Presentation made as a tutorial at the rcis2015 conference in Athens, Greece, on May 13, 2015.
Video recording available online on IEEE Education (http://www.computer.org/web/computingnow/education)
Using trained machine learning predictors in GurobiXavier Nodet
With Gurobi Machine Learning, an open-source Python package, you can integrate directly predictors written using scikit-learn, Keras or PyTorch in your optimization model.
This allows you, for example, to decide the selling price and deduce the expected demand in your optimization model, instead of assuming a fixed value for the price.
This talk was presented at ROADEF 2023, Rennes, France.
1) Design and Implementation of Multicore Processors
2) Coherence and Consistency
3) Power and Temperature
4) Interconnects
5) Multicore Caches
6) Security
7) Real world examples
This presentation discusses about the following topics:
Hybrid Systems
Hybridization
Combinations
Comparison of Expert Systems, Fuzzy Systems, Neural Networks and Genetic Algorithms
Current Progress
Primary Components
MultiComponents
Degree of Integration
Transformational, hierarchial and integrated
Stand Alone Models
Integrated – Fused Architectures
Generalized Fused Framework
System Types for Hybridization
Machine learning (ML) and natural language processing (NLP)Nikola Milosevic
Short introduction on natural language processing (NLP) and machine learning (ML). Speaks about sub-areas of artificial inteligence and then mainly focuses on the sub-areas of machine learning and natural language processing. Explains the process of data mining from high perspective
The dominant sequence transduction models are based on complex recurrent or convolutional neural networks in an encoder-decoder configuration. The best performing models also connect the encoder and decoder through an attention mechanism. We propose a new simple network architecture, the Transformer, based solely on attention mechanisms, dispensing with recurrence and convolutions entirely. Experiments on two machine translation tasks show these models to be superior in quality while being more parallelizable and requiring significantly less time to train.
Our model achieves 28.4 BLEU on the WMT 2014 English-to-German translation task, improving over the existing best results, including ensembles by over 2 BLEU. On the WMT 2014 English-to-French translation task, our model establishes a new single-model state-of-the-art BLEU score of 41.0 after training for 3.5 days on eight GPUs, a small fraction of the training costs of the best models from the literature. We show that the Transformer generalizes well to other tasks by applying it successfully to English constituency parsing both with large and limited training data.
A Review of Deep Contextualized Word Representations (Peters+, 2018)Shuntaro Yada
A brief review of the paper:
Peters, M. E., Neumann, M., Iyyer, M., Gardner, M., Clark, C., Lee, K., & Zettlemoyer, L. (2018). Deep contextualized word representations. In NAACL-HLT (pp. 2227–2237)
AI firsts: Leading from research to proof-of-conceptQualcomm Research
AI has made tremendous progress over the past decade, with many advancements coming from fundamental research from many decades ago. Accelerating the pipeline from research to commercialization has been daunting since scaling technologies in the real world faces many challenges beyond the theoretical work done in the lab. Qualcomm AI Research has taken on the task of not only generating novel AI research but also being first to demonstrate proof-of-concepts on commercial devices, enabling technology to scale in the real world. This presentation covers:
The challenges of deploying cutting-edge research on real-world mobile devices
How Qualcomm AI Research is solving system and feasibility challenges with full-stack optimizations to quickly move from research to commercialization
Examples where Qualcomm AI Research has had industrial or academic firsts
Using trained machine learning predictors in GurobiXavier Nodet
With Gurobi Machine Learning, an open-source Python package, you can integrate directly predictors written using scikit-learn, Keras or PyTorch in your optimization model.
This allows you, for example, to decide the selling price and deduce the expected demand in your optimization model, instead of assuming a fixed value for the price.
This talk was presented at ROADEF 2023, Rennes, France.
1) Design and Implementation of Multicore Processors
2) Coherence and Consistency
3) Power and Temperature
4) Interconnects
5) Multicore Caches
6) Security
7) Real world examples
This presentation discusses about the following topics:
Hybrid Systems
Hybridization
Combinations
Comparison of Expert Systems, Fuzzy Systems, Neural Networks and Genetic Algorithms
Current Progress
Primary Components
MultiComponents
Degree of Integration
Transformational, hierarchial and integrated
Stand Alone Models
Integrated – Fused Architectures
Generalized Fused Framework
System Types for Hybridization
Machine learning (ML) and natural language processing (NLP)Nikola Milosevic
Short introduction on natural language processing (NLP) and machine learning (ML). Speaks about sub-areas of artificial inteligence and then mainly focuses on the sub-areas of machine learning and natural language processing. Explains the process of data mining from high perspective
The dominant sequence transduction models are based on complex recurrent or convolutional neural networks in an encoder-decoder configuration. The best performing models also connect the encoder and decoder through an attention mechanism. We propose a new simple network architecture, the Transformer, based solely on attention mechanisms, dispensing with recurrence and convolutions entirely. Experiments on two machine translation tasks show these models to be superior in quality while being more parallelizable and requiring significantly less time to train.
