teams and the Fuzzy Front End of Innovation

Abstract: Science and technology has a long, intertwined history. At times science has driven technology and at other times technology has driven science. In recent years, funding agencies have frequently called for interdisciplinary research that is simultaneously innovative in both science and technology. That is, innovation is expected to co-emerge in multiple research areas based on synergistic interactions between diverse researchers. Though highly sought after, evidence of such outcomes is sparse. This seminar will provide an overview of our understanding of interdisciplinary research processes; how those processes can drive innovation; common barriers; and hypothesized mechanisms for overcoming barriers. In particular, theories of transformational learning will be invoked to explain the opportunities and challenges of confronting interdisciplinary research teams at their inception, during the fuzzy front end of innovation.

Friday September 23, 2011 -- 1:30pm in CS221

David Novick, Department of Computer Science, UTEP

Title:The Communicative Functions of Animation in User Interfaces

Abstract: To develop a model that relates the purpose of the communication to the nature of the animation, we surveyed existing user interfaces that use animation, analyzed these uses with respect to type of animation and communicative function, and considered ambiguous or otherwise difficult cases. From this analysis, we constructed a matrix with appropriateness/inappropriateness values for all combinations of communicative functions and animation types covered by our survey. To illustrate how the model could be applied to graphical user interfaces and to assess the model's plausibility, we used the model to develop two versions of a user interface for an MP3 player.

Friday September 9, 2011 -- 1pm in CS221

Eric Freudenthal, Department of Computer Science, UTEP

Title: Planting the seeds of computational thinking: An introduction to programming suitable for inclusion in STEM curricula

Abstract: Inadequate math preparation discourages many capable students - especially those from traditionally underrepresented groups - from pursuing or succeeding in STEM academic programs. iMPaCT is a family of Media Propelled courses and course enrichment activities that introduce students to Computational Thinking. iMPaCT integrates exploration of math and programmed computation by engaging students in the design and modification of tiny programs that render raster graphics and simulate familiar kinematics. Through these exercises, students gain experience and confidence with foundational math concepts necessary for success in STEM studies, and an understanding of programmed computation.

In this talk, I describe iMPaCT and present early results from our formal evaluation of semester-length iMPaCT courses indicating improved academic success in concurrently and subsequently attended math courses. They also indicate changes to the nature of student engagement with problem solving using mathematics. I also describe iMPaCT-STEM, a nascent effort of computer science,mathematics, and electrical engineerng faculty to distill iMPaCT's pedagogy into sequences of short learning activities designed to teach and reinforce a variety of mathematical and kinematic concepts that can be directly integrated into math and science courses.

Friday July 8, 2011 -- 12pm in CS221

Gozde Ulutagay, Department of Computer Engineering, Izmir University, Turkey

Title: An Overview of Fuzzy and Crisp Clustering Algorithms

Abstract: Data mining is a modern and crucial technology which leads to effective results by means of bringing mathematical methods and computerized data analysis together. In scientific journals, data mining, together with nanotechnology, biotechnology, and some other fields of technology, is among the most efficient 10 technologies that changes the world. Among the vital tools of data mining, perhaps, clustering, the process of grouping a set of objects into classes of similar objects is the most important one. It has its roots in many areas, including statistics, data mining, biology, machine learning, etc. Cluster analysis is an important human activity. Early in childhood, one learns how to distinguish between cats and dogs, or between animals and plants, by continuously improving subconscious clustering schemes. By clustering, one can identify dense and sparse regions, and therefore, discover overall distribution patterns and interesting correlations among data attributes. Clustering problems require significant infrastructure both mathematically and algorithmically. The aim of this presentation is to address the mathematical and algorithmic aspects of crisp and fuzzy clustering techniques and to illustrate computer applications.

