31st ACM Symposium
on Applied Computing
Pisa, Italy April 4-8, 2016
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Association for Computing Machinery |
Sponsored by
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Association for Computing Machinery |
| Sponsored by
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Professor Francesco Marcelloni
University of Pisa
Pisa, Italy
f.marcelloni@iet.unipi.it
Program Schedule:
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Room
A
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Room
B
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Room
C
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Room
D
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9:00am
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Giuseppe Amato, Fabrizio
Falchi, Claudio Gennaro AM
Coffee Break |
T#2:
Developing Next-Generation Embedded and Cyber-Physical Systems: Albert M. K. Cheng |
T#3: Mining (Streams of) Networked Data Michelangelo Ceci, João
Gama AM
Coffee Break |
Hossain Shahriar
AM Coffee Break |
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12:30pm
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Social
Luncheon for attendees who registered for the Tutorials.
The luncheon event will be held at the conference venue, and lunch tickets will be issued. |
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14:30pm
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Giuseppe Amato, Fabrizio
Falchi, Claudio Gennaro PM
Coffee Break |
Frèdèric
Loulergue PM
Coffee Break |
Yong Zheng PM
Coffee Break |
Giuseppe Anastasi, Simone
Brienza, Domenico De Guglielmo |
Tutorials Details:
Monday April 4, 2016, 9:00am - 12:30pm (Coffee Break: 10:30am - 11:00noon)
T#1:
Multimedia Information Retrieval on Very Large Scale
Presenters: Giuseppe Amato, Fabrizio Falchi, and Claudio Gennaro
Handout:
T1-Handout
Intro, Part-1,
Part-2, and
Part-3
(copyrighted materials.
The copyright belongs to the tutorial presenter unless otherwise stated)
Abstract:
Information on the web and on the social networks is increasingly becoming
multimedia driven rather than text driven. Techniques able to effectively
and efficiently deal with multimedia data are, therefore, of paramount importance.
Popular search engines such as Google and Bing already offer visual search
functionalities and the research effort in this direction is rapidly increasing.
This tutorial will discuss the issues related to Multimedia Information Retrieval
in very large dataset of visual documents. The tutorial will first give an
overview of the most popular and effective visual features for content based
retrieval: global visual descriptors, local visual descriptors, and deep/CNN
features. Then, it will introduce techniques, as for instance LSH and permutation
based methods, able to perform similarity search very efficiently, on a large
scale (hundred millions images and more) with limited computing and storage
resources. Finally, the tutorial will discuss how the above concepts can be
put in practice using Open Source solutions. It will introduce the OpenCV
library, that offers various tools for image analysis and feature extraction.
It will also discuss how Lucene, the text retrieval engine, can be easily
used to index and search for visual information.
Bios:
Giuseppe Amato graduated in Computer Science at the University of Pisa,
Italy, in 1992 and was awarded a PhD in Computer Science at the University
of Dortmund, Germany, in 2002. Since 1994 he has been a member of the research
staff of ISTI-CNR (previously IEI-CNR) in Pisa, working in the area of Multimedia
Information Systems. His main research interests are content-based retrieval
of multimedia documents, access methods for similarity search of multimedia
documents, wireless sensor networks. He has published in international journals
and conferences in the areas of information 4 Giuseppe Amato, Fabrizio Falchi,
Claudio Gennaro systems and multimedia information retrieval. He has participated
in several EC and national funded research actions in the area of multimedia
information retrieval.
Fabrizio Falchi is researcher at the Networked Multimedia Information System
Laboratory (NeMIS) of the Information Science and Technologies Institute (ISTI)
of the Italian CNR in Pisa. He has a Ph.D. in Information Engineering from
University of Pisa (Italy), and a Ph.D. in Informatics from Faculty of Informatics
of Masaryk University of Brno (Czech Republic). He also received an M.B.A.
from Scuola Superiore Sant’Anna in Pisa. His research interests include
similarity search, distributed indexes, multimedia information retrieval,
computer vision, peer-to-peer systems. He has participated
in several EC and National research projects. He has published in international
journals and conferences in the areas of information systems and multimedia
information retrieval.
