SAC 2016
31st ACM Symposium
on Applied Computing

Pisa, Italy   April 4-8, 2016
Association for
Computing Machinery
Sponsored by
Tutorials Program

SAC 2016 is offering 1 full-day tutorial and 6 half-day tutorials on Monday April 4, 2015. Tutorials are open for those who registered for them. Handouts will be available online right before the conference. No printed handouts are provided during the tutorials. Please bring your copies of the handouts (printed or electronic). Lunch tickets will be issues for registered attendees. For questions or inquiries about the tutorials, please contact the Tutorials Chair.

Professor Francesco Marcelloni
University of Pisa
Pisa, Italy
f.marcelloni@iet.unipi.it

Program Schedule:

 
Room A
Room B
Room C
Room D
9:00am


T#1: Multimedia Information Retrieval on Very Large Scale

Giuseppe Amato, Fabrizio Falchi, Claudio Gennaro

AM Coffee Break
10:30 - 11:00


This Tutorial has
been canceled

T#2: Developing Next-Generation Embedded and Cyber-Physical Systems:
Functional Reactive Programming, RTL-based Formal Verification, and
Real-Time Virtual Resources

Albert M. K. Cheng

AM Coffee Break
10:30 - 11:00


T#3: Mining (Streams of) Networked Data

Michelangelo Ceci, João Gama

AM Coffee Break
10:30 - 11:00


T#4: Secure and Reliable Mobile Applications: Challenges and Approaches

Hossain Shahriar

AM Coffee Break
10:30 - 11:00

12:30pm
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.
14:30pm


T#1: Multimedia Information Retrieval on Very Large Scale

Giuseppe Amato, Fabrizio Falchi, Claudio Gennaro

PM Coffee Break
16:00 - 16:30


T#5: Development of Correct-by-Construction Functional Parallel Programs

Frèdèric Loulergue

PM Coffee Break
16:00 - 16:30


T#6: Context In Recommender Systems

Yong Zheng

PM Coffee Break
16:00 - 16:30


T#7: Towards the Internet of Relevant Things

Giuseppe Anastasi, Simone Brienza, Domenico De Guglielmo

PM Coffee Break
16:00 - 16:30


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.


T#2: Developing Next-Generation Embedded and Cyber-Physical Systems: Functional Reactive Programming, RTL-based Formal Verification, and Real-Time Virtual Resources

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/.