Chatbots for Modelling, Modelling of Chatbots

Tesis Doctoral inédita leída en la Universidad Autónoma de Madrid, Escuela Politécnica Superior, Departamento de Ingeniería Informática. Fecha de Lectura: 28-03-202

21st International Congress of Aesthetics, Possible Worlds of Contemporary Aesthetics Aesthetics Between History, Geography and Media, Book of Abstracts

The Faculty of Architecture, University of Belgrade and the Society for Aesthetics of Architecture and Visual Arts of Serbia (DEAVUS) are proud to be able to organize the 21st ICA Congress on “Possible Worlds of Contemporary Aesthetics: Aesthetics Between History, Geography and Media”. We are proud to announce that we received over 500 submissions from 56 countries, which makes this Congress the greatest gathering of aestheticians in this region in the last 40 years. The ICA 2019 Belgrade aims to map out contemporary aesthetics practices in a vivid dialogue of aestheticians, philosophers, art theorists, architecture theorists, culture theorists, media theorists, artists, media entrepreneurs, architects, cultural activists and researchers in the fields of humanities and social sciences. More precisely, the goal is to map the possible worlds of contemporary aesthetics in Europe, Asia, North and South America, Africa and Australia. The idea is to show, interpret and map the unity and diverseness in aesthetic thought, expression, research, and philosophies on our shared planet. Our goal is to promote a dialogue concerning aesthetics in those parts of the world that have not been involved with the work of the International Association for Aesthetics to this day. Global dialogue, understanding and cooperation are what we aim to achieve. That said, the 21st ICA is the first Congress to highlight the aesthetic issues of marginalised regions that have not been fully involved in the work of the IAA. This will be accomplished, among others, via thematic round tables discussing contemporary aesthetics in East Africa and South America. Today, aesthetics is recognized as an important philosophical, theoretical and even scientific discipline that aims at interpreting the complexity of phenomena in our contemporary world. People rather talk about possible worlds or possible aesthetic regimes rather than a unique and consistent philosophical, scientific or theoretical discipline

Proceedings of the Seventh Congress of the European Society for Research in Mathematics Education

International audienceThis volume contains the Proceedings of the Seventh Congress of the European Society for Research in Mathematics Education (ERME), which took place 9-13 February 2011, at Rzeszñw in Poland

Aplicación de Machine Learning en productos software mediante un enfoque de Model-Driven Development

[ES] En la actualidad, cada vez es más relevante y demandada la figura del científico de datos en el sector de las TIC. Con el fin de satisfacer esta demanda, han surgido herramientas que permiten dotar de inteligencia a las aplicaciones siguiendo estrategias de low-code o no-code. A grandes rasgos, permiten el desarrollo de aplicaciones que resuelven problemas de inteligencia artificial (IA) sin necesidad de programación, esquivando su pronunciada curva de aprendizaje. Estas estrategias de desarrollo de software son derivadas del desarrollo dirigido por modelos (MDD). En este TFM se dará un primer paso en el desarrollo de una solución MDD para dotar a un producto software de funcionalidades cubiertas mediante machine learning. En concreto, se abordarán escenarios de análisis de sentimiento y de predicción de sucesos. El proyecto ha sido realizado en colaboración con una PYME dedicada al desarrollo de un ERP para el sector socio-sanitario. Esta empresa cuenta con diferentes herramientas de modelado y generación de código, con las que se realizará una integración. Finalmente, los escenarios se emplearán para modelar dos casos de uso dentro del propio ERP: el análisis de valoraciones médicas y la predicción de caídas en residencias.[EN] Nowadays, the figure of the data scientist in the ICT sector is increasingly relevant and in demand. In order to meet this demand, frameworks have emerged that allow cognifying applications following low-code or no-code strategies. Broadly speaking, they allow the development of applications that solve artificial intelligence (AI) problems without the need of programming, avoiding its difficult learning curve. These software development strategies are derived from Model-Driven Development (MDD). In this TFM, a first step is done in the development of an MDD solution to provide a software product with functionalities covered by machine learning. Specifically, sentiment analysis and event prediction scenarios will be addressed. The project has been carried out in collaboration with an enterprise dedicated to the development of an ERP for the socio-sanitary sector. This company has different modeling and code generation tools. An integration will be done with them. Finally, the scenarios will be used to model two use cases within the ERP: the analysis of medical progress notes and the prediction of falls in nursing homes.Iranzo Jiménez, VA. (2021). Aplicación de Machine Learning en productos software mediante un enfoque de Model-Driven Development. Universitat Politècnica de València. http://hdl.handle.net/10251/175328TFG