Our model achieves 28.4 BLEU on the WMT 2014 English-to-German translation task, improving over the existing best results, including ensembles by over 2 BLEU. On the WMT 2014 English-to-French translation task, our model establishes a new single-model state-of-the-art BLEU score of 41.0 after training for 3.5 days on eight GPUs, a small fraction of the training costs of the best models from the literature. We show that the Transformer generalizes well to other tasks by applying it successfully to English constituency parsing both with large and limited training data.
A Review of Deep Contextualized Word Representations (Peters+, 2018)Shuntaro Yada
A brief review of the paper:
Peters, M. E., Neumann, M., Iyyer, M., Gardner, M., Clark, C., Lee, K., & Zettlemoyer, L. (2018). Deep contextualized word representations. In NAACL-HLT (pp. 2227–2237)
AI firsts: Leading from research to proof-of-conceptQualcomm Research
AI has made tremendous progress over the past decade, with many advancements coming from fundamental research from many decades ago. Accelerating the pipeline from research to commercialization has been daunting since scaling technologies in the real world faces many challenges beyond the theoretical work done in the lab. Qualcomm AI Research has taken on the task of not only generating novel AI research but also being first to demonstrate proof-of-concepts on commercial devices, enabling technology to scale in the real world. This presentation covers:
The challenges of deploying cutting-edge research on real-world mobile devices
How Qualcomm AI Research is solving system and feasibility challenges with full-stack optimizations to quickly move from research to commercialization
Examples where Qualcomm AI Research has had industrial or academic firsts
Total Radiology Conference at Arab Health 2015Cheryl Prior
With constant developmenst in imaging technology and evolving clinical use of available modalities, it is important to provide radiologists, radiographers and radiology technicians with educational opportunities to review the latest trends in the field of radiology.
The 15th edition of the Total Radiology Conference is a four-day multidisciplinary scientific meeting which will present the latest advances in medical imaging, accurate imaging diagnosis and improvement of care quality for patients in the Middle East.
The topics covered in this Radiology Conference will feature enhanced efficiency of established modalities like X-ray and sonography for optimal utilisation and high-end imaging utilities like MRI, PETCT and how these can be utilized to their full potential.
World-renowned experts will discuss latest advancements in musculoskeletal imaging, breast imaging, nuclear medicine and neuroradiology.
Sessions on key and diverse aspects of radiology and special sessions for radiographers have been arranged throughout the event.
Key themes
Cardiac imaging
Breast imaging
Abdominal imaging
Nuclear medicine
Interventional radiology
Neuroradiology
High intensity frequency ultrasound
Quality assurance
Quality control & patient safety
ESTA ES LA PRESENTACIÓN ELABORADA POR LOS ALUMNOS DE 6º CURSO DEL ceip MIGUEL SERVET DE FRAGA Y QUE PARTICIPÓ EN LA EDICIÓN 2013 DEL CONCURSO ESCOLAR DE MERCOEQUIP
The Forrester Wave Enterprise Business Intelligence Platforms, Q3 2008Cezar Cursaru
SAS was among the select companies that Forrester invited to participate in its 2008 Forrester Wave report, The Forrester Wave: Enterprise Business Intelligence Platforms, Q3 2008. In this evaluation, SAS was cited as a leader in Enterprise Business Intelligence Platforms.
Concept extraction from the web of things (3)Amélie Gyrard
Mahda Noura, Amelie Gyrard, Sebastian Heil and Martin Gaedke. Concept extraction from the web of things knowledge bases. International Conference WWW/Internet. 21-23 October 2018, Budapest, Hungary,
Paper: http://knoesis.org/node/2913
Semantic web technologies are a major driver for semantic interoperability in IoT-generated data by using shared vocabularies in an ontology-driven approach. While there is a growing interest in standardization of ontologies for IoT, there is still a lack of common agreement for a specific IoT ontology. Numerous concepts and relations have been designed within existing ontologies to handle different features of IoT data. However, there are many redundant and overlapping concepts designed within existing standardizations and groups. We found that new ontologies constantly redesign the same concepts in IoT. Therefore, it is a challenge to reuse and unify these different IoT ontologies with redundant concepts. In this paper, we investigate what are the most used terms within IoT ontologies? We identify the fourteen most popular ontologies within generic IoT and WoT domain. Analysis of popular concepts among these ontologies allows to automatically rank the knowledge. This work will enable guiding ontology engineers to re-use and unify existing ontologies, a required step to achieve semantic interoperability. Moreover, this work could contribute towards building iot.schema.org.
SHELDON is the first true hybridization of NLP machine reading and Semantic Web. It is a framework that builds upon a ma- chine reader for extracting RDF graphs from text so that the output is compliant to Semantic Web and Linked Data patterns. It extends the current human-readable web by using Semantic Web practices and technologies in a machine-processable form. Given a sentence in any language, it provides different semantic functionalities (frame detection, topic extraction, named entity recognition, resolution and coreference, terminology extraction, sense tagging and disambiguation, taxonomy induction, semantic role labeling, type induction, sentiment analysis, citation inference, relation and event extraction) as well as nice visualization tools which make use of the JavaScript infoVis Toolkit and RelFinder, as well as a knowledge enrichment component that extends machine reading to Semantic Web data. The system can be freely used at http://wit.istc.cnr.it/stlab-tools/sheldon.
