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University Calendar
Events for October
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PhD Defense - Ivo Krka
Thu, Oct 03, 2013 @ 10:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
University Calendar
Title: Deriving Component-Level Behavior Models from Scenario-Based Requirements
PhD Candidate: Ivo Krka
Committee:
Nenad Medvidovic (Chair)
Leana Golubchik
Sandeep Gupta
Sebastian Uchitel (University of Buenos Aires)
Use-case scenarios, with notations such as UML sequence diagrams, are widely used, often in combination with formalized system goals and event invariants, to specify the desired behavior of a software system. These intuitive requirement specification notations only partially specify the system-to-be by prohibiting or requiring certain behaviors, while leaving other behaviors uncategorized into either of those. Engineers iteratively refine and elaborate the requirements specification by eliciting more requirements to finally arrive at a complete behavior description. Partial-behavior models, such as modal transition systems (MTS), have been utilized as a formal foundation for capturing partial system specifications. Mapping the requirements to partial behavior models enables automated analyses (e.g., requirements consistency checking) and helps to elicit new requirements, thus assisting the requirements specification practices.
Although intuitive, the existing requirements notations allow engineers to specify behaviors with unintended semantic side-effects. In particular, the current practices support reasoning about and specification of a system's behavior exclusively at the system level, disregarding the fact that a system typically consists of interacting components. This runs the risk of arriving at an inconsistent specification (i.e. one that is not realizable as a composition of the system's components), which can prove costly if left unresolved.
To address the shortcomings of the current practices, this dissertation explores three strategies to enable transitioning from a scenario-based requirements specification to a set of component-level MTSs: (1) heuristically creating component MTSs from a system-level scenario-based specifications, (2) enhancing the way scenarios are specified, and (3) mapping the refinements performed on a system MTS to refinements to-be-performed on component-level MTSs. These strategies have been implemented with the following suite of techniques:
1. A heuristic algorithm that synthesizes a set of component-level MTSs from a set of existential scenarios and system operation invariants.
2. Component-aware Triggered Scenarios (caTS), a triggered-scenario language that enables expressing reactive behaviors of system components.
3. A framework that, given a system MTS refinement based on a new requirement, propagates that refinement to a set of component MTSs.
As they work with different inputs, selecting the appropriate technique depends on the context such as restrictions on adopting new notations and the required level of formality. In addition, the heuristic synthesis algorithm has been adapted and modified into Trace-Enhanced MTS Inference (TEMI) algorithm to work with information about the observed implementation-level system executions.
The proposed techniques have been theoretically evaluated to assess their complexity, correctness, and completeness. The techniques have also been applied on a number of real-world and automatically generated case studies. The results suggest that the generated MTSs accurately capture those component implementations that (1) necessarily provide the behavior required by the scenarios, (2) restrict behavior forbidden by the requirements specification, and (3) leave the behavior that is neither explicitly required nor forbidden as undefined. Furthermore, the proposed techniques help to detect potential specification flaws as they are specified, correct the existing errors, and prevent future inconsistencies. In case of heuristic MTS synthesis, the algorithm has been proven applicable to very large system specifications. The performed quantitative evaluations also confirmed significant savings in specification effort when caTS scenarios are used in place of existing notations. Finally, based on evaluations performed on nine off-the-shelf libraries, the TEMI algorithm has improved significantly upon the state-of-the-art in dynamic model inference, producing models of higher quality in terms of precision and recall.