Claudio Gennaro is a researcher at CNR-ISTI. He received the ”Laurea”
degree in Electronic Engineering from the University of Pisa, Italy, in 1994
and Master Degree in Information Technology at CEFRIEL of Milan. He received
PhD Degree in Computer Engineering and Automatica in 1999 from Politecnico
di Milano. His main interests are: Wireless Sensor Networks, Access Structures
for Multimedia Retrieval, Peer-to-Peer Systems, Digital Libraries, Model of
Metadata for Audio/Video, Performance Evaluation, and Parallel Computing.
Claudio Gennaro has had considerable previous experience in participation
of European projects and has published several articles in the area of Multimedia
Information Retrieval.
Presenter: Albert M. K. Cheng
This
Tutorial has been canceled.
T#3: Mining (Streams of) Networked Data
Presenters: Michelangelo Ceci and João Gama
Handout:
T3-Handout
Part1 and
Part-2
(copyrighted materials.
The copyright belongs to the tutorial presenter unless otherwise stated)
Abstract:
Networks have become ubiquitous in several social, economical and scientific
fields, ranging from the Internet to social sciences, biology, epidemiology,
geography, communication systems, finance and many others. For this reason,
in recent years several data mining approaches, specifically designed for
tackling predictive and descriptive tasks for network structured data, have
been proposed. The main challenges they have to face with are: i) the inherent
dependency of the connected node which introduces some form of autocorrelation
ii) the possible dynamic nature of network data which demands for data stream
mining algorithms iii) the possible heterogeneity of nodes and edges. In this
tutorial we will discuss the different data mining tasks typically considered
when mining network data, with particular emphasis on the three main challenges
described before. It will conclude with a review of some practical applications
of the presented methods in the areas of functional genomics, sensor networks,
and social networks.
Bio:
Michelangelo Ceci received a "laurea"degree from the University
of Bari in 2001. In 2005 he received his Ph.D. degree in Computer Science
from the same University. Since 2005 he is an assistant professor at the Dept
of Computer Science, University of Bari, Italy. His main research interests
are in data mining and machine learning from complex and networked data. He
was a visiting researcher at the University of Bristol (U.K.) and at the JSI
(SLO). He has published more than 140 papers in refereed journals and conferences.
He is member of the editorial boards of: IJSNM, IJDSN, IJDATS and JAIS. He
is CoChair of DS 2016 and ECMLPKDD 2017. He has been the program cochair of
five workshops, the organizing committee chair of SEBD 2007, member of the
editorial committee of ``Intelligenza Artificiale'' and member of the editorial
board of the ECMLPKDD 2014 and 2015 journal tracks.
João
Gama received his Licenciado degree from the Fac. of Engineering of the University
of Porto, Portugal. In 2000 he received his Ph.D. degree in Computer Science
from the Faculty of Sciences of the same University. He joined the Faculty
of Economy where he holds the position of Associate Professor, He is also
a senior researcher at LIAAD, a group belonging to INESC Porto. He has worked
in projects and authored papers in areas related to machine learning, data
streams and adaptive learning systems and is a member of the editorial board
of international journals in his area of expertise. He served as Cochair of
ECML 2005, DS 2009, ADMA09, IDA 2011, ECMPKDD 2015 and a series of Workshops
on KDDS and Knowledge Discovery from Sensor Data with ACM SIGKDD. He is author
of a recent book on Knowledge Discovery from Data Streams.
T#4:
Secure and Reliable Mobile Applications: Challenges and Approaches
Presenter: Hossain Shahriar
Handout:
T4-Handout
(copyrighted materials.
The copyright belongs to the tutorial presenter unless otherwise stated)
Abstract:
An increasing number of mobile applications are being developed to meet
various needs of end users including SMS messaging, social networking, and
game playing. It has been estimated that the revenues from mobile applications
are expected to rise globally from $68Bn in 2013 to $143Bn in 2016. Android
has become the leading smartphone Operating System in the world and currently
occupying more than 50% of the global market share of smartphone. Unfortunately,
this emerging area is not free from security and reliability issues. Many
of developed mobile applications contain vulnerabilities that may be exploited
to cause unwanted actions. Reports find that 92% of Android’s top 500
popular applications are vulnerable to some extent of security or privacy
risk. More than 50% of mobile devices have unpatched vulnerabilities, opening
to malicious applications (malware) and attacks.