Presentation made for the event "Digital transformation in France and Germany: Consequences for industry, society & higher education" organized by the French-German University in cooperation with Institut Mines-Télécom https://www.dfh-ufa.org/fr/digital-transformation-in-france-and-germany/
Software Modeling and Artificial Intelligence: friends or foes?Jordi Cabot
See how modeling can help the AI world (e.g. a model-driven approach to build chatbots) and how AI can create smarter modeling tools (e.g. using ML to learn transformations and code generation templates)
ActiVis: Visual Exploration of Industry-Scale Deep Neural Network ModelsMinsuk Kahng
Presentation slides for the following paper presented at IEEE VIS 2017 (http://ieeevis.org).
Minsuk Kahng, Pierre Y. Andrews, Aditya Kalro, and Duen Horng (Polo) Chau. ActiVis: Visual Exploration of Industry-Scale Deep Neural Network Models. IEEE Transactions on Visualization and Computer Graphics, Vol. 24, No. 1 (VAST 2017).
Thought Leadership Session: Enterprise Semantics & Ontology, The Power of Und...Wim Laurier
Learn the 1-on-1 of Semantics & Ontology by international authorities. Explore how semantics and ontology is used as the underlying conceptual structure of an enterprise by transforming interoperability beyond existing boundaries. Understand the complex interdependencies of enterprise operations through semantics and ontology. Discover how the Global University Alliance researches, compares, analyzes and develops Best and LEADing Practices around Enterprise Semantics & Ontology.
Professor Simon Polovina
International authority and thought leader in Enterprise Semantics Sheffield Hallam University, United Kingdom
Head of Enterprise Semantics research and development at the Global University Alliance
Professor Wim Laurier
International authority and thought leader in Enterprise Ontology Université Saint-Louis, Bruxelles and Ghent University
Head of Enterprise Ontology research and development at the Global University Alliance
Thought Leadership Session: Enterprise Semantics & Ontology, The Power of Und...Wim Laurier
Learn the 1-on-1 of Semantics & Ontology by international authorities. Explore how semantics and ontology is used as the underlying conceptual structure of an enterprise by transforming interoperability beyond existing boundaries. Understand the complex interdependencies of enterprise operations through semantics and ontology. Discover how the Global University Alliance researches, compares, analyzes and develops Best and LEADing Practices around Enterprise Semantics & Ontology.
Professor Simon Polovina
International authority and thought leader in Enterprise Semantics Sheffield Hallam University, United Kingdom
Head of Enterprise Semantics research and development at the Global University Alliance
Professor Wim Laurier
International authority and thought leader in Enterprise Ontology Université Saint-Louis, Bruxelles and Ghent University
Head of Enterprise Ontology research and development at the Global University Alliance
IoT: New business paradigm for SMEs? - IoTSWC side event
Professor Ernest Teniente
Session 2: Modelling and Simulation for Industry 4.0 - round table on opportunities and challenges in the new era of IoT
Similar to Meta-modeling: concepts, tools and applications (20)
De l’automatisation des tâches à la transformation numérique : un regard rétr...Saïd Assar
Dans le cadre des webinaires « Beyond your PhD » proposés par le IS Lab (https://www.linkedin.com/showcase/is-lab-imt-bs/), cette 5e édition est un exposé de Saïd Assar sur l'historique de l'informatique et une rétrospective de la discipline des Systèmes d'Information.
Experimenting multiple approaches for teaching meta-modelingSaïd Assar
Experimenting multiple approaches for teaching meta-modeling
>>Teaching with software tools <<
Presented at https://www.jamk.fi/en/Event-Calendar/the-global-faculty-colloquium/global-faculty-research-colloquium/
Contributions to the multidisciplinarity of computer science and ISSaïd Assar
Les diapos de ma présentation HDR en informatique (CNU section 27) à l'université Paris 1 Panthéon Sorbonne le vendredi 20 janvier 2017. L'enregistrement vidéo de la soutenance est visible sur https://www.youtube.com/watch?v=1ro_iaI-roA
--
Slides of my presentation for Habilitation (HDR) defense in computer science (Informatique section 27 CNU) at University Paris 1 Panthéon Sorbonne on Friday January 2017.
Video recording is visible on https://www.youtube.com/watch?v=1ro_iaI-roA
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
Welcome to TechSoup New Member Orientation and Q&A (May 2024).pdfTechSoup
In this webinar you will learn how your organization can access TechSoup's wide variety of product discount and donation programs. From hardware to software, we'll give you a tour of the tools available to help your nonprofit with productivity, collaboration, financial management, donor tracking, security, and more.
Biological screening of herbal drugs: Introduction and Need for
Phyto-Pharmacological Screening, New Strategies for evaluating
Natural Products, In vitro evaluation techniques for Antioxidants, Antimicrobial and Anticancer drugs. In vivo evaluation techniques
for Anti-inflammatory, Antiulcer, Anticancer, Wound healing, Antidiabetic, Hepatoprotective, Cardio protective, Diuretics and
Antifertility, Toxicity studies as per OECD guidelines
Embracing GenAI - A Strategic ImperativePeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
Acetabularia Information For Class 9 .docxvaibhavrinwa19
Acetabularia acetabulum is a single-celled green alga that in its vegetative state is morphologically differentiated into a basal rhizoid and an axially elongated stalk, which bears whorls of branching hairs. The single diploid nucleus resides in the rhizoid.