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Lizsl De Leon
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Phd Defense - Charalampos Chelmis
Tue, Oct 08, 2013 @ 09:00 AM - 11:00 AM
Thomas Lord Department of Computer Science
University Calendar
Ph.D. Defense
Candidate: Charalampos Chelmis
“HETEROGENEOUS GRAPHS VS MULTI-MODAL CONTENT:
MODELING, MINING AND ANALYSIS OF SOCIAL NETWORK DATA”
Tuesday, October 8th
09:00 - 11:00 AM
EEB â 110
https://vsoeapp1.vsoe.usc.edu/calendar/?event=10469#user_options
Defense Committee:
Paul Bogdan
Aiichrio Nakano
Viktor K. Prasanna (Chair)
Thesis Abstract: Complex networks arise everywhere. Online social networks are famous complex networks due to (a) revolutionizing the way people interact on the Web, and (b) permitting in practice the study of interdisciplinary theories that arise from human activities, at both micro (i.e. individual) and macro (i.e. community) level. Understanding the rich properties and dimensional interdependencies of topology and content in complex networks is necessary to uncover hidden structures and emergent knowledge.
We propose a formal model that abstracts the semantics of complex networks into an integrated, context aware, time sensitive, multi-dimensional space, enabling holistic examination of their static and dynamic properties, facilitating joint analysis of graphs and content and their explicit and implicit interactions. Traditionally, network analysis methods, either ignore content and focus on the network structure, or make implicit assumptions about the complex correlation of these two components. We show that accurately modeling multiple symmetric or asymmetric, explicit and hidden interaction channels between people, integrating auxiliary networks into a unified framework, leads to significant performance improvements in a variety of prediction and recommendation tasks. We empirically verify this insight using real-world datasets from online social networks and corporate microblogging data.
In this research, we investigate implicit relationships in composite networks. We propose a novel, robust model which facilitates multimodal analysis of time varying, complex social networking data. We 1) study informal communication behavior, information sharing, and influence at the workplace, 2) perform accurate communication intention prediction using auxiliary information, and 3) significantly improve social tie recommendation in online social bookmarking systems by exploiting the dynamics of collaborative annotation.
Biography: Charalampos Chelmis is a PhD candidate in the Department of Computer Science at the University of Southern California, Los Angeles. His research interests include modeling, mining and analysis of composite networks, large-scale (big) data analytics and information integration. He received his Master of Science in Computer Science from the University of Southern California in 2010 and his Bachelor in Computer Engineering & Informatics from the University of Patras, Greece in 2007.
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 110
Audiences: Everyone Is Invited
Contact: Lizsl De Leon
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Chevron Design Challenge
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Thu, Oct 10, 2013 @ 05:30 PM - 08:30 PM
Viterbi School of Engineering Student Organizations
University Calendar
Come participate in a Chevron sponsored Design Challenge where you will be competing with other teams to build a drill and use it to reach an oil reservoir as quickly as possible.
To register:
Email your full name and resume to uscasme@gmail.com
Join our event on Facebook: https://www.facebook.com/events/300891453386454/
All mechanical engineers welcome, no experience necessary. This is a good opportunity to demonstrate your problem solving skills and network with Chevron engineers.Location: E-Quad
Audiences: Everyone Is Invited
Contact: American Society of Mechanical Engineers (ASME)
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4th Annual Electrical Engineering Research Festival hosted by MHI
Fri, Oct 11, 2013 @ 08:00 AM - 05:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
University Calendar
The Ming Hsieh Institute annually hosts the Ming Hsieh Department of Electrical Engineering Research Festival. Over 100 undergraduate and graduate students present their research through poster sessions, demonstrations and oral presentations at the event.
The Research Festival is a day-long festival that welcomes the entire USC Viterbi community, alumni and engineering industry representatives.
RSVP: Registration and event details
mhi.usc.edu
Questions:
hamra@usc.edu
213-740-2694More Information: SAVE THE DATE CARD 10.11.13 - Research Festival.pdf
Location: Gerontology Auditorium & Patio
Audiences: Everyone Is Invited
Contact: Danielle Hamra
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Predicting The Effects of Cancer Therapies Targeting Angiogenesis Signaling Pathways
Mon, Oct 14, 2013 @ 04:00 PM - 05:00 PM
Alfred E. Mann Department of Biomedical Engineering
University Calendar
Angiogenesis, the formation of new blood vessels from pre-existing vasculature, is a tightly regulated biological process involved in physiological function such as wound healing and exercise, as well as in pathological conditions, including preeclampsia, ischemic heart disease, and cancer. Inducing angiogenesis is a hallmark of cancer, as tumors cannot grow beyond 1 mm in diameter without eliciting the formation of blood capillaries to supply oxygen and other nutrients. Vascular endothelial growth factor (VEGF) is a key regulator of angiogenesis and its role in cancer biology has been widely studied. Given the action of VEGF in promoting angiogenesis, it has been targeted in various cancer treatments.