Bio: Gozde Ulutagay received her B.Sc. and M.Sc. degrees from Department of Statistics in Ege University, Izmir, Turkey in 2001 and 2004, respectively. She received her PhD degree from Department of Statistics, Dokuz Eylul University in 2009. Her main research area is fuzzy cluster analysis. She has a plenty of co-authored articles and presentations in the area. Her application of fuzzy neighborhood based clustering in the analysis of Bispectral Index of EEG data was the winning presentation in 2009. She is also interested data mining, optimization, and multivariate statistics. Dr. Ulutagay is currently working as an Assistant Professor in the Department of Industrial Engineering, Izmir University, Turkey. She is also the Vice Dean of The Faculty of Engineering.

Friday May 27, 2011 -- 12pm in CS308

Thomas Chou, UCLA

Title: Stochastic models of viral entry kinetics and inverse problems

Abstract: We develop and study a kinetic model to study the physics of viral infection via the two main entry pathways into cells: fusion and endocytosis. Analysis of the model allows us to derive a ``phase diagram" that yields qualitative predictions of the biophysical conditions under which each entry pathway is preferred. We will also discuss several extensions, all motivated by examining recent experimental protocols introduced to determine the receptor-coreceptor usage in HIV-1 infectivity. In the second part of the talk, I will discuss stochastic inverse problems and present some results on the reconstruction of drift functions in a Brownian motion, as well as on the branching number distribution in a Bellman-Harris branching process. Conditions and additional measurements that render the reconstruction better conditioned, when considering perfect data, will be outlined.

Bio: TBA

Friday May 6, 2011 -- 12pm in CS308

Christelle Jacob, IRIT, France

Title: Uncertainty handling in quantitative BDD-based fault-tree analysis by interval computation

Abstract: In fault-tree analysis probabilities of failure of components are often assumed to be precise. However this assumption is seldom verifi ed in practice. There is a large literature on the computation of the probability of the top (dreadful) event of the fault-tree, based on the representation of logical formulas in the form of a binary decision diagram (BDD). When probabilities of atomic propositions are ill-known and modelled by intervals, BDD-based algorithms no longer apply to the computation of the top probability interval. This paper investigates this question, and proposes an approach based on interval methods, relying on the analysis of the structure of the Boolean formula representing the fault-tree. The considered application deals with the reliability of aircraft operations.
Here are the slides of Christelle Jacob's presentation.

Bio: Christelle Jacob is a PhD student a the "Institut Supérieur de l'Aéronautique et de l'Espace" in Toulouse, France. She works under the supervision of Janette Cardoso and Didier Dubois on a project, @MOST, with Airbus and three other french labs : ONERA, LAAS and IRIT. She is studying the uncertainty management of models for preventive maintenance of aircrafts.

Friday April 29, 2011 -- 12pm at UGLC room 110

Suvrajeet Sen, Ohio State University

Title:A Prognosis for Stochastic Combinatorial Optimization

Abstract: By and large, the optimization literature focuses on deterministic problems, and the corresponding algorithms typically seek solutions that are very fine tuned to the specific data for the model. However, there are many real-world problems in which data is not quite certain, although one might have postulate a probabilistic description for the data. These lead to stochastic optimization models, and when the underlying choices involve combinatorial choices, these problems are stochastic optimization problems. They arise in numerous applications, especially, in situations where data becomes available over time. We will describe some applications from homeland security, and defense. Thereafter, we will discuss some optimal seeking methods based on decomposition algorithms. We will also provide computational evidence that in the face of uncertainty, such algorithms provide a much more realistic computational avenue than traditional deterministic approaches.

Bio: Suvrajeet Sen is Professor of Industrial and Systems Engineering and Director of the Center for Energy, Sustainability, and the Environment. Prior to joining OSU, he served on the faculty at the University of Arizona, and he also served as a program director at NSF where he was responsible for the Operations Research, and the Service Enterprise Engineering programs. Professor Sen is a Fellow of INFORMS. He has served on the editorial board of several journals, including Operations Research as Area Editor for Optimization, and as Associate Editor in INFORMS Journal on Computing, and Journal of Telecommunications Systems. Professor Sen is the past-Chair of the INFORMS Telecommunications Section and founded the INFORMS Optimization Section.

