Software development effort estimation (SDEE) is critical for predicting the required resource investment. Since the late 2000s, numerous studies have advocated using computational intelligence (CI) to enhance the precision of SDEE models (CI-SDEE). However, a systematic examination of empirical evidence surrounding CI-SDEE is lacking. Therefore, we conducted a meticulous and systematic literature review across four dimensions: CI technique classification, estimation fidelity, model comparative analysis, and contextual applicability. Surveying empirical studies published between 2008 and 2023, we identified 38 seminal works germane to our research objectives. Our investigation revealed five distinct CI technique families utilized in SDEE, exhibiting an overall estimation accuracy commensurate with the acceptable standards and superior to non-CI counterparts. In addition, we determined that specific CI models exhibit unique advantages and disadvantages, which make them better suited to specific estimation contexts. While CI techniques have been proven promising in advancing the field of SDEE, their industrial applications are limited, necessitating additional efforts to foster their adoption. This review provides actionable academic recommendations and operational guidelines for practitioners.

Digitization, digitalization and digital transformation (DT) are important for public organizations and private organizations. Despite their importance, these steps are approached differently in organizations. Public organizations emphasize the importance of digital transformation, while public organizations make efforts to align themselves with citizens' demands from a digitalization perspective. So far, no study has presented (1) to what extent this transformation is underway and (2) what are the determining factors with particular emphasis on Romanian cases. This research was carried out in two directions: research carried out for public organizations and research carried out for private organizations. The research is completed with comparative assessments of digitization and digital transformation in public and private organizations. The results show that public organizations are intensively involved in the digital transformation, while public organizations try to find solutions to the various barriers and are at an average level of digitalization. The research concludes with future research directions and research limitations.

Information is widely available and accessible, but frequently leads to information overload and overexposure and the effort for coding, storing, hiding, securing, transmitting, and retrieving it may be excessive. Intelligence, inspired by biological and other paradigms, is required to manage information and extract knowledge from it. Information and Multimedia Systems, with an increasing level of Intelligence, are being developed that incorporate these advances. As a result, new Technologies, Protocols, and novel Applications are emerging. In turn, the novel applications lead to the collection of new information and the “Information → Intelligence → Systems → Applications” circle is repeated at ever higher levels. This book includes extended versions of selected research works that were presented at the 14th International Conference on Information, Intelligence, Systems, and Applications (IISA2023), Volos, Greece, July 10–12, 2024 ( https://www.easyacademia.org/iisa2023 ) along with additional relevant papers by invited authors. These works cover a broad spectrum of topics from both novelties in theory and advanced methodologies as well as applications in the Energy, Agriculture, Medicine, Forensics, Healthcare, Education, Tourism, Inspection, Traffic and Software Engineering.

This book gathers selected papers from the KES-IDT 2023 Conference, held in Rome, Italy on June 14–16, 2023.

In the recent years, Machine Learning research has been exploring integrated or hybrid learning methodologies, i.e. methodologies that fuse together two or more Machine Learning approaches and promise to achieve higher performance and better efficiency when compared to those of their constituent components. The book at hand, consisting of this editorial note and an additional eight chapters, aims at updating the relevant computer science-related research communities, including professors, researchers, scientists, engineers and students, as well as the general reader from other disciplines, on the most recent advances in applications of methods based on Fusing Machine Learning Paradigms.

Intelligent Decision Technologies (IDT): An International Journal (

Artificial Intelligence research is presenting phenomenal progress in two directions: (i) new theories and methodologies, and (ii) applications that expand traditional domains with innovative interventions. As indicated by recent reports, this progress has created a disequilibrium, where demand for scientists with skills in Artificial Intelligence is not fulfilled, a trend that will intensify further in the years to come. A potential solution to this shortage of specialised workforce may come from encouraging more women to get educated and follow a career in one of the Artificial Intelligence areas. This special collection of invited papers is dedicated to all women researchers and practitioners in Artificial Intelligence and coincides with the March 8, 2023 International Women’s Day. Moreover, it has two specific goals: (i) to inspire more women to study and practice Artificial Intelligence through presentation of recognized women researchers who can act as role models, and (ii) to highlight some streamlined research areas of Artificial Intelligence.

Intelligent Decision Technologies (IDT): An International Journal (https://www.iospress.com/catalog/ journals/intelligent-decision-technologies) is dedicated to the advancement and dissemination of research results and knowledge in the theory and application of intelligent technologies and systems in support of decision making. The IDT Journal is affiliated with KES International (http://www.kesinternational.org/), “a professional community, with networking, research and publication opportunities for all those who work in knowledge-intensive subjects”. KES sponsors international conferences on leading-edge topics, including an annual conference for Intelligent Decision Technologies. The idea of the IDT Journal originated through discussions between Professor/Dr. Gloria Phillips-Wren and Professor/Dr. Lakhmi C. Jain at the Knowledge Engineering Systems (KES) International annual conferences in the timeframe of 2004–2006. The spark that at the time inspired the two Professors to initiate the IDT Journal lay in the fact that, while research mainly focused on algorithms and technical specifications, the technology was also becoming mature enough to be implemented into real-world decision support systems (DSS) for previously intractable problems. Thus, the IDT Journal was launched in 2007. Profs./Drs. Lakhmi C. Jain and Gloria Phillips-Wren introduced the IDT Journal to the research community with an editorial note stating that “The purpose of this peer reviewed, scholarly journal is to develop a forum for theoretical and applied research that combines artificial intelligence based in computer science, decision support based in information technology, and systems development based in engineering science. Interdisciplinary advances in these fields have the potential to significantly improve individual and organizational decision making. The growth of the internet with its concomitant availability of data has exploded the amount and types of information that must be considered by a decision maker. Decisions must often be made in real-time under uncertain, stressful conditions that may change rapidly. Synergies between intelligent and information technologies can, for example, deliver artificial intelligence to enhance human judgment, perceive anomalies in data, enable collaboration, speed processing of new information, assist in risk assessment, identify and retrieve needed knowledge, suggest alternatives to the decision maker, and automate some decisional tasks. We look forward to the dialogue within this community and welcome your research for publication” [1]. Since its launch, the IDT Journal is in continuous circulation with a new issue published quarterly by IOS Press (https://www.iospress.com/) headquartered in Amsterdam, the Netherlands. At the same time, the field of intelligent decision support has been enjoying continuous and rapid expansion in theory, paradigms and real-world systems and applications. This expansion is due to parallel advances and efficiencies in such enabling technologies as (1) Artificial Intelligence (AI); (2) connectivity between devices such as the Internet of Things (IoT); (3) data storage, processing and transmission in distributed, virtualized and networkcentric environments (e.g. cloud technologies); (4) remarkable computer and internet transmission speeds;