Cognification of Program Synthesis—A Systematic Feature-Oriented Analysis and Future Direction

Program synthesis is defined as a software development step aims at achieving an automatic process of code generation that is satisfactory given high-level specifications. There are various program synthesis applications built on Machine Learning (ML) and Natural Language Processing (NLP) based approaches. Recently, there have been remarkable advancements in the Artificial Intelligent (AI) domain. The rise in advanced ML techniques has been remarkable. Deep Learning (DL), for instance, is considered an example of a currently attractive research field that has led to advances in the areas of ML and NLP. With this advancement, there is a need to gain greater benefits from these approaches to cognify synthesis processes for next-generation model-driven engineering (MDE) framework. In this work, a systematic domain analysis is conducted to explore the extent to the automatic generation of code can be enabled via the next generation of cognified MDE frameworks that support recent DL and NLP techniques. After identifying critical features that might be considered when distinguishing synthesis systems, it will be possible to introduce a conceptual design for the future involving program synthesis/MDE frameworks. By searching different research database sources, 182 articles related to program synthesis approaches and their applications were identified. After defining research questions, structuring the domain analysis, and applying inclusion and exclusion criteria on the classification scheme, 170 out of 182 articles were considered in a three-phase systematic analysis, guided by some research questions. The analysis is introduced as a key contribution. The results are documented using feature diagrams as a comprehensive feature model of program synthesis showing alternative techniques and architectures. The achieved outcomes serve as motivation for introducing a conceptual architectural design of the next generation of cognified MDE frameworks

Collected Papers (on Physics, Artificial Intelligence, Health Issues, Decision Making, Economics, Statistics), Volume XI

This eleventh volume of Collected Papers includes 90 papers comprising 988 pages on Physics, Artificial Intelligence, Health Issues, Decision Making, Economics, Statistics, written between 2001-2022 by the author alone or in collaboration with the following 84 co-authors (alphabetically ordered) from 19 countries: Abhijit Saha, Abu Sufian, Jack Allen, Shahbaz Ali, Ali Safaa Sadiq, Aliya Fahmi, Atiqa Fakhar, Atiqa Firdous, Sukanto Bhattacharya, Robert N. Boyd, Victor Chang, Victor Christianto, V. Christy, Dao The Son, Debjit Dutta, Azeddine Elhassouny, Fazal Ghani, Fazli Amin, Anirudha Ghosha, Nasruddin Hassan, Hoang Viet Long, Jhulaneswar Baidya, Jin Kim, Jun Ye, Darjan Karabašević, Vasilios N. Katsikis, Ieva Meidutė-Kavaliauskienė, F. Kaymarm, Nour Eldeen M. Khalifa, Madad Khan, Qaisar Khan, M. Khoshnevisan, Kifayat Ullah,, Volodymyr Krasnoholovets, Mukesh Kumar, Le Hoang Son, Luong Thi Hong Lan, Tahir Mahmood, Mahmoud Ismail, Mohamed Abdel-Basset, Siti Nurul Fitriah Mohamad, Mohamed Loey, Mai Mohamed, K. Mohana, Kalyan Mondal, Muhammad Gulfam, Muhammad Khalid Mahmood, Muhammad Jamil, Muhammad Yaqub Khan, Muhammad Riaz, Nguyen Dinh Hoa, Cu Nguyen Giap, Nguyen Tho Thong, Peide Liu, Pham Huy Thong, Gabrijela Popović‬‬‬‬‬‬‬‬‬‬, Surapati Pramanik, Dmitri Rabounski, Roslan Hasni, Rumi Roy, Tapan Kumar Roy, Said Broumi, Saleem Abdullah, Muzafer Saračević, Ganeshsree Selvachandran, Shariful Alam, Shyamal Dalapati, Housila P. Singh, R. Singh, Rajesh Singh, Predrag S. Stanimirović, Kasan Susilo, Dragiša Stanujkić, Alexandra Şandru, Ovidiu Ilie Şandru, Zenonas Turskis, Yunita Umniyati, Alptekin Ulutaș, Maikel Yelandi Leyva Vázquez, Binyamin Yusoff, Edmundas Kazimieras Zavadskas, Zhao Loon Wang.‬‬‬