Friday April 8, 2011 -- 12pm in CS221

Michael McGarry, ECE Department, the University of Texas at El Paso

Title: Feed Forward Bandwidth Indication (FFBI): An Unconventional Approach to Bandwidth Forecasting

Abstract: Bandwidth forecasts can empower network protocols with a new intelligence that can bring packet switched networks to new levels of efficiency. With 90% of network traffic projected to consist of video information, our focus is on video bandwidth forecasting. We exploit the fact that for pre-recorded video, the size of every video frame is known prior to the video being delivered through the network. We propose Feed Forward Bandwidth Indication (FFBI) which feeds video frame sizes forward in a sequence of video frames. We extend FFBI to live video by introducing a delay at the source equivalent to the forecast window. We compare FFBI to the most accurate forecast methods found in the literature and use FFBI to improve network performance measures in Ethernet Passive Optical Networks (EPONs). The use of FFBI can provide a 50% reduction in queueing delay compared to the use of no forecasting and a 35% reduction in queueing delay compared to other forecasting methods.

Bio: Michael P. McGarry is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Texas at El Paso. He received his B.S. in Computer Engineering from Polytechnic University, Brooklyn, NY in 1997. He received his M.S. and Ph.D. in Electrical Engineering from Arizona State University, Tempe, in 2004 and 2007, respectively. He is the recipient of the 2009 IEEE Communications Society Best Tutorial Paper award. His research interests include bandwidth forecasting, congestion control, and the optimization of MAC protocols.

Friday March 25, 2011 -- 12pm in CS221

Jeffrey Rickman, Lehigh University
Joint Seminar with UTEP's Department of Metallurgical and Materials Engineering

Title: Some Applications of Computer Simulation in Physics and Engineering

Abstract: I will discuss two illustrative examples in which computer simulation provides insight into problems in physics and engineering. First, I will describe how the generation of weighted Voronoi diagrams and their analysis employing the methods of stochastic geometry are used to model microstructural evolution associated with a phase transformation. In conjunction with these simulations, the (reverse) Monte Carlo method is employed to deduce the nucleation and growth conditions that lead to a particular microstructure. Second, I will describe the modeling of plasticity in metals using level-set and other methods. Plastic deformation involves the motion of line defects (i.e., dislocations), and these methods permit the description of complex topological changes and defect interactions. From the results of simulation, I will then identify operative strengthening mechanisms.

Bio: Dr. Rickman is a Professor of Materials Science and Engineering and Professor of Physics. He joined the Lehigh University faculty in 1993 after postdoctoral appointments at the University of Michigan and Argonne National Laboratory. He did his graduate work in physics at Carnegie Mellon University and his undergraduate work in physics and mathematics at Miami University. His many research interests include the development of computer simulation methodologies for describing fluids and solids, determination of the elastic properties of defects and the kinetics of phase transformations. He has received several honors including the NSF Young Investigator Award, the Chambers Junior Professorship and the Culler Prize (Miami University). He is also a member of several honor societies including Phi Beta Kappa, Phi Kappa Phi and Sigma Xi and several professional organizations including the Materials Research Society, the TMS (Chemistry and Physics of Materials Committee) and the American Ceramics Society.

Thursday March 24, 2011 -- 2pm in CS308

Jan Sliwka, ENSTA-Bretagne, France

Title: Robust localization of underwater robots and other issues in the design of such devices

Abstract: Each year our engineering school ENSTA Bretagne participates in a European competition of autonomous underwater robots called SAUC'E (Student Autonomous Underwater Challenge Europe). The purpose of this competition is to build an intelligent robot capable of performing many missions, such as passing through an underwater gate, following a pipeline, detecting and manipulating underwater objects..., without the help of a human operator. In my talk, I will present our submarine robot "Sauc'isse". I will talk about its mechanical design, electronic design, and software design as well as the different algorithms needed to perform well during the competition. I will explain in more details the localization algorithm since it is part of my PhD work.