Honest Reviews of Tim Han LMA Course Program.pptxtimhan337
Personal development courses are widely available today, with each one promising life-changing outcomes. Tim Han’s Life Mastery Achievers (LMA) Course has drawn a lot of interest. In addition to offering my frank assessment of Success Insider’s LMA Course, this piece examines the course’s effects via a variety of Tim Han LMA course reviews and Success Insider comments.
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...Levi Shapiro
Letter from the Congress of the United States regarding Anti-Semitism sent June 3rd to MIT President Sally Kornbluth, MIT Corp Chair, Mark Gorenberg
Dear Dr. Kornbluth and Mr. Gorenberg,
The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
harassment and intimidation at the Massachusetts Institute of Technology (MIT). Failing to act decisively to ensure a safe learning environment for all students would be a grave dereliction of your responsibilities as President of MIT and Chair of the MIT Corporation.
This Congress will not stand idly by and allow an environment hostile to Jewish students to persist. The House believes that your institution is in violation of Title VI of the Civil Rights Act, and the inability or
unwillingness to rectify this violation through action requires accountability.
Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied
students that opportunity and have been hijacked to become venues for the promotion of terrorism, antisemitic harassment and intimidation, unlawful encampments, and in some cases, assaults and riots.
The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee.
• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
• The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X.
• The Committee on Ways and Means has been investigating several universities since November 15, 2023, when the Committee held a hearing entitled From Ivory Towers to Dark Corners: Investigating the Nexus Between Antisemitism, Tax-Exempt Universities, and Terror Financing. The Committee followed the hearing with letters to those institutions on January 10, 202
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
Instructions for Submissions thorugh G- Classroom.pptxJheel Barad
This presentation provides a briefing on how to upload submissions and documents in Google Classroom. It was prepared as part of an orientation for new Sainik School in-service teacher trainees. As a training officer, my goal is to ensure that you are comfortable and proficient with this essential tool for managing assignments and fostering student engagement.
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
1. Meta-modeling: concepts, tools
and applications
https://dl.dropboxusercontent.com/u/6656530/tutorial_rcis2015.html
(1) Associate Professor
Telecom Ecole de Management, Department of Information Systems
Evry, France
(2) Invited Researcher
Centre de Recherche en Informatique, University of Paris 1 La Sorbonne
France
Saïd Assar 1,2
2. 1. Introduction & background (cont'd)
2
Telecom Sud Paris
2
• INSTITUT MINES - TELECOM: 4 leading schools in
engineering and management
Telecom Paris
Telecom Bretagne
Telecom Ecole de
Management
3. 1. Introduction & background (cont'd)
33
Since 1999, long-term research collaboration with CRI at
Paris 1 Sorbonne
4. Learning objectives
To understand what is a meta-model, its historical
background, when it is needed and how it can be defined
and exploited.
To witness and participate in building concrete meta-
models and exploiting them using existing meta-modeling
technical infrastructures
To be aware of problems and challenges in meta-
modeling and the actual state-of-the-art regarding these
issues.
4
5. Agenda
5
1. Introductory examples
2. Abstraction levels and the instantiation problem
3. Computerized tools for meta-modeling
4. Illustration
a) A Domain Specific Language (DSL) for IoT v3.0 Framework
b) A DSL to model software development processes
c) A DSL to specify web applications
5. Research challenges
6. Conclusion
5
6. 1. Introductory examples – what is a model ?
6
"A model (M) for a system (S) and an observer (O) is any kind of representation
which can help O in answering questions and reasoning about S“
It is an abstraction, a reduction of reality to its most relevant aspects
It is the result (i.e. the product) of some specific process
It is built using some kind of notation (formal and/or graphical)
Descriptive vs. prescriptive models
Models are artifacts, i.e. they can also be modeled
Observer
7. 1. Introductory examples – what is a meta-model ?
7
Source: Hanns-Alexander Dietrich, Exercice 1 Meta-modelling, European Research
Center for Information Systems, Information Modelling Summer Term 2012.
Let’s consider this very simple process model with two concepts (event,
function) and one link among concepts (event – function)
8. 1. Introductory examples – what is a meta-model ?
8
Source: Hanns-Alexander Dietrich, Exercice 1 Meta-modelling, European Research
Center for Information Systems, Information Modelling Summer Term 2012.
A meta-model would be a textual,
graphical, and/or formal representation of
the concepts and how they are linked
InstanceOf
Questions
How to represent a meta-model?
How can a MM be leveraged in IS
engineering?
9. 1. Introductory examples – generic models (1)
GR model
GB model
RUS model
IND model
IRAN model
Québec model
New York model
TR model
Suppose a trans-national car tracking
system
interoperability issue
system evolution issue
Car
plate
model
IsA
9
Are all these plates special cases
of a car plate model?
10. 1. Introductory examples – generic models
GR model
GB model
RUS model
IND model
IRAN model
Québec model
New York model
TR modelVehicle
identification
model
InstanceOf
Or is there a generic vehicle ID
model from which these models -
and may be others - can be
derived?
Interactive question:
In terms of system evolution,
these two modeling solutions are
similar or very different?
