The sharing of data and digital assets in a decentralized settling is entangled with various legislative challenges, including, but not limited to, the need to adhere to legal requirements with respect to privacy and copyright. In order to provide more control to data and digital asset owners, usage control could be used to make sure that consumers handle data according to privacy, licenses, regulatory

The emergence of the Internet of Things (IoT) signifies a transformative wave of innovation, establishing a network of devices designed to enrich everyday experiences. Developing intelligent and secure IoT applications without compromising user privacy and the transparency of model decisions causes a significant challenge. Federated Learning (FL) serves as a innovative solution, encouraging collaborative

As society’s dependence on Information and Communication Technologies (ICTs) grows, providing efficient and resourceful services entails many complexities that require, among others, scalable systems that are provided with intelligent and automated management. In parallel, the different components of cloud computing are continuously evolving to enhance their capabilities towards leveraging the next

Ontology learning, particularly axiom learning, is a challenging task that focuses on building expressive and decidable ontologies. The literature proposes several research efforts aimed to resolve the complexities inherent in axiom and rule learning, which seeks to automatically infer logical constructs from diverse data sources. The goal of this paper is to conduct a comprehensive review of existing

The raster format of images and data is commonly intended as a synonymous of a square grid. Indeed, the square is not the only shape that can tessellate the plane. Other grids are well-known, and recently they have moved out of the fields of art and mathematics, and have started being of interest for technological applications. After introducing the main types of non-square grids, this paper presents

The Internet of Things (IoT) is the basis of smart agriculture technology since it connects all aspects of intelligent systems in other industries and agricultural applications. The current farming methods are sufficient to supply adequate food in the future due to the fast-expanding global population. Smart farming aims to increase farm output and efficiency by leveraging state-of-the-art information

Software Defined network (SDN) represents a sophisticated networking approach that separates the control logic from the data plane. This separation results in a loosely coupled architecture between the control and data planes, enhancing flexibility in managing and transforming network configurations. Additionally, SDN provides a centralized management model through the SDN controller, simplifying network

Due to the increasing popularity of application scenarios such as cloud computing, and the growing concern of users about the security and privacy of their data, information security and privacy protection technologies are facing new challenges. Consequently, Homomorphic Encryption (HE) technology has been developed. HE technology has evolved from Partially Homomorphic Encryption (PHE) to fully homomorphic

This review provides an overview of apple detection and localization using image analysis and artificial intelligence techniques for enabling robotic fruit harvesting in orchard environments. Classic methods for detecting and localizing infield apples are discussed along with more advanced approaches using deep learning algorithms that have emerged in the past few years. Challenges faced in apple detection

The dynamic and decentralized architecture of fog computing, which extends cloud computing closer to the edge of the network, offers benefits such as reduced latency and enhanced bandwidth. However, the existing fog architecture introduces unique security challenges due to the large number of distributed fog nodes, often deployed in diverse and resource-constrained environments. Further, the proximity

Object detection has been used extensively in daily life, and in computer vision, this sub-field is highly significant and challenging. The field of object detection has been transformed by deep learning. Deep learning-based methods have shown to be remarkably effective at identifying and localizing objects in images and video streams when it comes to object detection. Deep learning algorithms can

Demographic change in the world is a reality, and as a result, the number of elderly people is growing in both developed and developing countries, posing several social and economic issues. Most elderly people choose to stay alone at home rather than living with their families who can take care of them. Robots have the potential to revolutionize elderly care by providing aid, companionship, and monitoring

Machine Learning (ML) is currently being exploited in numerous applications, being one of the most effective Artificial Intelligence (AI) technologies used in diverse fields, such as vision, autonomous systems, and the like. The trend motivated a significant amount of contributions to the analysis and design of ML applications against faults affecting the underlying hardware. The authors investigate

Cluster-based routing techniques have become a key solution for managing data flow in Wireless Sensor Networks (WSNs), which often struggle with limited resources and dynamic network conditions. With the growing need for efficient data management in these networks, it is more important than ever to understand and enhance these techniques. This survey evaluates recent cluster-based routing protocols

Internet-of-things (IoT) is a revolutionary paragon that brings automation and easiness to human lives and improves their experience. Smart Homes, Healthcare, and Agriculture are some of their amazing use cases. These IoT applications often employ Machine Learning (ML) techniques to strengthen their functionality. ML can be used to analyze sensor data for various, including optimizing energy usage