Systems biology approaches, including experiment-based computational modeling, are useful in gaining insight into the complexity of tumor angiogenesis. Computational models provide a framework to test biological hypotheses and optimize effective therapies that aim to inhibit tumor vascularization and growth. Here, I describe the development of whole-body, molecular-detailed compartment models of VEGF kinetics and transport and the application of these models to predict the effect of various anti-angiogenic therapies that inhibit VEGF. The models reproduce experimental observations and predict the dynamics of VEGF in the body and can be applied to interpret pre-clinical and clinical data. Importantly, the models simulate the effects of intravenous administration of anti-VEGF agents. Model predictions are relevant to the clinical application of VEGF-targeting therapies and generate testable hypotheses that can aid in elucidating the mechanism of action of anti-VEGF agents. This work is useful for the development and optimization of personalized cancer treatment strategies that target the VEGF pathway.More Information: Stacey Finley Flyer 10-14-13.pdf
Location: Hedco Neurosciences Building (HNB) - 100
Audiences: Everyone Is Invited
Contact: BME-ENH Seminar
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Phd Defense - Nader Noori
Tue, Oct 15, 2013 @ 02:00 PM - 04:00 PM
Thomas Lord Department of Computer Science
University Calendar
PhD Candidate: Nader Noori
Laurent Itti (Chair)
Michael Arbib
Lisa Azzi-Zadeh (Outside member)
10/15/13
EEB 248
2pm-4pm
Title : The Symbolic Working Memory System
Subtitle: Deriving an Embodied Working Memory Machinery for the Symbolically-Intelligent Mind from Sensorimotor Resources of the Brain
Abstract
Dominant theoretical paradigms for describing the functioning of the brain's short-term memory management systems in the domains of low-level/perception-action and and high-level/intellectual functions follow drastically different principles: embedded and distributed in the low-level domain, disembodied and centralized in the high-level domain. Given that the human cognitive system functions at both levels in different contexts simultaneously this question arises whether indeed there are two types of working memory systems running in parallel under two different operational principles in human brain or, a more parsimonious account can explain all different manifestations of working memory in all domains.
Theoretical inconsistencies and biological/evolutionary implausibility of centralized paradigms of the intellectual domain was a motivation for theorizing about a working memory framework for high-level/intellectual functions based upon control theoretic principles of the low-level functional domain.
The proposed framework demonstrates how novel assemblage of embedded schemas in existing sensorimotor systems may supply a system for management of symbolically represented sensory and motor information serving intellectual tasks. In the
proposed framework, strategic and evolutionarily-constrained reuse of sensorimotor resources for management of respectively spatially-organized and temporally-sensitive information support random access and serial access schemas for management of
symbolic information. Through grounding access schemas for management of symbolic information in sensorimotor systems we are able to predict ramifications of working memory management during the performance of mental tasks at behavioral and neural levels. A detailed example in applying this methodology in well-studied cases of forward and backward recall tasks will be presented with additional computational modeling and the results of simulations.
Our systematic approach in mapping spatial/temporal characteristics of sensorimotor systems onto access modes provides a symbolic interface to other frameworks and
architectures for describing the symbolically-intelligent mind. Proposed framework provides for the first time a neurally-grounded and sensorimotor-based account for management of symbolic information with embodied cognition prospects with opportunities for experimental validations and applications.
In addition to theoretical and computational discussions the result of some experimental studies including eye-tracking during mental sorting tasks will be presented as the supporting evidence for the propose theory.