Friday February 25, 2011 -- 12pm in CS221

Vladik Kreinovich and Luc Longpre, the University of Texas at El Paso

Title: A Firm Foundation for Private Data Analysis

Abstract: Everyone understands that there is a need to preserve privacy, but it is not easy to precisely define what it means -- and, in situations when some privacy was lost, how to gauge the amount of lost privacy. For example, a person may not want to disclose his or her salary; in this case, disclosing one of the decimal digits of the annual salary amount is a violation of privacy. Disclosing the first digit of the salary does provide a lot of information, but disclosing the last digit seems almost harmless. In this talk, we present a recent survey paper on privacy definitions and measures written by Cynthia Dwork from Microsoft Research. If time allows, we will also explain limitations of the existing approaches -- and our ideas on how these limitations can be overcome.

Friday February 18, 2011 -- 12pm in CS221

Larry Hall, University of South Florida

Title: Finding the right genes for Disease and Prognosis Prediction

Abstract: It is possible to get gene expression data relatively inexpensively from micro-arrays. So, this leads to the possibility that the genes can tell us who will get or has a disease. Perhaps one can find the stage of the disease to enable effective treatments. However, we are currently at the stage where there are many challenges to evaluating the possibilities for genes to be used in diagnosis and treatment. There are typically many more genes that might be involved than samples for any given disease. Which genes are important and how stable are the choices an algorithm provides? We do not know the time of the true onset of a disease, just sometimes when symptoms started and sometimes when diagnosis was done. Some of the promising work on diagnosis or prognosis has suffered from data or scientific errors. This talk will discuss the problems and pitfalls of using genes to predict disease presence or prognosis. It will also discuss some promising ways to choose the genes that may be predictive for a particular disease, with a focus on cancer, and point out some open questions.

Bio: My research interests lie in distributed machine learning, extreme data mining, bioinformatics, pattern recognition and integrating AI into image processing. The exploitation of imprecision with the use of fuzzy logic in pattern recognition, AI and learning is a research theme. He has authored or co-authored over 65 publications in journals, as well as many conference papers and book chapters. Some recent publications appear in the IEEE Transactions on Pattern Analysis and Machine Intelligence, Neural Computation, Information Fusion, Journal of Machine Learning research, IEEE Transactions on Systems, Man, and Cybernetics, Pattern Recognition, the International Conference on Pattern Recognition, the Multiple Classifier Systems Workshop, and the FUZZ-IEEE conference. I co-edited the 1994 joint North American Fuzzy Information Processing Society (NAFIPS), IFIS and NASA conference proceedings and the 1998 proceedings. I am a fellow of the IEEE. I'm a past president of NAFIPS. Also, associate editor for the IEEE Transactions on Fuzzy Systems, International Journal of Approximate Reasoning, International Journal of Intelligent Data Analysis, and The Handbook of Fuzzy Logic. I'm a Fellow of the IEEE. I'm the former Editor-in-Chief for the IEEE Transactions on Systems, Man and Cybernetics, Part B. I am the Jr. Past President of the IEEE Systems, Man and Cybernetics Society.

Thursday December 9, 2010 -- 11am in CS221

Manish Jain, University of Southern California

Title:Game Theory for Security: Algorithms and Applications

Abstract: Predictable allocations of limited security resources such as police officers, canine units, or checkpoints are vulnerable to exploitation by attackers. Game theory provides a principled way to find optimal randomized security policies that thwarts this predictability. In this talk, I will describe game-theoretic models and algorithms that we have developed for security domains. I will also briefly describe the application of some of these algorithms by the Los Angeles Worlds Airport (LAWA) police and the Federal Air Marshals Service (FAMS).