The burgeoning field of automated negotiation systems represents a transformative approach to resolving conflicts and allocating resources with enhanced efficiency. This paper presents a thorough survey of this discipline, emphasising the implications of human factors, the application of machine learning techniques, and the real-world deployments of these systems. In traditional manual negotiation

Artificial Intelligence (AI) and Machine Learning (ML) are being used more and more to handle complex tasks in many different areas. As a result, interconnected information systems are growing, which means that autonomous systems are needed to help them adapt, find complex patterns, and make better decisions in areas like cybersecurity, finance, healthcare, authentication, marketing, and supply chain

Artificial Intelligence (AI) plays a crucial role in the digital transformation of organizations, with the influence of AI applications expanding daily. Given this context, the development of these AI systems to guarantee their effective operation and usage is becoming more essential. To this end, numerous international standards have been introduced in recent years. This paper offers a broad review

With the amplification of digitization, the surge in multimedia content, such as text, video, audio, and images, is incredible. Concomitantly, the incidence of multimedia tampering is also apparently increasing. Digital watermarking (DW) is the means of achieving privacy and authentication of the received content while preserving integrity and copyright. Literature has produced a plethora of state-of-the-art

With the rapid evaluation of virtual and augmented reality, massive Internet of Things networks and upcoming 6 G communication give rise to an emerging concept termed the “metaverse,” which promises to revolutionize how we interact with the digital world by offering immersive experiences between reality and virtuality. Edge computing, another novel paradigm, propels the metaverse functionality by enhancing

This study provides an in-depth survey of quantum secure authentication and key agreement protocols, investigating the dynamic landscape of cryptographic techniques within the realm of quantum computing. With the potential threat posed by quantum computing advancements to classical cryptographic protocols, the exploration of secure authentication and key agreement in the quantum era becomes imperative

The Metaverse is an evolving technology that leverages the Internet infrastructure and the massively connected Internet of Everything (IoE) to create an immersive virtual world. In the Metaverse, humans engage in activities similar to those in the real world, such as socializing, working, attending events, exploring virtual landscapes, creating and trading digital assets, participating in virtual economies

AI based multimedia content generation, already having achieved hyper-realism, deeply influences human perception and trust. Since emerging around late 2017, deepfake technology has rapidly gained popularity due to its diverse applications, raising significant concerns regarding its malicious and unethical use. Although many deepfake detectors have been developed by forensic researchers in recent years

The natural and artificial dispersal of climatic particles transforms images obtained in open-air conditions. Due to visibility diminishing aerosols, unfavorable climate situations such as mist, fog, and haze cause color change and reduce the contrast of the obtained image. Images seem deformed and inadequate in contrast saturation, affecting computer vision techniques considerably. Haze removal aims

This survey provides a comprehensive analysis of the integration of Reconfigurable Intelligent Surfaces (RIS) with edge computing, underscoring RIS’s critical role in advancing wireless communication networks. The examination begins by demystifying edge computing, contrasting it with traditional cloud computing, and categorizing it into several types. It further delves into advanced edge computing

Images play a substantial role in various applications such as medical imaging, satellite imaging, and military communications. These images often contain confidential and sensitive information, and are typically transmitted over public networks. As a result, they are vulnerable to various security threats. Therefore, efficient image security techniques are necessary to protect these images from unauthorized

Web 3.0, as the third generation of the World Wide Web, aims to solve contemporary problems of trust, centralization, and data ownership. Driven by the latest advances in cutting-edge technologies, Web 3.0 is moving towards a more open, decentralized, intelligent, and interconnected network. Currently, increasingly widespread data breaches have raised awareness of online privacy and security of personal

The exponential growth of textual data presents substantial challenges in management and analysis, notably due to high storage and processing costs. Text classification, a vital aspect of text mining, provides robust solutions by enabling efficient categorization and organization of text data. These techniques allow individuals, researchers, and businesses to derive meaningful patterns and insights

This paper provides a comprehensive survey of anomaly detection for the Internet of Things (IoT). Anomaly detection poses numerous challenges in IoT, with broad applications, including intrusion detection, fraud monitoring, cybersecurity, industrial automation, etc. Intensive attention has been received by network security analytics and researchers, particularly on anomaly detection in the network

