[dbjapan] ★サイバー・フィジカル・システム★ （ＣＰS) 講演会 （最先端・データ工学研究会・ＤＢＳJ・ACM SIGMODJ 共催） 6月9日午後

[Miyuki Nakano <miyuki [at] tkl.iis.u-tokyo.ac.jp>]

日本データベース学会の皆様、

以下、特別企画「Cyver Physical Systems」と題して、
米国の先端研究者からホットトピック情報を語っていただく
講演会が6月9日(木)・東大生研にて行われます。
ふるってご参加ください。
　　　　　　　　　　　　　　　　　東京大学生研
　　　　　　　　　　　　　　　　　中野美由紀

　☆☆☆　6月9日　特別企画「ＣＰＳ」講演会のご案内　　　☆☆☆

共催　電子情報通信学会データ工学研究専門委員会
　　　最先端研究開発支援プログラム（FIRST）: 「超巨大データベース時代に
　　　向けた最高速データベースエンジンの開発と当該エンジンを核とする
　　　戦略的社会サービスの実証・評価」
      日本データベース学会
　　　ACM SIGMOD日本支部


日時　6月9日（木）　午後1時半〜5時
場所　東京大学生産技術研究所　An棟　3階　大会議室（An 301,302）
      http://www.iis.u-tokyo.ac.jp/map/index.html


特別企画　Cyber Physical Systems 講演会

13:30-14:30
        Social Influence Models in Information Network Analysis
        Prof. Ling Liu (Georgia Institute of Technology)

14:45-15:45
        Participatory Urban Data Collection: Planning and Optimization
　　　　Prof. Cyrus Shahabi (USC)

16:00-17:00
        A World of Opportunities: CPS, IOT, and Beyond
        Prof. Calton Pu (Georgia Institute of Technology)

参加費　無料

皆様のご参加をお待ちしております。


　　　　　　　　　　　　電子情報通信学会データ工学研究会　委員長
　　　　　　　　　　　　　　　　　　　　　　　　　　　　 中野　美由紀
　　　　　　　　　　　　最先端(FIRST)プログラム　
                        「超巨大ＤＢ＆戦略的社会サービス」
　　　　　　　　　　　　　　　　　　　研究代表者　　　　　喜連川　優
　　　　　　　　　　　　　　　　　　　　　　
連絡(問合せ)先　cps_lecture [at] tkl.iis.u-tokyo.ac.jp

-----------------------------------------------------------------
To: cps_lecture [at] tkl.iis.u-tokyo.ac.jp

　講演会　参加申し込み

6月9日（木）の講演会に参加
・お名前　　　
・ご所属
------------------------------------------------------------------
プログラム詳細

13:30-14:30
Social Influence Models in Social Network Analysis

Ling Liu (Georgia Institute of Technology)

Social influence, the phenomenon that the actions of a user induce
similar behaviors among his/her friends via social ties, exists
prevailingly in socially networked systems. Social influence models
define the processes by which ideas and influence propagate through a
social network. The effects of “word of mouth” in the promotion of new
products represent one example application of the science of social
influence. In this talk, I will first give an overview of some
representative social influence models, focusing on the algorithmic
problem for social influence processes in social networks: Can we
convince a subset of individuals to adopt a new product, a new idea or
an innovation, such that a large cascade of further adoptions can be
triggered? and if so, which set of individuals should we target?
Existing studies mostly focus on studying flow of communication across
groups at macro-level (e.g., diffusion models). We argue that it is
equally important to understand and model flows within dyads or small
groups (micro level).   Social influence at microscopic scale (i.e., at
the granularity of individual users, actions and time-stamps)  may
significantly enhance our understanding of two important questions: (1)
how word of mouth interaction in dyads or small groups aggregates to
form large-scale patterns in the diffusion of information and influence
concerning innovations, fashions, fads, rumors and formation of consumer
attitudes, and (2) which interpersonal ties are more likely to be
activated for the flow of information and are more influential. In the
second part of the talk, I will give a brief overview of our recent work
in social influence across multiple networks. Concretely, I will discuss
how to model users’ actions as interactions between social network
(formed by users) and object network (formed by targets of actions), how
an occurred interaction may trigger another, when and where a new
interaction may be observed?  I will also illustrate the use of our
cross-network social influence analysis to answer the above two
fundamental questions of social influence. While macroscopic social
influence models may be amenable to stochastic analysis over large
populations of users and objects, microscopic analysis introduces new
computational challenges. We will end the talk with a set of research
challenges in influence driven social network analysis.

Short Bio:
Ling Liu is a full Professor in the School of Computer Science at
Georgia Institute of Technology. There she directs the research programs
in Distributed Data Intensive Systems Lab (DiSL), examining various
aspects of data intensive systems with the focus on performance,
availability, security, privacy, and energy efficiency. Prof. Liu and
her students have released a number of open source software tools,
including WebCQ, XWRAPElite, PeerCrawl, GTMobiSim. Prof. Liu has
published over 250 International journal and conference articles in the
areas of databases, distributed systems, and Internet Computing. She is
a recipient of the best paper award of ICDCS 2003, WWW 2004, the 2005
Pat Goldberg Memorial Best Paper Award, and 2008 Int. conf. on Software
Engineering and Data Engineering. Prof. Liu has served as general chair
and PC chairs of numerous IEEE and ACM conferences in data engineering,
distributed computing, service computing and cloud computing fields and
is a co-editor-in-chief of the 5 volume Encyclopedia of Database Systems
(Springer). She is currently on the editorial board of several
international journals, such as Distributed and Parallel Databases
(DAPD, Springer), Journal of Parallel and Distributed Computing (JPDC),
ACM Transactions on Web, IEEE Transactions on Service Computing (TSC),
and Wireless Network (WINET, Springer). Dr. Liu’s current research is
primarily sponsored by NSF, IBM, and Intel.