Malware on a smartphone can make a phone partially or fully unusable, cause unwanted billing, or steal contact information stored in a phonebook. Further, benign applications may contain vulnerabilities due to the lack of developer knowledge and malware applications can exploit the known vulnerabilities by providing malicious inputs. Android applications may also suffer from resource leakage. Particularly, memory leak can occur when users navigate applications in devices though screen rotation and pressing of built-in buttons leading to the crash of applications. This tutorial is intended to provide a basic overview of Android applications, malware engineering, classification of malware, and mitigation approaches. We also explore content leakage vulnerability that may lead tosecurity breaches and memory leakage that may cause an application to crash.
Bio:
Dr. Hossain Shahriar is currently an Assistant Professor of Information
Technology at Kennesaw State University, Georgia, USA. His research interests
include software security, web application security, software testing, mobile
application security, and malware analysis. Dr. Shahriar is an expert on application
security testing with extensive publications and industry experience. His
research has attracted a number of awards including IEEE DASC 2011 Best Paper
Award, Outstanding PhD Research Achievement Award 2011, and IEEE Kingston
Section Research Excellence Award 2008. Dr. Shahriar presented tutorials in
ACM SAC 2011 and IEEE ISSRE 2012, and has been invited to present a tutorial
on web application security issues in ACM/SIGSAC SIN 2013. He has served as
PC member in various international conferences related to computer and software
security such as ACM SAC 2014 (Computer Security Track), ACM/SIGSAC SIN 2014,
and IEEE ITNG 2014. He is also serving as an associate editor of the International
Journal of Secure Software Engineering. Dr. Shahriar is currently a member
of the ACM, ACM SIGAPP, and IEEE.
Monday
April 4, 2016, 2:30pm
- 6:00pm (Coffee Break: 4:00pm - 4:30pm)
T#1:
Multimedia Information Retrieval on Very Large Scale
Presenters: Giuseppe Amato, Fabrizio
Falchi, and Claudio Gennaro
Handout:
T1-Handout
Part-1, Part-2,
Part-3, and
Part-4
(copyrighted materials.
The copyright belongs to the tutorial presenter unless otherwise stated)
Abstract and Bios: Please see T#1 above.
T#5: Development
of Correct-by-Construction Functional Parallel Programs
Presenter: Fr´ed´eric Loulergue
Handout:
T5-Handout
(copyrighted materials.
The copyright belongs to the tutorial presenter unless otherwise stated)
Abstract:
With the current generalisation of parallel architectures and increasing
requirement of parallel computation arises the concern of applying formal
methods, which allow specifications of parallel and distributed programs to
be precisely stated and the conformance of an implementation to be verified
using mathematical techniques. However, the complexity of parallel programs,
compared to sequential ones, makes them more error-prone and difficult to
verify. This calls for a strongly structured form of parallelism, which should
not only be equipped with an abstraction or model that conceals much of the
complexity of parallel computation, but also provides a systematic way of
developing such parallelism from specifications for practically nontrivial
examples. Program calculation is a kind of program transformation based on
the theory of constructive algorithms. An efficient program is derived step-by-step
through a sequence of transformations that preserve the meaning and hence
the correctness. With suitable data-structures, program calculation can be
used for writing parallel programs. The SYDPACC system is a set of libraries
for the proof assistant Coq that allows to write naive (i.e. inefficient)
functional programs then to transform them into efficient versions that could
be automatically parallelised within the framework before being extracted
from Coq to code in the functional language OCaml plus calls to the parallel
functional programming library Bulk Synchronous Parallel ML. The tutorial
is an introduction both to Coq1 and the SYDPACC system for the systematic
development of correct and verified parallel programs.
