On the Rationality of Explanations in Classification Algorithms

This paper is a first step towards studying the rationality of explanations produced by up-to-date AI systems. Based on the thesis that designing rational explanations for accomplishing trustworthy AI is fundamental for ethics in AI, we study the rationality criteria that explanations in classification algorithms have to meet. In this way, we identify, define, and exemplify characteristic criteria of rational explanations in classification algorithms

Women in Artificial intelligence (AI)

This Special Issue, entitled "Women in Artificial Intelligence" includes 17 papers from leading women scientists. The papers cover a broad scope of research areas within Artificial Intelligence, including machine learning, perception, reasoning or planning, among others. The papers have applications to relevant fields, such as human health, finance, or education. It is worth noting that the Issue includes three papers that deal with different aspects of gender bias in Artificial Intelligence. All the papers have a woman as the first author. We can proudly say that these women are from countries worldwide, such as France, Czech Republic, United Kingdom, Australia, Bangladesh, Yemen, Romania, India, Cuba, Bangladesh and Spain. In conclusion, apart from its intrinsic scientific value as a Special Issue, combining interesting research works, this Special Issue intends to increase the invisibility of women in AI, showing where they are, what they do, and how they contribute to developments in Artificial Intelligence from their different places, positions, research branches and application fields. We planned to issue this book on the on Ada Lovelace Day (11/10/2022), a date internationally dedicated to the first computer programmer, a woman who had to fight the gender difficulties of her times, in the XIX century. We also thank the publisher for making this possible, thus allowing for this book to become a part of the international activities dedicated to celebrating the value of women in ICT all over the world. With this book, we want to pay homage to all the women that contributed over the years to the field of AI

Adaptive fuzzy system for algorithmic trading : interpolative Boolean approach

Тема овог рада je адаптивни фази систем за алгоритамско трговање. Систем је развијен коришћењем интерполативног Буловог приступа фази моделовању, анализи података и управљању. Предложени приступ укључује интерполативне логичке моделе за фази препознавање ценовних образаца на тржишту, логички ДуПонт метод за аутоматизовану анализу профитабилности предузећа, интерполативни фази контролер за управљање трговањем и генетски алгоритам за обучавање интерполативног фази контролера ради откривања стратегија. Интерполативни Булов приступ, заснован на интерполативној Буловој алгебри, превазилази проблем неконзистентности фази логике. Конструисани адаптивни фази систем може самостално, из података, да открије успешне стратегије, примени их за алгоритамско трговање и адаптира у случају пада њихових перформанси. Успешност система тестирана је на подацима са америчког тржишта акција, међународног девизног тржишта и тржишта криптовалута.The topic of this thesis is adaptive fuzzy system for algorithmic trading. The system is developed using interpolative Boolean approach for fuzzy modeling, data analysis and control. The proposed approach includes interpolative logical models for fuzzy recognition of price patterns in market data, logical DuPont method for automated analysis of company’s profitability, interpolative fuzzy controller for trading and a genetic algorithm for extracting trading strategies by training interpolative fuzzy controller. Interpolative Boolean approach, based on interpolative Boolean agebra, solves the problem of fuzzy logic’s inconsistency with Boolean axioms. The proposed system can independently discover successful trading strategies from data, apply them for algorithmic trading and adapt in the case of performance deterioration. The system was tested on historical data from US equity, foreign exchange market and cryptocurrency market

Classification of Explainable Artificial Intelligence Methods through Their Output Formats

Machine and deep learning have proven their utility to generate data-driven models with high accuracy and precision. However, their non-linear, complex structures are often difficult to interpret. Consequently, many scholars have developed a plethora of methods to explain their functioning and the logic of their inferences. This systematic review aimed to organise these methods into a hierarchical classification system that builds upon and extends existing taxonomies by adding a significant dimension—the output formats. The reviewed scientific papers were retrieved by conducting an initial search on Google Scholar with the keywords “explainable artificial intelligence”; “explainable machine learning”; and “interpretable machine learning”. A subsequent iterative search was carried out by checking the bibliography of these articles. The addition of the dimension of the explanation format makes the proposed classification system a practical tool for scholars, supporting them to select the most suitable type of explanation format for the problem at hand. Given the wide variety of challenges faced by researchers, the existing XAI methods provide several solutions to meet the requirements that differ considerably between the users, problems and application fields of artificial intelligence (AI). The task of identifying the most appropriate explanation can be daunting, thus the need for a classification system that helps with the selection of methods. This work concludes by critically identifying the limitations of the formats of explanations and by providing recommendations and possible future research directions on how to build a more generally applicable XAI method. Future work should be flexible enough to meet the many requirements posed by the widespread use of AI in several fields, and the new regulation

Methodology for identifying the key and enough factors for achieving objectives in sewer asset management