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Lizsl De Leon
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PhD Defense- Jongeun Jun
Mon, Oct 21, 2013 @ 12:00 PM - 01:30 PM
Thomas Lord Department of Computer Science
University Calendar
Phd Candidate: Jongeun Jun
10/21/13
12pm-1:30pm
SAL 222
Committee:
Dennis McLeod (chair)
Cyrus Shahabi
Daniel O'Leary (outside member)
DBSSC : Density-Based Searchspace-limited Subspace Clustering
We propose a mining framework that supports the identification of useful knowledge based on data clustering. With the recent
advancement of microarray technologies, we focus our attention on gene expression datasets mining. In particular, given that genes are often co-expressed under subsets of experimental conditions, we present a novel subspace clustering algorithm. In contrast to previous approaches, our method is based on the observation that the number of subspace clusters is related with the number of maximal subspace clusters to which any gene pair can belong. By performing discretization to gene expression profiles, the similarity between two genes is transformed as a sequence of
symbols that represents the maximal subspace cluster for the gene pair.
This domain transformation (from genes into gene-gene relations) allows us to make the number of possible subspace clusters dependent on the number of genes. Based on the symbolized genes, we present an efficient subspace clustering algorithm that is linearly scalable to the number of dimensions. In addition, the running time can be drastically reduced by utilizing inverted index and pruning non-interesting subspaces. Experimental
results indicate that the proposed method efficiently identifies
co-expressed gene subspace clusters for a yeast cell cycle dataset.
Furthermore, we incorporate density-based approach into subspace clustering. In the density-based clustering approach,
points with high density (i.e., core genes) and points with low
density (i.e., outlier points) are identified. Non-core, non-outlier points are defined as border points. Since a core point has high density, it is expected to locate well inside the cluster. Thus, core points and surrounding border points form multiple subspace clusters. That is, core points have high potential in belonging to multiple subspace clusters. Therefore, instead of performing subspace clustering on whole datasets, by performing subspace clustering on only core points, we can further reduce running time drastically. After that, border points are used to expand the cluster structure by assigning them to the most relevant cluster. Coupling with density-based approach, experimental results indicate that our
subspace clustering improves running time significantly.
Location: Henry Salvatori Computer Science Center (SAL) - 222
Audiences: Everyone Is Invited
Contact: Lizsl De Leon
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Evening with Faculty
Mon, Oct 21, 2013 @ 05:30 PM - 07:00 PM
Viterbi School of Engineering Student Organizations
University Calendar
Ever been too afraid to talk to a professor? Looking to meet more faculty in Viterbi? Well NSBE's evening with faculty is the perfect opportunity for you to mingle with the many distinguished faculty members at USC. Join us for a fun night of networking and discussion. Dinner will be provided, and dress is casual.
Please RSVP here by emailing nsbe@usc.edu to reserve your spot!Location: Grace Ford Salvatori Hall Of Letters, Arts & Sciences (GFS) - 101
Audiences: Everyone Is Invited
Contact: NSBE National Society of Black Engineers
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9th Annual Student Symposium
Tue, Oct 22, 2013 @ 10:00 AM - 04:00 PM
Mork Family Department of Chemical Engineering and Materials Science
University Calendar
Location: Edward L. Doheny Jr. Memorial Library (DML) - DML 240
Audiences: Everyone Is Invited
Contact: Ryan Choi
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ASME
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Tue, Oct 29, 2013 @ 06:30 PM - 08:00 PM
Viterbi School of Engineering Student Organizations
University Calendar
Have you ever wanted to get the inside scoop on what it truly means to be an intern at a company? Do you have questions that you may not feel comfortable asking a recruiter? Then come to ASME's Intern Panel Event where we will be having fellow mechanical engineering students speak about their internship experiences at companies such as Northrop Grumman, Disney, Chevron, and a satellite company.
Location: Mark Taper Hall Of Humanities (THH) - 215
Audiences: Everyone Is Invited
Contact: American Society of Mechanical Engineers (ASME)
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