The advent of cloud computing has made a global impact by providing on-demand services, elasticity, scalability, and flexibility, hence delivering cost-effective resources to end users in pay-as-you-go manner. However, securing cloud services against vulnerabilities, threats, and modern attacks remains a major concern. Application layer attacks are particularly problematic because they can cause significant

Lately, a lot of attention has been paid to securing the ownership rights of digital images. The expanding usage of the Internet causes several problems, including data piracy and data tampering. Image watermarking is a typical method of protecting an image's copyright. Robust watermarking for digital images is a process of embedding watermarks on the cover image and extracting them correctly under

A graph vertex-subset problem defines which subsets of the vertices of an input graph are feasible solutions. We view a feasible solution as a set of tokens placed on the vertices of the graph. A reconfiguration variant of a vertex-subset problem asks, given two feasible solutions of size , whether it is possible to transform one into the other by a sequence of token slides (along edges of the graph)

Fault tolerance is becoming increasingly important for upcoming exascale systems, supporting distributed data processing, due to the expected decrease in the Mean Time Between Failures (MTBF). To ensure the availability, reliability, dependability, and performance of the system, addressing the fault tolerance challenge is crucial. It aims to keep the distributed system running at a reduced capacity

Hyperspectral image (HSI) classification is a significant topic of discussion in real-world applications. The prevalence of these applications stems from the precise spectral information offered by each pixelś data in hyperspectral imaging (HS). Classical machine learning (ML) methods face challenges in precise object classification with HSI data complexity. The intrinsic non-linear relationship between

Despite the advances in machine learning techniques, similarity assessment among multimedia data remains a challenging task of broad interest in computer science. Substantial progress has been achieved in acquiring meaningful data representations, but how to compare them, plays a pivotal role in machine learning and retrieval tasks. Traditional pairwise measures are widely used, yet unsupervised affinity

Virtual humans have become a hot research topic in recent years due to the development of AI technology and computer graphics. In this survey, we provide a comprehensive review of the interaction design of 3D virtual humans. We first categorize the interac- tion design of virtual humans into speech, eye, facial expressions, and posture interactions. Then we describe the combination of different modalities

Mobile Robots (MRs) and their applications are undergoing massive development, requiring a diversity of autonomous or self-directed robots to fulfill numerous objectives and responsibilities. Integrating MRs with the Intelligent Internet of Things (IIoT) not only makes robots innovative, trackable, and powerful but also generates numerous threats and challenges in multiple applications. The IIoT combines

Reproducibility is widely acknowledged as a fundamental principle in scientific research. Currently, the scientific community grapples with numerous challenges associated with reproducibility, often referred to as the “reproducibility crisis”. This crisis permeated numerous scientific disciplines. In this study, we examined the factors in scientific practices that might contribute to this lack of reproducibility

Stock market is one of the attractive domains for researchers as well as academicians. It represents highly complex non-linear fluctuating market behaviours where traders, investors, and organizers look forward to reliable future predictions of the market indices. Such prediction problems can be computationally addressed using various machine learning, deep learning, sentiment analysis, as well as

Driven by the demand of time-sensitive and data-intensive applications, edge computing has attracted wide attention as one of the cornerstones of modern service architectures. An edge-based system can facilitate a flexible processing of tasks over heterogeneous resources. Hence, computation offloading is the key technique for systematic service improvement. However, with the proliferation of devices

For years, the scientific community has researched monitoring approaches for the detection of certain mental disorders and risky behaviors, like depression, eating disorders, gambling, and suicidal ideation among others, in order to activate prevention or mitigation strategies and, in severe cases, clinical treatment. Natural Language Processing is one of the most active disciplines dealing with the

Research in Software Engineering greatly benefits from Systematic Literature Reviews (SLRs), in view of the citations they receive. While there has been a focus on improving the quality of SLRs in terms of the process, it remains unclear if this emphasis on rigor has also led to an increase in relevance. This study introduces Citation Context Analysis for SLRs as a method to go beyond simple citation

The Transformer network is the main application area for natural language processing. It has gained traction lately and exhibits potential in the field of computer vision. This cutting-edge method has proven to offer a significant impact on image analysis, a crucial area of computer vision. The transformer's outstanding performance in vision computing places it as an alternative to the convolutional

The auto-scaling feature is fundamental to serverless computing, and it automatically allows applications to scale as needed. Hence, this allows applications to be configured to adapt to current traffic and demands and acquire resources as necessary without the need to manage servers directly. Auto-scaling is an important principle in developing serverless applications that is considered and increasingly