10
11. 1. Introductory examples – generic models
11
In terms of system evolution, these two modeling solutions are similar or very different?
InstanceOf
IsA
InstanceOf
InstanceOfWhat about the country code,
how to model it?
12. 1. Introductory examples – generic models (2)
12
Method M1 for simple projects
Method M2 for
large projects
Agile method M3 for
risky projects
S1
S2
S3
SN
…
L1
L2
L3
LM
…
G1
G2
G3
GK
…
General
method
IsA ?
General method
structure
InstanceOf ?
For a software development company
with different methods
evolution issue
enactment issue
13. 1. Introductory examples – IoT framework
In the field of Internet of Things (IoT), a large set of heterogeneous objects are
expected to interact and be part of a huge information network …
Is it possible to have a general model for all interacting objects?
13
14. 1. Introductory examples – IoT framework
Source
http://www.iot-a.eu/public/public-documents/d1.5/at_download/file 14
A reference model of IoT is
proposed by an FP7 project …
What this model is helpful
for?
Is it possible to provide
computerized support for
using this model?
16. Agenda
16
1. Introductory examples
2. Abstraction levels and the instantiation problem
3. Computerized tools for meta-modeling
4. Illustration
a) A Domain Specific Language (DSL) for IoT v3.0 Framework
b) A DSL to model software development processes
c) A DSL to specify web applications
5. Research challenges
6. Conclusion
16
17. 2. Abstraction levels – instanciation vs. generalisation
17
Object
CLASS
CLASS : a structure, a pattern
Object: identifier, values
• Attribute1
• Attribute2
• …
• "Value1"
• "Value2"
• …
CLASS B
• Attribute b1
• Attribute b2
• …
CLASS A
• Attribute a1
• Attribute a2
• …
InstanceOf
IsA
18. 2. Abstraction levels – the meta-modeling language issue
18
A meta-model is described using a meta-modeling language
How to describe the meta-modeling language … a circular issue.
20. 2. Abstraction levels – instantiation levels
20
• Instantiation levels in th Meta Object Facility (MOF) by OMG
Source: OMG
21. 2. Abstraction levels – the “Powertype” approach
21
Cointe, Pierre: Metaclasses are first class: The ObjVlisp Model. SIGPLAN Notices.
22(12), 156–162 (1987).
One of the earliest work on
these issues is by P. Cointe in
1987
Where does meta-modeling come from?
• Artificial intelligence (i.e. frame concept, Smalltalk, ObjVLisp)
• Databases (i.e. meta-database)
• Object oriented modeling (i.e. Classes are objects too => MetaClasses)
How to simultaneously create a generalization link AND an instantiation link
How to a define attributes to Classes
How to cross the strict instantiation levels
22. 2. Abstraction levels – the “Powertype” approach
22
How to simultaneously create a generalization link AND an instantiation link
How to a define attributes to Classes
How to cross the strict instantiation levels
Pet
PetName
DateOfBirth
Owner
AnimalSpecies
SpecieName
AvgLifeSpan
Vaccinations
Diet
1 0..*
"Cat specie"
8
"Triple", "Leukaemia"
"Fish"
"Valentina"
8-sep-2008
"César"
Illustration (Source: Gonzalez-Perez & Henderson-Sellers, Metamodelling for software engineering, p.38)
How to model species-specific characteristics, e.g. Breed ?
23. 2. Abstraction levels – the “Powertype” approach
23
Pet
PetName
DateOfBirth
Owner
CatSpecie
Breed
"Valentina"
8-sep-2008
"César"
Illustration (Source: Gonzalez-Perez & Henderson-Sellers, Metamodelling for software engineering, p.39)
Using specialization link to model
species-specific characteristics
26. 2. Abstraction levels – the “Powertype” approach
26
Task
Start
End
Duration
Task Kind
TaskName
Purpose
MinCapLevel
"Code writing"
"To write code …"
1
"12-sep-07"
"18-sep-07"
7d
"C#"
CodeWritingTask
ProgLanguage
Illustration (Source: Gonzalez-Perez & Henderson-Sellers, Metamodelling for software engineering, p.41)
PowerType and Clabject for method engineering
Clabject
Powertype
27. 2. Abstraction levels – deep instantiation
• Proposal:
– Add an indicator (potency) of the abstraction level at which the attribute
is to be instantiated
Task
+ TaskCategory1
+ TaskDuration0
CodeWritingTask
TaskCategory: Coding
T1
+ TaskDuration:10d
instance instance
27
28. Agenda
28
1. Introductory examples
2. Abstraction levels and the instantiation problem
3. Computerized tools for meta-modeling
4. Illustration
a) A Domain Specific Language (DSL) for IoT v3.0 Framework
b) A DSL to model software development processes
c) A DSL to specify web applications
5. Research challenges
6. Conclusion
28
29. 3. Computerized tools for meta-modeling
29
(1)
(2)
(3)
Focus on 3 meta-modeling tools :
30. 3. Computerized tools for meta-modeling
30
Other meta-modeling tools :
ADOxx Meta Modelling Platform
(http://www.adoxx.org/live/home)
(4)
(5)
(6) JastAdd (http://jastadd.org)
and
JastEMF
(https://code.google.com/a/eclipselabs.org/p/jastemf/)
for language engineering
(http://astreo.ii.uam.es/~jlara/metaDepth/)
33. 3. Computerized tools for meta-modeling