Bio:
Fr´Ed´Eric Loulergue obtained his PhD in Computer Science
from the University of Orl´eans in 2000 and his Habilitation in Computer
Science from Universit´e Paris Val-de-Marne in 2004. He is currently
a full professor at Universit´e d’Orl´eans. His research
interest is high-level parallel programming: semantics and implementation
of parallel languages, certification of parallel programs and compilers as
well as parallel (scientific) applications. Software associated to his research
work include Bulk Synchronous Parallel ML (BSML) and the SyDPaCC system for
the systematic development of programs for parallel and cloud computing. He
co-organised the series of international workshop on High-Level Parallel Programming
and Applications (HLPP) between 2003 and 2010 and is now a member of its steering
committee. He created and (co)-organised the series of international workshop
on Practical Aspects of High-Level Parallel Programming (PAPP) from 2004 to
2012. He is a member of the editorial board of Scalable Computing: Practice
and Experience, and Technique et Science Informatiques. He was deputy director
of the Laboratory of Algorithms, Complexity and Logic (LACL), and deputy director
of the Laboratoire d’Informatique Fondamentale d’Orl´eans
(LIFO). He is currently the head of the Logic Modelling and Verification (LMV)
research team at LIFO.
T#6: Context In
Recommender Systems
Presenter: Yong Zheng
Handout:
T6-Handout
(copyrighted materials.
The copyright belongs to the tutorial presenter unless otherwise stated)
Abstract:
Recommender system (RS) is a popular information system being able to alleviate
the information overload problem and assist user's decision makings by recommending
appropriate information to the end users. It has been widely used in different
domains and applications, such as e-commerce (e.g., Amazon.com and eBay),
social media (e.g., Facebook and Twitter), movies (e.g., Netflix and Moviepilot),
music (e.g., Pandora and Spotify), etc. During the past decades, several effective
and efficient recommendation algorithms have been developed to meet the requirements
of the corresponding applications in those domains. Meantime, there are many
novel RS emerged, such as social RS, group RS, and context-aware RS. Context-aware
recommender system (CARS) is the one trying to adapt their recommendations
to users' specific contextual situations, such as time, location, companion,
weather, and so forth. Accordingly, context-aware recommendation algorithms
additionally take contexts into consideration in contrast to the traditional
recommendation approaches. Researchers in CARS believe that recommendations
cannot stand alone without considering contexts, since users' preferences
or decisions are always changing from time to time, from contexts to contexts.
For example, you may choose a romantic movie to watch with partner, but probably
a cartoon if you are going to watch with kids. And you may choose a formal
restaurant for a dinner with your business partner, rather than a fast food
store for a quick lunch by yourself. In those examples, companion and occasions
are viewed as influential contextual factors in the movie and restaurant domain
respectively.
There are two typical recommendation tasks involved when context is taken
into account in recommender systems: one is context-aware recommendation (CAR)
and another one is context recommendation (CR). The typical research problems
or challenges in CAR include context identification and selection, context
incorporation and adaptation, context evaluation and interpretation, where
CAR aims to recommend items to users by adapting contextual information. For
example, which movies are appropriate to be recommended to John to watch with
his girlfriend? By contrast, context recommendation is a novel research direction
emerged in recent years, and it is going to suggest appropriate contexts for
the users to consume the item. For example, which could be the best contexts
for me to watch the movie "Titanic"? Potential answers could be
seeing it in a theater with your partner at weekend. In this half-day tutorial,
a comprehensive overview on those two recommendation tasks - CAR and CR, will
be introduced to the audience. In addition, an open-source context-aware recommendation
library, named as CARSKit, will also be introduced in order to show the ease
of adopting and evaluating context-aware recommendation algorithms by this
toolkit.
Bio:
Yong Zheng got his B.S. and M.S. degree in computer science in China, and
he is going to obtain the PhD degree from DePaul University, Chicago in early
2016. His research interests lie in multi-disciplinary areas, including artificial
intelligence, data mining and machine learning, information retrieval and
recommender systems, as well as user modeling, affective computing and human-computer
interactions. Over the past few years, his research focused on recommender
systems, especially the context-aware recommender systems. He has published
more than two dozens of high-quality papers in top-ranked and peer-reviewed
academic conferences. In addition, he served program committee member and
reviewer for several academic journals, such as ACM Transactions on Information
Systems (TOIS)? ACM Transactions on the Web (TWeb), User Modeling and User-Adapted
Interaction (UMUAI), and international conferences, such as WWW, ACM RecSys,
ACM IUI, ACM SAC, UMAP, ICWSM, and so forth. Besides, he is a member of Association
for Computing Machinery (ACM) and Institute of Electrical and Electronics
Engineers (IEEE). Additional information is available at http://goo.gl/3ksm6.