El principal objetivo de la tesis doctoral fue desarrollar una metodología para determinar los factores suficientes y necesarios para alcanzar objetivos específicos en la gestión patrimonial de alcantarillados, teniendo en cuenta la cantidad y calidad de la información disponible. El documento consta de cuatro partes: Parte A consiste en el marco teórico de los principales conceptos, pruebas, métodos, y métricas utilizados como base para desarrollar la metodología propuesta; Parte B contiene la descripción de los materiales (casos de estudio y herramientas computacionales) y los argumentos científicos de los modelos escogidos para desarrollar la metodología propuesta; Parte C es la más importante parte del documento, ya que describe las herramientas desarrolladas que apoyan la gestión patrimonial de alcantarillados y la metodología propuesta; y por último Parte D ilustra los resultados de las herramientas desarrolladas y la aplicación de la metodología propuesta a dos casos de estudio (Bogotá y Medellín). Las principales contribuciones de la tesis doctoral son: (i) una metodología basada en redes bayesianas para seleccionar un modelo rentable para apoyar la gestión patrimonial de activos como una herramienta de selección de atributos; (ii) métricas de desempeño vinculadas con objetivos en gestión patrimonial de alcantarillados; (iii) una metodología de optimización para modelos basados en aprendizaje de máquina para encontrar los hiper-parámetros óptimos para alcanzar objetivos de gestión; y finalmente (iv) la construcción de modelos de deterioro basados en diferentes métodos estadísticos y de aprendizaje de máquina en diferentes casos de estudio evaluado las predicciones a partir de diferentes perspectivas.The main objective of the doctoral thesis was to develop a methodology for determining which factors are enough and necessary to achieve specific objectives in sewer asset management considering the quantity and quality of the available information. The manuscript consists on four parts: Part A depicts the theoretical framework of the main concepts, tests, methods, and metrics used as the basis for developing the proposed methodology; Part B concerns the description of materials (case studies and computer-based tools) and the scientific arguments of the choosing methods for developing the proposed methodology; Part C is the most essential part of this manuscript because it describes the developed sewer asset management tools and the proposed methodology, objective of this doctoral thesis; and Part D illustrates the results of the proposed sewer asset management tools and the application of the proposed methodology in two case studies (Bogota and Medellin). The main contributions of the doctoral thesis are: (i) a Bayesian network-based methodology for selecting a cost-effective sewer asset management model as a feature selection tool; (ii) performance metrics linked with management objectives in sewer asset management; (iii) an optimization methodology for machine learning-based models to find the optimal hyperparameters for achieving management objectives; and (iv) building deterioration models based on different statistical and machine learning methods on different case studies, evaluating the predictions from different perspectives.Doctor en IngenieríaDoctoradohttps://orcid.org/0000-0001-5084-7937https://scholar.google.com/citations?hl=en&user=WSY6pA0AAAAJhttps://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=000146448

Intelligent Systems

This book is dedicated to intelligent systems of broad-spectrum application, such as personal and social biosafety or use of intelligent sensory micro-nanosystems such as "e-nose", "e-tongue" and "e-eye". In addition to that, effective acquiring information, knowledge management and improved knowledge transfer in any media, as well as modeling its information content using meta-and hyper heuristics and semantic reasoning all benefit from the systems covered in this book. Intelligent systems can also be applied in education and generating the intelligent distributed eLearning architecture, as well as in a large number of technical fields, such as industrial design, manufacturing and utilization, e.g., in precision agriculture, cartography, electric power distribution systems, intelligent building management systems, drilling operations etc. Furthermore, decision making using fuzzy logic models, computational recognition of comprehension uncertainty and the joint synthesis of goals and means of intelligent behavior biosystems, as well as diagnostic and human support in the healthcare environment have also been made easier

pHealth 2021. Proc. of the 18th Internat. Conf. on Wearable Micro and Nano Technologies for Personalised Health, 8-10 November 2021, Genoa, Italy

Smart mobile systems – microsystems, smart textiles, smart implants, sensor-controlled medical devices – together with related body, local and wide-area networks up to cloud services, have become important enablers for telemedicine and the next generation of healthcare services. The multilateral benefits of pHealth technologies offer enormous potential for all stakeholder communities, not only in terms of improvements in medical quality and industrial competitiveness, but also for the management of healthcare costs and, last but not least, the improvement of patient experience. This book presents the proceedings of pHealth 2021, the 18th in a series of conferences on wearable micro and nano technologies for personalized health with personal health management systems, hosted by the University of Genoa, Italy, and held as an online event from 8 – 10 November 2021. The conference focused on digital health ecosystems in the transformation of healthcare towards personalized, participative, preventive, predictive precision medicine (5P medicine). The book contains 46 peer-reviewed papers (1 keynote, 5 invited papers, 33 full papers, and 7 poster papers). Subjects covered include the deployment of mobile technologies, micro-nano-bio smart systems, bio-data management and analytics, autonomous and intelligent systems, the Health Internet of Things (HIoT), as well as potential risks for security and privacy, and the motivation and empowerment of patients in care processes. Providing an overview of current advances in personalized health and health management, the book will be of interest to all those working in the field of healthcare today