33
MetaEdit (1)
• A meta-CASE tool for automatic customization of CASE tools
• Result of research project at Jyväskyla (K. Lyytinen, M. Rossi, S. Kelly et al. - 1990')
• Actually commercialized by MetaCASE
• Targeted towards Domain Specific Modeling
Meta-model definition Model definition
Generate
(Executable)
code
37. 3. Computerized tools for meta-modeling
37
MetaEdit (5)
• MERL: A scripting language for generating code (i.e. flow of characters)
38. 3. Computerized tools for meta-modeling
38
MetaEdit (6)
• Example in MERL for generating SQL code from E/R schema
39. 3. Computerized tools for meta-modeling
39
Conceptbase (1)
• A deductive database supporting object-centered TELOS modeling language
• Result from research project DAIDA (J. Mylopoulos, M. Jarke et al. - 1990')
• Continued as an open source project (M. A. Jeusfled)
• Targeted towards Model Engineering
TELOS modeling language
• Any element (class, object, attribute, link, constraint … ) is internally represented as
a predicate in a deductive DB
• Attributes are first order objects i.e. they can have properties
• Attributes correspond to links between two elements
• Any object can be instantiated
Multiple instantiation ('Paul' in 'Employee' and 'Paul' in 'Student')
Multiple levels of instantiation
Multiple Generalisation/Specialisation (i.e. heritage)
Generalisation/Specialisation can co-exist with instantiation
40. 3. Computerized tools for meta-modeling
40
Conceptbase (2)
• Model llustration
Person in Class with
attribute
ID: Integer;
name:String
end
Client isA Person with
attribute
reduction:Real
end
Employee isA Person with
attribute
function: String
end
Student isA Person with
attribute
age:Integer
end
41. 3. Computerized tools for meta-modeling
41
Conceptbase (3)
• Multiple instantiation illustration
John in Student, Employee, Client with
ID
id_john: 44555
name
name_j: "John Legrand"
reduction
r1: 30.0
function
f1: "Sale manager"
age
age1: 24
end
Client with constraint
reduction_OK:
$ forall c/Client x/Real (c reduction x) ==> (x>=5.0) $
end
QueryClass AllPeople isA Person with
constraint
Allpeople_c: $ exists s/String (this nom s) $
end
42. 3. Computerized tools for meta-modeling
42
AnimalSpecies in Class, MetaClass with
attribute
SpecieName: String;
AvgLifeSpan: Integer;
Vaccinations: String;
Diet: String
end
Pet in Class, MetaClass with
attribute
PetName: String;
PetDateOfBirth: String;
PetOwner: String
end
CatSpecie in AnimalSpecies, Class with
attribute
Breed: String
SpecieName
sn: "Cat specie"
AvgLifeSpan
als: 8
Vaccinations
v1: "Triple"; v2: "Leukaemia"
Diet
d1: "Fish“ end
MyCat in CatSpecie, Pet with
Breed
MyCatBreed:"Siamese"
PetName
p1: "Valentina"
PetDateOfBirth
d1: "08-Sep-2008"
PetOwner
pow: "César“ end
Conceptbase (3)
• Implementing Class attributes and the “PowerType” concept
43. 3. Computerized tools for meta-modeling
43
Conceptbase (3)
• Implementing Class attributes and the “PowerType” concept
44. Agenda
44
1. Introductory examples
2. Abstraction levels and the instantiation problem
3. Computerized tools for meta-modeling
4. Illustration
a) A Domain Specific Language (DSL) for IoT v3.0 Framework
b) A DSL to model software development processes
c) A DSL to specify web applications
5. Research challenges
6. Conclusion
44
45. 4. Meta-modeling illustration examples
45
The IoT ARM is exemplified with a
use-case scene : A load carrier is
equipped with sensors and can
communicate with other devices in
terms of wireless radio technology.
With this hardware, every load
carrier continuously measures its
environmental parameters and
sends all measurements via the
embedded event service to the
mobile phone of the truck driver.
Source : http://www.iot-a.eu/public/public-documents/d1.5/at_download/file
Exercise 1 : Internet of Things framework
46. 4. Meta-modeling illustration examples
46
“For example, Ted is a truck driver transporting highly sensitive orchids to a retail store. After loading the orchids
on his truck, he attaches an array of sensors to the load carriers in order to measure the temperature.
While having lunch, Ted forgot that by turning of the engine, air condition for the transported goods highly sensitive
orchids - shuts off, too. The temperature inside the truck starts rising and when it reaches a predefined critical
level inside, one of its sensors notices this and its node sends an emergency signal to Ted's IoT-Phone. On the
IoT-Phone's display, Ted can now see that the orchids are in danger so he rushes back to the vehicle and turns
the air condition on.
The IoT-Phone also keeps track of any alert messages it receives from the load carriers and saves this message
history for future inspection in a way that cannot be altered. When the truck reaches the retail store for delivery,
the sensor history is transferred to the store’s enterprise system and the sensors authenticate themselves as
being un-tampered.”