Chaos Game Optimization Algorithm (CGO) is a novel advancement in metaheuristic optimization inspired by chaos theory. It addresses complex optimization problems in dynamical systems, exhibiting unique behaviours such as fractals and self-organized patterns. CGO’s design exemplifies adaptability and robustness, making it a significant tool for tackling intricate optimization scenarios. This study presents

To understand the real world using various types of data, Artificial Intelligence (AI) is the most used technique nowadays. While finding the pattern within the analyzed data represents the main task. This is performed by extracting representative features step, which is proceeded using the statistical algorithms or using some specific filters. However, the selection of useful features from large-scale

The variety of enormous information on the web encourages the field of recommender systems (RS) to flourish. In recent times, deep learning techniques have significantly impacted information retrieval tasks, including RS. The probabilistic and non-linear views of neural networks emerge to generative models for recommendation tasks. At present, there is an absence of extensive survey on deep generative

Software-defined Networking (SDN) is a transformative approach for addressing the limitations of legacy networks due to decoupling of control planes from data planes. It offers increased programmability and flexibility for designing of cloud-based data centers. SDN-Enabled cloud data centers help in managing the huge traffic very effectively and efficiently. However, the security of SDN-Enabled Cloud

Natural Language-based Source Code Generation (NLSCG) holds the promise to revolutionize the way how software is developed by means of facilitating a collection of intelligent technical enablers, based on sustained improvements on the natural language to source code pipelines and continuous adoption of new coding paradigms. In recent years, a large variety of NLSCG technical solutions have been proposed

Raspberry Pi is an invaluable and popular prototyping tool in scientific research for experimenting with a wide variety of ideas, ranging from simple to complex projects. This review article explores how Raspberry Pi is used in various studies, discussing its pros and cons along with its applications in various domains such as home automation, agriculture, healthcare, industrial control, and advanced

This paper provides an extensive and in-depth survey of behavior modeling for complex intelligent systems, focusing specifically on the innovative applications of Generative Adversarial Networks (GANs). The survey not only delves into the fundamental principles of GANs, but also elucidates their pivotal role in accurately modeling the behaviors exhibited by complex intelligent systems. By categorizing

The integration of multiple heterogeneous data into graph models has been the subject of extensive research in recent years. Harnessing these resulting Heterogeneous Information Networks (HINs) is a complex task that requires reasoning to perform various prediction tasks.

Cross-site scripting (XSS) is one of the major threats menacing the privacy of data and the navigation of trusted web applications. Since its disclosure in late 1999 by Microsoft security engineers, several techniques have been developed with the aim of securing web navigation and protecting web applications against XSS attacks. XSS has been and is still in the top 10 list of web vulnerabilities reported

This review paper offers an in-depth analysis of AI-powered virtual conversational agents, specifically focusing on OpenAI’s ChatGPT. The main contributions of this paper are threefold: (i) an exhaustive review of prior literature on chatbots, (ii) a background of chatbots including existing chatbots/conversational agents like ChatGPT, and (iii) a UI/UX design analysis of prominent chatbots. Another

Distributed Denial of Service (DDoS) attacks in IoT networks are one of the most devastating and challenging cyber-attacks. The number of IoT users is growing exponentially due to the increase in IoT devices over the past years. Consequently, DDoS attack has become the most prominent attack as vulnerable IoT devices are becoming victims of it. In the literature, numerous techniques have been proposed

Clustering is a fundamental data exploration technique to discover hidden grouping structure of data. With the proliferation of big data, and the increase of volume and variety, the complexity of data multiplicity is increasing as well. Traditional clustering methods can provide only a single clustering result, which restricts data exploration to one single possible partition. In contrast, multiple

Electricity is one of the mandatory commodities for mankind today. To address challenges and issues in the transmission of electricity through the traditional grid, the concepts of smart grids and demand response have been developed. In such systems, a large amount of data is generated daily from various sources such as power generation (e.g., wind turbines), transmission and distribution (microgrids

The growth rate in big data and internet of things (IoT) is far exceeding the computer performance rate at which modern processors can compute on the massive amount of data. The cluster and cloud technologies enriched by machine learning applications had significantly helped in performance growths subject to the underlying network performance. Computer systems have been studied for improvement in performance