T#7:
Towards the Internet of Relevant Things
Presenters: Giuseppe Anastasi, Simone Brienza, and Domenico De Guglielrmos
Handout:
T7-Handout and T7-Survey
(copyrighted materials.
The copyright belongs to the tutorial presenter unless otherwise stated)
Abstract:
The Internet of Things (IoT) will completely change the way we live and work.
In near future, billions of smart objects will be connected to the Internet,
paving the way for a large number of innovative services in different application
domains including smart cities, smart buildings, factory automation, e-health,
etc. In many of such domains, applications have stringent requirements in
terms of communication reliability, timeliness, scalability, and energy efficiency.
To address the needs of such critical applications, the IEEE has recently
released the 802.15.4e amendment that extends the original 802.15.4-2006 standard.
By combining time slotted access with multi-channel communication and frequency
hopping, the new 802.15.4e MAC protocols can provide highlyreliable, time-bounded,
and low-power communication. Also, they can easily support multi-hop mesh
networks.
This tutorial will present the opportunities offered by the new standard in
the perspective of the Internet of Things. Specifically, it will start with
a description of the IEEE 802.15.4 standard to highlight the main reasons
that limit its adoption in critical application scenarios. Then, the improvements
introduced by 802.15.4e will be discussed, with focus on the main 802.15.4e
MAC protocols (i.e., TSCH, DSME). For each considered MAC protocol, a description
of its specific features will be provided and potential application domains
will be identified. The tutorial will also include a survey of the main research
activities on 802.15.4e networks. Special attention will be devoted to issues
arising from the integration of 802.15.4e MAC protocols within the IoT framework.
Bio:
Giuseppe Anastasi is Full Professor and Associate Head at the Department of
Information Engineering (DII) of the University of Pisa, Italy. He is also
the director of the Smart Cities National Lab, supported by CINI (Italian
University Consortium for Informatics). Finally, he directs the executive
Master in Smart Cities, a post-graduate specialization program organized by
the University of Pisa in cooperation with the Institute for Informatics and
Telematics (IIT) of the Italian National Research Council (CNR). His scientific
interests include Distributed and P2P Systems, Internet of Things, Pervasive
Computing, Sustainable Computing, and ICT for Smart Cities. He is the founding
co-director of the Pervasive Computing & Networking Laboratory (PerLab)
at the University of Pisa, and has contributed to many research programs funded
by both national and international institutions. He is a coeditor of two books:
Advanced Lectures in Networking (LNCS 2497, Springer, 2002) and Methodologies
and Technologies for Networked Enterprises (LNCS 7200, Springer, 2012). He
has published about 130 research papers in the area of computer networking
and pervasive computing, gathering more than 4500 citations according to Google
Scholar (H-index=30).
Dr. Anastasi is Associate Editor of Sustainable Computing (SUSCOM) and Area
Editor of Pervasive and Mobile Computing (PMC). He is currently serving as
Program Co-chair of the IEEE Mobile Ad Hoc and Senso Networks (MSN 2015) and
of the IEEE International Conference on Smart Computing (SMARTCOMP 2016).
Previously, he has served as Area Editor of Computer Communications (ComCom,
2008-10), General Co-chair of IEEE WoWMoM 2005, Program Chair of IFIP/IEEE
SustainIT 2012, IEEE PerCom 2010 and IEEE WoWMoM 2008, Vice Program Chair
of IEEE MASS 2007. He has been the co-founder of a number of successful international
workshops and conferences. Currently, he is a member of the Board of Directors
of the Italian National University Consortium for Informatics (CINI). He has
been a member of the IEEE Computer Society since 1994. Dr. Anastasi received
the M.Sc. degree in Electronics Engineering, and the Ph.D. degree in Computer
Engineering, both from the University of Pisa, in 1990 and 1995, respectively.
Additional Information available at: http://www.iet.unipi.it/~anastasi/.