Bio: Manish Jain is currently a PhD candidate at the University of Southern California. He is a part of the Teamcore Research group, led by Prof. Milind Tambe. His work is on the applications of game-theoretic and large-scale optimization techniques, including the scheduling of flights/air marshals for the Federal Air Marshals Service (FAMS) and the scheduling of checkpoints for the Los Angeles International Airport (LAX) police. He has co-authored papers on the subject of security games that have been presented in major artificial intelligence and operations research conferences. His work published in Interfaces was a finalist for the EURO excellence in Practice award. He has also received a Letter of Commendation from the city of Los Angeles for his contributions to the development of the security assistant deployed at LAX.

Thursday November 11, 2010 -- 3pm in Bell Hall 143

Irina Perfilieva and Vilem Novak, University of Ostrava, Czech Republic

Title: Discrete Fuzzy Transforms and their Applications in Data Processing

Abstract: The theory of fuzzy (F-)transforms can be seen as a bridge between fuzzy modeling and the theory of linear (in particular, integral) transforms. In this talk, we will show backgrounds of the ordinary F-transform and a higher order F-transform. We will explain different ways of achieving a desired quality of approxima- tion by the, so called inverse F-transform. Various applications demonstrate the universality of this special technique of fuzzy modeling. We will mention two of them: image processing, and analysis and forecast- ing of time series. The talk will be self-contained, illustrated by pictures and provided with all necessary explanations.

Friday November 12, 2010 -- noon to 1pm, in CS308

Huiping Cao, New Mexico State University

Title: Feedback-driven Result Ranking and Query Refinement for Exploring Semi-structured Data Collections

Abstract: Feedback process has been used extensively in document-centric applications, such as text retrieval and multimedia retrieval. Recently, there have been efforts to apply feedback to semi-structured XML document collections as well.
In this work, I note that feedback can also be an effective tool for exploring (through result ranking and query refinement) large semi-structured data collections. In particular, in large scale data sharing and curation environments, where the user may not know the structure of the data, queries may initially be overly vague.
Given a path query and a set of results identified by the system to this query over the data, I consider two types of feedback: Soft feedback captures the user’s preference for some features over the others. Hard feedback, on the other hand, expresses users’ assertions regarding whether certain features should be further enforced or, in contrast, are to be avoided. Both soft and hard feedback can be “positive” or “negative”. For soft feedback, I develop a probabilistic feature significance measure and describe how to use this for ranking results in the presence of dependencies between the path features. To deal with the hard feedback efficiently (i.e., fast enough for interactive exploration), I present finite automata based query refinement solutions. In particular, I present a novel LazyDFA+ algorithm for managing hard feedback. I also describe optimizations that leverage the inherently iterative nature of the feedback process. I bring together these techniques in AXP, a system for adaptive and exploratory path retrieval. The experimental results show the effectiveness of the proposed techniques.

Bio: Dr. Huiping Cao received a Ph.D. in Computer Science from The University of Hong Kong in 2007, a Master's in Computer Science and a Bachelor's in Management Information Systems from Renmin University of China in 2002 and 1999 respectively. She is an assistant professor in Computer Science at New Mexico State University (NMSU). Before joining NMSU, she worked as a Research Fellow at University of California Santa Barbara and as a Postdoctoral Research Associate at Arizona State University. Huiping's research interests are broadly in the area of data management (e.g., data discovery, indexing and integration) and mining of non-traditional data (e.g., spatial, spatiotemporal and scientific data). She has published articles on data management and data mining in highly competitive venues.

Friday October 29, 2010 -- noon to 1pm, in CS308

Chris Kiekintveld, CS Department,UTEP

Title: Overview of research interests

Abstract: I will present a broad overview of my research and interests in the area of artificial intelligence, multi-agent systems, and strategic reasoning. I am interested in multi-agent decision problems, which include both traditional games such as chess or poker, as well as a wide variety of important real-world problems that can be modeled as games. For example, I am currently working on several project that use game theory to help make complex resource allocation decisions in security domains. One of these projects developed a software tools that is curently being used by the Federal Air Marshals Service (FAMS) to help create unpredictable, risk-based flight schedules for the air marshals. Border security is a new and exciting area where I am looking to apply similar methods. Finally, I will briefly describe some of my other work on developing intelligent trading agents, and on algorithms for distributed optimization.

