Background: Case-Based Reasoning (CBR) is a problem-solving paradigm that uses knowledge of relevant past experiences (cases) to interpret or solve new problems. CBR systems allow generating explanations easily, as they typically organize and represent knowledge in a way that makes it possible to reason about and thereby generate explanations. An improvement of this paradigm is ontology-based CBR, an approach that combines, in the form of formal ontologies, case-specific knowledge with domain one in order to improve the effectiveness and explanation capability of the system. Intelligent systems make daily activities more easily, efficiently, and represent a real support for sustainable economic development. On the one hand, they improve efficiency, productivity, and quality, and, on the other hand, can reduce costs and cut waste. In this way, intelligent systems facilitate sustainable development, economic growth, societal progress, and improve efficiency. Aim: In this vision, the purpose of this paper is to propose a new generation of intelligent decision support systems for Business Model having the ability to provide explanations to increase confidence in proposed solutions. Findings/result: The performance results obtained show the benefits of the proposed solution with different requirements of an explanatory decision support system. Consequently, applying this paradigm for software tools of business model development will make a great promise for supporting business model design, sustainability, and innovation.

Internet of Drones (IoD) is a dynamic network architecture in which multiple drones, equipped with communication, sensing, and computation capabilities, are interconnected through Internet of Things (IoT) technologies to perform coordinated tasks autonomously. This infrastructure enables seamless real-time data exchange and collaborative operations across diverse applications, ranging from surveillance to delivery services, while ensuring adaptability, scalability, and security in dynamic aerial environments. However, the IoD introduces new security challenges, as drones are highly vulnerable to various cyberthreats and cyberattacks. Existing Intrusion Detection Systems (IDS) for IoD face several limitations, including high false positive rates, resource constraints of drones, limited adaptability to evolving attack patterns, and a lack of standardized datasets for benchmarking, despite ongoing research efforts. Moreover, there is a lack of a comprehensive study that systematically consolidates existing research. In this paper, we present a systematic literature review to examine the current research area of intrusion detection systems for IoD, focusing on the effectiveness of implemented machine learning models, employed datasets, existing challenges and limitations, as well as emerging trends and future research directions. This review follows PRISMA guidelines, with peer-reviewed journal articles and conference papers selected as the inclusion criteria. Publications relevant to the topic are sourced from a range of databases, including Scopus, IEEE Xplore, ScienceDirect, SpringerLink, ACMDigital Library, and MDPI, covering a 10-year period from 2014 to 2024. From an initial pool of 1,909 records, 62 relevant reports are selected to address the identified research questions. The selected studies are categorized according to publication year, venue, journal, drone domain, IDS type, utilized algorithms, datasets, attack classifications, and software environments. Additionally, a comparative analysis across various factors is presented.

Video streaming is one of the challenging issues in vehicular ad-hoc networks (VANETs) due to their highly dynamic topology and frequent connectivity disruptions. Recent developments in the routing protocol methods used in VANETs have contributed to improvements in the quality of experience (QoE) of the received video. One of these methods is the selection of the next-hop relay vehicle. In this paper, a QoE-aware geographic protocol for video streaming over VANETs is proposed. The selection process of the next relay vehicle is based on a correlated formula of QoE and quality of service (QoS) factors to enhance the users’ QoE. The simulation results show that the proposed GeoQoE-Vanet outperforms both GPSR and GPSR-2P protocols in providing the best end-user QoE of video streaming service.

Several routing protocols have been proposed for ad hoc vehicle networks. They affect directly but differently the quality of the transmitted data. In this paper, we introduce a multipath feature to decrease packet loss in greedy perimeter stateless routing protocol (GPSR). Since using only one path during transmission may cause packet loss due to congestion and saturation in this path. Our enhancement is based on sending the same packet over two different paths to maximize its reception probability. This scheme is evaluated in a highway environment using Omnet++, Veins, and SUMO. The results show that the proposed solution overcomes GPSR in packet delivery ratio.

Vehicular Ad-hoc Networks (VANETs) are a new emerging technology which has attracted enormous interest over the last few years. It enables vehicles to communicate with each other and with roadside infrastructures for many applications. One of the promising applications is multimedia services for traffic safety or infotainment. The video service requires a good quality to satisfy the end-user known as the Quality of Experience (QoE). Several models have been suggested in the literature to measure or predict this metric. In this paper, we present an overview of interesting researches, which propose QoE models for video streaming over VANETs. The limits and deficiencies of these models are identified, which shed light on the challenges and real problems to overcome in the future.

In this paper we present a new approach for using semantic web technologies in modeling and simulation. In recent years ontologies have been used popularly in many fields to represent and structure their concepts. This work is an attempt to create a specific ontology for the process oriented discrete event simulation domain. The ontology instances represent the model instances. This instance described in XML format and then transformed to another form that is used to generate the simulation code via XSLT rules. The code is generated according to the open source library Japrosim. The objective of this work is to enhance interoperability and automation of the transition from the ontology to the code execution.