Exercise 1 : Internet of Things framework
Source : http://www.iot-a.eu/public/public-documents/d1.5/at_download/file
How to model this system using the IoT framework ?
47. 4. Meta-modeling illustration examples
47
Exercise 2: Method engineering
The design and development team in a company has defined a set of engineering methods
according to the nature of projects. Among others, and in the case of small size projects (number
of end-users <= 10, number of data tables <= 15, number of business process <=5), they have
defined the following simple method:
“The Requirements Engineering team (1 or 2 engineers) uses administrative documents and
conduct interviews with end-users to elicit general requirements, i.e a natural language
description of the required system (including NF requirements), and process definitions
represented as BMPN diagrams. The design team (2 to 4 engineers) uses the process models
together with the general description to sketch a system architecture, i.e. an UML class diagram,
use case diagrams and sequence diagrams. The development team (3 to 5 developers) build the
system according to the BPMN models and the system architecture, and deliver an operational
implementation composed of Java code for web services, a relational database and a workflow
script. The test team (2 to 3 persons) verify the quality of the system using a set of test cases
they have designed and in accordance with the NF requirements”.
How such method can be modeled using a
subset of SPEM and the MetaEdit+ workbench?
48. 4. Meta-modeling illustration examples
48
Exercise 3: Web questionnaires [Source : LWC2014 - Language Workbenches
Comparison, http://www.languageworkbenches.net/]
Forms-based software for data collection has found application in various areas, including scientific
surveys, online course-ware and guidance material to support the auditing process. As an overall
term for this kind of software applications we use the term "questionnaire". In this exercise, the goal
is to create a simple DSL, called QL, for describing questionnaires. Such questionnaires are
composed of sequential forms, each form is characterized by conditional entry fields and
(spreadsheet-like) dependency-directed computation. The following example presents a possible
textual representation of a simple questionnaire with only one form :
questionnaire HouseOwning
form Box1HouseOwning
{ hasSoldHouse: “Did you sell a house in 2010?” Boolean
hasBoughtHouse: “Did you by a house in 2010?” Boolean
hasMaintLoan: “Did you enter a loan for maintenance/reconstruction?” Boolean
if (hasSoldHouse)
{ sellingPrice: “Price the house was sold for:” money
privateDebt: “Private debts for the sold house:” money
valueResidue: “Value residue:” money(sellingPrice - privateDebt)
}
}
49. 4. Meta-modeling illustration examples
49
This simple form should generate into a GUI which allows the following user interaction:
Exercise 3: Web questionnaires [Source : LWC2014 - Language Workbenches
Comparison, http://www.languageworkbenches.net/]
How such language can be designed and implemented ?
50. Agenda
50
1. Introductory examples
2. Abstraction levels and the instantiation problem
3. Computerized tools for meta-modeling
4. Illustration
a) A Domain Specific Language (DSL) for IoT v3.0 Framework
b) A DSL to model software development processes
c) A DSL to specify web applications
5. Research challenges
6. Conclusion
50
51. 6. Research challenges in meta-modeling
51
Behavior meta-modeling
• Behavior perspectives are generally missing in software engineering
meta-models
Important knowledge about modeling languages is lacking
Essential for tools designers and method engineers
For a process modeling language, "behavior" perspective inquire
on its executable/operational semantics
52. 6. Research challenges – behavior modeling
52
Research goal
• How to express the operational semantics for a modeling language?
• How to design and build enactment engines for a given modeling language?
Maintainability and portability are central issues
[Source :T. Mayerhofer et al., “xMOF: Executable DSMLs Based on fUML”, SLE’2013 ]
53. 6. Research challenges – behavior modeling
53
Behavior meta-modeling
• Context : MAP process modeling notation
Example
55. 6. Research challenges in meta-modeling
55
Behavior meta-modeling
• Other approaches
KERMETA
For an example, see http://en.wikipedia.org/wiki/Kermeta
56. 6. Research challenges in meta-modeling
56
Behavior meta-modeling
xMOF (Mayerhofer et al., 2013)
57. Agenda
57
1. Introductory examples
2. Abstraction levels and the instantiation problem
3. Computerized tools for meta-modeling
4. Illustration
a) A Domain Specific Language (DSL) for IoT v3.0 Framework
b) A DSL to model software development processes
c) A DSL to specify web applications
5. Research challenges
6. Conclusion
57
58. 6. Conclusion
58
• No well established and recognized standard for meta-modeling
• Tool support is complicated
• … OMG's MOF and IBM Eclipse emerge as "market" leaders for UML & Java
• MetaEdit: leader for DSM engineering tools
• Conceptbase: most powerful and theoretically sound modeling language
• Semantics for process meta-models still to be defined
• Beyond DSM, few empirical studies on meta-modeling applications
59. References
59
Links
• MOF homepage: http://www.omg.org/mof/
• ISO/IEC 24744:2007 (Software Engineering -- Metamodel for Development
Methodologies): http://www.iso.org/iso/catalogue_detail.htm?csnumber=38854
• OPEN (Object-oriented Process, Environment and Notation) :
http://www.open.org.au/
• Metacase: http://www.metacase.com/
• Conceptbase: http://conceptbase.sourceforge.net/
• Kermeta: http://www.kermeta.org
S. Kelly et J.-P. Tolvanen, Domain-specific modeling:
enabling full code generation. Hoboken, N.J.: Wiley-
Interscience: IEEE Computer Society, 2008.