Cuauhtemoc Munoz, CS Department,UTEP

Title:Automated Testing of LTL Formulas with Execution Traces using Prospec

Abstract:Prospec is a tool that allows software engineers to create software specifications by combining patterns, scopes, and composite propositions (CPs). Patterns, scopes, and CPs are based on Linear Temporal Logic (LTL) formulas. Salamah designed a general algorithm for generating LTL formulas from patterns, scopes, and CPs, and Vela implemented the algorithm. The LTL generator is capable of generating LTL formulas for every pattern, scope, and CP combination. While there are at least 30,000 combinations of patterns, scopes and CPs, only 164 LTL formulas were manually tested in the implementation.
PROTEF is a framework for testing LTL formulas using execution traces. An execution trace represents a sequence of states, where each state is defined by a set of true atomic propositions. PROTEF takes an execution trace and an LTL formula and generates a model that can be checked using the NuSMV model checker. The model checker determines whether the formula is satisfied by the model of the execution trace. This talk describes the LTL Verifier, which automatically generates test cases to verify the LTL Generator. The approach to test case generation and the test oracle are novel. Test cases are composed of LTL formulas, execution traces, and expected results. Execution traces and expected results are automatically generated by the LTL Verifier. Test oracles predict the correct results. Test cases are generated by considering equivalence classes and boundary values and applying specific rules to patterns, scopes, and CPs. Test cases generated by the LTL Verifier are executed using PROTEF. Approximately 2% of the 3,836,960 test cases failed. Two types of errors were found in the LTL formulas by using the LTL verifier. The first type of error was missing parentheses in the LTL formulas. The second type of error was a wrong implementation of the LTL algorithm for a specific pattern, scope, and CP combination.

Luc Longpre, CS Department, UTEP

Title: Security and Privacy

Abstract: An important part of security is protection of confidentiality. We explore different aspects of privacy, including definitions, privacy in statistical databases, escrowed privacy.

Friday October 15, 2010 -- noon to 1pm, in CS221

Guoqiang Hu, CS Department, UTEP

Title: A Full Life-Cycle Methodology for Structured Use-Centered Quantitative Usability Requirements Specification and Usability Evaluation of Websites.

Abstract: World Wide Web has gained its dominant status in the cyber information and services delivery world in recent years. But how to specify website usability requirements and how to evaluate and improve website usability according to its usability requirements specification are still big issues to all the stakeholders. To help solve this problem, we propose a website usability requirements specification and usability evaluation methodology that features a structured use-centered quantitative full life-cycle method. A validation experiment has been designed and conducted to prove the validity of the proposed methodology, QUEST (Quantitative Usability Equations SeT). Its principle is to prove that QUEST has stronger website usability evaluation capability than the most typical existing usability evaluation methods. Apparently, if QUEST's website usability evaluation capability is established, then its usability metrics can be used to quantitatively specify upfront user usability requirements for websites. In the validation experiment, 7 usability experts and 20 student subjects were recruited to perform 4 tasks on 2 open source calendar websites, WebCalendar 1.0.5 and VCalendar 1.5.3.1; 4 sets of usability data had been collected, which were corresponding to the following 4 usability evaluation methods respectively: expert usability review, traditional user usability testing, SUS (System Usability Scale), and QUEST. According to the experiment results: both the expert usability review and the traditional user usability testing were inconclusive on which of the 2 target websites had better usability; although SUS rated the overall usability of WebCalendar 1.0.5 at 66.00 and VCalendar 1.5.3.1 at 61.75, it was subjective and vague on usability problems; in contrast, QUEST not only rated the overall usability of WebCalendar 1.0.5 at 56.59 and VCalendar 1.5.3.1 at 35.97, but also revealed where the usability problems were and how severe each usability problem was in a quantitative manner. In conclusion, it clearly can be stated that QUEST has stronger website usability evaluation capability than all other 3 most typical existing usability evaluation methods. So, the proposed methodology has been validated by the experiment results.