14:45-15:45
Participatory Urban Data Collection: Planning and Optimization

Abstract
In recent years, we have been witnessing the rapid advances of two
technological trends.  The first is the earth visualization systems
(e.g., Google Earth, Microsoft Virtual Earth) that are becoming more and
more realistic, allowing users to visualize almost every major urban
area at detailed street and building levels.   However, these systems
face a major challenge in updating their data frequently due to the high
cost of data collection.  The second trend involves the advances of
mobile devices equipped with sophisticated sensors, enabling people to
collect and transmit audio, video, image, and text information tagged
with location and time.  Hence, there is an opportunity here to
incentivize the public to participate in opportunistic data collection
campaigns in order to transform the static environment of earth
visualization systems to a dynamic one covering ever-changing,
up-to-the-minute information about our urban environments and their
events. The applications of su
ch a dynamic information-rich geospatial environment are plenty, from
tracking a contagious disease to the latest coverage of breaking news.
One of the main research challenges in enabling participatory urban data
collection is to find optimal plans for the participants such that they
can collectively acquire as much of data as possible without violating
their constraints.
In this talk, I will present one specific example of the abovementioned
vision, a participatory texture documentation (PTD) system, in which a
group of users (dedicated individuals and/or general public) with
camera-equipped mobile devices participate in collaborative collection
of dynamic urban texture information. PTD enables inexpensive, scalable
and high resolution urban texture documentation.  We focus on the
optimal planning challenges of PTD that consists of two phases:
viewpoint selection and viewpoint assignment.  First, during the
viewpoint selection phase, a minimum number of points in an urban
environment are selected from which the visible texture of the entire
urban environment can be collected/captured. Next, during the viewpoint
assignment phase, the selected viewpoints are assigned to the
participating users such that given a limited number of users with
various constraints; the users can collectively capture the maximum
amount of texture information within
a limited time interval


16:00 - 17:00
Title: A World of Opportunities: CPS, IOT, and Beyond
Speaker: Prof. Calton Pu, Georgia Institute of Technology
Abstract:
The continuous evolution of computing and networking technologies (e.g.,
Moore’s Law) is creating a
new world populated by many sensors on physical and social environments.
This emerging new world
goes much further than the original visions of ubiquitous computing and
World Wide Web. Aspects of
this new world have received various names such as Cyber Physical
Systems (CPS) and Internet of Things
(IOT). CPS links many physical sensor data to detailed simulation models
running on large data centers.
IOT brings together many appliances, making much more environmental data
available and supporting
control of these appliances. CPS/IOT applications are many, including
personalized healthcare,
intelligent transportation, smart grid, sustainable environment, and
disaster recovery as representative
examples. These CPS/IOT applications are motivated and strongly pushed
by significant new social,
economic, and human benefits. At the same time, these applications are
also mission-critical with
serious quality of service requirements such as real-time performance,
continuous availability, high
security and privacy.
We will argue that the traditional process-oriented programming
languages and software architectures
should be augmented by distributed event-based facilities and
abstractions (e.g., Continual Query) for
the construction of large scale distributed CPS/IOT applications. In
addition to the focus on
performance, we anticipate that other quality of service dimensions such
as availability, reliability,
security, and privacy will become important concerns. We will discuss
research opportunities and
challenges that bring systems concepts and techniques such as streams,
events, and code generation to
CPS/IOT applications, with real world application scenarios such as the
collection and management of a
large amount and variety of radiation sensor data and metadata.
----------------------------------------
Bio Sketch: Calton Pu was born in Taiwan and grew up in Brazil. He
received his PhD from University of
Washington in 1986 and served on the faculty of Columbia University and
Oregon Graduate Institute.
Currently, he is holding the position of Professor and John P. Imlay,
Jr. Chair in Software in the College of
Computing, Georgia Institute of Technology. He has worked on several
projects in systems and database
research. His contributions to systems research include program
specialization and software feedback.
His contributions to database research include extended transaction
models and their implementation.
His recent research has focused on automated system management in clouds
(Elba project) and
document quality, including spam processing. He has collaborated
extensively with scientists and
industry researchers. He has published more than 70 journal papers and
book chapters, 200 conference
and refereed workshop papers. He served on more than 120 program
committees, including the co-PC
chairs of SRDS'95, ICDE’99, COOPIS’02, SRDS’03, DOA’07, DEBS’09,
ICWS’10, CollaborateCom'11, and cogeneral
chair of ICDE'97, CIKM'01, ICDE’06, DEPSA’07, CEAS’07, SCC’08,
CollaborateCom’08, and World
Service Congress’11.

-- 
-----------------------------------------------------------------------
中野　美由紀	東京大学　生産技術研究所　戦略情報融合国際研究センタ
Miyuki NAKANO	Institute of Industrial Science, Univ. of Tokyo
　　　　　　　　Center for Information Fusion
miyuki [at] tkl.iis.u-tokyo.ac.jp