Fuzzy Logic

Fuzzy Logic is becoming an essential method of solving problems in all domains. It gives tremendous impact on the design of autonomous intelligent systems. The purpose of this book is to introduce Hybrid Algorithms, Techniques, and Implementations of Fuzzy Logic. The book consists of thirteen chapters highlighting models and principles of fuzzy logic and issues on its techniques and implementations. The intended readers of this book are engineers, researchers, and graduate students interested in fuzzy logic systems

Safety and Reliability - Safe Societies in a Changing World

The contributions cover a wide range of methodologies and application areas for safety and reliability that contribute to safe societies in a changing world. These methodologies and applications include: - foundations of risk and reliability assessment and management - mathematical methods in reliability and safety - risk assessment - risk management - system reliability - uncertainty analysis - digitalization and big data - prognostics and system health management - occupational safety - accident and incident modeling - maintenance modeling and applications - simulation for safety and reliability analysis - dynamic risk and barrier management - organizational factors and safety culture - human factors and human reliability - resilience engineering - structural reliability - natural hazards - security - economic analysis in risk managemen

Collected Papers (on various scientific topics), Volume XIII

This thirteenth volume of Collected Papers is an eclectic tome of 88 papers in various fields of sciences, such as astronomy, biology, calculus, economics, education and administration, game theory, geometry, graph theory, information fusion, decision making, instantaneous physics, quantum physics, neutrosophic logic and set, non-Euclidean geometry, number theory, paradoxes, philosophy of science, scientific research methods, statistics, and others, structured in 17 chapters (Neutrosophic Theory and Applications; Neutrosophic Algebra; Fuzzy Soft Sets; Neutrosophic Sets; Hypersoft Sets; Neutrosophic Semigroups; Neutrosophic Graphs; Superhypergraphs; Plithogeny; Information Fusion; Statistics; Decision Making; Extenics; Instantaneous Physics; Paradoxism; Mathematica; Miscellanea), comprising 965 pages, published between 2005-2022 in different scientific journals, by the author alone or in collaboration with the following 110 co-authors (alphabetically ordered) from 26 countries: Abduallah Gamal, Sania Afzal, Firoz Ahmad, Muhammad Akram, Sheriful Alam, Ali Hamza, Ali H. M. Al-Obaidi, Madeleine Al-Tahan, Assia Bakali, Atiqe Ur Rahman, Sukanto Bhattacharya, Bilal Hadjadji, Robert N. Boyd, Willem K.M. Brauers, Umit Cali, Youcef Chibani, Victor Christianto, Chunxin Bo, Shyamal Dalapati, Mario Dalcín, Arup Kumar Das, Elham Davneshvar, Bijan Davvaz, Irfan Deli, Muhammet Deveci, Mamouni Dhar, R. Dhavaseelan, Balasubramanian Elavarasan, Sara Farooq, Haipeng Wang, Ugur Halden, Le Hoang Son, Hongnian Yu, Qays Hatem Imran, Mayas Ismail, Saeid Jafari, Jun Ye, Ilanthenral Kandasamy, W.B. Vasantha Kandasamy, Darjan Karabašević, Abdullah Kargın, Vasilios N. Katsikis, Nour Eldeen M. Khalifa, Madad Khan, M. Khoshnevisan, Tapan Kumar Roy, Pinaki Majumdar, Sreepurna Malakar, Masoud Ghods, Minghao Hu, Mingming Chen, Mohamed Abdel-Basset, Mohamed Talea, Mohammad Hamidi, Mohamed Loey, Mihnea Alexandru Moisescu, Muhammad Ihsan, Muhammad Saeed, Muhammad Shabir, Mumtaz Ali, Muzzamal Sitara, Nassim Abbas, Munazza Naz, Giorgio Nordo, Mani Parimala, Ion Pătrașcu, Gabrijela Popović, K. Porselvi, Surapati Pramanik, D. Preethi, Qiang Guo, Riad K. Al-Hamido, Zahra Rostami, Said Broumi, Saima Anis, Muzafer Saračević, Ganeshsree Selvachandran, Selvaraj Ganesan, Shammya Shananda Saha, Marayanagaraj Shanmugapriya, Songtao Shao, Sori Tjandrah Simbolon, Florentin Smarandache, Predrag S. Stanimirović, Dragiša Stanujkić, Raman Sundareswaran, Mehmet Șahin, Ovidiu-Ilie Șandru, Abdulkadir Șengür, Mohamed Talea, Ferhat Taș, Selçuk Topal, Alptekin Ulutaș, Ramalingam Udhayakumar, Yunita Umniyati, J. Vimala, Luige Vlădăreanu, Ştefan Vlăduţescu, Yaman Akbulut, Yanhui Guo, Yong Deng, You He, Young Bae Jun, Wangtao Yuan, Rong Xia, Xiaohong Zhang, Edmundas Kazimieras Zavadskas, Zayen Azzouz Omar, Xiaohong Zhang, Zhirou Ma.‬‬‬‬‬‬‬