C. Gonzalez-Perez et B. Henderson-Sellers,
Metamodelling for software engineering. Wiley
Publishing, 2008.
Jeusfeld, M., Jarke, M., Mylopoulos, J.: Metamodeling
for method engineering. The MIT Press, (2009).
60. References
60
Atkinson, C., Kühne, T., « The Essence of Multilevel Metamodeling », in: Gogolla, M. et
Kobryn, C. (éd.) «UML» 2001 — The Unified Modeling Language. Modeling Languages, Concepts,
and Tools. LNCS, vol.2185, pp. 19-33. Springer, 2001.
C. Atkinson et T. Kühne, « Model-Driven Development: A Metamodeling Foundation », IEEE
Software, vol. 20, no 5, p. 36–41, 2003.
C. Gonzalez-Perez et B. Henderson-Sellers, « A powertype-based metamodelling framework
», Software and Systems Modeling, vol. 5, no 1, p. 72-90, 2006.
F. Jouault, F. Allilaire, J. Bézivin, et I. Kurtev, « ATL: A model transformation tool », Science of
Computer Programming, vol. 72, no 1-2, p. 31-39, 2008.
A. Gargantini, E. Riccobene, et P. Scandurra, « A semantic framework for metamodel-based
languages », Automated Software Engineering, vol. 16, no 3-4, p. 415-454, 2009.
M. Jarke, M. Jeusfeld, H. Nissen, C. Quix, et M. Staudt, « Metamodelling with Datalog and
Classes: ConceptBase at the Age of 21 », in Proceedings 2nd Int. Conf. on Object Databases
(ICOODB’09), M. Norrie et M. Grossniklaus, Éd. 2010, p. 95–112.
J. de Lara et E. Guerra, « Deep Meta-modelling with MetaDepth », in Objects, Models,
Components, Patterns, J. Vitek, Éd. Springer Berlin Heidelberg, 2010, p. 1-20.
B. Bryant, J. Gray, M. Mernik, P. Clarke, R. France, et G. Karsai, « Challenges and Directions
in Formalizing the Semantics of Modeling Languages », Computer Science and Information
Systems, vol. 8, no 2, p. 225-253, 2011.
61. References (cont’d)
61
J. Sprinkle, B. Rumpe, H. Vangheluwe, et G. Karsai, « Metamodelling », in Model-Based
Engineering of Embedded Real-Time Systems, vol. 6100, H. Giese, G. Karsai, E. Lee, B. Rumpe,
et B. Schätz, Éd. Berlin/Heidelberg: Springer, 2011, p. 57-76.
A. El Kouhen, C. Dumoulin, S. Gerard, et P. Boulet, « Evaluation of Modeling Tools
Adaptation », 2012. Available at http://hal.archives-ouvertes.fr/hal-00706701
B. Henderson-Sellers, O. Eriksson, C. Gonzalez-Perez, et P. J. Ågerfalk, « Ptolemaic
Metamodelling? The Need for a Paradigm Shift », in Progressions and Innovations in Model-
Driven Software Engineering:, V. G. Díaz, J. M. C. Lovelle, B. C. P. García-Bustelo, et O. S.
Martínez, Éd. IGI Global, 2013, p. 90-146.
O. Eriksson, B. Henderson-Sellers, et P. J. Ågerfalk, « Ontological and linguistic
metamodelling revisited: A language use approach », Information and Software Technology, vol.
55, no 12, p. 2099-2124, 2013.
C. Bürger, S. Karol, C. Wende, et U. Aßmann, « Reference Attribute Grammars for
Metamodel Semantics », in Software Language Engineering, vol. 6563, B. Malloy, S. Staab, et M.
van den Brand, Éd. Berlin/Heidelberg: Springer, 2011, p. 22-41.
T. Mayerhofer, P. Langer, M. Wimmer, et G. Kappel, « xMOF: Executable DSMLs Based on
fUML », in Software Language Engineering (SLE’13), M. Erwig, R. F. Paige, et E. V. Wyk, Éd.
Springer International Publishing, 2013, p. 56-75.
B. Neumayr, M. A. Jeusfeld, M. Schrefl, et C. Schütz, « Dual Deep Instantiation and Its
ConceptBase Implementation », in Advanced Information Systems Engineering, M. Jarke, J.
Mylopoulos, C. Quix, C. Rolland, Y. Manolopoulos, H. Mouratidis, et J. Horkoff, Éd. Springer
International Publishing, 2014, p. 503-517.
R. F. Paige, D. S. Kolovos, et F. A. C. Polack, « A tutorial on metamodelling for grammar
researchers », Science of Computer Programming, vol. 96, Part 4, p. 396-416, 2014.
62. THANK YOU FOR YOUR ATTENTION !
62
Questions? Comments? Insights?
Homepage
http://fr.linkedin.com/pub/sa%C3%AFd-assar/4/68a/66a
http://fr.slideshare.net/SaidAssar/
https://twitter.com/Said_Assar/
http://www-public.it-sudparis.eu/~assar/